ACTA SCIENTIAE is an international, peer reviewed, open access, scientific and scholarly journal which publishes Research papers, Review papers, Mini reviews, Case reports, Case studies, Short communications, Letters, Editorials, Books, Thesis, Dissertation works, etc., from all the aspects of Agricultural Science, Biological Science, Business, Chemical Science, Education Science, Engineering and Technology, Humanities, Life Science, Physical Science, Marine Science, Social science. After publishing, articles are freely available through online without any restrictions or any other subscriptions to researchers and readers worldwide ISSN:1517-4492 | E-ISSN:2178-7727 | Publisher: Lutheran University of Brazil | Year:1999
EFFECTS OF OTT ON FILM PRODUCERS IN TAMIL FILM INDUSTY
The introduction of digital photography the rapid transformation in data storage which came along has paved the way for the digital film making era. The emergence of over the top (OTT) media services has started to change the media space significantly. As is known digitization has created a new course of travel in cinema sector as in all areas of life. The speed revolution in the Internet and in smart phones has completely led consumer to easily watch movies or desired series from their smart phones, desktop computers, laptop, tablets or smart televisions (tv’s). Covid 19 is an unpredictable global pandemic which has changed the way audience consume media. An undeniable trend surfaced in this period-adoption of OTT’s. With this study the researchers have studied the evolution of OTT space in India and reviewed the dynamic OTT space evaluate big banner movie releases on platforms like Amazon and Netflix. To complete the study it was imperative to evaluate the effects on OTT for film producers in Tamil movie industry. With this background the researchers work on the objectives and tried to evaluate the role played by the pandemic evolving OTT media consumption trends. This article draws attention to the rise of OTT factors influencing its success and what are film makers and producers thinking?
MATHEMATICAL ANALYSIS OF ADAPTIVE CRYPTOGRAPHIC COMMUNICATION & CAT-BOOST BASED INTRUSION DETECTION IN IOV
The advanced computing technologies such as cloud computing, IoT, IoV, and machine learning create vast amounts of information that require efficient, reliable, and prompt processing. The use of the IoV technology becomes essential since it allows establishing communications between the vehicle and roadside infrastructure. Nonetheless, IoV communication networks are highly exposed to security vulnerabilities due to their decentralized architecture. Such threats as malicious vehicles, data injection attacks, and others can significantly influence the operation of the network and its users. To tackle the problem, the present research paper offers an architecture for secure communication based on trust management and hybrid encryption. Considering the idea of the hybrid encryption algorithm, both of the algorithms should be taken into account, as both of them are efficient in their specific areas. For instance, since the RSA algorithm may be employed for user authentication and key exchange, the efficiency of the AES algorithm will be helpful in encrypting the data quickly. Moreover, the Cat-Boost classifier should be utilized in our study, in order to create a novel IDS that will detect all malicious behaviour exhibited by vehicles and traffic problems according to the UNSW-NB15 dataset. We found out that the efficiency of our model equals 93.57 Some of the accomplishments which have been recorded using this suggested method have included the application of machine learning algorithms to analyse the data sets that include the UNSW-NB15 data set, which were analysed using the Cat-Boost technique, and which yielded an accuracy of 93.57 On the other hand, IoV -based networks suffer from many security issues due to their open and decentralized structure. There is no central entity managing the communications in this network. Hence, malicious vehicles can inject false data into the system, affect traffic behaviour, and even pose threats to the system as a whole by pretending to be some of the legitimate nodes. Thus, data protection and authentication have become crucial concerns that need to be addressed properly.
THE IMPACT OF CLIMATE CHANGE ON THAILAND’S OCCUPATIONAL HEALTH-RELATED ISSUES
Environmental change, including climate change, is one of the most urgent problems facing our time. Thailand is especially susceptible to climate change because of its position and reliance on industries that are sensitive to the changing climate. It is anticipated that climate change would increase occupational exposures to chemicals, ozone, high temperatures, and polycyclic aromatic hydrocarbons. In addition to increased workplace violence, climate change has been connected to an increase in the spread of wildfires, pathogenic microorganisms, and vector-borne infectious agents. A challenge to the productivity, social well-being, and health and safety of the diverse workforce worldwide is occupational exposure brought on by climate change and rising temperatures. Climate change is predicted to impact both indoor and outdoor workers. Common occupational health problems include heatstroke, headache, exhaustion, insomnia, skin, respiratory, renal, and heart disorders, immunological dysfunction, infections, injuries, cancer, and (in extreme cases) fatality. A range of strategies must be put in place by politicians, governments, and employers to protect workers against the long-term health implications of climate change. Any steps that could be made to lessen the negative health effects of climate change should also be communicated to employees.
CLOSED SETS AND CONTINUOUS FUNCTIONS VIA FUZZY QUADRIGEMINAL TOPOLOGICAL SPACES
Fuzzy Quadrigeminal sets is a new approach introduced for the purpose of measuring degree of belongingness of elements to a subset. Fuzzy Quadrigeminal set helps us to draw some conclusion whether a positive result be possible or not in an uncertain situation. The aim of this paper is to elicit some basic properties concerned to closed sets and continuous functions via Fuzzy Quadrigeminal Topological spaces which was proposed by Razzag et al in “Picture fuzzy topological spaces and associated continuous functions” [13]. Also, it tries to exhibit some properties of generalized closed sets. Existence of open cover for a Fuzzy Quadrigeminal Topological Space is proved, and hence, the compactness of spaces is derived. The concept of relations between two Fuzzy Quadrigeminal sets is developed. Thus, this article explores some topological concepts via Fuzzy Quadrigeminal Topological spaces.
REPRESENTATION OF TOXIC CHARACTERIZATION AND GENDER DYNAMICS IN SOUTH INDIAN CINEMA
The representation of intimate relationships in contemporary South Indian cinema has undergone a remarkable transformation, shifting from idealized notions of romance to psychologically complex narratives that foreground emotional vulnerability, possessiveness, manipulation and power imbalance. While romantic relationships have traditionally been portrayed through culturally accepted patriarchal frameworks, recent films increasingly explore the darker dimensions of love, exposing behaviours associated with toxic masculinity, emotional abuse, coercive control and gender inequality. This study comparatively examines the representation of toxic characterization and gender dynamics in the Tamil film Lover (2024) and the Telugu film Girlfriend (2025). Drawing upon Feminist Film Theory, Gender Performativity Theory, Male Gaze Theory and Hegemonic Masculinity Theory, the research investigates how cinematic narratives construct gender identities, negotiate emotional power and normalize or challenge toxic behavioural patterns within romantic relationships. The study adopts a qualitative research design using Multimodal Discourse Analysis and Narrative Discourse Analysis to examine dialogues, characterization, mise-en-scène. Comparative textual analysis reveals that both films depict toxic behavioural traits through emotional dependency, possessiveness, surveillance, jealousy, manipulation, and psychological abuse; however, they differ in the ways female agency is represented. The Tamil narrative critiques patriarchal possessiveness through psychological realism, whereas the Telugu narrative negotiates toxicity within broader cultural expectations of romance and gender performance. The study argues that contemporary South Indian cinema is gradually shifting from romanticizing toxic relationships toward encouraging critical reflection on gender equality, emotional accountability and healthy interpersonal communication. By comparing two linguistically and culturally distinct industries, this research contributes to feminist film studies, gender communication and South Indian cinema scholarship while expanding academic discourse on toxic characterization in contemporary visual culture.
GENERATING A POLITICAL PROCESS FOR AFGHANISTAN: RE-INTEGRATING AFGHANISTAN INTO THE INTERNATIONAL COMMUNITY
In the prevailing socio-economic and political situation, numerous radical changes have taken place in Afghanistan's engagement process due to the protracted high level of violence, a lack of political consensus, and a trust deficit among the various sides of the ongoing conflict, exacerbated by the hasty and chaotic withdrawal of U.S. and NATO troops in August 2021. In addition, inevitable national, regional, and global spoilers have played a devastating role in the international community's peacebuilding efforts. Nevertheless, engagement efforts in Afghanistan have culminated in bringing the Taliban back into power in Kabul and have further destabilized the country. The article "Generating a Political Process for Afghanistan" explores Afghan politics, focusing on challenges and opportunities in establishing a sustainable political process. Its main goal is to propose a framework to address ongoing instability, answering how to reintegrate Afghanistan into the international community through analysis of history, current politics, and challenges. The article uses a multidisciplinary approach, combining political science, history, and conflict resolution. It highlights Afghanistan's deep-rooted political issues like poor governance, ethnic divisions, and security threats. Despite these, opportunities for reform exist through inclusive governance, constitutional reform, and international support. The study's implications are relevant to policymakers, scholars, and practitioners seeking peace and stability. By understanding the complexities of Afghan politics and pathways for change, stakeholders can foster a more resilient, inclusive political process.
INVESTIGATING POSITIVE CONNECTIONS BETWEEN PSYCHOLOGICAL HEALTH AND WORK-LIFE BALANCE AS WELL AS EMPLOYEE ENGAGEMENT IN HYBRID WORKING SYSTEMS.
Hybrid employment has changed the performance of the modern workers with both advantages as well as disadvantages of sustaining employee engagement. This essay will look into the effect of a mixed workplace on employee engagement focusing on the mediating effects of psychological wellbeing and work-life balance. The research rests on the Job Demands Resources (JD-R) paradigm and the Social Exchange Theory that are premised on the notion that job flexibility and autonomy may have a positive impact on employee engagement. Nevertheless, hybrid employment also has dangers like a lack of social interactions and working-life boundaries. Through a quantitative analysis, data on employees in various organizational settings and are employed in a hybrid work place were collected. The relationships between the constructs as well as the mediation effects are objectively ascertained using structural equation modeling (SEM). The results would prove that work-life balance and psychological well-being mediate successively between the hybrid work models and employee engagement that is essential in generating remarkable work outcomes. The research can be discussed as a contribution to the existing literature on the topic of hybrid work as it is one model that can be used, to establish a connection between a practice in organizations and the level of psychological conditions and employee engagement rates. Moreover, business leaders and human resource managers should take into account how operational such a hybrid work practice is, one that gradually enhances worker engagement and well-being. The paper moves the subject of strategic human resource management and future of work forward since it is concerned with one of the modern and evolving work organizations.
Abstract: In this paper, we introduce a new index for the connected simple graph namely, anti eccentric harmonic index defined by, for all edges in where We determine the exact values of for some class of graphs and also we found the bound for where is a graph of order and size and respectively.
“ESG DISCLOSURE AND FINANCIAL PERFORMANCE OF INDIAN COMPANIES: AN EMPIRICAL INVESTIGATION”
This study titled “ESG Disclosure and Financial Performance of Indian Companies: An Empirical Investigation” examines the relationship between ESG disclosure and financial performance among selected Indian companies. ESG disclosure includes three major dimensions: environmental responsibility, social accountability and governance transparency. The study highlights that ESG reporting has become an important part of corporate disclosure in India, especially after the introduction of SEBI’s Business Responsibility and Sustainability Reporting framework for the top 1000 listed companies. The paper explains that ESG disclosure helps companies communicate their environmental practices, social responsibilities, governance systems, risk management, ethical conduct and long-term sustainability strategy. The study uses selected Indian companies such as Reliance Industries Ltd., Tata Consultancy Services Ltd., Infosys Ltd., HDFC Bank Ltd., ICICI Bank Ltd., ITC Ltd., Hindustan Unilever Ltd., Tata Motors Ltd., Maruti Suzuki India Ltd. and NTPC Ltd. ESG disclosure is measured through environmental and governance scores, while financial performance is measured through Return on Assets and Return on Equity. The findings show that Infosys Ltd. records the highest total ESG score, while Tata Consultancy Services Ltd. records the highest total financial score. The study indicates that ESG disclosure strengthens corporate transparency, investor confidence, stakeholder trust and long-term financial sustainability. However, the relationship between ESG disclosure and financial performance may differ across companies and sectors.
DIELECTRIC RESONATOR ANTENNA DESIGN FOR MIMO-BASED WIRELESS COMMUNICATION SYSTEMS
This work introduces a rack-shaped two-element dielectric resonator antenna (DRA) based multiple-input multiple-output (MIMO) system featuring improved axial ratio features for ultra-wideband (UWB) operations. The proposed antenna configuration employs two rectangular radiator elements modified into rack-shaped dielectric resonators to excite multiple resonant modes, namely ????????????111, ????????????121, and ????????????212, at 7.3 GHz, 9.3 GHz, and 10.74 GHz, respectively. The rack-based configuration markedly enhances the bandwidth effectiveness over the UWB wavelength spectrum. An inverted T-shaped magnetic strip is employed to attain elliptical polarisation while efficiently regulating both axial ratio spectrum & susceptibility spectrum, yielding a broad impedance spectrum of 101.87%. Simulated & measured outcomes demonstrate strong concordance and validate UWB functionality from 3.54 to 10.89 GHz. The MIMO effectiveness is assessed based on the envelope correlation ratio (ECC ≤ 0.0059), broadness gain (DG ≥ 9.93 dB), total reflection active coefficient (TARC) across various phases positions, grouping delay (ranging from 0.96 to −2.1 ns), and channel capability loss (CCL ≤ 0.4 bits/s/Hz, excluding the 8.8–9.6 GHz band). The outcomes demonstrate that the suggested transmitter meets typical MIMO requirements and is appropriate for high-data-rate uses within the C- & X-band spectrum categories.
DIGITAL BELONGING AND EMOTIONAL DISPLACEMENT IN DEVIKA REGE’S QUARTERLIFE
The rapid expansion of digital technologies has transformed contemporary experiences of belonging, mobility, and identity. While geographical distance once defined the migrant and diasporic existence, digital communication now enables continuous participation in multiple social and cultural worlds. Devika Rege’s Quarterlife (2023) captures this transformation through its portrayal of young urban Indians negotiating globalization, class mobility, political change, and networked forms of connection. This study examines the novel through the concepts of digital belonging and emotional displacement. Drawing upon Stuart Hall’s understanding of cultural identity, Dana Diminescu’s notion of the connected migrant, and contemporary discussions of networked publics, the study argues that Quarterlife presents digital connectivity as a paradoxical condition. Although digital networks create opportunities for affiliation and participation, they simultaneously intensify emotional uncertainty, social fragmentation, and feelings of unbelonging. Through the experiences of characters such as Naren and Rohit, Rege exposes the gap between connectivity and community, revealing the limitations of technologically mediated forms of belonging. The study asserts that the novel redefines home not as a fixed geographical location but as a fragile emotional space continually negotiated across physical and digital environments. Therefore, Quarterlife contributes to emerging literary conversations concerning migration, identity, and belonging in an increasingly interconnected world.
Dr. U. Maria Liny Jenifer, Mr. A. Augustine, Dr. (Sr). Judy Gomez
A COMPREHENSIVE REVIEW ON ANTIDIABETIC POTENTIAL OF ABIES WEBBIANA LINDL.
The rise in the incidence of type 2 diabetes mellitus (T2DM) around the world highlights the critical need for non-synthetic therapy options that are safe, inexpensive, and capable of targeting multiple targets. The Himalayan medicinal conifer Talisastra, or Abies webbiana, has a long tradition of usage in Ayurvedic treatment of respiratory and metabolic diseases, and currently it has the potential to be a natural anti-diabetic. The phytochemical characteristics, pharmacological processes, and translational potential of this compound are examined in this detailed review. Studies from phytochemical studies show that the plant contains bioactive terpenoids (abienol, limonene, and camphene), flavonoids (quercetin and kaempferol), and phenolics (gallic and caffeic acids) that have significant anti-inflammatory, antioxidant, and enzyme-inhibitory effects. A study conducted in both experimental environments and computational models shows that the α-amylase, α-glucosidase, and DPP-IV enzymes are inhibited, insulin sensitivity is enhanced through the PI3K/Akt and AMPK pathways, and pancreatic β-cells are protected from oxidative stress. Network pharmacology and molecular docking have verified interactions with multiple targets, including important metabolic regulators such as PPARγ, AKT1, NF-κB, and SIRT1. The effects of reducing glucose, normalising lipids, and protecting tissues are further supported by in vivo animal models. However, there is a dearth of evidence on toxicity, absorption, and pharmacokinetics, which limits its application in clinical settings. These restrictions could be solved by integrating delivery systems based on nanotechnology with autonomous screening. The transition of A. webbiana from an ethnomedical practice to a treatment based on scientific data requires standardisation, safety profiling, and clinical validation. Collectively, the data presented here indicate that A. webbiana represents a promising botanical candidate for future generations of phytopharmaceuticals used to treat diabetes.
Rupa Ganguly, Dildar Husain, Priyanka Singh
GENDER AND SEXUALITY: A STUDY OF SHYAM SELVADURAI'S FUNNY BOY
Shyam Selvadurai's Funny Boy (1994) is a significant postcolonial novel that explores the intersections of gender, sexuality, ethnicity and identity in Sri Lankan society. Through the experiences of the protagonist Arjie Chelvaratnam, the novel examines the challenges faced by individuals who do not conform to traditional gender roles and heterosexual norms. Arjie's journey from childhood to adolescence reveals the social pressures that regulate gender expression and sexual behavior. The novel presents masculinity as a socially constructed ideal that often suppresses individuality and emotional freedom. It also portrays the awakening of same-sex desire and the difficulties of negotiating sexual identity in a conservative society. Furthermore, the narrative links personal struggles with broader ethnic tensions between the Tamil and Sinhalese communities, demonstrating how different forms of marginalization intersect. Through themes of resistance, self-discovery and identity formation, Selvadurai critiques patriarchal structures and heteronormative expectations. This study analyzes the representation of gender and sexuality in Funny Boy and explores how the novel challenges dominant social norms. By examining Arjie's experiences, the paper highlights the complexities of growing up as a queer individual within a society shaped by patriarchy, cultural traditions and ethnic conflict. Ultimately, Funny Boy emerges as a powerful narrative of self-expression and resistance against oppressive social structures.
COMPARATIVE EVALUATION OF ANTIMICROBIAL EFFICACY OF NANOCHITOSAN-COATED ORTHODONTIC BRACKETS AGAINST FOUR ORAL MICROORGANISMS: AN IN VITRO STUDY
Background and Aim. Fixed orthodontic appliances create plaque-retentive microenvironments that promote colonization by cariogenic and opportunistic microorganisms, increasing the risk of enamel demineralization and white spot lesion (WSL) formation. Conventional compliance-dependent preventive strategies demonstrate limited long-term efficacy. Surface modification of orthodontic brackets with antimicrobial nanocoatings offers a promising compliance-independent approach. This study aimed to comparatively evaluate the antimicrobial efficacy of nanochitosan-coated stainless-steel orthodontic brackets against four clinically relevant oral microorganisms in an in vitro setting. Methods. A total of 160 pre-adjusted edgewise stainless-steel maxillary premolar brackets (MBT prescription, 0.022″ slot) were divided into two groups of 80 each: Group A (nanochitosan-coated) and Group B (uncoated control). Nanochitosan nanoparticles (molecular weight 3,800–20,000 Da; mean particle size ~50 nm) were deposited on bracket surfaces via a standardized hydrothermal method and confirmed by scanning electron microscopy (SEM) and field emission SEM (FESEM). Four microorganisms Streptococcus mutans, Lactobacillus acidophilus, Enterococcus faecalis, and Staphylococcus aureus were standardized to 10⁵ CFU/mL using a spectrophotometer (OD 600 nm) and inoculated into Mueller–Hinton broth containing bracket samples. Colony-forming unit (CFU) counts were recorded at T0 (1 h), T1 (6 h), T2 (12 h), T3 (24 h), and T4 (72 h). Intragroup and intergroup comparisons were performed using paired t-test and one-way ANOVA, respectively, at a 95% confidence level (p ≤ 0.05). Results. No microbial growth was detected in either group at 1 and 6 hours. From 12 hours onward, uncoated brackets demonstrated a progressive and statistically significant increase in CFU counts for all four organisms, reaching mean values of 123.75 ± 2.446, 124.45 ± 2.459, 123.80 ± 2.876, and 124.65 ± 1.954 × 10⁵ CFU/mL at 72 h for S. mutans, L. acidophilus, E. faecalis, and S. aureus, respectively. In contrast, nanochitosan-coated brackets maintained consistently low and stable CFU counts (22–24 × 10⁵ CFU/mL) across all time points. Intergroup differences were highly significant for all organisms at all post-baseline intervals (F values 1,025–27,604; p < 0.001). Conclusions. Nanochitosan surface modification significantly enhances the antimicrobial properties of stainless-steel orthodontic brackets, providing broad-spectrum, sustained inhibition of bacterial adhesion and proliferation. This compliance-independent coating strategy holds considerable potential for reducing biofilm accumulation, enamel demineralization, and white spot lesion formation during fixed orthodontic treatment. Further in vivo studies are warranted to confirm clinical durability and biocompatibility.
nanochitosan; orthodontic brackets; antimicrobial activity; white spot lesions; biofilm inhibition; Streptococcus mutans
Dr. Rahul Paul,Dr. Deepti Yadav, Dr. Ish Kumar Sharma, Dr. Mainak Halder,Dr. Ratika Sawhney,Dr. Kanika Gupta
TRANSFORMER-BASED ABSTRACTIVE TEXT SUMMARIZATION:A COMPREHENSIVE REVIEW OF MODELS, CHALLENGES, AND EVALUATION
The exponential growth of digital textual information across news portals, academic repositories, legal corpora, and social media platforms has intensified the need for efficient automated text summarization systems. Transformer-based architectures have emerged as the dominant paradigm in abstractive text summarization, offering superior capabilities in modeling long-range linguistic dependencies and generating fluent, coherent summaries. This review paper provides a comprehensive examination of the development, current state, and open challenges of transformer-based abstractive text summarization. We systematically analyze foundational encoder-decoder architectures, pre-trained language models such as BERT, GPT-2, BART, T5, and PEGASUS, and survey critical research contributions addressing hallucination mitigation, factual consistency, long-document processing, and evaluation methodology. We further review prominent benchmark datasets including CNN/Daily Mail, XSum, MultiNews, and ArXiv, and discuss evaluation metrics spanning ROUGE, BERTScore, BARTScore, and NLI-based faithfulness measures. Our analysis identifies persistent challenges in scalable inference, domain adaptation, multilingual summarization, and reliable automatic evaluation, and outlines promising directions for future research in this rapidly evolving field.
Abstractive summarization, Transformer, BERT, BART, T5, PEGASUS, ROUGE, hallucination, factual consistency, pre-trained language models, natural language processing, deep learning.
COMPARATIVE ANALYSIS OF MACHINE LEARNING ALGORITHMS FOR CLASSIFYING CHEST X-RAY IMAGES OF COVID-19
The fast spread of COVID-19 has made it essential to have quick and accurate ways to diagnose the disease using medical images. In this study, we present a comparative analysis of six machine learning algorithms for classifying chest X-ray images into three categories: COVID-19, pneumonia, and normal. The algorithms evaluated include Support Vector Machine (SVM), Random Forest, Decision Tree, K-Nearest Neighbors (KNN), Naive Bayes, and Logistic Regression. The models were trained and validated using a dataset of labeled X-ray images, with performance assessed based on key metrics such as validation accuracy, test accuracy, Matthews Correlation Coefficient (MCC), and ROC-AUC scores. Among the models, the SVM algorithm achieved the highest validation accuracy of 92.6% and test accuracy of 94.0%, with an MCC of 0.8785 and a macro-average ROC-AUC of 0.9877. Logistic Regression and Random Forest followed closely, with Logistic Regression attaining a test accuracy of 93.8% and Random Forest achieving 92.6%. K-Nearest Neighbors showed moderate performance, while Naive Bayes exhibited the lowest accuracy, likely due to its simplistic assumptions. Overall, the SVM model outperformed the others, demonstrating its robustness in distinguishing between the three categories in chest X-ray images. This comparative study highlights the potential of machine learning techniques in automating the detection of COVID-19 and pneumonia from radiographs, contributing to faster and more accurate diagnostic tools in healthcare.
Healthcare, Machine Learning, COVID-19, SVM, KNN, Regression, Random Forest
CERTAIN INVESTIGATION AND PREDICTION OF BIGMART SALES USING MACHINE LEARNING TECHNIQUES
Accurate sales forecasting is critical for retail optimization, yet many predictive models struggle with the inherent noise and categorical complexity of retail datasets. This study presents a rigorous investigation into machine learning techniques for predicting sales using the Big Mart dataset. Unlike previous narrative studies, we implement a reproducible pipeline incorporating median-imputation for missing values, one-hot encoding for categorical features, and a 5-fold cross-validation protocol to ensure model stability. We evaluate four distinct architectures: Linear Regression, Polynomial Regression, Decision Trees, and XGBoost. Our results demonstrate that XGBoost significantly outperforms traditional models, achieving a Root Mean Squared Error (RMSE) of 0.0231 and a Mean Absolute Error (MAE) of 0.018 after systematic hyperparameter tuning. Beyond predictive accuracy, we provide a feature importance analysis revealing that Item MRP and Outlet Type are the primary drivers of sales variance. This work contributes a validated framework for retail forecasting that balances predictive power with business interpretability, offering actionable insights for inventory management and strategic decision-making.
Predictive Analysis, Polynomial Regression, Linear Regression, Xgboost and Decision Tree.
GLOBALISATION AND ITS INFLUENCE ON INDIA’S EXPORT–IMPORT DYNAMICS: AN ANALYTICAL STUDY
Globalisation has changed India's economy a lot, especially its trade with other countries. India's integration with global markets has grown since the economic reforms of 1991. This has led to more exports, a wider range of imports, more competition, and faster economic growth. This analytical study investigates the impact of globalisation on India's export-import dynamics, emphasising growth trends, structural transformations, trade composition, and policy reforms. The study analyses secondary data from government reports, economic surveys, WTO publications, and trade databases to elucidate significant trends in India's trade performance. The results show that the Indian economy is becoming more open, that it is shifting from exporting raw materials to manufactured goods and services, that it is importing more technology-intensive goods, and that it is participating more in global value chains. The paper concludes that globalisation has led to more trade and economic growth, but there are still big problems like trade deficits, reliance on foreign technology, and unstable global markets.
Globalisation, India, Export–Import Dynamics, Trade Liberalisation, Economic Reforms, External Sector
TRANSFORMER-BASED ABSTRACTIVE TEXT SUMMARIZATION: MODELS, CHALLENGES, AND EVALUATION
Text summarization has undergone significant transformation with the advent of transformer-based neural architectures. This research examines the landscape of transformer models for abstractive summarization, exploring how attention mechanisms and pre-training strategies have revolutionized the field. We investigate prominent models including BERT, GPT variants, T5, and PEGASUS, analyzing their architectural innovations and summarization capabilities. The study addresses persistent challenges including factual consistency, handling long documents, computational efficiency, and evaluation reliability. Through comprehensive analysis of existing approaches and evaluation methodologies, we identify critical gaps in current summarization systems and propose directions for advancement. Our findings reveal that while transformer models achieve impressive fluency and coherence, ensuring factual accuracy remains problematic. The research contributes a structured understanding of the transformer summarization ecosystem, highlighting that future progress depends on developing better evaluation metrics, improving factual grounding, and creating more efficient architectures suitable for practical deployment.
Transformer Models, Abstractive Summarization, Natural Language Processing, Attention Mechanisms, Neural Networks, Pre-training, Evaluation Metrics
AI-BASED MULTIMODAL LEARNING ANALYTICS FOR PREDICTING BEHAVIORAL CHANGES IN STUDENTS WITH SPECIAL EDUCATION
The present project is aimed at forecasting behavioral changes in the students with Special Education Needs (SEN) based on the analysis of their learning activities and interactions. Classroom activity, accomplishment of tasks, attendance, and teacher observations are all gathered and handled in order to come up with trends in student behavior. The machine learning model predicts possible positive or negative behavior change to support the teacher and caregivers to offer prompt assistance and intervention. It also contains basic visualization, like dashboard or charts, so that it is easier to have the educators see the trends of behaviors at a glance. With a simple data-driven model, the project permits the behavior in the classroom to be managed in advance, promotes engagement, and facilitates better learning the results in a practical and readily constructible way.
Multi modal learning analytics (MMLA), special education needs (SEN)
Dr. Srinivasan Nagaraj, Dr.Y. Dasaratha Rami Reddy, Ms. Somesula Sujatha, Dr. G. Sreenivasula Reddy, Ms. Shaik Muneera
EVALUATION OF MOLAR PROTRACTION WITH DISTRACTOR AND MICRO-OSTEOPERFORATION- A COMPARATIVE STUDY”
Background: Accelerating orthodontic tooth movement is a major clinical goal to reduce treatment duration. Techniques such as micro-osteoperforation (MOP) and distraction osteogenesis (DO) have been proposed as effective adjuncts. Materials and methods This in-vivo randomized clinical study was conducted on 30 patients with Class I malocclusion requiring molar protraction. The subjects were randomly allocated into three groups of 10 each: Group A treated with conventional T-loop mechanics, Group B with distractor-assisted osteogenesis, and Group C with micro-osteoperforation (MOP) combined with T-loop mechanics. Standard MBT fixed appliances were used in all patients. Molar protraction was measured intraorally as the distance between the second molar and premolar using a digital vernier caliper at baseline (T0), 45 days (T1), and 90 days (T2). The collected data were subjected to statistical analysis using appropriate parametric and non-parametric tests, with the level of significance set at p < 0.05. Objective: To evaluate and compare the amount and rate of second molar protraction using conventional T-loop mechanics, distractor-assisted osteogenesis, and MOP combined with T-loop mechanics. Results: All groups showed significant molar protraction (p<0.05). The distractor group demonstrated the highest rate of tooth movement, followed by MOP with T-loop, while conventional T-loop showed the least movement. Conclusion: Distractor-assisted osteogenesis provides maximum acceleration but is invasive. MOP offers a minimally invasive alternative with significant acceleration, while T-loop remains a reliable conventional method.
Molar protraction, Micro-osteoperforation, Distraction osteogenesis, T-loop, Accelerated orthodontics
Rahul Paul, Deepti Yadav, Ish Kumar Sharma, Sanjeev K Shokeen,Ratika Sawhney,Kanika Gupta
DESIGN OVER HYPE: EMPIRICAL EVIDENCE ON EFFECTIVE AI INTEGRATION IN EDUCATION
Artificial Intelligence (AI) has grown rapidly from optional experiments to core infrastructure in the current learning environment while it’s evidence of real impact remains inconclusive. This study synthesizes contemporary empirical research on AI-integrated learning, teaching and assessment in the era of generative systems and large language models. A comprehensive search on popular reputed databases resulted in 612 records which was further filtered to include only 35 peer reviewed studies after performing PRISMA 2020 reporting standards. The corpus ranges from K-12, higher education, and professional learning, encompassing AI-powered personalization, smart tutoring systems, generative AI assistants, AI-enhanced assessment, chatbots and adaptive feedback environments. Across various study results, AI-powered interventions consistently show positive influence on academic performance, with an average impact from small to large (g/d ≈ 0.43–0.70), while promoting growth in metacognitive regulation, learner engagement and self- efficacy. The most effective outcomes occur when AI functions as structured, feedback-oriented and pedagogically-aligned co-instructor, whereas peripheral or unstructured usage results in modest or minimal impact. Moderator patterns reflect the necessity of instructional design, institutional capacity, educator readiness, and student AI literacy, as well as growing concerns on equity, transparency, academic integrity and over-reliance on generative outputs. The review outlines that AI-enabled learning environments can improvise both cognitive and affective results when coupled with supervised, ethically governed and context-sensitive scenarios, and identifies necessity for longitudinal, cross-disciplinary and multi-site assessments of generative and adaptive AI in education.
Metacognitive, AI literacy, self-efficacy.
Adyasha Samal, S Suriya, S. Sindhu, Dr.C.Priya
AI-BASED DECISION SUPPORT FOR CROP FARMING
Agriculture plays a crucial role in ensuring food security and economic sustainability. Farm- ers face challenges such as climate variability, crop diseases, soil nutrient imbalance, and volatile market prices. Traditional decision-making methods often lead to reduced productivity and financial losses.This paper presents AgroVision, an AI-driven intelligent decision support system designed to assist farmers throughout the crop lifecycle. The system integrates Convolutional Neural Networks for crop disease detection, supervised learning models for soil fertility estimation and crop yield prediction, and time-series forecasting models for market price prediction.Unlike IoT-based systems, AgroVision operates without hardware sensors, making it cost- effective and accessible to small and medium-scale farmers.
Artificial Intelligence, Crop Disease Detection, Soil Fertility Estimation, Yield Prediction, Market Forecasting, Sustainable Agriculture
Dr. G. Sreenivasula Reddy, Dr. Srinivasan Nagaraj, Ms. Somesula Sujatha, Dr.Y. Dasaratha Rami Reddy, Mrs. P.Mahaboob Chand
DYNAMIC PRESSURE ON A FLOATING PLATFORM DUE TO SURFACE WAVES
Floating platforms serve a wide range of strategic and functional purposes, including offshore infrastructure for industrial operations and oil exploration, as well as civic applications such as floating airstrips and recreational parks. They are also critical in defence sectors, particularly for naval bases and mobile support systems. Given their exposure to dynamic environmental forces, especially wave action, understanding their structural response is essential for safe and efficient design. In this study, the behaviour of a rectangular floating platform is examined under hydrodynamic loading. The platform is assumed to float on an infinitely extended fluid domain with finite depth, which reflects realistic ocean conditions where lateral boundaries have negligible influence but depth remains a governing factor. The problem is treated as a coupled fluid–structure interaction system, where the fluid domain is modelled in three dimensions using pressure as the primary nodal variable, while the platform is represented as a two-dimensional structural element characterized by displacement. To accurately capture the mechanics, the platform behaviour is modelled using Mindlin plate theory, which accounts for transverse shear deformation and is suitable for moderately thick plates. The fluid motion is governed by the Navier–Stokes equations, simplified under the assumptions of incompressibility and inviscid flow to focus on dominant pressure effects. The base of the fluid domain is considered perfectly rigid, ensuring complete wave reflection without energy dissipation—an assumption that helps isolate the impact of wave-structure interaction. The resulting time-dependent coupled equations are solved using Newmark-beta method, which provides stable and accurate solutions for dynamic systems. Dynamic pressure acting on the platform is evaluated, and the additional stresses induced by wave action are quantified in terms of bending moments. These are further expressed as non-dimensional coefficients, offering practical utility for engineers to estimate bending responses efficiently in design applications.
Floating Platforms, Hydrodynamic Loading, Lateral Boundaries, Mindlin Plate Theory, Navier–Stokes Equations.
Dr. Bhagirathi Tripathy, Dr. Pratap Kumar Pani, Dr. Abhijeet Das, Dr. Krishna Pada Bauri
Desire and Denial: Masculinity Crisis and the Politics of Intimacy in Red Lipstick: The Men in My Life by Laxmi Narayan Tripathi
The present research explores the issue of intimacy and masculinity crisis in Laxmi Narayan Tripathi's memoir titled Red Lipstick: The Men in My Life (2016) using the theory of hegemonic masculinity by R.W. Connell. According to the paper's main postulate, hegemonic masculinity constructed by society in India is inherently fragile in its confrontation with male lust for a transgender person. Using qualitative textual analysis, the research detects the presence of four major themes in Red Lipstick (i.e., desire and denial, secrecy, power disparity, and emotional labour). Based on these themes, it is possible to conclude that the characters of the men depicted in the book tend to pursue intimacy in private and disown it publicly in compulsive manner. By referring briefly to the ideas of Butler regarding gender performativity and Sedgwick about the closet, the paper demonstrates that Red Lipstick becomes an essential field for understanding the disruption of hegemonic masculinity due to the presence of transgender individuals.
: hegemonic masculinity, transgender studies, masculinity crisis, intimacy.
IMPACT OF EMPLOYEE EXPERIENCE ON EMPLOYEE PRODUCTIVITY WITH SPECIAL REFERENCE TO PRECOT MERIDIAN LIMITED, WALAYAR, PALAKKAD
Employee experience has emerged as a critical factor influencing productivity and overall organizational performance, especially in manufacturing industries like textiles. This study examines the impact of employee experience on employee productivity at Precot Limited (formerly Precot Meridian Limited), Walayar, Palakkad. The research focuses on key factors such as work environment, management support, communication, welfare measures, and employee engagement. A descriptive research design was adopted, and data were collected from 306 employees selected using Krejcie and Morgan’s sample size table and a simple random sampling method. Quantitative analysis, including correlation, revealed a strong positive relationship (r = 0.72) between employee experience and productivity. The findings indicate that a supportive work environment, effective communication, recognition, and welfare initiatives significantly enhance employee motivation, engagement, and efficiency. The study highlights the importance of employee-centric HR practices for achieving sustainable organizational growth and improved performance in the textile sector.
Employee Experience, Employee Productivity, Work Environment, Management Support, Employee Engagement, Textile Industry
STUDY ON WORKFORCE AGILITY AND ORGANIZATIONAL CITIZENSHIP BEHAVIOUR OF HIGHER EDUCATION PROFESSIONALS
The higher education sector is experiencing rapid transformation due to globalization, technological advancements, and increasing societal expectations, thereby demanding greater adaptability from academic professionals. In this context, the present study examines the relationship between workforce agility and organizational citizenship behaviour (OCB) among higher education professionals in Coimbatore district. The study adopts a descriptive research design and collects data from 150 respondents using a structured questionnaire comprising workforce agility and OCB scales. Statistical tools such as mean, standard deviation, t-test, ANOVA, correlation, and regression analysis were employed. The findings reveal that the majority of respondents exhibit a moderate level of workforce agility and OCB. Significant differences were observed in workforce agility and OCB based on designation, while OCB also varied across institution types. The study further identifies a positive and significant relationship between workforce agility and OCB (r = 0.239, p < 0.05). Regression analysis indicates that workforce agility significantly predicts OCB, explaining 5.7% of the variance. The results suggest that professionals who are adaptable, flexible, and proactive are more likely to engage in extra-role behaviours that support organizational effectiveness. The study concludes that enhancing workforce agility through continuous learning, skill development, and supportive institutional practices can strengthen organizational citizenship behaviour among higher education professionals, thereby contributing to institutional growth and performance
A STUDY ON IDEAL TIME AND METHODS OF COMMITTED SUICIDE IN VILLUPURAM DISTRICT, TAMIL NADU
The study examines the patterns, causes, and socio-demographic profile of suicide in India with a specific focus on Villupuram District, Tamil Nadu. Suicide is a major public health concern and one of the leading causes of death globally, particularly among youth. In India, over 1.7 lakh suicides were reported in 2023, with rising trends linked to family problems, illness, and substance abuse. The study adopts a descriptive research design using secondary data collected from Government Villupuram Medical College records (October 2023–September 2025), covering 160 cases. Findings reveal that males (65%) and married individuals (82%) constitute the majority of victims, with the highest incidence in the 21–30 age group. Family-related issues emerged as the primary cause, followed by interpersonal conflicts. Most suicides occurred during late night and early morning hours, commonly through poisoning and hanging. The study highlights the need for community-based interventions, mental health awareness, and strengthened preventive strategies to address this growing social problem.
Family Problems, Mental Health, Suicide, Villupuram District
HIGH-PERFORMANCE CR₂O₃ THIN FILMS VIA OPTIMIZED SOL-GEL DEPOSITION: STRUCTURAL AND ELECTRICAL ANALYSIS
Nanostructured Cr₂O₃ thin films were synthesized using the sol-gel method and deposited onto glass substrates by spin coating. The optimization of deposition parameters, including precursor concentration (0.5 M, 1.0 M, 1.5 M), spin speeds (1000, 2000, 3000 rpm), and deposition times (30, 60, 90 seconds), was performed using Design Expert software. The films were annealed at 500°C for 2 hours to promote crystallization. Characterization of the films was carried out using X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), atomic force microscopy (AFM), and transmission electron microscopy (TEM). The XRD patterns revealed a dominant (104) diffraction peak at 2θ = 36.5°, indicating the formation of Cr₂O₃ with a crystallite size of approximately 25 nm. FTIR spectra showed strong peaks at 570 cm⁻¹, confirming Cr-O bonding in the films. SEM images demonstrated smooth, uniform surfaces with no cracks at a spin speed of 2000 rpm, and AFM analysis revealed an average surface roughness of 3.2 nm. TEM images confirmed the nano-sized grains and homogeneity of the films. The electrical conductivity of the films was found to be 1.2 × 10⁻³ S/cm, and the thermal conductivity was measured at 0.85 W/m·K. The optimized Cr₂O₃ thin films exhibited good crystallinity, excellent morphology, and desirable electrical and thermal properties, making them suitable for applications in sensors and optoelectronics.
Crystallinity, Electrical conductivity, Energy storage, Nanostructured thin films, Spray deposition, Chromium oxide
Cu2+ and Cr6+ recovery from Simulated Waste Water using Zinc oxide Loaded Potato Peel Nanocomposites
In the present study, potato peel loaded nanoparticles were employed as adsorbent materials for the removal of Cu2+ and Cr6+ from aqueous solutions. Experimental observations indicated that different nanoparticles exhibited significant adsorption potential toward ampicillin. The maximum adsorption capacities were calculated as 128.6 mg/g for copper and 98.99 mg/g for chromium using ZnO@PP nanoparticles. Equilibrium analysis revealed that the adsorption behavior was best represented by the Freundlich isotherm model, suggesting multilayer adsorption on a heterogeneous surface. Kinetic investigations further indicated that the adsorption process is mainly controlled by a chemisorption mechanism. The removal of both metals is likely governed by several interactions, including surface complexation, electrostatic attraction, and hydrogen bonding between the adsorbent surface and antibiotic molecules. Thermodynamic evaluation demonstrated that the adsorption process is spontaneous and thermodynamically favorable. In addition, all combinations of nanoparticles showed satisfactory regeneration ability, maintaining considerable adsorption efficiency for up to three successive reuse cycles.
Antibiotics, copper oxide NPs, iron oxide NPs, synthesis and characterization, adsorption studies.