Volume 13 | Issue 3 |

 Abstract

?????? ??? ????? ???? ????? ????? ?? ?????? 3.7 ????? ?? ????? ??? ????????? ?? ??? ???? ????? ???? ???? ??? ??, ???? 1947 ??? ????-????????? ?????? ?? ????? ???? ?? ????????? ???? ?? ????? ????? ?????? ??? ???? 2011 ?? ?????? ?? ??????, ???? ??? ????? ???? ???????? ?? ???????? 27,72,264 ??? 27 ??? ?? ???? ?? ?? ????? ??? ?? ??? ????? ?????? ?????? ???? ???????? ?? ????? ??? ??? ??? ?? ??? ???? ??? ???????? ????? ?????? ?????? ?? ???? ?????? ??? ???? ????????? ?? ??????? ??? ???????? ????????? ?? ????? ?? ?????? ???? ??? ??? ???? ??? ?? ?? ??? ??????? ????????? ?????? ??? ?? ???????? ?? ??????? ?? ?? ????? ???? ?? ?? ??????? ??? ??? ????? ?????? ?????? ?? ?????? ???? ??? ??? ?????? ?? ??? ????? ???? ??? ?????? ?? ??????? ???? ?????? ?? ???? ????

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The paper study analyses Thomas Harris's Hannibal and Hannibal Rising using Social Cognitive Theory (SCT) by Albert Bandura. It explores how Hannibal Lecter's transformation from a traumatized child to a sophisticated predator is shaped by observational learning, reciprocal determinism, and moral disengagement. In Hannibal Rising, Hannibal experiences severe trauma during World War II, witnessing violence and cannibalism, which later influences his behaviour. Through observational learning, he adopts violent tendencies from his environment and refines them under the guidance of his aunt, Lady Murasaki. His intelligence and adaptability allow him to develop a self-regulated moral code, justifying his actions as acts of justice. In Hannibal, Lecter's fully formed persona demonstrates reciprocal determinism, where his thoughts, actions, and environment reinforce his identity as both a cultured intellectual and a ruthless predator. He engages in moral disengagement, rationalizing his killings by targeting only those he deems unworthy, thus detaching himself from guilt. His ability to manipulate and control situations reflects his mastery of learned behaviour. By applying Social Cognitive Theory, this study provides a deeper understanding of Hannibal Lecter's psychology beyond typical criminological and psychoanalytic perspectives. It highlights how external influences, cognitive processes, and behavioral reinforcement shape identity and moral reasoning. This analysis contributes to broader discussions on learned behaviour, trauma, and the complexities of villainous characters in literature.

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 Keywords

: Social Cognitive Theory, Observational Learning, Reciprocal Determinism, Moral Disengagement, Trauma.

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The COVID-19 pandemic marked a paradigm shift in education, as it catalyzed the use of technology to overcome challenges in traditional teaching methods. This paper explores emerging trends in educational technology, focusing on Artificial Intelligence (AI), Virtual Reality (VR), Learning Management Systems (LMS), and their integration into blended and hybrid learning models. AI-based learning tools have revolutionized education through customized learning, auto-assessment, and real-time data analytics that help refine the teaching strategies. VR has provided immersive learning; students are exposed to interactive simulations of complex ideas, making learning more efficient and productive. Learning management systems have been at the forefront of online learning as they manage all content, facilitate communication, and provide an opportunity for assessment. Such progressions have allowed a smooth shift toward blended learning: a mixture of face-to-face and digital instructions. Success with Ed-Tech in post-pandemic learning indicates a likelihood of access, engagement, and better outcomes in diverse populations. The National Education Policy 2020 is the backbone in integrating technology in education, digital infrastructure, and skill development through learner-centric approaches. AI tools, VR, and LMS solutions have therefore bridged the gaps in education, making it more inclusive, equitable, and relevant to current needs by aligning with NEP 2020. This paper points out how these innovations address post-pandemic challenges and transform education, preparing students for a technology-driven future in alignment with policy objectives and global trends.

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Online Learning, AI & VR in learning, Collaborative learning, Educational Technology in NEP2020

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This research examines the impact of perceived parental emotional immaturity in terms of inconsistent emotional responses, restricted empathy, and psychological control on self-autonomy and emotional regulation in young adults in India. With a quantitative, correlational design, 132 participants between 18 and 29 years were surveyed through the Parental Bonding Instrument (PBI), Emotional Regulation Questionnaire (ERQ), and Index of Autonomous Functioning (IAF). Findings indicated maternal care correlated positively with self-autonomy (r = 0.22, p < 0.05) and cognitive reappraisal (r = 0.18, p < 0.05) and decreased emotional suppression (r = -0.26, p < 0.01), reflecting its protective function. In contrast, overprotection by both parents adversely affected autonomy (maternal: r = -0.21, p < 0.05; paternal: r = -0.25, p < 0.01), although it had no significant influence on emotional regulation. Regression analysis revealed that although the total model predicted autonomy (F(3, 128) = 3.53, p = 0.017), individual predictors were not significant, implying minimal predictive value of emotional immaturity by itself. These findings underscore the nuanced influence of parenting behaviors in a collectivist context, emphasizing maternal care's benefits and overprotection's drawbacks.

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Parental Emotional Immaturity, Self-Autonomy, Care, Young Adults, Overprotection, Emotional Growth.

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This research examines the impact of social media influencer marketing on Generation Z consumers' buying habits in India's online retail clothing market. With platforms like Instagram, YouTube, and TikTok dominating social media landscapes, influencers have become central figures in shaping customer preferences. This study aims to explore the extent to which influencer marketing influences Gen Z's trust, brand perception, and purchasing decisions within the online clothing industry. A mixed-methods approach is utilized, combining quantitative surveys with qualitative in-depth interviews to gather comprehensive insights. The survey sample comprises 222 respondents aged between 18-25 years, predominantly engaging with social media fashion influencers. Statistical methods such as chi-square tests and regression analysis are employed to examine the relationships between demographic factors and consumer purchasing behavior. Findings indicate that most Gen Z consumers find influencer endorsements more trustworthy than traditional advertisements. The authenticity and credibility of influencers are identified as the most significant drivers of trust and purchasing decisions. Visual content formats such as outfit reviews, styling tutorials, and haul videos notably enhance product awareness and purchasing intent. However, the research also highlights challenges such as growing skepticism towards sponsored content and the overwhelming volume of influencer promotions, which can erode trust and engagement. While influencer marketing proves to be a powerful sales driver, it is essential for brands to maintain authenticity and transparency to foster long-term consumer relationships. The study offers valuable insights for marketers, suggesting that they should collaborate with authentic influencers, develop engaging and informative content, and adhere to ethical marketing practices to build trust with Gen Z consumers. The findings contribute to the existing body of knowledge on consumer behavior and digital marketing and provide useful guidance for brands aiming to engage India's young, digitally-savvy online clothing shoppers.

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Keywords: Social Media Influencer Marketing, Gen Z Consumers, Online Retail Clothing Market, Purchase Decisions, Consumer Behavior, Authenticity and Credibility, Content Engagement, Trust Building.

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Fake news refers to false or misleading information presented to as legitimate news. It is often produced to harm the reputation of individuals or organizations or to generate profit through advertising. While false information has been circulated throughout history, the term fake news originated in the 1890s when sensationalized newspaper reports were widespread. However, the term lacks a clear and consistent definition and is often broadly applied to any misleading content portrayed as news. Additionally, some high-profile figures have used the term to dismiss news that portrays them negatively. Moreover, fake news is typically defined by sensationalism, deceptive headlines, and a lack of reliable sources. Leveraging these features, researchers have developed machine learning models and algorithms for fake news detection. These models utilize textual analysis, linguistic patterns, and metadata to differentiate between authentic and false news articles. The techniques employed for fake news detection, which encompass both supervised and unsupervised learning approaches. Supervised learning methods involve training classifiers on labelled datasets, while unsupervised techniques rely on clustering algorithms and anomaly detection to identify suspicious content. Additionally, deep learning architectures, including Recurrent Neural Networks (RNNs) and Transformers, have demonstrated effectiveness in capturing semantic nuances and contextual information, improving the accuracy of fake news detection systems.

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Fake News, Fake News Detection, Recurrent Neural Networks.

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This study investigates the seasonal variation in the nest construction behavior of Oecophylla smaragdina (weaver ants) in a mango garden located in Mokhada, Maharashtra. Weaver ants are known for their unique nest-building behavior, where they use the silk produced by their larvae to weave leaves together. The study focuses on how environmental factors such as temperature, humidity, and mango fruiting cycles influence the nest-building activities. Data were collected over the course of one year, with observations made in different seasons: pre-monsoon, monsoon, and post-monsoon. The findings suggest that nest construction activity fluctuates with changes in the availability of food resources, environmental conditions, and reproduction cycles of the ants. Nest construction peaked during the pre-monsoon season.

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Weaver ants, Oecophylla smaragdina, nest construction, seasonal variation, mango garden, Mokhada.

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The Inquiry Training Model (ITM) was developed by Richard Suchman, aiming to help students cultivate the intellectual disciplines and skills necessary to ask questions and seek answers driven by curiosity. This study investigates the effectiveness of the Inquiry Training Model on the academic achievement of eighth-grade students in geography, comparing it to traditional teaching methods. The research was experimental in nature, with one group being taught using the Inquiry Training Model and a control group receiving traditional instruction. A total of 120 students from Nagpur district were selected as participants. The results indicate that the Inquiry Training Model was more effective for teaching geography than traditional classroom methods. Overall, the Inquiry Training Model significantly enhanced the academic achievement of eighth-grade students studying geography.

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Inquiry Training Model, academic achievement, traditional teaching methods

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This research paper presents "VoteChain", a blockchain-integrated, cross-platform mobile voting application designed to overcome the inefficiencies, security vulnerabilities, and exorbitant operational costs of traditional electoral systems in populous democracies such as India. VoteChain utilizes a hybrid architecture that leverages blockchain exclusively for immutable vote recording via smart contract while delegating non-critical operations to a secondary database, all while maintaining scalability. VoteChain enforces jurisdictionally constrained voting through region-based validation, multifactor authentication, and anti double-voting protocols. Its robust security framework employs cryptographic hashing of voter identities, role-based access control, and automated measures to prevent cross-constituency fraud. A hierarchical UI/UX design enables voters to navigate elections by constituency, party, or region, with real-time results visualized through dynamic charts and detailed metadata analytics on demographic trends and voter turnout. Overall, VoteChain establishes a blueprint for secure, transparent, and cost-effective digital democracy, bridging the gap between decentralized trust and real-world electoral pragmatism.

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Blockchain, Smart Contracts, Hybrid Architecture, E-Voting, Voting Protocols, Security & Transparency, Digital Democracy, Mobile Voting, Cross-Platform Application.

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The COVID-19 pandemic has reshaped the pharmaceutical industry, presenting significant challenges and opportunities. This research examines the industry's response, including supply chain disruptions, regulatory adaptations, and accelerated digital transformation. It explores emerging trends such as personalized medicine, digital health technologies, and global health initiatives. Findings suggest that while the pandemic exposed vulnerabilities, it also fostered innovation, collaboration, and resilience. The paper concludes with strategic recommendations for sustaining industry growth and improving global health security.

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COVID-19, pharmaceuticals, supply chain, regulation, digital health, innovation, collaboration, resilience, global health

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