Optimizing Fixed-Time Artificial Insemination Efficiency through Co-Synch Techniques in Water Buffaloes (Bubalus bubalis)

The main aim of the study was to optimize the potential of CIDR-CoSynch-hCG protocols developed in water buffaloes. Multiparous animals (163) were assigned to three hormonal treatments. CIDR-Synch-hCG (T1/Control), wherein CIDR and GnRH were given (day 0), prostaglandin (day 7), hCG (day 9), and artificial insemination (AI) was performed twice on day 10. CIDR-CoSynch-hCG-day-9 (T2): Same hormones were given on days 0 and 7, but injection of hCG and AI were concomitantly performed on day 9. CIDR-CoSynch-hCG-day-10 (T3): the same hormones were given on days 0 and 7, but hCG and AI were injected concomitantly on day 10. The size of the pre-ovulatory follicle (POF) at the time of AI was likewise determined to evaluate its influence on pregnancy. The effect of the number of inseminations on pregnancy was determined. Results revealed that pregnancy rates of T1 (43.70%), T2 (43.27%), and T3 (46.07%) were not significantly different (P>0.05). The study demonstrated that simultaneous injection of hCG and AI, either on Day 9 or Day 10 of the CIDR-CoSynch-hCG protocol, is as effective as doing them separately (T1/Control). In addition, large-size (≥12 mm) POF at the time of AI increased pregnancy outcomes (65.52%) compared to medium (41.46%) and small (26.05%) follicles. Meanwhile, twice insemination (51.10%) resulted in significantly higher (P=0.0004) pregnancy rates than single insemination (21.64%). This work identifies key factors and innovative strategies to enhance FTAI implementation in water buffaloes

Shear Strengthening of Deep Beams Using Polymer-Based CFRP Bars via the Near-Surface Mounting (NSM) Technique

Near-surface-mounted strengthening with polymer-based carbon fiber-reinforced polymer (CFRP) bars has been proved as one of the efficient techniques in enhancing the shear capacity of reinforced concrete RC deep beams. This paper presents an experimental investigation on the shear behavior of RC deep beams strengthened with NSM CFRP bars. Five identical RC deep beam specimens with the same geometry and internal steel reinforcement were tested under two-point loading. One specimen was left un-strengthened as a control beam; while four specimens have been strengthened by CFRP bars embedded in the shear zone with two orientations, 0°/90° and 45°/135°, and two spacing configurations, 100 and 150 mm. Response parameters of prime interest included first shear cracking load, ultimate shear capacity, crack pattern, and mid-span deflection. The findings of the experiment demonstrated that NSM CFRP strengthening improved the shear performance of deep beams; depending on the orientation and spacing of the CFRP bars, shear capacity augmentation ranged from about 14% to 47% in comparison to the control specimen. Additionally, at similar load levels, strengthened beams demonstrated a 10% to 40% decrease in mid-span deflections and fracture widths. The test results demonstrate how well polymer-based CFRP bars inserted using the NSM technology improve the stiffness and shear strength of RC deep beams

A Study on Postpartum Depression in Tertiary Care Hospital: Implication for Maternal Mental Health

Background: Postpartum depression (PPD) is a significant maternal health issue often overlooked in India. This study assesses its prevalence, risk factors, and implications in a tertiary care hospital in Pune. Methods: A cross-sectional study was conducted from March 2025 to June 2025, involving 102 postpartum women. The Edinburgh Postnatal Depression Scale (EPDS) was used to assess depression immediately postpartum and at six months Results: The incidence of PPD was 12.75% immediately postpartum and 15.69% at six months. Significant risk factors included young maternal age (<20 years), low family income, unplanned pregnancy, preterm birth, antenatal complications, and low self-esteem. Employment status and lack of antenatal care were also associated with higher EPDS scores. However, factors such as education level, delivery mode, and baby’s gender did not show statistical significance. Conclusion: PPD is a prevalent yet underdiagnosed condition that requires urgent integration into maternal healthcare programs. Early screening, mental health support, and targeted interventions can improve outcomes for mothers and infants. Further research and policy focus on maternal mental health are necessary for better healthcare delivery

Ghosts in Ancient Egypt from a Literary Perspective: An Analysis of ‘Khonsemhab and the Spirit’. A Possible Pessimistic Tale of the Middle Kingdom?

In this study, we examine one of the most enigmatic compositions of Ancient Egyptian literature. Although preserved in a copy of Ramesside period from the New Kingdom, the text appears to be based on an earlier narrative tradition. The tale centres on the encounter and dialogue between its two eponymous protagonists: Khonsemhab, a priest of Amun, and Nebusemekh, a spirit. The narrative unfolds through their exchange concerning the spirit’s lament over the dilapidated state of its tomb, a condition that prevents it from attaining eternal rest, and the assurances offered by the priest to restore it—assurances which the spirit receives with scepticism, shaped by past disappointments. Owing to the fragmentary preservation of the text, the fate of both characters remains unknown. Based on its formal and thematic features, it is plausible to suggest that this tale could be tentatively situated within the corpus of so‑called pessimistic texts traditionally associated with the Middle Kingdom. In this regard, it exhibits several noteworthy affinities with compositions from that period, such as its dialogic structure, the thematic tension between order and chaos, and the spirit’s expressions of despair in response to the neglected state of his burial place. In this study, I examine the tale in detail and seek to address a central question at the end of the article: Could this story have originally belonged to the tradition of Middle Kingdom Pessimistic Literature

Crisis Communication and Response Strategies in Car Manufacturing Companies: A Multiple Case-Study Approach in Gauteng, South Africa

South Africa has several car manufacturing companies or plants, referred to as open systems, and in fact, the automotive industry is the biggest employer in the country with 120 000 employees and a 6.4% stake of the national GDP (against 8% of the mining sector, 5 years ago). Although its contribution to the economic prospects of this nation is undeniably huge (more or less 14.2% of national exports and 24% of manufacturing output), the car manufacturing industry also comes with its own challenges and, at worse, crises. This study, amongst the other things, sought to address car manufacturing crises by looking into four car manufacturing companies’ chaotic situations and related theories. The research shows that crises are inevitable in business and industry alike. It also demonstrates that crisis communication steps and response strategies thereof, if followed and adhered to, could help to better understand potential crises, avoid them, address them at hand or in their aftermath. Through this research, it is obvious that the car manufacturing industry, specific models tend to have potentially fatal defects, leading to numerous car recalls as shown in selected case studies. This research followed a multiple case study and qualitative approach. The research was conducted by administering semi-structured indepth interviews, doing thematic and content analyses of obtained raw data, making sense of them and infering/deriving knowledge for all to use. The participants were four car manufacturing companies (herein referred to as Companies A, B, C and D) with their head offices in Gauteng, South Africa. The crisis management teams were selected as the target population because they actively attempt to remedy the crises and interact with various organisational stakeholders when a chaos occurs. The findings identified gaps in crisis communication planning and implementation, given the ever-changing business and public relations’ environments in which organisations operate. As a result, recommendations are made to assist public relations and communications practitioners today and in the future to handle various crises effectively. Ultimately, car manufacturing companies will benefit by improving the protection of their organisations and stakeholders from threats, thus reducing those threats’ negative impacts on business and the economy. Future research could be done either at national level to include more car manufacturing companies in order to allow comparison, or selectively across the regions in the continent, to pursue an hybrid study which equally considers crises in the only other truelly African industrial economy, namely Egypt

Enhanced Prediction of Chronic Kidney Disease using XGBoost Machine Learning Model

Chronic kidney disease (CKD) might progress to end stage renal disease; moreover, cardiovascular dangers are dire. Machine learning used in for more speed and accurate diagnosis of CKD. The CKD prediction model proposed in this paper was developed using the XGBoost algorithm, which is quite effective in classification problems. Other clinical parameters such as blood urea, serum creatinine and white blood cell count are some of the 24 indices identified from among the 400 patient records in the dataset. Feature selection using SelectKBest was relevant, and hyperparameter tuning was done by RandomizedSearchCV Both quantitative and categorical data were preprocessed. Altogether, 75% of data used for training, while 25% of data used for testing. The XGBoost model had a better result with 96.88 % recall, 100% precision, and 98% accuracy. However, the proposed approach has disadvantages; namely, a small sample cross-section and possibly an imbalanced class. Further, the dataset will be increased, the methods of dealing with class imbalance will be applied using SMOTE algorithm, and the effectiveness of the proposed model will be tested in real clinical practice. This work also highlight how crucial it is to employ and enhance machine learning, especially XGBoost to detect early stage of CKD, proper treatment, low mortality rate, and increased survival rate among patients

From Artificial Intelligence to Real-Life Practice: Can ChatGPT be a Guide About Pediatric Dysphagia?

Introduction: The widespread use of Artificial Intelligence (AI)-based tools has significantly simplified access to medical information. Pediatric dysphagia, or difficulty swallowing in children, is among the commonly queried topics because of its close relationship with feeding safety, nutritional intake, and growth outcomes. This study aims to evaluate the reliability, usefulness, and safety of responses generated by Chat Generative Pre-Trained Transformer (GPT) regarding pediatric dysphagia. Methods: A set of thirty carefully selected questions covering various aspects of pediatric dysphagia, including general information, risk factors, diagnosis, treatment, and follow-up, was prepared based on clinical data, digital trends, and frequently asked questions from health websites. These questions were submitted to ChatGPT (version 4.0), and the responses were independently evaluated by two experts using a 4-point Likert-type scale (1: lowest, 4: highest) to assess reliability, usefulness, and safety. Additionally, the readability of each response was measured using the Flesch-Kincaid Grade Level test, which estimates the educational level required to comprehend the text. The implications of this readability score for caregiver comprehension were also interpreted. Results: ChatGPT’s responses received high scores overall, with average ratings of 3.73 for reliability, 3.87 for safety, and 3.87 for usefulness. The average Flesch-Kincaid Grade Level was 13.03, indicating suitability for university-level readers. This suggests that while the responses are accurate and informative, their linguistic complexity may limit accessibility for some caregivers. Conclusion: ChatGPT shows promise as a supportive tool in providing basic information about pediatric dysphagia. However, to ensure accurate and personalized medical evaluation, these AI-generated responses must be verified through professional clinical review. Given that pediatric dysphagia directly affects nutritional intake, growth, and feeding safety, validated AI-based guidance tools could help caregivers recognize feeding problems earlier and seek appropriate medical care promptly

Extreme Heterogeneity in Global Prevalence Meta-Analyses: Evaluating Current Practices and Exploring Bayesian Alternatives - an Umbrella Review

Introduction: Global prevalence meta-analyses often exhibit extreme heterogeneity (I² > 90%), yet criteria designed for clinical trials, where homogeneity is desirable, continue to be applied without recognizing that in prevalence studies, variability reflects real differences between populations. Objective: To document the magnitude of heterogeneity in global prevalence meta-analyses, evaluate the methodological strategies employed for its exploration and management, and explore through illustrative application how Bayesian methods—rarely employed in prevalence meta-analyses—compare with standard frequentist approaches. Methods: Umbrella review conducted according to PRIOR guidelines. Systematic search in SCOPUS for systematic reviews with global/worldwide prevalence meta-analyses published between 2015-2025. Data were extracted on I², statistical models, subgroup analyses, sensitivity analyses, meta-regression, and prediction intervals. Three meta-analyses were randomly selected for illustrative Bayesian re-analysis using hierarchical models with weakly informative priors, and the results were compared with those from frequentist approaches. Results: Of 53 included meta-analyses, 52 (98.1%) presented I²≥75%, 47 (88.7%) I²≥90%, and 34 (64.2%) I²>99%. Management strategies showed a decreasing implementation rate: subgroup analyses (96.2%), sensitivity analyses (64.2%), meta-regression (34.0%), and prediction intervals (5.8%). Among studies with I²≥75%, 63.5% provided explicit justification for proceeding with pooling. The illustrative Bayesian analysis of three randomly selected studies demonstrated excellent concordance with frequentist estimates (differences <0.1%), while providing additional uncertainty quantification for heterogeneity parameters unavailable from standard approaches. Conclusions: Extreme heterogeneity constitutes the norm in global prevalence meta-analyses. The underutilization of prediction intervals (5.8%) and meta-regression (34.0%) represents the critical gap for improving statistical rigor. An exploratory Bayesian analysis demonstrated concordance with frequentist estimates, while providing additional uncertainty quantification. This illustrates that alternative methods are feasible, though their value lies primarily in specific scenarios rather than routine application. Prevalence-specific frameworks should recognize high heterogeneity as an expected characteristic requiring comprehensive exploration rather than elimination

The Efficacy of Natural Mineral Water “Kara-Shoro” in Caries Prevention in Children

Background: Dental caries remains one of the most prevalent oral health issues among children and adults. This study investigates the efficacy of “Kara-Shoro” mineral water as a natural source of fluoride for caries prevention in children aged 7-15. The mineral water used in the study contains 7.83 mg/L of fluoride, along with high concentrations of bicarbonates (1,680 mg/L) and chlorides (4,541 mg/L), classifying it as a bicarbonate-chloride type mineral water. Methods: The research was conducted over three years in two villages of the Kyrgyz Republic and included educational, therapeutic, and preventive phases. In the test group, a regimen of regular “Kara-Shoro" mineral water use was implemented, both for topical application (oral rinsing) and systemic consumption. The control group followed standard caries-prevention methods, including toothbrushing without using this mineral water. Findings: Children consuming “Kara-Shoro” mineral water exhibited a significant reduction in caries intensity, as measured by the DMFT+dmft index (number of decayed, missing, and filled permanent and deciduous teeth) and the DMFT index (same metric, limited to permanent teeth), compared to the control group. By the end of the study, three years after the initiation of preventive measures, the DMFT index was 0.52±0.18 in the test group and 3.44±0.68 in the control group. The mean caries increment in the test group was 0.46 cavities, representing 16.91% of the increment observed in the control group, which reached 2.72 (p<0.001). The final reduction in caries prevalence in the test group compared to the control was 83.09%. No signs of fluorosis were observed in either group. Conclusion: As a result, the use of “Kara-Shoro" mineral water may be a promising approach to caries prevention in children, particularly in regions with low fluoride levels in drinking water. Further research is required to determine the optimal application regimen and assess long-term effects

Comparative Evaluation of Inception V3 and ResNet 50 for Pneumonia Prediction

Pneumonia is a fatal respiratory infection that has become the leading cause of death among many people across the world. Its widespread has grabbed great attention making it a major topic for research under various domains. Its severity has led to the development of systems that can predict whether a patient has chances of being diagnosed with pneumonia or not, this is also called as computer aided diagnosis. However, current study intends to identify an Artificial Neural Network (ANN) model that has been able to provide the highest accuracy when it comes to predicting this life-threatening condition. The prediction was initially done with Machine learning techniques but with the introduction of ANN, it was observed that there are models that provided higher accuracy than the ML models. This study investigates how the concept of deep learning which is a vital part of ANN makes use of one of its most efficient models including Inception V3 and ResNet 50 for the prediction of pneumonia and compare their performance to suggest a better solution to the problem. Results indicate that ResNet50 offers clinically meaningful improvements in sensitivity and specificity, supporting its role as a decision-support tool for early pneumonia detection