Volume 13 | Issue 5 |

 Abstract

Background: Seasonal variations influence dietary habits and nutritional status. This study examines the impact of seasonal changes on dietary diversity among individuals aged 13 years and above in Surat City. Objectives: The study aims to assess seasonal variations in dietary intake, analyse their effect on meal frequency and nutritional status, and explore the association between seasonal dietary habits and BMI categories. Methods: A cross-sectional study was conducted with 500 participants across four age groups. Nutritional status was assessed using BMI, and seasonal dietary preferences were analysed through structured questionnaires and dietary recall across monsoon (July-October), summer (May-June), and winter (November-February). Results: Significant variations were observed in dietary intake and BMI across seasons. Winter (31.4%) recorded the highest intake of high-calorie and protein-rich foods, with 34.4% in the normal BMI range and 29.9% classified as Obese-I, leading to the highest overweight and obesity prevalence (47.1%). Summer (4%) had the lowest meal frequency, with 35% underweight individuals. Monsoon (7.2%) showed a balanced dietary pattern, with 25.0% categorized as underweight or normal weight. Conclusion: Seasonal changes affect dietary intake, meal frequency and nutritional status, emphasizing the need for season-specific dietary interventions. Public health strategies should promote balanced seasonal diets to support optimal nutrition across age groups.

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 Keywords

Seasonal variations, Dietary diversity, Nutritional status, Meal frequency, Body Mass Index (BMI), Obesity prevalence, Seasonal dietary habits

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Creative Commons Attribution 4.0 and The Open Definition

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Food Labeling is critical in educating consumers on the nutritional value, ingredients, and health claims of food products. The lack of knowledge, indifferent attitude, and improper practice of food labelling can contribute to unhealthy food choices, especially among young adults. This study was conducted to evaluate the baseline knowledge, attitude, and practice (KAP) of university students on food labelling, introduce an educational intervention, and test its effectiveness. A standardized questionnaire was applied to assess participants' pre-intervention KAP levels, and this was followed by an educational session in the form of a PowerPoint presentation. Post-intervention assessment was done via the same questionnaire. The results showed that there was an improvement in participants' knowledge, where the percentage of students showing good knowledge improved from 40% to 72%. Attitudinal changes were noted, with an increase in students with good attitudes toward food labelling from 10% to 44%. The findings are a strong demonstration that specific, educational interventions targeting consumer literacy will increase positive beliefs and stimulate thoughtful food selection. Ongoing encouragement through interactive instructional strategies could contribute to even further enhanced food label understanding and integration into everyday eating habits.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Food labelling, nutrition awareness, dietary choices, students, consumer education

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

B.Ed prashiksuko mein siksha patrata pariksha ke prati abhivrutti ka adhyayan

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Creative Commons Attribution 4.0 and The Open Definition

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B.Ed prashiksuko mein siksha patrata pariksha ke prati abhivrutti ka adhyayan

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Creative Commons Attribution 4.0 and The Open Definition

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In recent years, wheat classification has seen vast improvements with the integration of machine learning.The classification models efficacy, however, heavily depends on the careful tuning of model parameters. This paper reviews advancements in wheat classification models, emphasizing hyperparameter optimization techniques. Various tuning methods such as Grid Search, Random Search, Bayesian Optimization, and others are explored in the context of wheat classification. Ultimately optimized models promise high accuracy and efficiency, challenges such as over-tuning, scalability, and computational costs are discussed in later in this article. The review also revealed the key role of hyperparameter tuning in advancing wheat classification, opening the novel way for better agricultural outcomes.

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 Keywords

Wheat classification, machine learning, hyperparameter optimization, Grid Search, Random Search, Bayesian Optimization,

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Creative Commons Attribution 4.0 and The Open Definition

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Human development is a complex, lifelong process influenced by biological, psychological, and social factors. This research article explores the critical stages of human and child development, highlighting major theories, key developmental milestones, and the impact of environmental and genetic factors. Special attention is given to cognitive, emotional, and social development in children, considering the contributions of prominent theorists such as Piaget, Erikson, and Vygotsky. Understanding human and child development is crucial for educators, psychologists, and policymakers in shaping interventions that support healthy growth.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Human Development, Child Development, Cognitive Development, Emotional Growth, Socialization, Lifespan Development

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Creative Commons Attribution 4.0 and The Open Definition

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Due to bacterial infections, especially from Aeromonas hydrophila, a main pathogen in freshwater aquaculture, global aquaculture suffers significant difficulties. Diseases, including motile aeromonad septicaemia (MAS), which this bacterium produces, have substantial death rates and financial losses. Using antibiotics extensively to fight A. hydrophila has resulted in the development of antibiotic-resistant strains, therefore reducing the efficacy of therapy and generating public health issues. Consequently, there is an increasing demand for substitute, environmentally acceptable, sustainable methods to control bacterial diseases. Promising is bacteriophage therapy, in which particular bacteria are targeted and killed using viruses (bacteriophages). Phages have great selectivity, infecting just the intended bacteria, and they could fight strains resistant to many drugs. Phages can also self-replicate at the infection site, therefore reducing ecological disturbance and causing a weak immunological reaction in fish. The promise of phage therapy as a focused substitute for antibiotics in aquaculture in the control of A. hydrophila is investigated in this review. It goes over the benefits of phage therapy over conventional antibiotics, summarises present studies, and outlines future research requirements. The application in aquaculture is the public view of bacteriophage treatment, including elements of safety, efficacy, and cultural acceptance.

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 Keywords

Bacteriophage therapy, Aeromonas hydrophila, Antibiotic resistance, Aquaculture, Public perception

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Creative Commons Attribution 4.0 and The Open Definition

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The rapid expansion of big data has led to significant challenges in data processing, requiring efficient and intelligent optimization techniques to enhance performance. Traditional data processing methods often struggle with high computational complexity, scalability issues, and real-time data handling. This paper presents an intelligent optimization technique designed to improve data processing performance in big data environments. The proposed approach integrates machine learning-based optimization, heuristic algorithms, and distributed computing frameworks to enhance data retrieval, storage efficiency, and processing speed. By leveraging intelligent resource allocation, task scheduling, and adaptive learning mechanisms, the system dynamically adjusts to workload variations, reducing latency and improving throughput. Experimental results demonstrate that the intelligent optimization technique significantly enhances processing efficiency compared to conventional methods. The framework achieves better performance in terms of execution time, fault tolerance, and energy efficiency, making it a viable solution for large-scale data-intensive applications. This research work emphasis in the domain of big data analytics that offers some key features like robust, scalable, and intelligent optimization model that enhances decision-making and overall system performance. Future work will explore further refinements and integration with emerging technologies such as edge computing and federated learning for enhanced real-time data processing.

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 Keywords

Deep learning Algorithm, Confusing Matrix- CF, Random Forest Algorithm, Gradient Boosting Algorithm, GA- Genetic Algorithm, Ant Colony Optimization -ACO.

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Creative Commons Attribution 4.0 and The Open Definition

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Education is undergoing a significant transformation with the integration of Artificial Intelligence (AI) and digital learning platforms. AI is revolutionizing personalized learning, assessment, and administrative tasks, while digital platforms offer accessible and flexible learning opportunities. This paper explores the impact of AI and digital learning platforms on education, highlighting their benefits, challenges, and future implications. The study is based on recent advancements and research, providing a fresh perspective on how AI and digital tools are reshaping teaching and learning.

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 Keywords

Artificial Intelligence, Digital Learning Platforms, Personalized Learning, Education Technology, AI in Education.

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Creative Commons Attribution 4.0 and The Open Definition

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The vision of Viksit Bharat underscores the need for the improvement & inclusive education system to change India into developed India. This paper shows the strategic pathways needed for addressing the challenges of 21st Century. The main moto in this transformation is the implementation of the New Education Policy 2020. The study emphasizes the Integration of technology to improve the method of teaching and learning process and promoting digital literacy & to empower learners across diverse socio economics background. It also examines the importance of skill development. The paper indicates for teacher training programs aimed at modernizing pedagogical approaches & fastening critical thinking. This paper outlines a roadmap for leveraging education as a tool to achieve the goals of Viksit Bharat.

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Viksit Bharat, Skill development, NEP digital literacy.

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Saracaasoca (Roxb.) De. Wild., commonly known as Ashoka and classified under the family Caesalpinaceae, is renowned for its traditional and pharmacological significance. In light of the growing preference for natural remedies over synthetic drugs due to their minimal side effects, medicinal plants like Ashoka are receiving increased attention. Traditionally, Ashoka has been employed in managing conditions such as dysentery, colic, piles, biliousness, dyspepsia, and ulcers. It is also recognized for its central nervous system (CNS) depressant effects and its role in addressing irregular menstrual cycles. The plant is a rich source of bioactive compounds, including glycosides, flavonoids, tannins, and saponins, which exhibit promising therapeutic and diagnostic potential. Extracts derived from its leaves, flowers, fruits, and bark have demonstrated antimicrobial, anti-inflammatory, anti-menorrhagia, antidiabetic, anthelmintic, and analgesic activities. This review highlights the medicinal applications, phytochemical composition, and pharmacological attributes of Saracaasoca, underscoring its importance in contemporary healthcare systems.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Saraca asoca; plant extracts; herbal medicine , pharmacognostic features

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Creative Commons Attribution 4.0 and The Open Definition