Volume 13 | Issue 2 |

 Abstract

Inflammation is a complex biological response of the body's immune system to harmful stimuli, including pathogens, damaged cells, toxins, or irritants. While acute inflammation serves as a protective mechanism to eliminate the initial cause of cell injury and initiate tissue repair, chronic inflammation can contribute to the development of various diseases, such as cardiovascular disorders, neurodegenerative diseases, cancer, and autoimmune conditions. The inflammatory response is mediated through a cascade of cellular and molecular events involving immune cells, cytokines, chemokines, and signaling pathways such as nuclear factor-kappa B (NF-?B), mitogen-activated protein kinases (MAPKs), and Janus kinase/signal transducer and activator of transcription (JAK/STAT) pathways. Organ-specific inflammation, including neuroinflammation, pulmonary inflammation, and hepatic inflammation, highlights the localized impact of dysregulated immune responses, leading to tissue damage and disease progression. Understanding the molecular mechanisms and pathways involved in inflammation is crucial for developing targeted anti-inflammatory therapies. This review explores the fundamental aspects of inflammatory mechanisms, the activation of inflammatory pathways, organ-specific inflammation, and current therapeutic approaches targeting inflammation.

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 Keywords

Inflammation, Acute Inflammation, Chronic Inflammation, Inflammatory Pathways, Cytokines, Organ-Specific Inflammation, Anti-inflammatory Agents

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Morphometric analysis is important in any hydrological investigation and it is inevitable in development and management of drainage basin. This paper shows on the one-dimensional quantification of a tributary Kushkarni river basin. The detail study suggests that the topographic region of this basin is almost mountain and the basin is a 3rdorder river basin. The analysis reveals that the stream order varies from 1 to 3 and the total number of stream segments of all orders counted as 41, out of which the maximum area is covered by 1st order streams and the minimum by 3rd order.

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 Keywords

Linear Parameters, Bifurcation Ratio, Length Ratio, Law of Stream Length, Allometric Growth, Junction Angle

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In present study, Iron oxide nanoparticles were synthesized using Pongamia pinnata leaves and characterised by UV-visible spectroscopy,FTIR,and SEM.The synthesized nanoparticles were spherical in shape with an average particle size of 500 nm and confirmed by Scanning electronic microscopy (SEM).The FT-IR spectrum revealed the functional groups of the phytoconstituents present in Pongamia pinnata leaves. Green synthesized iron oxide nanoparticles showed antifungal activityagainst Candia albicans,Aspergillus flavus,Aspergillus niger .The results support the advantages of using simple and cost effective bio-green method for synthesizing iron oxide nanoparticles with anti fungal activities.

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 Keywords

Pongamia pinnata; Iron oxide nanoparticle,UV- Visible Spectrophotometry, FTIR, SEM.

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Service quality is a critical factor influencing customer satisfaction and loyalty in the competitive banking sector. This study assesses the service quality of HDFC Bank utilizing the SERVQUAL model, focusing on five dimensions: reliability, responsiveness, assurance, empathy, and tangibles. Targeting the young adult demographic (18-25 years) with savings accounts, the research identifies significant gaps in service quality, particularly in reliability, assurance, and responsiveness, which substantially impact customer satisfaction. Demographic analysis reveals that 73% of respondents are male, 56% earn below INR15,000 monthly, and 48% have been customers for less than a year. Statistical analyses indicate that reliability and assurance are the strongest predictors of satisfaction, with tangibility moderately influencing assurance. Limited engagement frequency, insufficient personalization, and underutilized tangible resources are identified as barriers to fostering customer loyalty. This study presents empirical recommendations for HDFC Bank, including enhancing reliability, improving personalization, and leveraging physical and digital resources to meet customer expectations, cultivate trust, and drive long-term satisfaction and loyalty.

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 Keywords

Service Quality, SERVQUAL Model, HDFC Bank, Customer Satisfaction, Young Adults, Digital Resources

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This study evaluates the performance of six machine learning classifiers on publicly available scRNA-seq datasets. The dataset was preprocessed using normalization, scaling, and feature selection. Gradient Boosting achieved the highest accuracy (82% on the test set before balancing), followed by Random Forest (75%) post-balancing. Hyperparameter tuning further optimized model performance, with the best model achieving 90.77% training accuracy and 82% test accuracy. Cross-validation confirmed model robustness, ensuring generalizability and reduced overfitting. The study emphasizes the importance of feature selection, ensemble learning, and data augmentation techniques in improving classification performance. Future research should explore deep learning models and multi-omics data integration for enhanced breast cancer subclassification.

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 Keywords

Breast Cancer Subclassification, Machine Learning, sc-RNA-seq, Random Forest, Gradient Boosting, SMOTE, Hyperparameter Tuning.

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As India continues to experience rapid economic growth and urbanization, the demand for electricity is rising steadily. To meet this demand sustainably, the country has set ambitious goals for expanding its renewable energy capacity, targeting 500 GW of non-fossil fuel-based capacity by 2030. This paper aims to forecast the installed electricity generation from renewable energy per capita in India until 2030, focusing on solar, wind, hydro, and biomass energy. Using historical data from 2014 to 2022.Additionally, the research considers key exogenous factors such as population growth, technological advancements, and policy shifts in India's renewable energy landscape. The results indicate a significant increase in per capita renewable energy generation, primarily driven by solar and wind power. However, challenges related to grid integration, energy storage, and regional disparities in energy access may affect the realization of these projections. This study provides valuable insights for policymakers, energy planners, and stakeholders in India's renewable energy sector, highlighting the need for continued investments in infrastructure and technology to ensure equitable and sustainable energy access across the country.

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 Keywords

Renewable Energy, Solar Energy, Wind Energy, Energy Forecasting, Regression Analysis, Energy Transition, Energy Demand Forecasting, Green Energy, Energy Policy, 500 GW Renewable Energy Target, Sustainable Development, Energy Systems Modeling, Energy Supply and Demand, India's Renewable Energy, Energy Planning, Climate Change Mitigation, Carbon Emission Reduction, Clean Energy Future, Energy Infrastructure, Forecasting Models, Statistical Modeling, Linear Regression, Time Series Forecasting,

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Abstract This study explores the intertwined struggles of Kali and Leila, protagonists from Perumal Murugan's One Part Woman and Elif Shafak's 10 Minutes 38 Seconds in This Strange World, who resist patriarchal oppression in distinct yet interconnected ways. Kali's identity is reduced to his reproductive ability, illustrating the rigid expectations of masculinity within his rural Tamil society. His inability to father a child diminishes his self-worth, exposing the limitations of patriarchal definitions of manhood. Conversely, Leila's defiance of societal norms regarding morality, sexuality, and respectability renders her body a site of strict social control. Her journey reveals the systemic oppression that restricts female autonomy under the guise of cultural propriety. By juxtaposing these narratives, this paper examines how patriarchal structures dehumanize both men and women, enforcing restrictive social roles that suppress individuality and freedom. Through a comparative analysis, the study underscores the urgent need to dismantle these oppressive frameworks, advocating for a reevaluation of gender norms that prioritize autonomy and equality over rigid societal expectations. Murugan and Shafak's narratives challenge the conventional constructs of masculinity and femininity, exposing the far-reaching consequences of patriarchal oppression. This paper argues for a broader, more inclusive discourse on identity and self-worth, moving beyond reproductive and moral roles to a more liberated and equitable social framework.

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Keywords: Patriarchy, Gender Norms, Masculinity, Femininity, Oppression, Autonomy Deconstructing Gendered Oppression: A Comparative Study of Masculinity

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This research investigates the continuation and switching behavior of cosmetic products among working women in Pondicherry, exploring factors such as product quality, brand loyalty, innovative features, and societal influences. The study, conducted through a questionnaire-based survey with an Opportunistic Random Sampling Method and a sample size of 150 participants, fills a significant knowledge gap in the local cosmetic market. Findings indicate a substantial impact of product quality, brand loyalty, and innovative features on consumer decisions. With a p-value of 0.04, the null hypothesis is rejected, affirming that the introduction of innovative features significantly influences the continuation behavior of working women in Pondicherry. The study contributes valuable insights for marketers and researchers, shedding light on the nuanced dynamics shaping consumer choices in the Pondicherry cosmetic market and emphasizing the need for tailored marketing strategies.

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Cosmetic,Advertisements, Purchase,Decisions, Celebrity,Endorsements, Women, switching behaviour

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Autism Spectrum Disorder (ASD) is a complex neurodevelopment condition characterized by challenges in social interaction, communication, and repetitive behaviors. Early and accurate diagnosis of ASD is crucial for effective intervention and treatment. Traditional diagnostic methods rely on behavioral assessments, which can be time-consuming and subjective. In recent years, machine learning (ML) techniques have emerged as powerful tools for automating and improving ASD detection by analyzing diverse data sources such as clinical reports, neuroimaging scans, genetic data, and behavioral patterns. This systematic review explores the latest advancements in ML-based ASD detection, highlighting various algorithms, feature selection methods, and performance metrics used in recent studies. We examine supervised, unsupervised, and deep learning approaches, emphasizing their strengths and limitations in ASD diagnosis. Additionally, we discuss the challenges associated with dataset availability, model interpretability, and generalization across diverse populations. The review aims to provide insights into the current trends and future directions of ML applications in ASD detection, ultimately contributing to the development of more efficient, accurate, and accessible diagnostic tools.

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 Keywords

Autism Spectrum Disorder, Machine Learning, Early Diagnosis, Neurodevelopment Disorder, Deep Learning

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The study aims to evaluate and visualize key scientometric indicators from the four most prolific journals in cancer research. Data retrieved from Scopus on December 6, 2024, were filtered to include publications from these journals. The analysis focused on growth metrics such as annual productivity trends, relative growth rate (RGR), annual growth rate, doubling rate, and growth ratios. Findings indicate an increase in doubling time from 0.82 to 9.90, alongside a decline in RGR from 0.84 to 0.07, reflecting the field's maturation. A comparative analysis revealed that the USA leads global contributions, followed by the UK, Germany, France, and Canada. This study provides quantitative insights into the performance of top cancer research journals and highlights the application of bibliometric tools to explore the intellectual structures within the discipline.

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 Keywords

Cancer research, Scientometrics, Bibliometric Analysis, The Lancet Oncology, Journal of Clinical Oncology.

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