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Multifunctional Characterization of Fucoidan: Structural Insights and Efficient Removal of Toxic Metal Ions
Get PDFIn this study, commercial fucoidan was subjected to comprehensive physicochemical and structural characterization to evaluate its potential for removing heavy metal ions from aqueous media. Fourier transform infrared spectroscopy (FTIR) and proton nuclear magnetic resonance (1H NMR) confirmed the presence of sulfated heterofucans, with distinct signals corresponding to carboxyl, sulfate, and sugar ring functionalities. Thermogravimetric analysis (TGA) revealed notable thermal stability, with major degradation occurring above 240 °C. Interaction mechanisms have been proposed on the basis of functional groups, particularly sulfates and carboxylates. Finally, the efficacy of fucoidan for Ni(II), Pb(II), and Cu(II) removal was validated via inductively coupled plasma (ICP) spectroscopy, which revealed removal rates of up to 99.89% for Cu and 99.84% for Pb. These findings highlight the dual role of fucoidan as both a bioactive polymer and a promising biopolymer for wastewater remediation
Psychological Implications of Recreational Drug use among Students with Intellectual Disabilities in Nigeria
Get PDFAim: The psychological consequences of drug use in individuals with intellectual disabilities can include worsened cognitive deficits, anxiety, aggression, depression, and impaired academic functioning. These effects are often underrecognized due to stigma or limited school support systems. Examine the psychological implications and patterns of recreational drug use among students with intellectual disabilities in Cross River and Akwa Ibom States, Nigeria. Five study objectives were stated to guide the research. Five research questions were formulated, and three hypotheses were stated. Literature was reviewed based on the variables under study.
Method: The study adopted a descriptive survey research design. The study was conducted in Cross River and Akwa Ibom States, located in Nigeria's South-South geopolitical zone. The population comprises 1067 students with intellectual disabilities enrolled in public and private special education schools and inclusive education programs. Purposive and stratified random sampling techniques were used. A total sample of 200 respondents were selected for the study. Data was collected using a structured questionnaire. Experts validated the instruments, which were tested for reliability using the Cronbach Alpha reliability method. The test result revealed a reliability index of 0.80. Results of the research questions were presented using frequency counts, percentages, mean and standard deviation. Multiple linear regression was used to analyze the hypothesis.
Results: The results revealed that substances such as marijuana, codeine, and tramadol were the most commonly reported. There is a significant relationship between recreational drug use and the psychological well-being of students with intellectual disabilities. Students with intellectual disabilities in Cross River State experience significantly higher psychological implications related to drug use compared to their peers in Akwa Ibom State. Peer influence and neighborhood environment are significant predictors of recreational drug use among students with intellectual disabilities, while family background is not.
Conclusion: The findings of this study highlight a disturbing reality: students with intellectual disabilities are at substantial risk of psychological harm due to recreational drug use.
Recommendation: Schools and disability support centers should implement peer-mentoring programs, social skills training, and anti-drug clubs that empower students to resist negative peer pressure
The Effect of Interpersonal Communication on Prevention Behavior of Early Hypertension among Student at SMAN 6 and SMAN 19 Bone
Get PDFBackground: Hypertension is a health issue that is not only experienced by adults but can also develop during adolescence. This condition often continues into adulthood, with essential hypertension in adults frequently stemming from habits and risk factors that emerge during adolescence. Centers for Disease Control and Prevention (CDC) 2023 revealed that one in every 25 adolescents aged between 12 to 19 years old is diagnosed with hypertension. Among adolescents diagnosed with hypertension, 10% were found to have a prior history of prehypertension.
Objective: This study aims to determine the effect of interpersonal communication on early hypertension prevention behavior among students of SMAN 6 and SMAN 19 Bone.
Materials and Methods: The research design used was Quasi Experiment with pretest-posttest control group design. 110 grade 11 students made up the study population. They were split into two groups: the experimental group, which got an interpersonal communication intervention (n=55), and the control group, which received counseling (n=55). This study was carried out at SMAN 6 and SMAN 19 Bone. Simple random sampling was the method of sampling employed in this study, and a questionnaire was utilized as the research tool to gauge students' knowledge, attitudes, and action both before and after they received the intervention, which had been validated and proven to be reliable. Wilcoxon and Mann-Whitney tests were used for both univariate and bivariate data analysis.
Results: This study showed significant differences in knowledge, attitudes, and actions in the experimental group regarding hypertension prevention behaviors, with p-values for knowledge (p=0.017), attitude (p=0.000), and action (p=0.002).
Conclusion: The interpersonal communication approach applied in the intervention proved to have an influence on hypertension prevention behavior, including knowledge, attitudes, and actions in students of SMAN 6 and SMAN 19 Bone
Comparative Analysis of Kolmogorov-Inspired CNN and Traditional CNN Models for Pneumonia Detection: A Study on Chest CT Images
Get PDFAim: In this study, our goal is to compare the effectiveness of Kolmogorov Inspired Convolutional Neural Networks (KAN) with traditional Convolutional Neural Networks (CNN) models in pneumonia detection and to contribute to the development of more efficient and accurate diagnostic tools in the field of medical imaging.
Methods: Both models are structured with the same layers and hyperparameters to ensure a fair comparison of their performance. For a robust evaluation, the relevant dataset was divided into 80% for training and 20% for testing.
Results and Conclusion: Performance metrics of KAN; 95.2% sensitivity, 97.6% specificity, 94.1% precision, 96.9% accuracy (Acc), 0.9466 F1 score (F1) and 0. 9251 Matthews Correlation Coefficient (MCC), while the CNN model was found 92.5%, 96.4%, 91.2%, 95.3%, 0.9188 and 0.8858 for the same criteria, indicating that KAN outperformed. This comparison emphasizes that KAN has the potential to be a more effective model for pneumonia detection in chest CT images
Chronic kidney Disease Classification through Hybrid Feature Selection and Ensemble Deep Learning
Get PDFDiagnosing and treating at-risk patients for chronic kidney disease (CKD) relies heavily on accurately classifying the disease. The use of deep learning models in healthcare research is receiving much interest due to recent developments in the field. CKD has many features; however, only some features contribute weightage for the classification task. Therefore, it is required to eliminate the irrelevant feature before applying the classification task. This paper proposed a hybrid feature selection method by combining the two feature selection techniques: the Boruta and the Recursive Feature Elimination (RFE) method. The features are ranked according to their importance for CKD classification using the Boruta algorithm and refined feature set using the RFE, which recursively eliminates the least important features. The hybrid feature selection method removes the feature with a low recursive score. Later, selected features are given input to the proposed ensemble deep learning method for classification. The experimental ensemble deep learning model with feature selection is compared to Support Vector Machine (SVM), Logistic Regression (LR), and Random Forest (RF) models with and without feature selection. When feature selection is used, the ensemble model improves accuracy by 2%. Experimental results found that these features, age, pus cell clumps, bacteria, and coronary artery disease, do not contribute much to accurate classification tasks. Accuracy, precision, and recall are used to evaluate the ensemble deep learning model
Unconventional Monetary Policy, Disruptions in the Banking Sector and Banking Sector Efficacy: An ARDL and Bound Testing Applied to the Tunisian Banking Sector
Get PDFA longstanding debate is raised about whether banking sector is efficacious in the meaning it helps respond to investors financing requirements and whether it serves the conduct of monetary policy in its conventional formulation.
There are much concerns also about the alternatives of monetary policy conduct when the interest rate channel transmission mechanism does no longer work in terms of effectiveness of monetary policy and how to step aside credit supply insufficiencies and disruptions in order to respond to excess credit demand.
This article provides an assessment of the relevance of unconventional monetary policy to deal with the issue of the vicious role played by the credit sector depicted from its failure to fulfill banking sector efficacy due to an excessive search for yield motivation and extreme awareness from systemic risk.
For that sake we run an ARDL and Bound test to the data collected on the Tunisian banking sector and show that Banking sector efficacy is affected in the short run by Fisherian sensitivity another expression of the impact of inflation on real activity and banking sector specificities and in the long run it is affected by the impact of inflation on real activity and business cycle effects expressed in terms of sensitivities of Credit supply and demand to output gap.
We highlight that over the long run, Banking specificities do no longer matter and banking sector efficacy is not at all affected by Monetary policy because of nominal rigidities and monopolistic competition and backward oriented expectations that divert the pass through effect of monetary policy as the pricing of loans and is exclusively tributary on the search for yield motivation and the agency costs that result in a non competitive price of risk premiums that do not translate the transmission of monetary policy.
We conclude that the behavior of the banking sector is vicious because it conveys importance exclusively to the search for yield motivation, profitability and to the mitigation of systemic risk and does not play any role in the promotion of local investment which is a pillar of economic performance and growth.
We hence propose the Credit easing as an unconventional monetary policy that can step aside the hindrance of an inelastic credit supply through modifying asset prices and thereby improving attractiveness of assets to the banking sector and forcing financing through credit allocation but warn from the difficulties that might result from unconventional monetary policy in terms of inability to withdraw from the perturbation and gauge discretionary policy accurately
Preschool Wheezing and Progress to Childhood Asthma
No full textAim: This narrative review aims to identify key elements that facilitate the transition from recurrent episodes of wheezing to chronic inflammatory airway disease.
Methods: The article presents the results of numerous studies that identify the influence of genetic and environmental factors on the development of asthma in children. Whole-genome data analysis revealed novel genetic loci associated with various asthma phenotypes. Additionally, the study underscored the significance of environmental factors, such as air pollution and microbial colonization, in the disease's onset.
Results: The results provided a foundation for developing new prevention and treatment strategies for childhood asthma, emphasizing a personalized approach that considers each patient's unique genetic and environmental profile. The main findings indicate that up to 50% of children under 6 years old experience wheezing episodes, but only 30% of these children develop asthma. Data analysis demonstrated that both genetic and environmental factors significantly influence asthma development in children with preschool wheezing. Genetic research has identified several genes associated with early-onset asthma, including CDHR3, IL33, and genes at the 17q12-21 locus. Surrounding conditions such as viral infections, allergens, tobacco smoke, and the microbiome also play a substantial role in asthma development.
Conclusions: Understanding the relationship between hereditary and environmental influences in the advancement from preschool wheeze to asthma is crucial for developing effective prophylactic and treatment strategies. The study of factors influencing the development of asthma in children is important for understanding the mechanisms of disease formation and developing effective methods of prevention and treatment. Special attention is paid to the interaction of genetic and external factors influencing the early stages of pathogenesis
Adapted Physical Exercise as Therapy in Managing Obesity among Persons with Down Syndrome
No full textThis study investigated the efficacy of adapted physical exercise in managing obesity among persons with Down Syndrome (ID) in selected special schools in Cross River state. Three null hypotheses were generated for the study. A quasi-experimental research design was adopted. Two special schools and 20 persons with DS were purposively selected from the Special Schools Centre, Ibom Layout, and the Special Education Centre, Ikom, both in Cross River State, Nigeria. The age distribution of the participants is between 6-16 years. Adapted physical activities were used as a therapeutic intervention for six weeks. Kilograms Assessment Scale (KAS) (0.76) was used as an instrument for data collection. ANCOVA was used for data analysis. Results indicated that persons with ID who received intervention (adapted physical exercise) had their body weight reduced. Age and sex did not affect the efficacy of the intervention. It was recommended that physical exercise should be adopted in the management of obesity among persons with DS
Breastfeeding Practices in Morocco (1992-2025): Multicentric Analysis of National Surveys, Meta-Analysis, and Exploration of Key Indicators
Get PDFIntroduction: Breastfeeding is a cornerstone of infant nutrition, playing a crucial role in neonatal health, growth, and maternal-infant bonding. Despite WHO recommendations advocating exclusive breastfeeding for the first six months, breastfeeding practices in Morocco remain suboptimal, with disparities in both initiation and continuation. This study aims to analyze the epidemiology of breastfeeding in Morocco, assess maternal knowledge, and evaluate the effectiveness of national promotion programs while forecasting breastfeeding trends for 2025.
Materiel and Methods: A systematic review and meta-analysis were conducted, synthesizing data from 1992 to 2025 across databases including PubMed, ScienceDirect, Scopus, and Google Scholar. National surveys (ENPSF, PAPCHILD) and epidemiological studies were analyzed to determine the prevalence, trends, and determinants of breastfeeding. A linear regression model was applied to estimate the relationship between early breastfeeding initiation and exclusive breastfeeding at six months, with statistical significance assessed using Pearson correlation and p-value analysis. Projections for 2025 were made using predictive epidemiological modeling.
Results:
The early breastfeeding rate in Morocco remains inconsistent, with significant regional variations and socio-economic disparities.
Exclusive breastfeeding rates remain below WHO recommendations, with a projected stagnation at 40.6% by 2025.
The correlation between early and exclusive breastfeeding at six months is weak (r=0.36, p=0.759), indicating that additional determinants influence breastfeeding duration.
Despite national awareness efforts, maternal knowledge gaps persist, contributing to premature breastfeeding cessation and early introduction of complementary feeding.
Discussion: The findings highlight structural and behavioral barriers to sustained breastfeeding, including limited postpartum support, workplace constraints, and aggressive infant formula marketing. The current focus on early breastfeeding promotion may be insufficient to improve exclusive breastfeeding rates. Strengthening maternity leave policies, healthcare professional training, and postpartum follow-up strategies is essential to prevent stagnation in breastfeeding rates.
Conclusion: This study underscores the urgent need for comprehensive breastfeeding promotion policies in Morocco, extending beyond initiation efforts to focus on long-term adherence to exclusive breastfeeding. Strengthening healthcare interventions, workplace accommodations, and maternal education programs is essential to achieving WHO’s recommended breastfeeding targets and improving infant health outcomes.
Impact and Contribution: This study provides a robust assessment of breastfeeding practices in Morocco by combining epidemiological modeling, national survey data, and predictive analysis. The findings support public health strategies to increase breastfeeding rates, reduce disparities, and enhance maternal and infant nutrition
Policy Innovation in Healthcare: Exploring the Adoption and Implementation of Telemedicine
Get PDFBackground: Telemedicine has emerged as a transformative solution in healthcare, offering improved accessibility and efficiency. However, its widespread adoption remains influenced by policy frameworks, digital infrastructure, and financial sustainability. This study examines the role of policy innovation in telemedicine adoption and implementation, assessing regulatory impact, technological readiness, and reimbursement structures.
Methods: A cross-sectional survey design with a mixed-methods approach was employed, integrating quantitative surveys and qualitative interviews. Data were collected from healthcare policymakers, administrators, physicians, and technology developers across hospitals, clinics, and telemedicine service providers. Logistic regression and chi-square tests were conducted to analyze key predictors of telemedicine adoption, including regulatory support, digital infrastructure, and reimbursement policies. A total of 400 participants were surveyed, and 25 stakeholders were interviewed to analyze key predictors of telemedicine adoption.
Results: The findings indicate that institutions with clear licensing regulations and policy support exhibited significantly higher telemedicine adoption rates (OR = 2.15, p = 0.004). Standardized reimbursement policies positively influenced adoption rates (χ² = 14.91, p = 0.008). Digital infrastructure readiness, including broadband connectivity and EHR interoperability, was strongly associated with increased telemedicine utilization (OR = 2.31, p = 0.005). Major barriers included regulatory fragmentation, financial constraints, and technological literacy gaps.
Conclusion: Policy innovation, digital infrastructure investments, and structured reimbursement models are critical for telemedicine expansion. Addressing regulatory inconsistencies and financial limitations will enhance adoption. Future research should explore long-term policy impacts and AI integration in telemedicine