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.

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.

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.

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.

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.

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.

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.

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.

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.

Objective: Previous research has underscored the link between allostatic load—a comprehensive indicator of the cumulative physiological burden of chronic stress—and depression. However, there remains a significant gap in understanding how this relationship may differ across race and sex intersectional groups. This study aimed to investigate variations in the association between elevated allostatic load (AL>4) and depression among different race-sex intersectional groups within the general population. Methods: This cross-sectional secondary analysis utilized data from the National Health and Nutrition Examination Survey (NHANES) spanning 2005-2018. The analysis included variables such as race, sex, age, socioeconomic status, depression (measured via the Patient Health Questionnaire - PHQ), and allostatic load. Linear regression analyses were conducted to examine the interactions between race and sex with allostatic load, focusing on the likelihood of high depression as the outcome. Results: Across the pooled sample, an allostatic load greater than 4 was significantly associated with increased depression. Notably, an interaction effect was observed between race and AL>4 on depression among women, indicating that non-Hispanic Black women with a high allostatic load exhibited more pronounced depressive symptoms (Beta: 1.09, CI: 0.02-2.61). Conversely, among men, allostatic load greater than 4 neither correlated with nor interacted with race to influence depression levels. Conclusion: The study highlights the critical need to consider allostatic load as a key target for interventions that aim to reduce depression among Black women. These findings underscore the necessity for customized intervention strategies that address the nuanced race-sex disparities in the impact of allostatic load on mental health across populations.

A Medical devices and pharmaceutical drugs are packaged to maintain their stability and integrity during post-production shipping and storage prior to clinical usage. During delivery and storage, the packaging may come into direct or indirect contact with the drug product or medical device, which may result in chemical interactions between the two. Packaging can be crucial for success, protection, and sale. Like other supermarket items, prescription pharmaceuticals must be packaged in a way that will meet the needs of security and provide speedy packaging, safety, identity, superiority of products, patient safety, and goods superiority. Packaging is a science and an art where many factors are taken into account, starting with the fundamental design and technology used to pack the product without any instability and providing protection, presentation and observance of manufactured goods during transportation, storage, and consumption. In order to keep the drug physiochemical, biological, and chemical stability, packaging professionals create containers that can withstand the pressures that are applied during the supply and shipping processes. Improvements in the analysis of prescription drug development had long been fixated on packaging expertise.

Networking has become more common in recent years because it provides structural support and consistent avenues for contact among experts. The purpose of the study was to examine tutors’ and students’ perceptions and sustenance of networking in Food and Nutrition education in the Colleges of Education of Ghana. Quantitatively the study employed a cross-sectional survey research design. The population of the study comprised tutors and students in the Colleges of Education in Ghana offering Food and Nutrition. Purposive, stratified and simple random sampling techniques were used to select colleges of education, 16 tutors and 256 students for the study. The main instrument used for data collection was a questionnaire. The data collected were processed and analysed with the aid of Statistical Package for Social Sciences (SPSS) version 23.0. All statistical analyses were tested at a 5% level of significance. Levene's Test for Equality of Variances was computed to determine the significant difference in the perception of networking in Food and Nutrition education between tutors and students. It can be concluded that both tutors and students are in favour of networking in Food and Nutrition education. The tutors and students believed networking education can foster collaboration, help implement new ideas to improve the quality of teaching, create an environment conducive to teaching and learning; and help students in sharing vital information. Since there is a positive perception on the use of networking, it is recommended that the tutors should foster collaboration, and create a conducive environment to enhance the positive perception and smooth implementation of networking in Food and Nutrition education at Colleges of Education in Ghana. The study indicated that in order to sustain networking education, teachers need to be more cognizant of their interactions and the influence they have on students. It is therefore recommended that teachers maintain contact with students, and ensure a spirit of unity in diversity among the students.

The study sought to analyze the communicative functions of metaphors in Selected political speeches of Mr. John Dramani Mahama. Critical Metaphor Analysis (CMA) developed by Jonathan Charteris-Black as an approach solely for the analysis of metaphors in political discourse was adopted as a theoretical framework for the study. The study is rooted in a qualitative research approach and grounded in textual analysis as the design. The sampling method adopted in the study was purposive, and the analysis was done in line with the research question posed. The study has shown that language plays a crucial role in human existence as a means of communicating world events. The study has also revealed that in Critical Discourse Analysis, metaphor is conceived as speech actions which build together to create coherent social interactions. This study has indicated that metaphor is a cognitive phenomenon other than a purely lexical one. The study concludes that metaphor is a deep-seated conceptual phenomenon that shapes the way we think (and not just the way we speak). Working inductively from the bottom up with a metaphor, CDA has been able to reveal a rich body of facts about discourse and demonstrate that CDA follows an elaborate, but systematic, set of rules or architecture. It is recommended that future studies could explore the possibility of quantifying the frequency of the occurrence of metaphors and known end results to find out whether there is a correlation between the number of metaphors and persuasion. It is also recommended that research could also be carried out into Ghanaian politics as a discourse community with a view to unearthing language basically associated with that vocation. A study could also be conducted into the use of other rhetorical/oratorical devices, e.g. the politicians’ use of analogy in their speeches.

Effective Inclusive education experiences can be built through structured interventions. The purpose of the study was to assess the impact of inclusive education experiences on teacher-trainees with sensory impairment in the Ghana Colleges of Educations of Ghana. The study was based on pragmatist philosophy. The study adopted convergent parallel mixed-methods approach. The population involved all 66 students with sensory (visual and hearing) impaired in the three (3) CoEs (PCE, Akropong Akwapim, WESCO, Kumasi and NJA, Wa) that practice inclusive education (IE) during the 2018/19 academic year. Purposive and census sampling techniques were used to select the three (3) colleges of education and sixty-six students for the study. The main instruments for data collection were questionnaire and focus group discussion. The quantitative data items were coded for input into the Statistical Product and Service Solutions (SPSS) version 23 software and analysed using means and standard deviations. The qualitative extracts collected into themes that were coded, analysed and interpreted. The study revealed that teacher-trainees had varied experiences on campus, while they felt welcomed into the inclusive institution; they also felt the Colleges were not well prepared to meet their needs. The physical environment was not conducive for the VI on campus. It is recommended that, College authorities should work with the MoE and agencies concerned with disability issues in the society to provide comfortable environment on College campuses for TTSI. It is also recommended that, providing a comfortable environment should include facilities and resources needed for the TTSI to learn effectively. It also involves physical arrangement of the campus environment. The TTSI, regardless of their disabilities, should be provided with an environment where their movement, their studies, their interactions with their peers and tutors are made easier to help them graduate successfully.

First, based on the many levels and their cycles in geoscience, we research the hypercycle of geoscience. This is the hypercycle as a tool of self-organization applied to geoscience. It may form from a level to other higher levels. These levels influence each other and the co-evolution. Second, we discuss some possible mathematical methods, which include graph, vector, matrix, some equations, similar theories, etc. This method can be developed and perfected. Third, we propose the nonlinear whole geoscience and its three basic laws. Fourth, we discuss thermodynamics of geoscience, and in which possible entropy decrease under some sates, such as evolution and cycles of Earth, etc. Sustainable development of society must study the mode from high entropy to low entropy. Various cycles in geoscience cannot all be entropy increases, and cannot all be originated from the external interactions.

Water is essential for food security and animal agricultural productivity, but it is becoming more scarce due to climate change. The interaction between climate change and livestock water resources has received little attention from researchers, despite the significance of small-scale animal husbandry for the rural poor in Africa and the size of the changes that are anticipated to have an impact on smallholder livestock systems. Threats to livestock water are undoubtedly one of the most significant environmental issues that have impacted food security on the continent, given their links to small-scale animal husbandry and the detrimental impacts on productivity. In order to balance the negative effects of climate change scenarios for sustainable animal productivity and contribute to food security through small-scale animal agriculture, the most climate-smart and resilient agricultural water practices and technologies must be used. Changes in rainfall and a decline in the biomass available for grazing and rangelands as a result of water stress brought on by the climate would have the most severe effects. This is due to the rain-fed nature of small-scale livestock farming. The local animal genetic resources are essential for animal productivity and food security in Africa, particularly in areas where livestock water is becoming scarce owing to climate change. Research and development goals on the effects of climate change on livestock water, animal productivity, and food security may need to be reviewed if demands of vulnerable small-scale animal producers are to be successfully addressed in the future decades. It is best to use an interdisciplinary approach to comprehend the relationships between small-scale animal husbandry, food security, and climate change. By navigating the complexities of climate adaptation, small-scale livestock farmers can manage livestock water scarcity by taking adaptation measures that are in line with evolving climate impacts and associated means of implementation based on pertinent and useful knowledge that takes into account a blend of traditional and modern water science. In this paper, an effort is made to close some significant information gaps and shed light on how water-induced stress impacts small-scale animal production, which has an effect on food security.

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.

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.

The main goal of this paper is to study the effect of winding topology on coils electrical behavior in experimental way to take into account the self capacitance of coils, several coils are fabricated using copper wire with changing the number of winding layers and fixing the spiral numbers, in addition two coils was fabricated to study the effect of the winding wire diameter, the measured reactance and resistance of eddy current coils are done using precision LCR-meter with a frequency range from 0Hz to 5 MHz, the experimental results shows very remarkable interactions of resonator due to the changing of winding topology and his effect on self capacitance of coils.

Many attempts have been made to repurpose existing and approved drugs for the treatment of COVID-19 infection. This involves anti-malarial drugs such as hydroxychloroquine and chloroquine, which have been shown to be less successful than initially believed, with a substantial risk of often fatal complications and interactions. This also involves Remdesivir, which has been shown to decrease recovery time significantly in hospitalized patients. However, for patients who are not yet hospitalized, there is no currently accepted treatment. Treating patients before they need to be admitted or even prophylactically could greatly decrease the load on hospitals, protect healthcare workers and reduce the spread of COVID-19. An in-vitro study indicated that Ivermectin was dynamic against COVID-19-infected cell. Ivermectin has antimicrobial, antiviral, and anticancer, immunomodulatory properties. This drug could reduce the viral load in COVID-9 infected patients, with potential effect on disease progression and spread. Therefore, Ivermectin may be a therapeutic choice for treatment of COVID-19, however, there is still a lack of evidence-based studies to support ivermectin treatment of patients with COVID-19.

For the adequate treatment of bone fractures, it is necessary to have knowledge about mechanical concepts as the interaction of implants and bone. The understanding of the concept of stress riser must be clear for surgeon for adequate surgical planning, thus preventing refracture due to incorrect application of implants. This article presents the concept of stress riser applied to orthopedics and briefly discussion.

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. Δπ_dr and ΔSASA_dr 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. π_d, π_r, SASA_Sd and SASA_Sr 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 Δπ_dr and ΔSASA_dr 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 (ΣΔπ_dr)_binding-site, (ΣΔπ_dr)_{catalytic-site}, (ΣΔSASA_dr)_binding-site, (ΣΔSASA_dr)_{catalytic-site} shows that peptidic HIV-1-PRIs interact with binding site rather than catalytic site as binding site have lower value of ΣΔπ_dr and ΣΔSASA_dr. Among the binding site, Val has maximum interaction than Ile, as it has lower vale of Δπ_dr and ΔSASA_dr.

With numerous unique physical, mental, psychological, and emotional challenges associated with being a university-level student-athlete, it can be assumed that student-athletes may be at great risk of mental health conditions such as burnout. Burnout results from the interaction of three different elements: physical or emotional exhaustion, sport devaluation, and reduced athletic accomplishment. This study sought to answer the following research questions: (1) Why do student-athletes experience burnout in their sport?, and (2) What can be done to avoid burnout? using standard qualitative interviewing techniques of a Division I Women’s Soccer coach. There were two prominent themes answering research question 1: Perfection and Performative Social Media and It’s a Job and Coach is the Boss. There were three prominent themes identified answering research question 2: Parental Influence, De-Professionalize Amateur Sport, and Value Athletes’ Time. Where this work differs from other qualitative studies regarding athlete burnout, is that it explores the perceptions and opinions of a coach. The coach interviewed for this study clearly expressed concerns for his student-athletes and their holistic well-being. In addition to a continuation of scholarship through the student-athletes lens, more research conducted exploring the perspectives of coaches, parents, and institutional administrators in pursuit of solutions to mitigating the effect of burnout on student-athletes is of value.

The purpose of the study was to examine the interactional linguistic resources in concession speeches of Selected Political Leaders in Ghana and the United States of America. The past three decades have witnessed an increasing scholarly interest in political discourse. Despite this, concession speeches have received limited scholarly attention. This study, therefore, comparatively analyzed the concession speeches delivered by John Dramani Mahama and Nana Addo Danquah Akuffo-Addo of Ghana and Hillary Clinton and Al Gore of the United States of America. Speech Act and Metadiscourse Interactionist Theories were used to examine the interpersonal linguistic resources found in the speeches. The speeches, were analyzed qualitatively. The study concluded that speakers of CSs in the two different cultural contexts use similar statements, as has already been discussed earlier in this study. For instance, the four losing candidates used almost the same interpersonal linguistic resources (hedges, boosters, self-mention, attitude markers, and engagement markers) to establish a bond between them and their interlocutors and supporters. It is recommended that, concession speeches (CSs) to be studied from other theoretical perspectives, this will allow for a detailed analysis of a wider range of linguistic resources such as noun phrases, verb phrases, and the use of adjuncts, beyond the SAs in CSs in order not to treat them as mere rhetoric in politics.

Background: Psoriasis is extensively studied among middle-aged adults, but not many have studied psoriasis in older adults(geriatrics). OBJECTIVES: To analyze epidemiological, clinical, comorbidities and therapeutic profile of geriatric psoriasis(GP). METHODS: All consenting clinically diagnosed psoriatic patients ≥60 years were divided into two groups: Elderly psoriatic(EP)(60-75 years) and Ultra elderly psoriatic(UP)(>75 years). The dermatologist filled their clinical characteristics’ standardised questionnaire to determine comorbidities, drug interactions profile and compared with age-matched controls using Chi square test. RESULTS: Prevalence of GP is 14.5%(Average age:68 years; Sex ratio=2.5:1)among geriatrics attending dermatology OPD. Most common(49.9%) as well as initial site affected(39.3%) were Palms±Soles. Nummular plaque (90.2%) was most common type. Superficial fungal infection(26.9%) and pruritus(90.8%) were commonly associated cutaneous disease and symptom(p<0.05) respectively. Hypertension(49.7%),Diabetes Mellitus(22.8%), dyslipidemia(25.8%) and Metabolic syndrome(MS)(17.8%) were associated systemic comorbidities. Dyslipidemia and MS(p<0.0001) were more common among GP(163) than controls(963). Drug aggravated psoriasis could not be linked to polypharmacy. Although, topicals were mainstay, oral Methotrexate was most efficacious systemically. CONCLUSION: Our findings suggest a trimodal age of psoriasis onset at 68 years. As age advances, psoriasis severity decreases, unstable guttate lesions decrease; palms±soles commonly involved; infrequent familial occurrence with Polypharmacy not aggravating psoriasis. Active screening for cardiovascular comorbidities in all geriatric psoriasis patients is highly recommended.

The present study raises the problem of empathy of caregivers vis-à-vis patients in a covid/post-covid context. It is based on the observation that health workers are increasingly invaded by excessive fear and persistence of COVID-19 contamination. This induces avoidance, a certain suspicion, persecution and indifference/coldness towards patients, and plunges them into a strong insidious emotional deficiency. These attitudes, which are significantly close to paranoid and phobic access, seem to gradually dominate therapeutic interactions within hospitals. Freudian and Rogerian psychoanalysis advocates empathetic/benevolent listening, positive consideration and unconditional acceptance of the patient as ethical and deontological indispensable principles for any therapeutic evolution. Thus, it is predicted that within hospitals, the current non empathetic attitudes of care towards patients have their origin in a generalized covid-phobic atmosphere that develops a quasi-dominant paranoia in caregivers. Using a subscale of caregiver's Covid-phobic quasi-paranoia, and the one of caregiver's empathy in a covid/post-covid context, the data were collected from 126 participants including 55 nursing assistants, 61 state-certified nurses and 10 doctors, chosen at random from the staff of three (03) health facilities in the city of Bafoussam, MIFI department, West Cameroon region, including one (01) public district medical center (CMA) and two (02) private hospitals (clinics). After analysis, the results obtained sufficiently demonstrate that within the health institutions of West Cameroon, the higher the professional level of the caregiver, the more the severity of his quasi-paranoid covid-phobic accesses is significant, and the less he expresses an authentic empathy towards the patients who arrive at the hospital. This implies that in this period of health crisis, caregivers must reinvest in a real function of providers of affectivity and relay of empathy at the bedside of the patient both in hospital and outpatient. Thus, a real systematical vaccination operation may insure their total immunity and better reduce their quasi-paranoid empathy in this generalized Covid-phobic context.

Online shopping is a growing phenomenon and social media namely Facebook has radically changed consumers online purchase behaviour; especially the interactive information system of consumers, peers, and vendors. Similar to other online purchasing products or services, e-cigarette marketing in Facebook has potential. This study aims to determine the association between individual’s online interaction and e-cigarette purchase intention from Facebook vape groups. A cross-sectional study was conducted among 214 respondents using the Facebook platform from September to December 2019. Data were collected via a self-administered questionnaire. The Chi-square test was used for data analyses using SPSS (version 25.0). Most of the participants were male; the mean age of the respondents was 27.41 ± 2.1. Total 93.9% (201 of 214) and 56.1% (120 of 214) respondents were vaper and smoker respectively. Among the non-smokers, most of the respondents were vaper (84 of 94, 89.4%). Consumers smoking and vaping status were associated with each other (χ2 = 6.11, P=0.01). There was an association between vaping status and purchase intention of e-cigarettes from the Facebook vape group (χ2 = 5.06, P=0.02). Online interactions, namely like (χ2 = 5.88, P <0.01), post (χ2 = 7.16, P <0.01) and sharing (χ2 = 10.14, P <0.01) of the e-cigarette related information or advertisements in social media were associated with purchase intention of e-cigarettes from Facebook vape group. This study revealed individuals vaping and online interactions were associated with an online purchase the intention of e-cigarette in Facebook. Public health researchers and policymakers might contemplate the regulatory environment of online marketing of e-cigarettes to curtail the uptake of e-cigarettes among non-smokers.

The heart remained a mystery for many years and was considered surgically untouchable. With the use of extracorporeal circulation, there has been a revolution in this area. Due to its mechanical components and interactions with blood, cardiopulmonary bypass (CPB) can cause significant changes in the body. Factors such as contact between artificial materials and blood, continuous flow, hemodilution, hypothermia and anticoagulation affect all organs during CPB, and may result in various complications. The minimally invasive extracorporeal circulation (MiECC) system was developed to minimize the contact of blood with air and foreign surfaces during conventional CPB. In addition, the biocompatibility of the components that make up the MiECC circuits increased, which reduced the inflammatory response. The absence of a venous reservoir and shorter lines allow the prime volume to be used to decrease, which also reduces the damage to the blood elements, and consequently, the need for blood transfusion. The MiECC system also has its downsides, the most important one being the difficulty in removing the air that can enter through the venous line, the impairment of the pump function, and embolization. During the use of these systems, perfusion safety and communication with the whole team must be at the highest level. In line with this information, the use of these systems can become standard in cardiac surgery with new technological additions.

Environmental regulation is one of the most important subsets of social regulation. Regulation is a framework for implementing the rules adopted in society, and legal standards guarantee this framework. Thus, if the legislation prohibits the dumping of waste on public waterways and imposes a penalty for its violation, this prohibition can be interpreted as an expression of society's public commitment to environmental protection and public condemnation of polluting behaviors. On the other hand, it can be said that the destruction of the environment is morally wrong, and therefore the legal prohibition of these behaviors can be interpreted as an expression of this moral claim. This research is based on library studies and descriptive-analytical methods and has an innovative approach. The purpose of this study is to explain the role of law as a facilitator of the executive structure of environmental regulation inappropriate conditions in line with social interaction. It also seeks to explain the importance of regulation and regulation. Regulation is one of the most important social standards and guarantees the strong implementation of legal obligations in society. This fundamental standard has been established in public law and seems to be an important approach to protecting the environment and citizens' adherence to environmental obligations.

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.

Advances of wearables, sensors, smart devices, and electronic health records have generated patient-oriented longitudinal data sources that are analyzed with advanced analytical tools to generate enormous opportunities to understand patient health conditions and needs, transforming healthcare significantly from conventional paradigms to more patient-specific and preventive approaches. Artificial intelligence (AI) with a machine learning methodology is prominently considered as it is uniquely suitable to derive predictions and recommendations from complex patient datasets. Recent studies have shown that precise data aggregation methods exhibit an important role in the precision and reliability of clinical outcome distribution models. There is an essential need to develop an effective and powerful multifunctional machine learning platform to enable healthcare professionals to comprehend challenging biomedical multifactorial datasets to understand patient-specific scenarios and to make better clinical decisions, potentially leading to the optimist patient outcomes. There is a substantial drive to develop the networking and interoperability of clinical systems, the laboratory, and public health. These steps are delivered in concert with efforts at enabling usefully analytic tools and technologies for making sense of the eruption of overall patient’s information from various sources. However, the full efficiency of this technology can only be eliminated when ethical, legal, and social challenges related to reducing the privacy of healthcare information are successfully absorbed. Public and media are to be informed about the capabilities and limitations of the technologies and the paramount to be balanced is juvenile public healthcare data privacy debate. While this is ongoing, the measures have been progressed from patient data protection abuses for progress to realize the full potential of AI technology for hosting the health system, with benefits for all stakeholders. Any protection program should be based on fairness, transparency, and a full commitment to data privacy. On-going innovative systems that use AI to manage clinical data and analyzes are proposed. These tools can be used by healthcare providers, especially in defining specific scenarios related to biomedical data management and analysis. These platforms ensure that the significant and potentially predictive parameters associated with the diagnosis, treatment, and progression of the disease have been recognized. With the systematic use of these solutions, this work can contribute to the realization of noticeable improvements in the provision of real-time, personalized, and efficient medicine at a reduced cost [1].

Through a digitally connected ecosystem, the innovative realm of fintech significantly enhances human capabilities across various dimensions. AI-based fintech solutions are increasingly proving to be invaluable by providing effective enforcement of regulations that ensure compliance and protect stakeholders involved. Numerous expert investigations conducted in the arena of high-technology litigation have reinforced both the pressing need and the immense value of enforced compliance in today's fast-paced digital landscape. Open banking APIs have boldly pioneered this critical regulatory enforcement role, allowing broader access and improved services for consumers. Predictive AI certainty, facilitated through sophisticated validation systems, represented a fundamental evolution in their rule-based legal formulations that govern many aspects of financial transactions. These advanced products were deployed within global legislative codes, allowing for standardized practices, and consequently, all market sectors quickly adopted them to ensure they remain competitive and compliant. During the latest of these professionals' encouraging comments, it became clear that awareness of the inception of these groundbreaking innovations must be convened into a steadfast commitment to continue launching natural language processing products that can refine consumer interaction. Since this pivotal point, the increasing dependency of the financial expert community on these incisive factors underscores the paramount importance they now hold for their clients and end users alike, shaping the future of finance in profound ways [1].

The evolution of supply chains (SC) from a linear to a network structure created an opportunity for new processes, product/service offerings, and provider-business. Rising customer service expectations have led to the need for innovative SC designs to develop and sustain competitive performance globally. Firms are forced to respond and adapt accordingly, thereby leading to design, network, operational, and performance dynamics. Traditionally, SCs are treated as static structures, focusing solely on design and/or operational optimization. Such perspectives are not viable options for SC domains, as they address only a portion of the dynamic problem space, use a deterministic assumption of dominant design variables, capitalize on past data to predict future decisions, and offer pre-classified forecasting options complemented with a limited comprehension of systemic SC elasticity. Novel self-learning agentic systems are proposed that blend the sciencematics of SC decisions and dynamics. The designs guide firms seeking to build adaptive SCs using operational decision processes. The designs address the agentic nature of SC, embedding computational interaction models of firm SC networks. The designs contrast the stochastic action-taking and thereby the performance outcomes, discovering opportunities for adaptive operational designs of SC tasks. Fine-tuning and meta-learning are new design capabilities that adapt to evolving dynamic environments. Frameworks for behavioral customization and systematic exploration of the design space are provided as user guides. Exemplar designs are also provided to serve as a translation template for users to express operational models of their own contexts. To account for the dynamics of supply chains (SC), agent-based models are increasingly adopted. Such models exhibit SC structure and/or formulation dynamics. Though existing efforts commence adjacent-only structural changes, dynamism with respect to tasks is crucial for SC design and operational strategy development. Proposed is a process modeling library and workflow for discovering intricate designs of adaptive agentic systems. The library revises Dataflow and Structure, concealing sequencing and context designs of processes. Prompted specifications describe and enact designs. Applications in SC formulation discovery are provided.

This study aims to achieve a new understanding of how, why, and when consumer behavior is shaped, enacted, and experienced inside and across integrated digital ecosystems related to large-scale trackable goods, all in service of helping marketers optimize their business performance in the new economy. The pioneering understanding begins by exploring what motivates the choices of a homogeneous group of consumers to organize their consumption of national and store brand varieties of consumer package goods in a certain manner. Thereafter, the essay explores how, if at all, the other digital activities of consumers across various product-related digital spaces and on various platforms build expertise and interest in these products such that they exert an effect on the purchase choices for these products. The essay then advances to asking how online information seeking, in various product-related digital spaces, on various platforms, and from various sources, and taking place at various points in the purchase journey affects online-offline dynamics in purchasing these products. Thereafter, the research examines how paid digital communication in various product-related digital spheres and forms, enabled by consumer advertising engagement on various platforms, boosts the offline sales of these products. Finally, by employing a new methodology that combines consumer scanning data, self-reported online activity data, and transaction data collected from an ad-tech partner, the research presents a fresh set of marketing action levers and performance outcomes on chosen products. Along the way, progress is made on four under-investigated topics in the advertising literature – the role of consumer actors and their expertise in the online-offline purchasing dynamics for ads, advertising engagement, consumer digital spaces, and consumer digital activity investment.

Time series data are increasingly prevalent across domains such as finance, healthcare, manufacturing, and IoT, making accurate forecasting and anomaly detection critical for decision-making and system reliability. Traditional statistical methods (e.g., ARIMA, Holt-Winters) often fail to capture complex temporal dependencies and high-dimensional interactions inherent in modern time series. Recent advances in artificial intelligence particularly deep learning architectures such as recurrent neural networks (RNNs), convolutional neural networks (CNNs), temporal convolutional networks (TCNs), graph neural networks (GNNs) and Transformers have demonstrated marked improvements in modeling both univariate and multivariate series, as well as in detecting anomalies that deviate from learned norms (Darban, Webb, Pan, Aggarwal, & Salehi, 2022; Chiranjeevi, Ramya, Balaji, Shashank, & Reddy, 2024) [1,2]. Moreover, ensemble techniques and hybrid signal-processing + deep-learning pipelines show enhanced sensitivity and adaptability in real-world anomaly detection scenarios (Iqbal, Amin, Alsubaei, & Alzahrani, 2024) [3]. In this work, we provide a unified survey and comparative analysis of AI-driven time series forecasting and anomaly detection methods, highlight key industrial application domains, evaluate performance trade-offs (e.g., accuracy vs. latency, supervised vs. unsupervised learning), and discuss emerging challenges including interpretability, data drift, real-time deployment on edge devices, and integration of causal reasoning. Our findings suggest that while AI approaches significantly outperform classical techniques in many settings, careful consideration of data characteristics, evaluation metrics and deployment environment remains essential for effective adoption.