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Spontaneous Fermentation of Regional Fruit Beverages using Buffalo Yogurt Whey
Get PDFYogurt whey is a by-product of the filtration process in Greek-style buffalo yogurt. It contains beneficial compounds such as proteins, minerals, carbohydrates, and lactic acid bacteria; yet, it is often discarded, contributing to environmental contamination due to its high biological oxygen demand. This study aimed to valorize this by-product by developing fermented beverages formulated by combining yogurt whey with regional citrus and tropical fruits. Eighteen formulations were prepared using whey, fruit pulp or juice (grapefruit and passion fruit), sugar, and filtered water, followed by spontaneous fermentation for 48 hours at ambient temperature (25 ± 2 °C). Physicochemical parameters (pH, °Brix, and Density) were measured before and after the filtration process. Two formulations, grapefruit (citrus group) and passion fruit (tropical group), were selected for sensory evaluation by 30 untrained panelists, who used a 9-point hedonic scale to assess aroma, flavor, and color. Physicochemical results showed minor changes in pH and significant increases in °Brix and Density in samples after filtration, particularly in beverages made with tropical fruits. Sensory analysis revealed high overall acceptability; passion fruit beverages received significantly higher overall and flavor scores from female participants than from males (p = 0.043). The results demonstrate the feasibility of transforming buffalo yogurt whey into a regionally inspired fermented functional beverage with favorable sensory acceptance and commercial potential. This approach presents an innovative strategy for reducing waste in the dairy industry. It supports sustainable food systems through the valorization of underutilized by-products and local fruits, which aligns with the principles of the circular economy
Unusual Congenital Development of Hoof- and Tail-Like Structure in the Buccal Mucosa of a Buffalo Calf: A Rare Case Report
Get PDFA rare congenital anomaly was observed in a neonatal buffalo calf presenting with unusual tissue growth resembling hoof and tail-like structures within the oral mucosa. This case is the first of its kind reported in buffalo calves and contributes to the limited literature on oral anomalies in large animals. The buccal space's limited size and distribution of adipose tissue make it an anatomically significant location. Clinical and histopathological evaluations were conducted to characterize the nature of the growth because of the variety of tissues present. A unilateral (right side) buccal space tissue (horn and tail) growth and its surgical management, along with prognosis, are discussed in this report
Predicting Sex from Hand Dimensions using Statistical Models: A Cross-Sectional Study of Medical Students
Get PDFDetermining sex from dismembered body parts is crucial for forensic and medico-legal investigations. Hand anthropometry offers a practical, non-invasive approach, particularly when utilising statistical models. This study aims to assess sexual dimorphism in hand dimensions and evaluate the effectiveness of statistical methods in determining sex from various hand measurements. Data for this study were obtained from a cross-sectional survey conducted from July to December 2021 involving a sample of 150 undergraduate medical students (78 males, 72 females) aged 18 to 24 years at a private medical college in India. Medical students were selected as a relatively homogeneous population to minimize confounding factors such as occupational variation, lifestyle, and health status, thereby increasing the internal validity of the findings. Measurements of hand length, breadth, and palm length for both the left and right hands were taken. Logistic regression was employed to develop models for sex classification. By using various combinations of explanatory variables, three logistic regression models were fitted to predict sex. Among these models, the one with the best fit was selected as the final model for sex prediction. It was observed that the mean scores of male and female respondents differ significantly. All hand dimensions were significantly larger in males (p < 0.001). According to the best-fitting model, the Right Hand Index (RHI) along with height was identified as the most significant predictors of sex. The best-fitted logistic model achieved 90% accuracy with an AUC of 0.93. Hand dimensions, particularly the Right Hand Indices (RHI), are effective predictors of sex and logistic regression provides a reliable method for forensic identification when complete body parts are unavailable, and this model can be utilised for other types of forensic predictions
Robustness of Bayesian Methods in Healthcare System Assessment: A Comprehensive Review
Get PDFBackground: 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
Machine Learning-Based Prediction of Seasonal Influenza Trends in Saudi Arabia: A Tool for Regional Public Health Planning
Get PDFInfluenza has continued to be a worldwide social health problem, especially in high-density population areas with minimal early-warning mechanisms. The present study evaluates the predictive ability of two machine learning models Support Vector Regression (SVR) and Random Forest (RF) to predict weekly influenza cases in Saudi Arabia, spanning from 2017 to 2022, on 313 weekly influenza records in the WHO Global Influenza Surveillance and Response System (GISRS). The performance of these models was measured with R², MAE, MSE, and RMSE. Although SVR had a better training accuracy (R² = 0.96), RF had a better generalization (R² = 0.818) and more consistent predictions at the peaks of the seasons. These observations show that RF is appropriate to real-time influenza surveillance and can provide a replicable and versatile framework to assist data-driven epidemic preparedness in Saudi Arabia and other similar contexts throughout MENA and Asia-Pacific
Comparing Frequentist and Bayesian Quantile Regression Models for Child Hypertension in South Africa
Get PDFBackground: Traditional approaches to modelling paediatric hypertension in South Africa have relied on descriptive or mean regression methods, which inadequately capture risk factors driving the distributional extremes of blood pressure. Quantile regression provides a flexible alternative, and Bayesian methods offer advantages in precision and uncertainty estimation, yet their comparative performance has not been assessed in this context.
Methods: Nationally representative cross-sectional data from 1,812 adolescents (15–17 years) in the South African National Income Dynamics Study (NIDS) Wave 5 (2017–2018) was analysed. Frequentist and Bayesian quantile regression models were fitted for systolic (SBP) and diastolic blood pressure (DBP) at the 75th and 95th percentiles. Model performance was compared in terms of parameter estimates, interval precision, and convergence diagnostics.
Results: BMI and gender were consistent predictors of both SBP and DBP across models. Bayesian quantile regression additionally identified age, race, and pulse rate as significant risk factors for upper quantiles. Bayesian credible intervals were consistently narrower than frequentist confidence intervals, indicating improved precision. Convergence diagnostics confirmed robust posterior inference.
Conclusion: Bayesian quantile regression provides more efficient inference than the frequentist alternative when modelling health outcomes concentrated in distributional extremes. This is the first study to apply Bayesian quantile regression to paediatric hypertension in South Africa, demonstrating both methodological value and empirical insights into adolescent health risks
FTIR Analysis of Nanoparticle-Doped Polymer Dispersed Cholesteric Liquid Crystals
Get PDFThis study investigates the structural and chemical interactions in nanoparticle-doped polymer dispersed cholesteric liquid crystals using Fourier Transform Infrared (FTIR) spectroscopy. Cholesteric liquid crystals known for their helical structure and optical selectivity, were embedded in a polymer matrix, and doped with silver metal nanoparticles. Samples were fabricated using polymerization-induced phase separation and analyzed through FTIR to examine the addition of nanoparticles and their influence on functional group behavior. Shifts in characteristic absorption bands (C=O, O–H, and metal–oxygen) and appearance of new peaks in the fingerprint region suggested significant interfacial interactions among the nanoparticles and the composite matrix. The findings reveal the effectiveness of FTIR in elucidating the molecular-level effects of nanoparticle doping in liquid crystal-based hybrid systems. Such improvements underscore the significance of nanoparticle–polymer interactions in designing thermally robust functional composites, thereby expanding their potential for advanced structural, optical, and sensing applications
Improving Mechanical Properties of Polymer Modified Steel Fiber Reinforced Concrete Made with Concrete Waste by usingPC-600-Super-Plasticizer
Get PDFThis study investigates the enhancement of mechanical properties in polymer-modified steel fiber-reinforced concrete (PMSFRC) incorporating demolition waste as a sustainable coarse aggregate replacement. The work addresses the dual objectives of resource recycling and performance optimization within environmentally responsible construction practices. Results show that replacing natural coarse aggregates with demolition waste slightly reduces compressive strength from 44.1 MPa to 41.6 MPa. However, the incorporation of PC-600 Flocrete superplasticizer effectively compensates for this reduction, increasing compressive strength to 49.4 MPa. Significant improvements were also observed in tensile strength, which increased from 5.7 MPa to 6.1 MPa, and in flexural strength, which increased from 12.1 MPa to 15.5 MPa for mixes with 100% waste replacement. Additionally, the modulus of elasticity improved from 26.5 GPa to 30.5 GPa, demonstrating enhanced stiffness and structural viability. These findings confirm that polymer modification enables effective utilization of concrete waste without compromising structural integrity, promoting cleaner production, circular material use, and sustainable innovation in civil infrastructure
Parental Age and Gender: How they Influence Knowledge and Perceptions of Inclusive Education for Children with Intellectual Disability
Get PDFBackground: This study investigated how parental age and gender influence their knowledge and perspectives of inclusive education for their children with intellectual disabilities (ID). This study is essential as it provides valuable insights into how parental factors, such as age and gender, can shape their knowledge, perceptions, and attitudes toward inclusive education, which will likely impact the educational experiences and outcomes for children with intellectual disabilities.
Methods: Employing a cross-sectional research design, the study surveyed 96 parents, consisting of 55 males (57.3%) and 41 females (42.7%). The participants were categorised by age: under 25 (n=20, 20.8%), 25-34 (n=24, 25.0%), 35-44 (n=28, 29.2%), and 45 and above (n=24, 25.0%). Data were collected using a structured questionnaire, demonstrating a reliability coefficient of 0.88 (Cronbach's alpha). The data analysis used Multivariate Analysis of Variance (MANOVA) to assess the main and interaction effects of parental age and gender on their knowledge regarding inclusive education.
Results: Tests of Between-Subject Effects indicated a significant interaction between age and gender, F (3, 88) = 5.67, p < 0.01, revealing that older female parents (M = 4.10) had higher knowledge scores than older male parents (M = 3.60). Estimated marginal means supported these findings, explicitly showing significant differences between parents aged 25-34 and 45 and above (p < 0.05). These differences are evident in pairwise comparisons, particularly in the 35–44-year-old age cohort (M = 3.95).
Conclusion: The results indicate that age and gender influence parental knowledge and perceptions of inclusive education. A targeted intervention considering these factors is crucial to enhancing supportive educational environments for children with ID
Poetry Therapy, Disability, and Trauma Expression: A Therapeutic-Phenomenological Perspective
Get PDFThis study aims to explore how individuals with disabilities express traumatic experiences through literary works from a therapeutic-phenomenological perspective. The research employs a qualitative-phenomenological method, with data collected from 45 literary works written by individuals with disabilities. The therapeutic process involved filtering, handling, and follow-up stages, involving 45 participants with disabilities. Data analysis was conducted through identification, classification, reduction, and exposition. The findings revealed varied themes: social criticism (35.5%), absurdism (17.7%), religion (13.3%), romanticism (4.4%), feminism (2.2%), and other themes (26.6%). Social criticism was the most dominant theme, followed by absurdism, religion, romanticism, feminism, and others. These works not only reflect emotional expression but also serve as a medium for critiquing discrimination and injustice experienced in society. The trauma expressed is primarily relational, such as social rejection and bullying, beyond just physical limitations. This study confirms that literary works are a vital means for individuals with disabilities to authentically voice their experiences and symbolically resist non-inclusive social systems. These findings aim to enrich interdisciplinary studies in literature, psychology, therapy, and disability studies