Synergistic Effect of Zinc Oxide and Magnesium Oxide Co-Cure Activators on Polybutadiene Rubber Vulcanization: Mechanical Properties and Thermal Characteristics

Zinc oxide (ZnO) is widely recognized as an effective cure activator in the sulphur vulcanization of polybutadiene rubber (PBR). However, its high toxicity to aquatic organisms has raised environmental concerns, prompting the search for non-toxic alternatives. Despite this, no industrially viable substitute has been identified. This study explores the potential of using a combination of ZnO and magnesium oxide (MgO) to reduce ZnO levels while enhancing vulcanization performance. The crosslinking density and thermal stability of the vulcanized PBR were assessed to evaluate the efficacy of MgO. The results demonstrate that the inclusion of MgO as a co-activator significantly accelerates the vulcanization rate. Specifically, formulations with 60% MgO exhibited a tensile strength of 1.1 MPa, elongation at break of 111%, and hardness of 46 Shore A. When using MgO exclusively, the material achieved a tensile strength of 1.4 MPa, elongation at break of 212%, and hardness of 43 Shore A, with an abrasion loss of 64.82 mm³. Swelling studies revealed that crosslink density was highest in the PBR formulation with 3 phr MgO and 2 phr ZnO, exhibiting the lowest swelling index (3.10). As MgO content increased, the swelling index also rose, indicating reduced crosslink density. The highest swelling index (4.24) was observed in the formulation with 5 phr MgO, confirming weaker crosslink formation. These results highlight that MgO alone lacks the ability to form an effective sulfurating complex, but when combined with ZnO, it enhances crosslinking efficiency and vulcanization performance. The use of MgO, either alone or in combination with ZnO, presents a viable approach for developing environmentally friendly PBR compounds with potential applications in high-performance elastomers such as tires

Management of Antipsychotic Therapy in Patients with Schizophrenia

Antipsychotic therapy is the main approach in the treatment of schizophrenia, but there is often irrational use due to inappropriate drug selection, inappropriate dosage, and long-term use without evaluation. Factors that support therapeutic rationality include adherence to clinical guidelines, selection of safer antipsychotics, and optimal management of side effects. Therefore, it is important to evaluate the factors that contribute to rational and irrational therapy in the use of antipsychotics in patients with schizophrenia. This study aims at antipsychotic medication management and factors that cause irrational therapy, as well as evaluating factors that support therapeutic rationality in the use of antipsychotics in schizophrenic patients. This study used a cross-sectional study design involving schizophrenia patients undergoing antipsychotic therapy in a psychiatric hospital. Data were collected through patient medical records and interviews with health workers. Quantitative data were analyzed using descriptive statistics and inferential tests, including chi-square and regression analysis, to determine the association between patient characteristics and antipsychotic selection as well as therapy rationality. The results showed that 26.7% of patients received irrational therapy, with the main causes being inappropriate drug selection (45%), inappropriate dosage (30%), and long-term use without evaluation (25%). Meanwhile, 73.3% of patients received rational therapy, with the main contributing factors being adherence to clinical guidelines (50%), selection of safer antipsychotics (30%), and good side effect management (20%). Irrational antipsychotic therapy remains a significant problem in the management of schizophrenia. Adherence to clinical guidelines and appropriate therapy selection can improve treatment effectiveness and reduce the risk of side effects. Regular evaluation and a multidisciplinary approach are needed to improve the rationality of antipsychotic therapy

Effectiveness of Art-Therapy-Based Intervention Programmes for Improving Social Communication in Children with Rett Syndrome

The research into effective art-therapy-based interventions for improving the social communication skills of children with Rett syndrome is important for the adaptation of this group of children. This study aims to evaluate the effect of a 6-month art-therapy-based intervention program based on art therapy on improving social communication in children with Rett syndrome. The research employed a quasi-experimental method, direct (unstructured) observation, a standardized Social Responsiveness Scale, and mathematical and statistical data processing methods (Levene test, paired sample t-test). The results showed a significant improvement in social communication in the experimental group (EG) after the intervention, as evidenced by paired and independent sample t-tests. This indicates statistically significant differences between pre-and post-test scores in the EG (mean difference 14.525 with a standard deviation of 22.592). The standard error for this group was 3.572, and the 95% confidence interval for the mean difference ranged from 7.300 to 21.750. The Student's t-test reached 4.066 with 39 degrees of freedom, resulting in a two-tailed p-value of less than 0.001. It has been found that art therapy can significantly improve social communication and emotional regulation subscales in children with Rett syndrome. The obtained data indicate the need to include therapeutic strategies based on art therapy in intervention programs for children with Rett syndrome. Prospects for further research are based on studying the impact of art therapy and other interventions not only on social communication but also on the cognitive development of children with Rett syndrome

Advisory Opinions under Protocol No. 16 to the ECHR. A Theoretical and Empirical Analysis of the Legal Nature of the ‘Questions of Principle’

One of the most significant legal arguments against the ratification of Protocol No. 16 to the European Convention on Human Rights (ECHR) is that advisory opinions issued by the European Court of Human Rights (ECtHR) would pose a threat to national sovereignty and judicial discretion. Several counterarguments have already been examined by scholars. The counterargument that will be demonstrated here is that advisory opinions cannot pose a threat to national sovereignty or judicial discretion because they are issued on ‘questions of principle’. In other words, this means that the requesting domestic highest courts or tribunals keep sufficient margin of discretion, when it comes to the concrete case brought before them. Such hypothesis will be demonstrated from a theoretical perspective, reflecting upon the legal concept of ‘principle’; and through an empirical analysis of the advisory opinions issued so far by the ECtHR. Demonstrating the hypothesis would be relevant in order to allow the States to understand that the ratification of Protocol No. 16 would not pose any threat to the discretion of domestic Courts, neither in theory nor in practice

Structural Equation Modeling of Oral Stomatitis and Its Determinants among the Sundanese Ethnic Group: Evidence from IFLS-5

Background: Oral stomatitis is an inflammation of the mucosa in various oral structures such as cheeks, gums, tongue, lips, palate, and floor of the mouth that commonly occurs in communities, including among the Sundanese ethnic group. Risk factors affecting stomatitis incidence in the Sundanese population need to be analyzed for developing more effective prevention programs. Aim: To analyze risk factors for stomatitis among the Sundanese population using panel data from the Indonesian Family Life Survey (IFLS). Method: This was an analytical observational study using secondary data from IFLS-5. The research design employed structural equation modelling (SEM) analysis examining variables including age, gender, education, residential area classification, general health status, and smoking habits. Results: The study revealed that age and general health variables had significant associations with stomatitis occurrence (p<0,001). Ages below 25 years and suboptimal health conditions proved to be significant factors influencing increased stomatitis incidence. Meanwhile, gender, education level, residential area classification, and smoking habits showed no significant correlation. Conclusion: Age and general health status are the main risk factors for stomatitis occurrence among the Sundanese population, which can serve as a reference for prevention program development

Improving Alzheimer’s Disease Detection with Transfer Learning

Accurate and prompt diagnosis of Alzheimer's disease (AD) remains a challenge, with only a small percentage of patients receiving timely confirmation. Manual interpretation of MRI scans, the primary diagnostic tool, is time-consuming, subjective, and prone to error, particularly in differentiating between disease stages. This study aimed to develop a computer-aided diagnosis system (CAD) for AD classification using deep learning models. MobileNetV1 and Xception architectures were employed to classify AD into four stages: mild, normal, moderate, and severe. Transfer learning and layer freezing techniques were applied for feature extraction and classification. Model performance was evaluated using precision, recall score, and accuracy metrics. The Xception model achieved a higher accuracy (79%) compared to MobileNetV1 (73%) in classifying AD stages. Compared to MobileNetV1, this study shows that Xception-based CAD systems have the potential to diagnose AD more accurately, providing a promising path for future research and clinical application

Multifunctional Characterization of Fucoidan: Structural Insights and Efficient Removal of Toxic Metal Ions

In 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

Bayesian Estimation of Spatiotemporal Immune-Viral Dynamics in COVID-19 Using Partial Differential Equations

This study proposes a Bayesian framework for estimating parameters in partial differential equation (PDE) models of viral dynamics. We develop a computational methodology combining Markov Chain Monte Carlo (MCMC) sampling with B-spline basis expansions to address inverse problems in COVID-19 immunology. Applied to clinical data from 30 patients, the model quantifies lymphocyte recruitment kinetics and infection rates during SARS-CoV-2 pathogenesis. Key results demonstrate: (1) mean daily lymphocyte recruitment rate λ̂ = 11.87/day (range: 6.55–14.66), and (2) mean infection rate of pulmonary/lymphoid cells β̂ = 3,556 cells/mL (range: 2,290–5,699). The Bayesian estimator achieved 93.2% posterior coverage probability, confirming its efficacy in characterizing immune response dynamics. These findings provide clinically actionable parameters for optimizing antiviral therapies through precise quantification of host-pathogen interactions. Notably, λ reflects the immune system's capacity to mobilize lymphocytes, with elevated values predicting rapid viral clearance and recovery. In contrast, β serves as a biomarker of viral infectivity severity, where higher values signal increased tissue-level viral load and a greater risk of adverse clinical outcomes

Serum 25-Hydroxyvitamin D Concentration Status and Neonatal Immune Function: New Perspectives in Anticipating Late Onset Sepsis among Preterm Neonates at Tertiary Care Centres (A Prospective Study)

Objective: This study aims to investigate the impact of low vitamin D levels in cord blood on the incidence of neonatal sepsis in preterm infants. Patients and Methods: This prospective study was conducted at Al-Azhar and Helwan University Hospitals from September 2024 to January 2025. 150 neonate premature infants with a gestational age of <37 weeks were enrolled. In the present study, vitamin D deficiency (group 1, n=75) was defined as a 25-hydroxyvitamin D (25(OH)D) concentration <15 ng/mL; and vitamin D sufficiency (group 2, n =75), 25(OH)D concentration ≥15 ng/mL. Results: All markers were higher in Group 1 compared to the other groups (P < 0.05). Interestingly, the mean Del PCT was lower in group 2 compared to different groups. The cut-off of the umbilical cord CRP was 10.5 mg/L, the sensitivity, specificity, PPV and NPV were 41, 88.0, 29 and 28%, respectively. At a PCT cut-off of 1.18 ng/mL, the sensitivity, specificity, PPV and NPV were 79, 91, 51 and 61%, respectively Conclusion: Our study is one of the few that examines the relationship between neonatal sepsis in preterm newborns and the level of vitamin D in cord blood. Based on the findings of our investigation, we concluded that neonatal sepsis in preterm newborns is not related to vitamin D levels in the cord blood. To investigate these findings further, a larger patient sample or randomized controlled trials are required

Robustness of Bayesian Methods in Healthcare System Assessment: A Comprehensive Review

Background: Healthcare systems generate heterogeneous, incomplete, and evolving data; methods that combine prior knowledge with new evidence are needed. Aim: The present research critically evaluates the usefulness and resilience of Bayesian methods for healthcare system assessment. Scope: This study synthesizes foundational principles and contrasts with frequentist approaches; examines applications across quality of care benchmarking, health economic evaluation, epidemiologic surveillance, resource allocation, policy appraisal, and personalized medicine; and highlights computational advances enabling practical deployment. Key Findings: Bayesian techniques provide partial pooling through hierarchical models, formal incorporation of prior information, accurate probabilistic inference, and dynamic updating as data accumulates. These features give more stable estimates in sparse settings, transparent quantification of uncertainty, and decision‑relevant outputs (e.g., posterior probabilities and cost-effectiveness acceptability). Modern samplers and approximate inference make complex models tractable, yet results remain sensitive to prior specification and data quality, stressing the need for validation, sensitivity analysis, and clear reporting. Conclusion: Bayesian methods offer a meticulous, flexible framework for assessing performance, value, and equity in healthcare systems. They can enhance policy-making and clinical decision support when paired with principled prior elicitation, robust computation, and reproducible workflows. Next, the practical recommendations and research priorities to accelerate responsible adoption across healthcare analytics were outlined. At the end, this review highlights both methodological robustness and translational potential, positioning Bayesian methods as indispensable for evidence-based healthcare decision-making