Volume 13 | Issue 7 |

 Abstract

Mpox or monkeypox is zoonotic illness caused due to monkeypox virus (an Ortho poxvirus). Mpox is close relative of Variola(smallpox) virus. MPXV is a double-stranded DNA virus transmitted by droplet exposure via exhaled large droplets, direct contact (Sexual/Infected skin lesions, contagious materials such as towels, bedding) MPXV was first detected in 1958 in an outbreak of a vesicular disease among captive monkeys transported from Africa to Denmark for research purposes. The largest animal reservoirs of the virus have been found in squirrels, giant pouched rats. In Aug.1970 the first case of monkeypox was identified in 9-year-old child in the village of Bukenda in the equatorial region of Zaire (now DRC). Mpox is endemic in both Central Africa and West Africa. The recent outbreaks of MPXV have now occurred in several countries on almost all components. Symptoms of Mpox include Fever, Headache, Myalgia, Characteristics rash that develops into papules which evolve to vesicles, pustules and crusts in the genital, anal or oral regions. Diagnosis can be made through presence of Ortho poxvirus DNA in PCRs from lesion swab or body fluids. Patients with severe manifestations and people at risk of severe disease (e.g. immunosuppressed people) could benefit from antiviral treatment which includes (e.g. tecovirimat, brincidovir, cidofovir) and vaccinia immune globulin intravenous (VIGIV). JYNEEOS(TM)(live replication incompetent vaccinia virus) and ACAM 2000(live, replication competent vaccinia virus) are two vaccines currently available as medical counter measures for Ortho poxvirus such as monkeypox

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 Keywords

Monkeypox, Orthopoxvirus, democratic republic of Congo, Prodromal stage, PCR kit.

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The current study investigates the association of serious games (SGs) preference with cultural heritage, community, educational, and sustainable development (SD). Quantitative and qualitative research methods were used to achieve this objective, and data were collected using the survey technique. An original and historical HTML5 memory serious game was developed to give the audience at the museum a fast, informative look at the dinosaur era in Egypt. The study's sample consisted of 104 students residing in different countries. The reliability of the questionnaire was evaluated via Cronbach Alpha (0.953), showing data authenticity. The results obtained from the survey showed significant associations (P <= 0.05) of students' preference after playing that SG on community and educational development, cultural heritage (CH), and SD via chi-square test. The study concluded that SGs are now associated with community and educational development, SD, and CH. The results also concluded that it should be designed for a wider audience with low violence, positivism, responsible gaming, and educational value. Hopefully, the results of this study will help develop games incorporating users' recommendations for SGs.

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 Keywords

serious games; sustainable development; educational development; cultural heritage; serious games preference.

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The present design is based on the theory of planned behavior and tests the demography variable role in TPB's major variable. The study examined age, education, and income as independent variables and attitude towards chocolate buying intention and buyer behavior as dependent variables. Results showed no significant differences in buyer behavior among education and income groups. However, younger respondents showed higher buyer behavior. No significant differences were found in attitudes towards chocolate among different age and income groups. High-income consumer groups showed significant differences in buying intentions.

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 Keywords

Attitude, buying intention , buyer behavior

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Ayurveda is a life science dedicated to protecting human health. The eyes are vital sensory organs that are susceptible to harmful influences. Ayurvedic methods, known as Kriyakalpa, safeguard eye health, with Tarpana being a straightforward yet effective technique. This method strengthens and heals the eyes from various disorders.

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 Keywords

Sensory organ, Kriyakalpa, Tarpana

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Chronic Kidney Disease (CKD) is a critical health concern affecting millions globally, often progressing silently until it reaches an advanced stage. Early detection and accurate prediction of CKD can significantly reduce the risk of kidney failure, improve patient outcomes, and decrease the financial burden of long-term treatments like dialysis and transplantation. Traditional diagnostic methods are time-consuming, expensive, and sometimes inaccessible in remote areas. In response to these challenges, this project proposes a data-driven approach using machine learning to predict CKD at an early stage based on clinical and physiological parameters. The primary objective of this study is to develop and evaluate various machine learning models for predicting CKD using a publicly available dataset from the UCI Machine Learning Repository. The dataset contains 400 instances with 24 attributes, including age, blood pressure, blood sugar levels, serum creatinine, and more. The data was preprocessed to handle missing values, normalize numerical features, and encode categorical variables. Following preprocessing, multiple supervised learning algorithms were implemented and evaluated, including Logistic Regression, Random Forest, Support Vector Machines (SVM), K Nearest Neighbors (KNN), and Decision Trees. Model evaluation was performed using performance metrics such as accuracy, precision, recall, F1-score, and Area Under the ROC Curve (AUC-ROC). Among all models tested, the Random Forest classifier delivered the highest predictive accuracy and robustness. Cross-validation was used to ensure generalizability and avoid overfitting. Additionally, feature importance analysis was conducted to identify the most influential parameters contributing to CKD prediction. This project demonstrates the practical applicability of machine learning in the healthcare domain, particularly in predictive diagnostics. The outcomes of this study can aid healthcare professionals in early identification of CKD and can serve as a foundation for building intelligent diagnostic support systems. Future enhancements may include deploying the model as a web or mobile application, integrating real-time hospital data, and expanding the dataset for higher precision and clinical relevance.

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 Keywords

Logistic Regression, Support Vector Machines, Random Forest

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Climate is a critical determinant of agricultural productivity, influencing crop growth, livestock health, and overall farm output. In recent years, growing concerns about the impacts of climate change on agriculture have led to a surge in research focused on this issue. Much of the existing literature examines the potential physical effects of climate change, including variations in crop and livestock yields, and explores the resulting economic implications. This study provides a comprehensive review of the impacts of climate change on agricultural systems. It highlights the significance of human adaptation strategies, assesses potential regional disparities in agricultural vulnerability, and examines projected shifts in food production patterns and market prices in response to changing climatic conditions.

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Regional climate effects, Physical effects ,Adaptations,Agriculture, Climate change,

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This review explores the antidiabetic mechanisms of Pyrus pashia, such as the inhibition of key carbohydrate-hydrolysing enzymes (?-amylase and ?-glucosidase), enhancement of insulin secretion, and potent antioxidant and anti-inflammatory effects. In vitro and in vivo studies have demonstrated the plant's ability to lower blood glucose levels, improve glucose tolerance, and protect pancreatic ?-cells from oxidative damage.Pear fruits have been reported to contain abundant bioactive compounds and exhibit antidiabetic activity. In this study, pear (Pyrus pashia) fermentation broth was sequentially extracted by five solvents with increasing polarity (petroleum ether, chloroform, ethyl acetate, n-butanol, and water) to evaluate its antioxidant and hypothermic activities, and then the main compounds of the fraction with the highest activity were assessed, which might be responsible for such activities.Eleven monomeric compounds were seriatim examined for ?-glucosidase inhibitory activity to fish out anti-diabetic components. For the first time, this study delineated pear peel's anti-diabetic prospect of treatment for type 2 diabetes.

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 Keywords

Phyrus pashia , antidiabetic activity, diabetes

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Aquaculture is a vital sector in global food production, yet its success is heavily dependent on optimal water quality management. This research investigates the application of fuzzy modeling to assess and predict key water quality parameters in aquaculture systems. Recognizing the inherent complexities and uncertainties in aquatic environments, fuzzy logic provides a robust framework for integrating diverse parameters such as temperature, dissolved oxygen, pH, ammonia levels, and turbidity. Through the development of a comprehensive fuzzy model, this study aims to analyze the interactions between various water quality factors and their impacts on aquatic species health, growth rates, and overall system productivity. By employing fuzzy inference systems, the research enables better decision-making for aquaculture management, allowing stakeholders to adapt to fluctuating environmental conditions and optimize aquaculture practices. The findings highlight the effectiveness of fuzzy modeling as a tool for improving water quality monitoring and management strategies, ultimately contributing to more sustainable aquaculture operations. This approach not only enhances the resilience of aquaculture systems but also supports the long-term viability of aquatic resources in the face of environmental challenges.

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Aquaculture, Modeling, Fuzzy, Membership function, Analysis, Water quality

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This review article discusses the disruptive possibilities of no-code AI in closing the skills gap related to AI in the Software as a Service (SaaS) environment. These platforms democratize development of AI and enable non technical professionals, engineers, project and line managers, and business analysts to directly work with artificial intelligence tools creating more collaboration and innovation. Its paper discusses the advantages of no-code AI such as the faster development loop, economical, and even more accessible and compares it to other conventional AI development paradigms. The review demonstrates, via case studies, the benefits of the combination of different data sources through the no-code platform to create more efficient AI models and decision making. Their implications to the practitioners and policymakers are outlined, and it is conveyed that education, training, and universal technological policies are necessary. At the conclusion of the paper, recommendations as to the future research are provided, where the emphasis was made on the long-term effect of no-code AI systems, the potential of their cross-industry application, and the creation of the best practice frameworks, in which such systems can be deployed.

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 Keywords

No-code AI, AI skills gap, SaaS ecosystems, machine learning, democratization of AI, data integration, predictive models, software development, AI adoption, cross-functional collaboration, AI empowerment.

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Creative Commons Attribution 4.0 and The Open Definition

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Abutilon crispum, Anti-inflammatory activity, Phytochemical screening, Soxhlet evaporation, Aspirin.

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Creative Commons Attribution 4.0 and The Open Definition