Volume 13 | Issue 4

 Abstract

The overarching mystery of the novel serves as a major contributor for the emotional imbalance that is witnessed throughout the work. Emotional imbalance could be identified in the characters when they try to shift their emotions from one to another at an irregular pace. Emotions like anger, fear, despair and hope influence individuals to a great extent, and when a person shifts among these emotions rapidly and erratically, emotional imbalance becomes visible predominantly. Various factors contribute to emotional imbalance in 400 Days.

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Artificial Intelligence (AI) has emerged as a transformative force in manufacturing, enhancing efficiency, reducing costs, and improving quality control. The paint industry, characterized by complex production processes, is increasingly leveraging AI-driven solutions such as predictive maintenance, process automation, and real-time quality monitoring. This study examines the impact of AI implementation in paint manufacturing, focusing on three key areas: operational efficiency, cost reduction, and quality control. Using a mixed-method approach, including industry surveys and case studies, the research evaluates AI adoption levels, its tangible benefits, and the perception of industry professionals. Findings indicate that AI significantly enhances operational efficiency by optimizing workflows and reducing downtime. Cost savings are primarily observed through waste minimization and energy efficiency, while AI-driven quality control mechanisms improve product consistency. However, challenges such as high implementation costs and workforce adaptation persist. The study concludes with recommendations for scalable AI adoption in the paint manufacturing sector.

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Artificial Intelligence, Paint Manufacturing, Cost Reduction, Quality Control, Operational Efficiency.

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Recruitment processes have undergone considerable change with the introduction of automation tools and analytics in the field of Human Resource (HR) management. This research examines the influence of HR automation tools on recruitment efficiency which includes candidate sourcing, evaluation, and decision-making pertaining to hiring. This study analyzes multiple HR technologies such as applicant tracking systems (ATS), chatbots, and predictive analytics, and illustrates their impacts on reduced hiring timelines, candidate experience, and bias mitigation. The research also analyzes how insights derived from data aid the decision-making process and detail the impact on the strategic hiring decision. The study intends to provide implementable propositions regarding recruitment strategy optimization through analysis of leading automation tools and case studies of organizations that incorporated these tools into their processes. The results of the research indicate that there is a growing need for incorporating automation and analytics into human resources workflows to optimize efficiency, scalability, and fairness in the hiring process.

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HR Automation, Recruitment Efficiency, Digital Transformation in HR, Applicant Tracking System (ATS), Automated Resume Screening, Hiring Process Automation

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Deep Convolutional Neural Network, Cancer Blood Disorder, Classification, Machine Learning.

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In Response To Escalating Environmental Concerns, Sustainable Packaging Has Emerged As A Critical Focus For Industries Aiming To Reduce Ecological Footprints And Meet Consumer Expectations. This Study Explores The Role Of Generation Z And Millennials--Collectively Termed "Generation Green"--In Influencing Corporate Decisions On Sustainable Packaging. By Employing A Mixed-Methods Approach, Including Surveys And Case Study Analysis, The Research Assesses The Relationship Between Youth-Driven Sustainability Values And Brand Loyalty. Findings Reveal That Educational Attainment Significantly Enhances Environmental Consciousness Among Youth, While Age And Gender Have Negligible Effects. Although Sustainable Packaging Is A Growing Demand, Its Impact On Brand Loyalty Appears Limited, Suggesting That Additional Factors Influence Consumer Retention. The Research Provides Key Insights For Companies Aiming To Align Packaging Strategies With The Expectations Of Environmentally Conscious Consumers.

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Sustainable Packaging, Generation Green, Environmental Consciousness, Brand Loyalty, Youth Consumer Behavior, Eco-Friendly Strategies

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Financial inclusion serves as a vital catalyst for economic advancement and societal progress, ensuring that both individuals and enterprises can access reasonably priced financial services. Digital payment systems have surfaced as a crucial facilitator of financial inclusion by offering affordable, secure, and efficient financial options. This document investigates the influence of digital payment systems on financial inclusion, evaluating their advantages, obstacles, and future opportunities. The research delves into the significance of mobile money, digital wallets, and online banking in enhancing financial accessibility, especially for marginalized communities. Empirical data indicates that digital payments foster economic empowerment by lowering transaction expenses, improving convenience, and encouraging financial literacy. Nonetheless, issues such as cybersecurity threats, lack of digital skills, and regulatory challenges remain. The paper wraps up with policy suggestions aimed at optimizing the advantages of digital payment systems for comprehensive financial development. Content marketing revolves around creating and distributing meaningful, pertinent content to engage with your audience. The goal? To not only grab attention but to maintain it and foster a long-term relationship. A successful content marketing approach acts like a loudspeaker for your brand in a busy market. It's not merely about making sales; it's about leaving a memorable impact that lingers when customers are prepared to make a choice. Ultimately, it's about narrating your story in a memorable manner that ignites that bond with your audience.

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Digital Payments, Financial Inclusion, Debit Cards, Credit Cards, Economic Factor, Demographic Variables, Quantitative Analysis

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This paper discusses the development of a peculiar script born from the confluence of Arabic and Malayalam languages in Malabar, Kerala. The study follows the historic traces of Arabi-Malayalam and traces its nativity to the early Arab traders' interactions with the local people speaking in Malayalam. The paper establishes this through an analysis of historical documents, manuscripts, and oral traditions that establish the emergence of this script system through adapting Arabic script to represent Malayalam phonetics. It looks at how oral tradition was put into the written text, challenges in the process of standardisation of the script, and whether techniques of performance of oral tradition were adequately adapted to the written medium. It also argues about how technological, logistic, and socio-political factors-configurations of colonialism and resistance-applied their influence upon both the development and dissemination of Arabi-Malayalam literature. The interviews reveal that Arabi-Malayalam has been and continues to be a steadfast contributor in this field, making serious contributions toward literacy and regional linguistic diversity. The paper reflects upon the renewed interest in Arabi-Malayalam in modern times as an essential component in the preservation of Kerala's cultural heritage against globalising pressures. The study is an exhaustive analysis of how Arabi-Malayalam has stood resilient and adaptable for generations, serving as a symbol of cultural synthesis and linguistic diversity within Malabar society.

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Arabi-Malayalam, Mappila, Kerala, Muslim, Language, Malabar

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Effective treatment of skin diseases requires drug delivery to specific skin compartments, such as the viable epidermis, dermis, and hair follicles. However, delivering drugs into and across the skin remains a significant challenge due to the complex barrier properties of the skin. A deeper understanding of skin barrier physiology is essential for optimizing drug penetration and permeation. To achieve this, it is crucial to thoroughly investigate the various skin barriers and develop reliable methods to assess their functionality, including the movement of molecules from the external environment into the skin (outside-in) and from within the skin to the outside (inside-out). This review provides a comprehensive overview of the mechanical barriers, such as the stratum corneum and tight junctions, within the interfollicular epidermis, hair follicles, and associated glands. It also explores the barrier roles of the basement membrane and dermal blood vessels. Alterations in skin barrier function, particularly in individuals with atopic dermatitis, are discussed in detail. Lastly, we critically evaluate current physical, biochemical, and microscopic techniques--such as transepidermal water loss measurement, impedance spectroscopy, Raman spectroscopy, immunohistochemical staining, optical coherence microscopy, and multiphoton microscopy--for their effectiveness in analyzing these barriers and assessing drug permeation both in vitro and in vivo.

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Keywords:Transdermal drug delivery,Skin barrie ,Stratum corneum,Tight junctions, Hair follicles,Basement membrane,Dermal blood vessels,Atopic dermatitis,Drug permeation,Skin physiology,Transepidermal water loss (TEWL), Impedance spectroscopy, Raman spectroscopy, Immunohistochemistry, Optical coherence microscopy, Multiphoton microscopy, In vitro permeation studies, In vivo skin analysis

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This study pioneers the development of an advanced digital tool utilizing artificial intelligence (AI) for the classification and informational enrichment of a wide array of food items, transcending the initial focus on fruits and vegetables. Aimed at revolutionizing the way individuals' access and interact with nutritional information, our project leverages a sophisticated convolutional neural network (CNN) alongside natural language processing (NLP) technologies. These are designed not only to accurately identify diverse food items from images but also to generate detailed, user-friendly content regarding their nutritional content, health benefits, and culinary uses. The research embarked with a comprehensive dataset, initially comprising over 10,000 images of 500 different fruits and vegetables, achieving an impressive 98% accuracy in image classification. This success laid the groundwork for the subsequent expansion of our dataset to include a broader spectrum of food items, addressing the critical need for a more inclusive and versatile nutritional information tool. Our findings, underscored by a pilot user study with 50 participants, indicate significant engagement and positive feedback, suggesting the tool's potential to significantly impact public health by enhancing nutritional awareness and food literacy across diverse populations. Moreover, the planned expansion to include a wider variety of food items reflects our commitment to adapt and respond to the evolving dietary needs and preferences of the global community. This research not only demonstrates the feasibility of applying AI in the domain of nutritional education and public health but also highlights the potential for such technologies to foster informed food choices, support dietary planning, and contribute to the broader goals of improving public health and nutritional awareness on a global scale.

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Artificial Intelligence, Food Classification, Nutritional Information, Dietary, Public Health, Convolutional Neural Network, Natural Language Processing.

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This review paper provides a comprehensive overview of derivative-free iterative methods for solving nonlinear equations. The study evaluates and synthesizes existing literature, highlighting the strengths and weaknesses of different techniques. The paper contributes by proposing a new family of iterative methods, specifically focusing on the application of divided difference operators and various approximations. The review identifies research gaps and challenges in the field, suggesting directions for future studies. The conclusion summarizes key findings, emphasizing the added value to the literature, and outlines foundational aspects for future research.

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Derivative-free methods, Iterative methods, Nonlinear equations, Divided difference operators, Research gaps.

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This study examines the integration of Automation in Human Resource Management (HRM) and its impact on strategic decision-making within organizations. As businesses strive to remain competitive, leveraging Automation-driven HR practices has become increasingly crucial. This research explores key human resources functions such as talent acquisition, employee development, performance evaluation, leveraging automated technology, and workforce planning, assessing how automation enhances these processes in terms of Human Resources. By analysing qualitative and quantitative data from organizations leveraging Automated technologies, the study highlights the transformative role of automation in improving decision-making, efficiency, and employee experience. The findings aim to provide HR professionals and business leaders with insights into designing Automated HR frameworks that align with organizational goals. Additionally, the study addresses challenges such as data security, ethical concerns, and employee adaptability, offering recommendations to ensure a balanced approach that leverages Automated technologies potential while maintaining a human-centric HR environment.

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Automation, leveraging, automated systems, HR, Professionals, integrating, organization, talent, skills, technology.

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The current study explores the effect of DeepSeek-based blended teaching mode on improving the comprehensive academic English ability of medical students. Through a quasi-experimental design, 36 clinical medicine students were divided into an experimental group (DeepSeek-enabled teaching) and a control group (traditional blended teaching) for an 18-week intervention. The experimental group integrated DeepSeek functions in the whole process of "before class-during class-after class", including personalized reading recommendations, intelligent correction of academic writing, and interactive training of terminology. Through standardized tests, learning log analysis and qualitative interviews, it was found that the experimental group was significantly better than the control group in academic writing (p<0.01) and literature reading (p<0.05), especially in the accuracy of terminology and the standardization of paper structure; but the improvement in oral ability was limited, which may be related to the insufficient adaptability of AI voice interaction to medical scenarios. The current study shows that DeepSeek can effectively empower blended teaching, solve the "reading and writing pain points" of medical EAP in a targeted manner, and provide practical references for intelligent medical English teaching. In the future, it is necessary to further optimize the discipline-specific corpus and multimodal interaction functions.

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DeepSeek Empowerment; Blended Teaching; Medical Students; Comprehensive Ability of Academic English; Improvement

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The partition of British India in 1947 was one of the most defining and traumatic events in South Asian history. It led to the creation of two sovereign nations, India and Pakistan, and was accompanied by large-scale violence and mass displacement. The division was primarily based on religious lines, with India emerging as a secular state with a Hindu-majority population and Pakistan as a Muslim-majority nation. However, the partition was quickly executed, resulting in communal riots that claimed over a million lives and forced nearly 15 million people to migrate across newly drawn borders. One of the most contentious outcomes of the partition was the unresolved status of Jammu and Kashmir. At the time of independence, princely states were given the choice to join either India or Pakistan. The Maharaja of Kashmir, Hari Singh, initially sought to remain independent but later agreed to India following an invasion by Pakistani-backed tribal militias. This decision led to the first Indo-Pakistani war (1947-1948) and resulted in the division of Kashmir into Indian-administered and Pakistani-administered territories, a dispute that remains unresolved to this day.

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Partition of British India

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ABSTRACT: Present investigations aim to analyse the tap water quality of Bilaspur district by water quality index. Eight physicochemical parameters such as Calcium, Magnesium, Chlorine, total hardness, pH, Electrical conductivity, TDS, Turbidity and also bacterial contamination. Out of total parameters studies, 80% water samples were bring into being good quality and only 20% of water trials falls under temperately poor category. Therefore, prerequisite treatment of drinking water can be done before usage and also the study area has to be protected from anthropogenic contamination.

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KEYWORDS: Drinking water, physio-chemical, Bilaspur, water treatment.

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This research articles explores the remarkable journeys of Indian entrepreneurs who have made significant strides in the global startup ecosystem. By examining their innovative approaches, resilience, and strategic decisions, we aim to highlight the factors that contributed to their success and the impact they have had on both the Indian and global markets. These case studies serve as inspiration for aspiring entrepreneurs and provide valuable insights into the dynamics of entrepreneurship in a rapidly evolving landscape. By highlights the backgrounds, key success factors, and impacts of Ritesh Agarwal (OYO Rooms), Kunal Bahl and Rohit Bansal (Snapdeal), Bhavish Aggarwal (Ola Cabs), N. R. Narayana Murthy (Infosys), Nikhil Kamath (Zerodha), Aman Gupta (boAt), Deepinder Goyal (Zomato), and Neeraj Kakkar (Paper Boat). Each entrepreneur's innovative approaches and strategic decisions have not only transformed their respective sectors but have also played a significant role in shaping the Indian economy and promoting entrepreneurship.

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Keywords: Entrepreneurship, Innovation, E-commerce, Hospitality, Technology

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Chronic inflammation is a common trait in the pathogenesis of several dis- eases of the gut, including inflammatory bowel disease and celiac disease. Control of the inflammatory response is crucial in these pathologies to avoid tissue destruction and loss of intestinal function. Over the last 50 years, the identification of the mechanisms and mediators involved in the acute phase of the inflammatory response, which is characterized by massive leukocyte recruitment, has led to a number of therapeutic options. New drugs targeting inflammatory flares are still under development. However, interest on the other end of the spectrum--the resolution and repair phases--has emerged, as promoting tissue functional repair may maintain remission and counter- act the chronicity of the disease. This review aims to discuss the current and future pharmacological approaches to the treatment of chronic intestinal inflammation and the restoration of functional tissues.

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Intestinal Inflammation,Inflammatory Bowel Disease (IBD),Pharmacological Interventions,Anti-inflammatory Agents

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The way people search for jobs has changed drastically with the rise of online job portals. These digital platforms have made it easier for job seekers and recruiters to connect, offering features like AI-driven job matching, mobile access, and real-time communication. This review takes a closer look at four key studies on job portals, comparing their strengths, weaknesses, and methodologies. It highlights how job portals have evolved, the challenges they still face, and potential improvements, such as better AI-based candidate profiling, seamless mobile experiences, and stronger security. Additionally, this paper discusses how government-backed platforms and emerging trends are shaping the future of online job searching.

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Jobs, Job Seeker, Job Application, Recruiter, Resume, Skills, Job Portal, AI in Recruitment, Mobile Job Search, Security in Job Portals, Blockchain in Hiring.

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Drug repurposing is an important area of research for pharmaceutical companies and chemical scientists. In the recent times, there has been an increased focus on the process of finding a new therapeutic use for already-approved medications. Machine learning (ML) and artificial intelligence (AI) algorithms are transforming drug repurposing because they can minimize risks, maximize efficiency, cut down on development time, and be inexpensive. This article discusses algorithms used in drug repurposing that are based on AI and ML. It also describes the ways in which methods from AI and big data have evolved to meet the growing demands of research in terms of planning development of drug candidates more efficiently and at a lower cost. With an analysis of current trends and recommendations for best practices, this study aims to give researchers a comprehensive understanding of how AI and ML may be utilized as a resource to help them navigate the always evolving field of drug discovery.

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Drug repurposing; Artificial Intelligence; Machine Learning; Deep Learning, Big data.

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Dielectric measurement of a binary mixture of Allyl Bromide with 2-Pentanone and 2-Hexanone was carried out over the entire concentration range using a Time-domain Reflectometer (TDR) at temperatures 293.15K, 303.15K, and 313.15K in microwave frequency range 10 MHz to 10 GHz. The static dielectric constant(?_s) and relaxation time(?) of binary mixture were determined which are further used to study excess static dielectric constant(?_s^E), excess inverse relaxation time??((1/?))?^E, effective Kirkwood correlation factor(geff), and Bruggeman factor(fB). These parameters are used to study intermolecular interaction between Allyl Bromide (ALB) and the carbonyl group of 2-Pentone (2-PE) and 2-Hexanone (2-HE). Intermolecular interaction of Allyl Bromide with 2-Pentanone and 2-Hexanone occurs through dipole-dipole interaction. The excess static dielectric constant and excess inverse relaxation time are fitted to Redlich-Kister equation.

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Static dielectric constant, Effective Kirkwood correlation factor, Relaxation time

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Abstract The "hard problem" of consciousness--explaining how subjective experience arises from physical processes--remains a persistent challenge in philosophy and science. Quantum physics, with its probabilistic, non-local, and observer-dependent nature, has emerged as a provocative framework for addressing this enigma, suggesting that consciousness may be intertwined with quantum processes. This article traces the historical evolution of quantum mechanics and its intersection with consciousness studies, critically examines key theoretical models (e.g., the Orchestrated Objective Reduction model), and evaluates their philosophical and empirical viability. While quantum approaches offer novel insights into the mind-body problem, they face significant hurdles in coherence, testability, and ontological grounding. The article concludes by proposing interdisciplinary pathways to refine these models, emphasizing the need for empirical validation and philosophical rigor to bridge quantum physics and consciousness.

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Quantum Physics, Consciousness, Hard Problem, Orch-OR, Philosophy of Mind, Quantum Mechanics

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