Filter options

Publication Date
From
to
Subjects
Journals
Article Types
Countries / Territories
Open Access September 09, 2025

Biopsy-Negative Giant Cell Arteritis Presenting as Stroke Mimic with Vision Loss and Complex Vascular Disease

Abstract A man in his 60s with multiple vascular comorbidities presented with sudden, painless vision loss in one eye. Although he had a high risk for atherosclerotic events, initial evaluation for stroke was negative for acute ischemia, but found to have markedly elevated inflammatory markers. Accordingly, giant cell arteritis was investigated and Ophthalmologic findings and fulfillment of the 2022 [...] Read more.
A man in his 60s with multiple vascular comorbidities presented with sudden, painless vision loss in one eye. Although he had a high risk for atherosclerotic events, initial evaluation for stroke was negative for acute ischemia, but found to have markedly elevated inflammatory markers. Accordingly, giant cell arteritis was investigated and Ophthalmologic findings and fulfillment of the 2022 American College of Rheumatology/European Alliance of Associations for Rheumatology classification criteria supported the diagnosis of giant cell arteritis, despite a negative temporal artery biopsy. Management included high-dose glucocorticoids and delayed tocilizumab initiation due to the need for multiple vascular surgeries. Vision loss was irreversible, but systemic symptoms resolved and vascular interventions were successful. This case highlights the diagnostic and management complexities of biopsy-negative giant cell arteritis in patients with severe atherosclerotic vascular disease, emphasizing the importance of clinical judgment and established classification criteria when imaging and biopsy results are inconclusive.
Figures
PreviousNext
Case Report
Open Access June 02, 2025

Residual Sets and the Density of Binary Goldbach Representations

Abstract A residual-set framework is introduced for analyzing additive prime conjectures, with particular emphasis on the Strong Goldbach Conjecture (SGC). For each even integer En4, the residual set [...] Read more.
A residual-set framework is introduced for analyzing additive prime conjectures, with particular emphasis on the Strong Goldbach Conjecture (SGC). For each even integer En4, the residual set (En)={Enp p<En,p} is defined, and the universal residual set E=En(En) is constructed. It is shown that E contains infinitely many primes. A nontrivial constructive lower bound is derived, establishing that the number of Goldbach partitions satisfies G(E)2 for all E8, and that the cumulative partition count satisfies ENG(E)N2log4N. An optimized deterministic algorithm is implemented to verify the SGC for even integers up to 16,000 digits. Each computed partition En=p+q is validated using elliptic curve primality testing, and no exceptions are observed. Runtime variability observed in the empirical tests corresponds with known fluctuations in prime density and modular residue distribution. A recursive construction is formulated for generating Goldbach partitions, using residual descent and leveraging properties of the residual sets. The method extends naturally to Lemoine's Conjecture, asserting that every odd integer n7 can be expressed as n=p+2q, where p,q. A corresponding residual formulation is developed, and it is proven that at least two valid partitions exist for all n9. Comparative analysis with the Hardy-Littlewood and Chen estimates is provided to contextualize the cumulative growth rate. The residual-set methodology offers a deterministic, scalable, and structurally grounded approach to additive problems in prime number theory, supported by both theoretical results and large-scale computational evidence.
Figures
PreviousNext
Article
Open Access February 15, 2025

Knowledge related to umbilical cord care among mothers of neonates attending outpatient departments in Sherpur district, Bangladesh

Abstract Background: Proper umbilical cord care prevents neonatal infections and reduces neonatal mortality. Despite global recommendations for evidence-based cord care practices, traditional beliefs, and inadequate maternal knowledge often lead to unsafe practices, particularly in low-resource settings like Bangladesh. This study aimed to assess the understanding of umbilical cord care among [...] Read more.
Background: Proper umbilical cord care prevents neonatal infections and reduces neonatal mortality. Despite global recommendations for evidence-based cord care practices, traditional beliefs, and inadequate maternal knowledge often lead to unsafe practices, particularly in low-resource settings like Bangladesh. This study aimed to assess the understanding of umbilical cord care among mothers of neonates in Sherpur District, Bangladesh, and identify factors associated with knowledge levels. Methods: A descriptive cross-sectional study was conducted from July to October 2020 at Sherpur Sadar Hospital. A total of 193 mothers of neonates were recruited using a non-randomized purposive sampling method. Data was collected through a pre-tested, semi-structured, interviewer-administered questionnaire. Knowledge levels were categorized as "Good" (>6) or "Poor" (≤6) based on responses to 10 structured questions. Statistical analyses, including chi-square tests and crude odds ratios (COR), were performed to identify socio-demographic factors associated with knowledge levels. Results: Of the 193 participants, 48.7% demonstrated "Good" knowledge, while 51.3% had "Poor" knowledge. Education level (p = 0.01), occupation (p = 0.02), family type (p < 0.001), and family size (p = 0.04) were significantly associated with knowledge levels. Mothers with higher education and those from joint families exhibited better knowledge. However, 28.5% of respondents were unaware of the typical umbilical cord-shedding timeframe, and 44% could not identify signs of infection. Unsafe practices, such as using medications (14.5%) or hot compression (7.2%) for drying the cord, were reported. Conclusion: The study reveals significant gaps in maternal knowledge regarding umbilical cord care in Sherpur District, driven by socio-demographic disparities and cultural practices. Targeted health education programs, emphasizing evidence-based cord care practices and leveraging local social structures, are urgently needed to improve neonatal health outcomes in similar resource-limited settings. Future research should evaluate the effectiveness of these interventions to inform policy and practice.
Figures
PreviousNext
Article
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.
Figures
PreviousNext
Article
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.
Figures
PreviousNext
Article
Open Access October 31, 2023

Effectiveness of Probiotics for Treatment of COVID-19: A Systematic Review and Meta-analysis

Abstract Background: Recently specific interactions and crosslinks between the gut microbiota and the lungs have been recognized, particularly with regard to respiratory immune and anti-microbial reactions. This is often known as the “gut-lung axis” or “a common mucosal immunological system”. Objective: The aim of the current systematic review was to evaluate evidence, from published clinical trials and cohort studies, if probiotics may have an effect in improving and managing COVID-19 symptoms. Materials and methods: The available studies were searched through a comprehensive search of electronic databases that included PubMed, Science Direct, Scirus, ISI Web of Knowledge, Google Scholar and CENTRAL (Cochrane Central Register of Controlled Trials), using a combination of the following keywords: “COVID-19" OR [...] Read more.
Background: Recently specific interactions and crosslinks between the gut microbiota and the lungs have been recognized, particularly with regard to respiratory immune and anti-microbial reactions. This is often known as the “gut-lung axis” or “a common mucosal immunological system”. Objective: The aim of the current systematic review was to evaluate evidence, from published clinical trials and cohort studies, if probiotics may have an effect in improving and managing COVID-19 symptoms. Materials and methods: The available studies were searched through a comprehensive search of electronic databases that included PubMed, Science Direct, Scirus, ISI Web of Knowledge, Google Scholar and CENTRAL (Cochrane Central Register of Controlled Trials), using a combination of the following keywords: “COVID-19" OR "SARS-CoV-2" AND "Microbiota" OR "Probiotics” OR “Gut Lung Axis”. The literature was reviewed until August 31, 2022. Results: Only 3 studies were included. One of them evaluated the efficacy of probiotics in COVID-19 patients to obtain complete remission of all signs and symptoms. The clinical trial proves that probiotics have a significant effect on complete remission of all signs and symptoms of COVID-19 patients with statistical significant difference. Only one clinical trial out of the 3 included studies had evaluated the need for O2 therapy during the study between the probiotics and control groups, but without statistical significant difference. No statistical significant difference between the probiotics group and placebo group was observed regarding fatal prognosis during the only clinical trial that measured death as an outcome. Conclusion: We couldn’t judge on these results as they are insufficient data for pooling and meta-analysis. However, what we can say is “Most probably Probiotics have no role in treatment of COVID-19 infection”.
Figures
PreviousNext
Meta-Analysis
Open Access October 16, 2023

Clinical Characteristics and Imaging Findings of Adult COVID-19 and Influenza-related Pulmonary Complications due to Methicillin-susceptible Staphylococcus aureus

Abstract The pulmonary characteristics of Staphylococcus aureus (S. aureus) co-infection with respiratory viruses, such as SARS-CoV-2 and influenza virus, are still unclear. Case series: Two patients with methicillin-susceptible S. aureus [...] Read more.
The pulmonary characteristics of Staphylococcus aureus (S. aureus) co-infection with respiratory viruses, such as SARS-CoV-2 and influenza virus, are still unclear. Case series: Two patients with methicillin-susceptible S. aureus (MSSA) infection in the lungs co-infected with either SARS-CoV-2 or influenza virus are reported. Case 1 was a 66-year-old woman who was admitted with SARS-CoV-2 infection. Her chest X-ray and computed tomography (CT) showed multiple cavity formations with infiltration shadows, and MSSA was detected from her sputum and blood, suggesting COVID-19-related bacterial pneumonia and pulmonary embolism. No catheters had been used, but she had skin eruptions and a history of SARS-CoV-2 vaccination. Ampicillin/sulbactam (ABPC/SBT) was administered, and she finally improved. Case 2 was an 87-year-old man with a history of atopic dermatitis who was admitted with moderate pneumonia, and influenza virus co-infection was found. He showed multiple cavitary shadows, and MSSA was isolated from both his sputum and blood. He was diagnosed with influenza-related bacterial pulmonary embolism. No catheters had been used, but he had a history of influenza vaccination. He was also treated by ABPC/SBT and finally improved. Conclusions: These cases suggest that MSSA showed affinity to the lungs when co-infected with either SARS-CoV-2 or influenza virus, and it presented as septic emboli without catheter use. We should consider MSSA infection when patients have SARS-CoV-2 or influenza virus co-infection, and multiple cavity formation and skin disorders are seen, even though they were vaccinated and no catheters were used.
Figures
PreviousNext
Case Series
Open Access October 11, 2023

Quality of Life Assessment of Health Record Professionals Working in a Tertiary Health Facility, during the COVID 19 Pandemic in South Western Nigeria

Abstract Background: There is paucity of data on health-related quality of life (HRQoL) among Health Information Managers/Health Record Officers (HROs) in the Nigeria health system. Hence, this study investigated the impact of the COVID-19 pandemic on health-related quality of life (QoL) among HROs in Obafemi Awolowo University Teaching Hospital Complex (OAUTHC), Ile-Ife, Nigeria. Methods: A [...] Read more.
Background: There is paucity of data on health-related quality of life (HRQoL) among Health Information Managers/Health Record Officers (HROs) in the Nigeria health system. Hence, this study investigated the impact of the COVID-19 pandemic on health-related quality of life (QoL) among HROs in Obafemi Awolowo University Teaching Hospital Complex (OAUTHC), Ile-Ife, Nigeria. Methods: A cross-sectional study was conducted in the University Hospital, where a total of 52 health record officers were purposively sampled. Relevant data were collected using the Short Form survey (SF-36v2) questionnaire. One-way ANOVA was used to determine mean group differences across the nine and the two QoL (physical and mental) summary domains based on respondents’ socio-demographics, while level of significance was set at 0.05. Results: All the QoL sections of the instrument used yielded an α-Cronbach’s score of > 0.70. Analysis of some QoL physical component dimensions showed that; Bodily pain (BP) was found to be significantly (P=0.032) associated with marital status, Physical functioning (PF) with gender (P=0.023), and general health (GH) with age group (P=00.025) and highest level of education (P=0.023). On the other hand, mental health component analysis revealed that Social Functioning (SF) was associated with age group (P=014), Role limitation (RE) with marital status (P=0.048), highest level of education (P=0.048) and years of service (P=0.015) etc. Conclusion: The QoL among HROs studied was generally above average, and demographic characteristics such as age, gender and marital status significantly influence QoL. Health managers and stakeholders should consider some of the factors identified in managing HROs.
Article
Open Access September 19, 2023

Differential Complete Blood Count for Diagnosis of COVID-19?

Abstract Background: The World Health Organization (WHO) has declared COVID-19 a public health emergency of international concern. In this context, effective and affordable diagnostic procedures are essential for identifying and managing cases. Complete blood counts (CBC) are among the most common and readily available diagnostic tests. The current study aimed to evaluate the efficacy of CBC in [...] Read more.
Background: The World Health Organization (WHO) has declared COVID-19 a public health emergency of international concern. In this context, effective and affordable diagnostic procedures are essential for identifying and managing cases. Complete blood counts (CBC) are among the most common and readily available diagnostic tests. The current study aimed to evaluate the efficacy of CBC in diagnosing COVID-19 and identifying cases. Patients and Methods: A case-control study was conducted on 173 patients at Ain Shams University Hospitals over a period of three months. Patients were allocated into two groups according to COVID-19 PCR results: Group 1 included patients with COVID-19 positive PCR, and Group 2 included patients with COVID-19 negative PCR. Results: The study found that differential CBC had significant value in diagnosing COVID-19 disease. Many COVID-19 patients had lymphopenia and leucopenia compared to non-COVID-19 suspected patients. The low values of leukocytes, neutrophils, lymphocytes, and eosinophils with a CBC test were found to be valuable in the initial diagnosis of COVID-19. Conclusion: The definitive diagnosis of COVID-19 requires RT-PCR analysis, which is time-consuming and less accessible. Thus, the initial diagnosis and treatment of patients may be delayed. This study suggests that CBC, which is easily available and affordable, can be valuable in the early identification of COVID-19 cases, allowing for prompt treatment and management.
Article
Open Access September 19, 2023

Lonely No More: Investigating the Connection between Family Health, Social Support, and Well-being in Chinese “Empty Nest Youth”

Abstract Background: The phenomenon of "empty nest youth" is becoming increasingly ubiquitous, capturing the attention of society at large. However, few studies have been conducted in recent years on this group, especially focusing on their family and mental health. As such, this study investigates the correlation between family health and well-being among "empty nest youth," as well as the function of social support and loneliness in this relationship. Methods: A cross-sectional survey was conducted from June to August 2022 across 32 provinces, municipalities, and autonomous regions in China, utilizing a multi-stage sampling technique. And we screened individuals who were unmarried, living alone, and between 22-44 years old, resulting in a valid sample size of 908 cases; multiple regression analysis, mediation effect testing, and moderation effect testing are used to examine research hypotheses. Results: The regression analysis results show that family health not only has a direct impact on well-being (β = 0.36, p < 0.001) but also indirectly affects well-being through social support [β = 0.23, 95% CI: 0.19 0.28]. Additionally, the loneliness moderates the predictive impact of not only family health on social support (β = -0.13, p < 0.001) but also social support on well-being (β = -0.06, p [...] Read more.
Background: The phenomenon of "empty nest youth" is becoming increasingly ubiquitous, capturing the attention of society at large. However, few studies have been conducted in recent years on this group, especially focusing on their family and mental health. As such, this study investigates the correlation between family health and well-being among "empty nest youth," as well as the function of social support and loneliness in this relationship. Methods: A cross-sectional survey was conducted from June to August 2022 across 32 provinces, municipalities, and autonomous regions in China, utilizing a multi-stage sampling technique. And we screened individuals who were unmarried, living alone, and between 22-44 years old, resulting in a valid sample size of 908 cases; multiple regression analysis, mediation effect testing, and moderation effect testing are used to examine research hypotheses. Results: The regression analysis results show that family health not only has a direct impact on well-being (β = 0.36, p < 0.001) but also indirectly affects well-being through social support [β = 0.23, 95% CI: 0.19 0.28]. Additionally, the loneliness moderates the predictive impact of not only family health on social support (β = -0.13, p < 0.001) but also social support on well-being (β = -0.06, p < 0.001). Conclusions: These findings underscore the significance of directing policymakers and healthcare professionals towards the "empty nest youth's" familial and social support systems. It underscores the need for the development of policies aimed at addressing their emotional and material requirements by leveraging these familial and social networks. This approach ultimately contributes to the enhancement of their overall psychological well-being, promoting a more coherent and logical pathway for intervention and support.
Figures
PreviousNext
Article
Open Access March 03, 2023

Novel Approaches to Address the Dual Challenges of Neurodegeneration and Aging

Abstract Neurodegeneration and aging are pressing issues with significant personal, economic, ethical, and social consequences. However, the underlying biological mechanisms of these conditions remain largely unknown, making the development of effective treatments challenging. The difficulty in early detection and diagnosis of neurodegenerative diseases further compounds the issue. Recent advancements in [...] Read more.
Neurodegeneration and aging are pressing issues with significant personal, economic, ethical, and social consequences. However, the underlying biological mechanisms of these conditions remain largely unknown, making the development of effective treatments challenging. The difficulty in early detection and diagnosis of neurodegenerative diseases further compounds the issue. Recent advancements in genetics, genomics, and brain imaging technology hold great promise for improving our understanding of neurodegeneration and aging, as well as the development of personalized medicine and new drugs and therapies. Addressing these challenges will require a multi-disciplinary and collaborative approach from researchers in various fields. This Special Issue offers valuable insights and perspectives on this critical area of research, which can help advance our understanding and improve the health and well-being of our aging population.
Editorial
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.
Figures
PreviousNext
Review Article
Open Access January 25, 2026

Meigs’ syndrome presenting with pleuritic chest pain and dyspnea: rapid resolution after resection of an ovarian fibroma

Abstract Meigs’ syndrome is a rare triad of a benign ovarian fibroma (or fibroma‑like tumor), ascites, and pleural effusion that resolves after tumor resection. A 53‑year‑old multiparous woman presented with progressive exertional dyspnea and right‑sided pleuritic chest pain. Respiratory and cardiac evaluations were initially unrevealing. Bedside assessment identified mild right basal dullness, and [...] Read more.
Meigs’ syndrome is a rare triad of a benign ovarian fibroma (or fibroma‑like tumor), ascites, and pleural effusion that resolves after tumor resection. A 53‑year‑old multiparous woman presented with progressive exertional dyspnea and right‑sided pleuritic chest pain. Respiratory and cardiac evaluations were initially unrevealing. Bedside assessment identified mild right basal dullness, and point‑of‑care abdominal ultrasound demonstrated mild free fluid and a solid right adnexal mass. Chest radiography confirmed a small right pleural effusion. Without computed tomography and without diagnostic paracentesis or thoracentesis, Meigs’ syndrome was suspected. The patient underwent laparotomy with total abdominal hysterectomy and bilateral salpingo‑oophorectomy. Histopathology confirmed an ovarian fibroma. Postoperatively, symptoms resolved dramatically, and follow‑up imaging demonstrated complete resolution of the pleural effusion and ascites. This case highlights the importance of considering gynecologic etiologies in unexplained pleural effusion and dyspnea, especially when accompanied by abdominal distension or pelvic pressure.
Case Report
Open Access December 28, 2025

Acute Right Ovarian Torsion with Six Twists: Successful Ovarian Preservation Following Detorsion

Abstract Introduction: Ovarian torsion is a rare gynecological emergency that can result in permanent ovarian loss if not promptly recognized and managed. Cases involving multiple rotations of the ovary are highly unusual and pose a significant risk for ovarian viability. Clinical Description: A 33-year-old P2 woman presented with sudden severe lower abdominal pain. Imaging showed a complex [...] Read more.
Introduction: Ovarian torsion is a rare gynecological emergency that can result in permanent ovarian loss if not promptly recognized and managed. Cases involving multiple rotations of the ovary are highly unusual and pose a significant risk for ovarian viability. Clinical Description: A 33-year-old P2 woman presented with sudden severe lower abdominal pain. Imaging showed a complex midline adnexal mass, more towards left and mild free fluid with suspected torsion. Emergency laparotomy showed a sixfold torsion of the right ovary with a dermoid cyst. Detorsion and cystectomy were performed with preservation of the ovary. Postoperative recovery was uneventful and histopathology further confirmed a benign dermoid cyst. Discussion: Ovarian torsion with multiple rotations is extremely rare so early recognition and timely surgical intervention enable ovarian salvage even in severe cases. Moreover, Dermoid cysts are the most common predisposing factor. Conclusion: This case highlights the importance of prompt diagnosis and immediate management of ovarian torsion to prevent complications, preserve ovarian integrity and fertility.
Figures
PreviousNext
Case Report
Open Access December 13, 2025

Clinical Characteristics of Block-Confirmed Sacroiliac Joint Arthropathy: Referral Pain Distribution, Triggering Positions, and Provocative Maneuvers

Abstract Background: The sacroiliac joint (SIJ) plays a crucial role in transmitting axial loads and maintaining pelvic stability. Sacroiliac joint arthropathy (SIJA) accounts for 10%–30% of low back pain cases but remains underrecognized due to overlapping pain referral patterns and nonspecific imaging findings. Diagnosis relies primarily on characteristic pain distribution and provocative [...] Read more.
Background: The sacroiliac joint (SIJ) plays a crucial role in transmitting axial loads and maintaining pelvic stability. Sacroiliac joint arthropathy (SIJA) accounts for 10%–30% of low back pain cases but remains underrecognized due to overlapping pain referral patterns and nonspecific imaging findings. Diagnosis relies primarily on characteristic pain distribution and provocative maneuvers, with image-guided intra-articular block serving as the diagnostic gold standard. This study aimed to characterize the clinical profile of block-confirmed SIJA, emphasizing referral pain distribution, triggering position, and provocative test responses. Methods: A cross-sectional study was conducted on 98 patients with diagnostic block–confirmed SIJA at Siloam Hospital Lippo Village, Indonesia. Demographic data, referral pain sites, sitting duration, and results of FABER, compression, and distraction tests were analyzed descriptively. Results: The mean age was 52.07 ± 14.17 years, with 72.4% females. Referral pain most frequently involved the lower back (28.6%) and thigh (28.6%), with occasional extension to the groin (8.2%) or calf (4.1%). Over half of patients (55.1%) reported sitting more than six hours daily. Pain was predominantly triggered during sit-to-stand transitions (85.7%) and while sitting (74.5%). SIJ tenderness (98.0%) and FABER positivity (75.5%) were most consistent. Conclusion: The dominant referral pain in SIJA involves the lower back and posterior thigh. Sit-to-stand transition is the most frequent triggering position, while FABER testing demonstrates the highest diagnostic yield among provocative maneuvers. These consistent patterns may serve as practical clinical indicators to improve diagnostic accuracy in suspected SIJ-related pain.
Article
Open Access December 09, 2025

Hidden Malignancy in Pregnancy: Metastatic Adenocarcinoma of Colon Disguised as Liver Hemangioma Leading to Maternal Mortality

Abstract Introduction: Colorectal cancer during pregnancy is a complex and rare condition often presenting with benign gastrointestinal symptoms that overlap with normal pregnancy related changes, leading to delayed or misdiagnosis. Further, hepatic metastases may complicate recognition, especially when initially interpreted as benign lesions such as hemangiomas. So, early identification and [...] Read more.
Introduction: Colorectal cancer during pregnancy is a complex and rare condition often presenting with benign gastrointestinal symptoms that overlap with normal pregnancy related changes, leading to delayed or misdiagnosis. Further, hepatic metastases may complicate recognition, especially when initially interpreted as benign lesions such as hemangiomas. So, early identification and management are crucial and remain challenging for optimizing maternal and fetal outcomes. Clinical Description: A case of 39-year-old gravida 5 para 4 at 24 weeks+1 day with chronic hypothyroidism, longstanding anemia and a one year history of epigastric + right upper quadrant pain with suspected hemorrhage from a known liver hemangioma. Further imaging suggested a malignant hepatic lesion where colonoscopy and biopsy confirmed stage IV metastatic colon adenocarcinoma with liver and adrenal metastases. Her condition deteriorated and delivered a stillborn infant at 26 weeks of 780 grams following placental abruption. She continued to decline despite supportive care and died. Conclusion: This case illustrates the diagnostic challenges of colorectal cancer in pregnancy where nonspecific symptoms and inaccurate imaging results contributed to delayed diagnosis. The aggressive nature of the disease emphasizes the importance of prompt diagnosis and integrated care approach to improve both maternal and fetal outcome.
Case Report
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 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 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.
Figures
PreviousNext
Article
Open Access July 24, 2025

Atypical Presentation of Lemierre’s Syndrome Masquerading as Gastroenteritis Lemierre’s Syndrome Mimicking Gastroenteritis

Abstract Lemierre’s syndrome (LS) is a rare clinical condition characterized by septic thrombophlebitis of the internal or external jugular vein, usually following an oropharyngeal infection. Here, we present a 20-year-old male patient who developed diarrhea, nausea, and vomiting after receiving clarithromycin for an upper respiratory tract infection. On admission, he had fever, hypotension, and elevation in acute phase reactants (WBC: 20,410/µL, CRP: 197 mg/L). Empirical treatment with ceftriaxone and metronidazole was initiated. Stool and throat cultures were negative. On the second day, abdominal tenderness developed; direct abdominal radiograph showed dilated bowel loops, but toxic megacolon was excluded during follow-up. Thoracic CT revealed septic emboli in the lungs. Due to persistent fever despite ceftriaxone and metronidazole therapy, treatment was escalated to meropenem on the fifth day. On the same day, blood cultures grew Fusobacterium necrophorum, raising suspicion of LS. Doppler ultrasound detected a thrombus in the left external jugular vein. Anticoagulant therapy with low-molecular-weight heparin and clopidogrel was initiated. The fever resolved by the seventh day of full antibiotherapy After three weeks of intravenous therapy, follow-up imaging showed regression of the thrombus. The patient completed a four-week course of antibiotics and anticoagulants and was discharged with full recovery. This case highlights the diagnostic challenge of LS presenting with gastrointestinal symptoms and emphasizes the importance of early blood cultures and imaging. External jugular vein involvement due to F. necrophorum [...] Read more.
Lemierre’s syndrome (LS) is a rare clinical condition characterized by septic thrombophlebitis of the internal or external jugular vein, usually following an oropharyngeal infection. Here, we present a 20-year-old male patient who developed diarrhea, nausea, and vomiting after receiving clarithromycin for an upper respiratory tract infection. On admission, he had fever, hypotension, and elevation in acute phase reactants (WBC: 20,410/µL, CRP: 197 mg/L). Empirical treatment with ceftriaxone and metronidazole was initiated. Stool and throat cultures were negative. On the second day, abdominal tenderness developed; direct abdominal radiograph showed dilated bowel loops, but toxic megacolon was excluded during follow-up. Thoracic CT revealed septic emboli in the lungs. Due to persistent fever despite ceftriaxone and metronidazole therapy, treatment was escalated to meropenem on the fifth day. On the same day, blood cultures grew Fusobacterium necrophorum, raising suspicion of LS. Doppler ultrasound detected a thrombus in the left external jugular vein. Anticoagulant therapy with low-molecular-weight heparin and clopidogrel was initiated. The fever resolved by the seventh day of full antibiotherapy After three weeks of intravenous therapy, follow-up imaging showed regression of the thrombus. The patient completed a four-week course of antibiotics and anticoagulants and was discharged with full recovery. This case highlights the diagnostic challenge of LS presenting with gastrointestinal symptoms and emphasizes the importance of early blood cultures and imaging. External jugular vein involvement due to F. necrophorum is rare and should be considered in patients presenting with septic emboli.
Case Report
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 15, 2025

Teaching Social Studies in an Integrated Manner: The Lived Experience of Out-Of-Field Social Studies Teachers

Abstract This study investigated the pedagogical implications of out-of-field teaching in Social Studies. The Out-of-field Social Studies teachers could encounter several challenges in their preparation and the implementation of the integrated Social Studies curriculum. This study sought the lived experiences of the out-of-field teachers concerning the causes of out-of-field teaching in social studies, [...] Read more.
This study investigated the pedagogical implications of out-of-field teaching in Social Studies. The Out-of-field Social Studies teachers could encounter several challenges in their preparation and the implementation of the integrated Social Studies curriculum. This study sought the lived experiences of the out-of-field teachers concerning the causes of out-of-field teaching in social studies, problems encountered by the out-of-field teachers and the mechanisms they employ to cope with the teaching of Social Studies. The study chose the qualitative phenomenological research design. Data were collected from all the 17 out-of-field Social Studies teachers through in-depth structured interview. Data were transcribed and analysed, through the inductive thematic analysis approach, unveiling of themes and concepts from the narratives of the research participants. The study revealed that out-of-field teaching in Social Studies occurs as a result of teacher shortage in integrated social studies programme. It is also caused by the perception that any teacher could teach Social Studies irrespective of the teachers’ qualification. Out-of-field teacher encounter problems such as inadequate content and pedagogical knowledge, lack of classroom managerial techniques and inability to deliver lessons through the integrated approach. Engaging in professional development courses, peer coaching, in-service training and workshops were some of the mechanisms employed by out-of-field teachers to cope with the teaching of Social Studies. The pedagogical implications of this phenomenon are that when teaching the Social Studies, the out-of-field teachers place more emphasis on aspects of the Social Studies curriculum where they have much knowledge and skip or put less emphasis on other aspects they lack in-depth knowledge, thus, the integrated approach to teaching Social Studies is not adopted effectively by out-of-field teachers. This waters down the content of Social Studies at the Senior High School level. Addressing the problem of out-of-field teaching in Social Studies requires training and recruiting more teachers who have background training and experience in the integrated approach to the teaching of Social Studies.
Review Article
Open Access May 01, 2025

The Importance of Job Satisfaction, Work Engagement, and Sufficient Staffing in the Nursing Practice

Abstract The commentary paper reviewed the above research study conducted by Wang et al. (2025), and the investigators examined the association between nurse staffing, job satisfaction, and work engagement, and how these variables impact the quality of care provision provided among the Chinese hospitals. Despite knowing that low staffing within the healthcare facilities is a global issue, Wang and [...] Read more.
The commentary paper reviewed the above research study conducted by Wang et al. (2025), and the investigators examined the association between nurse staffing, job satisfaction, and work engagement, and how these variables impact the quality of care provision provided among the Chinese hospitals. Despite knowing that low staffing within the healthcare facilities is a global issue, Wang and colleagues believed that low staffing is negatively and significantly associated with nurse’s welfare and patient care outcome. This issue causes an increase in burnout and decreased retention of healthcare providers within the clinical setting. It is important to consider and focus on improving and fostering job satisfaction and work engagement among nurses to provide better quality care even within a low staffing environment. According to Wang and colleagues, low staffing outcomes could be mitigated by encouraging workplaces to create healthy and supportive environments for the engaged and satisfied nurses. These would result in better out among patients and increase job fulfilment and welfare among nurses.
Commentary
Open Access April 10, 2025

Advancements in Pharmaceutical IT: Transforming the Industry with ERP Systems

Abstract The pharmaceutical industry is undergoing a profound transformation driven by advancements in Information Technology (IT), with Enterprise Resource Planning (ERP) systems playing a pivotal role in reshaping operations. These systems offer integrated solutions that streamline key business processes, such as production, inventory management, supply chain optimization, regulatory compliance, and data [...] Read more.
The pharmaceutical industry is undergoing a profound transformation driven by advancements in Information Technology (IT), with Enterprise Resource Planning (ERP) systems playing a pivotal role in reshaping operations. These systems offer integrated solutions that streamline key business processes, such as production, inventory management, supply chain optimization, regulatory compliance, and data integration, contributing significantly to operational efficiency and organizational agility. This paper explores the evolution and impact of ERP systems within the pharmaceutical sector, highlighting their contributions to overcoming the industry’s inherent challenges, including complex regulatory requirements, the need for accurate and real-time data, and the demand for supply chain resilience. The integration of cloud-based ERP solutions, the incorporation of emerging technologies like Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT), and enhanced data analytics capabilities have revolutionized pharmaceutical IT. These advancements not only reduce operational costs, improve forecasting accuracy, and enhance collaboration but also ensure compliance with stringent global regulations, such as Good Manufacturing Practices (GMP) and FDA guidelines. Moreover, ERP systems have been instrumental in managing the pharmaceutical supply chain, ensuring product traceability, and improving inventory control and order fulfillment processes. This manuscript examines how ERP systems enable pharmaceutical companies to maintain high standards of product quality, improve decision-making, and ensure the safety and efficacy of drugs through robust tracking and auditing mechanisms. A case study of a pharmaceutical company that implemented an ERP system demonstrates the tangible benefits, including increased operational efficiency, improved compliance rates, and enhanced customer satisfaction. However, despite the clear advantages, challenges such as customization complexities, data integration issues, and resistance to change remain. As the pharmaceutical industry continues to evolve, ERP systems will remain a cornerstone of digital transformation, facilitating smarter decision-making, better resource management, and enhanced collaboration across global operations. This paper also identifies future trends, including the potential of AI and blockchain technologies in further strengthening ERP systems and transforming the pharmaceutical landscape.
Review 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 22, 2025

Enhancing Scalability and Performance in Analytics Data Acquisition through Spark Parallelism

Abstract Data acquisition serves as a critical component of modern data architecture, with REST API integration emerging as one of the most common approaches for sourcing external data. This study evaluates the efficiency of various methodologies for collecting data via REST APIs and benchmark their performance. It explores how leveraging the Spark distributed computing platform can optimize large scale [...] Read more.
Data acquisition serves as a critical component of modern data architecture, with REST API integration emerging as one of the most common approaches for sourcing external data. This study evaluates the efficiency of various methodologies for collecting data via REST APIs and benchmark their performance. It explores how leveraging the Spark distributed computing platform can optimize large scale REST API calls, enabling enhanced scalability and improved processing speeds to meet the demands of high volume data workflows.
Figures
PreviousNext
Review 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.
Figures
PreviousNext
Original Article
Open Access February 26, 2025

Innovations and Challenges in Pharmaceutical Supply Chain, Serialization and Regulatory Landscape

Abstract The pharmaceutical supply chain has become increasingly complex and vulnerable to various risks, including counterfeit drugs, diversion, and fraud. As these challenges threaten patient safety and the integrity of global healthcare systems, serialization has emerged as a pivotal innovation in pharmaceutical logistics and regulatory compliance. Serialization involves assigning unique identifiers to [...] Read more.
The pharmaceutical supply chain has become increasingly complex and vulnerable to various risks, including counterfeit drugs, diversion, and fraud. As these challenges threaten patient safety and the integrity of global healthcare systems, serialization has emerged as a pivotal innovation in pharmaceutical logistics and regulatory compliance. Serialization involves assigning unique identifiers to individual drug packages, enabling precise tracking and authentication at every stage of the supply chain. This process provides unprecedented transparency, enhances product security, and facilitates real-time monitoring of pharmaceutical products as they move from manufacturers to end consumers. Despite its potential to revolutionize pharmaceutical traceability, the integration of serialization technologies faces numerous obstacles. These include high implementation costs, regulatory inconsistencies across regions, and the technological challenges of managing vast amounts of data. Moreover, the complex, multi-tiered nature of the global supply chain introduces additional risks related to data integrity, cybersecurity, and interoperability between systems. As pharmaceutical companies seek to navigate these challenges, innovations in serialization technology—such as blockchain, artificial intelligence (AI), the Internet of Things (IoT), and radio frequency identification (RFID)—are providing promising solutions to enhance efficiency, reduce fraud, and increase visibility. This manuscript explores both the innovative advancements and the key challenges associated with the integration of serialization in the pharmaceutical supply chain. It delves into the evolving regulatory landscape, highlighting the need for global harmonization of serialization standards, and examines the impact of serialization on securing pharmaceutical distribution networks. Additionally, the paper emphasizes the importance of collaboration among manufacturers, technology providers, and regulatory bodies in overcoming implementation barriers and realizing the full potential of serialization. As the pharmaceutical industry moves towards a more interconnected and data-driven future, serialization promises to play a central role in shaping the next generation of drug safety and supply chain management. By addressing the hurdles to adoption and leveraging emerging technologies, the pharmaceutical sector can create a more secure, transparent, and efficient supply chain that better serves public health and fosters greater trust among consumers and healthcare professionals alike.
Review 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.
Figures
PreviousNext
Article
Open Access February 24, 2025

Socioeconomic Status, Trauma, Cognitive Function, Impulsivity, Reward Salience, and Future Substance Use: Role of Left Caudate Connectivity with the Cingulo-Opercular Network

Abstract Background: While understanding how corticostriatal connectivity is associated with socioeconomic status (SES), trauma exposure, cognitive function, reward salience, impulsivity, and future substance use is essential to identifying neurobiological pathways that contribute to health disparities and behavioral outcomes, very few studies have tested the role of left caudate resting-state [...] Read more.
Background: While understanding how corticostriatal connectivity is associated with socioeconomic status (SES), trauma exposure, cognitive function, reward salience, impulsivity, and future substance use is essential to identifying neurobiological pathways that contribute to health disparities and behavioral outcomes, very few studies have tested the role of left caudate resting-state functional connectivity (rsFC) with the cingulo-opercular network as a proxy of corticostriatal connectivity in social, cognitive, and behavioral processes. Objective: This study investigates the associations between left caudate-cingulo-opercular connectivity and multiple biopsychosocial domains, including low SES, high trauma exposure (financial and life events), cognitive function, reward salience, impulsivity, depression, and future substance use (tobacco and marijuana use). Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) data were analyzed to assess connectivity between the left caudate and the cingulo-opercular network. Data on socioeconomic status, trauma exposure, cognitive performance, and mental health were collected from participants. Future substance use behaviors were evaluated through longitudinal follow-ups. Correlation and regression analyses were conducted to examine relationships between corticostriatal connectivity and the targeted domains. Results: Corticostriatal hypoconnectivity was associated with lower SES, higher trauma exposure, poorer cognitive function, heightened reward salience, higher impulsivity, and history of depression. Additionally, corticostriatal hypoconnectivity at baseline predicted future tobacco and marijuana use during follow-up years. Conclusion: Corticostriatal hypoconnectivity, particularly the rsFC between the left caudate and the cingulo-opercular network, may represent a potential mechanism linking a wide range of social, emotional, and behavioral problems in youth. These findings suggest that corticostriatal hypoconnectivity could serve as a neurobiological marker for identifying individuals at risk for depression, low cognitive function, high reward salience, impulsivity, and substance use, emphasizing the interplay between socioeconomic and neurocognitive factors in shaping behavioral health trajectories.
Figures
PreviousNext
Article
Open Access February 09, 2025

The Future of Longevity Medicine from the Lens of Digital Therapeutics

Abstract Digital therapeutics (DTx) are emerging as a pivotal tool in promoting longevity by addressing non-communicable diseases (NCDs) such as diabetes, cardiovascular diseases, and mental health disorders. These software-driven interventions offer personalized, evidence-based treatments that can be accessed via digital devices, making healthcare more accessible and scalable. One of the key advancements [...] Read more.
Digital therapeutics (DTx) are emerging as a pivotal tool in promoting longevity by addressing non-communicable diseases (NCDs) such as diabetes, cardiovascular diseases, and mental health disorders. These software-driven interventions offer personalized, evidence-based treatments that can be accessed via digital devices, making healthcare more accessible and scalable. One of the key advancements in DTx is the integration of artificial intelligence (AI) and machine learning (ML) to tailor interventions based on individual health data. This personalization enhances the effectiveness of treatments and supports preventive care by identifying risk factors early. The need for digital therapeutics is underscored by the rising prevalence of NCDs, which are responsible for a significant portion of global mortality and healthcare costs. Traditional healthcare systems often struggle to provide timely and personalized care, especially in low-resource settings. DTx can bridge this gap by offering cost-effective solutions that are easily scalable. Moreover, digital therapeutics can address health inequities by providing low-cost interventions to underserved populations, thereby reducing the burden of NCDs and improving overall health outcomes. As technology continues to evolve, the potential for DTx to enhance longevity and quality of life becomes increasingly promising. Recent advancements in longevity medicine and technology have focused on extending both lifespan and healthspan, ensuring that people not only live longer but also maintain good health throughout their extended years. This review article highlights these advancements that are contributing to this compelling subject of Longevity.
Figures
PreviousNext
Review Article
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 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.
Figures
PreviousNext
Article
Open Access November 16, 2024

Digital Therapeutics: A New Dimension to Diabetes Mellitus Management

Abstract Digital therapeutics (DTx) play a transformative role in diabetes management by leveraging technology to provide personalized, data-driven medical interventions. These tools enhance self-management by offering continuous monitoring and real-time feedback on glucose levels, diet, and physical activity. This personalized approach helps patients adhere to treatment plans and make informed lifestyle [...] Read more.
Digital therapeutics (DTx) play a transformative role in diabetes management by leveraging technology to provide personalized, data-driven medical interventions. These tools enhance self-management by offering continuous monitoring and real-time feedback on glucose levels, diet, and physical activity. This personalized approach helps patients adhere to treatment plans and make informed lifestyle changes, leading to improved clinical outcomes such as reduced HbA1c levels and better overall diabetes control. The importance of DTx lies in their ability to make diabetes care more accessible and convenient. Mobile apps and telemedicine platforms enable patients to receive support and guidance from anywhere, reducing the need for frequent in-person visits. Additionally, DTx often include behavioral support features like reminders, educational content, and motivational tools, which are crucial for maintaining healthy habits and managing stress. Currently, the dynamics of DTx in diabetes are rapidly evolving, with increasing integration of artificial intelligence and machine learning to further personalize and optimize care. As the adoption of these technologies grows, they hold the potential to significantly improve patient outcomes and revolutionize diabetes management on a global scale. This article will focus on the benefits of novel digital therapeutics for prevention and management of type II diabetes that are currently available in the market.
Figures
PreviousNext
Article
Open Access November 07, 2024

Optimizing Pharmaceutical Supply Chain: Key Challenges and Strategic Solutions

Abstract Pharmaceutical supply chains are critical to ensuring the availability of safe and effective medications, yet they face numerous challenges that can jeopardize public health. This article provides a comprehensive analysis of the key issues impacting pharmaceutical supply chains, including regulatory compliance, demand forecasting, supply chain visibility, quality assurance, and geopolitical risks. [...] Read more.
Pharmaceutical supply chains are critical to ensuring the availability of safe and effective medications, yet they face numerous challenges that can jeopardize public health. This article provides a comprehensive analysis of the key issues impacting pharmaceutical supply chains, including regulatory compliance, demand forecasting, supply chain visibility, quality assurance, and geopolitical risks. Regulatory compliance remains a significant concern due to the stringent guidelines imposed by authorities such as the FDA and EMA, which can lead to increased operational costs and time delays. Additionally, traditional demand forecasting methods often fail to accurately predict fluctuations in drug demand, resulting in stockouts or excess inventory. Limited supply chain visibility further complicates these challenges, hindering timely decision-making and operational efficiency. Quality assurance is paramount, as maintaining the integrity of pharmaceutical products throughout the supply chain is crucial to preventing costly recalls and ensuring patient safety. Moreover, the globalization of supply chains introduces vulnerabilities to geopolitical risks, trade disputes, and natural disasters. In response to these issues, this article outlines strategic recommendations for optimizing pharmaceutical supply chains. These include leveraging advanced analytics and IoT technologies to enhance demand forecasting and visibility, strengthening compliance through automated systems and training, fostering collaboration among stakeholders, implementing robust risk management frameworks, and investing in quality management systems. By adopting these strategies, pharmaceutical companies can enhance the efficiency and resilience of their supply chains, ultimately ensuring the continuous availability of essential medications for patients worldwide. This analysis serves as a critical resource for industry professionals seeking to navigate the complexities of pharmaceutical supply chains in an increasingly dynamic global environment.
Review 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.
Figures
PreviousNext
Article
Open Access October 30, 2024

Smokers with Multiple Chronic Disease Are More Likely to Quit Cigarette

Abstract Objective: This study aims to investigate the relationship between the presence of chronic medical conditions and cessation among U.S. adults who use combustible tobacco. We hypothesized that having chronic medical conditions would be associated with a higher likelihood of successfully quitting combustible tobacco. Methods: We utilized longitudinal data from the Population [...] Read more.
Objective: This study aims to investigate the relationship between the presence of chronic medical conditions and cessation among U.S. adults who use combustible tobacco. We hypothesized that having chronic medical conditions would be associated with a higher likelihood of successfully quitting combustible tobacco. Methods: We utilized longitudinal data from the Population Assessment of Tobacco and Health (PATH) Study, using data from Waves 1 to 6. Only current daily smokers were included in our analysis. The independent variable was the number of chronic medical conditions, defined as zero, one, or two or more. The outcome was becoming a former smoker (quitting smoking). Using multivariate regression analyses, we assessed the association between the number of chronic conditions and tobacco cessation over the six waves. We controlled for potential confounding variables, including demographic factors and socioeconomic status. Results: Our analysis revealed a significant association between the number of chronic medical conditions and the likelihood of quitting smoking. Specifically, individuals with two or more chronic conditions exhibited a greater probability of quitting smoking compared to those with no chronic conditions. The results remained significant after adjusting for potential confounders. Conclusions: Multiple chronic medical conditions may act as a catalyst for smoking cessation among U.S. adults. This suggests that the presence of multimorbidity, defined as multiple chronic disease diagnoses, may serve as “teachable moments,” prompting significant health behavior changes. These findings highlight the potential for leveraging chronic disease management and healthcare interventions to promote tobacco cessation, particularly among individuals with multiple chronic conditions.
Article
Open Access September 22, 2024

Societal Perception of New Religious Movements’ Televangelism: A Study of House of Power Ministry International and Gilgal Pentecostal Prayer Ministry International in Dunkwa-On-Offin in the Central Region of Ghana

Abstract This aimed to examine the societal perception of new religious movements' televangelism in Dunkwa-On-Offin, Ghana's Central Region. The study used a sequential explanatory mixed-methods design, using the mixed methods approach to research. The population of this study comprised Women, Regular churchgoers, believers, and those listening to televangelism services by new religious movements, as well [...] Read more.
This aimed to examine the societal perception of new religious movements' televangelism in Dunkwa-On-Offin, Ghana's Central Region. The study used a sequential explanatory mixed-methods design, using the mixed methods approach to research. The population of this study comprised Women, Regular churchgoers, believers, and those listening to televangelism services by new religious movements, as well as clergy, lay leaders, and other male worshippers. Random and purposive sampling techniques were used to select 200 women and 20 men from House of Power Ministry International and GILGAL Pentecostal Prayer Ministry International as the respondents for the study. The instruments used for data collection were questionnaires and interview guides. IBM SPSS statistics software version 23 was used to analyse the quantitative data, while qualitative data was analysed thematically with an interpretative lens. The study has revealed that society perceives the televangelism movements as helpful and encouraging but could also create trouble in fundamental Christian worship principles. The study also indicates that televangelists emphasise material things rather than spiritual matters. Other concerns included that televangelism brings about the separation of family and friends because they always inform members that their friends and family are evil. It is recommended that there is the need to change or improve the credibility perception among Christians in Ghana about televangelism. Televangelists must exhibit accountability and integrity to their worshippers by providing adequate information to encourage viewers to support their ministries.
Figures
PreviousNext
Article
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 August 16, 2024

Race, College Graduation, and Time of Retirement in the United States: A Thirty-Year Longitudinal Cohort of Middle-Aged and Older Adults

Abstract Introduction: College education is typically associated with the ability to work in less physically demanding occupations, allowing for a later retirement age. However, research indicates that highly educated Black individuals often work in more demanding occupations, which affects their retirement age. Aim: Building on the Minorities’ Diminished Returns [...] Read more.
Introduction: College education is typically associated with the ability to work in less physically demanding occupations, allowing for a later retirement age. However, research indicates that highly educated Black individuals often work in more demanding occupations, which affects their retirement age. Aim: Building on the Minorities’ Diminished Returns (MDRs) literature, we tested whether the benefit of college education on delaying the time of retirement is weaker for Black compared to White middle-aged and older adults. Methods: We utilized data from the Health and Retirement Study (HRS), which includes a 30-year longitudinal follow-up of a nationally representative sample of middle-aged and older adults in the United States. Education levels at baseline were categorized as less than college graduate (some high school, GED, high school diploma, or some college) and college graduate. The outcome was the time to retirement, measured from wave 2 to wave 15 (baseline to 30 years later). We graphed survival curves and used independent samples t-tests to assess associations between college graduation and time of retirement, overall and by race. Results: Our analysis included 6,803 White and Black participants who were employed at baseline and followed for up to 30 years. Overall, there was a positive association between college graduation and retirement timing, with individuals with higher education retiring later. However, we found significant racial differences in the retirement age of college graduates, indicating notable racial disparities in the effects of college graduation on retirement timing, disadvantaging Black college-educated individuals. Specifically, among Whites, but not Blacks, college education was associated with later retirement. Conclusion: Consistent with Minorities’ Diminished Returns theory, the positive effect of college education on retirement timing are weaker for Black than for White middle-aged and older Americans. To address racial disparities, it is insufficient to focus solely on economic disparities. While closing the educational gap is important, we must also work to equalize labor market experiences for Black and White individuals with similar educational credentials. Structural factors contributing to the diminished returns of college education for Black populations must be addressed to effectively close racial disparities.
Figures
PreviousNext
Article
Open Access August 12, 2024

Handling Practices of Folded Vermicelli by Small-scale Processors in Tanga City, Tanzania

Abstract This study assessed the handling and processing practices of 30 small-scale folded vermicelli processors in Tanga, specifically in urban areas of Tanga City, Tanzania. However, the micro- and small-scale processors were producing in unhygienic way because they are lacking facilities and equipment to process and handle the product hygienically. Multistage sampling design was adopted for this study [...] Read more.
This study assessed the handling and processing practices of 30 small-scale folded vermicelli processors in Tanga, specifically in urban areas of Tanga City, Tanzania. However, the micro- and small-scale processors were producing in unhygienic way because they are lacking facilities and equipment to process and handle the product hygienically. Multistage sampling design was adopted for this study and face-to-face interviews were conducted to collect data from all processing units through nine streets using semi-structured questionnaires and observation checklists. Data were analyzed using Statistical Package for Social Sciences, where the statistics aspect was determined from the results obtained. The processors found across various streets (ranging from 3.3% in Kwaminchi Street to 23.3% in Mabawa Street), exhibited diverse demographics, with 53.3% being owner-operators and 40% and 6.7% in labourer and supervisor roles, respectively. A significant portion (53.3%) had 1-3 years of experience, and a small portion (10%) attended formal training in pasta processing. Despite 73.3% possessing food manufacturing licenses, many were unfamiliar with legal requirements, lacking documentation and standardized processes, raising concerns about food safety. Raw materials were sourced locally, but 56.7% lacked storage facilities. Hygienic practices varied, with 43.3% undergoing periodic medical check-ups, 70% using protective gear, and 60% had hand washing facilities. Sun drying was the sole method employed, with 86.7% placed drying trays on rooftops. Packaging practices raised concerns, as 93.3% reused woven polypropylene bags, potentially impacting product quality. Awareness of aflatoxin and its health implications was lacking in 90% of the processors. Overall, the study highlighted gaps in awareness, training, and adherence to standards among processors, posing potential risks to food safety and quality. Encourage them to adhere with Tanzania Bureau of Standards requirements and formalize their quality control practices.
Figures
PreviousNext
Article
Open Access July 25, 2024

Leadership Styles of Female Leaders in Management of Senior High Schools in the Central Region of Ghana

Abstract The role and contribution of women in modern organisations have been phenomenal. However, societal norms and other patriarchal values continue to stifle the progress of women leaders. The study's overall purpose was to examine the leadership styles of female leaders in managing senior high schools in the Central Region of Ghana. The study adopted non-numerical data and used a purely qualitative [...] Read more.
The role and contribution of women in modern organisations have been phenomenal. However, societal norms and other patriarchal values continue to stifle the progress of women leaders. The study's overall purpose was to examine the leadership styles of female leaders in managing senior high schools in the Central Region of Ghana. The study adopted non-numerical data and used a purely qualitative research approach. A phenomenological design supported the study framework, and the required data was collected through interviews. The target population for the study were female headmistresses and assistant headmistresses in the various Senior High Schools in the Metropolis. The study involved all six female headmistresses and eight assistant headmistresses in the Metropolis. The participants were sampled using the census to meet the study objectives. The data were analysed thematically. The study revealed that married couples use the participatory leadership style, but those who are single use the assertive style. The study also concluded that women leaders who are single and are farther from 60 years old are more likely to have problems in the discharge of their duties as leaders since men, per societal influence, will always try to resist the control of women leaders. The Ghana education service should package special incentives for women who aspire to achieve the utmost leadership role of becoming heads of senior high schools. It will motivate the young women generation. It is also recommended that women in leadership positions in the Ghana Education Service are advised to learn by updating their skills and competencies to grow in confidence and share ideas with colleagues in the same field to adopt and adapt leadership styles that have worked in other institutions to handle institutional challenges.
Review Article
Open Access July 21, 2024

Securing Pharmaceutical Supply chain to Combat Active Pharmaceutical Ingredient Counterfeiting

Abstract Pharmaceutical Product serialization aims to assign distinct serial numbers to items within a pharmaceutical supply chain. However, this process faces several security challenges like Theft of valid serial numbers may occur, enabling the labelling of counterfeit products. Therefore, it's essential to ensure the uniqueness of serial numbers can be verified at any point in the product's lifecycle [...] Read more.
Pharmaceutical Product serialization aims to assign distinct serial numbers to items within a pharmaceutical supply chain. However, this process faces several security challenges like Theft of valid serial numbers may occur, enabling the labelling of counterfeit products. Therefore, it's essential to ensure the uniqueness of serial numbers can be verified at any point in the product's lifecycle within the supply chain. Intimidatory nodes along the distribution network could corrupt planned changes of custody for products. Ensuring verifiability of compliance with these changes is crucial. Manufacturers and consumers need assurance that perishable goods with expired shelf lives are appropriately discarded. In this paper, we review a product serialization method leveraging blockchain technology to address these security concerns within a multi-party perishable goods supply chain. Blockchains offer potential solutions by providing a secure platform for data sharing in multi-party environments, enhancing security and transparency. Within Blockchain technology, each distribution partner is registered to uphold transparency regarding drug information. The system facilitates real-time transfer of ownership changes, recording them as blocks with date and time stamps. This ensures visibility to all partners in real time, maintaining the authenticity of drugs. This article aims to outline how Blockchain technology benefits the pharmaceutical industry by enhancing traceability and trackability of drugs throughout the entire pharmaceutical supply chain.
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.
Figures
PreviousNext
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.
Figures
PreviousNext
Article
Open Access July 10, 2024

Achieving Maintainability, Readability & Understandability of Software Projects using Code Smell Prediction

Abstract Maintenance of large-scale software is difficult due to large size and high complexity of code.80% of software development is on maintenance and the other 60% is on trying to understand the code. The severity of the code smells must be measured as well as fairness on it because it will help the developers especially in large scale source code projects. Code smell is not a bug in the system as it [...] Read more.
Maintenance of large-scale software is difficult due to large size and high complexity of code.80% of software development is on maintenance and the other 60% is on trying to understand the code. The severity of the code smells must be measured as well as fairness on it because it will help the developers especially in large scale source code projects. Code smell is not a bug in the system as it doesn’t prevent the program from functioning but it may increase the risk of software failure or performance slowdown. Therefore, this paper seeks to help developers with early prediction of severity of code smells and test the level of fairness on the predictions especially in large scale source code projects. Data is the collection of facts and observations in terms of events, it is continuously growing, getting denser and more varied by the minute across different disciplines or fields. Hence, Big Data emerged and is evolving rapidly, the various types of data being processed are huge, but no one has ever thought of where this data resides, we therefore noticed this data resides in software’s and the codebases of the software’s are increasingly growing that is the size of the modules, functionalities, the size of the classes etc. Since data is growing so rapidly it also mean the codebases of software’s or code are also growing as well. Therefore, this paper seeks to discuss the 5V’s of big data in the context of software code and how to optimize or manage the big code. When we talk of "Big Code for Big Software's," we are referring to the specific challenges and considerations involved in developing, managing, and maintaining of code in large-scale software systems.
Figures
PreviousNext
Technical Note
Open Access May 14, 2024

A review of reliability techniques for the evaluation of Programmable logic controller

Abstract PLCs, or programmable logic controllers, are essential parts of contemporary industrial automation systems and are responsible for managing and keeping an eye on a variety of operations. PLC reliability is critical to maintaining industrial systems' continuous and secure operation. A wide range of reliability strategies were used to improve the reliability of Programmable Logic Controllers, and [...] Read more.
PLCs, or programmable logic controllers, are essential parts of contemporary industrial automation systems and are responsible for managing and keeping an eye on a variety of operations. PLC reliability is critical to maintaining industrial systems' continuous and secure operation. A wide range of reliability strategies were used to improve the reliability of Programmable Logic Controllers, and this article methodically looks at them all. The evaluation classified PLC reliability techniques into Root Cause Analysis (RCA), Reliability Centered Maintenance (RCM), Hazard analysis (HA), Reliability block diagram (RBD), Fault tree analysis (FTA), Physics of failure (PoF) and FMEA/FMECA, after thoroughly reviewing the body of literature. The proportion of reviewed papers using either RCA, RCM, FMEA/FMECA, FTA, RBD, RCM, PoF, or Hazard analysis to increase the reliability of PLCs showed that RCA, which makes up 20% of the publications reviewed, has been used the most to increase the reliability of the PLC, followed by HA, RCM, RBD, FTA, and PoF, which account for 17%, 16%, 16%,13%, 10%, and 8% of the articles reviewed, respectively. The paper discusses new developments and trends in PLC reliability, such as the application of machine learning (ML) and artificial intelligence (AI) to fault detection and predictive maintenance.
Figures
PreviousNext
Review Article
Open Access April 24, 2024

Optimization of Delirium Care in Adult Patients with Cancer: A Comprehensive and Integrative Review of Efficacy and Patient Outcomes

Abstract Delirium is a major complication most commonly observed in patients with advanced cancer. However, despite its prevalence, the early diagnosis, management, and prevention of this condition have not seen significant progress. Aim of this research is to provide insights into the prevalence of delirium, the optimization of interventions for managing delirium symptoms, their effectiveness and the [...] Read more.
Delirium is a major complication most commonly observed in patients with advanced cancer. However, despite its prevalence, the early diagnosis, management, and prevention of this condition have not seen significant progress. Aim of this research is to provide insights into the prevalence of delirium, the optimization of interventions for managing delirium symptoms, their effectiveness and the impact of underlying factors on the reversibility of delirium in advanced cancer patients receiving palliative care. The review involved systematic searches of relevant databases including MEDLINE, CINAHL, ProQuest Nursing and Allied Health, and PsychInfo using refined search terms. Eight publications out of 614 studies originally searched were selected and critically reviewed. Their quality was assessed using Joanna Briggs Institute's Critical Appraisal Tool for Case Series. Data abstraction and content analysis were performed to synthesize the findings. Delirium is prevalent among advanced cancer patients in palliative care, with rates ranging from 10.3% to 24.1%. Pharmacotherapy and non-pharmacological interventions showed effectiveness in reducing delirium symptoms. Delirium was found to be reversible through palliative care interventions, antipsychotic medications, and exercise therapy. Effective delirium management is crucial in improving the quality of life of cancer patients. This review emphasizes the importance of subtype-specific treatments, standardized guidelines, and long-term follow-up studies. Implementing evidence-based individualized approaches to delirium management can optimize treatment efficacy and clinical outcomes in patients as well as improve the quality of care. Tailored interventions, standardized protocols, and further research are hereby recommended.
Figures
PreviousNext
Review Article
Open Access April 11, 2024

5V’s of Big Data Shifted to Suite the Context of Software Code: Big Code for Big Software Projects

Abstract Data is the collection of facts and observations in terms of events, it is continuously growing, getting denser and more varied by the minute across different disciplines or fields. Hence, Big Data emerged and is evolving rapidly, the various types of data being processed are huge, but no one has ever thought of where this data resides, we therefore noticed this data resides in software’s and the [...] Read more.
Data is the collection of facts and observations in terms of events, it is continuously growing, getting denser and more varied by the minute across different disciplines or fields. Hence, Big Data emerged and is evolving rapidly, the various types of data being processed are huge, but no one has ever thought of where this data resides, we therefore noticed this data resides in software’s and the codebases of the software’s are increasingly growing that is the size of the modules, functionalities, the size of the classes etc. Since data is growing so rapidly it also mean the codebases of software’s or code are also growing as well. Therefore, this paper seeks to discuss the 5V’s of big data in the context of software code and how to optimize or manage the big code. When we talk of "Big Code for Big Software's," we are referring to the specific challenges and considerations involved in developing, managing, and maintaining of code in large-scale software systems.
Article
Open Access March 06, 2024

Embedded Architecture of SAP S/4 HANA ERP Application

Abstract The SAP HANA Application to handle operational workloads that are consistent with transactions while also supporting intricate business analytics operations. Technically speaking, the SAP HANA database is made up of several data processing engines that work together with a distributed query processing environment to provide the entire range of data processing capabilities. This includes graph and [...] Read more.
The SAP HANA Application to handle operational workloads that are consistent with transactions while also supporting intricate business analytics operations. Technically speaking, the SAP HANA database is made up of several data processing engines that work together with a distributed query processing environment to provide the entire range of data processing capabilities. This includes graph and text processing for managing semi-structured and unstructured data within the same system, as well as classical relational data that supports both row- and column-oriented physical representations in a hybrid engine. The next-generation SAP Business Suite program designed specifically for the SAP HANA Platform is called SAP S/4HANA. The key features of SAP S/4HANA are an intuitive, contemporary user interface (SAP Fiori); planning and simulation options in many conventional transactions; simplification of business processes; significantly improved transaction efficiency; faster analytics.
Review Article
Open Access September 18, 2023

An Empirical Study of Challenges and Management Supports in Teaching and Learning of Social Studies in the Public Senior High Schools of Ghana

Abstract The purpose of this study was to examine the challenges and management supports in teaching and learning of Social Studies in Public Senior High Schools in Akuapem South and North Districts in the Eastern Region of Ghana. Quantitatively, the study adopted a cross-sectional survey using a descriptive correlational research design to assess Challenges and Management Supports Teaching and Learning of [...] Read more.
The purpose of this study was to examine the challenges and management supports in teaching and learning of Social Studies in Public Senior High Schools in Akuapem South and North Districts in the Eastern Region of Ghana. Quantitatively, the study adopted a cross-sectional survey using a descriptive correlational research design to assess Challenges and Management Supports Teaching and Learning of Social Studies in Public Senior High Schools of Ghana. The population of the study comprised social studies teachers and students in the Akuapem South and Akuapem North Districts of the Eastern Region of Ghana. Purpose and probabilistic sampling procedures were used to select senior high schools, teachers and students for the study. The main instrument for data collection was a structured questionnaire (SQ). Data was collected from 261 final year students from five Senior High Schools and 33 Social Studies teachers using structured questionnaire. Data was analysed using SPSS Version 24. Descriptive statistics (mean, SD) was conducted to summarise the data and t-test was applied to establish if there is a statistically significant difference in the perceptions of students and teachers on the school-based drivers and effective teaching and learning of social studies. The results of the study revealed that the key school-based drivers influencing the teaching and learning of social studies in the two districts relate to classroom environment; lack of management supports in terms of resource provision for practical lessons, lack of supportive physical environment such as large class size (t = 32.881, mean difference = 6.2422, p<0.05)- thus preventing teachers from engaging students in practical work and individualising their assignments (t-statistics=37.563, mean difference= 3.0920, p<0.05); and teachers inability to use diagnostics assessment tools to unraveled students difficulties and support them. The conclusion is that, the key drivers influencing effective teaching and learning of social studies are school-based and policy driven. The study therefore recommends that the government should support the teaching of Social Studies through provision of adequate resources to help teachers improve their output. Again, the student-teacher ratio should be reduced.
Article
Open Access September 09, 2023

Knowledge Base on “Burkina” Beverage in Ghana

Abstract The purpose of this study was to examine people’s knowledge base on Burkina beverages in Winneba in the Central Region of Ghana. The study employed a Mixed Sequential Explanatory research approach. The population for the study were dairy consumers living in Winneba. The Krejcie and Morgan table in 1970 was used to determine the 381 sample size of this study. The study employed the [...] Read more.
The purpose of this study was to examine people’s knowledge base on Burkina beverages in Winneba in the Central Region of Ghana. The study employed a Mixed Sequential Explanatory research approach. The population for the study were dairy consumers living in Winneba. The Krejcie and Morgan table in 1970 was used to determine the 381 sample size of this study. The study employed the purposive, convenient and simple random sampling technique to select 100 out of 381 respondents for the study. The instrument employed in this study was a semi-structured interview guide to generate responses on people’s knowledge of “Burkina”. An Independent t-test was used to test the null hypothesis raised at a 0.05 level of significance. Based on the results of the study, it is concluded that respondents have substantial knowledge of “Burkina”. Street-sold “Burkina” can be modified using flavours and other cereals. Fresh milk must be pasteurized before using it for “Burkina”, well packaged, and sold in a hygienic condition. Certain factors such as packaging, environment, food safety, price, variation in thickness and flavours influence the rate of consumption of the “Burkina”. ‘‘Burkina’’ prepared with corn agglomerates had improved physicochemical attributes and health benefits. It is recommended that Food and Drug Authority representatives in winneba should regulate the “Burkina” samples on the Winneba market to ensure they are nutritious and, prepared and sold under hygienic conditions. There is the need also for Food and Drug Authority representatives in Winneba to ensure the standardization of the “Burkina” preparation to achieve a fair distribution of nutrients from all producers in Winneba and to ensure that the product meets standards before selling. Due to varying cereals, flavour options, good packaging, and pasteurization of the milk (fresh) and sold in a hygienic environment. It is again recommended that researchers develop ‘‘Burkina’’ with several flavour options and other cereals and test for consumer acceptability.
Figures
PreviousNext
Article
Open Access September 10, 2023

Pharmaceutical Drug Packaging and Traceability: A Comprehensive Review

Abstract 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, [...] Read more.
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.
Review Article
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.
Figures
PreviousNext
Article
Open Access July 21, 2023

Covid-19-Associated Myopericardial Injury: A Macro and Microscopic Description

Abstract Authors describe autoptic findings of two cases whose COVID-19 diagnosis was supported by laboratory data. Both patients were Caucasian individuals of middle age (one male, 47 years old; the other a female aging 36 years) that were considered as previously healthy. Clinically they died from cardiorespiratory insufficiency while being treated in intensive care units. None of them was intubated and [...] Read more.
Authors describe autoptic findings of two cases whose COVID-19 diagnosis was supported by laboratory data. Both patients were Caucasian individuals of middle age (one male, 47 years old; the other a female aging 36 years) that were considered as previously healthy. Clinically they died from cardiorespiratory insufficiency while being treated in intensive care units. None of them was intubated and blood oxygen levels (SpO2) decreased below 90% only during the agonal phase. Myopericardial changes were visible from a macroscopic point of view, with hemorrhagic and necrotic areas involving pericardium. Fresh hemorrhage and severe hyperemia were both signs of vascular damage and extravasation leading to acute myocardial injuries. Lymphocytic presence was disparate and not constant.
Figures
PreviousNext
Clinical Image
Open Access February 26, 2023

Teachers Supervisory Practices in the Kindergarten Schools in Ghana: A Case of Komenda Edina Eguafo Abirem Municipality

Abstract The supervisory role of kindergarten teachers is primarily concerned with supervising and managing the efforts of their learning environment to create safe, positive learning environments for all learners. The purpose of this study was to assess teachers’ supervisory practices of learners in Kindergarten schools in Komenda Edina Eguafo Abirem municipality. (K.E.E.A) Municipality in the Central [...] Read more.
The supervisory role of kindergarten teachers is primarily concerned with supervising and managing the efforts of their learning environment to create safe, positive learning environments for all learners. The purpose of this study was to assess teachers’ supervisory practices of learners in Kindergarten schools in Komenda Edina Eguafo Abirem municipality. (K.E.E.A) Municipality in the Central Region of Ghana. The study employed the qualitative research approach using the interpretivism paradigm. The instrumental case study design was adopted for this study. Population of the study comprised public kindergarten schools in KEEA Municipality. A multi-stage purposeful random sampling technique was used to select sixteen (16) respondents for the study. The semi-structured interview and observation checklist were the main instruments employed in the data collection for this study. The qualitative data was analysed by the use of the interpretative method based on the themes arrived at during the data collection. The themes were related to the research question and interpreted on the number of issues raised by respondents. These were based on question on the semi-structured interview. The study indicated that, kindergarten teachers do not supervise their learners during out-door activities or at playground, thinking it is the available time to relax after learners are out to play. The study also revealed that, kindergarten teachers do not pay close attention to learners and their physical environment to detect danger and threats. Also, in relation to proximity in supervision, the study found that, kindergarten teachers do not maintain physical closeness supervision of their learners to promptly salvage them from occurring danger during supervision. It is recommended that, the Ministry of Education (MoE), Ghana Education Service (GES), and other Agencies in Education (AiE) should strategically and periodically organize workshop trainings and seminars on teacher supervision and safety for kindergarten teachers. It is also recommended that, Tertiary institutions like the teaching universities and colleges of education should mount courses specifically for Teachers Supervision and School Safety for pre-service teachers and school administrators.
Article
Open Access November 25, 2022

Effects of Teachers’ Supervision on the Safety of Kindergarten Pupils in the Central Region of Ghana

Abstract The supervisory role of kindergarten teachers is primarily concerned with supervising and managing the efforts of their learning environment to create safe, positive learning environments for all learners, as well as ensuring that no child is left alone or unsupervised by teachers or caregivers while under their supervision. The purpose of this study was to examine the effects of teachers’ [...] Read more.
The supervisory role of kindergarten teachers is primarily concerned with supervising and managing the efforts of their learning environment to create safe, positive learning environments for all learners, as well as ensuring that no child is left alone or unsupervised by teachers or caregivers while under their supervision. The purpose of this study was to examine the effects of teachers’ supervision on the safety of kindergarten pupils in Komenda Edina Eguafo Abirem (K.E.E.A.) Municipality in the central region of Ghana. Qualitatively, the Instrumental Case Study Design was employed in this study to gather information on the participants. The population consisted of 227 Kindergarten teachers in the KEEA Municipality of Ghana. Convenience sampling technique was used to select sixteen (16) public kindergarten teachers for the study. The main instrument used for data collection was semi-structured interview guide. The data were analyzed thematically. The analysis of the data was done with the help of online qualitative software, Taguette version 1.3, Using the Taguette, the researchers highlighted quotes and phrases from the interviews that were significant to the study. The study supported that, establishing a well-conducive school environment enhance teachers’ supervision which goes a long way to ensures learners’ comfortability and safety; maximize learners’ academic performance; lessen fear in learners; promote teaching and learning; and support learners’ participation in play experiences. It is recommended that, key players in education such as Ministry of Education and Ghana Education Service should investigate the effect of teacher supervision on learners’ safety vis-a-vis with its educational implications. It is also recommended that, kindergarten teachers should be encouraged to supervise their learners to guarantee positive outcomes of promoting learners’ comfortability and safety; maximizing learners’ academic performance; promoting teaching and learning; and contributing to support learners’ participation in play experiences.
Article
Open Access November 21, 2022

Impact of Lesion Locations on the Severity of Post-Stroke Depression

Abstract Background: Depression occurs in one-third of stroke patients, in what is known as post-stroke depression. The lesion sites in stroke have been associated with the degree of depression. However, studies have provided different perspectives, and this necessitates further clarification. This study investigates the relationship between the lesion sites and the severity of depression in [...] Read more.
Background: Depression occurs in one-third of stroke patients, in what is known as post-stroke depression. The lesion sites in stroke have been associated with the degree of depression. However, studies have provided different perspectives, and this necessitates further clarification. This study investigates the relationship between the lesion sites and the severity of depression in ischemic stroke patients. Methods: This cross-sectional study was conducted between January and April 2020. All samples were obtained from admitted patients with ischemic stroke who agreed to participate in the study. Data were collected using Beck’s Depression Inventory-II (BDI-II), which was used to determine the severity of depression, and the lesion sites were based on radiological imaging interpretation. Results: The study showed a significant association between the lesion site and the degree of depression (OR = 5,368, p-value = 0,013). Lesions in the frontal lobe demonstrated stronger associations with the severity of depression. Conclusion: The location of the lesion, especially in the frontal lobe, was associated with more severe post-stroke depression.
Case Study
Open Access September 01, 2022

Dynamics of Pharmaceutical Drugs Serialization

Abstract The healthcare access is fundamental rights for every human being. It is Governments responsibility to provide good healthcare services and infrastructure to its citizen. Since last few decades, Government and healthcare industries are struggling to minimize the adverse events impacting people health due to fake medicine. The world health organization also predicted that 4 out of 10 medicines in [...] Read more.
The healthcare access is fundamental rights for every human being. It is Governments responsibility to provide good healthcare services and infrastructure to its citizen. Since last few decades, Government and healthcare industries are struggling to minimize the adverse events impacting people health due to fake medicine. The world health organization also predicted that 4 out of 10 medicines in developing and poor countries are either fake or potentially adulterated. Counterfeit drugs cost billions of dollars deficit to world economy and reduce research and development (R&D) funds allocation from organizations. Stopping counterfeit medicine into supply chain is main challenge for Government and regulatory authorities. The Government and regulatory authorities are now making stringent guidelines to prohibit criminals and counterfeiters to supply fake medicine in markets. Healthcare industry need stringent regulations and secure technologies provide sage and authentic drugs to patients. The FDA has published the 10 years roadmap to implement the drug traceability in United States. The Healthcare Distribution Alliance (HDA) has also mandated to print several barcodes and human readable data in product packaging hierarchy. The FDA is participating in pilot project with leading pharmaceutical drug manufacturer and wholesales to use blockchain technology in interoperable digital network for securing digital traceability data transfer between authorized trading partners.
Review Article
Open Access August 22, 2022

Managing Challenges Women Face in Leadership Positions: Carl Rogers' Humanistic Approach

Abstract The purpose of the study was to examine Carl Rogers' humanistic approach to supporting women in leadership positions to make a formed decision on how to manage the challenges they face. A qualitative approach was adopted for the study. The population of the study included fifteen (15) headmistresses and housemistresses in the Senior High Schools in the New Juaben Municipality in the Eastern [...] Read more.
The purpose of the study was to examine Carl Rogers' humanistic approach to supporting women in leadership positions to make a formed decision on how to manage the challenges they face. A qualitative approach was adopted for the study. The population of the study included fifteen (15) headmistresses and housemistresses in the Senior High Schools in the New Juaben Municipality in the Eastern Region. The purposive sampling technique was used to select schools, headmistresses and housemistresses in the schools. The schools selected were Oyoko Methodist Senior High School (OMESS), SDA Senior High School (SEDASS), Ghana Senior High School (GHANASS), Koforidua Technical Institute (KOTECH), Nana Kwaku Boateng Senior High School (OBOSS) and New Juaben Senior High School (NJUASCO). The main instruments used for data collection were a semi-structured interview guide and Reflective dialogue. Data was analysed through the use of the thematic approach. Within-case and across-case analytical technique was used to analyse the qualitative data. This was done through the identification of themes, categories and sub-categories the analytical tool for the qualitative data through interviews and reflective dialogue (RD). Themes that were extracted from the interview corresponding to Carl Rogers' humanistic person-centred) the approach were; inherent potentialities, support, motivation, power relation, INSET, cultural dimension, and guidance and counselling. The study revealed that women face challenges using inadequate school facilities they do their best possible to manage their challenges with the few facilities available, the introduction of Carl Rogers' intervention, and women became more aware of their potential in managing the challenges they face at work in their leadership positions. It is recommended that guidance programmes should be conducted often to inform both teachers and students about the potential of women. It has also emerged that women leaders do not know who they are and therefore they should undergo counselling in order to be self-actualised.
Figures
PreviousNext
Article
Open Access August 01, 2022

Counselling as a Critical Tool in Managing Ill-Discipline in Colleges of Education in Ghana

Abstract Ill-discipline has become a canker that threatens the moral fibre of institutions. This study aimed to explore the comprehensive counselling approaches that could be used to manage ill-discipline acts in Colleges of Education in Ghana. A qualitative discourse analysis study design was employed in the study. In all, 25 respondents were purposively selected from five colleges of education for the [...] Read more.
Ill-discipline has become a canker that threatens the moral fibre of institutions. This study aimed to explore the comprehensive counselling approaches that could be used to manage ill-discipline acts in Colleges of Education in Ghana. A qualitative discourse analysis study design was employed in the study. In all, 25 respondents were purposively selected from five colleges of education for the study using a semi-structured interview guide. Data collected were transcribed, coded, categorised and qualitatively analysed under themes that emerged from the analysis using the thematic approach. The study revealed that several ill-discipline acts exist in colleges of education, with perversion being the most prevailing ill-discipline act. The study recommended that the college council and management should put adequate measures in place to strengthen Guidance and Counselling units in the colleges of education. The study also recommended that college counsellors should be equipped to use appropriate counselling approaches and techniques to counsel students to desist from indulging in ill-discipline acts.
Figures
PreviousNext
Article
Open Access June 27, 2022

Development of Cellulose Nanofibre (CNF) Coating on (1) Metal Surface for Free Standing CNF Film and (2) Paper Substrates for CNF Barrier Laminates

Abstract Paper is widely used in packaging applications and is biodegradable and therefore perfectly safe as green packaging wrap for the environment. The hydrophilic nature of cellulose fibrils limits the water vapour and oxygen barrier properties of paper. To mitigate these limitations, paper is often associated with other materials, such as plastics, wax and aluminum, for achieving their good barrier [...] Read more.
Paper is widely used in packaging applications and is biodegradable and therefore perfectly safe as green packaging wrap for the environment. The hydrophilic nature of cellulose fibrils limits the water vapour and oxygen barrier properties of paper. To mitigate these limitations, paper is often associated with other materials, such as plastics, wax and aluminum, for achieving their good barrier properties. However, these materials suffer from serious environmental issues, as difficult and inefficient to recycle. Recently, cellulose nanofibre (CNF) based materials has been considered as an alternative to produce eco-friendly barrier materials. Existing techniques to prepare cellulose nanofibre films/sheets/composites/ laminates on the paper substrates are commercially not feasible and expensive. Therefore, other cost effective and readily implementable methodologies are required to achieve cellulose nanofibre barrier layers. In the present report, a novel approach is developed using spray coating technique to produce CNF materials with excellent barrier properties. Among many coating techniques, the spray coating has many advantages such as the production of even coating surface on the base sheet and contactless coating with the substrate. A laboratory scale spray coating of cellulose nanofibre suspension on a paper substrate was developed. When the cellulose nanofibre suspension concentration was varied from 0.5 to 1.5 wt. %, coat weight is increased from 2.9±0.7 to 29.3±6.9 g/m2. As a result, the air permeability of composite was decreased 0.78±0.17 to <0.0030 µm/Pa.s. Scanning electron microscopy studies of spray coated CNF laminates on the paper confirms that the surface pores in the paper substrates are filled with sprayed cellulose nanofibre and forms a continuous film on the surface of the substrate. These are the probable reasons for the reduction of air permeability of composites. A rapid preparation technique to prepare free standing cellulose nanofibre films/sheets was also developed using a bench scale spray coating system. Cellulose nanofibre suspension with concentration ranging from 1 to 2 wt% was sprayed onto a stainless steel plate, which is moving on a conveyor at a velocity of 0.32 cm/sec and then air dried. The basis weight of produced cellulose nanofibre films is varied from 52.8±7.4 to 193.1±3.4 g/m2. Processing time taken to prepare films was approximately 1.0 min, which is much less than processing times reported in the previous literature. Thus, the significant reduction in preparation time for producing the cellulose nanofibre sheet recommends that this spray coating technique can be utilized for the development of a scalable process for the fabrication of various cellulose based nanocomposite. Therefore, the laboratory scale spray coating confirms that the spraying could provide a platform for development of films/sheets/nanocomposite and also a CNF barrier layer on the base sheet. The future work is the development of a continuous spray coating of cellulose nanofibre on the base sheet and evaluation of mechanical and barrier properties spray coated barrier layers on the base sheet.
Figures
PreviousNext
Project Report
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.
Figures
PreviousNext
Article
Open Access May 23, 2022

Cellulose Nanofiber Lamination of the Paper Substrates via Spray Coating – Proof of Concept and Barrier Performance

Abstract Cellulose nanofibre (CNF) is a biorenewable and biodegradable nanomaterial and belongs to fibrous based carbohydrate polymers applied in the fabrication of various functional materials such as coating, nanocomposite, flexible electronics substrates and biomedical devices. Recently, CNF can be used as coating material for papers and paperboards to replace synthetic plastics, wax and aluminum foil [...] Read more.
Cellulose nanofibre (CNF) is a biorenewable and biodegradable nanomaterial and belongs to fibrous based carbohydrate polymers applied in the fabrication of various functional materials such as coating, nanocomposite, flexible electronics substrates and biomedical devices. Recently, CNF can be used as coating material for papers and paperboards to replace synthetic plastics, wax and aluminum foil which is not recyclable and also a threat to environment. The coating of CNF on the paper substrates enhances their barrier and mechanical properties. Spray coating is a newly proposed technique to deposit CNF on the paper and produce CNF laminates on the surface of paper to block their surface pores and allowing improve their barrier performance against water vapor, air and oxygen. Various concentration of CNF was sprayed on various paper substrates such as newsprint papers, packaging paper (brown paper) and blotting papers. The air permeability of CNF laminated paper substrates is completely impermeable against air. The SEM micrograph reveals that the surface pores in the paper substrates are filled with sprayed CNF and formed a barrier film as a laminate on the paper substrates. As a result, a considerable drop in the air permeability of the paper substrates was observed. Given this correspondence, spraying of cellulose nanofiber on the paper substrates allows the improvement of barrier performance and proof of concept for coating CNF on the paper and paperboard.
Figures
PreviousNext
Article
Open Access April 18, 2022

Preliminary Survey Analysis on Food Choices among Randomly Selected Social Media Users amidst COVID-19 Pandemic in Nigeria

Abstract A survey on food choices with a randomized sample population of individuals using various social media in Nigeria was conducted during the COVID1-19 pandemic. The data generated was subjected to basic standard statistical analysis. The parameters indicated that 94% of the population is young adults, 58.9 % percent are city dwellers, 63.6% are students, 23.4 % are into business, 86.9% are [...] Read more.
A survey on food choices with a randomized sample population of individuals using various social media in Nigeria was conducted during the COVID1-19 pandemic. The data generated was subjected to basic standard statistical analysis. The parameters indicated that 94% of the population is young adults, 58.9 % percent are city dwellers, 63.6% are students, 23.4 % are into business, 86.9% are graduates; 73.8% consume various diets, 23.4% are vegetarians and only 2.8% fed only on proteins, 30.8% of them go on two meals per day. The most choices on influence on food purchases decision are hunger (26.2%), mood (26.2%), past experience (45.8%), quality of the food products (66.7%), cost of the food products (50.5%) and government approval (28%). Also,other most preferred choices are for self-prepared food (40.21%), enhanced local diets (36 %), and a blend of foreign and local diets purchases (24%). Other highest choices include: easy preparation (37.4%), shelf life (29%); cute packaging (23.4%), swelling property preference (20.6%), minimal cooking time and energy preference (37.4%). The weighted sum, index and rank on factors influencing food choices showed that the influence of quality of food product ranked highest, followed by influence on cost. Also preference for enhanced local healthy diets to foreign ranked highest, minimal cooking time and energy costs ranked highest. These nutritional adaptations have implications to individuals, food scientists, manufacturers in the food industry, food regulatory agencies, government and other decision bodies.
Figures
PreviousNext
Article
Open Access January 10, 2022

Cardiac Hydatid Cyst: A Case Report

Abstract Although rarely, echinococcosis might present cardiac involvement, with cysts growing inside myocardial structures of arising adjacent to heart. A careful differential diagnosis with other mass formations and rare cardiac tumours is necessary, whenever there is a clinical and radiological suspicion. Imaging studies and serology will establish diagnosis. A multidisciplinary approach is warranted in [...] Read more.
Although rarely, echinococcosis might present cardiac involvement, with cysts growing inside myocardial structures of arising adjacent to heart. A careful differential diagnosis with other mass formations and rare cardiac tumours is necessary, whenever there is a clinical and radiological suspicion. Imaging studies and serology will establish diagnosis. A multidisciplinary approach is warranted in all cases, with surgical intervention being unavoidable in most settings. Patients generally present with chest pain and dyspnoea. Cases need a close follow up of their postoperative course, while being treated appropriately with albendazole (or mebendazole) for prevention of recurrences.
Figures
PreviousNext
Case Report
Open Access November 22, 2021

COVID-19 and Legionella Co-Infection

Abstract Introduction: Concurrent infections or co-infections in patients diagnosed with Coronavirus Disease-19 (COVID-19) are not uncommon and predict a pejorative prognosis. A co-infection accounts for 1 out of every 5 cases of COVID-19 and increases the likelihood of adverse health outcomes such as mechanical ventilations, ICU admissions, and death. Specifically, Legionella spp. [...] Read more.
Introduction: Concurrent infections or co-infections in patients diagnosed with Coronavirus Disease-19 (COVID-19) are not uncommon and predict a pejorative prognosis. A co-infection accounts for 1 out of every 5 cases of COVID-19 and increases the likelihood of adverse health outcomes such as mechanical ventilations, ICU admissions, and death. Specifically, Legionella spp. co-infection presents additional challenges in COVID-19 patients because of its rarity, similar clinical presentation to SARS-CoV-2, and poorer outcomes without prompt treatment. Cases Presentation: Case 1. A 62-year-old female presented with a 3-day history of subjective fever and worsening shortness of breath. Room air saturation (saO2) was 70% and improved to 100% on noninvasive positive- pressure ventilation (NIPPV). Lung auscultation revealed rales BL. Chest X –Ray (CXR) showed patchy airspace opacities bilaterally (BL), SARS-CoV-2 PCR and urine legionella antigen tests were positive. The diagnosis of hypoxic respiratory failure secondary to COVID-19 and Legionella pneumonia was made. Patient was admitted to intensive care unit (ICU) and managed with decadron, remdesivir, one unit of convalescent plasma for COVID-19 and Azithromycin for Legionella. Patient subsequently developed acute respiratory distress syndrome (ARDS). ARDS protocol was initiated. 13 days after, the patient was compassionately extubated. Case 2. A 41-year-old male presented with 5-day history of fever, worsening shortness of breath, cough and diarrhea. Patient admitted history of ethanol abuse. SaO2 was 88% and improved on oxygen canula. Lung auscultation revealed rhonchi BL. CXR showed extensive left lung consolidation. Urine test for legionella antigen was positive. COVID-19 PCR was negative, but SARS-CoV-2 IgG was reactive. The diagnosis of Legionnaire disease was made. Despite initial treatment with Azithromycin, patient's hypoxia continued to worsen requiring NIPPV, and subsequently mechanical ventilation in the ICU. The adjunction of empiric treatment for COVID-19 with convalescent plasma, remdesivir and steroids improved both clinicals and laboratory findings. Discussion: The cases illustrated the practical challenges of managing COVID-19 and legionella co- infection. Legionella spp and SARS-CoV-2 overlapping incubation periods and similar clinical presentations and complications. In the absence of diagnosis and treatment, legionella pneumonia has an intrinsic mortality rate of up to 80%. As some COVID-19 mitigation strategies, such as the closure of businesses, have enhanced the conditions for Legionella spp proliferation, the incidence of Co-infection with COVID-19 may increase. We recommend clinicians to have high-indexed suspicion of COVID-19 and Legionella co-infection in order to obtain complete work up at patient’s initial presentation.
Figures
PreviousNext
Case Report
Open Access November 05, 2021

Cerebral Palsy and Heterotaxy Syndrome: A Case Report

Abstract Background: Cerebral palsy is not only a serious neurodevelopmental disease causing significant morbidity in children, but also a traumatic experience leading to psychosocial trauma to the parents/caregivers of the affected children. It is usually caused by prenatal or early post-natal insults to the newborn brain which may be associated with some congenital syndromes like congenital heart [...] Read more.
Background: Cerebral palsy is not only a serious neurodevelopmental disease causing significant morbidity in children, but also a traumatic experience leading to psychosocial trauma to the parents/caregivers of the affected children. It is usually caused by prenatal or early post-natal insults to the newborn brain which may be associated with some congenital syndromes like congenital heart disease with transposition of the viscera but rarely a heterotaxy syndrome, a condition characterized with congenitally abnormal arrangement of the thoracic and abdominal viscera. Method: We present a case report of a 12-month-old boy with neurodevelopmental delay, recurrent episodes of non-mucoid and non-bloody diarhoea, occasional constipation, bilious vomiting, abdominal distension and fever with associated cough and difficulty in breathing. Results: We discuss an unusual presentation of cerebral palsy and heterotaxy syndrome diagnosed clinically with supporting evidence from both laboratory and radiological tests. Cerebral palsy was diagnosed from the history of birth asphyxia, delayed developmental milestone, limb spasticity and low values for all sub-scores of Bayley-III scale. Heterotaxy syndrome was diagnosed from the radiologic evidence of dextrocardia, left-sided stomach, centrally located liver and malrotation of gut with volvulus. We also provide a brief literature review of the incidence and prevalence, causes and risk factors, classification, clinical presentation and associated co-morbidities of heterotaxy syndrome. Conclusion: Diagnosis of heterotaxy syndrome in a child with background cerebral palsy is a great challenge to both physicians and radiologists. This is more so in developing countries due to poor availability of good diagnostic apparatus, therefore, a high index of suspicion is needed. A clear understanding of the clinical features, comprehensive history taking and thorough physical examination are important in making prompt diagnosis. Timely and appropriate imaging is necessary to prevent delays in diagnosis and treatment which lead to poor outcomes.
Figures
PreviousNext
Case Report
Open Access October 19, 2021

The Medical Community Should Make the Unified Disease Concept, Definition, and Diagnostic Criterion of Medically Unexplained Pain (or Symptoms)

Abstract MUP (medically unexplained pain) is a pain whose cause cannot be determined by diagnostic imaging, blood test, physical examination and past medical history, etc. Many departments have independently created the concept, definition, and diagnostic criterion in MUP. This leads to an abnormal situation in which each department has different disease concepts and diagnostic criteria. It is [...] Read more.
MUP (medically unexplained pain) is a pain whose cause cannot be determined by diagnostic imaging, blood test, physical examination and past medical history, etc. Many departments have independently created the concept, definition, and diagnostic criterion in MUP. This leads to an abnormal situation in which each department has different disease concepts and diagnostic criteria. It is out-of-the-ordinary that physicians from the different departments make different diagnoses in the same patient. MUP has caused confusion in clinical practice. The medical community should make the unified disease concept, definition, and diagnostic criterion of MUP. For this purpose, the various scientific organizations involved in MUP need to discuss. In this case, the first priority should not be the majority vote, but the treatment outcomes. The solution to a medical controversy is to choose a medical theory or treatment method that produces better long-term results.
Opinion
Open Access September 23, 2021

Standards for Digitization in Cases of Maps, Documents, and other Relics in the Service of Cultural Heritage

Abstract This paper discusses the analysis of correct digitization practices to follow for maximum performance of the technique. Although it is written for cases that fall within the broader context of culture and cultural heritage, it is ultimately about writing rules that are not limited to the above-mentioned cases, but can be used in more general situations, particularly printed materials. This paper [...] Read more.
This paper discusses the analysis of correct digitization practices to follow for maximum performance of the technique. Although it is written for cases that fall within the broader context of culture and cultural heritage, it is ultimately about writing rules that are not limited to the above-mentioned cases, but can be used in more general situations, particularly printed materials. This paper will therefore discuss the technical characteristics of the choice of digital imaging devices and distinguish the types of quality calculation in the different cases of digitized text, digitized manuscript, digitized maps, and photographs.
Figures
PreviousNext
Article
Open Access December 27, 2021

Leveraging AI and ML for Enhanced Efficiency and Innovation in Manufacturing: A Comparative Analysis

Abstract The manufacturing industry has embraced modern technologies such as big data, machine learning, and artificial intelligence. This paper examines AI and machine learning developments in the manufacturing industry, comparing current practices and data-driven projects. It aims better to understand these technologies and their potential benefits and challenges. The research identifies opportunities [...] Read more.
The manufacturing industry has embraced modern technologies such as big data, machine learning, and artificial intelligence. This paper examines AI and machine learning developments in the manufacturing industry, comparing current practices and data-driven projects. It aims better to understand these technologies and their potential benefits and challenges. The research identifies opportunities for innovative business solutions and explores industry practices and research results. The paper focuses on implementation rather than technical aspects, aiming to enhance knowledge in this area.
Figures
PreviousNext
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.
Figures
PreviousNext
Review Article
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.
Figures
PreviousNext
Review Article
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.
Figures
PreviousNext
Review Article
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.
Figures
PreviousNext
Review Article
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.
Figures
PreviousNext
Review Article
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.
Figures
PreviousNext
Review Article
Open Access December 27, 2021

Predictive Analytics and Deep Learning for Logistics Optimization in Supply Chain Management

Abstract Managing supply chains efficiently has become a major concern for organizations. One of the important factors to optimize in supply chain management is logistics. The advent of technology and the increase in data availability allow for the enhancement of the efficiency of logistics in a supply chain. This discussion focuses on the blending of analytics with innovation in logistics to improve the [...] Read more.
Managing supply chains efficiently has become a major concern for organizations. One of the important factors to optimize in supply chain management is logistics. The advent of technology and the increase in data availability allow for the enhancement of the efficiency of logistics in a supply chain. This discussion focuses on the blending of analytics with innovation in logistics to improve the operations of a supply chain. An approach is presented on how predictive analytics can be used to improve logistics operations. In order to analyze big data in logistics effectively, an artificial intelligence computational technique, specifically deep learning, is employed. Two case studies are illustrated to demonstrate the practical employability of the proposed technique. This reveals the power and potential of using predictive analytics in logistics to project various KPI values ahead in the future based on the contemporary data from the logistics operations; sheds light on the innovative technique of employing deep learning through deep learning-based predictive analytics in logistics; suggests incorporating innovative techniques like deep learning with predictive analytics to develop an accurate forecasting technique in logistics and optimize operations and prevent disruption in the supply chain. The network of supply chains has become more complex, necessitating the need for the latest technological advancements. The sectors that have gained a fair amount of attention for the application of technology to optimize their operations are manufacturing, healthcare, aerospace, and the automotive industry. A little attention has been diverted to the logistics sector; many describe how analytics and artificial intelligence can be used in the logistics sector to achieve higher optimization. Currently, significant research has been done in optimizing logistics operations. Nevertheless, with the explosive volume of historical data being produced by the logistics operations of an organization, there is a great opportunity to learn valuable insights from the data accumulated over time for more long-term strategic planning. To develop the logistics operations in an organization, the use of historical data is essential to understand the trends in the operations. For example, regular maintenance planning and resource allocation based on trends are long-term activities that will not affect logistics operations immediately but can affect the business’s strategic planning in the long run. A predictive analysis technique employed on historical data of logistics can narrow down conclusions based on the future trends of logistics operations. Thus, the technique can be used to prevent the disruption of the supply chain.
Figures
PreviousNext
Review Article
Open Access December 27, 2022

Advancing Pain Medicine with AI and Neural Networks: Predictive Analytics and Personalized Treatment Plans for Chronic and Acute Pain Managements

Abstract There is a growing body of evidence that the number of individuals suffering from chronic and acute pain is under-reported and the burden of the veteran, aging, athletic, and working populations is rising. Current pain management is limited by our capacity to collaborate with individuals continuing normal daily functions and self-administration of pain treatments outside of traditional healthcare [...] Read more.
There is a growing body of evidence that the number of individuals suffering from chronic and acute pain is under-reported and the burden of the veteran, aging, athletic, and working populations is rising. Current pain management is limited by our capacity to collaborate with individuals continuing normal daily functions and self-administration of pain treatments outside of traditional healthcare appointments and hospital settings. In this review, the current gap in clinical care for real-time feedback and guidance with pain management decision-making for chronic and post-operative pain treatment is defined. We examine the recent and future applications for predictive analytics of opioid use after surgery and implementing real-time neural networks for personalized pain management goal setting for particular individuals on the path to discharge to normal function. Integration of personalized neural networks with longitudinal data may enable the development of future treatment personalizations paired with electrical simulations.
Figures
PreviousNext
Review Article
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.
Figures
PreviousNext
Review Article
Open Access December 27, 2023

Ensuring High Availability and Resiliency in Global Deployments: Leveraging Multi-Region Architectures, Auto Scaling, and Traffic Management in Azure and AWS

Abstract Modern organizations leverage highly distributed, global deployments to provide high availability and resiliency for cloud-first applications. By hosting these applications across multiple geographic locations and relying on highly available services, organizations can prevent disruption to their business and reduce complexity by employing the scale of infrastructure offered by major cloud [...] Read more.
Modern organizations leverage highly distributed, global deployments to provide high availability and resiliency for cloud-first applications. By hosting these applications across multiple geographic locations and relying on highly available services, organizations can prevent disruption to their business and reduce complexity by employing the scale of infrastructure offered by major cloud providers. Global deployments in the cloud are built on well-known models such as failover, load balancing, and scalability. However, traditional methods used to recover from regional failure—while effective—can be complex. Typical multi-region recovery and high availability system architectures have latency and cost risks that should be considered when facing other limitations such as deployment models in the cloud. This document describes the different traffic management techniques that can be applied to multi-region strategies, focusing on trade-offs and costs. The introduction of new traffic management techniques being applied to the traditional global architectures now allows organizations to adopt cloud services more efficiently. Traffic management is much more straightforward in some environments, while others have started to leverage their traffic management platform via routing. In multi-region deployments, active-active and active-passive are the most common architectural models, allowing organizations to seamlessly handle failover, scalability, and global distribution based on business goals and requirements. However, traffic management for these infrastructures is critical to ensure just data distribution and efficiency, maintaining costs under control and workloads rerouted when necessary. Using the new traffic management techniques will allow organizations to evolve system architectures easily based on business requirements, taking advantage of cost benefits from multiple infrastructures. In these scenarios, traffic management becomes a crucial backbone of success to ensure that traffic is being efficiently and intelligently distributed [1].
Figures
PreviousNext
Review Article
Open Access February 22, 2023

Navigating the Pharmaceutical Supply Chain: Key Strategies for Balancing Demand and Supply

Abstract The pharmaceutical industry is fundamental to global healthcare, providing essential medicines that improve health outcomes and quality of life. However, the demand and supply dynamics within this sector are highly complex, shaped by various factors including demographic changes, evolving disease burdens, technological advancements, regulatory challenges, and economic pressures. This manuscript [...] Read more.
The pharmaceutical industry is fundamental to global healthcare, providing essential medicines that improve health outcomes and quality of life. However, the demand and supply dynamics within this sector are highly complex, shaped by various factors including demographic changes, evolving disease burdens, technological advancements, regulatory challenges, and economic pressures. This manuscript explores the intricate relationship between pharmaceutical medicine demand and supply, focusing on key strategies that can help companies effectively navigate these challenges. The demand for pharmaceutical products is driven by several factors, such as population growth, the aging population, the rise of chronic diseases, and the emergence of new health threats. Additionally, healthcare accessibility, affordability, and policy changes significantly impact the consumption of medicines, while innovations in medical technologies and therapies create new treatment needs. On the supply side, pharmaceutical companies face challenges related to manufacturing capacity, raw material availability, distribution logistics, and compliance with ever-evolving global regulatory frameworks. To address these challenges, the manuscript discusses strategic approaches to managing both demand and supply in the pharmaceutical sector. Key strategies include advanced demand forecasting through data analytics, optimizing supply chains for efficiency and resilience, implementing just-in-time inventory models, and investing in flexible manufacturing systems. Furthermore, global collaboration and partnerships, as well as effective risk management practices, are highlighted as essential to ensuring the availability of medicines, particularly in times of crisis or global health emergencies. This manuscript also delves into the role of policy advocacy and regulatory harmonization in stabilizing the pharmaceutical market, ensuring that medicines are accessible to all populations. In conclusion, the pharmaceutical industry must continually adapt to meet the evolving challenges of demand and supply, embracing innovation and collaboration while maintaining a focus on patient access and global healthcare equity. Through strategic planning and adaptive solutions, the pharmaceutical sector can ensure the continuous availability of critical medicines worldwide, meeting both current and future health needs.
Case Report
Open Access December 27, 2023

Leveraging Machine Learning Techniques for Predictive Analysis in Merger and Acquisition (M&A)

Abstract M&A is a strategic concept of business growth through consolidation, gaining market access, increasing strategic positions, and increasing operational efficiency. To understand the dynamics of M&A, this paper looks at aspects such as targeted firm identification, evaluation, bidding for the target firm, and post-acquisition integration. All forms of M&A, including horizontal, [...] Read more.
M&A is a strategic concept of business growth through consolidation, gaining market access, increasing strategic positions, and increasing operational efficiency. To understand the dynamics of M&A, this paper looks at aspects such as targeted firm identification, evaluation, bidding for the target firm, and post-acquisition integration. All forms of M&A, including horizontal, vertical, conglomerate, and acquisitions, are discussed in terms of goals and values, including synergy, cost reduction, competitive advantages, and access to better technology. However, issues such as cultural assimilation, adhesion to regulations, and calculating an inaccurate value are also resolved. The paper then goes deeper to provide insight into how predictive analytics applies to M&A, using ML to improve decision-making with forecasting benefits. Including healthcare, education, and construction industries, the presented predictive models using regression analysis, neural networks, and ensemble techniques help to make decisions. Through time series and real-time data, PDA enables sound M&A strategies, effective risk management and smooth integration.
Figures
PreviousNext
Review Article
Open Access January 10, 2022

The Impact of Instant Credit Card Issuance and Personalized Financial Solutions on Enhancing Customer Experience in the Digital Banking Era

Abstract In today's fast-changing world, digital has become a way of life in every single field, and it is affecting all industries by providing multi-channel connectivity with people. In the banking industry, moving to the digital age allows for more improvements in customer-related operations and transaction-related operations within a day. These studies are from the perspective of customers. Customers [...] Read more.
In today's fast-changing world, digital has become a way of life in every single field, and it is affecting all industries by providing multi-channel connectivity with people. In the banking industry, moving to the digital age allows for more improvements in customer-related operations and transaction-related operations within a day. These studies are from the perspective of customers. Customers prefer the flexibility of using digital financial services. Banking clients are commonly given technology-related services, whether they are online or not. Now, banks are focused on providing instant credit card issuance and personalized financial solution services to their clients. They are responsible for managing mass affluent clients who conduct transactions approximately the same as mass retail clients. Providing personalized services on time to individual end users will significantly enhance customer value with the banks. Customers who use the bank digitally perform more operations than those who go to the branch. Thus, they become more valuable clients for the banks. This strategic approach to the digitization process takes place in this fast-changing environment, and the major steps of this journey will be explained in the next chapters [1].
Figures
PreviousNext
Review Article
Open Access November 19, 2022

Analyzing Behavioral Trends in Credit Card Fraud Patterns: Leveraging Federated Learning and Privacy-Preserving Artificial Intelligence Frameworks

Abstract We investigate and analyze the trends and behaviors in credit card fraud attacks and transactions. First, we perform logical analysis to find hidden patterns and trends, then we leverage game-theoretical models to illustrate the potential strategies of both the attackers and defenders. Next, we demonstrate the strength of industry-scale, privacy-preserving artificial intelligence solutions by [...] Read more.
We investigate and analyze the trends and behaviors in credit card fraud attacks and transactions. First, we perform logical analysis to find hidden patterns and trends, then we leverage game-theoretical models to illustrate the potential strategies of both the attackers and defenders. Next, we demonstrate the strength of industry-scale, privacy-preserving artificial intelligence solutions by presenting the results from our recent exploratory study in this respect. Furthermore, we describe the intrinsic challenges in the context of developing reliable predictive models using more stringent protocols, and hence the need for sector-specific benchmark datasets, and provide potential solutions based on state-of-the-art privacy models. Finally, we conclude the paper by discussing future research lines on the topic, and also the possible real-life implications. The paper underscores the challenges in creating robust AI models for the banking sector. The results also showcase that privacy-preserving AI models can potentially augment sharing capabilities while mitigating liability issues of public-private sector partnerships [1].
Figures
PreviousNext
Review Article
Open Access December 27, 2019

Revolutionizing Patient Care and Digital Infrastructure: Integrating Cloud Computing and Advanced Data Engineering for Industry Innovation

Abstract This work details how the integration of cloud computing and advanced data engineering can innovate and reshape patient care and digital infrastructure. In the healthcare sector, cloud services offer the necessary support to generate digitally-oriented services and service kits. These services can contain high levels of availability, low levels of latency, and on-demand scaling capabilities, while [...] Read more.
This work details how the integration of cloud computing and advanced data engineering can innovate and reshape patient care and digital infrastructure. In the healthcare sector, cloud services offer the necessary support to generate digitally-oriented services and service kits. These services can contain high levels of availability, low levels of latency, and on-demand scaling capabilities, while following the strictest data protection laws and regulations. On the other hand, these services can be combined with data engineering techniques to construct an ecosystem that enhances and adds an optimized data layer on any cloud environment. This ecosystem includes technologies to acquire, process, and manage healthcare data while respecting all regulatory obligations and institutions and can be part of a comprehensive digitalization strategy. The objective is to augment the healthcare services that the industry offers by leveraging healthcare data and AI technologies. Designed services, processes, and technologies can be described either as industry-agnostic services or healthcare-specific services that process and manage electronic healthcare records (EHR). Industry-agnostic services offer a set of tools and methodologies to conduct optimized data experiments. The goal is to exploit any variety, velocity, volume, and veracity of medical data. Healthcare-specific services offer a set of tools and methodologies to connect to any common EHR vendor in a privacy-preserving manner. Participating companies are thus able to hold, share, and make use of healthcare data in real-time. The proposed architecture can be transformative for the healthcare industry, opening up and facilitating experimentation on new and scalable service models. The transition to a more digital health approach would help overcome the limits encountered in traditional settings. Limitations in the availability of healthcare facilities and healthcare professionals have underpinned the increasing share of telemedicine in the care process. However, the record-keeping of the patients that undergo care outside of traditional healthcare facilities is often missing and can severely influence the continuity of treatment. Identifying new methods to implement disease prevention and early intervention processes is crucial to avoid more extensive treatment and to support those on multiple line therapies. For chronic patients, having a service available that monitors the state of health and intervenes when parameters go off the wanted range is crucial. However, the same patients are the most under the influence of the decision of care providers; a second opinion might be given remotely which the patient can access at any time on-demand. To address these different kinds of services, an ecosystem composed of a dictionary's worth data layer is outlined, able to live and operate seamlessly in any cloud environment. This future work's envisioned outcome is the rapid evolution and re-definition of the European healthcare landscape.
Figures
PreviousNext
Review Article
Open Access December 27, 2022

Optimizing Retirement Planning Strategies: A Comparative Analysis of Traditional, Roth, and Rollover IRAs in LongTerm Wealth Management

Abstract Retirement planning can be a complex endeavor. One consideration is whether or not to invest in an Individual Retirement Account (IRA). The present study compares the effect of several contributions to a traditional, Roth, and rollover IRA. The returns generated for each model are derived from the historic growth rates of the S&P 500 over 40 years. Results are presented in terms of employer [...] Read more.
Retirement planning can be a complex endeavor. One consideration is whether or not to invest in an Individual Retirement Account (IRA). The present study compares the effect of several contributions to a traditional, Roth, and rollover IRA. The returns generated for each model are derived from the historic growth rates of the S&P 500 over 40 years. Results are presented in terms of employer match, taxes due, and the number of shares utilized in the long-term investment strategy for each withdrawal method. Results show traditional IRA contributions or Roth IRA contributions are equally matched until employment termination. Taking an active role in managing the investment strategy, possibly by working with a financial representative, suggests a more favorable positioning upon employment termination [1]. Traditional and other pre-tax plans usually do not have an employer match, are usually paired with decreased taxes paid, and the number of shares available to the long-term investment strategy is somewhat reduced. In all cases, risk is increased. Rollover IRAs enjoy a match, lower taxes, and decrease the amount of calculated risk involved. A certified financial planner should be the resource of choice to determine how corporate retirement planning programs fit into the overall investment strategy.
Figures
PreviousNext
Review Article
Open Access December 27, 2021

Advancements in Smart Medical and Industrial Devices: Enhancing Efficiency and Connectivity with High-Speed Telecom Networks

Abstract Emerging smart medical instruments combined with advanced smart industrial equipment facilitate the collection of vast volumes of critical data. This data not only enables significantly more accurate and cost-effective diagnosis and maintenance but also enriches the datasets available for AI algorithms, leading to improved insights and outcomes. The integration of high-speed and ultra-reliable [...] Read more.
Emerging smart medical instruments combined with advanced smart industrial equipment facilitate the collection of vast volumes of critical data. This data not only enables significantly more accurate and cost-effective diagnosis and maintenance but also enriches the datasets available for AI algorithms, leading to improved insights and outcomes. The integration of high-speed and ultra-reliable telecommunications infrastructure is crucial, as it supports the cloud model. This model allows for off-device aggregation in the cloud, which effectively offloads infrastructure demands and provides an extended runway for future technological improvements before the deployment of the next generation of devices. However, in certain scenarios, latency and bandwidth limitations present significant challenges. These limitations require that a substantial amount of AI and machine learning processing is conducted directly on the transmitted data, which places rigorous demands on both the processing subsystems and the communications links themselves. The current project directly addresses the accelerator side of this multifaceted issue. It will carry out comprehensive end-to-end demonstrations leveraging pilot 5G networks and telemedicine facilities, collaborating closely with major industry participants to showcase the capabilities and potential of this innovative technology. This collaborative effort is essential to pushing the boundaries of what is possible in smart medical instruments and industrial applications [1].
Figures
PreviousNext
Review Article
Open Access December 27, 2021

Innovative Financial Technologies: Strengthening Compliance, Secure Transactions, and Intelligent Advisory Systems Through AI-Driven Automation and Scalable Data Architectures

Abstract 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 [...] Read more.
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].
Figures
PreviousNext
Review Article
Open Access December 27, 2020

Optimizing Unclaimed Property Management through Cloud-Enabled AI and Integrated IT Infrastructures

Abstract With unclaimed property assets reaching record levels, businesses have become, in some cases, overwhelmed and hamstrung by stagnant, unoptimized processes. That sentiment is compounded by ever-evolving regulatory changes, resulting in organizations struggling to hit compliance deadlines while delivering an optimal claimant experience. Often, early systems had periods of short-term success but are [...] Read more.
With unclaimed property assets reaching record levels, businesses have become, in some cases, overwhelmed and hamstrung by stagnant, unoptimized processes. That sentiment is compounded by ever-evolving regulatory changes, resulting in organizations struggling to hit compliance deadlines while delivering an optimal claimant experience. Often, early systems had periods of short-term success but are on the verge of obsolescence, resulting in stressed workflows and cumbersome integrations. Deploying an integrated IT infrastructure, supported by cloud-enabled AI, represents the quickest path to modernizing unclaimed property management. A fully integrated IT infrastructure is crucial to optimize the management of unclaimed property [1]. When lone solutions exist across an organization, companies miss out on automation opportunities generated through the interconnectedness of systems and data. AI presents organizations with the opportunity to traverse these gaps, enabling a vast library of applications to improve the perturbed workflows of unclaimed property teams. Automated data extraction, document comparison, fraudulent claim detection, and workflow completion analysis are just a few popular applications well suited for the unclaimed property space. In addition to the lagging technology currently deployed by many organizations, the unclaimed property landscape itself is evolving. Compliance issuance, asset availability, rates, the ability to collect fraudulently posted claims, and the claimant experience have all become hot-button items that are now front of mind for regulation agencies and businesses alike. Issuing duplication letters in a compliant manner, accommodating claimant inquiries regarding held assets, and managing, processing, and understanding the operational impact of rate changes are vexing problems many organizations now find themselves playing catch-up to address. The opportunity posed by cloud-enabled AI is furthered by economic, regulatory, and report cycle pressures on unclaimed property teams to do more with the same size or fewer resources. It’s now no longer simply a case of hitting the audit date deadline and checking off a box but an emerging priority for businesses at all sides of the market, from Fortune 500 to mid-market firms. In-house shared service teams are comfortable in areas of monitoring and curating business data; however, unclaimed property is an unknown territory with a learning curve, compliance gaps, and operational holes that, if ignored, stand to scale up exponentially. The combined fallout from regulatory changes and the recent pandemic have only made the situation riskier, with increased volatility in balancing time-sensitive tasks against stringent regulatory deadlines and growing claimant outreach.
Figures
PreviousNext
Review Article
Open Access December 27, 2022

Advance of AI-Based Predictive Models for Diagnosis of Alzheimer's Disease (AD) in Healthcare

Abstract The effects on the elderly are disproportionately Alzheimer’s disease (AD) is one of the most prevalent and chronic types of dementia. Alzheimer's disease (AD), a fatal illness that can harm brain structures and cells long before symptoms appear, is currently incurable and incurable. Using brain MRI pictures from a publicly accessible Kaggle dataset, this study suggests a prediction model based [...] Read more.
The effects on the elderly are disproportionately Alzheimer’s disease (AD) is one of the most prevalent and chronic types of dementia. Alzheimer's disease (AD), a fatal illness that can harm brain structures and cells long before symptoms appear, is currently incurable and incurable. Using brain MRI pictures from a publicly accessible Kaggle dataset, this study suggests a prediction model based on Convolutional Neural Networks (CNNs) to help with the early detection of Alzheimer's disease. Four levels of dementia have been applied to the 6,400 photos in the collection: not demented, slightly demented, moderately demented, and considerably mildly demented. Pixel normalization, class balancing utilizing data augmentation techniques, and picture scaling to 128×128 pixels were all part of a thorough workflow for data preparation. To improve the gathering of spatial dependence in volumetric MRI data, a 3D convolutional neural network (CNN) architecture was used. We used important performance measures including F1-score, recall, accuracy, precision, and log loss to gauge the model's effectiveness. A review of the available data indicates that the total F1-score, accuracy, recall, and precision were 99.0%, 99.0%, and 99.38%, respectively. The findings demonstrate the model's potential for practical use in early AD diagnosis and establish its robustness with the help of confusion matrix analysis and performance curves.
Figures
PreviousNext
Article
Open Access November 24, 2022

Bridging Traditional ETL Pipelines with AI Enhanced Data Workflows: Foundations of Intelligent Automation in Data Engineering

Abstract Machine Learning (ML) and Artificial Intelligence (AI) are having an increasingly transformative impact on all industries and are already used in many mission-critical use cases in production, bringing considerable value. Data engineering, which combines ETL pipelines with other workflows managing data and machine learning operations, is also significantly impacted. The Intelligent Data [...] Read more.
Machine Learning (ML) and Artificial Intelligence (AI) are having an increasingly transformative impact on all industries and are already used in many mission-critical use cases in production, bringing considerable value. Data engineering, which combines ETL pipelines with other workflows managing data and machine learning operations, is also significantly impacted. The Intelligent Data Engineering and Automation framework offers the groundwork for intelligent automation processes. However, ML/AI are not the only disruptive forces; new Big Data technologies inspired by Web2.0 companies are also reshaping the Internet. Companies having the largest Big Data footprints not only provide applications with a Big Data operational model but also source their competitive advantage from data in the form of AI services and, consequently, impact the cost/performance equilibrium of ETL pipelines. All these technologies and reasons help explain why the traditional ETL pipeline design should adapt to current and emerging technologies and may be enhanced through artificial intelligence.
Figures
PreviousNext
Article
Open Access December 27, 2021

Digital Transformation in Insurance: Migrating Enterprise Policy Systems to .NET Core

Abstract Migrating enterprise policy systems to .NET Core is a key objective of digital transformation in the Insurance IT ecosystem. This change directly addresses strategic drivers: enabling adoption of cloud-first development, resisting market pressure for more flexible and usable enterprise solutions, and preparing for changing demands from regulation and compliance. Phases of operational benefit [...] Read more.
Migrating enterprise policy systems to .NET Core is a key objective of digital transformation in the Insurance IT ecosystem. This change directly addresses strategic drivers: enabling adoption of cloud-first development, resisting market pressure for more flexible and usable enterprise solutions, and preparing for changing demands from regulation and compliance. Phases of operational benefit aligned with risk mitigation form the basis of the migration roadmap, with a strong focus on engaging all relevant stakeholders. Market pressure for a SEAMLESS user experience across ALL applications is a fundamental driver for Investment in digital transformation. Gaps remain in enterprise Operations, where Legislative and regulatory accountability Demand rigid and complex solutions that Liberty has not yet been able to provide. New risk-based capital requirements, Data-Sovereignty controls, Controls for sensitive Data in the Cloud, and new Audit requirements create a long list of challenges for the ecosystem that can no longer be Deferred. At the same time, Cross-organisational integration is becoming more important and integrating partners from the insurance supply-chain requires a much more flexible approach to development and Deployment. These factors combine to generate a credible case for accelerated digital investment with a focus on Migration to Cloud Platforms, with related Risk mitigation, Quality Improvements, and flexibility benefits that close Industry gaps.
Figures
PreviousNext
Review Article
Open Access December 27, 2021

Digital Signal Processing Challenges in Financial Messaging Systems: Case Studies in High-Volume SWIFT Flows

Abstract Digital signal processing played a central role in two practical studies addressing challenging problems related to high-volume SWIFT financial messaging flows conveyed by the interconnected banking network. Technical methods and results are summarized here for each study, with the links to fundamental concepts underlying the work shown in parentheses. The first addresses real-time fraud [...] Read more.
Digital signal processing played a central role in two practical studies addressing challenging problems related to high-volume SWIFT financial messaging flows conveyed by the interconnected banking network. Technical methods and results are summarized here for each study, with the links to fundamental concepts underlying the work shown in parentheses. The first addresses real-time fraud detection, integrating pattern recognition and anomaly scoring procedures into a latency conscious processing system. The second focuses on minimizing delay without degrading detection accuracy, balancing speed and fidelity in filter design and control. Together, they demonstrate the potential for applying a DSP perspective to broad classes of problems encountered in processing financial messaging data. The first study extends work on a signal representation of financial messaging data streams and the associated noise characteristics by developing a vocabulary that translates real-world fraud patterns into DSP operations. Examination of the resulting choice of signal features, combined with considerations of detection speed, form the basis for details about implementing the pattern-recognition and anomaly-scoring tasks within a streaming-processing architecture.
Figures
PreviousNext
Review Article
Open Access December 21, 2021

Optimizing Data Warehousing for Large Scale Policy Management Using Advanced ETL Frameworks

Abstract Data warehousing is a technique for collecting, managing, and presenting data to help people analyze and use that data effectively. It involves a large database designed to support management-level staff by providing all the relevant historical data for analysis. This chapter begins with a definition of data warehousing, followed by an overview of large-scale policy management to highlight the [...] Read more.
Data warehousing is a technique for collecting, managing, and presenting data to help people analyze and use that data effectively. It involves a large database designed to support management-level staff by providing all the relevant historical data for analysis. This chapter begins with a definition of data warehousing, followed by an overview of large-scale policy management to highlight the need for data warehousing. Next, an overview of an ETL framework is presented, along with a discussion of advanced ETL techniques. The chapter concludes with an outline of performance optimization techniques for data warehousing. Data warehousing is considered a key enabler for efficient reporting and analysis, with implementation choices ranging from cost-effective desktop systems to large-scale, mission-critical data marts and warehouses containing petabytes of data. Extract, transform, and load (ETL) systems remain one of the largest cost and effort areas within data warehouse development projects, requiring significant planning and resources to build, manage, and monitor the flow of data from source systems into the data warehouse. The technology and techniques used for ETL can greatly influence the success or failure of a data warehouse. Complex business requirements for data cleansing, loading, transformation, and integration have intensified, while operational plans for real-time and near-real-time reporting add additional challenges. Parallel loading mechanisms, incremental data loading, and runtime update and insert strategies not only improve ETL performance but also optimize data warehousing performance, particularly for large-scale policy management.
Figures
PreviousNext
Article
Open Access December 22, 2020

Cloud Migration Strategies for High-Volume Financial Messaging Systems

Abstract Key business objectives for digital infrastructure cloud adoption are often framed in terms of reducing cost, improving fault tolerance and resilience, simplifying scale, and enabling innovation. Given the critical nature of the financial sector, however, where timeliness and price can significantly determine an outcome, cloud migration in delivery environments demands greater throughput on the [...] Read more.
Key business objectives for digital infrastructure cloud adoption are often framed in terms of reducing cost, improving fault tolerance and resilience, simplifying scale, and enabling innovation. Given the critical nature of the financial sector, however, where timeliness and price can significantly determine an outcome, cloud migration in delivery environments demands greater throughput on the critical path and, in many enterprise-scale settings, forgoes hybrid complexity and multi-cloud risks. Nevertheless, slack in system designs does exist; financial institutions enable market functionality—trading, clearing/best execution—despite potentially being able to meet such sets with lower service levels than other verticals. A cloud multi-account structure for sensitive data, for example, naturally limits exposure when combined with observed risk. Fulfilling predictions of elasticity during periods of high demand usually requires support from a dedicated environment (or environments) located nearer to the operations. Components can consequently be allocated on a per-account basis or maintained as shared sink systems to which the dedicated streams write. The automation code can similarly be targeted for dedicated accounts, avoiding the resource constraints that beset such operations during industry events like emergency triage/contact desking.
Figures
PreviousNext
Review Article
Open Access December 18, 2021

A Comparative Study of Traditional Reporting Systems versus Real-Time Analytics Dashboards in Enterprise Operations

Abstract Seamless integration of information in organizations promotes not only the operational efficiency but also the quality of decisions made by managers. Real-time decision support systems enable organizations to evaluate organizational changes immediately and ideally gives a hint of problems before they even appear in the organization. Such real time systems are nowadays regarded as the front-line [...] Read more.
Seamless integration of information in organizations promotes not only the operational efficiency but also the quality of decisions made by managers. Real-time decision support systems enable organizations to evaluate organizational changes immediately and ideally gives a hint of problems before they even appear in the organization. Such real time systems are nowadays regarded as the front-line solutions for managing organizations effectively. The technological possibilities seem not to conquer management. For most companies the data is still dealt with traditional solutions, data is collected and reports are generated to evaluate the past occurrences which only gives information on what has happened in the organization. The problem with these non-real-time systems is the reflection of organizational condition very late. These are the common rear-mirror descriptions for what already has been. Managers are receiving information from their organizations too late and often too little to make optimal decisions. Is it not possible to manage operations in real-time? Is real-time decision support really needed? If so, why most organizations still rely on traditional reporting systems.
Figures
PreviousNext
Review Article
Open Access December 26, 2021

Architectural Frameworks for Large-Scale Electronic Health Record Data Platforms

Abstract Architectural frameworks for large-scale Electronic Health Record (EHR) data platforms are described. Existing EHR data platform architectures often leverage multiple cloud-based solutions blended with institutional infrastructures to manage and analyze clinical data at scale. Key design principles governing the scale of existing EHR data architecture include model design, governance structure, [...] Read more.
Architectural frameworks for large-scale Electronic Health Record (EHR) data platforms are described. Existing EHR data platform architectures often leverage multiple cloud-based solutions blended with institutional infrastructures to manage and analyze clinical data at scale. Key design principles governing the scale of existing EHR data architecture include model design, governance structure, data access management, data security/policy/protection, data-information-language-based standardization, and analytics tool alignment, among others. The rapidly evolving technology landscape and the unprecedented volume of incident and retrospective clinical data being collected and generated within healthcare organizations have led to the emergent need for a dedicated architectural framework to support large-scale computing in the health informatics domain. The application areas of large-scale computing in health informatics include real-time predictive analytics, risk stratification, patient cohort analytics, development of predictive models for specific institutions or population groups, and many more. The use of EHR data for a multitude of decision-making processes in both clinical and non-clinical settings has prompted the establishment of policies prescribing the conditions of access and use of EHR data for non-employed individuals in the organization. Consequently, the demand for accessing, using, and managing EHR data at scale has impacted the over.
Figures
PreviousNext
Review Article

Query parameters

Keyword:  Aging

View options

Citations of

Views of

Downloads of