Volume 13 | Issue 6 |

 Abstract

Social media platforms have revolutionized how individuals, particularly college students, access and consume information. This paper explores the impact of social media on the information-seeking behaviour of college students, focusing on their preferences, challenges, and outcomes. By analysing recent literature and survey data, the study highlights the dual role of social media as a tool for academic growth and a source of misinformation. Recommendations to optimize social media for effective information-seeking are also discussed.

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 Keywords

Social media, information-seeking behaviour, college students, academic resources, digital literacy.

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Amblyopia, commonly known as "lazy eye," is a neurodevelopmental disorder characterized by impaired vision, often due to misalignment, refractive issues, or other visual deficits. Early detection is critical to prevent long-term vision impairment. This project proposes a dual model approach leveraging artificial intelligence to enhance amblyopia diagnosis through both image-based and genetic risk analysis. The first model utilizes an image classifier to analyze eye images, identifying physical markers of amblyopia using convolutional neural networks (CNNs) or Vision Transformers. The second model incorporates Random Forest and Naive Bayes algorithms to evaluate genetic predispositions and familial risk factors, offering a probabilistic assessment of a child's susceptibility to developing amblyopia. A hybrid model integrates both the image-based and genetic-risk predictions, producing a unified risk score to improve diagnostic accuracy. This comprehensive diagnostic framework holds potential for early detection of amblyopia and a more personalized, predictive approach to pediatric eye care. By combining visual and genetic data, the proposed method aims to provide clinicians with a robust tool to address amblyopia risk more accurately and efficiently.

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 Keywords

Amblyopia, Artificial Intelligence, Convolutional Neural Networks, Image Classification, Genetic Risk Prediction, Random Forest, Naive Bayes, Hybrid Model, Vision Transformers.

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Abstracts: Mysore city is positioned well in tourism but its cluster has to be focused more to improve its promotional activities and facilities for attracting more number of international tourists. Tourism has become the world's largest industry, generating wealth and employment, opening the minds of both visitors and the visited to different ways of life. India has strong signs of becoming one of the emerging giants in world tourism. The main objectives of the study are to highlight the theoretical background of tourism industry in Mysore City: In general and to analyze demographic profile of tourist and to assess the tourist insights in different dimensions to visit Mysore city and also to study the different tourist places and the overall perception of tourists towards in Mysore city. Therefore finally this study covers the tourist perceptions towards Mysore city. To study the growth and development of tourist accommodation in Mysore city, To analyze the spatial distribution of accommodation in study area, the present study has been collected from primary data was collected by on the basis issue of questionnaire, and use sampling methods by visited few hotels and restaurants and gathered the information which is relevant to my study. Finally this study results majority of the tourist has strongly agreed and positive opinions about all tourist services available in Mysore City.

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Keywords: Tourism Development, Accommodation, Spatial Analysis and Mysore city

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Bioactive substances with potential antibacterial effects are abundant in red algae. In order to determine the antibacterial activity of a few red algae species, this study will analyze their proximate composition and biochemistry. Using conventional analytical techniques, the proximate composition--which includes moisture, ash, protein, fat, fiber, and carbohydrate content--was estimated. Biochemical components were also measured. By employing the agar well diffusion method, the antibacterial activity of red algal extracts was evaluated against both Gram-positive and Gram-negative bacterial strains as well as fungal pathogens. The findings showed that in addition to bioactive substances with antibacterial qualities, red algae also contain substantial amounts of proteins and carbs. Increased antibacterial and antifungal action, especially against Staphylococcus aureus, Escherichia coli, and Candida albicans. The comparatively low lipid content suggests that the antibacterial actions are caused by non-lipid bioactive molecules. One of the examined species showed greater inhibitory zones, indicating that it might be used as a natural antibacterial. In response to worries about antibiotic resistance, the results of this study demonstrate the possibility of red algal extracts as a substitute for manufactured antimicrobials. It is advised that more study be done on the characterization and purification of active chemicals in order to investigate their potential uses in industry and medicine. This study adds to the increasing interest in marine bioresources as long-term antibacterial agent sources.

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 Keywords

Red algae, antimicrobial activity, proximate composition, bioactive compounds, phenolics, flavonoids

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The integration of Artificial Intelligence (AI) into language education is reshaping traditional approaches to English language acquisition, especially within multilingual contexts such as India. This study investigates the impact of AI-powered tools--ChatGPT, Duolingo, and Grammarly--on improving linguistic competence, motivation, and learner autonomy among Indian engineering undergraduates. Employing a mixed-methods design, the study involved 120 intermediate-level English learners from engineering colleges across India. Quantitative data from pre- and post-tests assessing grammar, vocabulary, and writing skills were complemented by qualitative insights from semi-structured interviews and learner diaries. Results revealed statistically significant gains in all measured competencies in the experimental group, with enhanced learner engagement and self-directed learning. Nevertheless, challenges such as digital access disparities and over-dependence on AI tools persist. This article contributes to current discourse on AI-assisted language acquisition and offers context-sensitive pedagogical recommendations tailored to Indian bilingual and technical education settings.

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Artificial Intelligence, Engineering Students, English Language Skills, Language Learning Tools, India, Educational Technology, Bilingual Education

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Post Surgical wound infection is a rare but serious post-surgical complication. The basic line of treatment for dushta vrana is adopted here to manage the surgical site infected wound includes vranashodhana (wound cleaning) followed by vranaropana (wound healing). Ayurveda has effective internal medicines and local applications for the management of dushtavrana.

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Post-Surgical Infection Management using Ayurvedic Herbs: A Review

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Hemoglobin (Hb) abnormalities are commonly encountered in medical practice and represent a gateway to diagnosing a wide spectrum of clinical disorders. Understanding deviations in Hb levels--either elevated or decreased--requires a meticulous and methodical clinical approach. This article focuses on providing a comprehensive, stepwise diagnostic strategy for evaluating abnormal hemoglobin values, with an emphasis on interpreting red cell indices such as mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC). Diagnostic algorithms and decision trees are presented as clinical flowcharts to aid real-time diagnosis and enhance physician decision-making.

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Hemoglobin, Anemia, Polycythemia, MCV, MCH, MCHC, Diagnostic Algorithm, Clinical Decision Tree, CBC Reading, CBC interpretation, High Hb(Hemoglobin), Low Hb.

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With urban populations projected to reach 68% of the global total by 2050, cities face unprecedented challenges in managing transportation, energy, public safety, and citizen services. Big Data analytics is pivotal in smart city development, enabling real-time, data-driven solutions to enhance urban efficiency and quality of life. This paper investigates Big Datas transformative impact through a comprehensive literature review and case studies from Singapore, Copenhagen, Dubai, and Toronto. We explore applications in traffic management, energy optimization, crime prevention, and citizen engagement, while addressing challenges such as data privacy, interoperability, and social equity. Our findings underscore Big Datas potential to revolutionize urban ecosystems, emphasizing the need for ethical and technical frameworks to ensure inclusive and sustainable outcomes.

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Big Data Smart Cities Urban Innovation Data-Driven Decision Making IoT (Internet of Things) Urban Analytics Sustainable Development Intelligent Transportation Systems Smart Infrastructure Real-Time Data Urban Planning Digital Governance Predictive Analytics Data Integration Urban Mobility

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Sustainable development is the development that meets the needs of the present without compromising the ability of future generation to meet their own needs. The UN sustainable development goals approved by the UN general assembly in September 2015 to secure all round development to the marginalized and maintain environment sustainability. Women have a vital role in development and environment sustainability therefore their participation is essential to achieve sustainable development. Gender Equality is a fundamental human right as well as it is necessary for Sustainable World and it is a significant goal of Sustainable Development Goals. Indian women always remain underprivileged group in accessing the economic, political and socio-cultural rights because of the patriarchal nature of Indian society. Therefore, the focus of the paper is to explore the present scenario of Gender Equality in India in comparison to the other countries of the various parts of the world. The study is exploratory and analysed qualitatively by using secondary data resources. The paper is expected to help policy makers and civil society to understand the significance of Women Empowerment and Gender Equality in the successful implementation of Sustainable Development Goals in India.

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Sustainable Development, Sustainable Development Goals, Gender Equality, Human Right, Women Empowerment.

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The purpose of the study was to evaluate the effectiveness of Carolina Curriculum (Infant & Toddler) intervention to improve developmental milestones among children with developmental delay. METHOD: A Quasi-Experimental (Single group Pretest- Posttest) design was adopted for the study. Convenience sampling was used for the study. 25 children with developmental delay ranging between the age group 2- 5 years were included in the study. Developmental milestones of the participants were assessed (pre-test) using the Carolina Curriculum for Infant and Toddler with Special Needs (CCITSN). The Carolina Curriculum intervention was given to the participants, with a duration of 1hour per session, five days a week for 12 weeks for each child. Developmental milestones of the participants were reassessed (post-test) using Carolina Curriculum for Infant and Toddler with Special Needs (CCITSN). The pre-test and post- test developmental milestones were analysed and interpreted. RESULTS: Based on the analysis, there were significant changes observed in the developmental milestones and most of the improvements had been shown in motor skills [upright: posture & locomotion (96%), prone on stomach (84%), bilateral skills (76%)], and cognitive skills [problem solving (76%), and Attention & Memory: Visual/ Spatial skills (72%)]. CONCLUSION: The study demonstrated that Carolina Curriculum interventions are effective in improving developmental milestones among children with developmental delay.

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Carolina Curriculum Intervention, Developmental Milestone, Developmental Delay, Motor skills and Cognitive skills.

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