Asian Journal of Advanced Research and Reports

Histochemistry and the Biological Roles of Glycosaminoglycans: Clinical Significance in Human Tissues

Josiah Hart, Chidi Onyenaucheya, Ikechukwu Ezeah, Ugochukwu Onwugbufor — Thu, 19 Jun 2025 00:00:00 +0000

Glycosaminoglycans (GAGs) are long, unbranched polysaccharides which are composed of repeating disaccharide units. They are negatively charged molecules which associate with proteins to yield proteoglycans. This study will examine the histochemistry, biological compositions and activities of GAGs in the human body. Histochemical identification methods of GAGs include Hale’s colloidal iron method, Periodic-acid-Schiff’s reaction (PAS), Alcian blue, and Metachromatic dyes. They exist naturally in different parts of the body, both in the free and protein-bound states. They play several important functions in human health, such as angiogenesis, inflammation, wound healing, and neurogenesis, a few mentioned. There are six different classes of GAGs found in various tissues of the body. The classes and quantities of GAGs found in the body depend on the tissue location and whether the tissue is in its normal or pathological state. It is commonly known that there is a change in the amount of GAGs in various tissues after injury. For example, it has been revealed that patients with radiculopathy showed significantly lower GAGs values in the nucleus pulposus of the intervertebral discs (2.82% ± 3.12% vs. 4.09% ± 2.25%, P = 0.017). Changes in the quantities of GAGs have also been observed during intrinsic ageing and photoaging of the human skin. GAGs act as potential biomarkers of certain pathologies, e.g. lung cancer. They are also believed to be crucial inhibitors of calcium oxalate crystal growth and crystallisation. GAGs can be used in treatment. For example, minimally invasive injectable GAG hydrogel has been introduced to reinstate the physiological properties of the spine. Physiologically based investigations show that the mediator proteins-GAGs interactions are majorly regulated by sulphation degree, sulphation pattern, and composition and structure of the carbohydrate. Studies on GAGs are evolving and more researches are required to exploit their characteristics, compositions, and importance.

Artificial Intelligence in Digital Learning Platforms in Education: Impact, Benefits, Limitations and Future Prospects

Vijay Chandrakant Patil — Fri, 20 Jun 2025 00:00:00 +0000

Education is experiencing a major shift driven by the integration of Artificial Intelligence (AI) and digital learning systems. AI is reshaping the way learners receive personalized instruction, how assessments are conducted, and how administrative tasks are managed. Meanwhile, digital platforms are making learning more accessible, flexible, and inclusive for diverse groups of students. This paper investigates the effects of AI and digital education tools on modern learning environments, outlining their key advantages, potential challenges, and future prospects. Grounded in current technological trends and scholarly research, this study presents a new outlook on how these innovations are transforming both teaching methods and educational experiences.

Efficacy of Cognitive Behavioral Therapy Compared to Other Evidence-Based Mental Health Interventions in Children and Adolescents with Symptoms of Childhood Adversities: A Scoping Review

Sat, 21 Jun 2025 00:00:00 +0000

Aims: To assess the relative efficacy of Cognitive Behavioral Therapy (CBT) compared to other proven therapies in improving mental health for children and adolescents affected by childhood trauma.

Methodology: As part of the scoping review, a structured literature search of PubMed, Medline (EBSCO), PsychAPA, CINAHL, and Google Scholar identified studies published from January 1, 2022, to December 31, 2024, on evidence-based mental health interventions for minors experiencing trauma. English-language studies on cognitive behavioral therapy (CBT) or related interventions, either standalone or integrated, were included. Duplicates were removed, and references were reviewed for completeness. Data extracted included author, year, intervention type, therapy level, age group, and summarized findings. Eligible publication types were research articles, peer-reviewed articles, and systematically curated reviews.

Results: The review synthesized findings from 26 studies published between 2022 and 2024, concentrating on therapeutic interventions for children and adolescents who have experienced adverse childhood experiences (ACEs). Trauma-focused cognitive behavioral therapy (TF-CBT) was identified as the most efficacious intervention, demonstrating robust effectiveness in alleviating symptoms of PTSD, anxiety, and depression across a range of clinical settings. The reviewed studies utilized diverse methodological approaches and predominantly focused on PTSD, anxiety, and depressive disorders, with a subset addressing substance use disorders, bereavement, and interpersonal functioning. Notably, the review highlighted significant gaps in the literature regarding the exploration of broader psychological outcomes and the efficacy of interventions beyond TF-CBT.

Conclusion: Trauma-focused cognitive behavioral therapy (TF-CBT) stands out as the most effective treatment for enhancing mental health in children and adolescents experiencing trauma-related symptoms. Modifications of CBT and combined approaches, such as psychoeducation and family-oriented strategies, also play a significant role in diminishing post-traumatic stress symptoms and boosting resilience.

A Visual “STAGED” Nomogram to Predict the Risk of Full Stomach in Adult Outpatients Undergoing Elective Sedated Upper Endoscopy

Sat, 07 Jun 2025 00:00:00 +0000

Background: A full stomach during elective sedated upper endoscopy (UE) is highly associated with aspiration. Aspiration is related to increased morbidity and mortality. We aimed to develop a nomogram model to predict the risk of having a full stomach in adult outpatients undergoing elective sedated UE.

Methods: Data of 1171 adult outpatients undergoing elective sedated UE were collected retrospectively between July 2021 and February 2022. Univariable analysis, multivariable logistic regression, and Boruta were used to identify independent risk factors associated with full stomach. Using the identified risk factors, a nomogram was developed. The area under the receiver operating characteristic (AUROC), decision curve analysis (DCA), and calibration curve (CC) were used to evaluate the model’s performance.

Results: After exclusion, 990 patients were enrolled in this study. In the training set, 305 patients (38.5%) had a full stomach, and 71 patients (35.9%) had a full stomach for the testing set. The AUROC (95% Cl) was 0.819 (0.788-0.85) and 0.823(0.759-0.887) for the training and testing set, respectively. The variables incorporated in the development of our STAGED model were Sex = female (OR: 2.147), fasting Time (OR: 0.839), Age (OR: 0.971), GERD (OR: 15.61), diabEtes (OR: 8.614) and Diet (OR: 3.691). DCA and CIC analyses showed that our model had a significant net benefit compared to the "treat all or "treat none" strategies and had high predictive value, making it clinically useful.

Conclusion: The “STAGED” nomogram model was successfully developed and made easily accessible online via a visual web-based calculator.

Summary of the patient’s inclusion along with the study design, the methodology used for model development, the implementation of the model, and model performance.

Factors Influencing Women's Attitudes towards Family Planning: An Explorative Study in Eku Community, Delta State, Nigeria

Mon, 09 Jun 2025 00:00:00 +0000

The awareness of family planning is a major subject in the present-day health education advocacy with respect to child and maternal health considerations. Specifically, the aim of this study was to unravel the educational influence, religion, age, health, culture of women, including income as an important consideration in family planning. This research used a descriptive cross-sectional study and was carried out in Eku Community in Ethiope East Local Government of Delta State with the aid of a convenient sampling technique. A structured questionnaire was used to collected data from 100 respondents made up of women of childbearing age from the main street and quarters of the Eku community in Delta State, Nigeria. The percentage system was used to determine the outcome of the data collected to map out considerations of various societal values, such as religion, finance, education, and cultural influence, as a determinant of couples' measures of involvement in family planning. The results showed that 42% of the respondents strongly agreed that the educational status of women of childbearing age influences the choice of family planning. Moreover, 20% of the respondents highly agreed that cultural and religious beliefs support family planning. In terms of socio-economic status and knowledge of family planning, 42% of the respondents strongly agreed that socio-economic status influences the attitude of women toward family planning. Lastly, 27% of the respondents strongly agreed that Healthcare providers' attitude influences family planning services. Incentive and educational awareness program was a key determinant recommended through various media channels to childbearing individuals to adopt family planning. The study showed that women in the Eku community in Delta State, Nigeria, still see family planning as a means of impeding a natural process that could have a major negative impact on reproductive health.

Smart Irrigation in Nigeria: A Panacea to Curbing Hunger and Food Insecurity

Efiong Antigha Archibong, Armstrong Oreh Njok, Jonathan Eyire Osang — Tue, 10 Jun 2025 00:00:00 +0000

Nigeria has enormous agricultural potential, covering an area of over 923,768 square kilometres. However, despite Nigeria's economy heavily relying on agriculture and petroleum, poverty and hunger still exist. The primary causes of famine and food shortage in Nigeria are insecurity and conflict, poor farming methods, erratic weather patterns, insufficient water management plans, inadequate infrastructure, inadequate government regulations and low agricultural investment. Other concerns include inequality and poverty, food waste and losses after harvest. This project proposes designing an Internet of Things (IoT)-enabled irrigation system that comprises a lithium battery, ESP8266 microcontroller, solar panel, capacitive moisture sensor, and the Blynk smartphone app. The solar panel charges the lithium battery that powers the system, and the charge controller regulates charging and prevents overcharging and deep discharge. The ESP8266 microcontroller evaluates the real-time data gathered from the soil by the moisture sensor to determine whether to activate the DC pump to irrigate the area. The device efficiently irrigates crops based on monitored moisture levels, saving water and increasing agricultural productivity. The Internet of Things (IoT) combines smart sensors, networked devices and cloud computing to continuously gather, process and analyze data, allowing for automation and real-time monitoring, removing human intervention and enabling remote system control, predictive maintenance and instantaneous decision-making. Industry sectors such as agriculture can benefit from IoT's automated responses and data-driven insights to improve safety, increase productivity and optimize operations.

Leveraging Machine Learning and Data Analytics to Predict Corporate Financial Distress and Bankruptcy in the United States

Wed, 11 Jun 2025 00:00:00 +0000

Predictions about a company's financial distress and potential bankruptcy are important for a business, investor, or even a regulator. Imagine scanning the horizon for financial issues and being able to nip them in the bud. This study looks into the possibilities that lie within machine learning and data analysis for predicting corporate bankruptcy in the United States. We build predictive models that depend on huge streams of data alongside elaborate algorithms to accurately assess the scope of financial turmoil a company may be facing. The research highlights the most effective data analytic techniques alongside financial indicators that are accurate predictors of sound decision making for businesses and investors, thus revealing the level of ruin they may face. The discovery equips stakeholders with the right guidance in need to deal with dangers and stumbles within the financial world, avoiding losses. Data-driven analytics can be leveraged to create a better business landscape that isn’t as brittle and can withstand future challenges. The justification behind this study lies in the growing scope of corporate failure and the necessity of more rapid, more precise, and more interpretable means to predict financial distress. Given past attempts with common statistical techniques, there is still a gap in research using and comparing state-of-the-art machine learning algorithms on an extensive, up-to-date dataset. To bridge this lacuna, the research employs comparative Random Forest, XGBoost, Support Vector Machines, and Neural Networks analysis of financial data between 2010 and 2024 for 1,000 U.S. companies. Employing supervised learning, the dataset was divided into training, validation, and test periods. The findings indicated the highest predictive accuracy being that of XGBoost at 93.2%, followed by Neural Networks (92.6%), followed by Random Forest (91.4%), and SVM (88.7%). These results demonstrate the superior performance of ensemble-based models for early warning signalling of financial distress, thereby achieving the purpose of this study to enhance financial decision-making via early, precise prediction.

A Study of In vivo Biochemical Estimation of Ethanolic Fruit Extract of Physalis angulate

Fri, 13 Jun 2025 00:00:00 +0000

The fruits of Physalis angulata are recommended locally for treating infection, infertility, inflammation, postpartum infection, skin diseases. Some medicinal plants may contain toxins that affect the organs in the body, especially the liver and kidneys. In order to validate the use of Physalis angulata fruits in traditional medicine, it is important to evaluate its effect on liver and kidney functions in experimental animals.

Materials and Methods: 18 adults female Wistar rats weighing 120 ± 20 g were grouped into 3 groups, with each group consisting of 6 rats. The control group was on a normal diet and distilled water while the other groups received 500 mg/bwt, and 1500 mg/ body wt of ethanolic extract of Physalisangulata for 28 days respectively. Animals were acclimatized for 2 weeks before commencement of the experiment. Blood samples were analyzed for alanine aminotransferase, aspartate aminotransferase and alkaline phosphatase.

Results: The concentration of AST in the control was significantly (p<0.05) lower than the values in the treatment groups. Concentrations of ALT and ALP concentrations were not significantly different among treatment groups. Serum electrolytes (potassium, sodium, and chloride ions) were not statistically significant. Significantly (p<0.05) higher concentrations of creatinine were observed in Physalis angulate 1500mg/kg group compared to the control.

Conclusion:Physalis angulate fruit extracts is safe and non-toxic to the liver and kidney.

Students’ Attitudes and Academic Achievement in Mathematics in the Modern World (MMW): A Correlational Analysis

Jabel Phillip L. Irinco — Fri, 13 Jun 2025 00:00:00 +0000

Aims: This study aims to examine the relationship between students’ attitudes toward mathematics and their academic achievement in Mathematics in the Modern World (MMW) at the University of Eastern Philippines. It seeks to determine whether a positive attitude significantly influences students' performance in MMW.

Study Design: A descriptive-correlational research design was employed, with the descriptive method used to characterize students’ attitudes toward mathematics and their achievement, while the correlational approach assessed the relationship between these two variables.

Place and Duration of Study: The study was conducted at the University of Eastern Philippines, during the second semester of the 2024–2025 academic year.

Methodology: The study utilized proportional sampling, involving 310 students enrolled in MMW. A structured questionnaire was used for data collection, consisting of two sections: a checklist on students’ attitudes toward mathematics, adapted from Bangalan and Hipona, and a 40-item achievement test, covering the four mandated topics in MMW, adapted from Garcia. Statistical analyses, including the Pearson correlation, were conducted to determine the significance of the relationship between attitudes and achievement.

Results: Findings revealed that students generally hold a positive attitude toward mathematics, with an overall mean attitude score of 3.524 (SD = 0.4808), interpreted as positive. The students' achievement in MMW was categorized as satisfactory, with a mean score of 19.00 (SD = 7.638). A significant positive correlation (r = .386, p < .01) was found between students’ attitudes and their academic achievement, indicating that students with more favorable perceptions of mathematics tend to achieve higher scores in MMW.

Conclusion: The study underscores the importance of fostering positive attitudes toward mathematics to enhance academic achievement. It recommends interactive teaching methodologies, confidence-building initiatives, curriculum integration of practical applications, and individualized learning support to improve student engagement and mathematical proficiency. These findings reinforce the need for strategic educational interventions to optimize learning outcomes in mathematics.

Exploring the Perspectives of Health and Social Care Workers on the Influence of CQC-Regulated Services on Providers in the Health and Social Care Sector

Igwe, Chijioke Paul, Igwe, Ejikeme Peter, Ephraim, Fimbaya Chua — Fri, 13 Jun 2025 00:00:00 +0000

Within the United Kingdom, particularly England, this work is an exploration of the health and social care employees’ perspective on the impacts of Care Quality Commission (CQC)-regulated services. The CQC plays a paramount role in sustaining, maintaining, and improving the quality of service delivery, being the primary regulator. Nonetheless, these roles have practical implications for health and social care frontliners. The CQC regulations influence the quality of service delivery in England. Based on the foregoing, the present study examines the impact assessment of CQC-regulated activities through the health and social care personnel perspective, covering areas like roles, practices, outcomes, and quality of care. This study uses a quantitative research method as well as a survey method to gather data from various healthcare providers by administering a well-structured Google Form (survey questionnaire) to about 250 persons. About 143 participating individuals within the health and social care sector responded. Data was analysed through the lens of descriptive statistics and correlation analysis. Findings reveal a structural disconnect between the approach to inspection and the health and social care service realities. It is, however, compounded by genuine concerns about accuracy, fairness, frontline engagement, and lack of flexibility in implementation—with 64.3% suggesting that CQC is a reflection of true standards; other results, as also shown in RQ2, indicate that CQC ratings are also influenced by internal strategies and external perceptions. 58.1% and 49% viewed CQC as impactful; meanwhile, 12.6% and 11.9% reflect the gaps in capturing staff needs and the daily operational struggles. Critical gaps in regulatory methodologies and potentially biased approaches are voiced out in the analysis and pinpointed by 10.5% and 12.6% of respondents, respectively. The findings further highlighted the challenges and the positive aspects of CQC regulation. Moreover, the research provides substantial input to the ongoing discussion in both academic and health settings regarding regulation in care settings. It also offers service enhancement and insight to regulatory bodies, policymakers, and health providers.

Reducing Anxiety in Left-behind Children: A Study on the Effectiveness of Video Games as a Therapeutic Intervention" in Rural Province of China

Sat, 14 Jun 2025 00:00:00 +0000

Purpose: The study aimed to find out the effect of video games on the level anxiety of school-age children who are left behind by their parents in the rural province of China.

Background: The school-age children who have been left behind are facing a significant increase in vulnerability to anxiety symptoms. The commercial, 3d Video Games have shown potential applications in preventive and therapeutic medicine. The researcher intended to determine the potential benefits of video on the level of anxiety of school-age LBC in the rural province of China.

Methods: A Quantitative research approach, particularly quasi pre-test and post-test design used to carry out the study. Fifty-eight (58) school-age children were selected through purposive sampling and randomly assigned the twenty-four (24) participants to experimental, twenty-four (24) participants to comparison groups, and ten (10) participants to pilot study thru the fishbowl technique. The Beck Anxiety Inventory (BAI) was used to assess the levels of anxiety of the two groups before and after treatment.

The MiNi World 3D video games administered to the experimental group for 20 minutes daily in 14 days as an intervention. Whereas the comparison group played the school play activities of grabbing stones and kicking sandboxes for 20 minutes in 14 days as a treatment. Data subjected to the statistical treatment of frequency, percentage, mean score, SD, Mann-Whitney U test, and Wilcoxon signed rank test.

Results: All participants or 100% (24=n) of the experimental group were at a low level of the anxiety after treatment. There is no significant difference in the level of anxiety of the comparison group and experiment group in the pretest with a p-value of 0.060. There is a significant difference in the level of anxiety of pretest and post-test of the experimental group with a p-value of <0.0005) after 14 days of the intervention of video games.

Conclusions: The video games of MiNi World (3D Video Games) have a positive effect on the levels of anxiety among school-age children who left behind by their parents in rural province China.

Bridging Social and Structural Factors in Addressing Firearm Mortality: A PMESII-informed Approach

Michael Olayinka Gbadebo, Oluwafemi Adeola Gbadebo — Tue, 17 Jun 2025 00:00:00 +0000

This study investigates the social and infrastructural determinants of firearm violence in the United States through a PMESII-informed analytical framework. Drawing from open-access national datasets, including CDC WISQARS, the American Community Survey, County Health Rankings & Roadmaps, and the CDC/ATSDR Social Vulnerability Index, the research analyzes data from 2,914 U.S. counties. Employing multivariate linear regression, principal component analysis with clustering, and interaction term modeling, the study evaluates how systemic variables contribute to firearm homicide rates. The findings highlight that higher educational attainment (β = -0.176, p < .001) and stricter gun laws (β = -0.045, p < .001) are the most significant protective factors. Furthermore, infrastructural strength measured through healthcare access, housing quality, digital connectivity, and civic support shows a strong inverse correlation with firearm mortality. Notably, a compounded risk effect (β = 3.303, p < .001) emerges in counties with both high social vulnerability and weak infrastructure, underscoring the need for integrated interventions. The study advocates for targeted policy reforms that strengthen educational equity, enforce robust firearm regulations, and expand infrastructure in high-risk areas. These findings emphasize the critical importance of multi-dimensional, data-driven strategies in mitigating gun violence and offer an actionable framework for researchers, policymakers, and urban planners addressing public safety through systemic resilience.

Evaluation of Public Service Quality Using the SERVQUAL Model: Case Study of Bank Mandiri KCP Paguyaman Gorontalo Regency, Indonesia

Nurhadi Abbas, Irawaty Igirisa, Rusli Isa — Wed, 18 Jun 2025 00:00:00 +0000

This study aims to evaluate the quality of public services at Bank Mandiri KCP Paguyaman in Gorontalo Regency using the SERVQUAL approach, which covers five main dimensions: tangibles, empathy, responsiveness, reliability, and assurance. This study is motivated by the success of bank branches in rural areas in building customer loyalty despite facing infrastructure and human resources limitations. This study employs a descriptive qualitative design with a case study approach. Informants were selected purposively based on their direct experience with bank services, and data were collected through in-depth interviews, participatory observation, and documentation, then analysed thematically using the Miles and Huberman model. The results indicate that all SERVQUAL dimensions have been implemented fairly well, but there is still room for improvement. The tangible dimension indicates adequate physical facilities but is not optimal for comfort. Empathy is reflected in positive personal interactions but is not yet fully inclusive for vulnerable groups. Responsiveness is assessed as quick under normal conditions but unprepared to handle complex situations. Reliability shows consistency in basic services, but there is inconsistency in product information. Assurance guarantees transaction security, though interpersonal communication aspects must be strengthened. In conclusion, the quality of public service at Bank Mandiri KCP Paguyaman has reached a good level but is not yet ideal. Strategic recommendations include empathy-based staff training and educational communication, improvements to main service facilities, and strengthening the digital system for real-time complaint handling to achieve adaptive, trustworthy, and socially just public service.

Perception of Students on Selective Factors Affecting Their Academic Performance in School of Medical Laboratory Sciences, Usmanu Danfodiyo University, Sokoto, Nigeria

Wed, 18 Jun 2025 00:00:00 +0000

The measure of a student’s ability to accomplish his or her academic tasks or studies successfully is referred to as academic performance. It has been observed that often the academic performance of students fall below expectation due to one or more factors militating against their educational objectives. The specific objective of the study was to determine the perception of the respondents on demographic, socio-economic status, environmental and psychological factors affecting the academic performance of final year students of School of Medical Laboratory Sciences, Usmanu Danfodiyo University, Sokoto. The research utilized a descriptive cross-sectional design; thus, Taro Yamane’s formula was adopted to generate 120 students as the sample size, which were randomly selected from the study population of 172 students. A validated and reliable self-structured questionnaire was developed and utilized for data collection. The students’ cumulative grade point average (CGPA) was used as a measure of academic performance. The data were analyzed quantitatively and the results indicated an overall good academic performance. No statistically significant difference was found between demographic factors and academic performance. The respondents perceived parental income, parent education level, family size, parent occupation, school location, school basic amenities, sleeping, stress and motivation as factors which more significantly affect their academic performance (p = 0.000). Despite the very good academic performance displayed by the respondents, this could be further improved by taking steps to address all the factors perceived by the students as hinderance to their academic performance, such as the socio-economic status of parents, school basic amenities and stress.

Analysis on Determinants of Loan Repayment among Rice Farmers in North-West Agricultural Zone of Benue State, Nigeria

Burbwa Philip Aondover, Ameh David Enemune, Ogebe Francis Ozoko — Thu, 19 Jun 2025 00:00:00 +0000

In developing countries, the role of agricultural credit is closely related to providing the needed resources which farmers cannot source from their own available capital. Little or none of these studies examined the influence of socio-economic factors on loan repayment ability among rice farmers in the North-West agricultural zone of Benue State, Nigeria. This study is therefore intended to fill the existing gaps through investigating factors affecting loan repayment of rice farmers in the study area, as well as ascertaining which of these factors significantly influence loan repayment in the study area. Several reasons have been advanced for low repayment ability among farmers in less developed countries (LDC). Reasons have ranged from deliberate refusal to pay by some farmers to non-repayment of loans arising from loss of income due to the devastating effects of crop failure and ill health. This study investigated the determinants of loan repayment by rice farmers in Benue State, Nigeria. The study focused on analysing socio-economic characteristics, loan performance, credit adequacy and the key factors affecting repayment: describe the socio-economic characteristics of respondents, assess the factors that affect loan repayment among rice farmers, examine the level of loan repayment performance and ascertain the credit adequacy of the respondents in the study area. The study was conducted in the North-West agricultural zone of Benue State, Nigeria. Primary data were collected with the aid of a well-structured questionnaire from 424 randomly selected rice farmers. Data were analysed using descriptive statistics, credit adequacy ratio (CAR), loan repayment index (LRI) and Ordinary Least Squares (OLS). Data covering socio-economic characteristics such as age, farm size, farming experience with credit use, amount of loan obtained, amount of loan repaid, income earned, etc., were elicited from respondents through the use of a well-structured questionnaire. Results showed that males were dominant (75.47%) in rice production, and the majority (42.45%) were between 41-50 years, with most (48.35%) farmers accessing loans exclusively from informal sources. Also, the result found that the majority (76.65%) of the sampled rice farmers indulged in loan diversion to family uses. Loan performance indices estimated showed that only 25.94% of the borrowed amount was repaid as due. This repayment rate is significantly below optimal levels, raising concerns about the effectiveness of the existing loan mechanism. This situation indicated a low repayment performance of the farmers in the study area. Empirical results from regression analysis showed that the sex of the respondents, loan from other sources, collateral value, amount of money borrowed and total income of the farmers were the significant factors that influenced loan repayment. It was concluded that low repayment limited effective loan administration in the study area. It was recommended that regular monitoring by lenders should be heightened to ensure prompt repayment.

Assessment of Flood Awareness and Impact in Selected Southern States in Nigeria

Thu, 19 Jun 2025 00:00:00 +0000

Background: Floods remain one of the most destructive climate-induced hazards in Southern Nigeria, causing extensive damage to lives, properties, and infrastructure.

Research Aim: This study investigates the level of flood awareness and its impact in three flood-prone southern states—Akwa Ibom, Rivers, and Lagos.

Methodology: Using a positivist, cross-sectional survey approach, data were collected from 118 respondents through an online questionnaire and analyzed with SPSS 22 using descriptive and Pearson correlation tools.

Results: Results revealed that 59.3% of respondents reported being aware of flood causes, while 47.5% had personally experienced flooding. Despite this awareness, only 13.6% followed weather alerts regularly, and just 6.8% had received any flood response training. Critically, 79.7% received no warning before flood events. The impact was significant—66.1% experienced property damage, 32.2% reported cholera, and 59.3% received no post-flood assistance. Statistically, flood preparedness negatively correlated with perceived severity (r = -0.273, p < 0.01) and recovery duration (r = -0.607, p < 0.01). Conversely, training positively influenced awareness and reduced flood severity (r = -0.553, p < 0.01). There is a moderately strong level of flood awareness in Southern Nigeria; Flood was found to impact negatively on properties i.e. buildings and human health; The severity of flooding was moderately rated; Participants’ perception of the state of being sufficiently ready for handling flood events negatively correlates with various factors such as the intensity of flood, knowing people who flood affected, previous warnings and duration of recovery from flood events. Findings underscore the urgent need for localized flood risk communication, structural preparedness, and early warning systems. The study recommends a three-tier response involving education, community planning, and policy enforcement to improve resilience.

Towards a Greener Future: Addressing Infrastructural Challenges in E-waste Management

Manjot Kaur Bhatia, Chetna Laroiya — Sat, 14 Jun 2025 00:00:00 +0000

E-Waste Management system (Scrapmanager) represents a crucial step toward addressing the escalating global crisis of electronic waste (e-waste). As technology advances at an unprecedented pace, the rapid obsolescence of electronic devices poses significant environmental and health risks. We are facing issues in e-waste management at three levels. Firts this sector is diminated by informal infrastructure like kbarialas. Second there is not enough authorized recycling facilities in proportion with the amount of e-waste generated. Latly people are not much aware about the e-waste recycling recycling. Also the policies about the e-waste management are not strategically placed. Our proposed model the scrapmanager is a step to create a sustainable ecosystem by bridging the gap between responsible disposal and environmental preservation. Key features of this system are clean UI design which makes it accessible to all, connects users with certified e-waste collectors across cities. Our proposed system (Scrapmanager) educates users about impact of e-waste through informative articles, infographics, and FAQs. This system contributes to economic growth and sustainable development of the earth. Aim of this system is to protect the environment from the hazardous element used in electronic devices. This system is a platform to connect e-waste sources with the right recycling facilities. Scrapmanager isn’t just a system, it’s a promise—to our planet, future generations, and collective responsibility.

Clinical Presentation of IgG4-Related Disease: A Rare Case Report and Literature Review

Mon, 16 Jun 2025 00:00:00 +0000

IgG4-related disease (IgG4-RD) is a new growing entity of immune-mediated origin, characterized by a mass-forming lesion, the infiltration of IgG4-positive plasma cells and occasionally elevated serum IgG4. It is considered to be both a systemic inflammation and sclerosing disease.

The clinical presentation varies widely, as one or more organs may be affected, either synchronously or metachronously.

Glucocorticoid therapy is the most effective traitement but may be followed by relapses.

It is important to highlight this case and those of the literature, as many gastro-enterologist may have never seen a case of IgG4-RD.

This manuscript provides a better understanding of certain aspects of IgG4-related disease. It will be useful for researchers with a passion for immunology. New research projects may arise from this manuscript such as estimating the incidence and prevalence of IgG4-RD, the raisons that men are more prone to the classic form of IgG4-RD than women in different parts of the world and also why the elderly are often the target.

Through the column of this article, we describe 24-years-old women to whom the clinical presentation, radiological and biological findings were that of IgG4-RD presented as acute hepatitis.

Securing AI-Powered Healthcare Decision Support Systems: A Comprehensive Review of Attack Vectors and Defensive Strategies

Fri, 06 Jun 2025 00:00:00 +0000

Background: Artificial intelligence (AI) is emerging as a transformative technology in healthcare, enabling the development of AI-powered clinical decision support systems (CDSS). These systems leverage large-scale data and advanced computational algorithms to assist in diagnosis, treatment planning, and patient management. However, the integration of AI into clinical practice faces critical challenges, particularly related to cybersecurity and system vulnerability.

Objectives: This review aims to evaluate the security vulnerabilities of AI-powered healthcare decision support systems by identifying common attack vectors and examining current defensive strategies. It also explores the implications of these vulnerabilities for patient safety, data integrity, and healthcare delivery.

Methods: A comprehensive literature review was conducted using databases such as PubMed, Scopus, IEEE Xplore, Web of Science, SpringerLink, and Google Scholar. Articles published between 2015 and 2025 were screened using PRISMA guidelines. Keywords included "AI in healthcare", "decision support systems", "cybersecurity", "adversarial attacks", and "defensive strategies".

Results: Out of 1,255 initially identified articles, 200 were included after applying inclusion and exclusion criteria. The findings reveal that AI-powered systems are susceptible to various threats, including adversarial inputs, model inversion, data poisoning, and privacy breaches. Several defensive mechanisms, such as secure model training, encryption, and adversarial detection frameworks, have been proposed and partially implemented.

Conclusions: AI-powered decision support systems hold great promise in enhancing healthcare delivery. However, unresolved security vulnerabilities pose significant risks. Addressing these concerns requires multidisciplinary collaboration among AI developers, healthcare professionals, and cybersecurity experts. Future research and funding should prioritize secure deployment, ethical governance, and regulatory compliance to ensure safe and effective integration into clinical practice.

Dietary and Nutritional Influence on Mental Health Outcomes: A Review

Mon, 09 Jun 2025 00:00:00 +0000

The present review aims to evaluate and synthesize previous research on the impact of food and dietary patterns on mental health. Over the past decade, dietary choices have been implicated in the onset, the progression, and the management of mental disorders. In this review, we analyze evidence on the association between nutritional components and mental health outcomes, such as depression, anxiety, and cognitive functioning from randomized controlled trials (RCTs), cohort studies, and meta-analyses published over the last decade.

The purpose of this review is to highlight the significant impact of diet on mental health and to emphasize the potential of diet interventions to contribute to an integrated approach to the treatment of mental illness. The current evidence suggests that improving diet quality should be a key component in the prevention and management of mental health disorders. Public health initiatives and clinical practices should incorporate dietary counseling to promote mental well-being among the general population.

A Systematic Review on Prediction Models for Postoperative Delirium in Non-cardiac Surgery Patients

Sat, 14 Jun 2025 00:00:00 +0000

Introduction: Numerous risk prediction models (RPMs) for postoperative delirium (POD) following non-cardiac surgery have been developed and validated recently. However, the robustness and applicability of these models require further investigation.

Methods: Using PRISMA-2020 guidelines and PROBAST checklist, studies on POD RPMs in non-cardiac surgery patients were searched from PubMed and Google Scholar from January 2021 to December 2023. Inclusion criteria were: (a) adults (aged ≥18 years), (b) non-cardiac surgery patients, (c) development and/or validation of delirium RPMs, and (d) full papers in English. Exclusion criteria were studies not meeting these inclusion parameters.

Results: Twelve studies included non-cardiac surgery patients with varying rates of POD (3.22% to 38.30%). The Confusion Assessment Method (CAM) was commonly used for assessing POD risk, with logistic regression being the most employed prediction model. Predictors often found were age, intraoperative blood loss, albumin levels, anesthesia duration, and ICU stays. Internal validation was done in 75% of all the models included. The area under the curve (AUC) ranged from 0.68 to 0.94 for internal validation and from 0.630 to 0.880 for external validation sets. Additionally, most of the models showed a minimal risk of bias (83.3%) and were considered to have a low concern regarding their applicability (75%).

Conclusion: Based on this review, current RPMs for POD among non-cardiac surgery patients exhibit high accuracy, low risk of bias, and minimal concerns regarding their applicability. We recommend that future research prioritize the external validation of existing models to improve their clinical utility.