Volume 14 | Issue 3 |

 Abstract

Ek Ladki ko Dekha Toh Aisa Laga , directed by Shelley Chopra Dhar, is a romantic comedy-drama movie based on an LGBTQ and displays the same gender love story inspired by the novel "A Damsel in Distress" by P.G. Woodhouse written in 1919. Ek Ladki ko Dekha Toh Aisa Laga is a story of a lesbian girl Sweety Chaudhary who belongs to a religious and traditional Punjabi family. This film is centred around young Sweety Chaudhary from Moga in Punjab who has spent her life hiding her truth from those dearest to her, but the film is not about same-gender love alone. It is about living and loving as we choose, not allowing societal norms around age, gender, religion or anything else to suffocate us and hamper or personal or professional choices. Drawing on theories of performance, heteronormativity, and cultural reception, this paper explores how the film challenges patriarchal expectations, redefines romantic conventions, and expands the discourse on same-gender love in Indian popular culture. It further analyzes how the film's moderate box office success and critical acclaim signal a gradual but meaningful shift in public perception. Ultimately, the paper argues that Ek Ladki Ko Dekha Toh Aisa Laga functions not merely as entertainment, but as a political and pedagogical text that encourages audiences to "rethink love" in a changing socio-legal landscape.

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 Keywords

Gender Performativity, Judith Butler, Lesbian Identity, LGBTQ+ in Indian Cinema, Post-Section 377, Queer Theory, Cultural Reception

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Emotional Quotient (EQ), also known as Emotional Intelligence (EI), has become a vital psychological concept that significantly affects personal well-being, relationships, and social interactions. In the areas of child and women welfare, EQ plays a crucial role in fostering resilience, improving decision-making abilities, regulating emotions, developing leadership skills, and promoting social empowerment. This review explores the foundational concepts of EQ, important theoretical frameworks, and its impact on child development and women's welfare. It draws on established models from researchers like Peter Salovey and John D. Mayer, as well as the work of Daniel Goleman, to summarize the literature on how emotional skills enhance mental health, educational success, protection against abuse, leadership abilities, and socio-economic empowerment. The review also addresses intervention strategies and policy implications. The findings suggest that enhancing EQ at the individual, family, and community levels can greatly improve welfare outcomes for both children and women.

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Emotional Quotient, Emotional Intelligence, Child Welfare, Women Empowerment, Mental Health, Social Development

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Background: Gingival phenotype (GP) represents the morphologic characteristics of gingival tissue and underlying bone. It plays a significant role in periodontal stability, orthodontic treatment planning, and implant success. This study evaluated the correlation between gingival phenotype in maxillary anterior teeth and vertical facial types and gender using Cone Beam Computed Tomography (CBCT). Aim: To assess the association between gingival thickness and vertical facial types and gender. Materials and Methods: A cross-sectional analytical study was conducted using 30 archived CBCT scans selected through simple random sampling. Gingival thickness and alveolar bone thickness were measured at standardized levels. Skeletal classification was determined using ANB angle. Statistical analysis was performed using SPSS version 21 with significance set at p < 0.05. Results: Comparison of gingival thickness revealed that females exhibited significantly greater values than males at the CEJ and coronal to the bone crest (p < 0.05). However, no significant differences were observed at 3 mm and 5 mm apical to the CEJ. Alveolar bone thickness did not differ significantly between sexes at either 3 mm or 5 mm apical to the CEJ (p > 0.05). Analysis of facial type distribution showed Type I as the most prevalent in both sexes, followed by Type II and Type III, with no statistically significant sex-related differences (p = 0.824). Conclusion: Gingival phenotype may show correlation with vertical skeletal morphology and gender, which can influence interdisciplinary treatment planning.

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 Keywords

Gingival phenotype, Cone beam computed tomography, Vertical facial pattern, Gingival thickness, Maxillary anterior teeth, Periodontal biotype.

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Alzheimer's disease (AD) is a progressive neurological disorder that affects memory, cognition, and brain structure. Accurate and early diagnosis is essential for effective treatment and clinical decision-making. This paper presents a deep learning-based framework for automated detection and stage classification of Alzheimer's disease using brain Magnetic Resonance Imaging (MRI) scans. A dataset containing approximately 6,400 MRI images was utilized and categorized into four stages of disease severity. Image preprocessing techniques, including Contrast Limited Adaptive Histogram Equalization (CLAHE) and Enhanced Super-Resolution Generative Adversarial Network (ESRGAN), were applied to improve contrast and resolution. An ensemble classification model combining MobileNetV2 and DenseNet121 architectures was implemented using TensorFlow and Keras. The performance of the system was evaluated using accuracy, precision, recall, and F1-score metrics. Experimental results demonstrate that the proposed approach improves classification performance and provides reliable detection of Alzheimer's disease stages. The system offers a computationally efficient and scalable solution for computer-aided medical diagnosis.

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Keywords: Alzheimer's disease, MRI, Deep learning, MobileNetV2, DenseNet121, Image enhancement, CLAHE, ESRGAN, Classification

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Fluorenyl-based hydrazide derivatives represent a promising class of compounds with potential antimicrobial properties due to their lipophilicity and structural versatility. In this study, a series of Hydrazide -- N'-(9H-fluoren-9-ylidene) acetohydrazide, 2-chloro-N'-(9H-fluoren-9-ylidene) acetohydrazide, N'-(9H-fluoren-9-ylidene)-2-methylpropanehydrazide, N'-(9H-fluoren-9-ylidene)-2,2-dimethylpropanehydrazide, N'-(2,7-dichloro-9H-fluoren-9-ylidene) benzohydrazide, and N'-(2,7-dichloro-9H-fluoren-9-ylidene)decanehydrazide were synthesized through condensation of 2,7-dichlorofluorenone hydrazone with various acid chlorides. The compounds were characterized using spectroscopic techniques including IR and NMR. Their antimicrobial activity was assessed against Gram-positive and Gram-negative bacterial strains, as well as Candida albicans. Several derived hydrazides exhibited moderate to significant antimicrobial activity, especially against E. coli and Candida albicans. These results reinforce the potential of fluorenyl-hydrazide as a platform for antimicrobial drug design.

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Hydrazide derivatives; Fluorenone hydrazone; Acid chlorides; Schiff bases; antimicrobial activity

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Pregnancy is a unique physiological, psychological and spiritual process where maternal environment plays a decisive role in shaping fetal development. Ayurveda conceptualizes this through Garbha Samskara, a systemic approach for nurturing the fetus by regulating maternal diet, lifestyle, emotions and sensory inputs. Among all sensory modalities, sound (shabda) is regarded as the most powerful and subtle influence. Raga chikitsa, the therapeutic application of Indian classical music utilizes structured sound vibrations to harmonize the body, mind and consciousness. This article comprehensively explores the role of music therapy during pregnant state by integrating Ayurvedic principles with classical scriptural examples from the Vedas, Ramayana, Mahabharata and Bhagavatha and modern scientific evidence and establishes prenatal exposure to sattvika sound and Raga based music contributes significantly to maternal well-being and holistic fetal development.

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Raga chikitsa, Music therapy in pregnancy, Maternal-Fetal bonding, Integrative prenatal care.

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Creative Commons Attribution 4.0 and The Open Definition

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Architectures, Agentic AI, multi-agent systems, human-in-the-loop, safety, small LMs, coordination.

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Creative Commons Attribution 4.0 and The Open Definition

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Livestock diseases pose a major challenge to farmers as they directly impact animal health, agricultural productivity, and economic stability. Early identification of diseases is essential to prevent the spread of infections and reduce losses. However, traditional diagnostic methods mainly rely on manual observation and veterinary expertise, which may not always be accessible in rural areas. To address this issue, this paper presents a deep learning-based livestock disease detection system that analyzes images of animals to identify possible diseases. The proposed system uses a Convolutional Neural Network (CNN) to automatically learn visual patterns associated with different livestock diseases. Farmers can upload images of affected animals through a simple web interface, and the system predicts the disease along with recommended remedies. The application integrates image processing, deep learning techniques, and database management to provide a practical and user-friendly solution for livestock health monitoring. Experimental evaluation demonstrates that the proposed approach achieves reliable classification performance and supports faster disease identification. By enabling early diagnosis and timely treatment recommendations, the system can assist farmers in improving livestock management and reducing dependency on immediate veterinary assistance.

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 Keywords

Livestock Disease Detection; Deep Learning; Convolutional Neural Network (CNN); Image Classification; Artificial Intelligence in Agriculture; Animal Health Monitoring; Smart Farming

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Index Terms -- Machine Learning, Sustainable Transportation, Carbon Emission Analysis, Random Forest Regression, Green Mobility Index.

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Creative Commons Attribution 4.0 and The Open Definition

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Music has been closely connected with spirituality since ancient times. In many cultures, music is not only a form of artistic expression but also a powerful medium for connecting with the divine and achieving inner peace. In the Indian tradition, music is often viewed as a path to spiritual realization. The philosophical idea of Nada Brahma suggests that the entire universe is made of sound and vibration, and through music one can experience this universal energy .Indian music has deep roots in sacred texts such as the Samaveda, where hymns were chanted in melodic patterns for spiritual and ritual purposes. Over time, music developed into various classical and devotional forms that aim to elevate the mind and soul. Concepts like Raga are designed not only to create melodies but also to evoke specific emotions and spiritual moods. The influence of the Bhakti Movement further strengthened the relationship between music and devotion, as saints and poets used songs to express love and surrender to God. Through practices such as bhajans, kirtans, and devotional compositions, music became a form of spiritual practice and meditation. Thus, spirituality in music reflects the belief that sound and melody can transcend ordinary experience, helping individuals achieve emotional purification, inner harmony, and a deeper connection with the divine.

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 Keywords

Bhajan , Kirtan, Samaved, Devotional, Music, Bhakti, Spiritual ,Divine

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Creative Commons Attribution 4.0 and The Open Definition