Volume 13 | Issue 10

 Abstract

This comparative financial analysis will provide comparison of performance of top 3 indian Quick Service Restaurant (QSR) i.e. Jubilant foodworks ltd, Devyani international ltd, Westlife foodworld ltd for period 2021-2025. In research, Comparison has been conducted on the basis ratio analysis, mainly focusing on liquidity and profitability. It is secondary data based study and data gathered from annual audited reports published on their website and crosscheck with money control. Such an analysis gives important inputs to stakeholders and future investors who are ready to know its position, strength and weakness of the companies.

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Liquidity, profitability, ratio analysis, qsr,jubilant foodworks ltd, Devyani international ltd, Westlife foodworld ltd.

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Accurate implant placement is essential for achieving functional, esthetic and long-term clinical success in implant dentistry. Traditionally, freehand surgery and static surgical guides have been employed to enhance precision. Recently, dynamic navigation systems (DNS), adapted from medical neurosurgical navigation, have gained attention in implantology. This review summarizes the principles, workflow, advantages, limitations and current evidence on the clinical performance of dynamic navigation systems for dental implant placement.[1-

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KEYWORDS: Dyanmic, implant, Precision.

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Banking is vital in India for promoting economic growth by channelling savings into investments, offering important financial services such as loans and payments, enhancing financial inclusion, assuring effective money management, and facilitating both domestic and international trade. The banking sector supports economic stability and growth by providing funds to businesses and individuals, thereby stimulating spending, investment, and overall economic activity. This study aims to analyse the regional growth of credit and deposits among scheduled commercial banks in India and to assess the impact of rising credit and deposits on the nation's economic growth. The gathered data were analysed using basic percentage growth, and to examine the relationship between credit growth, deposit growth, and their impact on economic growth, the study employed the Lenior regression model. Augmenting credit facilities will result in enhanced overall economic development. Consequently, the null hypothesis, which posits a positive correlation between bank credit and GDP growth, has been substantiated. Consequently, scheduled commercial banks must increase deposit mobilization and provide lending services to society to facilitate economic growth.

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Deposits, Credit, Region, Commercial Banks

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Indigenous tribal practices represent a vital source of knowledge, traditions, and cultural heritage that have evolved over many generations, characterized by a deep connection to nature and community life. Tribal groups worldwide, particularly in India, continue to actively and creatively engage in their traditional lifestyles, even in the face of modern industrialization and state-driven development. This review paper is based on secondary data and scholarly literature alone to explore how the practices continue, evolve, and are relevant in the contemporary world. The article highlights indigenous peoples' health, ecological, spiritual, and social practices, and the impact of modernization, policy adjustments, and economic transformations on their development. The review finds that indigenous practices are not static leftovers of history; they are viable and dynamic systems that may foster human and environmental sustainability as long as they are supported within a culturally responsive framework.

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: Indigenous practices, Ecological balance, Gandhian ideologies

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 Abstract

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A Study Of The Determinant Factors Of Uttarakhand's Mountain Women's Political Development.

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A Study Of The Determinant Factors Of Uttarakhand's Mountain Women's Political Development.

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The National Education Policy (NEP) 2020 identifies Foundational Literacy and Numeracy (FLN) as the most critical and non-negotiable goal of the Indian education system, emphasizing that every child must attain basic reading, writing, and numeracy skills by Grade 3. Translating this vision into classroom practice depends largely on the awareness, perception, and preparedness of elementary teachers who are the key implementers at the ground level. The present study examines the level of awareness, perception, and preparedness of elementary teachers in Ganjam district, Odisha, toward implementing Foundational Literacy and Numeracy (FLN) as emphasized in India's National Education Policy (NEP) 2020 and NIPUN Bharat Mission. Using a descriptive survey design, data were collected from 150 teachers through a validated awareness and perception scale, along with semi-structured interviews from 50 participants. The findings revealed that more than half of the teachers exhibited moderate awareness of FLN concepts and NEP 2020 provisions, while one-third demonstrated high awareness. Female teachers and those with less than ten years of experience showed significantly higher awareness and readiness levels. Although teachers displayed generally positive perceptions toward FLN, they reported practical challenges such as inadequate teaching-learning materials, large class sizes, and insufficient follow-up support. Qualitative insights emphasized the need for continuous professional development, contextualized assessment tools, and stronger parental involvement. The study concludes that sustained teacher training, academic mentoring, and adequate institutional resources are essential to effectively translate NEP 2020's foundational learning goals into classroom practice, thereby ensuring that every child achieves basic literacy and numeracy competencies by Grade 3.

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Foundational Literacy and Numeracy, NEP 2020, NIPUN Bharat, Teacher Perception, Elementary Education, Ganjam District, Odisha

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Nanaji Deshmukh's Pedagogical Approach: An Overall Assessment

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Nanaji Deshmukh's Pedagogical Approach: An Overall Assessment

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“EIGHTH GRADE STUDENTS HAVE DIFFICULTIES DOING MULTIPLICATION AND DIVISION CALCULATIONS WITH DECIMALS”

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“EIGHTH GRADE STUDENTS HAVE DIFFICULTIES DOING MULTIPLICATION AND DIVISION CALCULATIONS WITH DECIMALS”

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Predicting stock prices is a central challenge in finance. This paper examines stock price behavior through two fundamental models: the Random Walk and the Autoregressive model of order one (AR(1)). Using Monte Carlo simulations, we generate 50 independent price paths over 100 time periods, all starting at the same initial price. The Random Walk paths diverge rapidly, demonstrating unpredictability and randomness, while the AR(1) paths exhibit smoother, persistent trends, indicating some short-term predictability. Through these visual and statistical comparisons, the study highlights how memory in price dynamics influences predictability and provides a hands-on illustration of these competing views on financial market behaviour.

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Random Walk, Autoregressive, Simulation, Efficient Market Hypothesis

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The conceptual development of victimology and recognition of victims under legal justice system took its time to reach India, impacting the coordination between victim and justice responses. In present time, the retributive approach of relief for victims has taken a turn towards restorative justice implementation by the introduction of new enactment of three new criminal laws. Still an imbalance between the victim's safety and the perpetrator's accountability can be observed as there is no acknowledgment of victims as a community. This absence of the victim's cultural relevance as a community directly impacts the key elements that contribute to the victim's restorative justice programs and support services. This lack of coordination between community readiness toward victims, survivors' services, and judicial responses has left no place for the survivors to turn. The victim justice initiatives are in their initial stage in the country despite of all the insight provided by victimology into the psychological, social, and legal needs of the survivors. It needs optimizing and some structural enhancements to establish a haven for victims as a community to safeguard them from secondary victimization and help them heal psychologically and socially. In this paper, an endeavor has been made to discuss the development of victims as a community by introducing Alcoholics Anonymous (AA) Meetings model as a framework for survivors so that victim justice practices can effectively support survivors and restorative justice is taken a step forward towards therapeutic justice.

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mental healing, therapeutic justice, victim community, victim support programs, etc.

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This study provides historical and contemporary experiences of Meitei Pangal women in the Barak Valley that highlights the way cultural traditions, socio-economic pressures and patriarchal norms that have shaped their lives. These women have long been the essential contributor tot their family and community survival through agriculture, weaving, and informal labor, their dignity has been often constrained by practice such as child marriage, dowry and restrictive interpretations of marriage laws.Drawing on field observation, community interaction, Primary and secondary research paper, the paper traces the consistency of such challenges and the gradual shift taking place.This study unfolds the complex issues of the education inconsistency the prevalent practice of child marriage, Burdens of dowry, Misuse of word Polygamy and the societal pressures related to physical appearance and family status. It also documents the silent, ongoing revolution that sees a new generation of women reclaiming their worth challenge such long standing barriers and open pathways towards a more dignified future through education and professional achievements, despite a steady generational gap.

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Meitei Pangal, Barak Valley, child marriage, dowry, women's empowerment, gender roles, economic contribution, education inconsistency, Polygamy, cultural traditions.

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Career counseling is essential in guiding both stu- dents and professionals toward informed career decisions. How- ever, traditional counseling methods often fall short in terms of personalization, scalability, and responsiveness to the evolving job market. With recent advancements in Machine Learning (ML) and Explainable Artificial Intelligence (XAI), it is now feasible to develop intelligent systems that not only recommend suitable career paths but also provide clear, interpretable justifications for their suggestions.

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Career guidance, Explainable AI, Machine learning, Career counseling, Recommender systems, Skill gap analysis

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Phytochemical profiling of medicinal plants is an essential step in identifying bioactive compounds responsible for their therapeutic properties. The present study focuses on the qualitative and quantitative analysis of various plant species to evaluate the presence and concentration of major phytoconstituents such as alkaloids, flavonoids, tannins, saponins, glycosides, phenols, and terpenoids. Preliminary qualitative screening was performed using standard chemical tests, while quantitative estimation was carried out through spectrophotometric and chromatographic techniques. The results revealed significant variations in the phytochemical composition among the selected plants, indicating their diverse pharmacological potential. Such comparative profiling provides valuable insights for the development of plant-based drugs, standardization of herbal formulations, and further isolation of active principles. Overall, this study highlights the importance of systematic phytochemical evaluation as a scientific basis for the validation of traditional medicinal claims.

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Phytochemical profiling, Medicinal plants, Bioactive compounds, Qualitative analysis, Quantitative analysis, Alkaloids, Flavonoids, Tannins, Saponins, Glycosides, Phenols, Terpenoids, Spectrophotometry, Chromatography, Herbal standardization, Plant-based drugs.

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ABSTRACT: The primary focus of this study is the formulation of an Antifungal herbal shampoo using curry leaves as the main ingredient, known for strengthening hair follicles and promoting hair growth. This herbal shampoo aims to prevent hair loss, a common hair disorder, while enhancing hair growth, strength, and natural darkening. In addition to curry leaves, other natural components such as Amla, Aloe Vera gel, Neem, Hibiscus and Fenugreek were combined to create an effective and safe shampoo formulation. The shampoo is designed to clean hair by removing sebum, dirt, and dandruff, while avoiding the risks associated with chemical ingredients commonly found in commercial shampoos. Various forms of shampoo exist, including solid and liquid types, but the focus here is on a natural herbal liquid shampoo that emphasizes efficacy and safety. The formulated herbal shampoo was evaluated through physicochemical tests, including pH measurement, foam formation, surface tension, viscosity, and wetting ability, to ensure quality and performance

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Key Words: Herbal shampoo, Curry Leaves, Amla, Fenugreek, Aloe Vera, Guar Gum, Natural surfactants, Hair nourishment, Scalp health, Dandruff prevention, pH stability, Eco-friendly formulation.

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Adolescence represents a critical developmental stage characterized by rapid physical, emotional, and psychological transformations. Among the most prevalent psychological concerns in this phase is anxiety, which can adversely affect academic performance, social interactions, and emotional health. This study examines the effectiveness of counseling techniques in reducing anxiety among adolescents in Calicut district, Kerala. The sample consisted of 200 higher secondary school students aged 15 to 17 years, selected through stratified random sampling from both government and private schools. Utilizing a quasi-experimental design, the study implemented both quantitative and qualitative methods. Standardized anxiety inventories were used to assess baseline anxiety levels. Over an eight-week period, students participated in structured group counseling sessions that included cognitive-behavioral therapy (CBT), mindfulness-based practices, relaxation training, and supportive counseling. These sessions were conducted by trained mental health professionals, emphasizing the development of coping skills, emotional regulation, and cognitive restructuring. Post-intervention assessments demonstrated a statistically significant reduction in anxiety levels among participants. CBT and mindfulness techniques were found to be the most effective in alleviating symptoms such as restlessness, concentration difficulties, and sleep disturbances. Female students and those with moderate to severe pre-intervention anxiety levels showed the greatest improvement. Qualitative data, collected through focus group discussions and reflective journals, further supported the findings. Students reported enhanced emotional awareness, improved interpersonal relationships, and an increased sense of self-efficacy. These results underscore the potential of structured counseling interventions to mitigate adolescent anxiety in educational settings. The study recommends the integration of professional counseling services in schools, the training of school counselors, and awareness initiatives targeting educators and parents. Given the ongoing psychosocial challenges faced by adolescents--especially in the post-pandemic context--such mental health support is both timely and essential. In conclusion, the research highlights the significant role counseling techniques play in promoting emotional resilience and mental well-being among adolescents. When thoughtfully implemented, these interventions can empower young individuals to cope effectively with the challenges of adolescence and support their overall developmental trajectory.

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adolescent anxiety, counseling techniques, cognitive-behavioral therapy, mindfulness, school mental health, Kerala

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Adolescent depression has considered as a serious mental health issue, particularly in rural areas where access to psychological services is limited. This study investigates the effectiveness of school-based counseling programs in managing depressive symptoms among higher secondary students in a rural Indian setting. A sample of 200 students aged 15 to 17 years was selected from three government-aided rural higher secondary schools using stratified random sampling. Depression levels were measured using the Beck Depression Inventory-II (BDI-II) before and after the implementation of an 8-week structured counseling intervention. The intervention, conducted by a trained school counselor, involved weekly group and individual sessions incorporating cognitive-behavioral strategies, stress management techniques, emotional awareness activities, and peer support components. Statistical analysis showed a significant reduction in post-intervention depression scores, indicating the positive impact of counseling on adolescent mental health. Students reported increased emotional regulation, reduced feelings of hopelessness, and improved classroom participation. The findings highlight the potential of school-based mental health services to address depression in underserved rural populations. The study recommends the integration of professional counseling services within the school system as a sustainable and accessible mental health support strategy for adolescents. This approach could bridge the existing treatment gap and promote emotional well-being in rural youth. The method adopted for the paper is gathering as many as information from reliable sources by analyzing the collected information with related to the existing condition of the school based programs, and reached certain conclusions. The conclusions are implemented to address adolescent's problems.

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Adolescent Depression, School-Based Counseling, Rural Adolescents, Mental Health Intervention, Emotional Well-being, Cognitive Behavioral Therapy, Indian Schools, Psychological Support, Student Counseling, Early Intervention

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Abstract--In today's competitive job market, it is essential for candidates to have well-structured and Application Tracking System (ATS)-friendly resumes that align with job requirements. This project presents an AI-based Resume Analyzer and Job Matching System developed using Machine Learning and Natural Language Processing (NLP) techniques. The system analyzes a user's resume to identify grammatical errors, formatting issues, and ATS compatibility. It also evaluates the similarity between a candidate's resume and a given job description by applying text embedding and similarity scoring models. Using algorithms such as TF-IDF and cosine similarity, or transformer-based embeddings like BERT, the system calculates a match percentage to determine how closely the resume fits the job criteria. If the similarity score is low, the model provides suggestions for improvement, including missing keywords or recommended sections to make the resume more ATS-friendly. The entire process is implemented locally using Python, ensuring data privacy, offline accessibility, and fast execution. This intelligent system aims to assist students, job seekers, and recruiters by automating the resume evaluation process, improving candidate profiles, and enhancing the chances of shortlisting in real-world recruitment systems.

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AI Resume Analyzer, Machine Learning, Natural Language Processing, ATS Compatibility, Job Description Matching, Text Mining, Semantic Similarity, Python, NLP Pipeline, Career Recommendation System.

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Water quality is a vital factor influencing human health, industrial productivity, and agricultural yield. Hard water, containing high concentrations of dissolved minerals such as calcium and magnesium, causes scaling in pipelines, reduces the efficiency and lifespan of household appliances, and increases soap consumption. Traditional water softening systems often lack continuous monitoring and automated control, leading to inefficient operation, excessive resource consumption, and unpredictable water quality. This project proposes the design and development of a Hard Water Softener with Automated Quality Monitoring, capable of real-time measurement of pH, Total Dissolved Solids (TDS), and specific mineral concentrations. The system integrates an ion-exchange resin softening unit with an array of digital water quality sensors. These sensors feed continuous data to a microcontroller-based control unit, which analyzes the parameters and automatically activates or regulates the softening process as per predefined thresholds. The monitoring system is complemented by an LCD display and IoT- enabled remote access, allowing users to track water quality trends and system performance from anywhere. Index Terms--Hard Water, Water Softener, Automated Quality Monitoring, pH Sensor, Total Dissolved Solids (TDS), Mineral Detection, Ion Exchange, Internet of Things (IoT), Smart Water Management, Real-Time Monitoring, Predictive Maintenance, AI Integration, Secure IoT Systems, Water Treatment Automation.

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Hard Water, Water Softener, Automated, Quality Monitoring, pH Sensor, Total Dissolved Solids (TDS), Mineral Detection, Ion Exchange, Internet of Things (IoT), Smart Water Management, Real-Time Monitoring, Predictive Maintenance, AI Integration, Secure IoT Systems, Water Treatment Automation

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The rapid proliferation of Internet of Things (IoT) devices in modern power systems has transformed the landscape of energy management, enabling real-time monitoring, predictive maintenance, and decentralized control. However, the exponential growth in data generation poses significant challenges for conventional cloud computing (CC) infrastructures, including high latency, bandwidth congestion, and security vulnerabilities. To address these limitations, emerging paradigms such as fog computing (FC) and edge computing (EC) offer localized processing closer to the data source, reducing latency and optimizing network resources. This review paper examines the integration of CC, FC, and EC within smart grid architectures, highlighting their technical advantages, implementation challenges, and contributions to enhancing system efficiency, resilience, and adaptability. Furthermore, the paper analyzes hierarchical EC architectures, including device, edge server, and cloud layers, and their role in enabling real-time energy management, fault detection, and adaptive control. The findings underscore the critical role of hybrid computing models in supporting large-scale, latency-sensitive, and data-intensive smart energy systems, while emphasizing the need for continued research in secure, scalable, and intelligent computational

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Smart Grids, Edge Computing, Cloud-Fog Integration

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