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Open Access February 06, 2026

Predictive Modeling of Public Sentiment Using Social Media Data and Natural Language Processing Techniques

Abstract Social media platforms like X (formerly Twitter) generate vast volumes of user-generated content that provide real-time insights into public sentiment. Despite the widespread use of traditional machine learning methods, their limitations in capturing contextual nuances in noisy social media text remain a challenge. This study leverages the Sentiment140 dataset, comprising 1.6 million labeled [...] Read more.
Social media platforms like X (formerly Twitter) generate vast volumes of user-generated content that provide real-time insights into public sentiment. Despite the widespread use of traditional machine learning methods, their limitations in capturing contextual nuances in noisy social media text remain a challenge. This study leverages the Sentiment140 dataset, comprising 1.6 million labeled tweets, and develops predictive models for binary sentiment classification using Naive Bayes, Logistic Regression, and the transformer-based BERT model. Experiments were conducted on a balanced subset of 12,000 tweets after comprehensive NLP preprocessing. Evaluation using accuracy, F1-score, and confusion matrices revealed that BERT significantly outperforms traditional models, achieving an accuracy of 89.5% and an F1-score of 0.89 by effectively modeling contextual and semantic nuances. In contrast, Naive Bayes and Logistic Regression demonstrated reasonable but consistently lower performance. To support practical deployment, we introduce SentiFeel, an interactive tool enabling real-time sentiment analysis. While resource constraints limited the dataset size and training epochs, future work will explore full corpus utilization and the inclusion of neutral sentiment classes. These findings underscore the potential of transformer models for enhanced public opinion monitoring, marketing analytics, and policy forecasting.
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Open Access August 26, 2025

The association between serum α1-AGP and chronic kidney disease among US female ages 20 to 49 years: Results from the 2015-2018 National Health and Nutrition Survey

Abstract Background: Chronic kidney disease (CKD) affects over 35.5 million US adults. Serum α1-acid glycoprotein (α1-AGP), an acute-phase protein, exhibits anti-inflammatory properties in animal models, but its association with CKD in younger women remains underexplored. This study investigated the relationship between serum α1-AGP and CKD risk in US women aged 20–49 years. Methods: This [...] Read more.
Background: Chronic kidney disease (CKD) affects over 35.5 million US adults. Serum α1-acid glycoprotein (α1-AGP), an acute-phase protein, exhibits anti-inflammatory properties in animal models, but its association with CKD in younger women remains underexplored. This study investigated the relationship between serum α1-AGP and CKD risk in US women aged 20–49 years. Methods: This nationally representative cross-sectional study used data on female adults in the US aged 20–49 years from the National Health and Nutrition Examination Survey 2015–2018 cycles. 2,137 individuals were included in the study after excluding individuals without serum α1-AGP, urine albumin, and creatinine data. Multivariate logistic regression models evaluated the association between serum α1-AGP and CKD. Moreover, we performed stratified and interaction analyses to see if the relationship was stable in different subgroups. Results: Among 2,137 participants (mean age 34.6 years, mean eGFR 111.7 mL/min/1.73 m²), CKD prevalence was 8.8% (n=188). Higher serum α1-AGP levels were associated with lower CKD risk in the fully adjusted model (OR 0.37, 95% CI 0.16–0.84, P = 0.017), with a dose-response trend across quartiles (P = 0.041). The association was stronger in women aged 40–49 years (OR 0.20, 95% CI 0.05–0.76) and Mexican Americans (OR 0.07, 95% CI 0.01–0.56), though interaction terms were not significant (P > 0.05). Conclusions: Higher serum α1-AGP levels are associated with lower CKD prevalence in young women, suggesting a protective role. Longitudinal studies are needed to confirm causality and explore α1-AGP as a biomarker for CKD risk stratification.
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Open Access June 26, 2025

The Relationship Between Lymphocyte Count and Mortality in Patients with Dysphagia

Abstract Background: Dysphagia is a common functional impairment in elderly populations, often leading to severe complications such as malnutrition and aspiration pneumonia, significantly increasing healthcare burdens. Currently, effective prognostic assessment tools are lacking. The absolute lymphocyte count (ALC), a biomarker reflecting immune-nutritional status, has potential predictive value in this context, though its role in dysphagia prognosis remains unclear. Methods: This retrospective cohort study included 253 dysphagic patients who received percutaneous endoscopic gastrostomy (PEG) or total parenteral nutrition (TPN) between 2014 and 2017. Five patients with missing ALC were excluded. Cox regression models assessed the association between ALC and mortality. ALC was analyzed as both continuous variable (using restriocted cubic splines) and categorical tertiles, with additional threshold analyses to assess non-linearity. Kaplan–Meier survival curves and subgroup analyses were also performed. Results: Lower ALC was associated with poorer nutritional status, higher inflammatory markers, and greater comorbidity burden. Higher ALC was independently associated with reduced mortality (adjusted HR: 0.60; 95% CI: 0.44–0.83; p = 0.002). Patients in the highest tertile had significantly better survival than those in the lowest (HR: 0.37; 95% CI: 0.23–0.59; P < 0.001). A non-linear threshold effect was identified at ALC = 1.899×109/L (p for non-linearity = 0.009). Kaplan–Meier analysis confirmed improved survival with higher ALC (p [...] Read more.
Background: Dysphagia is a common functional impairment in elderly populations, often leading to severe complications such as malnutrition and aspiration pneumonia, significantly increasing healthcare burdens. Currently, effective prognostic assessment tools are lacking. The absolute lymphocyte count (ALC), a biomarker reflecting immune-nutritional status, has potential predictive value in this context, though its role in dysphagia prognosis remains unclear. Methods: This retrospective cohort study included 253 dysphagic patients who received percutaneous endoscopic gastrostomy (PEG) or total parenteral nutrition (TPN) between 2014 and 2017. Five patients with missing ALC were excluded. Cox regression models assessed the association between ALC and mortality. ALC was analyzed as both continuous variable (using restriocted cubic splines) and categorical tertiles, with additional threshold analyses to assess non-linearity. Kaplan–Meier survival curves and subgroup analyses were also performed. Results: Lower ALC was associated with poorer nutritional status, higher inflammatory markers, and greater comorbidity burden. Higher ALC was independently associated with reduced mortality (adjusted HR: 0.60; 95% CI: 0.44–0.83; p = 0.002). Patients in the highest tertile had significantly better survival than those in the lowest (HR: 0.37; 95% CI: 0.23–0.59; P < 0.001). A non-linear threshold effect was identified at ALC = 1.899×109/L (p for non-linearity = 0.009). Kaplan–Meier analysis confirmed improved survival with higher ALC (p < 0.0001). Subgroup analyses showed the protective effect of higher ALC was consistent across age, sex, BMI, PEG use, and comorbidity strata, with no significant interactions. Conclusions: ALC is an independent, non-linear predictor of mortality in older dysphagic patients and may aid clinical risk stratification across diverse patient subgroups.
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Open Access June 26, 2025

Mathematical modelling of the impact of HIV prevention strategies among female sex workers on public health in Burkina Faso

Abstract This article presents a mathematical model designed to simulate the impact of targeted interventions aimed at preventing HIV transmission among female sex workers (FSWs) and their clients, while also analyzing their effects on the health of the general population. The compartmental model distinguishes between high-risk populations (FSWs and their clients) and low-risk populations (sexually active [...] Read more.
This article presents a mathematical model designed to simulate the impact of targeted interventions aimed at preventing HIV transmission among female sex workers (FSWs) and their clients, while also analyzing their effects on the health of the general population. The compartmental model distinguishes between high-risk populations (FSWs and their clients) and low-risk populations (sexually active men and women in the general population), and links prevention efforts in high-risk groups to the evolution of the epidemic in the low-risk population. The fundamental properties of the model, such as the positivity of solutions and the boundedness of the system, have been verified, and the basic reproduction number R0 has been calculated. Finally, the stability of the model was studied using Varga’s theorem and the Lyapunov method. Simulation results show that targeted prevention among FSWs and their clients reduces HIV incidence in the general population. This framework provides a valuable tool for guiding policymakers in the design of effective strategies to combat the epidemic, especially relevant in the context of suspension of USAID funding.
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Open Access June 06, 2025

Food security, dietary diversity, and age as determinants of nutritional status among adolescent girls in coastal Bangladesh

Abstract Background: Adolescent girls living in disaster-prone coastal regions of Bangladesh face heightened nutritional vulnerability due to limited food access, poor dietary diversity, and environmental stressors. Despite growing concerns about adolescent malnutrition, few studies have examined the combined influence of food security, dietary diversity, and age on nutritional outcomes in these [...] Read more.
Background: Adolescent girls living in disaster-prone coastal regions of Bangladesh face heightened nutritional vulnerability due to limited food access, poor dietary diversity, and environmental stressors. Despite growing concerns about adolescent malnutrition, few studies have examined the combined influence of food security, dietary diversity, and age on nutritional outcomes in these settings. Objectives: This study aimed to assess the association between dietary diversity, food security, and age with the nutritional status of adolescent girls in coastal Bangladesh. Methods: A cross-sectional survey was conducted among 345 adolescent girls aged 10–19 in Chattogram and Cox’s Bazar. Data on dietary intake were collected using a 24-hour dietary recall and a food frequency questionnaire. Household food security was assessed using a validated scale. Nutritional status was determined using BMI-for-age classifications. Bivariate and multivariate analyses explored associations between dietary diversity, food security, age, and nutritional status. Results: Among participants, 10.14% were underweight, and 29.85% were either overweight or obese. While 17.39% demonstrated high dietary diversity (≥7 food groups), the majority had moderate diversity (5 or 6 food groups) (59.42%). Food-insecure households were significantly more likely to have overweight or obese adolescents (p < 0.05). Although dietary diversity was associated with BMI in bivariate analysis, it was not a significant predictor in the multivariate model. Age showed a significant relationship with both dietary diversity and nutritional status. Conclusion: The findings emphasize the importance of addressing household food security and age-related nutritional vulnerabilities in coastal areas. Interventions should prioritize age-sensitive, culturally appropriate strategies to improve dietary quality and prevent the double burden of malnutrition among adolescent girls.
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Open Access March 06, 2025

Impact of Food Security on Dietary Diversity and Nutritional Intake Among Pregnant Women in Low-Resource Settings

Abstract Background: Food security and dietary diversity are essential determinants of maternal health, particularly among pregnant women in refugee populations who face heightened vulnerabilities due to displacement and inadequate living conditions. This study examines the impact of food security on dietary diversity and nutritional intake among pregnant Rohingya women residing in the makeshift [...] Read more.
Background: Food security and dietary diversity are essential determinants of maternal health, particularly among pregnant women in refugee populations who face heightened vulnerabilities due to displacement and inadequate living conditions. This study examines the impact of food security on dietary diversity and nutritional intake among pregnant Rohingya women residing in the makeshift camps of Ukhiya, Cox’s Bazar. Methods: A descriptive cross-sectional study was conducted among 96 pregnant Rohingya women from June to September 2022. Data were collected using structured questionnaires assessing socio-demographic characteristics, food security, and dietary diversity. Food security was evaluated using the Household Food Insecurity Access Scale (HFIAS), while dietary diversity was assessed through a 24-hour dietary recall and a 7-day food frequency questionnaire. Data were analyzed using SPSS (Version 26) and Stata (Version 13), employing descriptive statistics and chi-square tests to examine associations. Results: Most participants (57.3%) were food secure, and 85.4% demonstrated high dietary diversity, consuming seven or more food groups. However, 21.9% of households experienced severe food insecurity, highlighting ongoing challenges in food access. The highest consumption was observed for starch, flesh foods, dark green leafy vegetables, and vitamin A-rich fruits and vegetables (99.0%), while dairy products (69.8%) and organ meat (34.4%) were consumed less frequently. Despite high dietary diversity, severe food insecurity persists, indicating gaps in food assistance programs. Conclusions: While food support programs appear to contribute to high dietary diversity among pregnant Rohingya women, severe food insecurity remains a significant concern. Strengthening food security interventions, improving access to diverse nutrient-rich foods, and integrating sustainable food assistance models are essential to addressing these challenges. Future research should explore long-term strategies to enhance food security and assess the impact of targeted nutritional interventions on maternal health outcomes in refugee settings.
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Open Access February 21, 2025

Diminished Returns of Educational Attainment on Unpaid and Paid Maternity Leave of Mothers Giving Birth in Poverty

Abstract Background: Maternity leave, whether paid or unpaid, is a critical resource that can significantly impact maternal well-being and newborn outcomes. However, its availability and utilization among mothers living in poverty remain understudied. Education is widely recognized as a key factor that increases access to both paid and unpaid leave. However, the theory of Minorities’ [...] Read more.
Background: Maternity leave, whether paid or unpaid, is a critical resource that can significantly impact maternal well-being and newborn outcomes. However, its availability and utilization among mothers living in poverty remain understudied. Education is widely recognized as a key factor that increases access to both paid and unpaid leave. However, the theory of Minorities’ Diminished Returns (MDRs) posits that structural racism, segregation, and labor market discrimination limit the benefits of socioeconomic resources, such as education, for Black and Latino individuals. This suggests that the effects of education on maternity leave may not be uniform across racial and ethnic groups. Objective: This study aimed to examine the MDRs of education on access to unpaid and paid maternity leave among Black and Latino mothers compared to White mothers giving birth while living in poverty. Methods: We utilized baseline data from the Baby’s First Years Study (BFY), a longitudinal investigation of the effects of poverty on child development. The sample consisted of 1,050 mothers living in poverty who had recently given birth. Maternity leave (paid and unpaid) was assessed via self-report, and educational attainment was measured in years of schooling. Structural equation modeling (SEM) and interaction terms were employed to analyze racial and ethnic differences in the relationship between education and access to maternity leave. Results: Educational attainment was positively associated with access to unpaid maternity leave for the overall sample of mothers giving birth in poverty, but this association was weaker for Black and Latino mothers compared to non-Latino White mothers. Education did not significantly increase the likelihood of paid maternity leave, and there were no group differences for this association. Conclusion: This study highlights the urgent needs to address structural racism, labor market discrimination, and residential segregation that diminish the impact of education on living conditions for Black and Latino mothers, compared to non-Latino White mothers, even for those living under poverty. Policymakers and practitioners should develop targeted interventions to reduce racial and ethnic disparities in access to paid and unpaid maternity leave and other critical resources, particularly for new mothers living in poverty. Addressing these inequities is essential for improving maternal and newborn health outcomes and promoting social justice.
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Open Access January 11, 2025

Exploring LiDAR Applications for Urban Feature Detection: Leveraging AI for Enhanced Feature Extraction from LiDAR Data

Abstract The integration of LiDAR and Artificial Intelligence (AI) has revolutionized feature detection in urban environments. LiDAR systems, which utilize pulsed laser emissions and reflection measurements, produce detailed 3D maps of urban landscapes. When combined with AI, this data enables accurate identification of urban features such as buildings, green spaces, and infrastructure. This synergy is [...] Read more.
The integration of LiDAR and Artificial Intelligence (AI) has revolutionized feature detection in urban environments. LiDAR systems, which utilize pulsed laser emissions and reflection measurements, produce detailed 3D maps of urban landscapes. When combined with AI, this data enables accurate identification of urban features such as buildings, green spaces, and infrastructure. This synergy is crucial for enhancing urban development, environmental monitoring, and advancing smart city governance. LiDAR, known for its high-resolution 3D data capture capabilities, paired with AI, particularly deep learning algorithms, facilitates advanced analysis and interpretation of urban areas. This combination supports precise mapping, real-time monitoring, and predictive modeling of urban growth and infrastructure. For instance, AI can process LiDAR data to identify patterns and anomalies, aiding in traffic management, environmental oversight, and infrastructure maintenance. These advancements not only improve urban living conditions but also contribute to sustainable development by optimizing resource use and reducing environmental impacts. Furthermore, AI-enhanced LiDAR is pivotal in advancing autonomous navigation and sophisticated spatial analysis, marking a significant step forward in urban management and evaluation. The reviewed paper highlights the geometric properties of LiDAR data, derived from spatial point positioning, and underscores the effectiveness of machine learning algorithms in object extraction from point clouds. The study also covers concepts related to LiDAR imaging, feature selection methods, and the identification of outliers in LiDAR point clouds. Findings demonstrate that AI algorithms, especially deep learning models, excel in analyzing high-resolution 3D LiDAR data for accurate urban feature identification and classification. These models leverage extensive datasets to detect patterns and anomalies, improving the detection of buildings, roads, vegetation, and other elements. Automating feature extraction with AI minimizes the need for manual analysis, thereby enhancing urban planning and management efficiency. Additionally, AI methods continually improve with more data, leading to increasingly precise feature detection. The results indicate that the pulse emitted by continuous wave LiDAR sensors changes when encountering obstacles, causing discrepancies in measured physical parameters.
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Open Access January 10, 2025

Artificial Immune Systems: A Bio-Inspired Paradigm for Computational Intelligence

Abstract Artificial Immune Systems (AIS) are bio-inspired computational frameworks that emulate the adaptive mechanisms of the human immune system, such as self/non-self discrimination, clonal selection, and immune memory. These systems have demonstrated significant potential in addressing complex challenges across optimization, anomaly detection, and adaptive system control. This paper provides a [...] Read more.
Artificial Immune Systems (AIS) are bio-inspired computational frameworks that emulate the adaptive mechanisms of the human immune system, such as self/non-self discrimination, clonal selection, and immune memory. These systems have demonstrated significant potential in addressing complex challenges across optimization, anomaly detection, and adaptive system control. This paper provides a comprehensive exploration of AIS applications in domains such as cybersecurity, resource allocation, and autonomous systems, highlighting the growing importance of hybrid AIS models. Recent advancements, including integrations with machine learning, quantum computing, and bioinformatics, are discussed as solutions to scalability, high-dimensional data processing, and efficiency challenges. Core algorithms, such as the Negative Selection Algorithm (NSA) and Clonal Selection Algorithm (CSA), are examined, along with limitations in interpretability and compatibility with emerging AI paradigms. The paper concludes by proposing future research directions, emphasizing scalable hybrid frameworks, quantum-inspired approaches, and real-time adaptive systems, underscoring AIS's transformative potential across diverse computational fields.
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Open Access January 04, 2025

Knowledge Level of Street Fruit Vendors on Food Hygiene in the Tamale Metropolis

Abstract This study aimed to assess the knowledge level of street food vendors on hygiene in the Tamale metropolis in the Northern Region of Ghana. The study employed the health belief model as the theoretical basis. Quantitatively, the study employed a descriptive cross-sectional study design to examine the microbial load of street-cut fruits and assess the knowledge and practice of vendors of cut fruits [...] Read more.
This study aimed to assess the knowledge level of street food vendors on hygiene in the Tamale metropolis in the Northern Region of Ghana. The study employed the health belief model as the theoretical basis. Quantitatively, the study employed a descriptive cross-sectional study design to examine the microbial load of street-cut fruits and assess the knowledge and practice of vendors of cut fruits on personal and food hygiene in the study setting. The population consists of cut and vented pawpaw, watermelon, and street fruit vendors registered with the health directorate in the Tamale Metropolis. A convenient sampling technique was used to select 113 respondents for the study. The Yamane formula was used to determine the sample size to select one hundred and thirteen participants (113) out of one hundred and fifty-eight street fruit vendors in the Tamale Metropolis. The main instrument for data collection was a questionnaire. A questionnaire had close-ended questions which were developed using a 'Yes' and 'No' response, and a four-point Likert-type scale ranging from 1=Strongly Disagree (SD), 2=Disagree (D), 3=Agree (A) and 4= Strongly Agree (SA). The data were analysed using descriptive statistics (frequency, percentages, means and standard deviation). The findings revealed that the overall knowledge level of respondents is low. The findings also indicate that vendors do not control the rate at which their customers touch their vended fruits. It is recommended that Street fruit vendors and handlers be educated on fruit hygiene practices through engagement by the Health Directorate Unit of Tamale Metropolis and the Ministry of Health. To keep consumers safe, the Tamale Metropolitan Assembly must strictly enforce compliance with regulations on operation permits and health clearance certificates. Metropolitan sanitation officers must regularly monitor fruit vendors to ensure compliance with goods.
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Open Access November 15, 2024

Wolf Warrior II: Subtitle Translation and Transcreation of China’s Identity and National Branding from an Intersemiotic-multimodal Approach

Abstract The Chinese film Wolf Warrior II floats all the way at the domestic box office, and jumps into the top 100 of the world's film box office rankings. It has achieved great economic success and ratings are overwhelmingly positive in China. Nevertheless, in stark contrast to this, Wolf Warrior II [...] Read more.
The Chinese film Wolf Warrior II floats all the way at the domestic box office, and jumps into the top 100 of the world's film box office rankings. It has achieved great economic success and ratings are overwhelmingly positive in China. Nevertheless, in stark contrast to this, Wolf Warrior II is cold at the box office abroad, and the word of mouth is not satisfactory. Transcreation is the re-creation or adaptation of content for a group of specific target audience. As an inter-related process of translation, a successful and holistic transcreation can arouse the same emotions as well as connotations produced in the target language as the source language. There are different perspectives to detailed translation analysis of China’s identity as a prominent character of contemporary society. Insofar as this research probes into the branding and in subtitle translation, it also constructs a binary theoretical model based on triadic signs of intersemiotic translation and metafunctional framework of multimodal analysis to testify China’s core values in this film and beyond.
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Open Access November 15, 2024

Education Does Not Equally Increase Financial Well-being for All

Abstract Background: Financial well-being is a key domain of overall well-being, encompassing an individual's ability to meet financial obligations, secure their financial future, and maintain a sense of financial freedom. Education is often viewed as a critical pathway to enhancing financial well-being. However, the returns of education on financial well-being are not uniform across racial, ethnic, [...] Read more.
Background: Financial well-being is a key domain of overall well-being, encompassing an individual's ability to meet financial obligations, secure their financial future, and maintain a sense of financial freedom. Education is often viewed as a critical pathway to enhancing financial well-being. However, the returns of education on financial well-being are not uniform across racial, ethnic, and nativity groups. The theory of Minorities’ Diminished Returns (MDRs) suggests that the positive effects of education on outcomes such as income and financial security are weaker for marginalized groups, including Black individuals, Latinos, and immigrants. Objective: This study examines the diminished returns of education on financial well-being among Black, Latino, and immigrant populations in the United States. We aim to investigate how structural inequalities contribute to weaker financial returns on education for these groups compared to their White and native-born counterparts. Methods: We utilized data from the Understanding America Study (UAS 2014) to conduct a cross-sectional analysis of adult respondents. The study assessed financial well-being outcomes (e.g., income, savings, and financial security) and their association with educational attainment across racial, ethnic, and nativity groups. Regression models were employed to test for interaction effects between education and race/ethnicity/nativity, adjusting for sociodemographic factors such as age, gender, employment, and family structure. Results: Our analysis included 8,121 individuals. The mean age of the respondents was 48 years (SD = 16). High education was associated with higher financial well-being (B = 1.284, 95% CI: 1.157, 1.410). The interaction terms between education and immigrant status (B = -0.507, 95% CI: -0.930, -0.084), race (Black) (B = -0.770, 95% CI: -1.208, -0.331), and ethnicity (Hispanic) (B = -0.589, 95% CI: -0.969, -0.210) were all significant, suggesting that immigrant, Black, and Hispanic individuals experience diminished returns on education in terms of financial well-being, relative to US-born non-Hispanic White individuals. The significant negative interactions between education and minority statuses (Black, Hispanic, and immigrant) indicate that while education generally improves financial well-being, the magnitude of this improvement is substantially smaller for these marginalized groups. Conclusion: Understanding how education translates to financial well-being across different racial, ethnic, and nativity groups is critical for addressing persistent financial disparities.
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Open Access April 29, 2024

Predictors of Patient Outcomes Associated with Transfer Status to Definitive Care Hospitals: A Study of Admitted Road Traffic Injured Patients in Two Major Trauma Hospitals in The Gambia

Abstract The Gambia uses the Primary Health Care model with no trauma response system. Trauma patients are transferred through multiple levels of health care facilities before definitive care hospitals. This study was conducted to identify predictors of injury factors associated with transfer. In this study, we examined characteristics of transferred patients compared to those directly admitted in [...] Read more.
The Gambia uses the Primary Health Care model with no trauma response system. Trauma patients are transferred through multiple levels of health care facilities before definitive care hospitals. This study was conducted to identify predictors of injury factors associated with transfer. In this study, we examined characteristics of transferred patients compared to those directly admitted in definitive care hospitals. The study was conducted in two major trauma hospitals in The Gambia. 251 road traffic injury (RTI) patients were either transferred (84%) from lower-level health centers or directly admitted (16%) to one of the study hospitals. Transferred patients were more likely to have been pedestrian/bicyclists (aOR = 1.81; 95% CI = 0.86 – 3.80). Administration of antibiotics was significantly associated with direct admit than transferred patients (aOR = 6.84; 95% CI = 2.38 – 19.68). Transferred patients were more likely to receive intravenous fluid compared to direct admits (aOR = 0.03; 95% CI = 0.01 – 0.08). The study results have implications for policies and planning in the healthcare setting in The Gambia and other LMICs with similar settings. Based on the findings of this study, it is essential that hospital management teams adapt to increasing reliance of RTI patients on lower-level healthcare facilities. The study results suggest increased burden on lower-level health care facilities. Efforts and resources should focus more on supporting lower-level facilities.
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Open Access December 12, 2023

Threatened Wildlife for an Instructional Approach about Biodiversity Conservation

Abstract Biodiversity is related to a global problem: its destruction, a fact supported by scientific authorities. It is not trivial that educational dimension has been contemplated as one of the strategies for its conservation. Since 1992 global initiatives such as the Convention on Biological Diversity postulates concepts that linked education and nature conservation. The main objective of this research work is to test the level of assimilation of extracurricular scientific knowledge by primary school pupils. The method chosen for the content was, on the one hand, a master class intervention with an interactive presentation on a digital whiteboard. Third cases were chosen. Each case consisted of a presentation of the current status of a species of fauna present in Spain. On the second part, students were asked to write an essay and to illustrate the experience during the presentation. Regarding the essays, students showed that they were more attracted to the first species that was presented (Iberian lynx) in a proportion of over 45% of cases. The “Endangered species” concept appeared in more than 77% of the texts reviewed. In terms of drawings, almost 55% of the responses seem to devote more attention to the second species described (Testudo graeca [...] Read more.
Biodiversity is related to a global problem: its destruction, a fact supported by scientific authorities. It is not trivial that educational dimension has been contemplated as one of the strategies for its conservation. Since 1992 global initiatives such as the Convention on Biological Diversity postulates concepts that linked education and nature conservation. The main objective of this research work is to test the level of assimilation of extracurricular scientific knowledge by primary school pupils. The method chosen for the content was, on the one hand, a master class intervention with an interactive presentation on a digital whiteboard. Third cases were chosen. Each case consisted of a presentation of the current status of a species of fauna present in Spain. On the second part, students were asked to write an essay and to illustrate the experience during the presentation. Regarding the essays, students showed that they were more attracted to the first species that was presented (Iberian lynx) in a proportion of over 45% of cases. The “Endangered species” concept appeared in more than 77% of the texts reviewed. In terms of drawings, almost 55% of the responses seem to devote more attention to the second species described (Testudo graeca). An attempt was made to offer rigorous, structured information related to different aspects of natural reality in order to contemplate the broadest possible vision. The example of an instructional intervention presented here aims to be an alternative to other transmissive teaching models. Likewise, the linking of abstract concepts with socio-cultural reality proved to be a successful strategy to reinforce knowledge about natural biodiversity, endangered species or threat factors.
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Open Access November 03, 2023

Mathematical Modeling of the Price Volatility of Maize and Sorghum between 1960 and 2022

Abstract The price of grains like maize and sorghum is subject to significant fluctuations, which can have a significant impact on a country's economy and food security. The aim of the study is to model sorghum and maize price volatility in Nigeria. The data utilized in the study was extracted from World Bank Commodity Price Data (WBCPD), 2022. The data consists of monthly prices in nominal US dollars for [...] Read more.
The price of grains like maize and sorghum is subject to significant fluctuations, which can have a significant impact on a country's economy and food security. The aim of the study is to model sorghum and maize price volatility in Nigeria. The data utilized in the study was extracted from World Bank Commodity Price Data (WBCPD), 2022. The data consists of monthly prices in nominal US dollars for maize and sorghum from January 1960 – August 2022. The Autoregressive Conditional Heteroskedasticity (ARCH) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models were utilized for capturing the two-grain price volatility. Two types of conditional heteroscedastic models exist, the first group uses exact functions to control the evolution of , while the second group describes with stochastic equations. It is inferred from the result that inherent uncertainties and fluctuations existed in the prices of maize and sorghum in Nigeria which implies that the price volatility is positive and statistically significant suggesting that historical information and past shocks play a crucial role in determining the volatility observed in the grains. It is recommended that the ARCH, GARCH, EGARCH, TGARCH, PARCH, CGARCH, and IGARCH models should be employed for modeling and managing the volatility of maize and sorghum prices in Nigeria. These models have shown effectiveness in capturing different aspects of volatility, including the impact of past shocks, conditional volatility, asymmetry, and other relevant factors.
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Open Access November 01, 2023

Individual Wave Component Signal Modeling, Parameters Extraction, and Analysis

Abstract The accurate estimation of Individual Wave Components (IWC) is crucial for automated diagnosis of the human digestive system in a clinical setting. However, this process can be challenging due to signal contamination by other signal sources in the body, such as the lungs and heart, as well as environmental noise. To address this issue, various denoising techniques are commonly employed in bowel [...] Read more.
The accurate estimation of Individual Wave Components (IWC) is crucial for automated diagnosis of the human digestive system in a clinical setting. However, this process can be challenging due to signal contamination by other signal sources in the body, such as the lungs and heart, as well as environmental noise. To address this issue, various denoising techniques are commonly employed in bowel sound signal processing. While denoising is important, it can increase computational complexity, making it challenging for portable devices. Therefore, signal processing algorithms often require a trade-off between fidelity and computational complexity. This study aims to evaluate an IWC parameter extraction algorithm that was previously developed and reconstruct the IWC without denoising using synthetic and clinical data. To that end, the role of a reliable model in creating synthetic data is paramount. The rigorous testing of the algorithm is limited by the availability of quality and quantity recorded data. To overcome this challenge, a mathematical model has been proposed to generate synthetic bowel sound data that can be used to test new algorithms. The proposed algorithm’s robust performance is evaluated using both synthetic and clinically recorded data. We perform time-frequency analysis of original and reconstructed bowel sound signals in various digestive system states and characterize the performance using Monte Carlo simulation when denoising is not applied. Overall, our study presents a promising algorithm for accurate IWC estimation that can be useful for predicting anomalies in the digestive system.
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Open Access October 07, 2023

A Systematic Review of Observational Studies Focusing on Impact of Telehealth Consultation in Osteoporosis Management during the Pandemic

Abstract Background: The COVID-19 pandemic disrupted routine osteoporosis care due to clinic closures and limited in-person consultations. Telehealth emerged as an alternative model enabling remote care delivery and monitoring. However, previous reviews on telehealth either did not include the pandemic period or had a limited focus in scope. Evidence synthesized specifically for osteoporosis care [...] Read more.
Background: The COVID-19 pandemic disrupted routine osteoporosis care due to clinic closures and limited in-person consultations. Telehealth emerged as an alternative model enabling remote care delivery and monitoring. However, previous reviews on telehealth either did not include the pandemic period or had a limited focus in scope. Evidence synthesized specifically for osteoporosis care during the pandemic is needed but lacking. Methods: We systematically searched PubMed, MEDLINE, EMBASE, PsycINFO, Web of Science, and CINAHL for studies on telehealth for osteoporosis published between January 2021 and March 2023. Five studies met the inclusion criteria of: osteoporosis population, telehealth intervention, and COVID-19 pandemic timeframe. Data was extracted on study characteristics, COVID-19 outcomes, osteoporosis status, telehealth purpose, patient satisfaction, and clinical outcomes. Result: The five studies showed telehealth was used for monitoring data, delivering test results, adjusting medications, and assessments. Osteoporosis prevalence among telehealth users ranged 30-100%. High patient satisfaction was reported with telehealth versus in-person care. No major differences occurred in medication delays or fractures between telehealth and in-person groups. Conclusion: This review found telehealth enables effective osteoporosis care and monitoring during the pandemic, with high patient and provider satisfaction. However, more robust randomized controlled trials are needed to establish stronger evidence around telehealth's impacts on clinical osteoporosis outcomes. Implications: Though promising, further high-quality studies will help clarify telehealth's role in improving osteoporosis care and outcomes. Findings inform guidelines on integrating telehealth into routine management. Evidence on user perspectives optimizes telehealth implementation policies.
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Systematic Review
Open Access September 26, 2023

Charged Stellar Model with Generalized Chaplygin Equation of State Consistent with Observational Data

Abstract In this paper, we found a new model for a compact star with charged anisotropic matter distribution considering the generalized Chaplygin equation of state. The Einstein-Maxwell field equations have been solved with a particular form of metric potential and electric field intensity. The plots show that physical variables such as radial pressure, energy density, charge density, anisotropy, radial [...] Read more.
In this paper, we found a new model for a compact star with charged anisotropic matter distribution considering the generalized Chaplygin equation of state. The Einstein-Maxwell field equations have been solved with a particular form of metric potential and electric field intensity. The plots show that physical variables such as radial pressure, energy density, charge density, anisotropy, radial speed sound, and the mass are fully well defined and are regular in the star's interior. We obtained models consistent with stellar objects such as GJ 832, LHS 43, SAO 81292, GJ 380, GJ 412, and SAO 62377.
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Open Access September 13, 2023

A Comparative Study of Attention-Based Transformer Networks and Traditional Machine Learning Methods for Toxic Comments Classification

Abstract With the rapid growth of online communication platforms, the identification and management of toxic comments have become crucial in maintaining a healthy online environment. Various machine learning approaches have been employed to tackle this problem, ranging from traditional models to more recent attention-based transformer networks. This paper aims to compare the performance of attention-based [...] Read more.
With the rapid growth of online communication platforms, the identification and management of toxic comments have become crucial in maintaining a healthy online environment. Various machine learning approaches have been employed to tackle this problem, ranging from traditional models to more recent attention-based transformer networks. This paper aims to compare the performance of attention-based transformer networks with several traditional machine learning methods for toxic comments classification. We present an in-depth analysis and evaluation of these methods using a common benchmark dataset. The experimental results demonstrate the strengths and limitations of each approach, shedding light on the suitability and efficacy of attention-based transformers in this domain.
Article
Open Access March 30, 2023

Pulsatile Blood Flow Simulation for Subject-Specific Geometry of a Human Aortic Arch

Abstract Pulsatile blood flow in a subject-specific human aortic arch and its major branches is studied computationally for a peak Reynolds number of 1553 and a Womersley number of 22.74. The aortic geometry is constructed from the CT-scan images of a subject. The aorta has out-of-plane curvature and significant area variation along the flow direction. A physiologically representative pulsatile velocity [...] Read more.
Pulsatile blood flow in a subject-specific human aortic arch and its major branches is studied computationally for a peak Reynolds number of 1553 and a Womersley number of 22.74. The aortic geometry is constructed from the CT-scan images of a subject. The aorta has out-of-plane curvature and significant area variation along the flow direction. A physiologically representative pulsatile velocity waveform is applied as boundary condition at the inlet of the aorta. The primary velocity profiles are skewed towards the inner wall of the ascending aorta during the entire cardiac cycle. In the decelerating phase, reverse flow is noted along the inner wall and the magnitude of maximum velocity is about 50 % of the peak flow condition. Flow separation is observed in the inner wall of the ascending aorta during the decelerating and reverse flow phases of the cardiac cycle. In the accelerating phase, however, flow separation does not occur. The major observation of the present work is the existence of complex and asymmetrical vortical flow structures which are not observed either in simple curved pipes or in idealized aortic arch computational studies. The relative strength of the secondary flow with respect to the primary flow is quantified by means of Relative Secondary Kinetic Energy whose highest value is evaluated to be 1.202 occurring near the entrance of the right carotid artery during the maximum reverse flow condition. High values of wall shear stress is observed at distal of the left and right subclavian arteries, the bifurcation of brachiocephalic artery between right subclavian artery and right carotid artery, and proximal inner wall of descending aorta during the cardiac cycle. The wall shear stress at the bifurcations of the branches are low and oscillatory and generally correlates with the preferential sites for atherosclerosis. The flow structures on the aorta wall are explicitly highlighted by the limiting streamlines. The application of limiting streamlines to clearly elucidate the complex on-wall flow structures is one of the key contributions of the present study. During the decelerating and reverse flow phases several critical points are observed on the aortic wall. These complex flow structures vanish during the accelerating phase. The observations made in the present study will be helpful in creating accurate and clinically useful computational models.
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Article
Open Access March 18, 2023

The Efficiency of the Proposed Smoothing Method over the Classical Cubic Smoothing Spline Regression Model with Autocorrelated Residual

Abstract Spline smoothing is a technique used to filter out noise in time series observations when predicting nonparametric regression models. Its performance depends on the choice of the smoothing parameter. Most of the existing smoothing methods applied to time series data tend to over fit in the presence of autocorrelated errors. This study aims to determine the optimum performance value, goodness of [...] Read more.
Spline smoothing is a technique used to filter out noise in time series observations when predicting nonparametric regression models. Its performance depends on the choice of the smoothing parameter. Most of the existing smoothing methods applied to time series data tend to over fit in the presence of autocorrelated errors. This study aims to determine the optimum performance value, goodness of fit and model overfitting properties of the proposed Smoothing Method (PSM), Generalized Maximum Likelihood (GML), Generalized Cross-Validation (GCV), and Unbiased Risk (UBR) smoothing parameter selection methods. A Monte Carlo experiment of 1,000 trials was carried out at three different sample sizes (20, 60, and 100) and three levels of autocorrelation (0.2, 05, and 0.8). The four smoothing methods' performances were estimated and compared using the Predictive Mean Squared Error (PMSE) criterion. The findings of the study revealed that: for a time series observation with autocorrelated errors, provides the best-fit smoothing method for the model, the PSM does not over-fit data at all the autocorrelation levels considered ( the optimum value of the PSM was at the weighted value of 0.04 when there is autocorrelation in the error term, PSM performed better than the GCV, GML, and UBR smoothing methods were considered at all-time series sizes (T = 20, 60 and 100). For the real-life data employed in the study, PSM proved to be the most efficient among the GCV, GML, PSM, and UBR smoothing methods compared. The study concluded that the PSM method provides the best fit as a smoothing method, works well at autocorrelation levels (ρ=0.2, 0.5, and 0.8), and does not over fit time-series observations. The study recommended that the proposed smoothing is appropriate for time series observations with autocorrelation in the error term and econometrics real-life data. This study can be applied to; non – parametric regression, non – parametric forecasting, spatial, survival, and econometrics observations.
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Article
Open Access March 16, 2023

The Black-Scholes Exotic Barrier Option Pricing Formula

Abstract The paper considers a specific type of such financial instrument as an option, namely an exotic barrier call option of the European type. Exotic options are gaining popularity among ordinary investors due to the development of information and telecommunication technologies, thanks to which such specific financial instruments as options have become readily available. We investigate the hedging [...] Read more.
The paper considers a specific type of such financial instrument as an option, namely an exotic barrier call option of the European type. Exotic options are gaining popularity among ordinary investors due to the development of information and telecommunication technologies, thanks to which such specific financial instruments as options have become readily available. We investigate the hedging problem for such options with some restrictions on the payment function and the availability of dividend payment on a risky asset in the classical Black-Scholes model. An analogue of the Black-Scholes formula for the mentioned variant of the exotic barrier is proved. In the future, it is planned to generalize the obtained results for put options and for more general payment functions.
Article
Open Access February 07, 2023

Building a Holistic Approach: Uniting Marxist and Smithian Economics for a More Resilient Economic Theory

Abstract In this article, we discuss a new proposed concept of economic engineering that seeks to innovate a new model by combining the theories of Karl Marx and Adam Smith, taking into consideration main economic factors to create a sustainable and inclusive economic system that addresses existing challenges and provides a roadmap for future economic growth. Through a brief analysis of the existing gaps [...] Read more.
In this article, we discuss a new proposed concept of economic engineering that seeks to innovate a new model by combining the theories of Karl Marx and Adam Smith, taking into consideration main economic factors to create a sustainable and inclusive economic system that addresses existing challenges and provides a roadmap for future economic growth. Through a brief analysis of the existing gaps between Marxist and Smithian economics, we developed a new economic matrix that leverages the strengths of both theories while also incorporating the latest insights from modern economic research. Our novel approach to economic engineering represents a fresh perspective on the economy and offers practical tool for addressing the most pressing challenges facing society today.
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Review Article
Open Access January 28, 2023

A framework for the evaluation of the decision between onsite and offsite construction using life cycle analysis (LCA) concepts and system dynamics modeling

Abstract The decision to choose between onsite and offsite construction is important in the effort toward sustainable construction. Offsite construction is often promoted as an environmentally friendly approach to construction operations. However, previous studies have shown that there is a lack of clarity on the environmental trade-offs between onsite and offsite construction. Factors that can affect the [...] Read more.
The decision to choose between onsite and offsite construction is important in the effort toward sustainable construction. Offsite construction is often promoted as an environmentally friendly approach to construction operations. However, previous studies have shown that there is a lack of clarity on the environmental trade-offs between onsite and offsite construction. Factors that can affect the decision to build onsite or offsite include the availability of a local offsite manufacturing facility, the distance of the offsite factory to the final place of use, the proximity of the site to the local supply of material and labor, etc. This study provides a framework to apply the system dynamic modeling technique to evaluate how various factors can affect the environmental impact of the building construction phase (for onsite or offsite construction methods). The system dynamic model (using Vensim software) that was developed provides a platform that allows users to input variables such as the distance that is expected for transportation of labor, material, and equipment to both the onsite facility and the offsite construction location, factors associated with the use of equipment for construction, the distance needed for transportation of building panels or modules from the offsite facility to the final site, etc. Among other things, the model showed that an increase in the distance from the offsite yard to the final construction site increases the total impacts of transportation of completed modules. An increase in the number of trips for the transportation of material to the onsite construction location increases the total impact of onsite construction. In terms of the environmental impact of construction, none of the two methods of construction gives an absolute superiority over the other. The environmental performance of offsite and onsite depends on various associated factors. It is recommended that building practitioners review various factors that are peculiar to their projects to make an informed decision on the best construction methods.
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Article
Open Access November 30, 2022

A Review of Application of LiDAR and Geospatial Modeling for Detection of Buildings Using Artificial Intelligence Approaches

Abstract Today, the presentation of a three-dimensional model of real-world features is very important and widely used and has attracted the attention of researchers in various fields, including surveying and spatial information systems, and those interested in the three-dimensional reconstruction of buildings. The building is the key part of the information in a three-dimensional city model, so extracting [...] Read more.
Today, the presentation of a three-dimensional model of real-world features is very important and widely used and has attracted the attention of researchers in various fields, including surveying and spatial information systems, and those interested in the three-dimensional reconstruction of buildings. The building is the key part of the information in a three-dimensional city model, so extracting and modeling buildings from remote sensing data is an important step in building a digital model of a city. LiDAR technology due to its ability to map in all three modes of one-dimensional, two-dimensional, and three-dimensional is a suitable solution to provide hyperspectral and comprehensive images of the building in an urban environment. In this review article, a comprehensive review of the methods used in identifying buildings from the past to the present and appropriate solutions for the future is discussed.
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Review Article
Open Access November 29, 2022

The Application of Machine Learning in the Corona Era, With an Emphasis on Economic Concepts and Sustainable Development Goals

Abstract The aim of this article is to examine the impacts of Coronavirus Disease -19 (Covid-19) vaccines on economic condition and sustainable development goals. In other words, we are going to study the economic condition during Covid19. We have studied the economic costs of pandemic, benefits in terms of gross domestic product (GDP), public finances and employment, investment on vaccines around the [...] Read more.
The aim of this article is to examine the impacts of Coronavirus Disease -19 (Covid-19) vaccines on economic condition and sustainable development goals. In other words, we are going to study the economic condition during Covid19. We have studied the economic costs of pandemic, benefits in terms of gross domestic product (GDP), public finances and employment, investment on vaccines around the world, progress and totally the economic impacts of vaccines and the impacts of emerging markets (EM) on achieving sustainable development goals (SDGs), including no poverty, good health and well-being, zero hunger, reduced inequality etc. The importance of emerging economies in reducing the harmful effects of the Corona has also been noted. We have tried to do experimental results and forecast daily new death cases from Feb-2020 to Aug-2021 in Iran using Artificial Neural Network (ANN) and Beetle Antennae Search (BAS) algorithm as a case study with econometric models and regression analysis. The findings show that Covid19 has had devastating economic and health effects on the world, and the vaccine can be very helpful in eliminating these effects specially in long-term. We observed that there is inequality in the distribution of Corona vaccines in rich countries compared to poor which EM can decrease the gap between them. The results show that both models (i.e., Artificial intelligence (AI) and econometric models) almost have the same results but AI optimization models can robust the model and prediction. The main contribution of this article is that we have surveyed the impacts of vaccination from socio-economic viewpoint not just report some facts and truth. We have surveyed the impacts of vaccines on sustainable development goals and the role of EM in achieving SDGs. In addition to using the theoretical framework, we have also used quantitative and empirical results that have rarely been seen in other articles.
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Article
Open Access October 26, 2022

Asymptotic Properties of the Semigroup Generated by a Continuous Interval Map

Abstract The article's purpose is twofold. First, we wish to draw attention to the insufficiently known field of continuous-time difference equations. These equations are paradigmatic for modeling complexity and chaos. Even the simplest equation , easily leads to complex dynamics, its solutions are perfectly suited to simulate strong nonlinear phenomena such as large-to-small cascades of structures, [...] Read more.
The article's purpose is twofold. First, we wish to draw attention to the insufficiently known field of continuous-time difference equations. These equations are paradigmatic for modeling complexity and chaos. Even the simplest equation , easily leads to complex dynamics, its solutions are perfectly suited to simulate strong nonlinear phenomena such as large-to-small cascades of structures, intermixing, formation of fractals, etc. Second, in the main body of the article we present a small but very important part of the theory behind the above equation marked by . Just as the discrete-time analog of this equation induces the one-dimensional dynamical system on some interval , so the equation induces the infinite-dimensional dynamical system on the space of functions . In the latter case, not only are the long-term behaviours of solutions critically dependent on the limit behaviour of the sequence (as in the discrete case) but also on the internal structure of as . Assuming to be continuous, we consider the iterations of as the semigroup generated by on the space of continuous maps, and introduce the notion of a limit semigroup for in a wider map space in order to investigate asymptotic properties of . We construct a limit semigroup in the space of upper semicontinuous maps. This enables us to describe both of the aforementioned aspects of our interest around the iterations of.
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Open Access September 20, 2022

High Radio Frequencies interaction of Composite Materials Using Rectangular Waveguide

Abstract The main goal of this paper is studying the composite material behavior under microwave which they used in antennas reflectors. For that, a transmission line method based on X- band WR90 rectangular waveguide is used. The Bi-anisotropic electrical properties are defined as tensors in finite element model. The fibers of the single layer composite are oriented in different directions. The [...] Read more.
The main goal of this paper is studying the composite material behavior under microwave which they used in antennas reflectors. For that, a transmission line method based on X- band WR90 rectangular waveguide is used. The Bi-anisotropic electrical properties are defined as tensors in finite element model. The fibers of the single layer composite are oriented in different directions. The S-parameters (S11 and S12) are calculated using COMSOL Multiyphysics, the S-parameters and currents density behavior show that they very affected by the orientations of the fibers which mean must be considered in any design of RF equipments, more the fibers are parallel with the electrical field more the reflection coefficient get higher.
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Review Article
Open Access August 31, 2022

Extended Rule of Five and Prediction of Biological Activity of peptidic HIV-1-PR Inhibitors

Abstract In this research work, we have applied “Lipinski’s RO5” for pharmacokinetics (PK) study and to predict the activity of peptidic HIV-1 protease inhibitors. Peptidic HIV-1-PRIs have been taken from literature with their observed biological activities (OBAs) in term of IC50. The logarithms of the inverse of IC50 have been used as biological end point o(log1/C) in the study. For calculation of [...] Read more.
In this research work, we have applied “Lipinski’s RO5” for pharmacokinetics (PK) study and to predict the activity of peptidic HIV-1 protease inhibitors. Peptidic HIV-1-PRIs have been taken from literature with their observed biological activities (OBAs) in term of IC50. The logarithms of the inverse of IC50 have been used as biological end point o(log1/C) in the study. For calculation of physicochemical parameters, the molecular modeling and geometry optimization of all the derivatives have been carried out with CAChe Pro software using semiempirical PM3 method. Prediction of the biological activity of the inhibitors has shown that the best QSAR model is constructed from pharmacokinetic properties, molecular weight and hydrogen bond acceptor. This also proved that these properties play important role to describe the PKs of the drugs. On the basis of the derived models one can build up a theoretical basis to access the biological activity of the compounds of the same series.
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Article
Open Access June 20, 2022

Charged Anisotropic Stellar Models with the MIT Bag Model Equation of State

Abstract In this paper we present a new classes of solutions for the Einstein-Maxwell system of field equations in a spherically symmetric spacetime under the influence of an electric field considering the MIT bag model equation of state with a particular form the metric potential that depends on an adjustable parameter. The obtained solutions can be written in terms of elementary functions, namely [...] Read more.
In this paper we present a new classes of solutions for the Einstein-Maxwell system of field equations in a spherically symmetric spacetime under the influence of an electric field considering the MIT bag model equation of state with a particular form the metric potential that depends on an adjustable parameter. The obtained solutions can be written in terms of elementary functions, namely polynomials and algebraic functions. The obtained models satisfy all physical properties expected in a realistic star. The results of this research can be useful in the development and description of new models of compact structures.
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Article
Open Access May 20, 2021

Bioconcentration Factor of Polychlorinated Biphenyls and Its Correlation with UV- and IR-Spectroscopic data: A DFT based Study

Abstract Polychlorinated biphenyls (PCBs) are important class of persist organic pollutants that were used as a component of paints especially in printings, as plastificator of plastics and insulating materials in transformers and capacitors, heat transfer fluids, additives in hydraulic fluids in vacuum and turbine pumps. There is always a need to establish reliable procedures for predicting the [...] Read more.
Polychlorinated biphenyls (PCBs) are important class of persist organic pollutants that were used as a component of paints especially in printings, as plastificator of plastics and insulating materials in transformers and capacitors, heat transfer fluids, additives in hydraulic fluids in vacuum and turbine pumps. There is always a need to establish reliable procedures for predicting the bioconcentration potential of chemicals from the knowledge of their molecular structure, or from readily measurable properties of the substance. Hence, correlation and prediction of biococentration factors (BCFs) based on λmax and vibration frequencies of various bonds viz υ(C-H) and υ(C=C) of biphenyl and its fifty-seven derivatives have been made. For the study, the molecular modeling and geometry optimization of the PCBs have been performed on workspace program of CAChe Pro 5.04 software of Fujitsu using DFT method. UV-visible spectra for each compound were created by electron transition between molecular orbitals as electromagnetic radiation in the visible and ultraviolet (UV-visible) region is absorbed by the molecule. The energies of excited electronic states were computed quantum mechanically. IR spectra of transitions for each compound were created by coordinated motions of the atoms as electromagnetic radiation in the infrared region is absorbed by the molecule. The force necessary to distort the molecule was computed quantum mechanically from its equilibrium geometry and thus frequency of vibrational transitions was predicted. Project Leader Program associated with CAChe has been used for multiple linear regression (MLR) analysis using above spectroscopic data as independent variables and BCFs of PCBs as dependent variables. The reliability of correlation and predicting ability of the MLR equations (models) are judged by R2, R2adj, se, q2L10O and F values. This study reflected clearly that UV and IR spectroscopic data can be used to predict BCFs of a large number of related compounds within limited time without any difficulty.
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Editorial Article
Open Access May 21, 2021

Modeling of Target Audience'S Intellectual Behavior

Abstract The article considers the problems of theoretical substantiation of negative informational and psychological impact evaluation principles, and conducting of relevant researches in this field. At the same time, due to imperfections of theory and practice of negative informational and psychological impact evaluation, previous researches were conducted mainly by “mirroring” the ways of information [...] Read more.
The article considers the problems of theoretical substantiation of negative informational and psychological impact evaluation principles, and conducting of relevant researches in this field. At the same time, due to imperfections of theory and practice of negative informational and psychological impact evaluation, previous researches were conducted mainly by “mirroring” the ways of information counteraction, both for our own measures of information and psychological influence, and for the adversary. The rationale for the methodological approaches used in the organization of information and psychological influence is due to inability to access the adversary's target audiences freely and gather the necessary information, as well as the inadequacy of assessing the degree of change in their behaviour. Characteristics mentioned in article classify target audiences according to defined indicators of remote information control of social and individual behaviour of possible objects of influence. Using the formulated conditions and relying on the psychological and psychophysiological characteristics of individuals, a database of target audience behaviour vulnerabilities is forming, that reflects the dependence of indicators of social behaviour perception changes on the intensity of external negative informational and psychological influences. The algorithm of target audience’s information perception is developed based on the model of planned behaviour, in which the subject’s overestimation of small values of probabilities are compared in dynamic with decrease of big ones. The proposed algorithm of evaluation of information-psychological impact allows to receive initial data based on which the model of target audience behaviour will be designed in any environmental conditions.
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Open Access February 13, 2026

Influence of Religious Literacy and Multicultural Teaching Competence on Religious and Moral Education Teachers’ Self-Efficacy: Empirical Evidence from Public Basic Schools in the Kumasi Metropolis

Abstract The focus of this study was to determine the influence of religious literacy and multicultural teaching competence on the teaching self-efficacy of Religious and Moral Education (RME) teachers in public basic schools within the Kumasi Metropolis. The research employed a cross-sectional survey design with a sample of 308 RME teachers selected through the stratified sampling technique from 165 basic [...] Read more.
The focus of this study was to determine the influence of religious literacy and multicultural teaching competence on the teaching self-efficacy of Religious and Moral Education (RME) teachers in public basic schools within the Kumasi Metropolis. The research employed a cross-sectional survey design with a sample of 308 RME teachers selected through the stratified sampling technique from 165 basic schools across 14 circuits. Data were collected using questionnaires and analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings revealed that religious literacy significantly and positively influenced teachers’ self-efficacy (β = 0.487, p < 0.05), accounting for 23.7% of the variance. Similarly, multicultural teaching competence demonstrated a strong positive effect on teaching self-efficacy (β = 0.711, p < 0.05), explaining 50.6% of the variance. Finally, the study found that religious literacy and multicultural teaching competence together contributed 52.2% to RME teachers' teaching self-efficacy (SD = 0.692, p < 0.05, R² = 0.522). The study recommended that the Ghana Education Service (GES) and the National Council for Curriculum and Assessment (NaCCA) should design and mandate regular in-service training programmes focused specifically on religious literacy for RME teachers. Also, it was recommended that pre-service and in-service training should emphasise awareness of personal biases, deep knowledge of learners’ cultural and religious backgrounds, and practical skills for culturally responsive pedagogy.
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Open Access February 13, 2026

Integrated GIS and geotechnical assessment of the stability of the Oued Ayda dike (Kesra Siliana, Tunisia)

Abstract This study proposes an integrated approach combining geographic information systems (GIS) and geotechnical analyses to assess the stability of the Oued Ayda mountain lake dam, located in the Siliana Governorate, northwestern Tunisia. The mechanical properties of the embankment and foundation materials were integrated into a Mohr-Coulomb geomechanical model, while the pore water pressure [...] Read more.
This study proposes an integrated approach combining geographic information systems (GIS) and geotechnical analyses to assess the stability of the Oued Ayda mountain lake dam, located in the Siliana Governorate, northwestern Tunisia. The mechanical properties of the embankment and foundation materials were integrated into a Mohr-Coulomb geomechanical model, while the pore water pressure distribution was simulated for various representative hydromechanical scenarios: end of construction, normal operation, rapid drainage, and short- and long-term empty reservoir conditions. The stability analysis, performed using the Morgenstern-Price method with the SLOPE/W software (GeoStudio), reveals high safety factors on the upstream side (SF > 3 in the short term and SF ≥ 2 in the long term), indicating good resistance of this slope to hydraulic and mechanical stresses. Conversely, the results show that the downstream slope exhibits significantly lower safety factors, ranging from 1.335 to 1.338 under long-term conditions, particularly during normal operating and rapid drainage scenarios. These reduced values indicate a high vulnerability of this slope to persistent saturation and adverse hydraulic gradients. In conclusion, although the dam exhibits satisfactory overall stability, the downstream slope remains the most vulnerable area of the structure. The results underscore the need for rigorous management of water level fluctuations and suggest reinforcing the drainage system or implementing targeted stabilization measures to ensure the long-term safety and durability of the structure.
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Open Access January 13, 2026

Principles and Practices of Transformative Online Doctoral Mentoring—A Mentor’s Perspective

Abstract An effective mentor is critical to the success of an online doctoral student. Researchers have found that online doctoral students prefer frequent interactions with their mentor, while faculty prefer mentees to be autonomous. Transformative online doctoral mentoring (ODM) requires the development of a strong collaborative working relationship between the mentee and mentor, who serves as the link [...] Read more.
An effective mentor is critical to the success of an online doctoral student. Researchers have found that online doctoral students prefer frequent interactions with their mentor, while faculty prefer mentees to be autonomous. Transformative online doctoral mentoring (ODM) requires the development of a strong collaborative working relationship between the mentee and mentor, who serves as the link between the student and academia, as well as their guide and working partner throughout the dissertation process. In this paper, I argue that the ultimate objective of ODM, the establishment of such a relation-ship between mentor and mentee, increases the likelihood of student success. I support this contention with a set of principles and practices grounded in relevant models and methods of human development, participative leadership, and collaborative change management that provide insights into the what, why, and how of transformative ODM.
Article
Open Access December 22, 2025

Reimagining Mathematical Modeling for a Responsive and Integrated Future in Infectious Disease Epidemiology

Abstract Mathematical modeling plays a central role in infectious disease epidemiology, shaping outbreak response strategies and informing public health policy. The COVID-19 pandemic demonstrated the value of these models but also exposed persistent limitations related to data fragility, lack of transparency, limited stakeholder engagement, and insufficient consideration of social and political contexts. [...] Read more.
Mathematical modeling plays a central role in infectious disease epidemiology, shaping outbreak response strategies and informing public health policy. The COVID-19 pandemic demonstrated the value of these models but also exposed persistent limitations related to data fragility, lack of transparency, limited stakeholder engagement, and insufficient consideration of social and political contexts. Rather than critiquing modeling as a discipline, this perspective argues for a reorientation of infectious disease modeling toward a more responsive, equity-centered, and participatory paradigm. We propose a conceptual framework built on three interrelated principles: adaptability through real-time data integration, transparency via open-source and reproducible practices, and relevance through interdisciplinary and co-produced model design. Drawing on illustrative examples from COVID-19 and dengue control efforts, we highlight how integrating behavioral dynamics, local knowledge, and policy feedback can improve model usefulness and public trust. Reconceptualizing models as dynamic systems of inquiry rather than static forecasting tools can enhance decision-making and promote more equitable and effective responses to future public health emergencies.
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Brief Review
Open Access November 28, 2025

Determinants of the Carotid Tortuosity Index: Evidence from Digital Subtraction Angiography

Abstract Introduction: Stroke remains one of the leading causes of death and disability worldwide, with ischemic stroke accounting for most cases. Structural vascular factors such as carotid artery tortuosity have gained attention as potential markers of vascular aging and cerebrovascular risk. The carotid tortuosity index (CTI), defined as the ratio of actual vessel length to the straight-line [...] Read more.
Introduction: Stroke remains one of the leading causes of death and disability worldwide, with ischemic stroke accounting for most cases. Structural vascular factors such as carotid artery tortuosity have gained attention as potential markers of vascular aging and cerebrovascular risk. The carotid tortuosity index (CTI), defined as the ratio of actual vessel length to the straight-line distance between two fixed points, provides a quantitative measure of arterial curvature. A CTI value of ≥1.2 indicates pathological tortuosity. Although noninvasive modalities such as CTA and MRA are frequently used, digital subtraction angiography (DSA) remains the gold standard for evaluating vessel geometry due to its higher spatial precision. This study aimed to determine the association of age, sex, and hypertension with CTI measured by DSA. Methods: A cross-sectional study was conducted from November to December 2025 at the Neurointervention Clinic, RS Pelni Jakarta, Indonesia, involving 61 adult patients who underwent carotid DSA. CTI was measured bilaterally using digital imaging software and classified as <1.2 (non-tortuous) or ≥1.2 (tortuous). Clinical data, including age, sex, and hypertension status, were collected from medical records and analyzed using bivariate tests. Results: Older age (≥65 years), female sex, and hypertension were significantly associated with higher CTI values on both carotid sides. Tortuosity was more common among hypertensive patients and elderly females, indicating the influence of vascular remodeling and chronic hemodynamic stress. Conclusion: Carotid tortuosity increases with age, hypertension, and female sex. DSA-based CTI measurement provides a reliable and precise approach for evaluating vascular changes associated with cerebrovascular risk.
Article
Open Access November 10, 2025

Teaching in a Diverse Society: Influence of Religious Literacy and Multicultural Teaching Competence on the Self-Efficacy of Religious and Moral Education Teachers in the Accra Metropolis, Ghana

Abstract The ultimate goal of this study was to determine the influence of religious literacy and multicultural teaching competence of RME teachers on their teaching self-efficacy in the Accra Metropolis. Grounded in culturally responsive teaching and self-efficacy theory, this study employed a cross-sectional survey design. All 441 RME teachers in the eight (8) circuits in the Metropolis which has [...] Read more.
The ultimate goal of this study was to determine the influence of religious literacy and multicultural teaching competence of RME teachers on their teaching self-efficacy in the Accra Metropolis. Grounded in culturally responsive teaching and self-efficacy theory, this study employed a cross-sectional survey design. All 441 RME teachers in the eight (8) circuits in the Metropolis which has seventy-two (72) basic schools were involved in the study through the census method. Data were collected using a questionnaire and analyzed using descriptive statistics and partial least squares structural equation modeling (PLS-SEM). Findings revealed that RME teachers reported high levels of RL, MTC, and TSE. Religious literacy and multicultural teaching competence jointly explained 44.2% of the variance in TSE, with a statistically significant positive effect (p < 0.05). It was recommended that, the curriculum for training RME teachers should include in them topics on RL and MTC.
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Open Access November 09, 2025

Application of Building Information Modelling (BIM) for Enhancing Safety and Environmental Performance on Construction Sites in Nigeria

Abstract Background: Building Information Modelling (BIM) improves safety planning in construction by enabling visualization and simulation to identify and reduce risks. However, its adoption in Nigeria is limited. This study examines the application of BIM in enhancing safety and environmental performance on construction sites in Nigeria. Methodology: A quantitative cross-sectional survey [...] Read more.
Background: Building Information Modelling (BIM) improves safety planning in construction by enabling visualization and simulation to identify and reduce risks. However, its adoption in Nigeria is limited. This study examines the application of BIM in enhancing safety and environmental performance on construction sites in Nigeria. Methodology: A quantitative cross-sectional survey was conducted using a structured online questionnaire distributed to professionals in Nigeria’s construction industry. A purposive sampling method was employed to target respondents with relevant BIM experience. Data were analysed using SPSS version 28, applying descriptive statistics, chi-square tests, and logistic regression at a 5% significance level. Result: Findings show that BIM was fully adopted by 7.0% of organizations, with only 19.8% of respondents using it to identify safety hazards during planning. While 76.8% reported no notable safety benefit, 19.5% identified improved risk management as the key benefit. Most respondents (80.2%) reported no noticeable environmental benefits. Among those who did, improved energy efficiency was the most cited benefit (16.4%). Respondents with 10 or more years of experience were significantly more likely to report enhanced safety and environmental outcomes (AOR = 4.555; p = 0.003) and adequate BIM utilization (AOR = 3.255; p = 0.023). Those with intermediate BIM experience were also more likely to report high enhancement (AOR = 2.857; p = 0.039) and effective tool use (AOR = 2.881; p = 0.050). Conclusion: This study revealed that BIM has the potential to improve construction outcomes in Nigeria if supported by training, experience, and structured implementation.
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Article
Open Access November 06, 2025

Ventral Attention Network Resting State Functional Connectivity: Psychosocial Correlates among US Adolescents

Abstract Background: Resting-state functional MRI (rsfMRI) provides insights into large-scale brain network organization associated with cognitive control, emotion regulation, and attentional processes. The ventral attention network (VAN) is a key salience-driven network that supports attentional re-orienting to behaviorally relevant stimuli. However, little is known about how VAN [...] Read more.
Background: Resting-state functional MRI (rsfMRI) provides insights into large-scale brain network organization associated with cognitive control, emotion regulation, and attentional processes. The ventral attention network (VAN) is a key salience-driven network that supports attentional re-orienting to behaviorally relevant stimuli. However, little is known about how VAN resting state functional connectivity varies by demographic, socioeconomic, psychosocial, and behavioral factors during early adolescence. Objective: To examine associations between VAN rsfMRI connectivity and multiple demographic, socioeconomic, psychosocial, and behavioral characteristics. Methods: Data came from the baseline and early follow-up waves of the Adolescent Brain Cognitive Development (ABCD) Study. The analytic sample included youth with high-quality baseline rsfMRI data and complete socioeconomic and psychosocial measures. The primary outcome was mean resting-state functional connectivity within the VAN across subcortical and cortical regions of interest (ROIs). Bivariate correlations were computed between VAN connectivity and demographic (age, sex, puberty, race/ethnicity), socioeconomic (income, parental education, marital status, neighborhood income), psychosocial (trauma, discrimination, financial difficulty), trait (impulsivity), and behavioral variables (body mass index, depression, suicide, prodromal symptoms, and substance use). Unadjusted bivariate correlations and adjusted logistic regressions were used for data analysis. Results: VAN connectivity showed small but significant correlations with multiple contextual factors. Higher household income, parental education, and neighborhood affluence were associated with greater connectivity, whereas Black race and Hispanic ethnicity were related to lower connectivity. Youth reporting higher discrimination and financial difficulty exhibited weaker VAN connectivity. Greater VAN connectivity was negatively associated with impulsive reward-driven trait (drive), prodromal symptoms, BMI, and marijuana and alcohol use. Associations between VAN connectivity and suicide, depression, marijuana use, and alcohol use remained significant in age and sex adjusted models. Conclusions: VAN connectivity reflects subtle neural correlates of socioeconomic and psychosocial context in early adolescence. Our results underscore the importance of integrating structural and contextual factors in interpreting brain-behavior associations across diverse populations. These findings are suggestive of stable socioeconomic and psychosocial correlates of network efficiency.
Article
Open Access October 29, 2025

Mean Diffusivity of the Left Caudal Anterior Cingulate Cortex and Past Major Depressive Disorder in Adolescents: Evidence from the ABCD Study

Abstract Background: Adolescence is a critical developmental stage for the emergence of major depressive disorder (MDD). Structural and diffusion neuroimaging studies have highlighted the anterior cingulate cortex (ACC) as a key region implicated in emotion regulation, stress reactivity, and mood processing. However, few studies have examined whether microstructural characteristics of the ACC, [...] Read more.
Background: Adolescence is a critical developmental stage for the emergence of major depressive disorder (MDD). Structural and diffusion neuroimaging studies have highlighted the anterior cingulate cortex (ACC) as a key region implicated in emotion regulation, stress reactivity, and mood processing. However, few studies have examined whether microstructural characteristics of the ACC, reflected by mean diffusivity (MD) within gray matter–white matter (GM–WM) contrast regions, are associated with depression in early adolescence. Objective: To examine whether mean diffusivity (MD) within the GM–WM contrast of the left caudal anterior cingulate cortex (ACC) is associated with a past diagnosis of MDD among adolescents in the Adolescent Brain Cognitive Development (ABCD) Study, after accounting for demographic, socioeconomic, and adversity-related factors. Methods: Data were drawn from adolescents with diffusion MRI–derived mean diffusivity measures and diagnostics. The independent variable was mean diffusivity (MD) of the GM–WM contrast in the left caudal ACC. The primary outcome was past MDD diagnosis based on structured psychiatric assessments. Covariates included age, sex, socioeconomic status (SES), and exposure to adverse childhood experiences (ACEs). Logistic regression models tested the association between ACC MD and past MDD. A secondary model evaluated the relationship between ACC MD and past suicide attempt. Results: Mean diffusivity of the left caudal ACC was associated with the odds of past MDD, independent of age, sex, SES, and adversity exposure. In contrast, ACC mean diffusivity was not associated with a history of suicide attempt. Conclusions: Increased mean diffusivity in the caudal ACC may indicate microstructural alterations associated with depressive vulnerability in adolescence. ACC tissue integrity may serve as a sensitive neural correlate of early-onset depression.
Article
Open Access October 04, 2025

Unequal Burden of Loss of a Loved One in Non-Hispanic Black and White Californians

Abstract Purpose: Although the effect of loss of a loved one on depression is well established, very limited knowledge exists on racial differences in this effect. Aim: In the current study we compared Non-Hispanic White (NHW) and Non-Hispanic Black (NHB) Californians for the effects of loss of a loved one on depression in a representative sample of adults in California. Methods: This cross-sectional study used data from the Survey of California Adults on Serious Illness and End-of-Life 2019. Overall, 1603 people entered our study. We compared 901 (56.2%) NHB and 702 (43.8%) NHW adults (age 18 and older). Race/ethnicity, demographics (age and gender), socio-economic factors (education, income, employment, and marital status), religiosity, and health (self-rated health and number of chronic medical conditions), and depression were measured. To perform data analysis, we used logistic regression models. Results: In the pooled sample, loss of a loved one was not associated with self-reported depression, net of all covariates. Race, however, interacted with loss of a loved one on depression, suggesting a larger association for NHBs compared to NHWs. In race-specific models, loss of a loved one predicted depression for NHBs (OR = 1.54) but not NHWs (OR [...] Read more.
Purpose: Although the effect of loss of a loved one on depression is well established, very limited knowledge exists on racial differences in this effect. Aim: In the current study we compared Non-Hispanic White (NHW) and Non-Hispanic Black (NHB) Californians for the effects of loss of a loved one on depression in a representative sample of adults in California. Methods: This cross-sectional study used data from the Survey of California Adults on Serious Illness and End-of-Life 2019. Overall, 1603 people entered our study. We compared 901 (56.2%) NHB and 702 (43.8%) NHW adults (age 18 and older). Race/ethnicity, demographics (age and gender), socio-economic factors (education, income, employment, and marital status), religiosity, and health (self-rated health and number of chronic medical conditions), and depression were measured. To perform data analysis, we used logistic regression models. Results: In the pooled sample, loss of a loved one was not associated with self-reported depression, net of all covariates. Race, however, interacted with loss of a loved one on depression, suggesting a larger association for NHBs compared to NHWs. In race-specific models, loss of a loved one predicted depression for NHBs (OR = 1.54) but not NHWs (OR = 0.99). Conclusion: There are differences between NHBs and NHWs in the effect of loss of a loved one on depression. NHBs show a stronger association between loss of a loved one and depression than NHWs. This result is not in line with the NHB mental health paradox or with NHB resilience but is consistent with the notion that social relations may be more salient for NHBs than for NHWs.
Article
Open Access October 01, 2025

Place-Based Diminished Returns of Economic Resources in Rural America: A Framework for Understanding Geography-Conditioned Inequality

Abstract Background: Socioeconomic status (SES) is widely associated with improved health, behavioral, and educational outcomes. However, emerging research suggests that these benefits are not uniformly experienced across populations or contexts. The theory of Marginalization-related Diminished Returns (MDRs) has primarily focused on racial and ethnic disparities, showing that individuals from [...] Read more.
Background: Socioeconomic status (SES) is widely associated with improved health, behavioral, and educational outcomes. However, emerging research suggests that these benefits are not uniformly experienced across populations or contexts. The theory of Marginalization-related Diminished Returns (MDRs) has primarily focused on racial and ethnic disparities, showing that individuals from racially marginalized groups often experience weaker protective effects of SES. There is a lack of evidence on geography—particularly rural residence—as a moderator of SES effects. Objective: This review explores how place, especially rural contexts in the U.S., shapes the extent to which SES translates into improved outcomes. We extend the MDRs framework to include place-based and geography-based marginalization, arguing that even among non-Hispanic White populations, rural residence can lead to diminished returns on education, income, and other forms of capital. Content: Drawing on theoretical models such as Fundamental Cause Theory and Bronfenbrenner’s Ecological Systems Theory, and synthesizing empirical findings from studies of academic achievement, substance use, and educational aspirations, this review highlights how structural disadvantages in rural areas weaken the effectiveness of individual and family-level resources. Conclusion: Rural health and educational disparities are not solely due to a lack of resources but may also reflect systemic conditions that erode the value of existing resources. Policy interventions must be place-aware and address the contextual constraints that limit opportunity. Future research should more explicitly test how geography moderates the effects of SES across a range of outcomes and populations.
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Perspective Article
Open Access September 28, 2025

Mitochondrial Dysfunction and Oxidative Stress in Early-Onset Neurodegenerative Diseases: A Bibliometric and Data-Driven Analysis

Abstract Early-onset neurodegenerative diseases (EO-NDs), such as early-onset Alzheimer’s disease (EOAD), Parkinson’s disease (EOPD), and familial amyotrophic lateral sclerosis (fALS), often stem from monogenic causes and manifest before typical age thresholds. These disorders frequently feature disrupted mitochondrial function and heightened oxidative stress, which together accelerate neuronal damage and [...] Read more.
Early-onset neurodegenerative diseases (EO-NDs), such as early-onset Alzheimer’s disease (EOAD), Parkinson’s disease (EOPD), and familial amyotrophic lateral sclerosis (fALS), often stem from monogenic causes and manifest before typical age thresholds. These disorders frequently feature disrupted mitochondrial function and heightened oxidative stress, which together accelerate neuronal damage and degeneration. In this work, the author performs a comprehensive analysis of the literature and data related to mitochondrial dysfunction and redox imbalance in EO-NDs. Bibliometric trends were assessed using R-based tools on PubMed datasets, highlighting keyword networks and publication surges in recent years. Publicly available RNA-seq datasets from GEO and SRA were examined, with example DESeq2 analysis illustrating altered mitochondrial gene expression in EO-ND patient-derived samples. Network modeling of redox pathways using Python’s networkx demonstrates how oxidative stress can propagate through metabolic networks. Together, these computational approaches reinforce that mitochondrial DNA mutations, impaired electron transport chain (ETC) function, and reactive oxygen species (ROS) accumulation play central roles in EO-ND pathogenesis. The discussion further evaluates why antioxidant clinical trials have largely failed and how emerging therapies such as gene replacement, antisense oligonucleotides, and mitochondrial biogenesis modulators may provide more effective interventions.
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Brief Report
Open Access September 28, 2025

Gut-Brain Axis in Autism Spectrum Disorder: A Bibliometric and Microbial-Metabolite-Neural Pathway Analysis

Abstract The gut-brain axis (GBA) has emerged as a central focus in the study of neurodevelopmental disorders, particularly autism spectrum disorder (ASD). Research suggests that microbial composition and its metabolic byproducts influence neural development, synaptic plasticity, and behavior [1,2,3]. A structured bibliometric analysis of Scopus and Web of Science records was performed using Bibliometrix [...] Read more.
The gut-brain axis (GBA) has emerged as a central focus in the study of neurodevelopmental disorders, particularly autism spectrum disorder (ASD). Research suggests that microbial composition and its metabolic byproducts influence neural development, synaptic plasticity, and behavior [1,2,3]. A structured bibliometric analysis of Scopus and Web of Science records was performed using Bibliometrix and VOSviewer to trace trends and thematic evolution of GBA–ASD literature [7,8]. In parallel, a data-driven pathway modeling approach maps microbial metabolites (e.g., short-chain fatty acids, tryptophan catabolites) to host signaling pathways including vagal stimulation, immune cytokine modulation, and blood–brain barrier (BBB) permeability [4,5]. Simulations implemented in Python’s NetworkX illustrate how perturbations in metabolite flux may influence CNS outcomes. The findings reveal growing emphasis on butyrate, serotonin, microglial priming, and maternal immune activation in ASD-related GBA studies, and highlight the need for rigorous empirical validation of computational predictions [9,10,11].
Brief Report
Open Access September 18, 2025

Does Stress Explain the Effects of Sexual/Gender Minority Status on Children’s Behavioral and Emotional Risk?

Abstract Background: Sexual and gender minority (SGM) youth are at elevated risk for adverse mental health and substance use outcomes. Stressors such as family conflict, discrimination, and trauma have been suggested as possible mediators of these disparities. Aims: This study examined whether family conflict, discrimination, and trauma mediate the associations between SGM identity and [...] Read more.
Background: Sexual and gender minority (SGM) youth are at elevated risk for adverse mental health and substance use outcomes. Stressors such as family conflict, discrimination, and trauma have been suggested as possible mediators of these disparities. Aims: This study examined whether family conflict, discrimination, and trauma mediate the associations between SGM identity and adverse outcomes, including suicide attempt, major depressive disorder (MDD), nicotine use, and marijuana use. Methods: Participants were children from the Adolescent Brain Cognitive Development (ABCD) study. SGM identity was reported at baseline, while outcomes included past MDD and suicide attempts as well as future nicotine and marijuana use. Structural equation modeling (SEM) was used to test both direct and indirect pathways linking SGM identity to mental health and behavioral outcomes. Results: No significant mediation was found through family conflict, discrimination, or trauma. Instead, effects of SGM identity were primarily direct: SGM youth had higher odds of past suicide attempts and MDD, as well as future marijuana use, but not future nicotine use. Stressor variables, however, were independently associated with outcomes. Discrimination predicted all outcomes; trauma was positively associated with suicide, nicotine, and marijuana use but not MDD; and family conflict predicted all outcomes except MDD. Conclusion: Family conflict, discrimination, and trauma did not mediate SGM disparities in mental health and substance use, but each emerged as an independent predictor of risk. These findings highlight the complexity of mechanisms underlying SGM-related disparities and suggest the need for future research to explore additional pathways and contextual influences.
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Article
Open Access September 14, 2025

Lifecycle Management as a Roadmap to the Tobacco Endgame

Abstract Background: Tobacco endgame, defined as elimination of commercial tobacco sales The U.S. tobacco control landscape is a complex, adaptive system shaped by diverse stakeholders, evolving products and regulations, shifting social norms, and the strategic countermeasures of a powerful industry. Managing such complexity requires more than isolated interventions—it demands a coordinated, [...] Read more.
Background: Tobacco endgame, defined as elimination of commercial tobacco sales The U.S. tobacco control landscape is a complex, adaptive system shaped by diverse stakeholders, evolving products and regulations, shifting social norms, and the strategic countermeasures of a powerful industry. Managing such complexity requires more than isolated interventions—it demands a coordinated, enterprise-wide approach that accounts for dynamic interactions, feedback loops, and emergent risks. Objective: Drawing on complex systems thinking, Zachman enterprise architecture model, and public health best practices, we conceptualize tobacco control as an evolving enterprise progressing through six interconnected phases: (1) Conception & Initiation, (2) Policy & System Design, (3) Implementation & Operation, (4) Evaluation & Adaptation, (5) Consolidation & Endgame Transition, and (6) Sustainment or Sunset. Each phase incorporates governance structures, performance benchmarks, and transition criteria designed to manage interdependence and reduce systemic vulnerabilities. Results: The lifecycle framing emphasizes how tobacco control in the U.S. can evolve as a complex, adaptive enterprise—integrating public health objectives with legal, operational, and cultural change processes. This model supports strategic sequencing, cross-sector alignment, and risk mitigation against emergent industry tactics, enabling a resilient and measurable pathway to the endgame. Conclusions: Seeing tobacco control as a complex enterprise that operates under a lifecycle model may offer a roadmap for achieving and sustaining the tobacco endgame. Using this approach may enhance policy coherence, resource efficiency, and adaptability, ensuring tobacco endgame is achieved.
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Open Access August 03, 2025

Comparison of Rates of Air Leakage Due to Differences in Face Shape and Mask Size

Abstract Effective infection control requires a close fit between the mask and face to minimize gaps. This study investigated whether surgical mask performance varies with face shape and mask size. Three facial models were 3D-printed using head-related transfer function data. Two mask sizes were tested on each model, and 3D measurements were taken at five facial points: the nose, cheeks, and chin to assess [...] Read more.
Effective infection control requires a close fit between the mask and face to minimize gaps. This study investigated whether surgical mask performance varies with face shape and mask size. Three facial models were 3D-printed using head-related transfer function data. Two mask sizes were tested on each model, and 3D measurements were taken at five facial points: the nose, cheeks, and chin to assess mask-to-face gaps. To simulate droplet emission, an aqueous sodium chloride solution was released from a pseudo-oral cavity in the models, and air leakage was measured using a mask-fitting tester. A two-way analysis of variance (ANOVA) was used to examine the effects of face and mask size on leakage. Small face models showed significantly higher leakage than medium and large ones (p < 0.001), and S-sized masks leaked more than M-sized masks regardless of face size (p = 0.038). Linear regression showed a positive correlation between chin gaps and leakage when using S-sized masks (p < 0.05). These results suggest that medium-sized masks offer better overall performance. However, for small faces, fit—especially at the chin, requires particular attention.
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Open Access June 28, 2025

Development of a Hemodialysis Data Collection and Clinical Information System and Establishment of an Intradialytic Blood Pressure/Pulse Rate Predictive Model

Abstract This research is a collaboration involving a university team, a partnering corporation, and a hemodialysis clinic, which is a cross-disciplinary research initiative in the field of Artificial Intelligence of Things (AIoT) within the medical informatics domain. The research has two objectives: (1) The development of an Internet of Things (IoT)-based Information System customized for the hemodialysis machines at the clinic, including transmission bridges, clinical personnel dedicated web/app, and a backend server. The system has been deployed at the clinic and is now officially operational; (2) The research also utilized de-identified, anonymous data (collected by the officially operational system) to train, evaluate, and compare Deep Learning-based Intradialytic Blood Pressure (BP)/Pulse Rate (PR) Predictive Models [...] Read more.
This research is a collaboration involving a university team, a partnering corporation, and a hemodialysis clinic, which is a cross-disciplinary research initiative in the field of Artificial Intelligence of Things (AIoT) within the medical informatics domain. The research has two objectives: (1) The development of an Internet of Things (IoT)-based Information System customized for the hemodialysis machines at the clinic, including transmission bridges, clinical personnel dedicated web/app, and a backend server. The system has been deployed at the clinic and is now officially operational; (2) The research also utilized de-identified, anonymous data (collected by the officially operational system) to train, evaluate, and compare Deep Learning-based Intradialytic Blood Pressure (BP)/Pulse Rate (PR) Predictive Models, with subsequent suggestions provided. Both objectives were executed under the supervision of the Institutional Review Board (IRB) at Mackay Memorial Hospital in Taiwan. The system completed for objective one has introduced three significant services to the clinic, including automated hemodialysis data collection, digitized data storage, and an information-rich human-machine interface as well as graphical data displays, which replaces traditional paper-based clinical administrative operations, thereby enhancing healthcare efficiency. The graphical data presented through web and app interfaces aids in real-time, intuitive comprehension of the patients’ conditions during hemodialysis. Moreover, the data stored in the backend database is available for physicians to conduct relevant analyses, unearth insights into medical practices, and provide precise medical care for individual patients. The training and evaluation of the predictive models for objective two, along with related comparisons, analyses, and recommendations, suggest that in situations with limited computational resources and data, an Artificial Neural Network (ANN) model with six hidden layers, SELU activation function, and a focus on artery-related features can be employed for hourly intradialytic BP/PR prediction tasks. It is believed that this contributes to the collaborating clinic and relevant research communities.
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Article
Open Access June 26, 2025

The Intersection of Climate Change Adaptation and Smallholder Farmer Food Security: A Review of Strategies and Barriers

Abstract Smallholder farmers play a pivotal role in global food security; however, they remain exceptionally vulnerable to the impacts of climate change due to their reliance on natural resources and limited adaptive capacities. This narrative review synthesizes a wide range of global sources to explore the intersection of smallholder agriculture and climate adaptation strategies. The review examines [...] Read more.
Smallholder farmers play a pivotal role in global food security; however, they remain exceptionally vulnerable to the impacts of climate change due to their reliance on natural resources and limited adaptive capacities. This narrative review synthesizes a wide range of global sources to explore the intersection of smallholder agriculture and climate adaptation strategies. The review examines adaptation practices, agroecological methods, and the adoption of climate-resilient crop varieties. It reveals that the implementation of these strategies is frequently hindered by systemic barriers such as financial constraints, limited technological access, and institutional inefficiencies. Recognizing that previous studies have addressed isolated aspects of adaptation or relied on secondary data, this review highlights research gaps and offers a comprehensive synthesis of relevant literature. This review uses a narrative synthesis model suitable for integrating evidence from agronomy, economics, and social science to capture the complex challenges faced by smallholder farmers. The review emphasizes the importance of policy frameworks and participatory approaches that empower smallholder communities. This review synthesizes current evidence to inform potential directions for targeted interventions and future field-based studies, while recognizing the limitations of relying on secondary data. These recommendations aim to facilitate integrated policy reforms and drive research initiatives, ultimately strengthening the resilience and adaptability of smallholder agriculture in the face of ongoing climate change.
Review Article
Open Access June 03, 2025

Complexity Leadership Theory Integration into Nursing Leadership and Development in Addressing COVID-19 and Future Pandemics

Abstract Complexity Leadership Theory (CLT) is a new and revolutionary concept in addressing healthcare crises worldwide. Its relevance and applications were tested during the COVID-19 pandemic. However, no definite and encompassing research was done to apply it to nursing leadership. Thus, this study examines CLT integration into nursing leadership to address the challenges posed by the pandemic. Through [...] Read more.
Complexity Leadership Theory (CLT) is a new and revolutionary concept in addressing healthcare crises worldwide. Its relevance and applications were tested during the COVID-19 pandemic. However, no definite and encompassing research was done to apply it to nursing leadership. Thus, this study examines CLT integration into nursing leadership to address the challenges posed by the pandemic. Through a systematic review of literature from PubMed, Scopus, and Web of Science, relevant studies were analyzed to determine how complexity leadership theory was defined, conceptualized, and operationalized within nursing leadership context. The findings reveal that traditional hierarchical leadership models are insufficient in a dynamic crisis environment like the pandemic. Instead, CLT’s framework which encompasses adaptive, administrative, and enabling leadership facilitates innovation, resilience, and effective interprofessional collaboration. Nurse leaders employing these strategies are better positioned to manage resources limitation, foster shared decision-making, and implement technological advancements in rapidly changing healthcare settings. Overall, this study underscores the potential of complexity leadership theory to transform nursing leadership practices by promoting continuous learning and empowerment, thereby enhancing crisis response and preparedness for future pandemics.
Systematic Review
Open Access May 20, 2025

Periprosthetic Joint Infections in Total Hip Arthroplasty: Diagnostic Advances, Treatment Algorithms, and Technological Innovations — A Comprehensive Review

Abstract Objective: This integrative review aims to critically examine the clinical management of periprosthetic joint infections (PJI) in total hip arthroplasty (THA), emphasizing decision-making strategies, diagnostic advancements, and therapeutic innovations. The study focuses on the complexity of infection control, microbial resistance, and individualized treatment planning. Methods: [...] Read more.
Objective: This integrative review aims to critically examine the clinical management of periprosthetic joint infections (PJI) in total hip arthroplasty (THA), emphasizing decision-making strategies, diagnostic advancements, and therapeutic innovations. The study focuses on the complexity of infection control, microbial resistance, and individualized treatment planning. Methods: A systematic review of the literature was conducted using PubMed, Scopus, Web of Science, and Google Scholar, targeting studies published between 2015 and 2025. Articles were selected based on their contribution to understanding the clinical, microbiological, and surgical aspects of PJI in THA. Fifty-five studies met the inclusion criteria and were analyzed descriptively. Results: PJI in THA is influenced by multifactorial risk profiles, including obesity, diabetes, and immunosuppression. Staphylococcus aureus, particularly MRSA, remains the most frequently isolated pathogen, followed by Gram-negative organisms and fungal species. Diagnostic innovations such as next-generation sequencing have enhanced pathogen detection, while two-stage revision remains the gold standard for chronic infections. Emerging strategies—such as antimicrobial coatings, tailored antibiotic protocols, and multidisciplinary care models—demonstrate promise in improving clinical outcomes. Conclusion: Managing PJI in THA necessitates a comprehensive and individualized approach, integrating early and accurate diagnosis, pathogen-specific treatment, and advanced preventive measures. The integration of emerging technologies and personalized care pathways is critical to optimizing outcomes and reducing the clinical and economic burden of PJI.
Review Article
Open Access May 05, 2025

Persistent Social Welfare Needs Among Educated Caribbean Black Individuals: Evidence of Minorities' Diminished Returns

Abstract Background: Educational attainment is strongly linked to increased employment opportunities, higher income, and greater financial security, making its inverse relationship with reliance on social welfare programs well-documented. However, consistent with the Minorities' Diminished Returns (MDRs) theory, the protective effects of education may be weaker for racial and ethnic minority [...] Read more.
Background: Educational attainment is strongly linked to increased employment opportunities, higher income, and greater financial security, making its inverse relationship with reliance on social welfare programs well-documented. However, consistent with the Minorities' Diminished Returns (MDRs) theory, the protective effects of education may be weaker for racial and ethnic minority groups compared to non-Latino Whites. This study examines whether the impact of educational attainment (measured as years of schooling) on social welfare use differs between Caribbean Black and White adults in the United States, focusing on outcomes since age 18 and in the past year. Objective: To investigate the relationship between years of schooling and the likelihood of using social welfare programs, while exploring whether this association varies between Caribbean Black and White adults, in alignment with the MDRs framework. Methods: Data were derived from the National Survey of American Life (NSAL), a nationally representative dataset with a robust sample of Black and White adults in the United States. The study focused on Caribbean Black and White participants aged 18 and older. Structural equation modeling (SEM) was employed to examine the relationship between years of schooling and social welfare use, adjusting for covariates including age, gender, employment status, and marital status. Interaction terms were used to assess potential differences in the returns of education across racial groups. Results: Higher educational attainment was associated with reduced likelihood of using social welfare programs overall. However, consistent with the MDRs framework, the protective effect of education was weaker for Caribbean Black individuals compared to their White counterparts. Caribbean Blacks with similar levels of education as Whites were more likely to report using social welfare programs since age 18 and in the past year, highlighting diminished returns on education for this population. Conclusion: This study extends the MDRs framework to Caribbean Black populations, a group rarely studied in the U.S., revealing significant disparities in the economic benefits of education. The findings underscore the need for policies that address systemic barriers limiting the economic returns of education for racial and ethnic minorities, including Caribbean Blacks, to promote greater equity in social and economic outcomes.
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Article
Open Access May 05, 2025

Educated Yet Unhealthy? Diminished Returns of Education for Immigrants in the USA

Abstract Background: Minorities’ Diminished Returns (MDRs) theory posits that the health benefits of socioeconomic resources, such as education, are smaller for marginalized and minoritized populations, including immigrants. While MDRs have been extensively documented for racial and ethnic minorities, less is known about whether these diminished returns extend to immigrant populations. This study [...] Read more.
Background: Minorities’ Diminished Returns (MDRs) theory posits that the health benefits of socioeconomic resources, such as education, are smaller for marginalized and minoritized populations, including immigrants. While MDRs have been extensively documented for racial and ethnic minorities, less is known about whether these diminished returns extend to immigrant populations. This study tested MDRs of education on various health and cognitive outcomes, including self-rated health (SRH), cognitive function, numeracy, number of chronic medical conditions, and limitations in activities of daily living (ADLs) among immigrants compared to non-immigrants in the United States. Objective. To examine whether educational attainment confers weaker protective effects on SRH, cognitive function, numeracy, chronic medical conditions, and ADLs in immigrants compared to non-immigrants, confirming the presence of MDRs across these domains. Methods: We used data from the Understanding America Study (UAS), a nationally representative survey of U.S. adults. We tested the association between educational attainment and five outcomes—SRH, cognitive function, numeracy, number of chronic medical conditions, and limitations in ADLs—across immigrant and non-immigrant groups. Multivariate regression models were employed, adjusting for key sociodemographic covariates. Results: The protective effects of education on a range of health outcomes were significantly weaker for immigrants compared to non-immigrants. Education level showed weaker associations with SRH, cognitive function, numeracy, number of chronic conditions, and ADLs among immigrants. These findings suggest that even at higher levels of educational attainment, immigrants experience poorer health and cognitive functioning than their U.S.-born counterparts. Conclusion: This study offers strong evidence for the MDRs of education on multiple health outcomes among U.S. immigrants. One possible explanation is that, despite achieving higher levels of education, immigrants often face structural barriers—such as discrimination, limited access to resources, and economic inequities—that constrain the health-related benefits typically associated with educational attainment. Additionally, a portion of immigrant education may be acquired outside the United States, where credentials may not be fully recognized or rewarded within the U.S. labor market. These findings highlight the importance of policies aimed at addressing systemic inequities and improving access to healthcare, employment opportunities, and social support for immigrant communities. Future research should further explore the mechanisms underlying these diminished returns and identify policy solutions to reduce their impact. Keywords: Educational Attainment, Immigrants, Nativity, Self-Rated Health, Chronic Disease, Activities of Daily Living (ADL), Cognitive Function
Original Article
Open Access May 04, 2025

Educational Attainment Better Protects Non-Latino than Latino People Against Diabetes Mellitus

Abstract Background: High educational attainment is a well-recognized protective factor against health problems such as diabetes. However, the theory of Minorities' Diminished Returns (MDRs) suggests that this protective effect is weaker for ethnic minorities compared to non-Latino Whites. This diminished effect is thought to result from structural inequalities, such as lower-quality [...] Read more.
Background: High educational attainment is a well-recognized protective factor against health problems such as diabetes. However, the theory of Minorities' Diminished Returns (MDRs) suggests that this protective effect is weaker for ethnic minorities compared to non-Latino Whites. This diminished effect is thought to result from structural inequalities, such as lower-quality education and fewer occupational opportunities, faced by ethnic minorities. Objective: This study examined the protective effect of years of schooling—used as a proxy for educational attainment—on diabetes mellitus (DM), overall and by ethnicity. Based on the MDRs framework, we hypothesized that the protective effect of education would be weaker for Latino individuals compared to non-Latinos. Methods: Data were drawn from the 2012 wave of the Understanding America Study (UAS), a nationally representative, internet-based panel. The outcome of interest was self-reported doctor diagnosis of DM. Logistic regression models were used to assess the association between educational attainment and DM, with an interaction term to explore differences between Latino and non-Latino individuals. Models were adjusted for age, sex, employment, immigration status, and marital status. Findings were presented as adjusted odds ratios (OR), p-values, and 95% confidence intervals (CIs). Results: Higher educational attainment was associated with lower odds of DM in both Latino and non-Latino individuals (p < 0.001). An interaction between education and ethnicity (p < 0.05) indicated that the protective effect of education was weaker for Latino individuals compared to non-Latinos. Conclusion: The findings align with the MDRs framework, which suggests that the health benefits of education are not equally distributed across ethnic groups. For Latino individuals, structural barriers such as lower educational quality and labor market discrimination may limit the protective effect of education against DM. While education is a key determinant of health, its unequal returns contribute to ethnic health disparities. Policymakers must address structural inequalities in education and employment that disproportionately affect ethnic minorities. Tackling these disparities through multi-sector policy interventions will require bipartisan political support.
Article
Open Access April 03, 2025

Depression, Subjective Health, Obesity, and Multimorbidity are Associated with Epigenetic Age Acceleration

Abstract Background: Epigenetic aging, measured through various DNA methylation-based clocks, may have implications for predicting disease risk. However, the sensitivity of different epigenetic clocks that have emerged as biomarkers for biological aging and in predicting physical and mental health outcomes remains uncertain. This study examines the age and sex-adjusted associations between [...] Read more.
Background: Epigenetic aging, measured through various DNA methylation-based clocks, may have implications for predicting disease risk. However, the sensitivity of different epigenetic clocks that have emerged as biomarkers for biological aging and in predicting physical and mental health outcomes remains uncertain. This study examines the age and sex-adjusted associations between multiple epigenetic age acceleration measures and three key health indicators, including self-rated health, depressive symptoms, and body mass index (BMI), in a nationally representative sample of U.S. middle-aged and older adults. Methods: We analyzed data from 4,018 adults in the 2016 wave of the Health and Retirement Study (HRS), which included several epigenetic age acceleration measures: HORVATH, HANNUM, LEVINE, HORVATHSKIN, LIN, WEIDNER, VIDALBRALO, YANG, ZHANG, BOCKLANDT, GARAGNANI, and GRIMAGE. Linear regression models were used to assess the associations between epigenetic age acceleration and self-rated health (poor health), depressive symptoms, and BMI, adjusting for age and sex. Results: We found significant positive associations between epigenetic age acceleration and worse self-rated health, higher depressive symptoms, and increased BMI. However, these associations varied across different epigenetic clocks, with some measures potentially having more consistent utility for specific health outcomes than others. Conclusion: Epigenetic age acceleration is linked to poorer self-rated health, greater depressive symptoms, and higher BMI, but choosing which epigenetic clock(s) to use is also important. These findings underscore the need to consider multiple epigenetic aging markers when assessing health risks and highlight the potential for particular clocks to serve as more sensitive indicators of physical and mental health outcomes.
Article
Open Access March 29, 2025

How Stigma Affects Patients Seeking Help for Drug Addiction

Abstract Stigma surrounding drug addiction remains a critical barrier to effective treatment, significantly influencing healthcare access, patient engagement, and recovery outcomes. This study explores the multifaceted impact of stigma on individuals seeking help for substance use disorders (SUDs), with a focus on healthcare-related discrimination, internalized stigma, and structural barriers. Research [...] Read more.
Stigma surrounding drug addiction remains a critical barrier to effective treatment, significantly influencing healthcare access, patient engagement, and recovery outcomes. This study explores the multifaceted impact of stigma on individuals seeking help for substance use disorders (SUDs), with a focus on healthcare-related discrimination, internalized stigma, and structural barriers. Research indicates that negative perceptions among healthcare providers contribute to delayed treatment-seeking behaviors, reduced adherence to medication-assisted treatment (MAT), and increased relapse rates. Additionally, patients internalizing these societal judgments experience heightened psychological distress, social isolation, and decreased self-efficacy, further hindering their recovery process. To address these challenges, evidence-based strategies such as addiction medicine education, trauma-informed care, harm reduction approaches, and peer support models have been shown to effectively reduce stigma and improve treatment outcomes. Hospital administrators and nursing leaders play a critical role in fostering a culture of empathy, advocating for the reframing of addiction as a neuro-psycho-biological disease rather than a moral failing. Future research should explore digital mental health interventions, motivational interviewing techniques, and interdisciplinary collaboration to further dismantle stigma and enhance the effectiveness of addiction treatment programs. This study highlights the urgent need for systemic policy changes, targeted educational programs, and a shift in clinical attitudes to create a more inclusive and stigma-free healthcare environment. Through implementing these approaches, healthcare providers can ensure equitable access to treatment and improve long-term health outcomes for individuals with opioid use disorder (OUD) and other substance-related conditions.
Essay
Open Access March 22, 2025

I Am My Peers: How Social Ties Influence E-Cigarette Attitudes, Policy Support, and Use

Abstract Background: Electronic cigarette (e-cigarette) use is increasingly prevalent among youth and young adults, particularly college and university students. This is a population for whom e-cigarette use is not recommended due to potential health risks, including nicotine addiction and long-term respiratory effects. Social networks play a crucial role in shaping attitudes toward [...] Read more.
Background: Electronic cigarette (e-cigarette) use is increasingly prevalent among youth and young adults, particularly college and university students. This is a population for whom e-cigarette use is not recommended due to potential health risks, including nicotine addiction and long-term respiratory effects. Social networks play a crucial role in shaping attitudes toward e-cigarettes and influencing use behaviors. However, the relative influence of different social ties—parents, siblings, and friends—on e-cigarette attitudes and use remains unclear. Objective: This study utilizes data from the SMOKES study to compare the influence of e-cigarette use within different social network sections—parents, friends, and siblings—on personal e-cigarette attitudes and use among college and university students. Methods: Using a cross-sectional survey of college and university students, we examined the associations between e-cigarette use within different social networks and individual e-cigarette attitudes and use. Multivariate regression models assessed the strength of these associations, adjusting for key demographic and behavioral covariates. Results: Findings indicate that among college and university students, the strongest influence on both e-cigarette attitudes and use comes from friends who use e-cigarettes. In contrast, parental and sibling e-cigarette use showed weak or non-significant effects. These results suggest that peer influence, rather than family influence, plays a dominant role in shaping e-cigarette-related behaviors and perceptions in young adults. Conclusion: This study underscores the importance of peer influence in e-cigarette uptake and attitudes among college and university students. Public health interventions aimed at reducing e-cigarette use in this population should consider targeting peer networks rather than focusing solely on family-based influences.
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Article
Open Access March 20, 2025

Weaker Effects of Parental Education on Oral Nicotine Use of High School Students in Rural Areas: Marginalization-Related Diminished Returns

Abstract Background: Nicotine pouches, gummies, and candies have emerged as popular alternatives to traditional tobacco products among U.S. adolescents. While parental educational attainment is generally associated with youth substance use, marginalization-related diminished returns (MDRs) suggest that this effect may be weaker in marginalized populations, including non-Latino White communities. In [...] Read more.
Background: Nicotine pouches, gummies, and candies have emerged as popular alternatives to traditional tobacco products among U.S. adolescents. While parental educational attainment is generally associated with youth substance use, marginalization-related diminished returns (MDRs) suggest that this effect may be weaker in marginalized populations, including non-Latino White communities. In particular, place-based marginalization—such as neighborhood economic disadvantage and school-level poverty—may attenuate the benefits of parental education. This study examines MDRs in the relationship between parental educational attainment and nicotine pouch/gummy/candy use among non-Latino White 12th graders in the 2024 Monitoring the Future (MTF) study. Methods: This study analyzed nationally representative data from the 2024 MTF study, focusing on non-Latino White 12th graders who reported parental education levels and adolescents’ use of nicotine pouch/gummy/candy. Structural equation modeling (SEM) was used to estimate the effects of parental education on adolescents’ use of nicotine pouches, gummies, and candies, while adjusting for demographic covariates. Place-based marginalization was operationalized using rural vs urban /suburban residence. Interaction terms tested whether the effect of parental education varied based on place of residence. Results: Higher parental educational attainment was associated with lower use of nicotine pouches, gummies, and candies. However, this effect was significantly weaker in rural areas. Conclusion: Public health interventions should account for place-based disparities rather than assuming a uniform effect of SES factors. This study highlights the need for policy responses that address structural inequities beyond individual family SES.
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Original Article
Open Access March 11, 2025

Why High Income Fails to Reduce E-Cigarette Use: The Knowledge-Attitude Paradox in the SMOKES Study

Abstract Background: Electronic cigarette (e-cigarette) use and vaping tobacco have increased rapidly worldwide, raising concerns about their health effects, social acceptability, and regulatory challenges. In many countries, e-cigarettes are more commonly used by individuals from higher socioeconomic status (SES) backgrounds, who, in theory, should have greater knowledge about e-cigarettes and [...] Read more.
Background: Electronic cigarette (e-cigarette) use and vaping tobacco have increased rapidly worldwide, raising concerns about their health effects, social acceptability, and regulatory challenges. In many countries, e-cigarettes are more commonly used by individuals from higher socioeconomic status (SES) backgrounds, who, in theory, should have greater knowledge about e-cigarettes and their associated risks. However, it remains unclear why a group with more knowledge about e-cigarette risks would also hold more positive attitudes toward vaping and exhibit higher usage rates — a phenomenon that may represent a knowledge-behavior paradox. Understanding this paradox, along with the complex relationships between e-cigarette knowledge, attitudes, and behaviors, is critical for informing effective public health interventions, campaigns, social media messaging, and regulatory policies. Objectives: This study aimed to evaluate the complex relationship between SES, e-cigarette knowledge, pro-vaping attitudes, and e-cigarette use. Methods: The SMOKES Study (Study of Measurement of Knowledge and Examination of Support for Tobacco Control Policies) used a multi-center, cross-sectional design, collecting data from 2,403 college and university students across 15 provinces in Iran (covering nearly half of the country's provinces). The survey measured family income, age, sex, ethnicity, e-cigarette use, knowledge, and attitudes. Structural Equation Modeling (SEM) was employed to examine the interrelations between SES, knowledge, attitudes, and behavior, while adjusting for age, sex, and ethnic minority status. Results: SEM analysis confirmed the hypothesized paradox. Although greater knowledge about e-cigarettes was linked to less favorable attitudes toward vaping and lower use, pro-vaping attitudes emerged as the strongest predictor of vaping behavior, while knowledge played a weaker protective role. Notably, individuals with higher SES simultaneously showed higher knowledge and, paradoxically, more pro-e-cigarette attitudes and greater usage. Female students and ethnic minority students reported higher correct knowledge and lower pro-vaping attitudes and use. Although age and higher family income were associated with more favorable attitudes, they did not directly predict vaping behavior. These results suggest that for higher SES individuals, poor knowledge is not the main driver of e-cigarette use; rather, their pro-e-cigarette attitudes, which seem to outweigh the influence of knowledge, play a key role. Conclusions: Although individuals from higher SES backgrounds report greater correct knowledge about e-cigarettes, this knowledge does not necessarily translate into reduced positive attitudes or lower usage. This study highlights the complexity of these paradoxical effects and suggests that public health strategies need to go beyond simple education and knowledge-based interventions. Targeted approaches should address industry messaging, challenge misconceptions, and strengthen regulatory efforts to reduce e-cigarette use among young adults, including those from higher SES backgrounds.
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Original Article
Open Access March 09, 2025

Place-Based Diminished Returns of Parental Education on Adolescents’ Inhalant Use in Rural Areas

Abstract Background Adolescent substance use is often influenced by socioeconomic and geographical factors. While higher parental education is typically associated with lower substance use, these protective effects may be weaker for marginalized groups facing structural disadvantages that limit the utility and returns of their economic and social resources. Rural areas, characterized by fewer [...] Read more.
Background Adolescent substance use is often influenced by socioeconomic and geographical factors. While higher parental education is typically associated with lower substance use, these protective effects may be weaker for marginalized groups facing structural disadvantages that limit the utility and returns of their economic and social resources. Rural areas, characterized by fewer employment opportunities and limited recreational activities, may contribute to marginalization-related diminished returns (MDRs) of parental education on adolescent substance use, including inhalant use. Objectives This study applies the MDRs framework to examine whether the protective effect of higher parental education on current inhalant use (past 30 days) among 12th-grade American adolescents varies by geographic location. Specifically, we assess whether youth from highly educated families in rural areas are at a disproportionate risk of inhalant use compared to their urban and suburban peers. Methods Using data from the 2024 Monitoring the Future (MTF) study, a nationally representative survey of 12th-grade adolescents in the U.S., we tested main effects and statistical interactions between parental education and residence (rural vs. urban/suburban) in predicting the odds of inhalant use over the past 30 days. Logistic regression models, both with and without interaction terms, were applied to evaluate whether the protective effects of parental education varied by residence location, controlling for relevant demographic and socioeconomic factors. Results Findings indicate a significant interaction between parental education and rural residence. While higher parental education was associated with lower odds of inhalant use in urban and suburban areas, this protective effect was substantially weaker in rural settings. Adolescents from highly educated families in rural areas exhibited a higher-than-expected risk of inhalant use, suggesting that geographic marginalization attenuates the benefits of parental socioeconomic resources. Conclusions These results highlight the role of place-based marginalization in shaping adolescent substance use disparities, demonstrating that MDRs extend beyond race and ethnicity to location-based disadvantages. Rural youths from highly educated families may face unique structural and social challenges that counteract the protective effects of parental education. Public health efforts should consider place-based interventions that address the economic, recreational, and social limitations of rural environments to reduce substance use risk among high-SES adolescents residing in rural areas.
Article
Open Access March 09, 2025

Hippocampus Functional Connectivity, Impulsivity, and Subsequent Substance Use

Abstract Background: The hippocampus plays a critical role in memory and decision-making processes, with its resting-state functional connectivity (rsFC) linked to various behavioral outcomes. This study investigates whether baseline brain-wide rsFC of the hippocampus mediates the relationship between impulsivity and subsequent substance use, specifically tobacco and marijuana use, in adolescents. [...] Read more.
Background: The hippocampus plays a critical role in memory and decision-making processes, with its resting-state functional connectivity (rsFC) linked to various behavioral outcomes. This study investigates whether baseline brain-wide rsFC of the hippocampus mediates the relationship between impulsivity and subsequent substance use, specifically tobacco and marijuana use, in adolescents. Methods: Data were drawn from the baseline wave of the Adolescent Brain Cognitive Development (ABCD) study. Resting-state fMRI data were used to evaluate the functional connectivity of the hippocampus with key brain networks, including the cingulo-parietal network, visual network, sensory-motor network, and default mode network (DMN). Impulsivity was assessed using validated self-report measures, and substance use (tobacco and marijuana) was evaluated at follow-up. Mediation models were conducted to examine the extent to which hippocampal rsFC explains the association between impulsivity and substance use. Results: Baseline hippocampal rsFC with the cingulo-parietal network, visual network, sensory-motor network, and DMN showed marginal associations with future tobacco and marijuana use. Additionally, hippocampal rsFC was significantly associated with impulsivity, which, in turn, predicted higher substance use at follow-up. These findings suggest that hippocampal rsFC partially mediates the relationship between impulsivity and substance use behaviors. Conclusions: Hippocampal functional connectivity with brain networks may influence the pathway from impulsivity to future substance use in adolescence. These findings emphasize the importance of hippocampal connectivity in understanding the neural mechanisms underlying risk behaviors and may inform the development of targeted interventions to reduce substance use in this vulnerable population.
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Article
Open Access February 25, 2025

Nucleus Accumbens Resting State Functional Connectivity is Linked to Family Income, Reward Salience, and Substance Use

Abstract Background: As a central component of the brain's reward system, nucleus accumbens (NAcc) plays a crucial role in reward salience and substance use behaviors. Changes in the NAcc are also relevant to higher rates of substance use of youth and adults from low-income backgrounds. Although resting-state functional connectivity (rsFC) of the NAcc provides valuable insights into the neural [...] Read more.
Background: As a central component of the brain's reward system, nucleus accumbens (NAcc) plays a crucial role in reward salience and substance use behaviors. Changes in the NAcc are also relevant to higher rates of substance use of youth and adults from low-income backgrounds. Although resting-state functional connectivity (rsFC) of the NAcc provides valuable insights into the neural mechanisms underlying reward processing and the propensity for self-reported reward salience and substance use, research exploring the association between NAcc rsFC and brain networks beyond the default mode network (DMN) and prefrontal cortex (PFC) is limited. Objective: To investigate the role of the resting-state functional connectivity of the NAcc with the cingulo-opercular network, sensorimotor mouth network, and sensorimotor hand network in the association between socioeconomic status, self-reported reward salience, and future substance use. Methods: Data were obtained from the Adolescent Brain Cognitive Development (ABCD) study. NAcc rsFC with the cingulo-opercular network, sensorimotor mouth network, and sensorimotor hand network was assessed at baseline. Socioeconomic status was measured using family income. Self-reported reward salience was assessed using validated psychometric scales. Substance use outcomes were tracked longitudinally over the study period. Structural Equation Modeling was employed to examine the covariances between family income, NAcc rsFC, reward salience, and subsequent substance use. Results: Higher baseline family income was positively associated with baseline NAcc rsFC (B = 0.092, p < 0.001) and negatively associated with baseline reward salience (B = -0.040, p = 0.036) and future substance use (B = -0.081, p < 0.001). Baseline NAcc rsFC was strongly and positively associated with reward salience (B = 0.734, p < 0.001) and future substance use up to age 13 (B = 0.124, p < 0.001). Additionally, baseline reward salience was positively associated with future substance use (Covariance = 0.176, p < 0.001). Conclusion: The findings suggest that NAcc rsFC with brain networks beyond the DMN or PFC may contribute to the links between low parental socioeconomic status, reward salience, and substance use risk. Expanding the understanding of NAcc rsFC provides new insights into the neural mechanisms underlying these associations. These results have important implications for developing targeted interventions aimed at preventing substance use, particularly among low-income youth with heightened reward salience. Further research is needed to explore causal pathways and moderating factors influencing these relationships.
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Article
Open Access February 25, 2025

Resting-State Functional Connectivity Between the Cingulo-Opercular and Default Mode Networks May Explain Socioeconomic Inequalities in Cognitive Development

Abstract Background: The Cingulo-Opercular Network (CON) is a crucial executive control network involved in regulating actions and facilitating higher-order cognitive processes. Resting-state functional connectivity between the CON and the Default Mode Network (DMN) plays a vital role in cognitive regulation, enabling the transition between internally focused and externally directed tasks. This [...] Read more.
Background: The Cingulo-Opercular Network (CON) is a crucial executive control network involved in regulating actions and facilitating higher-order cognitive processes. Resting-state functional connectivity between the CON and the Default Mode Network (DMN) plays a vital role in cognitive regulation, enabling the transition between internally focused and externally directed tasks. This study investigates whether resting-state functional connectivity between the CON and DMN mediates the effects of social determinants, such as educational opportunities and family structure, on cognitive outcomes in youth. Aims: This study aims to explore how CON-DMN connectivity influences the relationship between social gradients and cognition in youth. Specifically, it examines whether resting-state functional connectivity between these networks mediates the effects of educational opportunities and family structure on cognitive outcomes and seeks to uncover the neural mechanisms underlying these social gradients. Methods: Data were derived from the Adolescent Brain Cognitive Development (ABCD) study, a large longitudinal dataset of over 11,000 children aged 9–10 years. Cognitive outcomes were assessed using standardized NIH toolbox measures: Total Composite, Fluid Reasoning, Picture Vocabulary, Pattern Recognition, and Card Sorting. Social determinants were operationalized using indicators such as parental education, family composition, and neighborhood educational opportunities (COI). Resting-state functional connectivity (rsFC) between the CON and DMN was measured using functional magnetic resonance imaging (fMRI). Structural equation modeling (SEM) was employed to test whether CON-DMN rsFC mediated the relationship between social determinants and cognitive outcomes, adjusting for potential confounders such as age, sex, and race/ethnicity. Results: Stable family structure and greater educational opportunities were significantly associated with improved cognitive performance. These relationships were mediated by reduced functional connectivity between the CON and DMN. Conclusion: Reduced functional connectivity between the CON and DMN serves as a neural mechanism linking social gradients, such as educational opportunities and family structure, to better cognitive outcomes in youth.
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Article
Open Access February 19, 2025

The CEASE Tobacco Cessation Controlled Trial for Low-Income Racial and Ethnic Minority Participants: Key Predictors of Success

Abstract Background: Tobacco use remains disproportionately high among low-income and racial-ethnic minority populations. The CEASE program, with its self-help, hybrid/online, and in-person modalities, has demonstrated efficacy in promoting tobacco cessation. However, predictors of successful cessation among participants in these groups remain unclear. Objective: To identify baseline predictors of successful tobacco cessation among low-income and racial-ethnic minority participants in the CEASE program, with a focus on demographic, socioeconomic, behavioral, and psychosocial factors. Methods: Participants were allocated into three intervention arms: self-help, CEASE hybrid/online, and CEASE in-person. Baseline characteristics, including demographics (e.g., age, gender), socioeconomic status (e.g., education, employment), substance use profiles (e.g., cigarette packs per week, use of other tobacco products, menthol tobacco use), physical health (e.g., general health, number of cardiometabolic risk conditions), mental health (e.g., depressive symptoms, perceived stress), perceived social support, and nicotine dependence, were analyzed as potential predictors of cessation success. Multivariable logistic regression models were used to identify factors associated with successful quitting, controlling for the study arm. Results: In addition to the study arm, gender, baseline depression, cardiometabolic conditions, tobacco flavor, and the use of other tobacco products were significant predictors of quit success. Individuals receiving in-person interventions had significantly higher odds of quitting (AOR = 3.79, p < 0.05). Women were significantly less likely to quit compared to men (AOR = 0.24, p < 0.01). Participants with a greater number of cardiometabolic risk conditions were more likely to quit (AOR = 1.93, p < 0.05), while those with higher levels of depression had lower odds of quitting (AOR = 0.61, p < 0.05). Menthol tobacco users were also less likely to quit (AOR = 0.10, p < 0.05). Interestingly, individuals who used other forms of tobacco in addition to cigarettes had increased odds of quitting (AOR = 2.86, p [...] Read more.
Background: Tobacco use remains disproportionately high among low-income and racial-ethnic minority populations. The CEASE program, with its self-help, hybrid/online, and in-person modalities, has demonstrated efficacy in promoting tobacco cessation. However, predictors of successful cessation among participants in these groups remain unclear. Objective: To identify baseline predictors of successful tobacco cessation among low-income and racial-ethnic minority participants in the CEASE program, with a focus on demographic, socioeconomic, behavioral, and psychosocial factors. Methods: Participants were allocated into three intervention arms: self-help, CEASE hybrid/online, and CEASE in-person. Baseline characteristics, including demographics (e.g., age, gender), socioeconomic status (e.g., education, employment), substance use profiles (e.g., cigarette packs per week, use of other tobacco products, menthol tobacco use), physical health (e.g., general health, number of cardiometabolic risk conditions), mental health (e.g., depressive symptoms, perceived stress), perceived social support, and nicotine dependence, were analyzed as potential predictors of cessation success. Multivariable logistic regression models were used to identify factors associated with successful quitting, controlling for the study arm. Results: In addition to the study arm, gender, baseline depression, cardiometabolic conditions, tobacco flavor, and the use of other tobacco products were significant predictors of quit success. Individuals receiving in-person interventions had significantly higher odds of quitting (AOR = 3.79, p < 0.05). Women were significantly less likely to quit compared to men (AOR = 0.24, p < 0.01). Participants with a greater number of cardiometabolic risk conditions were more likely to quit (AOR = 1.93, p < 0.05), while those with higher levels of depression had lower odds of quitting (AOR = 0.61, p < 0.05). Menthol tobacco users were also less likely to quit (AOR = 0.10, p < 0.05). Interestingly, individuals who used other forms of tobacco in addition to cigarettes had increased odds of quitting (AOR = 2.86, p < 0.05). No other factors, including demographic variables (e.g., age), socioeconomic status (e.g., education, marital status), substance use profiles (e.g., cigarette packs per week, NRT use), or nicotine dependence, were significant predictors of cessation success. Conclusion: Baseline self-reported anxiety/depression and depressive symptoms play a critical role in reducing the likelihood of successful tobacco cessation among low-income and racial-ethnic minority participants in the CEASE program. These findings underscore the importance of addressing mental health challenges as part of tobacco cessation interventions to enhance their efficacy. Future research should explore targeted strategies for integrating mental health support into cessation programs to improve outcomes for underserved populations.
Article
Open Access February 17, 2025

Gender Differences in the Association Between Socioeconomic Status and Cardiometabolic Health: National Health and Nutrition Examination Survey

Abstract Background: Socioeconomic status (SES) is a well-established determinant of health, often associated with lower risk of cardiometabolic diseases (CMD). However, the extent to which SES influences CMD may vary by gender due to differences in social roles, health behaviors, and biological susceptibilities. This study examined the relationship between SES, measured by the [...] Read more.
Background: Socioeconomic status (SES) is a well-established determinant of health, often associated with lower risk of cardiometabolic diseases (CMD). However, the extent to which SES influences CMD may vary by gender due to differences in social roles, health behaviors, and biological susceptibilities. This study examined the relationship between SES, measured by the poverty-to-income ratio (PIR), and CMD indicators—including obesity, diabetes, and cardiovascular disease (CVD)—among men and women using data from the National Health and Nutrition Examination Survey (NHANES). Methods: This cross-sectional study utilized NHANES data (1999-2018), adjusting for race/ethnicity and age. SES was operationalized using PIR, with CMD outcomes (obesity, diabetes, and CVD) as dependent variables. Generalized linear models (GLM) were employed to evaluate the main effects of SES on CMD, with gender included as a moderator. Results: Higher SES was associated with lower overall CMD risk. However, the protective effects of SES were more pronounced in women than in men for all outcomes. These findings suggest that gender-specific pathways may mediate the relationship between SES and CMD. Women may derive greater health benefits from higher SES due to factors such as reduced stress exposure, healthier behaviors, and increased healthcare utilization. Conversely, the weaker association observed in men may reflect differences in social hierarchy sensitivity, responses to unemployment, or other contextual factors. Conclusion: The findings highlight the importance of gender-specific considerations when addressing SES-related disparities in CMD outcomes. Policies and interventions aimed at reducing CMD burden should account for these gender differences to promote equitable improvements in cardiometabolic health. Further research is needed to unravel the mechanisms driving these differences and to inform targeted strategies.
Article
Open Access February 16, 2025

Uneven Impact of Maternal Education at Birth on High School Grades of Black and White Students

Abstract Background: The Minorities' Diminished Returns (MDRs) theory posits that social determinants of health, such as parental education, exert weaker protective effects on health and educational outcomes in racialized and minoritized populations compared to White populations. Aim: This study examines whether higher maternal education is associated with better high school GPA in Black [...] Read more.
Background: The Minorities' Diminished Returns (MDRs) theory posits that social determinants of health, such as parental education, exert weaker protective effects on health and educational outcomes in racialized and minoritized populations compared to White populations. Aim: This study examines whether higher maternal education is associated with better high school GPA in Black youth and whether this association aligns with the MDRs framework. Methods: Data were drawn from the Future of Families and Child Wellbeing Study also known as Fragile Families and Child Wellbeing Study (FFCWS) baseline and 22nd year follow-up (1990-2022). This study included 1873 Black or White participants who were followed from birth to age 22. Linear regression models were used to assess the association between maternal education and high school GPA, adjusting for sociodemographic covariates. Analyses focused on the differential effects of maternal education across racial groups, particularly among Black youth. Results: While maternal education was positively associated with high school GPA, this effect was weaker for Black students compared to their White counterparts. Specifically, each additional year of maternal education corresponded to a lower GPA increase in Black students, consistent with the MDRs hypothesis. Conclusion: Findings support the MDRs theory, indicating that maternal education has a reduced protective effect on high school GPA among Black youth. These results underscore the need for policies that address structural factors beyond education to promote equitable academic achievement.
Article
Open Access February 14, 2025

Trauma Erodes Financial Returns of Educational Attainment

Abstract Background: Educational attainment is often regarded as a pathway to economic stability and social mobility. However, the Minorities’ Diminished Returns (MDRs) framework has demonstrated that the effects of educational attainment on various economic, behavioral, and health outcomes are weaker for marginalized populations, including racial/ethnic minorities, immigrants, LGBTQ+ individuals, [...] Read more.
Background: Educational attainment is often regarded as a pathway to economic stability and social mobility. However, the Minorities’ Diminished Returns (MDRs) framework has demonstrated that the effects of educational attainment on various economic, behavioral, and health outcomes are weaker for marginalized populations, including racial/ethnic minorities, immigrants, LGBTQ+ individuals, and those living in disadvantaged areas. While MDRs have been documented for various marginalized demographic groups, the role of trauma in moderating socioeconomic outcomes remains underexplored. Objective: This study examines whether lifetime trauma exposure diminishes the positive association between educational attainment and poverty-to-income ratio (PIR), a key indicator of economic well-being. Methods: Using data from the National Survey of American Life (NSAL), we analyzed a nationally representative sample of 6,008 adults, including Black, White, Latino, and Other racial/ethnic groups. We employed linear regression models to evaluate the association between the independent variable educational attainment and the outcome PIR. We then tested lifetime trauma as a moderator of this association. Models controlled for age, gender, employment, and race/ethnicity. Results: Educational attainment was positively associated with PIR across all groups, but the strength of this association was significantly attenuated for individuals with a history of lifetime trauma. These effects were independent of covariates. Conclusions: These findings extend the MDRs framework by highlighting trauma as a potential contributor to diminished returns of education on socioeconomic wellbeing. Structural inequities that increase trauma exposure in minoritized populations may also limit the economic benefits of education, particularly for groups with multiple trauma exposures. Policies aimed at addressing economic inequality must integrate social policies that reduce trauma and stress.
Article
Open Access February 13, 2025

Psychosocial Correlates of Childhood Body Mass Index: Racial and Ethnic Differences

Abstract Objective: To examine racial/ethnic differences in the associations of family socioeconomic status (SES), neighborhood SES, and inhibitory control with body mass index (BMI) in 9-10-year-old children using data from the Adolescent Brain Cognitive Development (ABCD) study. Methods: This cross-sectional study included a diverse sample of children aged 9-10 years, representing [...] Read more.
Objective: To examine racial/ethnic differences in the associations of family socioeconomic status (SES), neighborhood SES, and inhibitory control with body mass index (BMI) in 9-10-year-old children using data from the Adolescent Brain Cognitive Development (ABCD) study. Methods: This cross-sectional study included a diverse sample of children aged 9-10 years, representing non-Latino White, Black, Latino, Asian, and Other racial/ethnic groups. BMI was the primary outcome. Key predictors were family SES, neighborhood SES, and inhibitory control. Multivariable regression models were stratified by race/ethnicity to identify group-specific associations. Results: Race/ethnic groups differed in psychosocial correlates of childhood BMI at age 9 and 10. Among non-Latino White children, higher family income (B = -0.086, p < 0.001), higher parental education (B = -0.069, p < 0.001), and living in a married household (B = -0.079, p < 0.001) were associated with lower BMI. Additionally, the presence of healthy food options in the zip code (B = -0.030, p = 0.032) was linked to lower BMI, while lack of planning (B = 0.032, p = 0.030) was associated with higher BMI. For non-Latino Black children, positive urgency (B = -0.068, p = 0.022) was negatively associated with BMI, while other factors such as family SES and neighborhood SES did not show significant associations. For Latino children, higher family income (B = -0.093, p = 0.001) and parental education (B = -0.099, p < 0.001) were associated with lower BMI. In this group, male gender (B = 0.043, p = 0.033) was associated with higher BMI. Among Asian children, higher family income (B = -0.199, p = 0.006) and parental education (B = -0.144, p = 0.037) were significantly associated with lower BMI. For children in the "Other" racial/ethnic category, higher family income (B = -0.101, p = 0.023), living in a married household (B = -0.076, p = 0.026), and higher median income in the zip code (B = -0.083, p = 0.013) were associated with lower BMI. In this group, male children had lower BMI compared to females (B = -0.089, p = 0.001). Conclusion: The findings highlight substantial racial/ethnic differences in the psychosocial and socioeconomic correlates of BMI in children. There is a need for tailored interventions that target social determinants of childhood high BMI. One size does not fit all.
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Open Access February 12, 2025

Unequal Benefits: How Parental Education Falls Short for Black and Latino Youth

Abstract Background: Parental education is a key determinant of academic performance, yet its protective effects may differ by race and ethnicity. The concept of Minorities’ Diminished Returns (MDRs) highlights the weaker association between socioeconomic resources and outcomes for marginalized populations, including Black and Latino youth. Objective: To investigate whether the [...] Read more.
Background: Parental education is a key determinant of academic performance, yet its protective effects may differ by race and ethnicity. The concept of Minorities’ Diminished Returns (MDRs) highlights the weaker association between socioeconomic resources and outcomes for marginalized populations, including Black and Latino youth. Objective: To investigate whether the positive association between parental education and school performance (letter grades) is weaker for Black and Latino youth compared to non-Latino White youth. Methods: Data were drawn from the Monitoring the Future (MTF) 2023 study. The sample included Black, Latino, and non-Latino White youth. The outcome was a nine-level continuous measure of academic performance based on self-reported letter grades, with higher scores indicating better performance. Multivariate regression models tested interactions between parental education and race/ethnicity in predicting grades, adjusting for confounders such as family income, gender, and school characteristics. Results: A total number of 7584 12th graders entered the study. Parental education was positively associated with school performance across all groups, but the magnitude of this association was significantly smaller for Black and Latino youth compared to non-Latino White youth. Even after controlling for socioeconomic and contextual factors, the racial and ethnic differences in the strength of this association persisted. Conclusions: Our findings provide evidence of Minorities’ Diminished Returns (MDRs) in the academic domain, with Black and Latino youth experiencing weaker benefits of parental education on school performance. These disparities suggest that structural barriers and systemic inequities undermine the translation of parental educational attainment into academic success for marginalized groups. Policy interventions must address these structural barriers to promote equity in educational outcomes.
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Open Access February 11, 2025

Childhood Depression, Hopelessness, and Suicidal Attempt Predict Earlier Tobacco and Marijuana Use Initiation During Adolescence

Abstract Background: Emotional problems have been associated with substance use, yet longitudinal research examining this relationship during childhood and adolescence in large, diverse, community-based samples remains limited. Aims: This study investigates the prospective associations between three emotional problems—hopelessness, depression, and suicide attempts—before ages 9–10 and [...] Read more.
Background: Emotional problems have been associated with substance use, yet longitudinal research examining this relationship during childhood and adolescence in large, diverse, community-based samples remains limited. Aims: This study investigates the prospective associations between three emotional problems—hopelessness, depression, and suicide attempts—before ages 9–10 and the subsequent initiation of tobacco and marijuana use before ages 14–15, using data from the Adolescent Brain Cognitive Development (ABCD) study. Methods: Data from the ABCD study were analyzed. Baseline emotional problems, including hopelessness, depression, and suicide attempts, were assessed at ages 9–10 through structured parent interviews. Substance use outcomes (tobacco and marijuana initiation) were tracked from baseline to follow-up at ages 14–15 using structured self-report measures. Structural Equation Modeling (SEM) was employed to assess the predictive roles of these early-life emotional problems, controlling for potential confounders such as demographic factors and family and neighborhood socioeconomic status. Results: Baseline hopelessness, depression, and suicide attempts at ages 9–10 were significant predictors of tobacco and marijuana use initiation at ages 14–15. These associations remained robust after adjusting for confounders, indicating the independent effects of early emotional problems on adolescent substance use initiation. Conclusions: Emotional problems in early childhood, including hopelessness, depression, and suicidal behavior, are critical predictors of substance use initiation during adolescence. These findings underscore the importance of early identification and targeted mental health interventions to reduce the risk of substance use among vulnerable youth.
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Open Access January 10, 2025

Extreme Heat Exposure is Associated with Lower Learning, General Cognitive Ability, and Memory among US Children

Abstract Background: The increasing frequency and intensity of extreme heat exposure is a significant consequence of climate change, with broad public health implications. While many health risks associated with heat exposure are well-documented, less research has focused on its impact on children’s cognitive function. Objectives: This study examines the [...] Read more.
Background: The increasing frequency and intensity of extreme heat exposure is a significant consequence of climate change, with broad public health implications. While many health risks associated with heat exposure are well-documented, less research has focused on its impact on children’s cognitive function. Objectives: This study examines the relationship between extreme heat exposure and various domains of cognitive function in children. Methods: Data were drawn from the Adolescent Brain Cognitive Development (ABCD) study. Key variables included race/ethnicity, age, gender, family socioeconomic status (SES), heatwave exposure, and multiple cognitive domains: total composite score, fluid composite score, crystallized intelligence, reading ability, picture vocabulary, pattern recognition, card sorting, and list recall. Structural equation modeling (SEM) was used for data analysis. Results: A total of 11,878 children were included in the analysis. Findings revealed significant associations between extreme heat exposure and lower cognitive performance across multiple domains. The strongest adjusted effects were observed in pattern recognition (B = −0.064, p < 0.001) and reading ability (B = −0.050, p < 0.001), both within the learning domain, as well as total composite cognitive ability (B = −0.067, p < 0.001), fluid composite (B = −0.053, p < 0.001), and crystallized intelligence (B = −0.061, p < 0.001), all within general cognitive ability. Weaker but still significant associations were found for list recall (B = −0.025, p = 0.006) and card sorting (B = −0.043, p < 0.001) within the memory domain, as well as picture vocabulary (B = −0.025, p = 0.008) within general cognitive ability. These associations remained significant after controlling for demographic factors, race/ethnicity, family SES, and neighborhood SES. Conclusions: This study underscores the impact of climate change on cognitive function disparities, particularly in learning and general cognitive ability among children exposed to extreme heat. Findings highlight the need for targeted interventions to mitigate the cognitive risks associated with heat exposure in vulnerable populations.
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Open Access February 10, 2025

Higher-than Expected Social Security Reliance Among Educated Black Americans: Minorities' Diminished Returns in National Health Interview Survey (NHIS) 2023

Abstract Background: While educational attainment is generally associated with reduced reliance on Social Security and disability benefits, Minorities' Diminished Returns (MDRs) theory suggests that the socioeconomic benefits of educational attainment are not equally distributed across racial groups and are weaker for minoritized populations. This study explores the association between educational [...] Read more.
Background: While educational attainment is generally associated with reduced reliance on Social Security and disability benefits, Minorities' Diminished Returns (MDRs) theory suggests that the socioeconomic benefits of educational attainment are not equally distributed across racial groups and are weaker for minoritized populations. This study explores the association between educational attainment and reliance on Social Security and disability benefits among Black and White adults in the United States. Objective: Building on the MDRs framework, we analyzed data from the National Health Interview Survey (NHIS) 2023 to examine how educational attainment impacts reliance on Social Security disability income, disability benefits, and public assistance for Black and White adults. Methods: We used a nationally representative sample of Black and White adults from the NHIS 2023 dataset. The outcomes assessed were reliance on three income sources: (1) Social Security disability income, (2) disability benefit income, and (3) public assistance disability income. Educational attainment was classified into three levels: less than high school (reference), high school diploma to some college, and college graduate or more. Logistic regression models assessed the relationship between educational attainment and reliance on each income source, with separate analyses for Black and White adults to evaluate differential effects. Results: Higher levels of educational attainment (high school diploma to some college and college graduate or more) were associated with lower odds of relying on Social Security disability, disability benefits, and public assistance. However, the protective effects of educational attainment were notably stronger for White adults than for Black adults. Among Black adults, even high educational attainment showed limited effectiveness in reducing reliance on these income sources, underscoring the Minorities' Diminished Returns (MDRs) phenomenon. Conclusions: Although educational attainment reduces reliance on Social Security and disability-related income sources, these protective effects are less pronounced for Black adults compared to White adults. The findings reveal persistent racial disparities in the economic returns of education, suggesting that structural factors may undermine the socioeconomic and health benefits of educational achievement for Black Americans. Targeted policy interventions may be needed to improve economic stability for Black adults, including those with higher educational credentials.
Article
Open Access February 10, 2025

Diminished Returns of Educational Attainment on Welfare Receipt of American Indian/Alaska Native People: National Health Interview Survey (NHIS) 2023

Abstract Background: Educational attainment is generally associated with reduced reliance on Social Security and disability benefits; however, the Minorities' Diminished Returns (MDRs) theory suggests that the socioeconomic benefits of education are weaker for minoritized populations. This study investigates the relationship between educational attainment and welfare receipt among American [...] Read more.
Background: Educational attainment is generally associated with reduced reliance on Social Security and disability benefits; however, the Minorities' Diminished Returns (MDRs) theory suggests that the socioeconomic benefits of education are weaker for minoritized populations. This study investigates the relationship between educational attainment and welfare receipt among American Indian/Alaska Native (AIAN) and White adults in the United States. Objective: Using the MDRs framework, we analyzed data from the National Health Interview Survey (NHIS) 2023 to examine how educational attainment impacts welfare receipt among AIAN and White adults. Methods: We analyzed a nationally representative sample of AIAN and White adults from the NHIS 2023 dataset. Welfare receipt was assessed as the receipt of any public assistance or welfare payments from state or local welfare offices. Educational attainment was categorized into three levels: less than high school (reference), high school diploma to some college, and college degree or higher. Logistic regression models were used to assess the relationship between educational attainment and welfare receipt, with separate analyses for AIAN and White adults to evaluate differential effects. Results: Higher educational attainment (high school diploma to some college and college degree or higher) was associated with lower odds of welfare receipt across both groups. However, the protective effect of a college degree was significantly weaker for AIAN adults compared to White adults. Consequently, AIAN adults remain at a higher risk of welfare reliance even with higher education, consistent with the Minorities' Diminished Returns (MDRs) framework. Conclusions: Although educational attainment generally reduces welfare reliance, this protection is less pronounced for AIAN adults than for White adults. This discrepancy suggests that structural factors, segregation, and social stratification may undermine the economic and health benefits of education for racialized groups in the U.S. Addressing these disparities requires policy interventions that extend beyond education, emphasizing quality job opportunities, healthcare access, and reduced labor market discrimination for individuals with advanced educational credentials, regardless of race.
Article
Open Access February 07, 2025

CEASE Tobacco Cessation Program: Validation of Self-Rated Quit with Fagerstrom Test for Nicotine Dependence

Abstract Background: Despite advancements in smoking cessation interventions, few programs have demonstrated sustained effectiveness among low-income, underserved populations. The Communities Engaged and Advocating for a Smoke-free Environment (CEASE) program was developed to address this gap and support tobacco cessation in these communities. However, it remains unclear whether self-reported [...] Read more.
Background: Despite advancements in smoking cessation interventions, few programs have demonstrated sustained effectiveness among low-income, underserved populations. The Communities Engaged and Advocating for a Smoke-free Environment (CEASE) program was developed to address this gap and support tobacco cessation in these communities. However, it remains unclear whether self-reported outcome measures in this context are in line with more objective outcome measures. Aims: This study aimed to validate self-reported quit rates using the Fagerström Test for Nicotine Dependence (FTND) as a gold standard outcome measure for evaluation of the effectiveness of the CEASE smoking cessation intervention compared to a self-help approach among low-income, underserved adult smokers. Methods: A quasi-experimental design was employed to evaluate this community-based intervention. Although participants were initially assigned to three groups, this report focuses on two arms that show the major difference in the efficacy of the program: (1) the self-help group (reference; Arm 1) and (2) the in-person CEASE group (Arm 2). Outcomes included successful quitting, assessed through self-reports, and changes in FTND scores. To examine the concordance between these measures, we tested whether changes in FTND scores fully explained the relationship between the intervention and self-reported quitting. Potential confounders included demographic, socioeconomic, and health-related variables. Data were analyzed using regression and structural equation modeling (SEM). Results: The majority of participants were Black Americans, followed by White individuals and those of other racial backgrounds. The CEASE intervention (Arm 2) demonstrated effectiveness in reducing nicotine dependence (measured by FTND) and increasing self-reported quit rates compared to the self-help group. Importantly, changes in FTND scores fully explained the effect of the CEASE intervention on self-reported quitting, highlighting the program’s impact on addiction severity. Conclusion: Successful quitting measured using self-report is in line with the decline in nicotine addiction severity among low-income racial minority populations. CEASE holds promise as a scalable solution to address smoking disparities in underserved communities.
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Open Access January 24, 2025

High Socioeconomic Status Black Adolescents Attend Worse Schools than Whites

Abstract Background: School characteristics — including poverty levels, teacher experience, graduation rates, and college enrollment — are essential determinants of students’ academic outcomes and long-term success. Families often use their socioeconomic resources, such as parental education and household income, to secure access to high-quality schools with favorable attributes. However, [...] Read more.
Background: School characteristics — including poverty levels, teacher experience, graduation rates, and college enrollment — are essential determinants of students’ academic outcomes and long-term success. Families often use their socioeconomic resources, such as parental education and household income, to secure access to high-quality schools with favorable attributes. However, Minorities’ Diminished Returns (MDRs) theory suggests that Black families may not experience the same benefits of high family SES due to structural barriers. This study examines the association between family SES and school characteristics, focusing on racial disparities in access to high-quality educational environments. Objective: To investigate the relationship between family SES (parental education and household income) and multiple school characteristics (poverty, teacher experience, graduation rates, and college enrollment), and to assess racial differences in these associations. Methods: Data from the Adolescent Brain Cognitive Development (ABCD) study, a national sample of US adolescents, was analyzed. We used multivariate regression models to examine associations between family SES and school characteristics and to test for interactions by race, specifically comparing Black and White adolescents. Results: Higher family SES was associated with positive school characteristics overall, including lower school poverty, greater teacher experience, and increased graduation and college enrollment rates. However, these positive effects of high family SES on school characteristics were significantly weaker for Black adolescents than for White adolescents. Black adolescents from high-income families were more likely than White adolescents from similar backgrounds to attend schools with higher poverty rates, less experienced teachers, and reduced graduation and college enrollment rates. Conclusion: Our findings highlight persistent racial inequities in access to educational opportunities, even among families with comparable socioeconomic resources. The diminished returns of family SES for Black adolescents underscore the role of structural barriers in limiting access to high-quality schools. These findings emphasize the need for policy interventions to address systemic inequalities that hinder Black families from fully leveraging their SES to access favorable educational environments.
Article
Open Access January 24, 2025

Pallidum Functional Hypoconnectivity and Inhibitory Control as Partial Mediators of Environmental Influences on Tobacco and Marijuana Initiation

Abstract Background: Low socioeconomic status (SES) has been linked to higher rates of tobacco and marijuana use initiation; however, the contributions of environmental and neurocognitive factors remain underexplored. This study investigates a potential pathway connecting low SES, fine particulate matter (PM2.5) exposure, brain functional connectivity, and inhibitory control to increased [...] Read more.
Background: Low socioeconomic status (SES) has been linked to higher rates of tobacco and marijuana use initiation; however, the contributions of environmental and neurocognitive factors remain underexplored. This study investigates a potential pathway connecting low SES, fine particulate matter (PM2.5) exposure, brain functional connectivity, and inhibitory control to increased tobacco and marijuana use initiation among adolescents. Objectives: To examine the mediating roles of PM2.5 exposure, resting-state functional connectivity between the right pallidum and the ventral attention network (P-VAN rsFC), and inhibitory control in the relationship between low SES and tobacco and marijuana use initiation. Methods: Data were drawn from the Adolescent Brain Cognitive Development (ABCD) study to assess associations between baseline SES, baseline PM2.5 exposure (based on zip code), baseline P-VAN rsFC, baseline inhibitory control, and subsequent tobacco and marijuana use initiation. Mediation models were used to determine whether PM2.5 exposure and changes in P-VAN rsFC act as pathways linking low SES to diminished inhibitory control and subsequent substance use initiation. Results: Low SES was associated with higher PM2.5 exposure, which, in turn, was linked to alterations in P-VAN rsFC. These alterations were correlated with lower inhibitory control, which significantly predicted tobacco and marijuana use initiation over time. Inhibitory control partially mediated the relationship between low SES and substance use initiation, indicating a complex pathway influenced by environmental and neurocognitive factors. Conclusions: This study identifies a potential mechanism linking low SES to tobacco and marijuana use initiation through environmental and neurobiological pathways. Understanding how PM2.5 exposure and neurofunctional connectivity impact inhibitory control can provide valuable insights for developing targeted interventions to reduce substance use among adolescents in low SES environments.
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Open Access January 23, 2025

Population Diversity Matters: Heterogeneity of Biopsychosocial Pathways from Socioeconomic Status to Tobacco Use via Cerebral Cortical Volume in the ABCD Study

Abstract Background: Most neuroscience research has predominantly focused on White, middle-class populations, leading to gaps in understanding how socioeconomic status (SES) influences brain development and health behaviors in racially diverse groups. Tobacco use, a major public health concern, is influenced by both family and neighborhood SES, with early initiation during adolescence predicting [...] Read more.
Background: Most neuroscience research has predominantly focused on White, middle-class populations, leading to gaps in understanding how socioeconomic status (SES) influences brain development and health behaviors in racially diverse groups. Tobacco use, a major public health concern, is influenced by both family and neighborhood SES, with early initiation during adolescence predicting long-term health outcomes. The Adolescent Brain Cognitive Development (ABCD) study provides a unique opportunity to examine racial disparities in the pathways from SES to brain development and behavior, especially through the lens of Marginalization-Related Diminished Returns (MDRs), where the effects of SES are attenuated for minority groups. Objective: This study investigates racial variation in the associations between SES, cerebral cortical volume, and tobacco use initiation, comparing Black and White youth over 4-6 years of follow-up. Methods: Data from the ABCD study were analyzed to assess pathways from family income to adolescents’ cortical volume via the needs-to-income ratio, and from cortical volume to tobacco use initiation. Structural equation modeling was used to evaluate these pathways, stratified by race, with a focus on comparing Black and White participants. Covariates included family and neighborhood SES, demographic factors, and baseline behavioral measures. Results: We found that the positive association between income (via the needs-to-income ratio) and total cortical volume was significantly weaker for Black youth compared to White youth. Additionally, the link between larger total cortical volume and reduced risk of tobacco initiation was also weaker in Black adolescents. These findings were consistent over 4-6 years of follow-up, suggesting that Black youth experience diminished returns from higher SES in terms of brain development and behavioral outcomes. Conclusions: Our findings highlight significant racial disparities in the pathways from SES to brain development and tobacco use initiation, supporting the Marginalization-Related Diminished Returns (MDRs) framework. While higher SES is associated with larger cortical volumes and lower tobacco use risk in White youth, these associations are attenuated in Black adolescents.
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Open Access January 23, 2025

Weaker Effects of Educational Attainment on Chronic Medical Conditions in American Indian Alaska Native, Black, and Latino Adults: National Health Interview Survey 2023

Abstract Background: Chronic medical conditions are major drivers of healthcare spending, morbidity, and mortality in the United States, as well as critical indicators of health disparities. The disproportionately high rates of chronic medical conditions among Black, Latino, and American Indian and Alaska Native adults compared to non-Latino Whites highlight the urgent need to examine the factors [...] Read more.
Background: Chronic medical conditions are major drivers of healthcare spending, morbidity, and mortality in the United States, as well as critical indicators of health disparities. The disproportionately high rates of chronic medical conditions among Black, Latino, and American Indian and Alaska Native adults compared to non-Latino Whites highlight the urgent need to examine the factors contributing to these disparities. While higher socioeconomic status is generally associated with better health outcomes, this benefit may be diminished for racialized and minoritized populations. Objective: This study investigates the protective effects of educational attainment and income-to-poverty ratio on the prevalence of chronic medical conditions and examines whether these effects vary across racial and ethnic groups, specifically among Black, Latino, and American Indian and Alaska Native adults compared to non-Latino White adults. Methods: Using data from the 2023 National Health Interview Survey (NHIS), this cross-sectional study analyzed the association between educational attainment and chronic medical conditions across racial and ethnic groups. Logistic regression models were employed to assess whether the strength of the relationship between education and chronic medical conditions differed by racial/ethnic group, controlling for key demographic and socioeconomic covariates. Sample size was 29,373 which was reflective of 256,566,689 US population. Results: Consistent with the theory of Minorities' Diminished Returns, findings showed that the protective effects of higher educational attainment on chronic medical conditions were significantly weaker for Black, Latino, and American Indian and Alaska Native adults than for their non-Latino White counterparts. Even among individuals with higher education, Black, Latino, and American Indian and Alaska Native adults faced elevated risks of chronic medical conditions. Conclusion: While educational attainment generally reduces the prevalence of chronic medical conditions, this protective effect is moderated by racial and ethnic background. Structural barriers limit the health benefits of educational attainment. This underscores the need for policies that address structural inequities—such as low-quality education and occupational segregation—that constrain the protective health effects of educational attainment for minoritized groups.
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Open Access January 23, 2025

Diminished Returns of Educational Attainment on Hypertension Prevalence among American Indian and Alaska Native Adults: National Health Interview Survey 2023

Abstract Background: Research on Minorities’ Diminished Returns (MDRs) consistently reveals that social determinants of health, especially educational attainment, do not yield equal health benefits across racial and ethnic groups in the United States. MDRs suggest that social stratification, segregation, lower education quality, and labor market discrimination contribute to diminished health returns [...] Read more.
Background: Research on Minorities’ Diminished Returns (MDRs) consistently reveals that social determinants of health, especially educational attainment, do not yield equal health benefits across racial and ethnic groups in the United States. MDRs suggest that social stratification, segregation, lower education quality, and labor market discrimination contribute to diminished health returns of education among minoritized groups. However, few studies have tested the relevance of MDRs in American Indian and Alaska Native (AIAN) populations compared to non-Hispanic White adults. Objectives: This study aimed to examine the strength of the inverse association between educational attainment and hypertension prevalence, hypothesizing that the protective effect of education on hypertension risk is reduced among AIAN adults relative to non-Hispanic Whites. Methods: Using data from the 2023 National Health Interview Survey (NHIS), we analyzed a nationally representative sample of adults aged 18 and older. Logistic regression models examined the association between educational attainment and self-reported hypertension diagnosis, stratified by racial/ethnic group (AIAN vs. non-Hispanic White). Models were adjusted for key covariates, including age, gender, income, and insurance status. Results: Higher educational attainment was associated with a lower prevalence of hypertension in the combined sample of AIAN and non-Hispanic White adults. However, this protective association was significantly weaker among AIAN adults compared to non-Hispanic White adults, as evidenced by a significant interaction between race and education. Conclusion: AIAN adults exhibit a higher prevalence of hypertension even at higher levels of educational attainment compared to non-Hispanic White adults, supporting the relevance of MDRs for AIAN populations. This finding underscores the need for public health interventions that address structural barriers and contextual factors unique to AIAN populations. Policies focused solely on educational access may be insufficient to reduce hypertension risk among AIAN adults without addressing broader social and structural inequities.
Article
Open Access January 23, 2025

Trauma and Early Puberty May Be Stronger Predictors of Early Tobacco Initiation in Girls Compared to Boys

Abstract Objective: This study investigates the pathways linking socioeconomic status (SES), trauma, early puberty, and tobacco use, with a focus on how these relationships differ by sex. Using data from the Adolescent Brain Cognitive Development (ABCD) study, we explore how SES and race contribute to trauma exposure, which in turn may influence early puberty and tobacco use. The study also examines [...] Read more.
Objective: This study investigates the pathways linking socioeconomic status (SES), trauma, early puberty, and tobacco use, with a focus on how these relationships differ by sex. Using data from the Adolescent Brain Cognitive Development (ABCD) study, we explore how SES and race contribute to trauma exposure, which in turn may influence early puberty and tobacco use. The study also examines potential mediating effects of trauma and early puberty on the association between SES and tobacco use, while comparing these pathways for males and females. Methods: Data were drawn from the ABCD study, and structural equation modeling (SEM) was employed to test direct and indirect pathways between SES, trauma, early puberty, and tobacco use. The sample was stratified by sex to assess differences in these relationships for males and females. Key predictors included SES, race, and age, while outcomes were trauma, early puberty, and tobacco use. The model assessed mediating effects of trauma and early puberty on tobacco use. Results: Trauma was a significant predictor of early puberty for females (B = 0.032, SE = 0.015, p = 0.039) but not males. Early puberty was significantly linked to tobacco use for females (B = 0.048, SE = 0.015, p = 0.001) but not for males. Additionally, trauma had an effect on tobacco use among females (B = 0.048, SE = 0.014, p < 0.001) but not males. Lower SES was significantly associated with higher trauma exposure for both males (B = -0.109, SE = 0.014, p < 0.001) and females (B = -0.110, SE = 0.015, p < 0.001). Conclusions: The findings suggest that trauma and early puberty play more significant roles in the pathways from SES to tobacco use for females than for males. While trauma and early puberty are crucial mediators for females, these factors are less predictive for males. These results highlight the importance of sex-specific interventions targeting trauma and early puberty as pathways to early tobacco use.
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Open Access January 23, 2025

Brain-Wide Resting-State Functional Connectivity Partially Mediates Socioeconomic Disparities in Children's Cardiometabolic Health

Abstract Background: Although some neural mechanisms underlying socioeconomic status (SES) disparities are known, the role of brain-wide resting-state functional connectivity in these effects remains less understood. Aim: This study aims to identify brain-wide resting-state functional connectivity signatures that may mediate the effects of SES on body mass index (BMI) and blood pressure in [...] Read more.
Background: Although some neural mechanisms underlying socioeconomic status (SES) disparities are known, the role of brain-wide resting-state functional connectivity in these effects remains less understood. Aim: This study aims to identify brain-wide resting-state functional connectivity signatures that may mediate the effects of SES on body mass index (BMI) and blood pressure in children, using data from the Adolescent Brain Cognitive Development (ABCD) study. Methods: Data were drawn from the ABCD study, a large, diverse cohort of children aged 9-10. Pre-processed resting-state functional MRI data were used, and factor analysis was conducted to extract a whole-brain connectivity factor. The first factor, capturing the greatest variance in brain-wide resting-state connectivity, was selected for further analysis in a structural equation model (SEM). This connectivity factor was tested as a potential mediator of the relationship between SES (measured by parental education, family income, and neighborhood characteristics) and two indicators of cardiometabolic health: BMI and systolic blood pressure. Results: Factor analysis revealed a robust first factor that accounted for a significant proportion of variance in brain-wide resting-state functional connectivity. This factor was significantly associated with SES, indicating that children from lower SES backgrounds exhibited distinct connectivity patterns. Additionally, the factor was linked to both BMI and systolic blood pressure, suggesting its relevance to cardiometabolic health. Mediation analysis showed that this connectivity factor partially mediated the relationship between SES and both BMI and systolic blood pressure. Conclusions: Brain-wide functional connectivity may be a mediator of SES effects on BMI and blood pressure in children. The first connectivity factor provides a promising neural signature linking SES with cardiometabolic risk. Comprehensive brain-wide approaches to functional connectivity may offer valuable insights into how social determinants of health shape neural and physical development in childhood.
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Open Access January 20, 2025

Deep Learning-Based Sentiment Analysis: Enhancing IMDb Review Classification with LSTM Models

Abstract Sentiment analysis, a vital aspect of natural language processing, involves the application of machine learning models to discern the emotional tone conveyed in textual data. The use case for this type of problem is where businesses can make informed decisions based on customer feedback, identify the sentiments of their employees, and make decisions on hiring or retention, or for that matter, [...] Read more.
Sentiment analysis, a vital aspect of natural language processing, involves the application of machine learning models to discern the emotional tone conveyed in textual data. The use case for this type of problem is where businesses can make informed decisions based on customer feedback, identify the sentiments of their employees, and make decisions on hiring or retention, or for that matter, classify a text based on its topic like whether it is about a particular subject like physics or chemistry as is useful in search engines. The model leverages a sequential architecture, transforms words into dense vectors using an Embedding layer, and captures intricate sequential patterns with two Long Short-Term Memory (LSTM) layers. This model aims to effectively classify sentiments in text data using a 50-dimensional embedding dimension and 20 % dropout layers. The use of rectified linear unit (ReLU) activations enhances non-linearity, while the SoftMax activation in the output layer aligns with the multi-class nature of sentiment analysis. Both training and test accuracy were well over 80%.
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Open Access January 16, 2025

Extreme Heat Exposure and Adolescent Cognitive Function

Abstract Background: Extreme heat exposure is an increasing public health concern, particularly in the context of climate change. Limited research has explored its impact on children's cognitive outcomes. This study investigates the association between extreme heat exposure and cognitive function in 9–10-year-old children, using data from the Adolescent Brain Cognitive Development (ABCD) study. [...] Read more.
Background: Extreme heat exposure is an increasing public health concern, particularly in the context of climate change. Limited research has explored its impact on children's cognitive outcomes. This study investigates the association between extreme heat exposure and cognitive function in 9–10-year-old children, using data from the Adolescent Brain Cognitive Development (ABCD) study. Additionally, we assess whether this effect is independent of socio-demographic factors such as race, family socioeconomic status (SES), and neighborhood SES. Methods: Data were drawn from the ABCD study, comprising over 10,000 children aged 9–10 years. Cognitive function was assessed through standardized cognitive tests, while extreme heat exposure was estimated using geographic and climate data. Structural equation modeling (SEM) was employed to examine the direct effects of heat exposure on cognitive outcomes and to account for potential confounding variables, including race, family SES, and neighborhood SES. Results: Black families, low SES households, and children from low SES neighborhoods were disproportionately exposed to extreme heat. Extreme heat exposure was significantly associated with lower cognitive function in children, and this association remained robust even after adjusting for socio-demographic factors. Conclusions: Extreme heat exposure is linked to diminished cognitive function in children, particularly among socio-economically disadvantaged and marginalized populations. Given the increasing frequency of extreme heat events due to climate change, future research should further explore these implications for children’s cognitive outcomes. Policy interventions that improve access to cooling infrastructure, expand green spaces, and prioritize at-risk populations are critical to mitigating the adverse cognitive effects of extreme heat in low SES communities.
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Open Access January 16, 2025

Heat Exposure Predicts Earlier Childhood Pubertal Initiation, Behavioral Problems, and Tobacco Use

Abstract Background: Climate change has raised significant concerns about its impact on health, particularly for vulnerable populations such as children and adolescents. While extensive research has examined physical health effects, limited attention has been given to the influence of extreme heat on developmental and behavioral outcomes. Objectives: This study investigates the association [...] Read more.
Background: Climate change has raised significant concerns about its impact on health, particularly for vulnerable populations such as children and adolescents. While extensive research has examined physical health effects, limited attention has been given to the influence of extreme heat on developmental and behavioral outcomes. Objectives: This study investigates the association between extreme heat exposure and early puberty initiation (ages 9-10), using data from the Adolescent Brain Cognitive Development (ABCD) study. It further explores how early puberty correlates with behavioral problems and tobacco use initiation. Methods: Data from 11,878 participants in the ABCD study were analyzed to examine the relationship between extreme heat exposure (independent variable) and puberty initiation (outcome). Behavioral problems and tobacco use initiation were evaluated as downstream outcomes of early puberty. Covariates included age, sex, and race/ethnicity, and behavioral problems were assessed using the Child Behavior Checklist (CBCL). Structural equation modeling (SEM) was employed for analysis. Results: Extreme heat exposure was significantly associated with earlier puberty initiation at ages 9-10. Early puberty, in turn, correlated with higher levels of behavioral problems and an increased likelihood of tobacco use initiation. Conclusions: These findings underscore the importance of addressing environmental factors such as extreme heat to reduce risks associated with early maturation, including behavioral and substance use challenges. Targeted interventions and policies are needed to mitigate the impact of extreme heat on child development, and longitudinal studies are essential to confirm these results and inform effective prevention strategies.
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Open Access January 16, 2025

Puberty Onset and Positive Urgency Explain Diminished Returns of Family Income on Tobacco and Marijuana Use

Abstract Background: Puberty is a crucial developmental milestone that involves significant physiological, emotional, and behavioral changes. Early puberty onset, influenced by both biological and social factors, is associated with an increased risk of engaging in substance use, such as tobacco and marijuana. While high family income is generally linked to delayed puberty onset and lower behavioral [...] Read more.
Background: Puberty is a crucial developmental milestone that involves significant physiological, emotional, and behavioral changes. Early puberty onset, influenced by both biological and social factors, is associated with an increased risk of engaging in substance use, such as tobacco and marijuana. While high family income is generally linked to delayed puberty onset and lower behavioral risks, these benefits may not be equally protective for Black youth due to the phenomenon of Minorities' Diminished Returns (MDRs). MDRs suggest that higher family income does not offer the same protective effects for Black youth as it does for White youth, potentially leading to earlier puberty and increased substance use among high-income Black adolescents. Objective: This study aimed to investigate whether early puberty onset and associated positive urgency (impulsivity) mediate the relationship between family income and the initiation of tobacco and marijuana use over a six-year follow-up period among adolescents. Additionally, the study examined whether the effects of family income on early puberty onset differ by race, testing the hypothesis that high-income Black youth would experience earlier puberty onset compared to their high-income White peers. Methods: Data were sourced from the Adolescent Brain Cognitive Development (ABCD) Study. Participants were 9-10-year-old adolescents at baseline, followed over a period of six years. Structural equation modeling (SEM) was used to assess whether early puberty onset mediated the effects of family income on substance use behaviors. Interaction terms between race and family income were included to test whether the impact of family income varies by race. Results: Early puberty onset and associated positive urgency partially explained the relationship between family income and the initiation of tobacco and marijuana use. High-income Black youth showed earlier puberty onset compared to their White counterparts. Earlier puberty onset then predicted higher positive urgency. These factors, in turn, were linked to higher rates of tobacco and marijuana initiation. Conclusions: This study provides additional evidence that the benefits of high family income do not extend equally to Black adolescents, particularly regarding delaying puberty onset and its consequences for substance use.
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Open Access January 15, 2025

Too Much Heat May Make You Smoke

Abstract Background: The rising concerns surrounding climate change have drawn attention to its potential impact on health, particularly among vulnerable groups such as children and older adults. Despite extensive research on health consequences, limited studies have explored the connection between extreme heat exposure and tobacco use initiation among adolescents in the United States. [...] Read more.
Background: The rising concerns surrounding climate change have drawn attention to its potential impact on health, particularly among vulnerable groups such as children and older adults. Despite extensive research on health consequences, limited studies have explored the connection between extreme heat exposure and tobacco use initiation among adolescents in the United States. Objectives: This study examines the relationship between extreme heat exposure and the initiation of tobacco use in adolescents, using data from the Adolescent Brain Cognitive Development (ABCD) study. It also evaluates the mediating roles of major depressive disorder (MDD) and childhood behavioral problems. Methods: Data from 11,878 participants in the ABCD study were analyzed to explore the link between extreme heat exposure (independent variable) and tobacco use initiation (dependent variable). Covariates included age, sex, and race/ethnicity, while MDD and behavioral problems (measured using the Child Behavior Checklist, CBCL) were assessed as potential mediators. Structural equation modeling (SEM) was applied for analysis. Results: The findings indicated a significant association between extreme heat exposure and an increased likelihood of tobacco use initiation in adolescents aged 9 to 15. MDD and behavioral problems partially mediated this relationship. Conclusions: These results underscore the importance of targeted interventions aimed at mitigating the impact of extreme heat on adolescent health, including its influence on tobacco use initiation. Addressing mental health and behavioral challenges could help reduce these risks. Future longitudinal research is needed to confirm these findings and evaluate the efficacy of strategies to protect vulnerable youth populations.
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Open Access November 21, 2024

Financial Strain Partially Explains Diminished Returns of Parental Education in the ABCD Study

Abstract Background: Previous research shows that socioeconomic status (SES) positively impacts children's development, yet the benefits are not equally distributed across racial groups. According to the Minorities’ Diminished Returns (MDRs) framework, Black children tend to experience smaller gains from parental education compared to White children. Objective: Building on the MDRs framework, [...] Read more.
Background: Previous research shows that socioeconomic status (SES) positively impacts children's development, yet the benefits are not equally distributed across racial groups. According to the Minorities’ Diminished Returns (MDRs) framework, Black children tend to experience smaller gains from parental education compared to White children. Objective: Building on the MDRs framework, this study examines whether high financial strain contributes to the diminished returns of parental education for Black children, using data from the Adolescent Brain Cognitive Development (ABCD) Study. We hypothesized that: (1) there would be a positive effect of parental education on total cortical volume, (2) this effect would be weaker for Black than White children, and (3) higher household financial strain in Black families would mediate the diminished returns of parental education on total cortical volume for Black children. Methods: Data were drawn from the baseline ABCD Study, focusing on 7,936 9- and 10-year-old children identified as either Black (n = 1,775) or White (n = 6,161). Parental education was the key independent variable, covariates included age, sex, household income, and marital status, race was the moderator, financial strain was the mediator, and total cortical volume was the outcome. Structural Equation Models (SEMs) were employed to examine the associations between parental education and cortical volume, with financial strain as a mediator and race as a moderator. Results: Higher parental education was associated with greater cortical volume in the pooled sample. However, this effect was significantly weaker for Black children. Financial strain partially mediated the observed diminished returns of parental education. Conclusion: High financial strain experienced by middle-class Black families partially explains why the association between parental education and child development is weaker in Black than White families. Interventions aimed at enhancing educational quality, increasing employability, expanding access to higher-paying jobs, and reducing labor market discrimination against Black individuals may help address racial inequities in child development in the U.S. Efforts to reduce financial strain should extend beyond low-income populations to also support higher-educated minority families.
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Open Access November 21, 2024

Diminished Returns of Educational Attainment on Body Mass Index Among Latino Populations: Insights from UAS Data

Abstract Background: Educational attainment is a well-established predictor of physical health outcomes, including body mass index (BMI). However, according to the theory of Minorities' Diminished Returns (MDRs), the health benefits of education tend to be weaker for ethnic minorities compared to non-Latino Whites, due to structural inequalities and social disadvantages. Objective: [...] Read more.
Background: Educational attainment is a well-established predictor of physical health outcomes, including body mass index (BMI). However, according to the theory of Minorities' Diminished Returns (MDRs), the health benefits of education tend to be weaker for ethnic minorities compared to non-Latino Whites, due to structural inequalities and social disadvantages. Objective: This study examines whether the association between educational attainment and BMI is weaker among Latino individuals compared to non-Latino individuals, in line with the MDRs framework. Methods: Data were drawn from the 2014 wave of the Understanding America Study (UAS), a nationally representative internet-based panel. Body mass index (BMI) was the outcome of interest. Linear regression models were used to analyze the association between educational attainment and BMI, with an interaction term for ethnicity to explore differences in the relationship between Latino and non-Latino people. Models were adjusted for age, sex, marital status, and labor market participation and results were presented as beta coefficients, p-values, and 95% confidence intervals (CIs). Results: Higher educational attainment was associated with lower BMI for both Latino and non-Latino participants (p < 0.001). However, the interaction between educational attainment and ethnicity was significant (p < 0.05), indicating that Latino individuals experienced smaller reductions in BMI because of higher education compared to non-Latino people. Conclusion: This study provides evidence of diminished returns from educational attainment on BMI among Latino individuals. These findings support the MDRs framework, suggesting that structural barriers may limit the health benefits of education for Latino populations. While education is a key determinant of physical and mental health, its benefits are not equitably distributed across ethnic groups. Structural inequalities, chronic stress, poor neighborhood environments, and adverse educational and occupational conditions likely contribute to this disparity. Addressing these underlying factors through targeted policy interventions is necessary to promote health equity for Latino populations.
Article
Open Access November 21, 2024

Unequal Returns: Education Fails to Fully Prepare Black and Latino Americans for Retirement

Abstract Background: Retirement is a universal life stage, marking the culmination of an individual's working years. However, many people face financial challenges during retirement due to insufficient financial planning. Retirement preparedness is essential for ensuring economic security and maintaining a high quality of life in later years. Education is often viewed as a key driver of retirement [...] Read more.
Background: Retirement is a universal life stage, marking the culmination of an individual's working years. However, many people face financial challenges during retirement due to insufficient financial planning. Retirement preparedness is essential for ensuring economic security and maintaining a high quality of life in later years. Education is often viewed as a key driver of retirement preparedness, as it is linked to higher earnings, better financial literacy, and improved decision-making. However, the Minorities' Diminished Returns (MDRs) theory suggests that the economic, cognitive, and behavioral benefits of education are weaker for racial and ethnic minorities compared to non-Latino Whites. Objective: This study aims to examine the relationship between educational attainment and retirement preparedness, focusing on whether this association differs among Black, Latino, and non-Latino White individuals, using data from the Understanding America Study (UAS). Methods: Data were drawn from the UAS, a nationally representative internet-based panel survey. The sample included participants from diverse racial and ethnic backgrounds. Linear regression models were used to evaluate the association between educational attainment, measured in years of schooling, and retirement preparedness. Interaction terms were included to test whether the association varied by race and ethnicity. Models were adjusted for potential confounders, including age, sex, marital status, employment status, and immigration. Results: In the overall sample, higher educational attainment was significantly and positively associated with better retirement preparedness (p < 0.001). However, consistent with the MDRs framework, the strength of this association was significantly weaker for Black and Latino participants compared to non-Latino White participants (p < 0.05). Non-Latino Whites with higher education levels reported substantially better retirement preparedness, while the same level of education yielded smaller gains in retirement preparedness for Black and Latino individuals. Conclusion: The findings support the Minorities' Diminished Returns theory, showing that although educational attainment enhances retirement preparedness for all groups, Black and Latino individuals derive fewer benefits compared to their non-Latino White counterparts. These disparities point to persistent structural inequalities and systemic barriers within the education system and labor market, as well as the effects of segregation and discrimination, which undermine the economic benefits of education for marginalized populations. Addressing these disparities requires targeted policy interventions aimed at eliminating racial and ethnic inequalities in retirement outcomes and ensuring equitable benefits from educational attainment for all groups.
Article
Open Access November 19, 2024

The Cost of Opportunity: Anti-Black Discrimination in High Resource Settings

Abstract Objective: Inequalities exist in children’s educational outcomes—including reading proficiency, school discrimination, and school disciplinary actions—across zip codes with different levels of educational childhood opportunity index (COI). This study examines the interaction between race and educational environment on children’s educational outcomes. We hypothesize that race, parental [...] Read more.
Objective: Inequalities exist in children’s educational outcomes—including reading proficiency, school discrimination, and school disciplinary actions—across zip codes with different levels of educational childhood opportunity index (COI). This study examines the interaction between race and educational environment on children’s educational outcomes. We hypothesize that race, parental education, and their interaction are associated with perceived school discrimination, which in turn reduces their cognitive, academic, and emotional wellbeing. We also hypothesize that Black children with high socioeconomic status (SES) report high perceived school discrimination in high-COI settings. Methods: Data were drawn from the Adolescent Brain Cognitive Development (ABCD) study, which measures a wide range of educational, cognitive, and emotional outcomes. At the same time, the ABCD children are sampled across areas with vast differences in COI rankings, that can be classified into these five categories: very high, high, average, low, and very low educational COIs. Our structural equation models (SEM) tested the additive and interactive effects of race and educational attainment on perceived school discrimination, and the effects of school discrimination on various cognitive abilities (reading proficiency, picture vocabulary, and list sorting working memory), school suspension, as well as depressed mood. Our multi-group SEM assessed how these relationships vary across educational COI levels. Results: Our findings showed that high SES Black children report highest school discrimination in residential areas with highest COIs. This is based on the observation that the interaction between race and parental education on experiences of school discrimination were only significant in areas with highest COI. Across residential areas with different COI levels, students who experienced higher school discrimination had higher suspension, worse depression, and worse cognitive performance. Conclusion: While higher COIs are associated with better academic outcomes, Black-White gaps exist in the role of increased COI through increased racial bias that children perceive. These findings underscore the complexity of educational equity, suggesting that improving COI alone is insufficient for eliminating racial disparities in school experiences. Policies should be in place to reduce school-based discrimination against Black students in high COI settings.
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Open Access November 19, 2024

Social Epidemiology of Dual Use of Electronic and Combustible Cigarettes Among U.S. Adults: Insights from the Population Assessment of Tobacco and Health (PATH) Study

Abstract Background: The dual use of e-cigarettes and combustible cigarettes poses significant public health concerns due to the compounded risks associated with the use of both products. Understanding the predictors of dual use can inform targeted interventions and tobacco control strategies aimed at reducing nicotine dependence and health risks among adults. Objective: This study [...] Read more.
Background: The dual use of e-cigarettes and combustible cigarettes poses significant public health concerns due to the compounded risks associated with the use of both products. Understanding the predictors of dual use can inform targeted interventions and tobacco control strategies aimed at reducing nicotine dependence and health risks among adults. Objective: This study aims to identify the sociodemographic predictors of dual use of e-cigarettes and combustible cigarettes among U.S. adults using baseline data from the Population Assessment of Tobacco and Health (PATH) Study. Methods: We analyzed baseline data from the PATH Study, focusing on adult participants who reported the use of both e-cigarettes and combustible cigarettes. Logistic regression models were used to identify the associations between dual use and key sociodemographic variables, including age, gender, race/ethnicity, and education level. Results: The analysis revealed that dual use of e-cigarettes and combustible cigarettes was predominantly observed among young, female, non-Latino, White, and highly educated adults. Younger adults were more likely to engage in dual use compared to older age groups. Females showed higher rates of dual use compared to males. Non-Latino White individuals were more likely to be dual users than individuals from other racial/ethnic backgrounds. Additionally, higher educational attainment was associated with increased dual use, contrary to traditional smoking patterns. Conclusion: The findings highlight specific demographic groups that are at higher risk of dual use of e-cigarettes and combustible cigarettes, particularly younger, highly educated, non-Latino White females. These insights suggest the need for tailored public health interventions that address the unique needs and behaviors of these populations. Future research should explore the underlying motivations and contextual factors contributing to dual use to enhance the effectiveness of tobacco control policies and cessation programs.
Article
Open Access November 19, 2024

High Education, Low Returns: Financial Literacy Challenges for African Americans and Hispanics

Abstract Background: Education is widely regarded as a key driver of financial literacy, yet racial and ethnic disparities persist. Even among highly educated individuals, African American and Hispanic populations may face challenges in financial literacy, likely due to structural racism and socioeconomic inequalities that diminish the benefits of education. This study examines the relationship [...] Read more.
Background: Education is widely regarded as a key driver of financial literacy, yet racial and ethnic disparities persist. Even among highly educated individuals, African American and Hispanic populations may face challenges in financial literacy, likely due to structural racism and socioeconomic inequalities that diminish the benefits of education. This study examines the relationship between education and financial literacy among African American and Hispanic individuals compared to their White counterparts, focusing on how structural factors contribute to these disparities. Objective: To determine whether highly educated African American and Hispanic individuals exhibit lower financial literacy compared to similarly educated White individuals and to explore the role of structural factors in explaining these disparities. Methods: Data from the 2016 Understanding America Study (UAS) were used to evaluate financial literacy among U.S. adults. The sample was stratified by race/ethnicity (African American, Hispanic, and White) and educational attainment. Financial literacy was assessed using standardized financial knowledge tests. Multivariate regression models were employed to investigate the relationship between race/ethnicity, education, and financial literacy, adjusting for socioeconomic factors such as income, employment, and household wealth. Results: African American and Hispanic individuals with higher levels of education demonstrated significantly lower financial literacy scores than their White peers (p < 0.001). The positive association between education and financial literacy was notably stronger for White individuals than for African American and Hispanic individuals. Further analyses suggest that structural barriers, including systemic discrimination in access to financial resources and disparities in educational quality, contribute to these diminished returns on education for racial and ethnic minorities. Conclusion: This study highlights persistent financial literacy disparities among highly educated African American and Hispanic individuals, underscoring the limitations of education alone in overcoming structural inequalities. The findings emphasize the need for targeted policies to address systemic barriers that restrict the financial knowledge and opportunities typically associated with higher education for racial and ethnic minority groups.
Article
Open Access November 18, 2024

Technological Caring Competence for Nursing Education (TCCNE) in Filipino Nurse Educators: Toward the Development of Basis for a Training Plan

Abstract Background: Nowadays, integrating online and remote instruction into education presents unique challenges, particularly in nursing education, where combining technology with the core value of caring is essential. Nurse educators must address students’ holistic needs, as their circumstances can influence overall learning development. Objectives: This study aims to ascertain the [...] Read more.
Background: Nowadays, integrating online and remote instruction into education presents unique challenges, particularly in nursing education, where combining technology with the core value of caring is essential. Nurse educators must address students’ holistic needs, as their circumstances can influence overall learning development. Objectives: This study aims to ascertain the technological caring competence of nurse educators Methodology: A descriptive design using an adapted tool on technological caring competence for nursing education (TCCNE) Results: A total of 243 Filipino nursing educators participated in this study. Overall, the participants’ perceived level of TCCNE was quite high. This sample representative of nursing educators holds strong perceptions of their TCCNE with the values of being considerate, supportive, and respectful to their students as the highest rated competency. This result implies that the educators keep the essence of what nursing is about as they model the importance of caring even in an academic setting considering that these teachers are using remote instruction. Conclusion: The study opens up a discussion on assessing the TCCNE of nursing education in an academic setting. Thus, its advocacy could start from implementing the research training plan. Further, the nurse educators should strengthen in balancing care with appropriate technology is viewed as a necessary step to maintain the essence of nursing, which is on caring that can be modeled out not just in clinical practice alone, but in nursing education.
Article
Open Access November 14, 2024

When Common Becomes Normal: Weaker Association Between Neighborhood Stress and Body Mass Index Among Black Adolescents Compared to White Adolescents

Abstract Objective: This study explores the relationship between neighborhood stress and Body Mass Index (BMI) in adolescents, while also examining whether this association differs between Black and White adolescents. Methods: Data from the Adolescent Brain Cognitive Development (ABCD) Study were analyzed using linear regression models to examine the association between neighborhood stress [...] Read more.
Objective: This study explores the relationship between neighborhood stress and Body Mass Index (BMI) in adolescents, while also examining whether this association differs between Black and White adolescents. Methods: Data from the Adolescent Brain Cognitive Development (ABCD) Study were analyzed using linear regression models to examine the association between neighborhood stress (defined as a composite score based on three items measuring perceived safety and neighborhood fear) and BMI in adolescents, controlling for demographic and socioeconomic variables. We tested models both with and without interaction terms to assess whether race moderated the association. Stratified analyses were conducted to further explore potential differences between Black and White adolescents. Results: A positive association was observed between neighborhood stress and BMI across the overall sample. However, this association was weaker for Black adolescents compared to White adolescents, even after adjusting for potential confounders. Conclusions: The contribution of neighborhood stress to higher BMI in adolescents may vary by race. Our findings suggest that while neighborhood stress is associated with increased BMI, Black adolescents appear to be less affected by these stressors than their White peers. This weaker association could be due to the normalization of stress in environments where it is pervasive (what is common becomes normal) or the presence of other significant risk factors affecting BMI in Black youth, such as poverty, limited food access, food culture, and food deserts. Future research should explore processes of habituation, inoculation, or even sensitization to stress among Black populations, who are often exposed to a wide range of stressors throughout the life course.
Article
Open Access November 09, 2024

Educated but Unhealthy? Examining Minorities' Diminished Returns

Abstract Background: Educational attainment is known to improve self-rated health; however, research suggests that these benefits may be less pronounced for racial and ethnic minority groups. The Minorities' Diminished Returns (MDRs) theory posits that the protective effects of resources such as education are weaker for marginalized populations, such as Black and Latino individuals, compared to [...] Read more.
Background: Educational attainment is known to improve self-rated health; however, research suggests that these benefits may be less pronounced for racial and ethnic minority groups. The Minorities' Diminished Returns (MDRs) theory posits that the protective effects of resources such as education are weaker for marginalized populations, such as Black and Latino individuals, compared to their White counterparts. Objective: This study aims to investigate racial and ethnic disparities in the association between years of schooling and self-rated health among U.S. adults, with a focus on understanding the reduced health benefits of education for Black and Latino individuals. Methods: Using data from the Understanding America Study (UAS; 2014), we conducted a cross-sectional analysis of adults aged 18 and older (N = 6,785). Self-rated health was the outcome, and years of schooling was the primary independent variable. We controlled for sociodemographic factors including age, gender, employment status, immigration status, and marital status. Stratified analyses were conducted by race/ethnicity (Non-Latino White, Non-Latino Black, and Latino). Linear regression models were used to examine the association between years of schooling and self-rated health, and interaction terms were included to assess variation in this relationship across racial/ethnic groups. Results: While years of schooling was positively associated with better self-rated health overall, the magnitude of this effect was weaker for Black and Latino individuals compared to White individuals. After adjusting for sociodemographic factors, Black and Latino adults reported worse self-rated health for each additional year of schooling, compared to their White counterparts, supporting the MDRs hypothesis. Conclusion: The findings suggest that while higher educational attainment is protective against worse self-rated health, this protection is not equally distributed across racial and ethnic groups. Black and Latino individuals experience diminished returns from their years of schooling in terms of self-rated health, likely due to structural barriers and social inequalities. Policies addressing health disparities must consider these diminished returns and aim to reduce structural racism and discrimination that undermine the benefits of education for minoritized populations.
Article
Open Access November 09, 2024

Educated but on Social Security Disability Insurance: Minorities’ Diminished Returns

Abstract Background: Educational attainment is widely regarded as a key predictor of economic and social outcomes in later life, including the likelihood of receiving Social Security Disability Insurance (SSDI). According to the Minorities' Diminished Returns (MDRs) theory, however, the benefits of education may be less pronounced for racial and ethnic minorities compared to non-Latino [...] Read more.
Background: Educational attainment is widely regarded as a key predictor of economic and social outcomes in later life, including the likelihood of receiving Social Security Disability Insurance (SSDI). According to the Minorities' Diminished Returns (MDRs) theory, however, the benefits of education may be less pronounced for racial and ethnic minorities compared to non-Latino Whites. This study investigates whether the effects of education on the likelihood of receiving SSDI differ by race and ethnicity, focusing on Black and Latino Americans. Objective: The primary aim of this study was to examine the relationship between educational attainment (measured in years of schooling) and the likelihood of receiving SSDI, with a specific focus on exploring how this relationship varies by race and ethnicity, in line with the MDRs framework. Methods: Data were drawn from the Understanding America Study (UAS), a nationally representative, internet-based panel survey. The sample included Black, Latino, and non-Latino White U.S. adults. Our sample size was 12,975 adults over the age of 18. Logistic regression models were used to assess the association between educational attainment and receiving SSDI, adjusting for demographic variables such as age, sex, employment status, and marital status. Interaction terms between race/ethnicity and educational attainment were included to explore whether the returns on education varied across racial and ethnic groups. Results: Higher educational attainment was significantly associated with a lower likelihood of receiving SSDI in the overall sample. However, consistent with the MDRs framework, the protective effect of education was significantly weaker for both Black and Latino individuals compared to non-Latino Whites. Black and Latino participants with similar levels of education as their non-Latino White counterparts were more likely to receive SSDI, reflecting diminished returns on educational attainment for these groups. Conclusion: This study provides strong evidence supporting the MDRs theory, demonstrating that the protective effects of education on the likelihood of receiving SSDI are not equally distributed across racial and ethnic groups. Black and Latino Americans experience weaker returns on their education when it comes to avoiding SSDI, likely due to structural inequalities and systemic barriers. These findings highlight the need for policies that address not only educational disparities but also the broader societal factors that limit the benefits of education for racial and ethnic minorities.
Article
Open Access August 07, 2024

Revolutionizing Active Pharmaceutical Ingredients: From Concept to Compliance

Abstract Active Pharmaceutical Ingredients (APIs) serve as the cornerstone of pharmaceutical development, driving therapeutic efficacy and safety in drug formulations. This article provides a comprehensive overview of the lifecycle of APIs, starting from their discovery and development, through to manufacturing processes and regulatory oversight. The development of APIs begins with intensive research and [...] Read more.
Active Pharmaceutical Ingredients (APIs) serve as the cornerstone of pharmaceutical development, driving therapeutic efficacy and safety in drug formulations. This article provides a comprehensive overview of the lifecycle of APIs, starting from their discovery and development, through to manufacturing processes and regulatory oversight. The development of APIs begins with intensive research and discovery efforts, where medicinal chemists and pharmacologists identify and optimize potential compounds through computational modelling, high-throughput screening, and structure-activity relationship studies. Promising candidates undergo rigorous preclinical testing to assess pharmacological properties, safety profiles, and potential adverse effects in animal models. Upon successful preclinical outcomes, APIs progress to clinical trials, involving phases of testing in human subjects to evaluate efficacy, dosage regimens, and safety profiles under controlled conditions. Clinical trial data are meticulously analyzed to support regulatory submissions, demonstrating the API's therapeutic benefits and safety for eventual patient use. Manufacturing APIs involves complex chemical synthesis or biotechnological methods, ensuring precise control over reaction conditions, purity, and yield. The scale-up from laboratory synthesis to industrial production demands adherence to Good Manufacturing Practices (GMP), where stringent quality control measures verify consistency, potency, and stability throughout production batches. Regulatory oversight by authorities such as the Food and Drug Administration (FDA) in the United States and the European Medicines Agency (EMA) in Europe ensures that APIs meet stringent standards of safety, efficacy, and quality before market approval. Manufacturers must submit comprehensive Chemistry, Manufacturing, and Controls (CMC) data, detailing manufacturing processes, analytical methods, and stability studies to support regulatory filings.
Review Article
Open Access November 05, 2024

Diminished Returns of Educational Attainment on Numeracy Score of Latino Populations: Insights from UAS Data

Abstract Background: Educational attainment is a well-established social determinant of various domains of cognitive function across the lifespan. However, the theory of Minorities' Diminished Returns (MDRs) suggests that the health benefits of educational attainment tend to be weaker for ethnic minorities compared to non-Latino Whites. This phenomenon may reflect the impact of structural [...] Read more.
Background: Educational attainment is a well-established social determinant of various domains of cognitive function across the lifespan. However, the theory of Minorities' Diminished Returns (MDRs) suggests that the health benefits of educational attainment tend to be weaker for ethnic minorities compared to non-Latino Whites. This phenomenon may reflect the impact of structural inequalities, social stratification, and historical disadvantage. Objective: This study examines whether the association between educational attainment and numeracy score, one domain of cognitive function, is weaker in Latino individuals compared to non-Latino individuals, as predicted by the MDRs framework. Methods: Data were drawn from the 2014 wave of the Understanding America Study (UAS), a national internet-based panel. Numeracy score, a domain of the cognitive function was measured using an 8-item measure. Linear regression models were used to analyze the association between educational attainment and numeracy score, with an interaction term for ethnicity x educational attainment to explore differences between Latino and non-Latino participants. Models were adjusted for age, gender, marital status, immigration, and employment, and results were presented as beta coefficients, p-values, and 95% confidence intervals (CIs). Results: Overall, 5,659 participants entered our analysis. Higher educational attainment was positively associated with higher numeracy score for both Latino and non-Latino participants (p < 0.001). However, the interaction between education and ethnicity was significant (p < 0.05), indicating that Latino individuals experienced smaller numeracy benefits from education compared to non-Latino individuals. These results support the MDRs framework, suggesting that structural barriers may reduce the numeracy returns of education for Latino individuals. Conclusion: This study provides evidence of diminished returns of educational attainment in terms of numeracy scores among Latino individuals. While education is a key determinant of cognitive abilities such as numeracy, its benefits are not equitably distributed across ethnic groups. Structural inequalities particularly in educational opportunities likely contribute to this disparity. Addressing these underlying factors through targeted policy interventions is necessary to promote cognitive equity for Latino populations.
Article
Open Access November 05, 2024

Black-White Gap Across Levels of Educational Childhood Opportunities: Findings from the ABCD Study

Abstract Objective: This study examines racial disparities in educational outcomes—including reading proficiency, grade point average (GPA), school discrimination, and school disciplinary actions—across regions with different levels of educational childhood opportunity index (COI). Our aim is to explore how these racial gaps between Black and White students vary in areas with differing educational [...] Read more.
Objective: This study examines racial disparities in educational outcomes—including reading proficiency, grade point average (GPA), school discrimination, and school disciplinary actions—across regions with different levels of educational childhood opportunity index (COI). Our aim is to explore how these racial gaps between Black and White students vary in areas with differing educational opportunities. We hypothesize that higher COI is associated with smaller academic achievement gaps but may also correspond with greater racial bias in unfair school treatment. Methods: Data were drawn from the Adolescent Brain Cognitive Development (ABCD) study, which provides comprehensive measures of educational outcomes, cognitive performance, and COI. National COI rankings were used to classify regions into five categories: very high, high, average, low, and very low educational opportunity. We analyzed racial gaps in reading proficiency, and experiences of discrimination and suspension across these COI categories. Multi-group Structural Equation Models (SEM) were used to assess how the relationship between race and educational outcomes varies across COI levels. Results: Our findings confirmed that Black-White gaps in reading proficiency and cognitive test performance (Flanker task) were less pronounced in regions with higher COI. However, racial disparities in school disciplinary actions and experiences of discrimination were more pronounced in higher-opportunity areas. Specifically, the effect of Black race was stronger in regions with the highest COI, where Black students experienced a disproportionately higher rate of unfair school treatment, including both school discrimination and suspensions, compared to their White peers. Conclusion: This exploratory study supports that while higher educational opportunities are associated with smaller academic achievement gaps between Black and White students, they might be linked to increased racial bias in school disciplinary actions and discriminatory treatment. These findings underscore the complexity of educational equity, suggesting that improving access to quality education alone is insufficient to eliminate racial disparities in school experiences. Addressing school-based bias and discrimination must accompany efforts to enhance educational opportunities.
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Open Access November 04, 2024

In-Person versus Virtual CEASE Smoking Cessation Interventions

Abstract Background: Smoking cessation interventions are critical for underserved populations, particularly among low-income individuals who may benefit from tailored support. However, the effectiveness of different intervention formats remains unclear, particularly as virtual and hybrid models gain popularity. Aims: This study compares the effectiveness of three smoking cessation intervention [...] Read more.
Background: Smoking cessation interventions are critical for underserved populations, particularly among low-income individuals who may benefit from tailored support. However, the effectiveness of different intervention formats remains unclear, particularly as virtual and hybrid models gain popularity. Aims: This study compares the effectiveness of three smoking cessation intervention arms in a quasi-experimental design: Self-help group (Arm 1), In-person group (Arm 2), and Virtual/hybrid group (Arm 3). The primary outcome was the rate of successful quit across these different intervention modalities. Methods: The study utilized a community-based intervention approach, controlling for potential confounders. The communities were randomized, and this process was blinded. The effectiveness of the In-person group and the Virtual/hybrid group was compared to the Self-help group. The odds ratio (OR) for successful quit rates was calculated for each group, with corresponding 95% confidence intervals (CIs). Results: Participants included 50.4% of women, 82.8% were Black Americans, 11.6% Whites, and 3.4% other races. In-person group (Arm 2) showed a higher rate of successful quit compared to the Self-help group (OR = 2.67, 95% CI = 1.05, 6.79). Virtual/hybrid group (Arm 3) was not associated with a significantly higher quit rate compared to the Self-help group (OR = 1.48, 95% CI = 0.57, 3.83). Conclusion: The In-person group, which utilizes the CEASE curriculum and incorporates peer motivation, proved to be significantly more effective than both the Self-help and Virtual/hybrid groups. The findings suggest that low-income, underserved smokers may not be fully prepared to benefit from virtual interventions, or the current curriculum may need adaptation to better serve their needs in a virtual format.
Article
Open Access October 31, 2024

The Long Shadow of Early Poverty: Poverty at Birth, Epigenetic Changes at Age 15, And Youth Outcomes at Age 22

Abstract Background: Early life socioeconomic conditions and race/ethnicity are critical determinants of long-term health and behavioral outcomes. Epigenetic changes, particularly those measured by the GrimAge biomarker, may mediate the impact of these early adversities on later life outcomes. This study investigates the relationships between race/ethnicity, poverty at birth, epigenetic aging at age [...] Read more.
Background: Early life socioeconomic conditions and race/ethnicity are critical determinants of long-term health and behavioral outcomes. Epigenetic changes, particularly those measured by the GrimAge biomarker, may mediate the impact of these early adversities on later life outcomes. This study investigates the relationships between race/ethnicity, poverty at birth, epigenetic aging at age 15, and subsequent self-rated health, school discipline, depression, and school dropout at age 22. We explored sex differences in these paths. Methods: Data were drawn from the Fragile Families and Child Wellbeing Study (FFCWS), which included 733 youth with comprehensive follow-up data up to age 22. Structural Equation Modeling (SEM) was employed to assess the pathways from race/ethnicity and poverty at birth to epigenetic aging (GrimAge) at age 15, and subsequently to self-rated health and school discipline at age 22. The model controlled for potential confounders including sex, family structure, and parental education. Results: Race/ethnicity and poverty at birth were significantly associated with higher GrimAge scores at age 15 (p < 0.05). Higher GrimAge scores were predictive of poorer self-rated health (β = -0.08, p < 0.05) and increased instances of school discipline (β = 0.13, p < 0.01) at age 22. The indirect effects of race/ethnicity and poverty at birth on self-rated health and school discipline through GrimAge were also significant (p < 0.05), suggesting that epigenetic aging partially mediates these relationships. Sex differences were also observed. Poverty at birth predicted faster epigenetic aging at age 15 for males not females. We also observed that faster epigenetic aging at age 15 was predictive of school discipline of male not female participants at age 22. In contrast, faster epigenetic aging at age 15 was predictive of self-rated health (SRH) of female not male participants at age 22. Conclusions: This study provides evidence that with some sex differences, race/ethnicity and poverty at birth contribute to accelerated epigenetic aging (GrimAge) by age 15, which in turn predicts poorer self-rated health and increased school discipline issues by age 22. These findings emphasize the importance of early interventions targeting social determinants to mitigate long-term health and behavioral disparities. Addressing these early life conditions is crucial for improving health equity and outcomes in young adulthood.
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Open Access October 30, 2024

Social Determinants of Successful Smoking Cessation: An Eight-Year Analysis of Population Assessment of Tobacco and Health (PATH) Data

Abstract Background: Smoking cessation is a crucial public health goal due to its substantial impact on reducing the morbidity and mortality associated with tobacco use. However, significant disparities in smoking cessation success persist across socioeconomic groups in the United States. Objectives: This study aimed to examine differences in smoking cessation rates among daily smokers [...] Read more.
Background: Smoking cessation is a crucial public health goal due to its substantial impact on reducing the morbidity and mortality associated with tobacco use. However, significant disparities in smoking cessation success persist across socioeconomic groups in the United States. Objectives: This study aimed to examine differences in smoking cessation rates among daily smokers based on race, ethnicity, and socioeconomic status (SES) using data from the Population Assessment of Tobacco and Health (PATH) study, spanning waves 1 to 6 (eight years). Methods: Longitudinal data from PATH were analyzed, focusing on baseline daily cigarette smokers followed over an eight-year period to assess cessation outcomes. SES was measured by education and poverty status. Successful smoking cessation was defined as sustained abstinence from cigarettes for 12 months or more at the final wave. Logistic regression models identified predictors of successful cessation, adjusting for potential confounders, including age, nicotine dependence, and access to cessation resources. Results: The analysis revealed significant disparities in cessation success across racial, ethnic, and SES groups. Smokers living in poverty and those with lower educational attainment were less likely to achieve cessation success than their counterparts. Race (Black) and ethnicity (Latino) were also significantly associated with lower cessation success. Conclusions: This study highlights the social determinants of smoking cessation success among U.S. adult smokers, with lower success rates observed among those in poverty and with less educational attainment. These findings emphasize the need for targeted interventions that address the unique barriers to cessation faced by low-SES groups. Public health strategies should prioritize equitable access to cessation resources and culturally tailored interventions to reduce these disparities and improve cessation outcomes among all smokers.
Article
Open Access October 19, 2024

Quantitative Intersectionality Scoring System (QISS): Opportunities for Enhancing Predictive Modeling, Comparative Analysis, Health Needs Assessment, and Policy Evaluation

Abstract Intersectionality has significantly enhanced our understanding of how overlapping social identities—such as race, ethnicity, gender, sex, class, and sexual orientation—interact to shape individual experiences. However, despite its theoretical importance, much of the existing literature has relied on qualitative approaches to define and study intersectionality, limiting its application in [...] Read more.
Intersectionality has significantly enhanced our understanding of how overlapping social identities—such as race, ethnicity, gender, sex, class, and sexual orientation—interact to shape individual experiences. However, despite its theoretical importance, much of the existing literature has relied on qualitative approaches to define and study intersectionality, limiting its application in predictive modeling, comparative analysis, and policy development. This paper introduces the concept of Quantitative Intersectionality Scoring System (QISS), a novel approach that assigns numerical scores to intersecting identities, thereby enabling a more systematic and data-driven analysis of intersectional effects. We argue that QISS can substantially enhance the utility and predictive validity of quantitative models by capturing the complexities of multiple, overlapping social determinants. By presenting concrete examples, such as the varying impacts of socioeconomic mobility on life expectancy among different intersectional groups, we demonstrate how QISS can yield more precise and reliable forecasts. Such a shift would allow policymakers and service providers to dynamically assess economic and health needs, as well as the uncertainties around them, as individuals move through different social and economic contexts. QISS-based models could be more responsive to the complexities of intersecting identities, allowing for a more quantified and nuanced evaluation of policy interventions. We conclude by discussing the challenges of implementing QISS and emphasizing the need for further research to validate these quantifications using robust quantitative methods. Ultimately, adopting QISS has the potential to improve the accuracy of predictive models and the effectiveness of policies aimed at promoting social justice and health equity.
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Perspective
Open Access September 12, 2024

Assessment of Coping Strategies Among Nursing Students: Basis for Psychological First Aid

Abstract Background: Telomere length is a critical biomarker of cellular aging and overall health. While childhood socioeconomic status (SES) indicators such as education and poverty can have long-lasting effects on biological aging, research has shown contradictory results regarding the impact of adulthood SES on future telomere length, particularly in racially and ethnically diverse individuals. [...] Read more.
Background: Telomere length is a critical biomarker of cellular aging and overall health. While childhood socioeconomic status (SES) indicators such as education and poverty can have long-lasting effects on biological aging, research has shown contradictory results regarding the impact of adulthood SES on future telomere length, particularly in racially and ethnically diverse individuals. This study investigates the effects of baseline adulthood SES indicators such as education and poverty on telomere length nine years later in women, using data from the Future of Families and Child Wellbeing Study (FFCWS). Methods: We analyzed data from the FFCWS, a longitudinal cohort study. The sample included baseline adulthood SES and follow-up telomere length measure of women (n = 2,421) with varying socioeconomic conditions. Telomere length was measured from saliva samples nine years after the baseline measure of adulthood SES. Education, poverty, and marital status at baseline were assessed. Multivariate linear regression models were used to examine the association between adulthood SES indicators at baseline and future telomere length, controlling for potential confounders. Results: From the total 2,421 women, 675 were Latino White, 1,158 were non-Latino Black, and 588 were non-Latino White. Our findings indicate that for non-Latino White women poverty at certain level, and childbirth weight, and for non-Latino Black maternal age were predictors of telomere lengths nine years later. Conclusion: Poverty at a specific level, maternal age and childbirth weight serve as predictors of telomere lengths nine years later in some women. These findings underscore the importance of socioeconomic factors and early-life influences in understanding telomere dynamics and aging processes among women from varied racial and ethnic backgrounds.
Article
Open Access September 10, 2024

Does Adulthood Socioeconomic Status Predict Subsequent Telomere Length in Racially and Ethnically Diverse Women?

Abstract Background: Telomere length is a critical biomarker of cellular aging and overall health. While childhood socioeconomic status (SES) indicators such as education and poverty can have long-lasting effects on biological aging, research has shown contradictory results regarding the impact of adulthood SES on future telomere length, particularly in racially and ethnically diverse individuals. [...] Read more.
Background: Telomere length is a critical biomarker of cellular aging and overall health. While childhood socioeconomic status (SES) indicators such as education and poverty can have long-lasting effects on biological aging, research has shown contradictory results regarding the impact of adulthood SES on future telomere length, particularly in racially and ethnically diverse individuals. This study investigates the effects of baseline adulthood SES indicators such as education and poverty on telomere length nine years later in women, using data from the Future of Families and Child Wellbeing Study (FFCWS). Methods: We analyzed data from the FFCWS, a longitudinal cohort study. The sample included baseline adulthood SES and follow-up telomere length measure of women (n = 2,421) with varying socioeconomic conditions. Telomere length was measured from saliva samples nine years after the baseline measure of adulthood SES. Education, poverty, and marital status at baseline were assessed. Multivariate linear regression models were used to examine the association between adulthood SES indicators at baseline and future telomere length, controlling for potential confounders. Results: From the total 2,421 women, 675 were Latino White, 1,158 were non-Latino Black, and 588 were non-Latino White. Our findings indicate that for women in our study, no adulthood SES indicators such as poverty status, education, or marital status at baseline were predictive of telomere lengths nine years later. Conclusion: Our observations challenge that expected longitudinal association between adulthood SES indicators and subsequent telomere length almost a decade later in racially and ethnically diverse group of women. These findings underscore the need for additional research on the validity of TL as a mediator of the effects of adulthood SES on future rate of biological aging.
Article
Open Access September 07, 2024

Stable Relationships

Abstract We study a dynamic model of the relationship between two people where the states depend on the “power” in the relationship. We perform a comprehensive analysis of stability of the system, and determine a set of conditions under which stable relationships are possible. In particular, stable relationships can occur if both people are dominant, but the sum of dominances is below a bound determined by [...] Read more.
We study a dynamic model of the relationship between two people where the states depend on the “power” in the relationship. We perform a comprehensive analysis of stability of the system, and determine a set of conditions under which stable relationships are possible. In particular, stable relationships can occur if both people are dominant, but the sum of dominances is below a bound determined by the model’s parameters. Stable relationships can also occur if one person is dominant and the other is submissive, provided the level of dominance exceeds the level of submissiveness but not beyond a threshold. We also conclude that a stable relationship is not possible if both people are submissive. While our model is motivated by a social or romantic relationship, it can also be applied to professional or business relationships, diplomatic relationships between nations, and certain biological interactions between organisms and between automated agents or robots.
Article
Open Access September 05, 2024

Caste-based Diminished Returns of Educational Attainment on Wealth Accumulation in India

Abstract Background: Education is widely recognized as a key driver of wealth generation, providing individuals with the opportunity to enhance their socioeconomic status. However, the effectiveness of education in generating wealth varies significantly across different social groups. In the United States, research has shown that Black individuals experience weaker economic returns on education [...] Read more.
Background: Education is widely recognized as a key driver of wealth generation, providing individuals with the opportunity to enhance their socioeconomic status. However, the effectiveness of education in generating wealth varies significantly across different social groups. In the United States, research has shown that Black individuals experience weaker economic returns on education compared to their White counterparts, a phenomenon explained by the theory of Minorities' Diminished Returns (MDRs). Although MDRs have been documented in various countries, their relevance to caste-based disparities in India remains unexplored. Objective: This study aims to investigate the caste-based diminished returns of education on wealth in India. We hypothesize that the returns on educational attainment, in terms of wealth generation, will be weaker for individuals from Scheduled Castes (SCs) compared to those from higher castes, using data from the India Demographic and Health Surveys (DHS). Methods: This study was a cross-sectional analysis of DHS -2019/2021 data from India, examining the relationship between educational attainment and wealth across different caste groups (scheduled castes and non-scheduled castes). Multivariate regression models will be employed to assess the interaction between caste and education in predicting wealth outcomes, controlling for relevant covariates such as age, gender, and region. Results: The study is expected to find that the returns on education, in terms of wealth, are significantly weaker for individuals from Scheduled Castes compared to those from higher castes. This would indicate that caste-based discrimination continues to hinder the economic progress of Scheduled Castes, even when they achieve similar levels of education as their upper-caste counterparts. Conclusion: The findings of this study will extend the MDR framework to the Indian context, demonstrating that caste-based disparities result in diminished returns on education for wealth generation. This study underscores the need for targeted policies that address the specific barriers faced by Scheduled Castes in translating educational attainment into economic success and highlights the ongoing impact of caste-based discrimination in India.
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Open Access September 04, 2024

Cognitive and Psychological Mediators of the Social Gradient in Tobacco Use Initiation Among Adolescents: Evidence from the ABCD Study

Abstract Background: Tobacco use among adolescents is a significant public health concern, with early initiation leading to long-term health risks. Understanding the factors that contribute to the initiation of tobacco use is crucial for developing effective prevention strategies. This study investigates the roles of substance use harm knowledge and tobacco susceptibility in mediating the [...] Read more.
Background: Tobacco use among adolescents is a significant public health concern, with early initiation leading to long-term health risks. Understanding the factors that contribute to the initiation of tobacco use is crucial for developing effective prevention strategies. This study investigates the roles of substance use harm knowledge and tobacco susceptibility in mediating the relationship between social gradients (race, ethnicity, and socioeconomic status) and tobacco use initiation among adolescents. Methods: Data from the Adolescent Brain Cognitive Development (ABCD) study, comprising a racially, ethnically, and economically diverse sample of tobacco-naive adolescents aged 9 to 16, were analyzed. Structural equation modeling (SEM) was used to test whether substance use harm knowledge and tobacco susceptibility mediate the effects of socioeconomic status (SES) on the initiation of tobacco use. Results: Findings indicated that both substance use harm knowledge and tobacco susceptibility partially mediate the relationship between SES and tobacco use initiation. Adolescents from lower SES backgrounds exhibited lower levels of harm knowledge and higher levels of tobacco susceptibility, which increased their likelihood of initiating tobacco use. Conclusion: This study highlights the complex interplay between social determinants and individual cognitive and psychological factors in influencing tobacco use initiation among adolescents. Public health interventions that enhance harm knowledge and reduce susceptibility to tobacco use are crucial for preventing initiation, particularly among racially, ethnically, and economically diverse adolescents. These efforts can help reduce health disparities and promote health equity.
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Open Access September 04, 2024

Social Epidemiology of Early Initiation of Electronic and Conventional Cigarette Use in Early to Middle Adolescents

Abstract Background: Early initiation of tobacco use among adolescents is a significant public health concern. While there is extensive research on overall tobacco use, much of it focuses on initiation in late adolescence, uses cross-sectional designs, and lacks specific exploration of electronic versus conventional cigarette use. This study aims to investigate social determinants influencing the [...] Read more.
Background: Early initiation of tobacco use among adolescents is a significant public health concern. While there is extensive research on overall tobacco use, much of it focuses on initiation in late adolescence, uses cross-sectional designs, and lacks specific exploration of electronic versus conventional cigarette use. This study aims to investigate social determinants influencing the early initiation of electronic and conventional cigarette use among U.S. adolescents. Methods: We utilized data from the Adolescent Brain Cognitive Development (ABCD) study, which follows a cohort of tobacco-naïve children from age nine through age 16. The social determinants examined included household income, parental education, financial difficulties, racial/ethnic minority status, family structure, neighborhood income, and gender minority status. Structural equation models were employed to assess associations between these determinants and early initiation of electronic and conventional cigarette use. Results: Male gender was associated with a higher likelihood of conventional cigarette use, while the risk of early initiation of electronic cigarette use was similar across genders. White adolescents were at a higher risk of conventional cigarette use; however, the risk for electronic cigarette use was comparable across White and non-White groups. Financial difficulties were linked to an increased likelihood of early initiation of conventional cigarette use but not electronic cigarette use. Higher household income was associated with a reduced risk of initiating conventional cigarettes but did not significantly impact electronic cigarette use. Adolescents from married families were less likely to initiate electronic cigarette use. No significant effects were found for parental education or neighborhood income on the initiation of either type of cigarette use. Age did not significantly affect the initiation of either cigarette type, and gender minority status was marginally associated with early initiation of conventional cigarette use. Conclusions: The social patterning of electronic cigarette use differs from that of conventional cigarette use, suggesting that distinct tobacco products do not pose a uniform risk across all adolescents. This study underscores the importance of tailored prevention efforts that address the unique challenges associated with early initiation of electronic and conventional cigarette use among adolescents. The differential risk factors identified suggest targeted prevention strategies for conventional cigarette use, focusing on financial difficulties, household income, and gender-specific interventions. In contrast, prevention efforts for electronic cigarette use may require broader, more inclusive approaches that address all adolescents, regardless of their background. Comprehensive universal screening for electronic cigarette use and targeted screening for conventional cigarette use among adolescents are recommended.
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Open Access August 30, 2024

Exploring the Benefits of Forgiveness among Adolescents in Junior High Schools in Bimbilla in Ghana: A Comparative Study Based on Age

Abstract This study investigates the benefits of forgiveness among adolescents in Junior High Schools (JHS) in Bimbilla, Ghana, focusing on the influence of age on the effectiveness of forgiveness interventions. The study adopted a mixed-method experimental design, a purposive selection of eight JHSs within the Nanumba North Municipality, from which 60 adolescents were randomly chosen to participate. The [...] Read more.
This study investigates the benefits of forgiveness among adolescents in Junior High Schools (JHS) in Bimbilla, Ghana, focusing on the influence of age on the effectiveness of forgiveness interventions. The study adopted a mixed-method experimental design, a purposive selection of eight JHSs within the Nanumba North Municipality, from which 60 adolescents were randomly chosen to participate. The study employed the Enright Forgiveness Inventory, Depression Mood Scale, and Anger Self-Report items to assess participants' emotional states before and after the intervention. The interventions were structured around the REACH model of forgiveness, which included sessions aimed at helping participants identify sources of hurt, understand the concept of forgiveness, and recognise the emotional costs of holding onto grievances. Qualitative data were analysed into themes using an interpretative lens. A two-way Analysis of Covariance (ANCOVA) was used to analyse the data. The findings revealed that exposure to forgiveness therapies significantly reshaped participants' negative emotions, leading to a marked decrease in feelings of anger and depression. Post-intervention assessments indicated that participants developed a more positive outlook towards their offenders, highlighting the transformative power of forgiveness in fostering emotional well-being. The study's results align with previous research, indicating that forgiveness interventions can effectively reduce negative emotional states and promote psychological resilience. The implications of these findings suggest that integrating forgiveness education into school curricula could be beneficial for enhancing the mental health of adolescents. By fostering an environment that encourages forgiveness, educators and mental health professionals can help mitigate the adverse effects of unresolved emotional conflicts, ultimately contributing to healthier interpersonal relationships and improved overall well-being among young individuals.
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Open Access August 29, 2024

Adversities Mediate Social Determinants of Youth Tobacco Use Initiation

Abstract Background: Social determinants of health (SDOH) significantly influence health behaviors, including tobacco use among youth. Adversities such as perceived discrimination, perceived neighborhood stress, life trauma, and financial strain are stressors that may mediate the relationship between various SDOH and youth tobacco use. This study aims to investigate whether multidimensional adversities [...] Read more.
Background: Social determinants of health (SDOH) significantly influence health behaviors, including tobacco use among youth. Adversities such as perceived discrimination, perceived neighborhood stress, life trauma, and financial strain are stressors that may mediate the relationship between various SDOH and youth tobacco use. This study aims to investigate whether multidimensional adversities mediate the effects of SDOH on tobacco use among youth. Methods: Data from the Adolescent Brain Cognitive Development (ABCD) study were used to test our hypotheses. The sample included a diverse cohort of youth aged 9-10 years old followed until they were 15-16 years old. We examined the effects of baseline parental education, household income, neighborhood income, and family structure on subsequent youth tobacco use. Structural equation models were used to test if adversities (perceived discrimination, life trauma, financial strain) operate as potential mediators. Results: All ABCD participants were eligible for our analysis, regardless of race, ethnicity, or SDOHs (n = 11,878). The findings indicated that the effects of parental education, household income, neighborhood income, and family structure on youth tobacco use were partially mediated by adversities. Higher levels of parental education and household income were associated with lower tobacco use, and this relationship was weakened when accounting for adversities. Similarly, stable family structures and higher neighborhood income were linked to reduced tobacco use, with adversities playing a mediating role. Conclusions: Multidimensional adversities partially mediate the relationship between SDOH at baseline and subsequent youth tobacco use. Interventions aimed at reducing youth tobacco use should address both the social determinants and multiple adversities experienced by adolescents. Policies to improve the educational and economic situations of families, enhance neighborhood environments, and support stable family structures all reduce youth tobacco use, with lower exposure to adversities explaining this effect.
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Open Access August 27, 2024

Tobacco Susceptibility Explains Diminished Returns of Family Income on Black Adolescents' Tobacco Initiation

Abstract Background: Minorities’ Diminished Returns (MDRs) theory posits that socioeconomic resources have weaker protective effects on health and behavior for racial and ethnic minorities compared to Whites. This study examines whether tobacco susceptibility, defined as curiosity, intention, and openness to future tobacco use, mediates the diminished returns of family income on tobacco initiation [...] Read more.
Background: Minorities’ Diminished Returns (MDRs) theory posits that socioeconomic resources have weaker protective effects on health and behavior for racial and ethnic minorities compared to Whites. This study examines whether tobacco susceptibility, defined as curiosity, intention, and openness to future tobacco use, mediates the diminished returns of family income on tobacco initiation among Black adolescents. Methods: Data from the Adolescent Brain Cognitive Development (ABCD) Study were analyzed. Participants were followed from age 9 to 16. All participants were tobacco naïve at baseline. Tobacco susceptibility was assessed through self-reported measures of curiosity, intention, and openness to future tobacco use. Structural equation modeling (SEM) was used to examine the relationship between family income, tobacco susceptibility, and tobacco initiation. Results: Overall, 10,653 Black or White youth entered our analysis. The analysis revealed that higher family income was less effective in preventing tobacco initiation among Black adolescents. Tobacco susceptibility significantly predicted tobacco initiation and partially mediated the relationship between family income and tobacco initiation. Conclusions: Tobacco susceptibility explains some of the diminished returns of family income on tobacco initiation among Black adolescents. Interventions aimed at reducing tobacco susceptibility may enhance the protective effects of family income and help mitigate health disparities.
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Open Access August 27, 2024

Role of Impulsivity in Explaining Social Gradient in Youth Tobacco Use Initiation: Does Race Matter?

Abstract Background: Socioeconomic status (SES) is traditionally viewed as a protective factor against impulsivity and subsequent tobacco use in youth. The prevailing model suggests that higher SES is associated with lower impulsivity, which in turn reduces the likelihood of future tobacco use. However, this pathway may not hold uniformly across racial groups due to differences in impulsivity and [...] Read more.
Background: Socioeconomic status (SES) is traditionally viewed as a protective factor against impulsivity and subsequent tobacco use in youth. The prevailing model suggests that higher SES is associated with lower impulsivity, which in turn reduces the likelihood of future tobacco use. However, this pathway may not hold uniformly across racial groups due to differences in impulsivity and the phenomenon of Minorities' Diminished Returns (MDRs), where the protective effects of SES, such as educational attainment, tend to be weaker or even reversed for Black youth compared to their White counterparts. Objectives: This study aims to examine the racial heterogeneity in the pathway from childhood SES to impulsivity and subsequent tobacco use initiation during adolescence, focusing on differences between Black and White youth. Methods: Data were drawn from the Adolescent Brain Cognitive Development (ABCD) Study, which includes a diverse sample of youth aged 9 to 16 years. The analysis examined the relationship between baseline family SES (age 9), impulsivity (age 9), and subsequent tobacco use (ages 9 to 16). Impulsivity was measured using the Urgency, Premeditation (lack of), Perseverance (lack of), Sensation Seeking, and Positive Urgency Impulsive Behavior Scale (UPPS-P). Structural equation modeling (SEM) was employed, with analyses stratified by race to explore potential differences in these associations. Results: Overall, 6,161 non-Latino White and 1,775 non-Latino Black adolescents entered our analysis. In the full sample, higher family SES was linked to lower childhood impulsivity and, consequently, less tobacco uses in adolescence. However, racial differences emerged upon stratification. Among White youth, higher SES was associated with lower impulsivity, leading to reduced tobacco use, consistent with the expected model. In contrast, among Black youth, higher SES was not associated with lower impulsivity, thereby disrupting the protective effect of SES on tobacco use through this pathway. These findings suggest that racial heterogeneity exists in the SES-impulsivity-tobacco use pathway, aligning with the MDRs framework, which highlights how structural factors may weaken the protective effects of high SES among Black youth. Conclusions: These findings underscore the importance of considering racial heterogeneity in the relationships between SES, impulsivity, and tobacco use. The observed disparities suggest a need for targeted interventions that address the unique challenges faced by Black youth, who may not experience the same protective benefits of high SES as their White peers. These results carry significant implications for public health strategies aimed at reducing tobacco use in racially diverse populations.
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Open Access August 18, 2024

Extreme Heat Exposure Is Associated with Higher Socioeconomic Disadvantage and Elevated Youth Delinquency

Abstract Background: Climate change has led to an increase in the frequency and intensity of extreme heat events, a trend expected to continue. This poses significant health risks, particularly for vulnerable populations like children. While previous research has largely concentrated on the physical health impacts of extreme heat, less attention has been given to behavioral outcomes, such as [...] Read more.
Background: Climate change has led to an increase in the frequency and intensity of extreme heat events, a trend expected to continue. This poses significant health risks, particularly for vulnerable populations like children. While previous research has largely concentrated on the physical health impacts of extreme heat, less attention has been given to behavioral outcomes, such as delinquency. Objectives: This study investigates the association between extreme heat exposure and delinquency among children, utilizing data from the Adolescent Brain Cognitive Development (ABCD) study. It also explores the potential mediating roles of neighborhood socioeconomic status (SES; measured by median home value), puberty, peer deviance, and financial difficulties. Methods: Data from the national ABCD study were analyzed to assess the relationship between extreme heat exposure (exposure) and delinquency (outcome). Covariates included race/ethnicity, sex, and age. Mediators examined were neighborhood SES, puberty, peer deviance, and financial difficulties. Structural equation modeling (SEM) was employed for data analysis. Results: Overall, 11,878 children entered our analysis. The analysis revealed a significant association between extreme heat exposure and higher levels of delinquency among children. Children more exposed to extreme heat were more likely to be Black, reside in lower SES neighborhoods, experience greater financial difficulties, and have more advanced puberty status. The group facing the highest heat exposure was also economically disadvantaged. Conclusions: The findings suggest that children already disadvantaged by socio-economic factors are disproportionately affected by extreme heat, leading to increased delinquency. This highlights the need for targeted interventions to protect these vulnerable populations and address the mediators of extreme heat exposure. Future research should focus on longitudinal studies and evaluate the effectiveness of various mitigation strategies to address these disparities.
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Article
Open Access August 17, 2024

Socioeconomic Status Partially Mediates the Effects of Structural Racism on Youth Tobacco Use Initiation

Abstract Background: Recent research has identified structural racism—systemic policies and practices that perpetuate racial inequalities—as a significant social determinant of population health. Studies utilizing data from the Adolescent Brain Cognitive Development (ABCD) study have shown an association between higher levels of state-level structural racism and increased tobacco use among youth in [...] Read more.
Background: Recent research has identified structural racism—systemic policies and practices that perpetuate racial inequalities—as a significant social determinant of population health. Studies utilizing data from the Adolescent Brain Cognitive Development (ABCD) study have shown an association between higher levels of state-level structural racism and increased tobacco use among youth in the United States. However, there has been limited exploration of the psychosocial mediators of this relationship, particularly in the context of youth aged 10-16 years. Objective: This study aimed to assess the roles of socioeconomic status (SES), tobacco susceptibility, and perceived discrimination as potential mediators in the relationship between state-level structural racism and youth tobacco initiation rates. Methods: We analyzed data from the ABCD study, a nationally representative longitudinal survey of 11,698 youth followed from ages 9/10 to 15/16. These data were combined with state-level indicators of structural racism. We employed structural equation modeling (SEM) to investigate the mediators of the association between structural racism and self-reported initiation of tobacco use, while controlling for individual and state-level covariates. Results: Our findings indicate that higher levels of structural racism were associated with increased rates of tobacco initiation among youth. This relationship was partially mediated by lower SES, but not by perceived discrimination or tobacco susceptibility. Conclusion: The association between structural racism and youth tobacco initiation appears to be influenced in part by the lower SES prevalent in states with higher levels of racism. These results highlight the need for addressing both racism and SES inequalities as key strategies for reducing tobacco disparities among youth.
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Open Access August 13, 2024

A Study of the Implementation of the Language-In-Education Policy in Three Primary Schools in Ghana

Abstract This study investigated the English-only language-in-education policy in three primary schools in Ghana: University Primary, OLA Presby Primary and Apewusika Primary School in the Cape Coast Metropolitan in the Central Region of Ghana. The study employed Coulmas’s (2005) eight-step language planning model as a conceptual framework for the study. Nine teachers were randomly selected from Basic One [...] Read more.
This study investigated the English-only language-in-education policy in three primary schools in Ghana: University Primary, OLA Presby Primary and Apewusika Primary School in the Cape Coast Metropolitan in the Central Region of Ghana. The study employed Coulmas’s (2005) eight-step language planning model as a conceptual framework for the study. Nine teachers were randomly selected from Basic One to Basic Three to respond to the selection and supply items. The selected items were analysed and put into frequencies and percentages, while the supply items were coded into recurrent themes. Findings from data indicate that most teachers preferred using the local language (Fante) as a medium of instruction in the lower primary. The study also revealed that code missing is a significant feature in teacher-learner interaction. It was also observed that teachers encountered little problems when using Fante as a medium of instruction. Finally, most teachers express a lukewarm attitude towards using English as a medium of instruction in the lower primary school.
Article
Open Access July 18, 2024

Household Income and Offspring Education Explain Blacks’ Diminished Returns of Parental Education

Abstract Background: High parental education promotes various aspects of offspring well-being including reducing their risk of depression/anxiety, criminal justice involvement, and welfare reliance. However, according to minorities’ diminished returns, these benefits are not equal across racial groups, with Black families experiencing diminished returns of parental education compared to White [...] Read more.
Background: High parental education promotes various aspects of offspring well-being including reducing their risk of depression/anxiety, criminal justice involvement, and welfare reliance. However, according to minorities’ diminished returns, these benefits are not equal across racial groups, with Black families experiencing diminished returns of parental education compared to White families. This study explores the role of household income and offspring educational attainment as potential serial pathways that operate as mechanisms underlying diminished returns of parental education on offspring outcomes in Black families. Gender differences in these effects were also explored. Methods: Utilizing data from the Future of Families and Child Wellbeing Study (FFCWS) over a 22-year follow-up period (seven waves), we examined the serial mediation by household income and offspring educational attainment in explaining the relationship between parental education and offspring outcomes namely depression, anxiety, criminal justice involvement, and welfare reliance [Temporary Assistance for Needy Families (TANF) and Supplemental Nutrition Assistance Program (SNAP)]. We used structural equation modeling (SEM) with household income as the first mediator and young adult education as the second mediator. Multi-group models were used to explore gender differences in these paths. Results: The study confirmed the role of our proposed serial mediators for Blacks’ weaker effects of parental education on offspring outcomes. We observed weaker effects of first affects household income, with this effect being for Black families compared to White families, which then impacted educational attainment of the offspring. The findings indicate that household income plays a crucial mediating role, but its effect is weaker in Black families. Additionally, the educational attainment of offspring from highly educated Black parents is less effective in improving outcomes compared to their White peers, further contributing to diminished returns. Some gender differences were observed for the effects of educational attainment on economic and health outcomes of young adults. Conclusions: The study underscores the need to reconsider traditional assumptions about the comparability of family conditions and outcomes across racial groups with similar levels of parental education. The findings highlight the importance of targeted policies and interventions aimed at enhancing the economic stability and educational outcomes of Black families to address these disparities. Policies should focus on promoting the economic well-being of highly educated Black parents and improving the educational outcomes of their children.
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Open Access July 16, 2024

Management of Saltwater Intrusion in Coastal Aquifers: A Review and Case Studies from Egypt

Abstract Groundwater is undeniably crucial to people's lives, particularly in coastal regions. Therefore, it is imperative to address this vital water source strategically and implement a management plan to maintain its optimal state. The salinization of groundwater poses a significant challenge for coastal communities, stemming from factors like excessive groundwater extraction from coastal aquifers, [...] Read more.
Groundwater is undeniably crucial to people's lives, particularly in coastal regions. Therefore, it is imperative to address this vital water source strategically and implement a management plan to maintain its optimal state. The salinization of groundwater poses a significant challenge for coastal communities, stemming from factors like excessive groundwater extraction from coastal aquifers, reduced recharge, rising sea levels, climate change, and other causes. Saltwater intrusion (SWI) is a prevalent issue that needs attention, as it significantly threatens groundwater quantity and quality. SWI happens when saline water infiltrates coastal aquifers, contaminating freshwater supplies. This review article aims to define SWI, explore its causes and influencing factors, and discuss various monitoring techniques. Additionally, it examines different modeling methods and management tools, including remote sensing, field surveys, modeling approaches, and optimization techniques. To mitigate the adverse effects of SWI, several control measures are outlined, along with their pros and cons. The final section reviews previous SWI studies and case studies from the Nile Delta, Sinai Peninsula, and North-West coast in Egypt. These studies offer suggestions, adaptations, and mitigation measures for future research.
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Review Article
Open Access July 16, 2024

Poverty Status at Birth Predicts Epigenetic Changes at Age 15

Abstract We used 15 years of follow up of 854 racially and ethnically diverse birth cohort who were followed from birth to age 15. Structural equation modeling (SEM) was used to examine the effects of race/ethnicity, maternal education, and family structure on poverty at birth, as well as the effects of poverty at birth on epigenetic changes at age 15. We also explored variations by sex. Results: [...] Read more.
We used 15 years of follow up of 854 racially and ethnically diverse birth cohort who were followed from birth to age 15. Structural equation modeling (SEM) was used to examine the effects of race/ethnicity, maternal education, and family structure on poverty at birth, as well as the effects of poverty at birth on epigenetic changes at age 15. We also explored variations by sex. Results: Our findings indicate that Black and Latino families had lower maternal education and married family structure which in turn predicted poverty at birth. Poverty at birth then was predictive of epigenetic changes 15 years later when the index child was 15. This suggested that poverty at birth partially mediates the effects of race/ethnicity, maternal education, and family structure on epigenetic changes of youth at age 15. There was an effect of poverty status at birth on DNA methylation of male but not female youth at age 15. Thus, poverty at birth may have a more salient effect on long term epigenetic changes of male than female youth. Conclusions: Further studies are needed to understand the mechanisms underlying the observed sex differences in the effects of poverty as a mechanism that connects race/ethnicity, maternal education, and family structure to epigenetic changes later in life.
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Open Access July 15, 2024

The Role of Dignity and Respect in Maternity Care: An Integrative Literature Review

Abstract This integrative literature review aims to explore the pivotal role of dignity and respect in maternity care, focusing on their profound impact on the experiences of pregnant individuals. Emphasis is placed on cultural competence as a crucial factor in fostering understanding and respect for diverse backgrounds, promoting inclusive approaches to maternal care. The overarching goal is to underscore [...] Read more.
This integrative literature review aims to explore the pivotal role of dignity and respect in maternity care, focusing on their profound impact on the experiences of pregnant individuals. Emphasis is placed on cultural competence as a crucial factor in fostering understanding and respect for diverse backgrounds, promoting inclusive approaches to maternal care. The overarching goal is to underscore the significance of dignified and respectful care in enhancing maternal satisfaction, postpartum outcomes, and overall well-being. Methods: The review synthesizes existing literature (n=22) on maternity care, dignity, and respect, drawing insights from diverse sources to comprehensively analyze the multifaceted nature of this critical healthcare aspect. Cultural competence is explored as a key theme in understanding and appreciating the varied backgrounds of pregnant individuals. The analysis encompasses factors such as effective communication, healthcare provider attitudes, cultural competence, informed consent, and systemic considerations, shedding light on their collective influence on dignity and respect in maternity care. Principal Findings: The literature review reveals that providing dignified and respectful care significantly contributes to improving maternal satisfaction and postpartum outcomes. Cultural competence emerges as a crucial element, ensuring that care approaches are inclusive and tailored to diverse cultural backgrounds. Effective communication, positive healthcare provider attitudes, and considerations for systemic factors are identified as key determinants of the dignity and respect experienced by pregnant individuals. The findings underscore the interconnectedness of these factors in shaping the overall quality of maternity care. Practical Applications: Recommendations stemming from the literature review include interventions aimed at enhancing healthcare providers' communication skills, cultural competence training, and the promotion of patient-centered care models. Acknowledging the systemic factors influencing maternity care, the review calls for collaborative efforts among healthcare providers, policymakers, and researchers to create an environment that upholds pregnant individuals' autonomy and values. The practical applications emphasize the need for comprehensive and culturally sensitive approaches to ensure that all pregnant individuals receive dignified and respectful care. In summary, this integrative literature review provides a comprehensive understanding of the critical role of dignity and respect in maternity care, offering insights into effective strategies for improvement and emphasizing the importance of cultural competence and collaborative efforts in shaping the future of maternal healthcare.
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Review Article
Open Access July 12, 2024

Race, Poverty Status at Birth, and DNA Methylation of Youth at Age 15

Abstract Epigenetic studies, which can reflect biological aging, have shown that measuring DNA methylation (DNAm) levels provides new insights into the biological effects of social environment and socioeconomic position (SEP). This study explores how race, family structure, and SEP (income to poverty ratio) at birth influence youth epigenetic aging at age 15. Data were obtained from the Future [...] Read more.
Epigenetic studies, which can reflect biological aging, have shown that measuring DNA methylation (DNAm) levels provides new insights into the biological effects of social environment and socioeconomic position (SEP). This study explores how race, family structure, and SEP (income to poverty ratio) at birth influence youth epigenetic aging at age 15. Data were obtained from the Future of Families and Child Wellbeing Study (FFCWS) cohort, with GrimAge used as a measure of DNAm levels and epigenetic aging. Our analysis included 854 racially and ethnically diverse participants followed from birth to age 15. Structural equation modeling (SEM) examined the relationships among race, SEP at birth, and epigenetic aging at age 15, controlling for sex, ethnicity, and family structure at birth. Findings indicate that race was associated with lower SEP at birth and faster epigenetic aging. Specifically, income to poverty ratio at birth partially mediated the effects of race on accelerated aging by age 15. The effect of income to poverty ratio at birth on DNAm was observed in male but not female youth at age 15. Thus, SEP partially mediated the effect of race on epigenetic aging in male but not female youth. These results suggest that income to poverty ratio at birth partially mediates the effects of race on biological aging into adolescence. These findings highlight the long-term biological impact of early-life poverty in explaining racial disparities in epigenetic aging and underscore the importance of addressing economic inequalities to mitigate these disparities. Policymakers should focus on poverty prevention in Black communities to prevent accelerated biological aging and associated health risks later in life. Interventions aimed at eliminating poverty and addressing racial inequities could have significant long-term benefits for public health. Future research should explore additional factors contributing to epigenetic aging and investigate potential interventions to slow down the aging process. Further studies are needed to understand the mechanisms underlying these associations and to identify effective strategies for mitigating the impact of SEP and racial disparities on biological aging.
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Open Access July 12, 2024

Racial Gap in Household Income Explains Black-White Disparities in the Intergenerational Transmission of Educational Attainment

Abstract Background: Racial disparities in educational outcomes persist in the United States, with Black individuals experiencing lower levels of educational attainment and a higher rate of school disciplinary actions compared to their White counterparts. Parental education is a known predictor of offspring educational attainment, but its effects may vary by race. Understanding the role of household [...] Read more.
Background: Racial disparities in educational outcomes persist in the United States, with Black individuals experiencing lower levels of educational attainment and a higher rate of school disciplinary actions compared to their White counterparts. Parental education is a known predictor of offspring educational attainment, but its effects may vary by race. Understanding the role of household income in mediating these effects is crucial for developing targeted policy interventions to reduce educational inequalities. Objectives: This study aimed to examine the role of household income in mediating the differential effects of maternal education on two youth educational outcomes (educational attainment by age 22 and school disciplinary action) in Black and White families. Methods: Data were drawn from the 22 years of follow-up of the Future of Families and Child Wellbeing Study (FFCWS), a longitudinal study following a cohort of children born in large U.S. cities between 1998 and 2000. Participants included 1,647 Black and 689 White young adults who were followed from birth to age 22. Maternal education, household income, family structure, and paternal incarceration were assessed at baseline (birth), and two youth educational outcomes, namely educational attainment and any school disciplinary action, were assessed at age 22 (emerging adulthood). Using structural equation modeling (SEM), mediation analysis was conducted to examine whether household income partially mediates the effects of maternal education on youth educational outcomes, with race (Black vs. White) as the moderator. Results: The results indicated that maternal education was positively associated with youth educational attainment and negatively associated with school disciplinary actions in the pooled sample that included both Black and White families. However, the effect of parental education on educational attainment at age 22 was weaker for Black than White families. Household income partially mediated racial differences in the effect of maternal education on youth educational attainment. The results suggest that lower household income in Black families is why we observe a weaker effect of parental education on youth educational attainment for Black youth compared to White youth. Conclusions: Findings suggest that the lower household income of families is one of the reasons high maternal education levels are associated with lower youth educational attainment in Black than White families. Addressing income disparities through tax policies may help reduce racial disparities in education and promote educational equity for Black youth.
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Open Access June 28, 2024

Nigeria Exchange Rate Volatility: A Comparative Study of Recurrent Neural Network LSTM and Exponential Generalized Autoregressive Conditional Heteroskedasticity Models

Abstract Business merchants and investors in Nigeria are interested in the foreign exchange volatility forecasting accuracy performance because they need information on how volatile the exchange rate will be in the future. In the paper, we compared Exponential Generalized Autoregressive Conditional Heteroskedasticity with order p=1 and q= 1, (EGARCH (1,1)) and Recurrent Neural Network (RNN) based on long [...] Read more.
Business merchants and investors in Nigeria are interested in the foreign exchange volatility forecasting accuracy performance because they need information on how volatile the exchange rate will be in the future. In the paper, we compared Exponential Generalized Autoregressive Conditional Heteroskedasticity with order p=1 and q= 1, (EGARCH (1,1)) and Recurrent Neural Network (RNN) based on long short term memory (LSTM) model with the combinations of p = 10 and q = 1 layers to model the volatility of Nigerian exchange rates. Our goal is to determine the preferred model for predicting Nigeria’s Naira exchange rate volatility with Euro, Pounds and US Dollars. The dataset of monthly exchange rates of the Nigerian Naira to US dollar, Euro and Pound Sterling for the period December 2001 – August 2023 was extracted from the Central Bank of Nigeria Statistical Bulletin. The model efficiency and performance was measured with the Mean Squared Error (MSE) criteria. The results indicated that the Nigeria exchange rate volatility is asymmetric, and leverage effects are evident in the results of the EGARCH (1, 1) model. It was observed also that there is a steady increase in the Nigeria Naira exchange rate with the euro, pounds sterling and US dollar from 2016 to its highest peak in 2023. Result of the comparative analysis indicated that, EGARCH (1,1) performed better than the LSTM model because it provided a smaller MSE values of 224.7, 231.3 and 138.5 for euros, pounds sterling and US Dollars respectively.
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Open Access May 03, 2024

Congruence Between Intended and Observed Transactions in the Implementation of the Senior High School (SHS) Social Studies Curriculum in Ghana

Abstract This study aimed to evaluate the Social Studies Curriculum for Senior High Schools in Ghana to determine whether the subject has attained its goal(s) or not, using Stake’s Countenance Evaluation Model. The study took place in the Asante Akim North District. The population for study were all Social Studies teachers and students in the district. The multi-stage sampling technique was adopted for the [...] Read more.
This study aimed to evaluate the Social Studies Curriculum for Senior High Schools in Ghana to determine whether the subject has attained its goal(s) or not, using Stake’s Countenance Evaluation Model. The study took place in the Asante Akim North District. The population for study were all Social Studies teachers and students in the district. The multi-stage sampling technique was adopted for the study and the sample size was 120, made up of 100 students and 20 teachers. The concurrent mixed method approach was adopted. The main instruments used for collecting data were questionnaires, interviews (focus group and unstructured interview), observation and documentary analysis. Quantitative data were tabulated, organised, analysed and interpreted to draw sound conclusions and generalisations. The data were presented in the form of tables and percentages. Words were used to interpret the tables and percentages for easy understanding. The qualitative data responses were described and explained in the form of themes. Sometimes responses were quoted verbatim to authenticate claims made. The study looked at the congruence between what was intended to occur and what was observed before and during the implementation of the curriculum in the Asante Akim North District. On the transactions, it was revealed that teachers in the district communicate the problem the topic seeks to address and the specific objectives to the learners during instruction. Also, teachers varied their teaching methods, techniques and strategies. However, teachers failed to take students out on field trips. Also, they failed to use video documentaries to deliver their lessons inhibiting students’ creativity as they are denied the opportunity to explore and get first-hand information to build up knowledge and develop the needed attitudes and values. From the findings, it is therefore recommended that the National Council for Curriculum and Assessment should increase the time allotted to the teaching of Social Studies at the SHS level from 3-periods of 40 minutes a week to 5-periods of 40 minutes a week to give teachers and learners ample time to discuss, debate, digest and solve problems during instructional hours to enable the goal of the subject attained.
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Open Access March 09, 2024

An Evaluation of Interventions to Promote Adolescent Gender Forgiveness

Abstract The purpose of this study was to examine indicators of forgiving behaviour and intervention among adolescent students in Junior High School in Bimbilla in the Nanumba North Municipality of Ghana. This study adopted the Pragmatist philosophy. The mixed methods experimental design was used for the study. The study population comprised all adolescents in Junior High Schools in the Nanumba [...] Read more.
The purpose of this study was to examine indicators of forgiving behaviour and intervention among adolescent students in Junior High School in Bimbilla in the Nanumba North Municipality of Ghana. This study adopted the Pragmatist philosophy. The mixed methods experimental design was used for the study. The study population comprised all adolescents in Junior High Schools in the Nanumba North Municipality of the Northern Region, Ghana. Purposive, random sampling techniques Krejcie and Morgan's table of determination of sample size were used for the schools and respondents for the study. Two major instruments were used for this study: a questionnaire and an interview guide. The interview schedule was used to gather the qualitative data whereas the quantitative data was gathered using the questionnaire. The study indicated that both the REACH model and Process model are efficacious in reducing the level of depression among adolescent students when their levels of forgiveness are increased through forgiveness counselling regardless of gender and age. The findings also revealed that both REACH and Process models were good interventions for the adolescents in showing greater emotional regulation (increased forgiveness, reduced anger and reduced depression, enhanced sense of well-being, positive feelings and positive thoughts towards the offender). It is recommended that counsellors organise training programmes with parents in conjunction with Non-governmental organisations on using the Process and REACH models. This will bring awareness of the interventions and encourage parents to seek assistance anytime their adolescents need assistance. It is once again recommended that teachers and school administrators consider forgiveness interventions (the Process model and REACH model) as a very effective strategy for treating unforgiveness to improve students' psychological well-being.
Article
Open Access March 01, 2024

Challenges Learners Face in Using the Flipped Classroom Model in the Teaching and Learning of Religious and Moral Education in the Nzema East Municipality of the Western Region of Ghana

Abstract Challenges are part and parcel of human activities. Quantitatively, a relational survey model research was adopted for the study. The population for this study comprised all Junior High School (JHS) Religious and Moral Education (RME) students in Bokro M/A JHS and the Eziom Methodist JHS in the Nzema-East Municipality of the Western Region. Purposive and random sampling techniques were used to [...] Read more.
Challenges are part and parcel of human activities. Quantitatively, a relational survey model research was adopted for the study. The population for this study comprised all Junior High School (JHS) Religious and Moral Education (RME) students in Bokro M/A JHS and the Eziom Methodist JHS in the Nzema-East Municipality of the Western Region. Purposive and random sampling techniques were used to select the schools and respondents for the study. The main instruments for data collection were a test and a questionnaire. The data from both the control and experimental groups on the challenges learners face in using the flipped classroom model in RME were analysed using means and standard deviations. The study indicates the challenges learners face by employing the flipped classroom model to learn include lack of data to access the internet, frequent light outs, lack of technological devices to access contents, frequent power outages, and difficulty in comprehending some of the materials given to them. Given that learners face frequent power outages during periods that they watch videos assigned to them by their teachers, it is recommended that the government and the Electricity Company of Ghana ensure that there is a constant flow of power to allow learners trying to use the flipped classroom to learn are without any hindrance. It is also recommended that the Ghana education service should organise continuing professional development for RME teachers on effective uses of technology in teaching and learning subject concepts. The government should also supply the basic schools with all the needed technological devices to promote effective teaching, learning and assessment.
Article
Open Access February 19, 2024

The use of contemporary Enterprise Resource Planning (ERP) technologies for digital transformation

Abstract Our lives are becoming more and more digital, and this has an impact on how we work, study, communicate, and interact. Businesses are currently digitally altering their information systems, procedures, culture, and strategy. Existing businesses and economies are severely disrupted by the digital revolution. The Internet of Things, microservices, and mobile services are examples of IT systems with [...] Read more.
Our lives are becoming more and more digital, and this has an impact on how we work, study, communicate, and interact. Businesses are currently digitally altering their information systems, procedures, culture, and strategy. Existing businesses and economies are severely disrupted by the digital revolution. The Internet of Things, microservices, and mobile services are examples of IT systems with numerous, dispersed, and very small structures that are made possible by digitization. Utilizing the possibilities of cloud computing, mobile systems, big data and analytics, services computing, Internet of Things, collaborative networks, and decision support, numerous new business prospects have emerged throughout the years. The logical basis for robust and self-optimizing run-time environments for intelligent business services and adaptable distributed information systems with service-oriented enterprise architectures comes from biological metaphors of living, dynamic ecosystems. This has a significant effect on how digital services and products are designed from a value- and service-oriented perspective. The evolution of enterprise architectures and the shift from a closed-world modeling environment to a more flexible open-world composition establish the dynamic framework for highly distributed and adaptive systems, which are crucial for enabling the digital transformation. This study examines how enterprise architecture has changed over time, taking into account newly established, value-based relationships between digital business models, digital strategies, and enhanced enterprise architecture.
Review Article
Open Access February 15, 2024

Stock Closing Price and Trend Prediction with LSTM-RNN

Abstract The stock market is very volatile and hard to predict accurately due to the uncertainties affecting stock prices. However, investors and stock traders can only benefit from such models by making informed decisions about buying, holding, or investing in stocks. Also, financial institutions can use such models to manage risk and optimize their customers' investment portfolios. In this paper, we use [...] Read more.
The stock market is very volatile and hard to predict accurately due to the uncertainties affecting stock prices. However, investors and stock traders can only benefit from such models by making informed decisions about buying, holding, or investing in stocks. Also, financial institutions can use such models to manage risk and optimize their customers' investment portfolios. In this paper, we use the Long Short-Term Memory (LSTM-RNN) Recurrent Neural Networks (RNN) to predict the daily closing price of the Amazon Inc. stock (ticker symbol: AMZN). We study the influence of various hyperparameters in the model to see what factors the predictive power of the model. The root mean squared error (RMSE) on the training was 2.51 with a mean absolute percentage error (MAPE) of 1.84%.
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Open Access February 12, 2024

An Appraisal of PROCESS and REACH Model on Forgiveness, Anger and Depression among Adolescents in Junior High Schools in Nanumba North Municipality, Ghana

Abstract The purpose of the study was to examine the effect of REACH and Process Models on forgiveness, anger and depression among 11- to 19-year-old adolescents in junior high schools in Bimbilla in the Northern Region of Ghana. The study employed a mixed-method design. The population for the study comprised all junior high school students totalling 3632. Of this number, 1,888 (55%) of the students were [...] Read more.
The purpose of the study was to examine the effect of REACH and Process Models on forgiveness, anger and depression among 11- to 19-year-old adolescents in junior high schools in Bimbilla in the Northern Region of Ghana. The study employed a mixed-method design. The population for the study comprised all junior high school students totalling 3632. Of this number, 1,888 (55%) of the students were males, while 1744(45%) were females. The accessible population was 1,636 from eight (8) JHSs with 952(55%) of them being boys and the remaining 684(45%) being girls. The participants were selected based on their low levels of forgiveness and high levels of anger and depression determined by the Depression Mode Scale and Anger Self-Report. Purposive and simple random sampling techniques were used to select 60 participants for the study, with each group having 20 participants. The main instruments used for the study are questionnaires (Enright Forgiveness Inventory (EFI). Anger self-report questionnaire (ASR), and Depressed Mood Scale (DMS) and semi-structured interview guide. One-way Analysis of Covariance (ANCOVA) was used to test the hypotheses. The study indicates that both the REACH model and PROCESS model have the efficacy in enhancing forgiveness among adolescents. The study also revealed that the REACH model and Process model have efficacy in reducing levels of depression among adolescent students. It is recommended that Counselling Centres should be set up by District Education Offices and the District Assemblies in the community so that students can visit the centre anytime they feel hurt. Regular seminars, lectures and symposia should be organized regularly by Counsellors and Psychologists using the efficacy of forgiveness therapies (Process and REACH Therapies) for students to be sensitized on the need to patronise forgiveness interventions. It is also recommended that the Government should provide adequate funds and support to encourage the conduct of research in forgiveness counselling since it is a new concept in Africa and Ghana in particular.
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Open Access January 23, 2024

Ethical assessment of the culture clash as a universal occurrence

Abstract The debate on culture clash necessitates a theoretical framework, and three perspectives that merit attention are homogenization, polarization, and hybridization theories. These intersecting paths lead to the hypothesis that all civilizations could assimilate into the Western model as it is currently conceived. Culture clash is approached from multiple angles due to the widely held belief that [...] Read more.
The debate on culture clash necessitates a theoretical framework, and three perspectives that merit attention are homogenization, polarization, and hybridization theories. These intersecting paths lead to the hypothesis that all civilizations could assimilate into the Western model as it is currently conceived. Culture clash is approached from multiple angles due to the widely held belief that rejecting culturally novel concepts is unethical. However, imposing new rules and customs will inevitably encounter innate resistance, as evidenced by numerous examples. The exchange of behavioral models does exist, with one of globalization's main tenets being the universality of values – including the uprooting of what we refer to as primitive manners. Nevertheless, anthropology and cultural research have witnessed intergenerational and long-term survival of elements that contemporary civilization believed it had overcome or at least suppressed deep within the subconscious mind. This article will offer an essayistic approach to certain forms of culture clash.
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Open Access January 19, 2024

Modelling Population Growth Prognosis

Abstract Logistic growth model and its variants have been adjudged to be the most appropriate model for forecasting human population. However, in this article, we estimated the carrying capacity of Abuja using the logistic model. Then, we presented the parameters used to ascertain that the logistic model has the best fit in modelling population growth of Abuja over time. Meanwhile, a population growth [...] Read more.
Logistic growth model and its variants have been adjudged to be the most appropriate model for forecasting human population. However, in this article, we estimated the carrying capacity of Abuja using the logistic model. Then, we presented the parameters used to ascertain that the logistic model has the best fit in modelling population growth of Abuja over time. Meanwhile, a population growth sensitivity analysis is presented for the year 1962 to 2200.The result shows that by the year 2050, Abuja population growth rate will be out of control, if nothing substantial is implemented. Similarly, from the year 2150, the results show that stability will return again. Furthermore, the result of the error analysis conducted on the logistic model shows that Abuja has a growing population and that logistic growth model with MAPE and RMSE values of 0.98% and 7,817.07 respectively is the most accurate. The study concludes that logistic growth model with R−squared value of 0.776 has the best fit for population growth projection of Abuja. With approximate growth rate at 9.3% per annum, the projected population of Abuja will hit 30,220,701 million by the year 2039 all things being equal. Therefore, we recommend that the government should invest in massive agricultural reforms to accommodate the growing population, expand Abuja by developing its suburbs, and engage in massive reorientation of the populace on the dangers of uncontrolled births and the education of the girl child.
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Open Access December 11, 2023

How Digital Technologies Improving Business Enterprise Applications

Abstract The review article presents how emerging technologies improves the business enterprise applications for process management. The paper considers certain technologies of enterprise applications and justifies the updated methodological and analytical tools for assessing, selecting, and regulating business processes in a single enterprise resource planning (ERP) system. Information technology must be [...] Read more.
The review article presents how emerging technologies improves the business enterprise applications for process management. The paper considers certain technologies of enterprise applications and justifies the updated methodological and analytical tools for assessing, selecting, and regulating business processes in a single enterprise resource planning (ERP) system. Information technology must be used to identify products, track their movement into and out of the warehouse using code scanning technology, and streamline the product management procedure. To increase the dependability of management techniques, guarantee that the business operates flawlessly, and maintain a regular management mode, the process management form should be implemented in the enterprise management process. The implementation of digital information technology is essential for achieving effective corporate management. In addition to providing ideal operational circumstances for businesses, it is essential to analyse information technology and manage businesses economically. The foundation for implementing the enterprise applications method strategy is the creation of a process management system and an in-depth, methodical review of the enterprise as a collection of processes. Process-oriented enterprise applications should be the foundation of contemporary novel technologies for modelling business processes. It shares a tight relationship with workflow management systems (WFM), enterprise resource planning (ERP), and total quality management (TQM).
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Open Access October 22, 2023

An Appraisal of Work-Family Conflict on Management Staff of Star-Rated Hotels

Abstract The objective of this research was to investigate work-family conflict among management staff of hotels in the Accra Metropolis of Ghana. The study employs the pragmatism approach and Convergent parallel mixed methods research technique. The population of the study is all-star-rated management staff of star-rated hotels in the Accra metropolis. Stratified, random and convenient sampling techniques [...] Read more.
The objective of this research was to investigate work-family conflict among management staff of hotels in the Accra Metropolis of Ghana. The study employs the pragmatism approach and Convergent parallel mixed methods research technique. The population of the study is all-star-rated management staff of star-rated hotels in the Accra metropolis. Stratified, random and convenient sampling techniques were used to select 182 out of 356 respondents. One hundred (100) were sampled using a formula and a table determination of sample size based on the confidence level needed from a given population as provided by Krejcie and Morgan in 1970 for the study. Ten managers were conveniently interviewed on the issues of work-family conflict. The main instruments for data collection were a questionnaire and a semi-structured interview guide. This study adopted factor analysis and a structural equation model to examine factors that influence work-family conflict. This statistical technique was used in the research to investigate the factorability of the variables of work-related and family-related factors separately and a structural equation model was used to combine both factors to better understand the relationship. Linear regression was used to determine the relationship between work-family conflict. Pearson product-moment Correlation and structural equation model were used to determine the consequences of work-family conflict. It can be concluded that both work-related such as work overload, job type and involvement as well as family-related factors such as life cycle stage, and childcare arrangement predict work-family conflict among managers of hotels in the Accra metropolis. It is also deducted WFC affect managers’ performance on the job, exhaust them emotionally and also influences their intentions to leave the job for another. Managers usually feel fatigued to prepare for work and physically drained after work. They also feel depressed and emotionally drained sometimes. It is recommended that top management of hotels should allocate a budget to build an organisational culture that encourages work-family balance. Frontline managers should be trained to be aware of the benefit of providing support in the work environment that will help staff balance work and family. It is also recommended that hotel jobs be redesigned by the human resource unit to reduce workload and make it more interesting for managers so they may not feel overworked. Overworking of managers will enhance their intentions to quit the job and this will be costly for hotels.
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Open Access July 28, 2023

An Assessment of Coping Strategies on Work-family Conflict and Job Performance in Ghana

Abstract The purpose of this study was to examine coping strategies for managing the effects of work-family conflict on the management staff of hotels in the Accra metropolis of Ghana. The study adopted a Convergent parallel mixed methods research technique. The population of the study is all-star-rated management staff of star-rated hotels in the Accra metropolis. multi-stage sampling. The estimation of [...] Read more.
The purpose of this study was to examine coping strategies for managing the effects of work-family conflict on the management staff of hotels in the Accra metropolis of Ghana. The study adopted a Convergent parallel mixed methods research technique. The population of the study is all-star-rated management staff of star-rated hotels in the Accra metropolis. multi-stage sampling. The estimation of the sample size for the hotel managers was based on Krejcie and Morgan’s table for the determination of the sample size for a given population. The population of 100 managers were stratified and randomly sampled out of the 182 managers. The main instruments for data collection were questionnaires and an interview. Statistical Package for Social Sciences (SPSS) version 22.0 was used to determine simple percentages and frequencies of responses. Pearson product-moment Correlation and structural equation model were used to determine the consequences of work-family conflict as well as coping strategies adopted by managers. Amos PLS was used to determine the moderating effect of coping strategies on work-family conflict and job performance. Hotel managers in the Accra metropolis combine the strategies of structural role redefinition, personal role redefinition, cognitive restructuring and reactive role redefinition to curb work-family conflict. The study demonstrated a positive relationship between coping strategies and job performance. Coping strategies had a moderating effect on the relationship between work-family conflict and the job performance of hotel managers. Thus, to improve the job performance of hotel managers, there should be the application of coping interventions to help them perform on the job. The study also determined that work-family conflict had a significant positive relationship with job performance. Similarly, the study established that coping strategies significantly moderate the relationship between work-family conflict and job performance among hotel managers in the Accra metropolis. Although coping strategies were employed by hotel managers in the Accra metropolis, it is recommended that training sessions on the use of coping strategies and stress management techniques should be considered by management to address psychological and emotional work environment stressors since they have been proven to reduce stress and WFC. It is also recommended that there should be an inter-hotel collaboration to offer smaller hotels which do not have the resources some leverage the impact of work-family conflict. This platform can be provided by the Ghana hotels association to impact knowledge of coping strategies in smaller hotels. The government must be encouraged to liaise with the Ghana hotels association to enforce the mandatory eight-hour work per day to avoid overworking of hotel managers.
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Open Access February 21, 2023

Religious and Moral Education Teachers’ Usage of the Flipped Classroom Model and its Influence on JHS Students’ Academic Performance in the Nzema-East Municipality, Ghana

Abstract The purpose of this study was to examine Religious and Moral Eduction teachers’ usage of the flipped classroom model Model and its Influence on JHS Students’ Academic Performance in the Nzema-East Municipality of Ghana.The study adopted the quasi-experimental research design. The population for this study comprised all JHS Religious and Moral Education students and teachers within the [...] Read more.
The purpose of this study was to examine Religious and Moral Eduction teachers’ usage of the flipped classroom model Model and its Influence on JHS Students’ Academic Performance in the Nzema-East Municipality of Ghana.The study adopted the quasi-experimental research design. The population for this study comprised all JHS Religious and Moral Education students and teachers within the Nzema-East Municipality of the Western Region. With the help of the Krejcie and Morgan’s sample determination table, a sample of 110 comprising 10 teachers and 100 students were selected for the study through multi-stage sampling. The instruments used for data collection were tests and questionnaires. The study indicated that, the flipped classroom is a very potent method of teaching RME. This is so because the study provides enough evidence that the flipped classroom significantly improves the performance of learners more than the traditional approaches to teaching. This is even more appropriate in a technological era such as ours. The study also revealed that, teachers have a positive view of the use of the flipped classroom in teaching RME. Junior High School RME teachers are ready to adopt the flipped classroom model in their teaching provided challenges students face are eliminated. It is recommended that, School Improvement Support Officers and Headteachers should ensure that teachers use the flipped classroom to bring variations in lesson delivery so as to improve the academic achievements of learners. It is also recommended that government should provide technological devices to schools and teachers and ensure that teachers employ the various technological devices at their disposal to the benefit of their students.
Article
Open Access February 17, 2023

The Frescoes in Lysi, Cyprus and the Digital Modelling of Their Environment in the UK

Abstract The article is about the finding (after stealing) and restauration of the frescos from the Church of Evphemianos, near Lysi, Cyprus. These wall-paintings have been dated to the thirteenth century. A team of British specialists lead by Laurence J. Morroco restored them and put them back in situ in 2012.
The article is about the finding (after stealing) and restauration of the frescos from the Church of Evphemianos, near Lysi, Cyprus. These wall-paintings have been dated to the thirteenth century. A team of British specialists lead by Laurence J. Morroco restored them and put them back in situ in 2012.
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Communication
Open Access February 07, 2023

Balancing of Planar Eight –Bar Mechanism using Genetic Algorithm

Abstract In the current study, the eight-bar planar mechanism is balanced by reducing variations in shaking force and moments using Minitab and a genetic algorithm. The objective function and constraint equations are taken into consideration, the mathematical model was developed to optimize the balancing of the planar eight-bar mechanism.A set of weighting factors were taken into consideration in order to [...] Read more.
In the current study, the eight-bar planar mechanism is balanced by reducing variations in shaking force and moments using Minitab and a genetic algorithm. The objective function and constraint equations are taken into consideration, the mathematical model was developed to optimize the balancing of the planar eight-bar mechanism.A set of weighting factors were taken into consideration in order to determine the ideal values for the design parameters based on the contributions of the X and Y components of the shaking force and the shaking moment. A genetic algorithm was used to find the best design parameters. The results showed that the shaking force and moments decreased by 34.5 and 61% from the initial values, respectively.
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Open Access February 03, 2023

Structural Vector Autoregressive Analysis of Crude Oil Price Shocks on Ghana’s Economy

Abstract The paper analyses the extent to which crude oil price shocks impact GDP growth, exchange rate, interest rate and inflation of an emerging oil exporting economy, Ghana. The Structural Vector Autoregressive model is used to analyse the quarterly data from 2009q1 – 2020q4. The results showed that exchange rate and GDP growth respond positively but temporal to the impulse of crude oil price. In [...] Read more.
The paper analyses the extent to which crude oil price shocks impact GDP growth, exchange rate, interest rate and inflation of an emerging oil exporting economy, Ghana. The Structural Vector Autoregressive model is used to analyse the quarterly data from 2009q1 – 2020q4. The results showed that exchange rate and GDP growth respond positively but temporal to the impulse of crude oil price. In contrast, inflation and interest rate respond negatively to crude oil price shock. Specifically, the exchange rate appreciates in the initial quarter and begins to depreciate, whereas GDP growth experiences an increase in the first two quarters and also reduces afterwards. Crude oil price shocks to the Ghanaian economy follow the conventional behaviour of the impact of crude oil on macroeconomic indicators. The positive impact of the price shock on GDP growth and exchange rate is not much reflecting the fact that Ghana is an emerging oil-producing country with low production and export level. Ghana’s prospects in the oil and gas sector should not just be a mere hoax. Policies should be directed toward petroleum exploration and production efforts since the energy transition endanger benefits for future exploitation. Policies should be implemented to attract competitive players locally and internationally in the oil industry. The shock of crude oil prices is beginning to show evidence based on this study. Therefore government must consider recognising the importance of other economic sectors in order not be become heavily dependent on oil.
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Open Access February 02, 2023

Quantifying 64 drugs, illicit substances, and D- and L- isomers in human oral fluid with liquid-liquid extraction

Abstract Although human oral fluid has become more routine for quantitative drug detection in pain management, detecting a large scope of medications and substances is costly and technically challenging for laboratories. This paper presents a quantitative assay for 64 pain medications, illicit substances, and drug metabolites in human oral fluid. The novelty of this assay is that it was developed on an [...] Read more.
Although human oral fluid has become more routine for quantitative drug detection in pain management, detecting a large scope of medications and substances is costly and technically challenging for laboratories. This paper presents a quantitative assay for 64 pain medications, illicit substances, and drug metabolites in human oral fluid. The novelty of this assay is that it was developed on an older model AB SCIEX 4000 instrument and renders obscure the need for more technical and expensive laboratory equipment. This method includes addition of internal standard and a 2-step liquid-liquid extraction and dry-down step to concentrate and clean the samples. The samples were suspended in 50% MeOH in water and separation and detection was accomplished using triple quadrupole mass spectrometry (LC-MS/MS). Separation was achieved using reverse-phase liquid chromatography with detection by LC-MS/MS. A second injection was done in negative mode to determine THC-COOH concentration as an indicator of THC. An aliquot of the (already) extracted samples was analyzed for D- and L- isomers of amphetamine and methamphetamine using a chiral column. The standard curve spanned from 5 to 2000 ng/mL for most of the analytes (1 to 2000 ng/mL for fentanyl and THC-COOH) and up to 1000 ng/mL for 13 analytes. Pregabalin and gabapentin ranged from 25 to 2000 ng/mL. The result is a low-cost method for the sensitive detection of a wide-ranging oral fluid menu for pain management. This assay has a high sensitivity, and good precision and accuracy for all analytes with an older model mass spectrometer.
Article
Open Access December 28, 2022

It’s time for reimagining the future of food security in sub–Saharan Africa: Gender-Smallholder Agriculture-Climate Change nexus

Abstract There is an ongoing debate regarding how to feed Sub-Saharan Africa's fast rising population in the long run, as well as the implications for food security. To maintain food security, various strategies have been recommended, including a focus on the significance of diversifying and improving people's diets. Proposals have been tabled elsewhere with a primary focus on enhancing agricultural inputs [...] Read more.
There is an ongoing debate regarding how to feed Sub-Saharan Africa's fast rising population in the long run, as well as the implications for food security. To maintain food security, various strategies have been recommended, including a focus on the significance of diversifying and improving people's diets. Proposals have been tabled elsewhere with a primary focus on enhancing agricultural inputs and technology adoption in order to increase agricultural production and productivity, hence strengthening food security. The current opinion piece attempts to contribute to this debate by examining smallholder agriculture and its role to African food security. This discussion proposes a future paradigm shift toward a gendered climate-smart smallholder agriculture and food production and security conceptual framework based on the promotion and development of smallholder agriculture and food production and security. Therefore, it's predicated that the micro-livestock-centered approach can remodel smallholder agrarian households and communities toward a gender-inclusive global climate change adaptive smallholder agriculture to strengthen production, supply, and food security in Sub-Saharan Africa. For Africa, today’s predicament is to ensure food security for the anticipated rapid population expansion, while on the other hand handling an overall net adverse effect of worldwide global climate change, and increased socio-economic ills associated with gender inequality in smallholder agriculture and ensuring long-term agriculture sustainable development. The failure to address gender inequality in smallholder agriculture and food production and pontificate of global climate change effect has thrown Sub-Saharan Africa into a state of perpetual food scarcity and insecurity because of low agricultural productivity and food supply, and by force of circumstances exposing the agricultural communities and its people to extreme poverty and nutrition and food insecurity. Therefore, it's predicated that the micro-livestock-centered approach can remodel smallholder agrarian households and communities toward a gender-inclusive global climate change adaptive smallholder agriculture to strengthen production, supply, and food security in Sub-Saharan Africa. For this purpose, this discussion proposes a future paradigm shift towards a gendered climate-smart smallholder agriculture and food production and security conceptual framework hinged on the promotion and development of the micro-livestock and/or unconventional animal species sub-sector to strengthen food security on the continent. Overall, the discussion emphasizes the importance of taking immediate action to alleviate the negative effects of climate change and address gender inequality through promotion of micro livestock to assist in the development of long-term adaptation measures to maintain smallholder agricultural productivity.
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Review Article
Open Access December 25, 2022

Psychometric of the Dark Personality (Dark Triad) Instrument in Iranian Students

Abstract This study aimed to assess the validity and reliability of the dark personality instrument in students of general physical education units of Mashhad universities. The participants include all students of Ferdowsi, Imam Reza, Islamic Azad, and Payame Noor universities who had chosen the units of general physical education and sport in the academic year of 2021-22, using the Morgan table, 196 [...] Read more.
This study aimed to assess the validity and reliability of the dark personality instrument in students of general physical education units of Mashhad universities. The participants include all students of Ferdowsi, Imam Reza, Islamic Azad, and Payame Noor universities who had chosen the units of general physical education and sport in the academic year of 2021-22, using the Morgan table, 196 people were randomly selected as a sample. A standard dark personality questionnaire (Jonason & Webster, 2010) was used to collect data. Cronbach's alpha test was used to confirm the reliability of the questionnaire. To confirm the instrument's validity, exploratory and confirmatory factor analyses were used. Data analysis showed that the factor load of all items is higher than the baseline value (0.4) and the research model has a significant fit. Also, the model fit indices had acceptable values. Finally, it is recommended to sports coaches and teachers of physical education classes and leisure time to use this scale at the beginning of each semester to get to know more about the personality characteristics of students in their class and to measure these people, this can help them a lot in how to manage their classes.
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Open Access December 15, 2022

Effective Parameters to Design an Automatic Parking System

Abstract The automated parking system is an extensive branch of smart transport systems. The smartness of such systems is determined by different parameters such as parking maneuver planning. Coding this control system includes vehicle parking and understanding the environment. A high-quality classification mask has been used on each sample to analyze the automated vehicle parking parameters. Mask [...] Read more.
The automated parking system is an extensive branch of smart transport systems. The smartness of such systems is determined by different parameters such as parking maneuver planning. Coding this control system includes vehicle parking and understanding the environment. A high-quality classification mask has been used on each sample to analyze the automated vehicle parking parameters. Mask region-based convolutional neural networks (R-CNN) was taught using a small computational workload titled faster R-CNN that operates in five frames per second. In this paper, the rapidly-exploring random tree (RRT) method was used for routing the parking space and a nonlinear model predictive control (NMPC) controller was added to develop this system. We add the line detection algorithm commands to the mask R-CNN algorithm. The results can be useful to design a secure automatic parking system as well as a powerful perception system.
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Open Access December 14, 2022

Applying Artificial Intelligence (AI) for Mitigation Climate Change Consequences of the Natural Disasters

Abstract Climate change and weather-related disasters are speeded very fast in the last decades with the consequences bringing to humanity: insecurity, destructing the ecological systems, increasing poverty, human victims, and economical losses everywhere on the planet. The innovative methods applied to mitigate the magnitudes of natural disasters and to combat effectively their negative impact consist of [...] Read more.
Climate change and weather-related disasters are speeded very fast in the last decades with the consequences bringing to humanity: insecurity, destructing the ecological systems, increasing poverty, human victims, and economical losses everywhere on the planet. The innovative methods applied to mitigate the magnitudes of natural disasters and to combat effectively their negative impact consist of remote and earth constantly monitoring, data collection, creation of models for big data extrapolation, prediction, in-time warning for prevention, and others. Artificial intelligence (AI) is used to deal with big data, for calculations, forecasts, predictions of natural disasters in the near future, the establishment of the possibilities to escape the hazards or risky situations, as well as to prepare the human being for adverse changes, and drawing the different choices as assistance the right decision to be accepted. Many projects, programs, and frameworks are adopted and carried out the separate governments and business makers to common goals and actions for the formation of a friendly environment and measures for reducing undesired climate alterations and cataclysms. The aim of the article is to review the last programs and innovations applied in the mitigation of climate change using AI.
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Brief Review
Open Access November 30, 2022

An Appraisal of Junior High School Learners Perception in Using Flipped Classroom Model in Learning Social Studies Lessons

Abstract Abstract: The purpose of this study was to examine the perception of Junior High School learners in using flipped classroom model in learning Social Studies in Aowin Municipality in the western north region of Ghana. Qualitatively, descriptive survey design was used for this study. The population of the comprised junior high school students of Enchi Methodist School. Convenient and [...] Read more.
Abstract: The purpose of this study was to examine the perception of Junior High School learners in using flipped classroom model in learning Social Studies in Aowin Municipality in the western north region of Ghana. Qualitatively, descriptive survey design was used for this study. The population of the comprised junior high school students of Enchi Methodist School. Convenient and purposive sampling techniques were used to select both the school and fifty (50) respondents for the study. The main instrument used for data collection was questionnaire. The questionnaire was made up of four-point Likert closed-ended statements that required learners to tick, where appropriate, their responses. The data were analysed using the SPSS software package. The data was edited, coded and analysed into frequencies, percentages with interpretations. The study concluded that, Junior High School Social Studies learners have a generally positive perception regarding the use of the flipped classroom model to learn Social Studies. This implies that, students positively respond to the use of flipped classroom as a teaching method. Since learners have a general positive perception of the use of the flipped classroom, it is recommended that teachers use the flipped classroom as a teaching method while parents are also encouraged to provide their wards with the necessary support such as phones and data to facilitate students’ learning.
Article
Open Access November 10, 2022

Modeling and Forecasting Cryptocurrency Returns and Volatility: An Application of GARCH Models

Abstract The future of e-money is crypocurrencies, it is the decentralize digital and virtual currency that is secured by cryptography. It has become increasingly popular in recent years attracting the attention of the individual, investor, media, academia and governments worldwide. This study aims to model and forecast the volatilities and returns of three top cryptocurrencies, namely; Bitcoin, Ethereum [...] Read more.
The future of e-money is crypocurrencies, it is the decentralize digital and virtual currency that is secured by cryptography. It has become increasingly popular in recent years attracting the attention of the individual, investor, media, academia and governments worldwide. This study aims to model and forecast the volatilities and returns of three top cryptocurrencies, namely; Bitcoin, Ethereum and Binance Coin. The data utilized in the study was extracted from the higher market capitalization at 31st December, 2021 and the data for the period starting from 9th November, 2017 to 31st December 2021. The Generalised Autoregressive conditional heteroscedasticity (GARCH) type models with several distributions were fitted to the three cryptocurrencies dataset with their performances assessed using some model criterion tests. The result shows that the mean of all the returns are positive indicating the fact that the price of this three crptocurrencies increase throughout the period of study. The ARCH-LM test shows that there is no ARCH effect in volatility of Bitcoin and Ethereum but present in Binance Coin. The GARCH model was fitted on Binance Coin, the AIC and log L shows that the CGARCH is the best model for Binance Coin. Automatic forecasting was perform based on the selected ARIMA (2,0,1), ARIMA (0,1,2) and the random walk model which has the lowest AIC for ETH-USD, BNB-USD and BTC-USD respectively. This finding could aid investors in determining a cryptocurrency's unique risk-reward characteristics. The study contributes to a better deployment of investor’s resources and prediction of the future prices the three cryptocurrencies.
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Open Access November 09, 2022

Economic Consequences of Covid-19 in Western Ethiopia: Challenges and Opportunities

Abstract This research is conducted with main aim of assessing the economic consequences of Covid-19 pandemic in Western Ethiopia. Primary data is collected through questionnaire and interview from 320 respondents living in three zones of Western Ethiopia. The study areas (zones) are selected purposively from Oromia region; however, the respondents are sampled by employing random sampling technique. The [...] Read more.
This research is conducted with main aim of assessing the economic consequences of Covid-19 pandemic in Western Ethiopia. Primary data is collected through questionnaire and interview from 320 respondents living in three zones of Western Ethiopia. The study areas (zones) are selected purposively from Oromia region; however, the respondents are sampled by employing random sampling technique. The respondents were stratified as community members, daily laborer, business owners, government sector and NGOs employees. Exploratory research design was adopted to achieve the research objectives. Simple descriptive statistics and ordinary least square regression model are used to analyze and interpret the collected data. The study results disclose that majority of community have good awareness about the pandemic and social interaction is reduced due to social distancing. Majority of respondents realize the negative impact of Covid-19 on their economy; reduction of office services; and reduced access to market; and absence of strong support from the government. The great severity of Covid-19 impacts is failed on daily laborers. The regression result shows that sales, experience in business, education level in years, employment status of the respondent, number of workers in the business and work hours per week are positively and significantly influencing daily income of business owner before and after the pandemic outbreak. It is advised the stakeholders to give frequent follow-up and support particularly for daily laborers and small business holders to reduce the future socio-economic impacts of Covid-19 pandemic.
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Article
Open Access November 08, 2022

An evaluation of Eating Pattern and Nutritional Status of Police Personnel in the Tamale Metropolis in Ghana

Abstract Police work is mentally demanding and stressful, which takes a heavy toll on the health of police personnel. This study was conducted to assess the eating pattern, physical activity and nutritional status of police personnel in the Tamale Metropolis. A cross-sectional research design was adopted for the study. The population of this study involved all the 1590 police personnel with two years [...] Read more.
Police work is mentally demanding and stressful, which takes a heavy toll on the health of police personnel. This study was conducted to assess the eating pattern, physical activity and nutritional status of police personnel in the Tamale Metropolis. A cross-sectional research design was adopted for the study. The population of this study involved all the 1590 police personnel with two years working experience within the Tamale Metropolis in the Northern Region of Ghana. Simple random sampling technique was used to select three hundred and eighty-four (384) respondents for the study. The main instrument for data collection was questionnaire. Data were analyzed using Statistical Package for Social Sciences (SPSS) version 21.0. Chi-square and Fisher’s exact tests were used to test associations. Logistic modeling was used to test the strength of the associations. P<0.05 was used to denote significance. The study revealed that the police eat two main meals, skip breakfast or eat in between meals, consume alcohol, ate foods belonging to the meat, soft drinks, fish, grain and eggs groups and their diet were more moderately diverse. The study also concluded the police personnel had normal BMI while was overweight and obese respectively. It is recommended that the police department should institute health education programs on the benefits of good dietary practices to achieve optimal health, to avoid the practice of police eating two main meals, skipping breakfast, consuming more alcohol but rather consumes diet that is moderately diverse to sustain him or her. It is also recommended that police department should institute a health education and screening exercise policy to examine the personals periodically to warrant their good health in the service.
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Article
Open Access November 05, 2022

Hepatic Histopathological Alterations induced by L-Arginine and/or Dexamethasone in Adult Male Albino Rats

Abstract The liver is critical organ for metabolic homeostasis and toxic substance clearance and plays an important role in the systemic response to critical illness. Acute panreatitis (AP) progresses with a local production of inflammatory mediators, eventually leading to systemic inflammatory response syndrome. Knowing that almost all pancreatic mediators released from the pancreas to the blood stream [...] Read more.
The liver is critical organ for metabolic homeostasis and toxic substance clearance and plays an important role in the systemic response to critical illness. Acute panreatitis (AP) progresses with a local production of inflammatory mediators, eventually leading to systemic inflammatory response syndrome. Knowing that almost all pancreatic mediators released from the pancreas to the blood stream may pass through the liver before their dilution in the systemic circulation, it would be reasonable to assume a determinant role of this organ in development of the inflammatory response associated with acute pancreatitis. Objectives: The study aimed to investigate the time courses of the effects of the exogenous glucocorticoids agonist dexamethasone on microscopical changes occurring in the liver of rats used as a model of AP induced by L-Arginine. Materials and Methods: 60 adult male albino rats weighing 150-200 gm were used. They were divided into 3 groups: Control group: Which is also divided into 2 subgroups (a & b) each of animals of the first were IM injected with 0.5ml/100gm B.W saline and those of second were injected by 0.5mg/100gm B.W dexamethasone. L-Arginine group: which received L-Arginine to induce AP. The animals of this group were divided into 3 subgroups a, b and c the animals of which were sacrificed 3 days, 2 weeks and 1 month after L-Arginine injection respectively. Dexamethasone and L-Arginine group: in which the animals were injected with both L-Arginine and dexamethasone. They were also divided into 3 subgroups a, b and c, the animals of which were sacrificed 3 days. 2 weeks, one month after the injection of the drugs. The liver of the scarified animals were dissected out and prepared for microscopical examination. Results: The histopathological changes that occurred in the livers of acute pancreatitis (AP) model animals started in the periphery of the classic hepatic lobules and progressively extended in a centripetal manner to involve all the cells of the lobules in the late period of the experiment. These changes were in the form of ballooning of the hepatocytes, progressive vacuolation of their cytoplasm most propably with fat globules and depletion of the PAS+ve glycogen granules. Injection of dexamethasone in AP model animals did not improve the case, but on the contrary it made the changes more intense, severe, and rapid. One month after injection of L-Arginine and dexamethasone, the hepatocytes all over the hepatic lobules were severely affected. They were markedly ballooned with severely vacuolated cytoplasm which was completely depleted from its PAS +ve glycogen granules, indicating severe fatty degeneration of the liver. Conclusion: From the previous data, it can be concluded that treatment of AP with dexamethasone is caused a late bad effect on the liver, where it causes its late fatty liver changes.
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Open Access November 04, 2022

An Artificial Intelligence Approach to Manage Crop Water Requirements in South Africa

Abstract Estimation of crop water requirements is of paramount importance towards the management of agricultural water resources, which is a major mitigating strategy against the effects of climate change on food security. South Africa water shortage poses a threat on agricultural efficiency. Since irrigation uses about 60% of the fresh water available, it therefore becomes important to optimise the use of [...] Read more.
Estimation of crop water requirements is of paramount importance towards the management of agricultural water resources, which is a major mitigating strategy against the effects of climate change on food security. South Africa water shortage poses a threat on agricultural efficiency. Since irrigation uses about 60% of the fresh water available, it therefore becomes important to optimise the use of irrigation water in order to maximize crop yield at the farm level in order to avoid wastage. In this study, combined application of an artificial neural network (ANN) and a crop – growth simulation model for the estimation of crop irrigation water requirements and the irrigation scheduling of potatoes at Winterton irrigation scheme, South Africa was investigated. The crop-water demand from planting to harvest date, when to irrigate, the optimum stage in the drying cycle when to apply water and the amount of irrigation water to be applied per time, were estimated in this study. Five feed –forward backward propagation artificial neural network predictive models were developed with varied number of neurons and hidden layers and evaluated. The optimal ANN model, which has 5 inputs, 5 neurons, 1 hidden layer and 1 output was used to predict monthly reference evapotranspiration (ETo) in the Winterton area. The optimal ANN model produced a root-mean-square error (RMSE) of 0.67, Pearson correlation coefficient (r) of 0.97 and coefficient of determination (R2) of 0.94. The validation of the model between the measured and predicted ETo shows a r value of 0.9048. The predicted ETo was one of the input variables into a crop growth simulation model, called CROPWAT. The results indicated that the total crop water requirement was 1259.2 mm/decade and net irrigation water requirement was 1276.9 mm/decade, spread over a 5-day irrigation time during the entire 140 days of cropping season for potatoes. A combination of the artificial neural networks and the crop growth simulation models have proved to be a robust technique for estimating crop irrigation water requirements in the face of limited or no daily meteorological datasets.
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Open Access November 02, 2022

Using the Concept of Precedence as an Approach to Explain the Logical Interaction and Interrelationships among Corporate Social Responsibilities: Battal's CSR Train VS. Carroll ′s CSR Pyramid

Abstract Purpose: The model of CSR devised by the American scientist ″Archie B. Carroll in 1991″ - which became well- known in academic circles as Carroll′s CSR pyramid, has been criticized by academics and researchers. The researcher firmly believes that one of the most important reasons that led to the emergence of these criticisms was Carroll's adoption of the idea of the pyramid as a form to [...] Read more.
Purpose: The model of CSR devised by the American scientist ″Archie B. Carroll in 1991″ - which became well- known in academic circles as Carroll′s CSR pyramid, has been criticized by academics and researchers. The researcher firmly believes that one of the most important reasons that led to the emergence of these criticisms was Carroll's adoption of the idea of the pyramid as a form to illustrate his idea of CSR. The content of the pyramid does not match the accompanying explanations given by Carroll. Carroll's CSR pyramid does not reflect the concept of simultaneous CSRs. Also, Carroll's CSR pyramid does not reflect the logical interaction and interrelationships among CSRs. It is also noted that, Carroll's pyramid reflects the expectations of stakeholders and does not reflect the expectations of companies from their commitment to their social responsibilities. This study aimed to design a model for CSR, in which the content of its figure matches the explanations attached to it, and reflects the concept of simultaneous CSRs, in addition to the logical interaction and the interrelationship among those responsibilities. Method: The researcher used the concept of precedence as an approach to explain the logical interaction and interrelationships among CSRs. The idea of precedence is clearly found only in the railway industry. The interaction of CSRs with each other can be likened to the interaction of the components of a classic train (a cockpit and coaches). Therefore, the researcher adopted the idea of the classic train as an innovative model to address some of the shortcomings of Carroll ′s pyramid. Battal's CSR train as an innovative model- in this study, can reflect the notion of simultaneous CSRs, the logical interaction and interrelationships among CSRs, and expectations and aspirations of both stakeholders and companies. Result: By adopting the idea of the classic train work and its components, this study was able to produce a model of CSR as an alternative model for Carroll′s pyramid (1991). Originality/Value: Battal ′s CSR train is an educational model that is designed to address some of the shortcomings of Carroll's CSR pyramid "as a figure and content." The content of Battal′s CSR train matches the attached explanation, and this will help to understand how CSRs interact with each other, as well as the concept of simultaneous CSRs. It is an enrichment of the thought of CSR.
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Open Access October 24, 2022

Probiotics and Intestinal Microbiome: A Review of Literature

Abstract Probiotics, prebiotics, and synbiotics modify various aspects of local and systemic immune function in multiple experimental models. However, their impact and mechanisms of action are not known across all products or noticed in every population studied, and impacts on in vitro, ex vivo, or other measures of immune function do not necessarily result in an impact on infection and illness in vivo [...] Read more.
Probiotics, prebiotics, and synbiotics modify various aspects of local and systemic immune function in multiple experimental models. However, their impact and mechanisms of action are not known across all products or noticed in every population studied, and impacts on in vitro, ex vivo, or other measures of immune function do not necessarily result in an impact on infection and illness in vivo. Studies have discussed that intestinal microbiota has an essential role in enhancing the immune system against viruses. The regulatory impact of the intestinal microbiota on viral infection is connected with local and systemic immune responses and plays a part in congenital and adaptive immune responses. The microbiota composition critically modulates the production of virus-specific CD4 and CD8 T cells and antibody responses following influenza virus infection. The intestinal microbiota has an important role in the stabilizing of immune homeostasis by augmenting the integrity of the barrier functions of the gut mucosa, which is a crucial aspect of systemic immunity. In conclusion, the intestinal microbiota can influence organismal immunity locally and systemically, proximally, and distally. Studying the possible mechanism by which the intestinal microbiota maintains host immunity can provide a clearer understanding of the occurrence and development of diseases.
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Open Access September 04, 2022

Drug-Receptor Interaction of Peptidic HIV-1 Protease: The Hydrophobic Effect-I

Abstract When a drug interacts with its receptor, the nonpolar substituent of drug and receptor proteins attract each other because they have opposite magnitude with respect to each other. X-rays structure studies reflected that the S2/S2’ pocket in HIV-1 protease enzyme are essentially hydrophobic. The residues that make up these pockets are Val-32, Ile-47, Ile-50, and Ile-84 in each monomeric [...] Read more.
When a drug interacts with its receptor, the nonpolar substituent of drug and receptor proteins attract each other because they have opposite magnitude with respect to each other. X-rays structure studies reflected that the S2/S2’ pocket in HIV-1 protease enzyme are essentially hydrophobic. The residues that make up these pockets are Val-32, Ile-47, Ile-50, and Ile-84 in each monomeric polypeptidic unit of the protease enzyme. Δπdr and ΔSASAdr have been used to measure the extent of hydrophobic interaction between peptidic protease inhibitors and receptor proteins (binding site: valine‒isoleucine; and catalytic site: glycine‒aspartic acid‒threonine) on the HIV-1 protease enzyme. For measurement of hydrophobic interaction, the molecular modeling and geometry optimization of all the inhibitors and the receptor amino acids have been carried out with CAChe Pro software by opting semiempirical PM3 methods. Log P was calculated using the atom-typing scheme of Ghose and Crippen, while solvent accessible surface area by conductor likes screening model. πd, πr, SASASd and SASASr well describe the hydrophobicities of the substituents and play the effective role for site selectivity for interaction of the drug with the receptor. Comparative study of values of Δπdr and ΔSASAdr show the order of hydrophobic interaction with respect to amino acids: Asp > Thr > Val > Ile and Thr > Val > Asp > Ile, respectively. Further, comparative study of the values of (ΣΔπdr)binding-site, (ΣΔπdr)catalytic-site, (ΣΔSASAdr)binding-site, (ΣΔSASAdr)catalytic-site shows that peptidic HIV-1-PRIs interact with binding site rather than catalytic site as binding site have lower value of ΣΔπdr and ΣΔSASAdr. Among the binding site, Val has maximum interaction than Ile, as it has lower vale of Δπdr and ΔSASAdr.
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Open Access July 22, 2022

DFT-Based Prediction of Anti-Leishmanial Activity of Carboxylates and Their Antimony(III) Complexes Against Five Leishmanial Strains

Abstract Carboxylates and their antimony(III) complexes experimentally scanned earlier for anti-leishmanial activity (IC50) against five leishmanial strains viz., L. major, L. major (Pak), L. tropica, L. mex mex, and L. donovani. These activities have been theoretically predicted by DFT method along with quantitative structure-activity relationship (QSAR) study. Molecular modeling and geometry optimization of the all the eight compounds have been performed on workspace program of CAChe Pro software of Fujitsu by opting B88-PW91 (Becke '88; Perdew & Wang '91) GGA (generalized-gradient approximation) energy functional with DZVP (double-zeta valence polarized ) basis set in DFT (Density Functional Theory). For QSAR, multiple linear regression (MLR) analysis has been performed on Project Leader Program associated with CAChe. The reliability of correlation between experimental activities and predicted activities are r2 = 0.826, r2CV = 0.426 (L. major); r2 = 0.905, r2CV = 0.507 (L. major (Pak)); r2 = 0.980, r2CV = 0.932 (L. tropica); r2 = 0.781, r2CV = 0.580 (L. mex mex) and r2 = 0.634, r2CV = 0.376 (L. donovani [...] Read more.
Carboxylates and their antimony(III) complexes experimentally scanned earlier for anti-leishmanial activity (IC50) against five leishmanial strains viz., L. major, L. major (Pak), L. tropica, L. mex mex, and L. donovani. These activities have been theoretically predicted by DFT method along with quantitative structure-activity relationship (QSAR) study. Molecular modeling and geometry optimization of the all the eight compounds have been performed on workspace program of CAChe Pro software of Fujitsu by opting B88-PW91 (Becke '88; Perdew & Wang '91) GGA (generalized-gradient approximation) energy functional with DZVP (double-zeta valence polarized ) basis set in DFT (Density Functional Theory). For QSAR, multiple linear regression (MLR) analysis has been performed on Project Leader Program associated with CAChe. The reliability of correlation between experimental activities and predicted activities are r2 = 0.826, r2CV = 0.426 (L. major); r2 = 0.905, r2CV = 0.507 (L. major (Pak)); r2 = 0.980, r2CV = 0.932 (L. tropica); r2 = 0.781, r2CV = 0.580 (L. mex mex) and r2 = 0.634, r2CV = 0.376 (L. donovani), and a comparison of the experimental values and the values obtained by theoretical calculations has been presented pictorially that shows close resemblance.
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Open Access July 13, 2022

Practical Teaching Model in Double Indicator Titration: Influences on Academic Achievement of Chemistry Students

Abstract The purpose of this study was to evaluate a practical model in teaching double indicator titration in chemistry in the senior high schools in Ghana Research design for the study was Action research. The population was made up of chemistry teachers and students. in four senior high schools with two schools located in the Kwaebibirim District and two senior high schools located in the Denkyembuo [...] Read more.
The purpose of this study was to evaluate a practical model in teaching double indicator titration in chemistry in the senior high schools in Ghana Research design for the study was Action research. The population was made up of chemistry teachers and students. in four senior high schools with two schools located in the Kwaebibirim District and two senior high schools located in the Denkyembuo District of the Eastern Region of Ghana. Purposive and simple random sampling techniques were used to select the respondents for the study. The sample comprised of twenty-five (25) chemistry teachers and one hundred and fifty (150) students in the four Senior High schools. The study indicated that Chemistry teachers would improve upon the academic performance of chemistry students in double indicator titration when they use the developed practical teaching model (DEPTEM) more. The main instruments used in this study were classroom observational checklists and questionnaires. Descriptive statistics (frequency, percentage, mean and standard deviation) were used to analyze the data gathered. Coding schemes were developed using Statistical Package for Social Sciences (SPSS) (version 21) to organize the data into meaningful and manageable categories. The study also revealed that the outcome of the post-test indicated that, the DEPTEM impact differently on the academic performance of SHS male and female chemistry students in the Kwaebibirim and Denkyembuo Districts of the Eastern Region. It is recommended that the government and non-governmental organizations should collaborate with the Ministry of Education to sponsor in production of more of the developed practical model (DEPTEM) for teaching chemistry lessons. This in a way would help improve the academic performance of chemistry students in the Kwaebibirim and Denkyembuo Districts of the Eastern Region and the nation at large. It is also recommended that chemistry teachers should consider teaching methods that would equally cater to both male and female chemistry students during chemistry lessons.
Article
Open Access July 05, 2022

Teaching and Learning Strategies in Double Indicator Titration: An appraisal of Chemistry Teachers

Abstract The purpose of this study was to examine chemistry teachers' teaching and learning strategies in double indicator titration in Senior High Schools in Ghana. Action research design using a quantitative approach was used for the study. Purposive and simple random sampling procedures were employed to select one hundred and seventy-five (175) participants (teachers and students) for the study. The [...] Read more.
The purpose of this study was to examine chemistry teachers' teaching and learning strategies in double indicator titration in Senior High Schools in Ghana. Action research design using a quantitative approach was used for the study. Purposive and simple random sampling procedures were employed to select one hundred and seventy-five (175) participants (teachers and students) for the study. The classroom observational checklist and questionnaire were the instruments used to collect data in the study. Descriptive statistics tools (frequency, percentage, mean and standard deviation) were used to analyse the quantitative data. The study revealed that Chemistry teachers in the Kwaebibirim and Denkyembuo Districts of the Eastern Region used the lecture method in teaching double indicator titration lessons instead of practical activities and this had negative effects on their academic performance. The study also indicated that the effective model that can be used to improve teaching and learning of double indicator titration is the developed practical teaching model (DEPTEM) as compared to the teachers’ method. It is recommended that in-service training should be organized for chemistry teachers who were already in the field of work to use more of the developed practical model (DEPTEM) in relation to the lecture method. It is also recommended that chemistry teachers should use teaching methods that would allow chemistry students to participate and manipulate equipment/materials using their five senses and other skills instead of teaching in abstract or allowing them to remain less active in their class.
Article
Open Access June 16, 2022

Clutter Suppression Algorithm of Ultrasonic Color Doppler Imaging Based on BP Neural Network

Abstract Aiming at the time complexity of singular value spectrum weighted Hankel SVD filtering algorithm, a clutter suppression algorithm for ultrasonic color Doppler imaging based on BP neural network model is proposed in this paper. Firstly, using the PRF data collected by portable ultrasound instrument, we verify the singular value weighted Hankel SVD filtering algorithm, and the results show that the [...] Read more.
Aiming at the time complexity of singular value spectrum weighted Hankel SVD filtering algorithm, a clutter suppression algorithm for ultrasonic color Doppler imaging based on BP neural network model is proposed in this paper. Firstly, using the PRF data collected by portable ultrasound instrument, we verify the singular value weighted Hankel SVD filtering algorithm, and the results show that the algorithm has high accuracy; Then, the BP neural network model is established based on the input and output data of singular value weighted Hankel-SVD filtering algorithm; Finally, the clutter suppression algorithm of ultrasonic color Doppler imaging based on BP neural network model is established. The experimental results show that compared with Hankel SVD filtering algorithm, the clutter suppression algorithm proposed in this paper greatly shortens the operation time without reducing the accuracy, so as to improve the real-time performance of the filtering algorithm.
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Open Access June 13, 2022

Studies on System Identification of Multiple Input Multiple Output (MIMO) Water Tank

Abstract In this study, the system identification of a multiple input multiple-output (MIMO) water tank has been investigated. The given experimental system is a first-order system. Its transfer function was evaluated and the time constant was predicted. Once the parameters of the transfer functions (delay, gain, and time constant) were determined for each step input. This model each of the step responses [...] Read more.
In this study, the system identification of a multiple input multiple-output (MIMO) water tank has been investigated. The given experimental system is a first-order system. Its transfer function was evaluated and the time constant was predicted. Once the parameters of the transfer functions (delay, gain, and time constant) were determined for each step input. This model each of the step responses using MatLab’s Simulink. These simulated responses were then compared to the observed experimental responses.
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Technical Note
Open Access May 22, 2022

Prevalence and predictors of physical activity among female high school students in The Gambia: an institutional-based cross-sectional study

Abstract Background: Everyone, irrespective of age, sex, colour, ethnicity, or present overall fitness level, can benefit from regular exercise. To improve one's health, one must engage in regular physical activity. People with underlying illnesses like long-term impairment can benefit from regular physical activity at the individual level, especially young women. Thus, the current study aimed to [...] Read more.
Background: Everyone, irrespective of age, sex, colour, ethnicity, or present overall fitness level, can benefit from regular exercise. To improve one's health, one must engage in regular physical activity. People with underlying illnesses like long-term impairment can benefit from regular physical activity at the individual level, especially young women. Thus, the current study aimed to assess the prevalence and determinants of physical activity among female school-aged adolescents in the West Coast Region of The Gambia. Methods: The present study used an institutional-based cross-sectional analytical study to collect quantitative data from 384 female high school students in The Gambia. The study used a content-validated, pretested structured questionnaire that consisted of both open and closed-ended questions on physical activity. The data were processed and analyzed using IBM SPSS version 26.0. Descriptive statistics and Chi-square and/or Fisher exact test were used with a p-value <0.15 for inclusion in the logistic regression model. Adjusted odds ratios (aORs) and 95% confidence intervals were calculated, while p-value <0.05 was considered for statistical significance. Results: The proportion of female students involved in physical activity was 37.5%. The mean age of students was 18.8 years with a standard deviation of 1.7 years. Factors such as female students between 17 – 20 years (aOR:3.05, 95% C.I. (1.807 – 5.138)), father never been to school (aOR: 2.82, 95% C.I. (1.495 – 5.334)), primary education (aOR: 2.15, 95% C.I. (1.027 – 4.493)), upper basic school (aOR: 2.31, 95% C.I. (1.055 – 5.074)) and science major students (aOR: 2.21, 95% C.I. (1.203 – 4.047)) had increased odds of involving in PA. Furthermore, students who knew that exercise would strengthen bones (aOR: 2.62, 95% C.I (1.444 – 4.739)), do a planned brisk walking (aOR: 19.16, 95% C.I. (6.698 – 54.811)), basketball/football (aOR: 29.76, 95% C.I. (10.004 – 88.512)) and skipping with rope (aOR: 29.15, 95% C.I. (9.726 – 87.333)) had increased odds to involved in PA after controlling for confounders. Other factors such as students whose mother never been to school (aOR: 0.31, 95% C.I. (0.140 – 0.674)), primary level (aOR: 0.25, 95% C.I. (0.123 – 0.518)), senior secondary level (aOR: 0.42, 95% C.I. (0.189 – 0.935)), nuclear family (aOR: 0.23, 95% C.I. (0.119 – 0.458)) and extended family (aOR: 0.45, 95% C.I. (0.225 – 0.915)) had reduced odds of involving in PA. Conclusion: There is low physical activity among female adolescents in schools. For this, it is imperative that suitable interventions be implemented to raise the level of physical activity among secondary school students. A future intervention for school-aged adolescents could benefit from these findings.
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Open Access May 22, 2022

Pooled prevalence and contextual determinants of contraceptive utilization among reproductive-age women in The Gambia: Evidence from 2013 – 2020 Demographic Health Surveys

Abstract Background: Family planning (FP) methods have been found as an efficient approach of reducing fertility and are therefore widely supported in order to decrease population growth, particularly in poor nations. Promoting contraception availability among women (15 – 49) age has also been shown to be an efficient public health strategy for improving maternal and newborn health outcomes. This [...] Read more.
Background: Family planning (FP) methods have been found as an efficient approach of reducing fertility and are therefore widely supported in order to decrease population growth, particularly in poor nations. Promoting contraception availability among women (15 – 49) age has also been shown to be an efficient public health strategy for improving maternal and newborn health outcomes. This paper aimed at exploring the pooled prevalence of contraceptive uptake and its contextual determinants among women of childbearing age in The Gambia. Methods: The Gambia Demographic and Health Survey (GDHS) in both 2013 and 2019-20 was used for this study. Data were obtained from a pooled 22,098 women aged 15-49 (10,233 for 2013 and 11,865 for 2019-20) through a stratified two-stage cluster sampling approach. Percentages and chi-square tests were used and variables with p-value <0.05 were included into the model. A multivariable logistic regression model was used to assess the predictors of contraceptive usage at 95% confidence interval (CIs) with computed adjusted odds ratios (aORs). All the study data were analyzed using Stata version 15. Results: The weighted pooled prevalence of modern contraceptive utilization in The Gambia was 10.1%. Younger age, compared with women aged 25-29; 30-34; 35-39; 40-44; primary education (aOR=1.25, 95% CI=1.05-1.49); secondary education (aOR=1.57, 95% CI= 1.32-1.85); Higher education (aOR=1.90, 95% CI=1.34-12.69); living in urban areas (aOR=1.49, 95% CI= 1.25-1.79); parity 2-4 (aOR=1.21, 95% CI= 1.01-1.47); told about FP at health facility (aOR=2.97, 95% CI= 2.61-3.38), and no desire for many children (aOR=1.96, 95% CI= 1.62-2.37) were more like to use modern contraceptives among Gambian women. Conclusion: The programme certainly needs to consider improvements in the quality of care being offered to acceptors. Government agencies should target these programs and campaigns on regional FP demands and provide suitable culturally sensitive and regionally adaptive services to the communities' contexts. The programme should intensify its efforts in rural and urban settings to improve accessibility to and availability of FP services.
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Open Access May 15, 2022

Kinetic, Equilibrium and Thermodynamic Study of the Adsorption of Pb (II) and Cd (II) Ions from Aqueous Solution by the Leaves Biomass of Guava and Cashew Plants

Abstract The plant leaves used as adsorbent in this study were Guava plant leaves (GPL) and Cashew plant leaves (CPL). The samples were collected within Gombe State. Batch adsorption method was used in determining the adsorption process. Fourier Transform Spectroscopy (FT-IR), Scan-ning Electron Microscopy (SEM) and X-Ray Diffraction (XRD) were used for the characterization. The results show promising [...] Read more.
The plant leaves used as adsorbent in this study were Guava plant leaves (GPL) and Cashew plant leaves (CPL). The samples were collected within Gombe State. Batch adsorption method was used in determining the adsorption process. Fourier Transform Spectroscopy (FT-IR), Scan-ning Electron Microscopy (SEM) and X-Ray Diffraction (XRD) were used for the characterization. The results show promising signs as they were in agreement with most literatures; various per-centage removals were obtained from Pb2+ and Cd2+ (GPL and CPL) at optimum conditions. The equilibrium data fitted well with both Langmuir and Freundlich isotherm models. Langmuir mod-el fitted well for Pb2+ (CPL) with R2 value (0.9855) and Cd2+ for (GPL and CPL) with R2 values (0.9945 and 0.9948) while Pb2+ (GPL) with correlation coefficient at 0.9116 best fits well with Freundlich isotherm model. Pseudo first order and second order were used in testing the kinetics study from which pseudo second order best fitted better than that of the first order kinetics. The thermodynamic study shows that ΔG is negative in most cases except for Cd2+ (GPL) where ΔG is positive. Whereas ΔH and ΔS are positive in some cases showing an endothermic and spontane-ous adsorption processes respectively, as well as negative in some. Based on this study, GPL and CPL could be used as a natural adsorbent to remove Pb2+ and Cd2+ heavy metals from wastewater and environment due to their high removal efficiencies.
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Open Access May 06, 2022

Movie Recommendation System Modeling Using Machine Learning

Abstract The task of recommending products to customers based on their interests is important in business. It is possible to accomplish this with machine learning. To reduce human effort by proposing movies based on the user's interests efficiently and effectively without wasting much time in pointless browsing, the movie recommendation system is designed to assist movie aficionados. This work focuses on [...] Read more.
The task of recommending products to customers based on their interests is important in business. It is possible to accomplish this with machine learning. To reduce human effort by proposing movies based on the user's interests efficiently and effectively without wasting much time in pointless browsing, the movie recommendation system is designed to assist movie aficionados. This work focuses on developing a movie recommender system using a model that incorporates both cosine similarity and sentiment analysis. Cosine similarity is a standard used to determine how similar two items are to one another. An examination of the emotions expressed in a movie review can determine how excellent or negative a review is and, consequently the overall rating for a film. As a result, determining whether a review is favorable or adverse may be automated because the machine learns by training and evaluating the data. Comparing different systems based on content-based approaches will produce results that are increasingly explicit as time passes.
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Open Access April 28, 2022

Analysis of Network Modeling for Real-world Recommender Systems

Abstract Nowadays, recommendation systems are existing everywhere in the internet world, online people are presented with the required needs not just for actual physical products, but also for several other things such as songs, places, books, friends, movies, and many more requirements. Most of the systems are developed with the basic collaborative and hybrid filtering, where the people or users are [...] Read more.
Nowadays, recommendation systems are existing everywhere in the internet world, online people are presented with the required needs not just for actual physical products, but also for several other things such as songs, places, books, friends, movies, and many more requirements. Most of the systems are developed with the basic collaborative and hybrid filtering, where the people or users are recommended items that the choices are based on the right preferences of other people by applying the machine intelligence strategies. In this research, the importance of network modeling is analyzed in solving real-world problems.
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Open Access April 27, 2022

Kinetic, Equilibrium and Thermodynamics Study of the Adsorption of Pb(Ii), Cu(Ii) and Ni(Ii) from Aqueous Solution using Mangiferaindica Leaves

Abstract The kinetics, equilibrium and thermodynamic study of the adsorption of Ni2+, Pb2+ and Cu2+ions from aqueous solution by the leaf of Mangiferaindica were investigated at different experimental conditions. Optimum conditions of initial metal ion concentration, pH, adsorbent dose, contact time and temperature were determined. The kinetics studies indicate that the [...] Read more.
The kinetics, equilibrium and thermodynamic study of the adsorption of Ni2+, Pb2+ and Cu2+ions from aqueous solution by the leaf of Mangiferaindica were investigated at different experimental conditions. Optimum conditions of initial metal ion concentration, pH, adsorbent dose, contact time and temperature were determined. The kinetics studies indicate that the adsorption process of the metals ions followed the pseudo second-order model with R2 value of 0.9938, 1.00 and 1.00 respectively. Equilibrium studies showed that the adsorption of Ni2+, Pb2+ and Cu2+ ions are well represented by both Langmuir and Freundlich isotherm but the Langmuir model gave a better fit for Pb2+ ions with R2 value of 0.9950 and Langmuir constant KL of 4.3383 while Freundlich isotherm model best fit the experimental data of lead(II) and nickel(II) with a R2 value of 0.976 and 0.9973 and Freundlich constant KF value of 4.2677 and 0.0874. The calculated thermodynamics parameters of Ni2+, Pb2+ and Cu2+ ions are ( ΔGo -1182.49,-5479.1 and 613.48 KJ/mol) showed that the adsorption of Ni2+ and Pb2+are spontaneous while Cu2+ non-spontaneous. The findings indicate that the leaf of Mangiferaindica could be used for the adsorption of Ni2+, Pb2+ and Cu2+ ions from industrial effluents.
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Open Access March 20, 2022

Botanical education for vocational training students and primary and secondary teacher

Abstract A domain of practical learning over the theoretical is provided in this work, for this several places of natural interest have been studied (Natural Parks), a quality pedagogical training is obtained, through which the students of Vocational Training and Primary and Secondary Education Teachers obtain competences in the management of natural spaces, which are of interest for conservation, [...] Read more.
A domain of practical learning over the theoretical is provided in this work, for this several places of natural interest have been studied (Natural Parks), a quality pedagogical training is obtained, through which the students of Vocational Training and Primary and Secondary Education Teachers obtain competences in the management of natural spaces, which are of interest for conservation, competences in flora, plant communities, habitats and interpretation of the landscape. The learning is eminently practical, which allows trained personnel to enter the labor market. The study of natural spaces has been carried out using direct observation techniques, with the participation of specialist teachers in various fields, because the interpretation of vegetation, habitats and landscape requires multidisciplinary techniques. For this, teaching methodologies in Botany are used, how have the phytosociological sampling techniques been; Geology, Edaphology, and Climatology, in the latter case creating future predictive models that allow the student to make decisions about the management of a territory; this study has made it possible to carry out a comprehensive interpretation of the natural environment, with a notable pedagogical improvement in learning.
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Open Access February 25, 2022

Prevalence and Determinants of Acute Respiratory Infections among Children under Five Years in Rural Settings of The Gambia: Evidence from a National Survey

Abstract Background: Acute respiratory infections (ARIs) generally describe a group of infections caused by a range of organisms whose site of action includes the nostrils, through the pharynx to the alveoli. ARIs are reportedly key contributing factors to childhood morbidities and deaths, with a higher impact on children less than the age of five years. This paper aimed at exploring the prevalence [...] Read more.
Background: Acute respiratory infections (ARIs) generally describe a group of infections caused by a range of organisms whose site of action includes the nostrils, through the pharynx to the alveoli. ARIs are reportedly key contributing factors to childhood morbidities and deaths, with a higher impact on children less than the age of five years. This paper aimed at exploring the prevalence of ARIs and their contextual determinants among children less than 60 months of age in the rural settings of the Gambia. Method: The Gambia Demographic and Health Survey (GDHS) in 2019-20 was used for this study. Data were obtained from 1364 rural women aged 15-49 with children less than 60 months through a stratified two-stage cluster sampling approach. Percentages and chi-square tests were used and variables with p-value <0.15 were included in the model. A multivariable logistic regression model was used to assess the predictors of acute respiratory infection at 95% confidence interval (CIs) with computed adjusted odds ratios (aORs). All the study data were analyzed using Stata version 17. Results: The weighted prevalence of ARIs among children under 60 months of age in the rural Gambia was 37.1% with 95% CI (34.5% - 39.6%). The magnitude of ARI was higher among children 25-60 months age group (38.6%), male children (38.9%) unvaccinated children (42.9%), and those whose fathers and mothers were not working at 60.5% and 38.7%, respectively. In the adjusted model, children whose mother had primary education (aOR=0.65, 95% CI= 0.46-0.91), currently non-breastfed children (aOR=1.40, 95% CI= 1.09-1.79) and those whose father were not working (aOR=2.65, 95% CI= 1.47-4.17) were found to be associated with ARIs among children less than 60 months in The Gambia. Conclusion: The prevalence of ARI was moderately high across children under 5 years of age in rural Gambia, low mother’s educational levels, and unemployed fathers. The program must consider improvements in the quality of care provided to children in both primary, secondary and tertiary healthcare levels in rural settings. Partner support and adapting community-based supporting systems on child health strategies should be strengthened especially in rural settings.
Article
Open Access February 25, 2022

How to Increase Customer Satisfaction by Beautifying Sports Facilities? What is the Key Role of Service Quality?

Abstract The purpose of this study was to investigate the key role of service quality and beauty of sports facilities in increasing customer satisfaction. The research method is descriptive and correlational research. The statistical population of the study was 154188 organized athletes covered by sports insurance (103890 men, 50298 women) who were working in sports halls of Mazandaran province and [...] Read more.
The purpose of this study was to investigate the key role of service quality and beauty of sports facilities in increasing customer satisfaction. The research method is descriptive and correlational research. The statistical population of the study was 154188 organized athletes covered by sports insurance (103890 men, 50298 women) who were working in sports halls of Mazandaran province and according to Morgan table, 384 athletes were randomly selected by cluster Were. Aesthetic questionnaire, service quality and customer satisfaction were used to collect information. Data analysis was performed using Pearson test and structural equation modeling by SPSS24 and Amos structure analysis software. According to the research results, the indirect effect of aesthetics of sports venues on increasing customer satisfaction through service quality is significant. Managers can take effective steps to increase their presence and increase the income of gyms by using quality improvement strategies and customer satisfaction.
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Open Access February 24, 2022

Computational Fluid Dynamics Modeling of Thermally Integrated Microchannel Reforming Reactors for Hydrogen Production

Abstract Many attempts have been made to improve heat transfer for thermally integrated microchannel reforming reactors. However, the mechanisms for the effects of design factors on heat transfer characteristics are still not fully understood. This study relates to a thermochemical process for producing hydrogen by the catalytic endothermic reaction of methanol with steam in a thermally integrated [...] Read more.
Many attempts have been made to improve heat transfer for thermally integrated microchannel reforming reactors. However, the mechanisms for the effects of design factors on heat transfer characteristics are still not fully understood. This study relates to a thermochemical process for producing hydrogen by the catalytic endothermic reaction of methanol with steam in a thermally integrated microchannel reforming reactor. Computational fluid dynamics simulations are conducted to better understand the consumption, generation, and exchange of thermal energy between endothermic and exothermic processes in the reactor. The effects of wall heat conduction properties and channel dimensions on heat transfer characteristics and reactor performance are investigated. Thermodynamic analysis is performed based on specific enthalpy to better understand the evolution of thermal energy in the reactor. The results indicate that the thermal conductivity of the channel walls is fundamentally important. Materials with high thermal conductivity are preferred for the channel walls. Thermally conductive ceramics and metals are well-suited. Wall materials with poor heat conduction properties degrade the reactor performance. Reaction heat flux profiles are considerably affected by channel dimensions. The peak reaction heat flux increases with the channel dimensions while maintaining the flow rates. The change in specific enthalpy is positive for the exothermic reaction and negative for the endothermic reaction. The change in specific sensible enthalpy is always positive. Design recommendations are made to improve thermal performance for the reactor.
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Open Access December 18, 2021

An Application of Remote Sensing Imagery for Geological Lineaments Extraction over Kaybarkuh Region in East of Iran

Abstract Kaybarkuh (Mount Kaybar) consists of intrusive igneous bodies with two age periods, located in North of Dasht-e-Bayaz left-lateral fault terminal. The spatial and structural analysis of fractures and dike networks may allow for the accurate identification of mineralization zones in the area. This study aims to characterize lineament network in the study area by automatic method using multispectral [...] Read more.
Kaybarkuh (Mount Kaybar) consists of intrusive igneous bodies with two age periods, located in North of Dasht-e-Bayaz left-lateral fault terminal. The spatial and structural analysis of fractures and dike networks may allow for the accurate identification of mineralization zones in the area. This study aims to characterize lineament network in the study area by automatic method using multispectral satellite images from Landsat 8 Operational Land Imager (OLI), visual extraction of lineaments from Landsat-8 and SENTINEL-2 images, and extraction of drainage network as lineament based on digital elevation models (DEMs) and their validation, compared with fault network of the area. The results showed that there is a significant relationship between the trend of studied lines in the region by the three methods mentioned and the overall trend is about N330⁰. This can indicate a tensile regime with a trend perpendicular to the mentioned orientation, which results from the activity of the Dasht-e-Bayaz fault. Finding more evidences requires further studies.
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Open Access November 23, 2021

BDNF, A Focus to Major Depression

Abstract Major depressive disorder is characterized, among other symptoms, by depressed mood and anhedonia associated with a high rate of suicidal ideation. In recent years, research has shown reduced expression of the brain-derived neurotrophic factor (BDNF) in limbic areas of individuals with depression. This reduction of BDNF is reversed by antidepressants in animal models of stress. Stress is one of [...] Read more.
Major depressive disorder is characterized, among other symptoms, by depressed mood and anhedonia associated with a high rate of suicidal ideation. In recent years, research has shown reduced expression of the brain-derived neurotrophic factor (BDNF) in limbic areas of individuals with depression. This reduction of BDNF is reversed by antidepressants in animal models of stress. Stress is one of the main triggers of mood disorders such as depression. Also, administration of BDNF increases the number of serotonergic fibers and serotonergic innervation, indicating an increase of serotonin in the synaptic cleft by this neurotrophin. Thus, BDNF appears to be one of the targets of antidepressant drugs for the increase of monoamines and remission of symptoms of major depression. The purpose of this review was to show the evidence that indicates BDNF as a molecular substrate for vulnerability to depression and the response of this substrate to the antidepressants.
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Review Article
Open Access November 16, 2021

Determination of Deflection of the Vertical Components: Implications on Terrestrial Geodetic Measurement

Abstract The deflection of the vertical is an important parameter that combines both physical (astronomic) and geometric (geodetic) quantities. It is critical in such areas as datum transformation, reduction of astronomic observation to the geodetic reference surface, geoid modelling and geophysical prospecting. Although the deflection of the vertical is a physical property of the gravitational field of [...] Read more.
The deflection of the vertical is an important parameter that combines both physical (astronomic) and geometric (geodetic) quantities. It is critical in such areas as datum transformation, reduction of astronomic observation to the geodetic reference surface, geoid modelling and geophysical prospecting. Although the deflection of the vertical is a physical property of the gravitational field of the earth; which almost all terrestrial survey measurements, with the exception of spatial distances, made on the earth surface are with respect to the Earth’s gravity vector, because a spirit bubble is usually used to align survey instruments. It has been ignored in most geodetic computation and adjustment. This research work is therefore aimed at computing the component of the deflection of the vertical component for part of Rivers State using a geometric method. This method involves the integration of Global Positioning System (GPS) to obtain the geodetic coordinate of points, precisely levelling to obtain the orthometric height of this point located within the study area. By least square using MATLAB program, the estimated deflections of vertical component parameters for the test station SVG/GPS-002 were; -0.0473” and 0.0393” arc seconds for the north-south and east-west components respectively. The associated standard errors of the North-south and East-west components were ±0.0093” and ±0.0060” arc seconds, respectively. The deflection of the vertical was also computed independently from gravimetric models of the earth as: ξ = 0.0204” ±0.0008814”, η = -0.0345” ±0.0014”; ξ =0.0157” ±0.000755”, η = -0.0246” ±0.0012”; ξ = -0.0546±0.0006014, η = -0.0208±0.0006014 for EGM 2008, EGM 1996 and EGM 1984 respectively. The two-tailed hypothesis test reveals that the estimated deflection component is statistically correct at 95% confidence interval. It was observed that the effect of the deflection of the vertical is directly proportional to the distance of the geodetic baseline. Therefore, including the derived component of deflection of the vertical to the ellipsoidal model will yield high observational accuracy since an ellipsoidal model is not tenable due to its far observational error in the determination of high-quality job. It is important to include the determined deflection of the vertical component for Rivers State, Nigeria.
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Open Access October 28, 2021

Development of an Improved Solid Waste Collection System using Smart Sensors

Abstract Waste collection system has become a challenging task, occasioned by the overflowing garbage bins littered all over the environment, causing environmental hazard and further leading to incurable diseases which endanger life. The present-day waste collection system has proven to be inefficient, taking into consideration the advancement in the technologies on the rise in recent years as well as the [...] Read more.
Waste collection system has become a challenging task, occasioned by the overflowing garbage bins littered all over the environment, causing environmental hazard and further leading to incurable diseases which endanger life. The present-day waste collection system has proven to be inefficient, taking into consideration the advancement in the technologies on the rise in recent years as well as the continuous increase in population growth. As a result of this inefficiency observed, this work developed a model for electronic waste collection system in a telecommunication driven environment. In the system's implementation, PIC18F4620 based instrumentation, integrated with proximity sensor for external monitoring and level sensors for internal monitoring was adopted, while the controlling of the opening and closing of the cabins was implemented using a smart switching board. A remote reporting to the waste management authority so as to systematically plan route-map for garbage collection when the waste cabin is fully filled was done by deploying a 900MHz transmitter interfaced with the system’s controller. The result shows that with this model the waste cabin opens only on account of a user approaching the sensing distance of the system and the cabin is not filled. But when the cabin gets filled and a user approaches the sensing distance of the system, it directs the user to use the nearest waste cabin by displaying a message on the LCD (Liquid Crystal Display), while communicating with relevant authority for the evacuation of the cabin via SMS. It was obviously seen that the automation incorporated into the system had zero impact on the success rate of the system or system availability while introducing a latency of 5.6seconds, which is just 28.0% of the maximum allowable latency of this kind of system, while protecting the environment from environmental pollution and spread of diseases. This work highlights the potentials of (EWCS) Electronic Waste Collection System in monitoring and controlling waste disposal for healthy and clean environment.
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Open Access October 19, 2021

Allometric Models for Predicting Biomass and Carbon Pools of Boscia Senegalensis(Pers.) Lam. Ex Poir. (Capparaceae) Populations in Central Africa: A Case Study from Cameroon

Abstract Accurate estimates of above-ground biomass (AGB) and below-ground biomass (BGB) are essential for estimating carbon (C) balances at various geographical scales and formulating effective climate change mitigation programs. This study aimed to formulate specific allometric equations and carbon stock for B. senegalensis in Cameroon. Destructive sampling technique was used for harvesting and weighing the biomass of 40 individual trees. Allometric models were developed using biomass as dependent variable and tree dendrometric parameters as independent variables. The best models selected based with Adjusted coefficients of determination (Adj.R2), residual standard error (RSE) and Akaike's information criterion (AIC) were: ln (leaf biomass) = 0.08 + 0.31*ln (D2×H×ρ); ln (branch biomass) = 0.14 + 0.65*ln (D²×H×ρ); ln (stem biomass) = 2.03 + 1.32*ln (D²×H); ln (AGB) = 4.55 + 2.85*ln(D) and ln (BGB) =3.04 + 1.64*ln(D). The belowground biomass of B. senegalensis represents on average 25 % of the total aboveground biomass. Aboveground carbon ranged between 7.09 ± 0.42- 9.01 ± 0.50 tC/ha; Belowground carbon ranged between 4.37 ± 0.26 - 7.11 ± 0.35 tC/ha; litter carbon ranged between 0.50 ± 0.02 - 0.95 ± 0.04 tC/ha; herbaceous carbon ranged between 1.05 ± 0.28 - 1.86 ± 0.20 tC/ha ; dead wood carbon ranged between 3.03 ± 0.40 - 8.98 ± 0.44 tC/ha; Soil Organic Carbon Stock varies between4.33 ± 0.79 - 6.14 ± 1.05 tC/ha ;Total carbon were 33.24 ± 4.28;27.40 ± 3.35;27.27 ± 3.27and 21.18 ± 3.00 tC/ha in site 3, site 2, site 1 and site 4 respectively.The specific allometric equation developed for B. senegalensis [...] Read more.
Accurate estimates of above-ground biomass (AGB) and below-ground biomass (BGB) are essential for estimating carbon (C) balances at various geographical scales and formulating effective climate change mitigation programs. This study aimed to formulate specific allometric equations and carbon stock for B. senegalensis in Cameroon. Destructive sampling technique was used for harvesting and weighing the biomass of 40 individual trees. Allometric models were developed using biomass as dependent variable and tree dendrometric parameters as independent variables. The best models selected based with Adjusted coefficients of determination (Adj.R2), residual standard error (RSE) and Akaike's information criterion (AIC) were: ln (leaf biomass) = 0.08 + 0.31*ln (D2×H×ρ); ln (branch biomass) = 0.14 + 0.65*ln (D²×H×ρ); ln (stem biomass) = 2.03 + 1.32*ln (D²×H); ln (AGB) = 4.55 + 2.85*ln(D) and ln (BGB) =3.04 + 1.64*ln(D). The belowground biomass of B. senegalensis represents on average 25 % of the total aboveground biomass. Aboveground carbon ranged between 7.09 ± 0.42- 9.01 ± 0.50 tC/ha; Belowground carbon ranged between 4.37 ± 0.26 - 7.11 ± 0.35 tC/ha; litter carbon ranged between 0.50 ± 0.02 - 0.95 ± 0.04 tC/ha; herbaceous carbon ranged between 1.05 ± 0.28 - 1.86 ± 0.20 tC/ha ; dead wood carbon ranged between 3.03 ± 0.40 - 8.98 ± 0.44 tC/ha; Soil Organic Carbon Stock varies between4.33 ± 0.79 - 6.14 ± 1.05 tC/ha ;Total carbon were 33.24 ± 4.28;27.40 ± 3.35;27.27 ± 3.27and 21.18 ± 3.00 tC/ha in site 3, site 2, site 1 and site 4 respectively.The specific allometric equation developed for B. senegalensis can be used in similar Sudano-Sahelian savannas to implement activities to reduce emissions from deforestation and degradation (REDD+) for the benefit of local carbon trading communities.
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Open Access October 17, 2021

Understanding Traffic Signs by an Intelligent Advanced Driving Assistance System for Smart Vehicles

Abstract Recent technologies have made life smarter. vehicles are vital components in daily life that are getting smarter for a safer environment. Advanced Driving Assistance Systems (ADAS) are widely used in today's vehicles. It has been a revolutionary approach to make roads safer by assisting the driver in difficult situations like collusion, or assistance in respecting road rules. ADAS is composed of a [...] Read more.
Recent technologies have made life smarter. vehicles are vital components in daily life that are getting smarter for a safer environment. Advanced Driving Assistance Systems (ADAS) are widely used in today's vehicles. It has been a revolutionary approach to make roads safer by assisting the driver in difficult situations like collusion, or assistance in respecting road rules. ADAS is composed of a huge number of sensors and processing units to provide a complete overview of the surrounding objects to the driver. In this paper, we introduce a road signs classifier for an ADAS to recognize and understand traffic signs. This classifier is based on a deep learning technique, and, in particular, it uses Convolutional Neural Networks (CNN). The proposed approach is composed of two stages. The first stage is a data preprocessing technique to filter and enhance the quality of the input images to reduce the processing time and improve the recognition accuracy. The second stage is a convolutional CNN model with a skip connection that allows passing semantic features to the top of the network in order to allow for better recognition of traffic signs. Experiments have proved the performance of the CNN model for traffic sign classification with a correct recognition rate of 99.75% on the German traffic sign recognition benchmark GTSRB dataset.
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Open Access October 07, 2021

Comparison of Weak and Strong Theories of Environmental Sustainability in the Conceptual Context of Sustainable Development

Abstract Ever since the idea of sustainable development was proposed, how to achieve it has always been the focus of researchers and policymakers. At the same time, in the letters of sustainable development, two approaches of weak sustainability and strong sustainability have been mentioned; Two approaches with different assumptions suggest different policies and will have different consequences. On the [...] Read more.
Ever since the idea of sustainable development was proposed, how to achieve it has always been the focus of researchers and policymakers. At the same time, in the letters of sustainable development, two approaches of weak sustainability and strong sustainability have been mentioned; Two approaches with different assumptions suggest different policies and will have different consequences. On the other hand, with the increase of environmental concerns in recent decades, the concept of natural capital and physical, human, and social capital has been added to the common literature of economics. Recently, with the collection of data related to the natural capital of nations by the World Bank, the possibility of statistical studies in this field has been provided. In the form of several regression models and at the international level, the present study will analyze the most fundamental difference between the two approaches of weak sustainability and strong sustainability, i.e., the possibility or impossibility of replacing physical capital instead of natural capital. The study results show that natural capital has a direct, positive, and independent role in explaining sustainable development indicators. Even the addition of physical, human, and social capital indicators does not threaten the significant coefficient of natural capital. Therefore, it can be concluded that under the assumption of a strong sustainability model, other types of capital can not replace natural capital.
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Open Access October 07, 2021

Estimation of Clear Sky Normal Irradiance over Northern Nigeria Atmosphere

Abstract Energy from the sun is an ideal new energy source for power systems, in a context of sustainable development, enthusiasm for concentrated solar power technologies is developing. Accurate estimation of clear-sky radiation is needed in many engineering, architectural and agricultural applications in order to integrate solar energy into the power grid. An evaluation of the irradiance input to solar [...] Read more.
Energy from the sun is an ideal new energy source for power systems, in a context of sustainable development, enthusiasm for concentrated solar power technologies is developing. Accurate estimation of clear-sky radiation is needed in many engineering, architectural and agricultural applications in order to integrate solar energy into the power grid. An evaluation of the irradiance input to solar power systems is required in many applications. Clear-sky models represent the maximum input of solar power systems, which is especially useful for forecasting solar irradiance and numerical weather prediction. This work examined the application of Yang model to estimate the monthly mean clear sky normal irradiance for northern Nigeria using meteorological variables like temperature, relative humidity and solar radiation considering the shading effect of the complex topography of terrain in Norther region of Nigeria, also to know the variation of beam radiation and diffuse radiation among the selected stations and also to ascertain the significance of aerosols, water vapor, and other transmittances in the estimation of the beam and diffuse radiation in the northern atmosphere. The modeling was computed using monthly mean maximum temperature and relative humidity gotten from the Nigeria Meteorological Agency (NIMET) for the period of fourteen years (1983-1997. The beam and diffuse irradiance for the northern atmosphere is compared by estimating their mean and standard deviation. Also, detailed information about the trend of radiation in each of the selected states in the northern hemisphere of Nigeria was obtained using a graphical method of data analysis. Result reveals that the value of beam and diffused radiation getting to the earth's surface depends on the aerosols, water vapour, atmospheric Ozone, gas transmittance and Rayleigh scattering. From the result above, the maximum beam radiation and the minimum diffused radiation occur during the raining season and the minimum beam radiation and maximum diffuse radiation occur during the dry season. This is due to the variations of these atmospheric constituents (aerosols, water vapour, atmospheric Ozone, gas transmittance and Rayleigh scattering) in the northern atmosphere on these seasons.
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Open Access September 23, 2021

Distributed Generation and Optimization of smart Grid Systems: Case Study of Kumba in Cameroon

Abstract The traditional electric grid of the City of Kumba has been experiencing a constant failure which leads inhabitant to experience constant blackout. This constant blackout persists and stays for a long time due to the lack of communication between equipment, consumer and supplier. Whenever there is a fault, the repairing agents walk along the feeder to find the fault. This manual fault finding [...] Read more.
The traditional electric grid of the City of Kumba has been experiencing a constant failure which leads inhabitant to experience constant blackout. This constant blackout persists and stays for a long time due to the lack of communication between equipment, consumer and supplier. Whenever there is a fault, the repairing agents walk along the feeder to find the fault. This manual fault finding increases the restauration time which leads to the augmentation of the blackout period. Factors responsible for the failure of the line are complex to be controlled. It is necessary to reduce restauration time by introducing Information and Communication Technologies (ICT) and sensing system in the grid and making it to be smart. ICT in this smart grid, sensors and smart meters are meant to assure two-way communication between the supplier and the consumer. They send real time information which is computed at the control center to optimize the entire grid. Distributed generation is also introduced in the system for two purposes. To complete the lag in power demand of the grid and to take over the supply when the main feeder is faulty. Various distributed generation sources studied led to the choice of solar power plants thanks to their low production of Greenhouse Gas (GHG) and availability of their resources in the city. A model has been proposed for the distributed generation and optimization of the smart grid. The system indexes obtained without distributed generation in the grid are different from that with. The difference in these indexes proved that the grid has been optimized. However, the reliability of the grid is enhanced after the introduction of distributed generation into the system. This enhancement in reliability declares that with distributed generation into the grid, the population of Kumba has a reliable power supply, which makes them to have energy throughout.
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Open Access August 24, 2021

The Art of Shoot: The 3D Model Presents a Smart Digital Way Teaching of Basketball

Abstract Sport is an art form. Every athlete thinks, creates, obeys rules, plans, and produces tangible results. Like most art forms, basketball for learning, monitoring, and understanding the sport requires all five senses. With the same logic by which an architect plans to build a building, the basketball team prepares for the game mode, the systems, which they will have in a match. In summary the [...] Read more.
Sport is an art form. Every athlete thinks, creates, obeys rules, plans, and produces tangible results. Like most art forms, basketball for learning, monitoring, and understanding the sport requires all five senses. With the same logic by which an architect plans to build a building, the basketball team prepares for the game mode, the systems, which they will have in a match. In summary the players and the coaching staff think before they do. For this reason, in basketball it is important to create a philosophy and a system of values in the team. Values such as trust, solidarity, cooperation, ambition, consistency are important for building the mindset among stakeholders for the successful course of the team and for titles. Finally, sport produces knowledge. Basketball is an evolving and progressive sport. Adapting to modern requirements, studying, and monitoring new trends. For example, the specialization of players in Shoot, in speed in, power, strong, results in an increase in the ability of players to man-to-man attacks. On the other hand, the defensive function of both individual and team needs to deepen the proper treatment of powerful offensive players.
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Open Access August 21, 2021

Virologic Microparticle Fluid Mechanics Simulation: COVID-19 Transmission in the Protected and Unprotected Conversations

Abstract SARS-COV-19 is a serious respiratory infection created by a devastating coronavirus family (2019-nCoV) that has become the first global epidemic of the last one hundred years. It is a highly transmissible virus transmitted by inhalation or contact with the droplet core produced by infected people when they sneeze, cough, and speak. SARS-COV-2 transmission in the air is possible even in a confined [...] Read more.
SARS-COV-19 is a serious respiratory infection created by a devastating coronavirus family (2019-nCoV) that has become the first global epidemic of the last one hundred years. It is a highly transmissible virus transmitted by inhalation or contact with the droplet core produced by infected people when they sneeze, cough, and speak. SARS-COV-2 transmission in the air is possible even in a confined space near the infected person. This study aimed to evaluate the effectiveness of using a shield or mask as a barrier to a patient’s face against the spread of virus particles. For the present simulation, the discrete phase model (DPM) is used; Because this model allows us to study the particle’s mass discretely in a fluid space with the continuous phase. Due to the choice of this model, the virus particles secreted from the patient’s mouth are considered a discrete phase, and the open airflow in the computational area is considered a continuous phase. The present study uses fluent 2019R3 software to simulate the virus transmission to model the transient flows numerically. The analysis found that the masks or shields can be an effective method of protecting the participants of a conversation in the presence of an infected person.
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Review Article
Open Access August 14, 2021

Complex Energy Conversion System Analysis: An Overview

Abstract This article describes the optimization models recently applied to the design and operation of power systems towards forming smart grids and identifies trends, barriers, and possible gaps in this area. Models are described to optimize the design and operation of power systems considering renewable energies, distributed generation, microgrids, demand management, and energy storage systems. It was [...] Read more.
This article describes the optimization models recently applied to the design and operation of power systems towards forming smart grids and identifies trends, barriers, and possible gaps in this area. Models are described to optimize the design and operation of power systems considering renewable energies, distributed generation, microgrids, demand management, and energy storage systems. It was concluded that it is necessary to validate many of the models formulated recently to optimize the operation through tests with real data and on a large scale. Furthermore, demand management and microgrids are aspects in which it is necessary to develop models for optimal power flow. Finally, it is necessary to predict stochastic variables with greater precision so that these models adapt to the real behavior of the system.
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Open Access August 14, 2021

Oil shocks and the Economic Growth: A Study for Oil-importing and Exporting Countries in the Time of Covid-19

Abstract This article discusses the effect of the oil shock on some OECD oil-importing countries such as Canada, France, Italy, China, and the United States and some OPEC oil-exporting countries such as Algeria, Iran, Kuwait, Saudi Arabia, and Venezuela. The model is estimated for the years 1976-2021. five annual variables are used for each country. The variables within the model include real oil prices, [...] Read more.
This article discusses the effect of the oil shock on some OECD oil-importing countries such as Canada, France, Italy, China, and the United States and some OPEC oil-exporting countries such as Algeria, Iran, Kuwait, Saudi Arabia, and Venezuela. The model is estimated for the years 1976-2021. five annual variables are used for each country. The variables within the model include real oil prices, GDP growth, inflation, real wages, and real effective exchange rates. Real GDP is the main variable that shows the effects of oil prices on the economy, and the impact of oil prices on other model variables will indirectly affect economic activities. For this purpose, we estimate the vector autoregression model. Estimates obtained for different countries show that oil price shocks are one of the variables affecting economic growth. Also, in oil-exporting countries, oil shocks on economic growth are positive and negative in oil-importing countries. Also, Covid-19 is studied as an effective parameter in creating oil shocks.
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Open Access August 09, 2021

Investigation of the Optimal Model for the Development of Renewable Energy in Iran using a Robust Optimization Approach

Abstract Due to its geographical location, Iran has numerous capacities in renewable energy, and this issue has made the need to develop renewable energy on the authorities’ agenda. This underscores the need to provide an optimal model for developing renewable energy. Therefore, in this study, the main purpose was to provide an optimal renewable energy model. In line with this goal, by choosing the cost [...] Read more.
Due to its geographical location, Iran has numerous capacities in renewable energy, and this issue has made the need to develop renewable energy on the authorities’ agenda. This underscores the need to provide an optimal model for developing renewable energy. Therefore, in this study, the main purpose was to provide an optimal renewable energy model. In line with this goal, by choosing the cost function as the objective function and considering the potential constraints of renewable energy (resource constraints), the amount of electricity consumption in each of the 16 electricity regions (demand constraint) and the limitation of renewable energy production coefficient (Technical constraints), the optimal model of renewable energy use was designed and solved using a solid programming model in LINGO software. The optimal model results show 15.19% small hydropower, 24.30% wind energy, 5.52% biomass energy, 6.13% is geothermal energy, 4.79% is tidal energy, and 44.07% solar energy. The optimum portfolio of renewable energy is estimated in this paper using the robust optimization approach. The results showed which renewable technology has the greater potential to take more share of the energy portfolio. The results of this investigation help policymakers to choose the most suitable renewable technologies to support.
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Open Access August 09, 2021

Optimization and Prediction of Biodiesel Yield from Moringa Seed Oil and Characterization

Abstract In this study, oil was extracted from Moringa seed using mechanical and solvent methods. To transesterify the oil into biodiesel, factorial design of experiment of 24 was used to obtain different combination factors at different level of reaction temperature, catalyst amount, reaction time and alcohol to oil ratio, giving rise to 48 experimental runs. The oil sample was transesterified [...] Read more.
In this study, oil was extracted from Moringa seed using mechanical and solvent methods. To transesterify the oil into biodiesel, factorial design of experiment of 24 was used to obtain different combination factors at different level of reaction temperature, catalyst amount, reaction time and alcohol to oil ratio, giving rise to 48 experimental runs. The oil sample was transesterified in 48 experimental runs, in each case the biodiesel yield was recorded in percentage. The biodiesel was then characterized according to ASTM test protocol. Factorial design model was developed using Design Expert 7.0, the model generated R of 0.987 and Mean Square Error (MSE) of 5.0453 and was used to predict and optimize biodiesel yield. Artificial Neural Network (ANN) model from MATLAB R2016a was developed using 4 input variables and 30 runs, the remaining 18 runs were tested with the ANN model to predict and compare the biodiesel yield with the experimental biodiesel yield, the model generated R value of 0.99687 and MSE of 3.50804. It was found that solvent method yielded more oil than mechanical method, the biodiesel has good thermo-physical property, optimum biodiesel yield of 91.45 % was obtained at 5:1 alcohol/ oil molar ratio, 18.89 wt% catalyst amounts, 45 minutes reaction time and at 45 reaction temperature. The experimental validation yielded 88.33 % biodiesel. The ANN model adequately predicted the remaining 18 runs with R2 value of 0.99649 and MSE of 4.914243. Both models proved adequate enough to predict biodiesel yield but ANN model proved more adequate.
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Open Access July 30, 2021

Air of Uncertainty from Pollution Profiteers: Status of Ambient Air Quality of Sawmill Industry in Ilorin Metropolis, Kwara State, Nigeria

Abstract We can’t stop breathing, but we can do something about the quality of air that we breathe. Clean fresh air is indispensable ingredient for a good life quality. Individuals poses the right towards expecting that the breathed air will not harm people. Thus, fighting air pollution will not only improve health outcomes, productivity, and well-being, it’s also essential toward reducing the emissions of [...] Read more.
We can’t stop breathing, but we can do something about the quality of air that we breathe. Clean fresh air is indispensable ingredient for a good life quality. Individuals poses the right towards expecting that the breathed air will not harm people. Thus, fighting air pollution will not only improve health outcomes, productivity, and well-being, it’s also essential toward reducing the emissions of greenhouse gas as well as fighting climate change. For examples, a third of the global population is at risk from unhealthy of ambient air pollutants concentrations, with the loss of approximately 6.4 million healthy-life-years attributed specifically to chronic exposure to ambient particulate matter. Expert panels have consistently rated air pollution as a greater health hazard than water pollution. Pollution of air is the leading source of unexplained and undiagnosed diseases, besides have remained associated with a variety of serious human health risks, and in fact, a threshold has not been established under which these pollutants exert no adverse effects. This study evaluates ambient air quality at major sawmill sites in Ilorin Metropolis, Kwara State, Nigeria. “Measurements of Air pollution were accurately carried out using direct reading, automatic in situ gas monitors; Hand held mobile multi-gas monitor with model AS8900 [Combustible (LEL), and Oxygen (O2)], BLATN with model BR – Smart Series air quality monitor (PM10, Formaldehyde) and air quality multimeter with model B SIDE EET100 (Dust (PM2.5), VOC, Temperature and Relative Humidity)”. The outcomes disclosed among others, the average concentrations of CO, O2 as well as other measured parameters for instance formaldehyde (HcHo) etc., they are also consistently low as well as within acceptable range in terms of National as well as Global monitoring standards for air quality indices. However, there are few exceptions for instance the average volatile organic compounds (VOCs) concentrations, PM2.5, PM10 as well as Combustible (LEL) respectively, which are higher when compared to National and Global standards. This high figure is due to pollutant amount existing in the sawmills air environment resulting from input of influents from activities of the sawmill. However, as a result, air pollution in the city of Ilorin is found to be increasingly polluted and are of major health concern because of their synergistic action. Due to the high evidences and values, it can lead to a remarkable rise in over-all figure of hospital visits/ patients’ admissions with acute respiratory illnesses as soon as air pollutants level remained high. Hence, there is the need for an aggressive control of ambient air pollution.
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Open Access July 24, 2021

Cancer Incidence in Algeria: Fuzzy Inference System Modeling

Abstract Background: Cancer surveillance data provide information on the incidence and trends of cancer in the population level. Analyzing cancer trends according to these characteristics plays an important role in cancer surveillance. Knowledge of the causes of cancer allow better prevent the appearance of it. A large number of epidemiological evidence supporting the effect of smoking on the causes [...] Read more.
Background: Cancer surveillance data provide information on the incidence and trends of cancer in the population level. Analyzing cancer trends according to these characteristics plays an important role in cancer surveillance. Knowledge of the causes of cancer allow better prevent the appearance of it. A large number of epidemiological evidence supporting the effect of smoking on the causes of cancer there is strong evidence supporting a role for smoking in the etiology of cancers. Alcohol appears to interact with the tobacco significantly and can be considered a risk factor in the development of cancers. Obesity which is now well recognized as a public health problem increases the risk of developing cancers. All these factors are characterized by uncertainty, complexity and imprecision. Methods: In this study, we propose an analysis of these factors based on the principles of fuzzy logic inference system. The data were collected from WHO data. As this technique addresses the uncertain, its application in this area is perfectly adequate. Results: A database is established, after the analysis system is done, it will be possible to read the prevalence of cancer by introducing randomly the values in inputs variables. Conclusion: like cancer has become a national scourge, this application allows predicting the impact of it just from the introduction inputs variables such as BMI, degree of physical activity, tobacco and sex.
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Open Access July 17, 2021

Nonlinear Whole Seismology, Topological Seismology, Magnitude-Period Formula of Earthquakes and Their Predictions

Abstract First, we propose the nonlinear whole seismology and its three basic laws. Next, based on the nonlinear equations of fluid dynamics in Earth’s crust, we obtain a chaos equation, in which chaos corresponds to the earthquake, and shows complexity on seismology. But, combining the Carlson-Langer model and the Gutenberg-Richter relation, a simplified nonlinear solution and corresponding [...] Read more.
First, we propose the nonlinear whole seismology and its three basic laws. Next, based on the nonlinear equations of fluid dynamics in Earth’s crust, we obtain a chaos equation, in which chaos corresponds to the earthquake, and shows complexity on seismology. But, combining the Carlson-Langer model and the Gutenberg-Richter relation, a simplified nonlinear solution and corresponding magnitude-period formula of earthquakes may be derived approximately. Further, we research the topological seismology. From these theories some predictions can be calculated quantitatively and are already tested. Combining the Lorenz nonlinear model, we may discuss the earthquake migration to and fro. Finally, if various modern scientific instruments, different scientific theories and some paranormal ways for earthquake are combined each other, the accuracy of multilevel prediction will be increased.
Article
Open Access July 17, 2021

DFT-Based Study of Physical, Chemical and Electronic Behavior of Liquid Crystals of Azoxybenzene Group: p-azoxyanisole, p-azoxyphenetole, ethyl-p-azoxybenzoate, ethyl-p-azoxycinnamate and n-octyl-p-azoxycinnamate

Abstract The present work describes the geometry and electronic structures of liquid crystals of azoxybenzene group and their reactivity with respect to molecular properties: total energy, ionization potential, electron affinity, HOMO energy, LUMO energy, electronegativity, hardness and dipole moment. Literature shows that mesomorphism depends particularly on the nature of terminal groups and their [...] Read more.
The present work describes the geometry and electronic structures of liquid crystals of azoxybenzene group and their reactivity with respect to molecular properties: total energy, ionization potential, electron affinity, HOMO energy, LUMO energy, electronegativity, hardness and dipole moment. Literature shows that mesomorphism depends particularly on the nature of terminal groups and their linkages with parent molecule. And thus, substitution of terminal groups can help to fine tune the liquid crystal behavior and also their applications. In this work the effect of four terminal groups of same and diverse nature has been studied. For the study, the molecular modeling and geometry optimization of the compounds have been performed on workspace program of CAChe Pro 5.04 software of Fujitsu using DFT method.
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Open Access August 20, 2022

Advancing Predictive Failure Analytics in Automotive Safety: AI-Driven Approaches for School Buses and Commercial Trucks

Abstract The recent evidence on AI in automotive safety shows the potential to reduce crashes and improve efficiency. Studies used AI techniques like machine learning and predictive analytics models to develop predictive collision avoidance systems. The studies collected data from various sources, such as traffic collision data and shapefiles. They utilized deep learning neural networks and 3D [...] Read more.
The recent evidence on AI in automotive safety shows the potential to reduce crashes and improve efficiency. Studies used AI techniques like machine learning and predictive analytics models to develop predictive collision avoidance systems. The studies collected data from various sources, such as traffic collision data and shapefiles. They utilized deep learning neural networks and 3D visualization techniques to analyze the data. However, there needs to be more research on AI in school bus and commercial truck safety. This paper explores the importance of AI-driven predictive failure analytics in enhancing automotive safety for these vehicles. It will discuss challenges, required data, technologies involved in predictive failure analytics, and the potential benefits and implications for the future. The conclusion will summarize the findings and emphasize the significance of AI in improving driver safety. Overall, this paper contributes to the field of automotive safety and aims to attract more research in this area.
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Review Article
Open Access December 27, 2020

Exploring AI Algorithms for Cancer Classification and Prediction Using Electronic Health Records

Abstract Cell division that is not controlled leads to cancer, an incurable condition. An early diagnosis has the potential to lower death rates from breast cancer, the most frequent disease in women worldwide. Imaging studies of the breast may help doctors find the disease and diagnose it. This study explores an effectiveness of DL and ML models in a classification of mammography images for breast cancer [...] Read more.
Cell division that is not controlled leads to cancer, an incurable condition. An early diagnosis has the potential to lower death rates from breast cancer, the most frequent disease in women worldwide. Imaging studies of the breast may help doctors find the disease and diagnose it. This study explores an effectiveness of DL and ML models in a classification of mammography images for breast cancer detection, utilizing the publicly available CBIS-DDSM dataset, which comprises 5,000 images evenly divided between benign and malignant cases. To improve diagnostic accuracy, models such as Gaussian Naïve Bayes (GNB), CNNs, KNN, and MobileNetV2 were assessed employing performance measures including F1-score, recall, accuracy, and precision. The methodology involved data preprocessing techniques, including transfer learning and feature extraction, followed by data splitting for robust model training and evaluation. Findings indicate that MobileNetV2 achieved a highest accuracy99.4%, significantly outperforming GNB (87.2%), CNN (96.7%), and KNN (91.2%). The outstanding capacity of MobileNetV2 to identify between benign and malignant instances was shown by the investigation, which also made use of confusion matrices and ROC curves to evaluate model performance.
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Open Access December 27, 2020

An Effective Predicting E-Commerce Sales & Management System Based on Machine Learning Methods

Abstract Due to influence of Internet, this e-commerce sector has developed rapidly. Most of the online retailing or selling businesses are seeking for way for predicting their products demand. Sales forecasting may help retailers develop a sales strategy that will enhance sales and attract more money and investment. The current research work puts forward a machine learning framework to forecast E-commerce [...] Read more.
Due to influence of Internet, this e-commerce sector has developed rapidly. Most of the online retailing or selling businesses are seeking for way for predicting their products demand. Sales forecasting may help retailers develop a sales strategy that will enhance sales and attract more money and investment. The current research work puts forward a machine learning framework to forecast E-commerce sales for strategic management using a dataset of E-commerce transactions. With 70 percent of the data for train and 30 percent for test, three models were produced, namely, Random Forest, Decision Tree, and XGBoost. In order to evaluate the models, performance measures inclusive of R-squared (R²) and Root Mean Squared Error (RMSE) were employed. Thus, the XGBoost model was the most accurate in marketing predictive capabilities for E-commerce sales with the R² score of 96.3%. This has demonstrated the increased capability of XGBoost algorithm to forecast E-commerce monthly sales more accurately than other models and can assist decision makers for managing inventory and arriving smart and quick decisions in this rapidly growing E-commerce market. The findings reiterate the importance of using advanced analytics in order to drive effectiveness and customer experience within E-commerce sector.
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Open Access October 15, 2022

Big Data and AI/ML in Threat Detection: A New Era of Cybersecurity

Abstract The unrelenting proliferation of data, entwined with the prevalence of mobile devices, has given birth to an unprecedented growth of information obscured by noise. With the Internet of Things and myriad endpoint devices generating vast volumes of sensitive and critical data, organizations are tasked with extracting actionable intelligence from this deluge. Governments and enterprises alike, even [...] Read more.
The unrelenting proliferation of data, entwined with the prevalence of mobile devices, has given birth to an unprecedented growth of information obscured by noise. With the Internet of Things and myriad endpoint devices generating vast volumes of sensitive and critical data, organizations are tasked with extracting actionable intelligence from this deluge. Governments and enterprises alike, even under pressure from regulatory boards, have strived to harness the power of data and leverage it to enhance safety and security, maximize performance, and mitigate risks. However, the adversaries themselves have capitalized on the unequal battle of big data and artificial intelligence to inflict widespread chaos. Therefore, the demand for big data analytics and AI/ML for high-fidelity intelligence, surveillance, and reconnaissance is at its highest. Today, in the cybersecurity realm, the detection of adverse incidents poses substantial challenges due to the sheer variety, volume, and velocity of deep packet inspection data. State-of-the-art detection techniques have fallen short of detecting the latest attacks after a big data breach incident. On the other hand, computational intelligence techniques such as machine learning have reignited the search for solutions for diverse monitoring problems. Recent advancements in AI/ML frameworks have the potential to analyze IoT/edge-generated big data in near real-time and assist risk assessment and mitigation through automated threat detection and modeling in the big data and AI/ML domain. Industry best practices and case studies are examined that endeavor to showcase how big data coupled with AI/ML unlocks new dimensions and capabilities in improved vigilance and monitoring, prediction of adverse incidents, intelligent modeling, and future uncertainty quantification by data resampling correction. All of these avenues lead to enhanced robustness, security, safety, and performance of industrial processes, computing, and infrastructures. A view of the future and how the potential threats due to the misuse of new technologies from bandwidth to IoT/edge, blockchain, AI, quantum, and autonomous fields is discussed. Cybersecurity is again playing out at a pace set by adversaries with low entry barriers and debilitating tools. The need for innovative solutions for defense from the emerging threat landscape, harnessing the power of new technologies and collaboration, is emphasized.
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Open Access December 27, 2021

Leveraging AI in Urban Traffic Management: Addressing Congestion and Traffic Flow with Intelligent Systems

Abstract Traffic congestion across the globe is a multimodal problem, intertwining vehicular, pedestrian, and bicycle traffic. The relationship between the multimodal traffic flow is a key factor in understanding urban traffic dynamics. The impact of excessive congestion extends to the excessive cost spent on traffic maintenance, as well as the inherent transportation inefficiency and delayed travel times. [...] Read more.
Traffic congestion across the globe is a multimodal problem, intertwining vehicular, pedestrian, and bicycle traffic. The relationship between the multimodal traffic flow is a key factor in understanding urban traffic dynamics. The impact of excessive congestion extends to the excessive cost spent on traffic maintenance, as well as the inherent transportation inefficiency and delayed travel times. From an urban transportation standpoint, an immediate consideration on one hand is monitoring traffic conditions and demand cycles, while on the other hand inducing flow modifications that benefit the traffic network and mitigate congestion. Embedded and centralized control systems that characterize modern traffic management systems extract traffic conditions specific to their regions but lack communication between networks. Moreover, innovative methods are required to provide more accurate up-to-date traffic forecasts that characterize real-world traffic dynamics and facilitate optimal traffic management decisions. In this chapter, we briefly outline the main difficulties and complexities in modeling, managing, and forecasting traffic dynamics. We also compare various conventional and modern Intelligent Transportation Strategies in terms of accuracy and applicability, their performance, and potential opportunities for optimization of multimodal traffic flow and congestion reduction. This chapter introduces various proposed data-driven models and tools employed for traffic flow prediction and management, investigating specific strategies' strengths, weaknesses, and benefits in addressing various real-world traffic management problems. We describe that the design phase of dependable Intelligent Transportation Systems bears unique requirements in terms of the robustness, safety, and response times of their components and the encompassing system model. Furthermore, this architectural blueprint shares similarities with distributed coordinate searching and collective adaptive systems. Town size-independent models induce systemic performance improvements through reconfigurable embedded functionality. These AI techniques feature elaborate anytime planner-engagers ensuring near-optimal performances in an unbiased behavior when the model complexity is varied. Sustainable models minimize congestion during peaks, flooding, and emergency occurrences as they adhere to area-specific regulations. Security-aware and fail-safe traffic management systems relinquish reasonable assurances of persistent operation under various environmental settings, to acknowledge metropolis and complex traffic junctions. The chapter concludes by outlining challenges, research questions, and future research paths in the field of transportation management.
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Open Access December 27, 2021

Financial Implications of Predictive Analytics in Vehicle Manufacturing: Insights for Budget Optimization and Resource Allocation

Abstract Factory owners and vehicle manufacturers increasingly opt for predictive analytics to inform their decisions. While predictive analytics have been proven to provide insights into the initiation of maintenance measures before a machine actually fails, the right models and features could have a significant impact on the budget spent and resources allocated. This means that financially oriented [...] Read more.
Factory owners and vehicle manufacturers increasingly opt for predictive analytics to inform their decisions. While predictive analytics have been proven to provide insights into the initiation of maintenance measures before a machine actually fails, the right models and features could have a significant impact on the budget spent and resources allocated. This means that financially oriented questions need to at least partially guide the decisions in the planning phase of data science projects. Data-driven approaches will play an increasingly important role, but only a few of the firms that were confident performed logistic regression models for predictive maintenance. Also, from the available knowledge, data-driven classification models connecting vehicle component failures and the occurrence of delays at the assembly line have not been published. This paper utilizes a real-world data-driven approach using classification models in predictive analytics by vehicle manufacturers and thereby links the financial implications of such data science projects to their results. We expand the existing literature on predictive maintenance and possess a unique dataset of newly launched series of vehicles, presented as-is. Our research context is of interest to researchers and practitioners in the automotive industry that manage and plan the final vehicle assembly with just-in-time principles, factoring the consequences of component failures on the assembly process. Key findings of this paper highlight that while minor tweaking of the models is possible, their potential input in decision-making processes for budget optimization is limited.
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Open Access October 29, 2022

Neural Networks for Enhancing Rail Safety and Security: Real-Time Monitoring and Incident Prediction

Abstract The growth in demand for rail transportation systems within cities, together with high-speed and long-distance transportation running on a rail network, raises the issues of both rail safety and security. If an accident or an attack occurs, its consequences can be extremely severe. To mitigate the impact of these events, the real-time monitoring of a rail system is required. In that case, the [...] Read more.
The growth in demand for rail transportation systems within cities, together with high-speed and long-distance transportation running on a rail network, raises the issues of both rail safety and security. If an accident or an attack occurs, its consequences can be extremely severe. To mitigate the impact of these events, the real-time monitoring of a rail system is required. In that case, the improvements in monitoring can be achieved using artificial intelligence algorithms such as neural networks. Neural networks have been used to achieve real-time incident identification in monitoring the track quality in terms of classifying the graphical outputs of an ultrasonic system working with the rails and track bed, to predict incidents on the rail infrastructure due to transmission channels becoming blocked, and also to attempt scheduling preemptive and preventative maintenance. In terms of forecasting incidents and accidents on board the trains, neural networks have been used to model passenger behavior and optimize responses during a train station evacuation. In tackling the incidents and accidents occurring on rail transport, we contribute with two methodologies to detect anomalies in real-time and identify the level of security risk: at the maintenance level with personnel operating along the railways, and onboard passenger trains. These methodologies were evaluated on real-world datasets and shown to be able to achieve a high accuracy in the results. The results generated from these case studies also reveal the potential for network-wide applications, which could enhance security and safety on railway networks by offering the possibility of better managing network disruptions and more rapidly identifying security issues. The speed and coverage of the information generated through the implementation of these methodologies have implications in utilizing prediction for decision support and enhancing safety and security on board the rail network.
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Open Access November 16, 2023

Innovations in Agricultural Machinery: Assessing the Impact of Advanced Technologies on Farm Efficiency

Abstract Progress in the development and adoption of technological innovations is instrumental in enhancing the efficiency of production systems across the globe. Through the introduction of cost-efficient and high-performing technologies, countries can both reduce the resource use intensity of their economies and boost the global supply of essential products. The focus of this study is to analyze the [...] Read more.
Progress in the development and adoption of technological innovations is instrumental in enhancing the efficiency of production systems across the globe. Through the introduction of cost-efficient and high-performing technologies, countries can both reduce the resource use intensity of their economies and boost the global supply of essential products. The focus of this study is to analyze the application of advanced machinery and mechanisms within the agricultural sector, a primary industry that acts as a major contributor to the gross domestic product (GDP) of many nations. Specifically, this paper provides an in-depth review of the latest impact assessments based on analytical and modeling tools conducted on agricultural machinery and production technologies. Our findings highlight the positive role played by scientific progress and innovation in driving the competitiveness, growth and improved sustainability of the agricultural sector. Over the years, advanced technologies have accelerated the development and modernization of machinery, equipment, and processes in farming. Typically, modern machinery and equipment have enabled large-scale production on farms, enhancing the cost-efficient use of both land and labor, as well as the capacity and timeliness in performing essential agricultural operations. The rapid diffusion of technical advancements has further contributed to resource savings, productivity growth, and the overall transformation of agricultural value chains. Accordingly, the implementation of appropriate enabling conditions is of vital importance in encouraging the widespread integration of technologies in agriculture, not only boosting productivity along the agri-food chain but also yielding widespread social, economic, and environmental benefits.
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Open Access October 30, 2022

Towards Autonomous Analytics: The Evolution of Self-Service BI Platforms with Machine Learning Integration

Abstract Self-service business intelligence (BI) platforms have become essential applications for exploring, analyzing, and visualizing business data in various domains. Here, we envisage that the business intelligence platform will perform automatic and autonomous data analytics with minimal to no user interaction. We aim to offer a data-driven, intelligent, and scalable infrastructure that amplifies the [...] Read more.
Self-service business intelligence (BI) platforms have become essential applications for exploring, analyzing, and visualizing business data in various domains. Here, we envisage that the business intelligence platform will perform automatic and autonomous data analytics with minimal to no user interaction. We aim to offer a data-driven, intelligent, and scalable infrastructure that amplifies the advantages of BI systems and discovers hidden and complex insights from very large business datasets, which a business analyst can miss during manual exploratory data analysis. Towards our future vision of autonomous analytics, we propose a collective machine learning model repository with an integration layer for user-defined analytical goals within the BI platform. The proposed architecture can effectively reduce the cognitive load on users for repetitive tasks, democratizing data science expertise across data workers and facilitating a less experienced user community to develop and use advanced machine learning and statistical algorithms.
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Open Access November 05, 2022

Application of Neural Networks in Optimizing Health Outcomes in Medicare Advantage and Supplement Plans

Abstract The growing complexity and variability in healthcare delivery and costs within Medicare Advantage (MA) and Medicare Supplement (Medigap) plans present significant challenges for improving health outcomes and managing expenditures. Neural networks, a subset of artificial intelligence (AI), have shown considerable promise in optimizing healthcare processes, particularly in predictive modeling, [...] Read more.
The growing complexity and variability in healthcare delivery and costs within Medicare Advantage (MA) and Medicare Supplement (Medigap) plans present significant challenges for improving health outcomes and managing expenditures. Neural networks, a subset of artificial intelligence (AI), have shown considerable promise in optimizing healthcare processes, particularly in predictive modeling, personalized treatment recommendations, and risk stratification. This paper explores the application of neural networks in enhancing health outcomes within the context of Medicare Advantage and Supplement plans. We review how deep learning models can be leveraged to predict patient risk, optimize resource allocation, and identify at-risk populations for preventive interventions. Additionally, we discuss the potential for neural networks to improve claims processing, reduce fraud, and streamline administrative burdens. By integrating various data sources, including medical records, claims data, and demographic information, neural networks enable more accurate and efficient decision-making processes. Ultimately, this approach can lead to better patient care, reduced healthcare costs, and improved satisfaction for beneficiaries of these programs. The paper concludes by highlighting the current limitations, ethical considerations, and future directions for AI adoption in the Medicare Advantage and Supplement sectors.
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Open Access November 16, 2023

Zero Carbon Manufacturing in the Automotive Industry: Integrating Predictive Analytics to Achieve Sustainable Production

Abstract This charge-ahead paper suggests that transitioning the automotive industry towards a zero-carbon ecosystem from material to end-of-life can be accomplished through disruptive zero-carbon manufacturing in the broad area of all-electric vehicle production technology. To accomplish zero carbon emission automotive manufacturing in the vehicle assembly domain, future paradigms must converge on the [...] Read more.
This charge-ahead paper suggests that transitioning the automotive industry towards a zero-carbon ecosystem from material to end-of-life can be accomplished through disruptive zero-carbon manufacturing in the broad area of all-electric vehicle production technology. To accomplish zero carbon emission automotive manufacturing in the vehicle assembly domain, future paradigms must converge on the decoupling of carbon dioxide emissions from automobile manufacturing and use the design, processing, and manufacturing conditions. The envisioned zero carbon emission vehicle manufacturing domain consists of two complementary components: (a) making more efficient use of energy and (b) reducing carbon in energy use. This paper presents the status of key scientific and technological advancements to bring the manufacturing model of today to a zero-carbon ecosystem for the entire automotive industry of tomorrow. This paper suggests the groundbreaking application of dynamic and distributed predictive scheduling algorithms and open sensing and visualization technology to meet the zero carbon emission vehicle manufacturing goals. Power-aware high-performance computing clusters have recently become a viable solution for sustainable production. Advances in scalable and self-adaptive monitoring, predictive analytics, timeline-based machine learning, and digital replica of cyber-physical systems are also seen co-evolving in the zero carbon manufacturing future. These methods are inspired by initiatives to decouple gross domestic product growth and energy-related carbon dioxide emissions. Stakeholders could co-design and implement shared roadmaps to transition the automotive manufacturing sector with relevant societal and environmental benefits. The automated mobility sector offers a program, an industry-leading example of transforming an automotive production facility to carbon neutrality status. The conclusions from this paper challenge automotive manufacturers to engage in industry offsetting and carbon tax programs to drive continuous improvement and circular vehicle flows via a multi-directional zero-carbon smart grid.
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Open Access December 27, 2023

Leveraging Artificial Intelligence to Enhance Supply Chain Resilience: A Study of Predictive Analytics and Risk Mitigation Strategies

Abstract The management of supply chains is increasingly complex. This study provides a comparative analysis of the cost-benefit analysis for managing various risks. It identifies the financial implications of leveraging artificial intelligence in supply chains to better address risk. Empirical results show a business case for managing some sources of risk more proactively facilitated through predictive [...] Read more.
The management of supply chains is increasingly complex. This study provides a comparative analysis of the cost-benefit analysis for managing various risks. It identifies the financial implications of leveraging artificial intelligence in supply chains to better address risk. Empirical results show a business case for managing some sources of risk more proactively facilitated through predictive modeling techniques offered by AI. Across investigation streams, the use of AI results in an average total cost saving ranging from 41,254 to 4,099,617. Findings from our research can be used to inform managers and theorists about the implications of integrating AI technologies to manage risks in the supply chain. Our work also highlights areas for future research. Given the growing interest in studying sub-second forecasting, our research could be a point of departure for future investigations aimed at considering the impact of forecasting horizons such as an intra-day basis. We formulate a conceptual framework that considers how and to what extent performance evaluation metrics vary according to differences in the fidelity of predictive models and factor importance for identifying risks. We also utilize a mixed-method approach to demonstrate the applicability of our ideas in practice. Our results illustrate the financial implications of integrating AI predictive tools with business processes. Results suggest that real-world companies can circumvent inefficiencies associated with trying to manage many classes of risk via the use of AI-enhanced predictive analytics. As managers need to justify investment to top management, our work supports decision-making by providing a means of conducting a trade-off analysis at the tactical level.
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