Volume 14 | Issue 5 |

 Abstract

Background Adolescent girls are highly vulnerable to nutritional deficiencies due to rapid physical growth, increased nutritional requirements, poor dietary habits, and inadequate nutritional awareness. Nutritional education plays a significant role in improving healthy dietary practices and promoting overall well-being among adolescents. Objectives 1. To assess the effectiveness of a structured nutritional education program on knowledge regarding nutrition among adolescent girls. 2. To evaluate changes in dietary habits and nutritional status after the intervention. 3. To determine the association between post-test scores and selected demographic variables. Methodology A quantitative randomized controlled study was conducted among 100 adolescent girls studying in selected schools of Nawanshahr, Punjab. The participants were selected using simple random sampling technique and equally divided into experimental and control groups. The experimental group received a structured nutritional education program, while the control group received routine school health education. Data were collected using a structured knowledge questionnaire, dietary habits checklist, and nutritional assessment scale. Descriptive and inferential statistics were used for data analysis. Results The findings of the study revealed that the experimental group showed significant improvement in knowledge scores, dietary habits, and nutritional status after administration of the structured nutritional education program. The mean post-test knowledge score of the experimental group was higher than the control group, and the calculated 't' value was statistically significant at p < 0.05 level. Improvement in healthy dietary behaviors such as increased intake of fruits, vegetables, and iron-rich foods was also observed. Conclusion The study concluded that the structured nutritional education program was effective in improving nutritional knowledge, dietary habits, and nutritional status among adolescent girls. School-based nutritional interventions can contribute significantly to the promotion of adolescent health and prevention of nutritional deficiencies.

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 Keywords

Structured Nutritional Education Program, Adolescent Girls, Dietary Habits, Nutritional Status, Nutrition Education, School Health.

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Abstract: The study focuses on two major objectives of this research. First, to comprehend the viewpoints that influence gender-neutral language; second, to ascertain how these insights enhance student instructors' attitudes towards gender-neutral language to foster inclusivity. This study was initiated by conducting a qualitative approach on college students of the Education Department from the government college of H.N.B. Garhwal University, Srinagar, Uttarakhand. The sample size for this study was 30. After the survey, content analysis was implemented, followed by the conceptual analysis and thematic analysis method for categorising the data into broader themes. This study focused on eight factors that are expected to influence gender-neutral language. The basic factors included are gender in teaching and learning, awareness, attitude, challenges, and barriers, the learning environment of the student teachers, the use and impact of language and linguistics, the impact of education on gender-neutral language, and language preferences for inclusivity. The findings indicate that the respondents agreed that all these factors influence gender-neutral language and that language neutrality should be emphasised at the teacher training level. Through this study, the researcher determined the awareness of gender-neutral language and its perspective among the pupil teachers. A collaborative perspective to promote the use of gender-neutral terms and to remove stereotypes and prejudice from society is proposed, which is expected to attain growth in the future direction of gender inclusivity. These study specifications can be applied to various sample sizes and age ranges.

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 Keywords

: gender-neutral language, gender inclusivity, pupil teachers, teacher education, gender awareness.

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The current research investigates how cultural translation affects the gender-based experience of displacement in three selected contemporary Indian novels. The research uses The Namesake, The Ministry of Utmost Happiness, and A Married Woman to study physical, emotional, psychological, and cultural aspects of displacement through their character portrayals. The study investigates how women form their identity while navigating between different cultures in societies that follow both patriarchal and postcolonial systems. The research employs qualitative textual analysis to examine migration themes, cultural conflict, memory and trauma, and identity reconstruction in the selected novels. The study uses postcolonial theory, feminist literary theory, and diaspora studies as its theoretical foundation to examine how cultural translation creates different experiences of displacement for different genders. The findings show that women character's experience more intense displacement because of three factors, which include cultural expectations, social restrictions, and patriarchal norms. The novels demonstrate that cultural identity remains in constant evolution as people navigate between their cultural heritage and contemporary values, their homeland and diaspora, and their personal desires and societal responsibilities. The research demonstrates that present-day Indian fiction dismantles established concepts of identity and home and belonging through its emphasis on marginalized perspectives and its depiction of female characters. The study adds to current research about postcolonial identity and diaspora and gender and cultural changes in Indian English literature.

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Cultural Translation, Gendered Displacement, Postcolonial Identity, Diaspora, Contemporary Indian Fiction

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India's dispute resolution ecosystem stands at a critical inflection point. With over 50 million cases pending before courts across the country, the promise of Online Dispute Resolution (ODR) has never been more urgent or more contested. This article examines the practical and human dimensions of ODR within the Indian legal context -- drawing upon the existing statutory framework, practitioner experiences, and the socio-cultural factors that shape how disputes are navigated in cyberspace. It argues that while ODR holds transformative potential for expanding access to justice in India, its practitioners must grapple with unique human, technological, and institutional challenges that have no straightforward analogues in traditional Alternative Dispute Resolution (ADR) practice.

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ODR, Mediation, Dispute Resolution.

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Water pollution due to floating waste, plastics, algae, and suspended particles has become a major environmental issue in lakes and other water bodies. Conventional cleaning methods require large manpower, high operational cost, and continuous maintenance. To overcome these problems, a Solar Powered Lake Surface Cleaning Robot is proposed. The robot utilizes solar energy as its primary power source and integrates IoT - based remote monitoring and control for autonomous cleaning operations. The proposed system consists of a floating robotic platform equipped with solar panels, DC motors, conveyor belt mechanism, ultrasonic sensor, infrared sensor, and turbidity sensor. The conveyor mechanism collects floating waste from the water surface and transfers it into a storage container. The ultrasonic sensor helps in obstacle detection and autonomous navigation, while the turbidity sensor monitors water quality in real time. The robot operates in both manual and autonomous modes using Wi-Fi communication and Android application control. Experimental analysis shows that the system can remove approximately 85-90% of floating waste from the lake surface while operating with low power consumption and minimum environmental impact. The buoyancy calculations confirm that the robot can safely float and carry additional waste load without sinking.

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Solar Energy, Lake Cleaning Robot, IoT, Water Pollution, Conveyor Mechanism, Autonomous Robot, Environmental Protection.

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This study analyses the stock price behaviour of selected Indian Information Technology (IT) and Artificial Intelligence (AI) companies, namely Tata Consultancy Services (TCS), Infosys, and HCL Technologies, over the period 2021-2025. The research focuses on the application of technical analysis tools such as Simple Moving Average (SMA), Relative Strength Index (RSI), and Moving Average Convergence Divergence (MACD) to evaluate market trends, price momentum, and trading signals. Secondary data consisting of daily stock prices were collected from reliable financial platforms. The findings reveal that technical indicators play a significant role in identifying price patterns, overbought and oversold conditions, and trend reversals. The study also highlights that combining multiple indicators improves prediction accuracy and enhances investment decision-making. The research contributes to understanding the effectiveness of technical analysis in the Indian IT & AI sector.

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Technical Analysis, SMA, RSI, MACD, IT Sector, Stock Market.

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A 60-year-old male with history of stroke for past 5 months had complaints of walking difficulty with asymmetrical weight shifts, with hemiplegia on the left side. He was diagnosed as sub acute stroke with the investigations of MRI and CT scan. Multi-directional step exercises along with weight shifting for 4 weeks is given to the patient as treatment plan.

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Stroke, Multi-directional Step Exercise, Balance, Gait

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The advent of cloud computing has fundamentally changed the way technology is used, as it enables many (most) companies to access an abundance (virtually unlimited) of computing resources (capacity) without making large investments in physical infrastructure (hardware). However, despite the flexibility that cloud computing provides and its low cost, efficient management of resources in a cloud environment (private/public/mixed) is often challenged when workloads change dynamically. Changes in the number of users accessing the cloud (demand), traffic spikes (demand), and unanticipated loads (computation) create significant inefficiencies in traditional static resource provisioning systems. All three of these types of issues result in inefficiently provisioning resources due to over- or underprovisioning. Auto scaling of cloud computing resources (capacity) has emerged as the best solution for dynamically adjusting cloud resources based on changing workloads. This research investigated various types of auto-scaling methodologies / strategies reactive, proactive, predictive and hybrid models - in order to evaluate their effectiveness in providing the most effective cloud resource management capabilities. The research provides an organizational framework to compare the various auto scaling methodologies / strategies based on various defined metrics of performance (e.g., efficiency, compliance with SLAs, operating cost, response time and scalability) using a standard simulation methodology. The uniqueness of this study is that it provides a single benchmarking approach for all of the various scaling strategies compared at the same point in time (i.e., under the same experimental conditions) while providing detailed information about how to successfully implement them. The primary contribution of this research is to provide new academic and meaningful industrial insight into intelligent cloud elasticity strategies, along with practical recommendations to optimize scalable cloud implementations.

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Cloud Computing, Auto Scaling, Resource Management, Predictive Scaling, Hybrid Scaling, SLA Optimization, Cloud Elasticity

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Creative Commons Attribution 4.0 and The Open Definition

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The proliferation of e-commerce platforms has fundamentally transformed the way consumers purchase smartphones. Among the many factors influencing purchasing decisions, customer reviews have emerged as one of the most powerful determinants of consumer behavior in the digital marketplace. This research investigates the role of online customer reviews in shaping purchasing decisions for smartphones, examining how review volume, review valence, reviewer credibility, and review recency collectively influence consumer trust and purchase intent. Drawing on survey data from 450 respondents across diverse demographic groups, alongside analysis of behavioral patterns from leading e-commerce platforms, this study finds that 84% of online smartphone buyers consult customer reviews before completing a purchase. The research further demonstrates that negative reviews exert a disproportionately stronger effect on purchase abandonment than positive reviews on purchase motivation. These findings have significant implications for smartphone manufacturers, e-commerce retailers, and digital marketers seeking to optimize product presentation and consumer engagement strategies.

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customer reviews, online purchase behavior, smartphones, e-commerce, consumer trust, review credibility, digital marketing

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Creative Commons Attribution 4.0 and The Open Definition

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: Achieving the United Nations Sustainable Development Goals (SDGs) requires coordinated global action, efficient data exchange, and trustworthy collaboration among a wide range of stakeholders. This project proposes a cloud-based collaboration platform that enables international NGOs, government agencies, academic and research institutions, and other partners to securely upload, curate, and share SDG-related datasets. The system ensures data integrity, provenance, and immutability through blockchain-backed mechanisms, while non-fungible tokens (NFTs) are utilized to attribute datasets to their rightful contributors, promoting transparency, accountability, and contributor recognition.

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 Keywords

- NGO, SDG, Cloud Computing, Blockchain, Web Application, Collaboration, Machine Learning, Data Integrity.

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Creative Commons Attribution 4.0 and The Open Definition