Volume 14 | Issue 4

 Abstract

Scabies, known as Jarab in the Unani (Greco-Arabic) system of medicine, is a persistent and highly contagious skin infestation that remains a significant global health burden, particularly in resource-limited and overcrowded environments. This integrative review synthesizes classical Unani medical doctrines with modern dermatological findings to provide a comprehensive understanding of the disease's etiopathogenesis. Historically, Unani scholars such as Rabban al-Tabri, Al-Razi, and Ibn Sina provided remarkably detailed descriptions of Jarab, identifying it as a manifestation of humoral imbalance, specifically the corruption of blood (Fasade Dam) and the accumulation of morbid humors (Khilt-e-Raddi). Notably, 10th-century Unani physicians like Ahmad bin Mohd Tabri were among the first to document the parasitic nature of the disease, describing a "lice-like" insect as the causative agent centuries before its official recognition in Western medicine. This paper critically analyzes the Unani classification of Jarab based on humoral dominance and morphological presentation, categorizing it into humid (Ratab), dry (Yabis), and other variants and explores the physiological parallels between the traditional concept of "heat in blood" (Hiddat-e-Dam) and the contemporary immunological understanding of Type-IV delayed hypersensitivity. Furthermore, the review evaluates the therapeutic efficacy of traditional blood purifiers (Musaffiyat-e-Dam) and topical herbo-mineral formulations containing sulfur and neem. By integrating historical development, conceptual depth, and modern therapeutic challenges such as emerging drug resistance, this review advocates for a holistic, integrative approach to managing this neglected tropical disease.

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 Keywords

Scabies, Jarab, Unani Medicine, Humoral Theory, Sarcoptes scabiei, Fasade Dam

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The exponential accumulation of digital documentation across professional domains has rendered manual information retrieval both impractical and error to prone. Cloud-based question-answering (QA) solutions, while capable, raise significant concerns regarding data confidentiality, unpredictable hallucinated outputs, and reliance on continuous internet access. This paper introduces InsightDoc, a locally executed, privacy-centric document QA framework that couples Term Frequency-Inverse Document Frequency (TF-IDF) retrieval with a locally hosted, lightweight large language model (LLM) to generate answers strictly from user-supplied PDF documents. The proposed architecture operates entirely offline by deploying the Qwen 1.8B language model through the Ollama runtime environment. The system extracts and normalizes textual content from PDFs, partitions it into sentence-bounded chunks, constructs a TF-IDF sparse index, retrieves the most contextually relevant passages via cosine similarity, and delivers the assembled evidence to the LLM for grounded answer generation. Evaluation on a 50-question benchmark yields a retrieval Precision@5 of 0.76, an F1 Score of 0.73, and a mean retrieval latency well below 0.2 seconds, with zero observed hallucinations. InsightDoc provides a practical and resource-efficient baseline for offline document QA, ensuring verifiable data sovereignty.

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Retrieval-Augmented Generation (RAG), TF-IDF Vectorization, Local Large Language Model, Document Question Answering, Cosine Similarity, Information Retrieval, Ollama, Privacy-Preserving AI.

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Sushruta is venerated as the primordial surgeon who pioneered reconstructive and aesthetic procedures, earning the epithet "Father of Plastic Surgery." His magnum opus, the Sushruta Samhita, remains the most comprehensive surgical compendium in Ayurveda, meticulously delineating practical operative techniques. Conceived as a didactic manual, it was intended to guide physicians in delivering holistic patient care. Equally eminent, Acharya Charaka endorsed Shalya Tantra--the surgical discipline--for conditions necessitating urgent intervention, such as Bhagandara (fistula), Arsha (hemorrhoids), and Mudhgarbha (obstructed labor). The surgical armamentarium described in Ayurvedic treatises was ingeniously fashioned from organic materials including timber, lithic implements, broad foliage, and arboreal branches. A distinctive convention was the christening of instruments after fauna and avian species, a nomenclatural practice that persists in modern surgical taxonomy. Rigorous Yogya (preparatory training) was mandated for apprentices prior to undertaking actual operations. The Sushruta Samhita furnishes exhaustive expositions on surgical classifications, instrumentation, suturing methodologies, ligatures (Bandhana), protocols of informed consent, and the establishment of operative theatres (Shalyagar). Remarkably, these principles continue to resonate as foundational standards in contemporary surgical practice.

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Mudhagarbha, Shalyagar, Bandhana

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Rabindra Nath Tagore, the embodiment of wisdom and perfection occupies the most coveted and aspired throne in the realm of Indian English literature. This most versatile grate of his time, Rabindra Nath Tagore left no genre of literature un-attempted. Poems, Novels, Plays, short stories, various kinds of prose and miscellaneous writing followed ceaselessly from his fertile heart and mind. Although he left no genera of literature untouched, he is mostly acclaimed for his achievement as a poet, specially for his Magnum Opus 'Gitanjali' for which he won the Nobel Prize in the year 1913. His poetic talent and exposure reached new heights as he was acclaimed all over the World with the publication of Gitanjali in 1912 . This paper is an attempt to explore the underlying spiritualism in the poetry of Rabindra Nath Tagore, specially in Gitanjali and the way Tagore achieves spiritual enlightenment in his poetry by dwelling in the World of the Divine.

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Spiritualism, Eco-Feminism, Ecology, Deep Ecology, divine, Union

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Sportswear clothes are designed with consideration of performance, comfort, and functionality for those people taking part in physical exercise with design factors changing with varying levels of exercise intensity. The most frequent types of fabrics used include polyester-cotton blend which comes in two major designs; compression and loose designs. This work will focus on defining the characteristics of each material and fit in terms of comfort and physiological performance. Every material and fit have advantages and disadvantages. Polyester-cotton blends are soft and comfortable although they retain moisture after prolonged exercise periods. Polyester allows for better moisture removal and faster drying as well as being durable. Compression design ensures proper muscle support and reduces exhaustion although when tight it can create discomfort for the user. Loose design improves airflow and flexibility but provides little stability during rigorous exercises. Finally, materials and designs should be chosen depending on personal comfort perception, exercise level, and period. However, the use of polyester sportswear is considered the best because of its moisture management and performance.

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Sportswear, Polyester, Cotton, Compression, Breathability, Comfort, Performance

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E -commerce is now seen as a reality and a normal part of business plan. Companies planning to offer e -commerce should have long term vision and an objective to transform it to e- business which provide business value to shareholders. This paper throws light on the role of e- commerce in small business and recommend effective strategies for the implementation of e- commerce. When e -commerce strategies are used it improves customer service and interaction. Branding as it is more important it can make our brand more aware and popular. We can compete with bigger rivals and survive in the market. Future of e -commerce is tremendous as new players are entering into market and the government is taking various steps to stimulate trading through e -commerce Due to the change in life style and busy schedule people are reluctant to go for shopping. Instead, they can sit in homes and can get variety of products and services. Therefore, e-commerce is striving its way to success and the only way is that the business has to open their heart to e-customers to our business

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ROLE OF E- COMMERCE IN SMALL BUSINESS

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Keywords: Rotato cuff injury, Ultrasound therapy, Kinesio taping, Shoulder pain, Physiotherapy, Sports injuries

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The rapid expansion of the electric vehicle market has increased the need for transparent and accurate cost estimation methods for consumers, manufacturers, and policymakers. This paper presents a machine learning-based framework for the analysis and prediction of electric vehicle costs using technical and market-related vehicle attributes. A structured dataset containing features such as brand, acceleration, top speed, battery range, energy efficiency, fast-charging capability, plug type, body style, market segment, and seating capacity was used for model development. Data preprocessing techniques including missing value handling, feature encoding, normalization, and train-test splitting were applied to improve prediction quality. Multiple supervised learning algorithms, namely Linear Regression, Decision Tree, Random Forest, Support Vector Machine, and Artificial Neural Network, were trained and compared using standard regression metrics such as RMSE and R-squared. Experimental results showed that Random Forest and ANN models achieved superior predictive performance compared to traditional approaches, with Random Forest offering an effective balance between accuracy and computational efficiency. A web-based user interface was also developed to allow users to enter vehicle specifications and obtain real-time estimated costs. The proposed system demonstrates that machine learning can provide reliable and practical support for EV price estimation, helping reduce uncertainty in purchasing decisions and market analysis.

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Electric Vehicles, Machine Learning, Cost Prediction, Random Forest, Artificial Neural Network, Price Estimation, Regression Analysis, EV Market

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This study explores the evolving financial independence of women and its influence on their consumer behavior. Traditionally dependent on male family members for financial support, modern women are increasingly self-reliant, leading to a significant shift in their consumption patterns. This shift reflects greater autonomy in purchasing decisions and the freedom to acquire desired goods without restriction. The paper analyses female consumer behavior, examining how income levels and personal preferences influence buying patterns. Based on responses from female participants, the study aims to examine and interpret behavioural trends, drawing relevant conclusions about the impact of financial independence on consumption choices. The study focuses on female respondents to analyse behavioural changes in consumption and spending habits. Also, it investigates how increased autonomy influences women's purchasing decisions, particularly their freedom to buy desired products. The behavioral patterns are observed through primary data collection from female consumers, enabling informed conclusions. The significance of the study is to offer insight into the evolving role of women in the economy and the implications for marketers and consumer researchers.

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Female, consumer behavior, buying, consumption, Independence

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The overconsumption of medicine has become a pressing concern in public health, particularly in regions where healthcare systems are overburdened or inadequately regulated. This research paper investigates the growing trend of medication overuse, characterized by self-medication, irrational prescriptions and the misuse of both over the counter and prescription drugs. Key drivers include increased accessibility to pharmaceuticals, lack of awareness among the public, insufficient regulatory enforcement, and the influence of aggressive pharmaceutical marketing. Commonly overused drugs - such as antibiotics, sedatives and antacids are often consumed without proper medical supervision, leading to serious health consequences like drug dependency, organ toxicity, weakened immunity and increased drug reactions. Findings suggest that among 125 respondents through online survey , the majority of people (49.2%) consume cold/flu medicines which indicates a tendency toward self-treatment for common ailments which might lead to dependency or addiction if not properly guided while 91.9% people want to know more about safe medicine use , during menstruation 77.5% women do not take medication while 22.5% does which must be monitored to avoid addiction and long term side effects , 35.6% women rely more on herbal remedies than modern medications , almost 80% parents do not give medications to their child without prescription while 16.7% parents does which indicate a serious need for parental guidance , child safe drug practices. This research concludes by recommending rational use of drugs, public health awareness and foster more responsible medication practices.

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Overconsumption, Self-medication, Drug misuse, Public Health, Antibiotic resistance, Rational drug use.

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Acne is one of the most common skin diseases affecting people across different age groups, and accurate classification of lesion types is essential for effective dermatological diagnosis and treatment planning. However, manually assessing acne lesions can be both subjective and time-consuming, which has driven the development of automated computer-aided diagnostic systems. In this context, the authors propose a multiclass deep learning-based object recognition model for acne lesion classification using facial skin images. The system is designed to detect and classify various types of acne lesions, including blackheads, nodules, papules, pustules, whiteheads, as well as background regions. Initially, the skin images undergo preprocessing to enhance quality and reduce noise that could otherwise affect feature extraction. Subsequently, a deep learning model is employed to automatically learn discriminative visual features of different lesion categories. These learned features enable precise multiclass classification of acne lesions present in facial skin images.

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Acne classification, skin lesion detection, deep learning, multiclass analysis of skin diseases, and computer-aided dermatology.

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This study examines parental awareness of school-related stress in children among corporate-sector parents in Bengaluru. Using a descriptive quantitative design and a Likert-scale questionnaire, awareness was assessed across behavioral, emotional, communication, and physical domains. Findings indicate higher recognition of observable behavioral indicators, such as irritability and school avoidance, but lower awareness of internal emotional indicators like anxiety and withdrawal. The study highlights the need to improve parental emotional sensitivity, strengthen communication, and implement awareness programs.

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parental awareness, school-related stress, children, behavioural indicators, emotional awareness, communication

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The law of evidence plays a crucial role in the administration of justice, as it sets the rules for proving facts in court. One important type of evidence is expert evidence, which is especially useful in cases that involve specialized knowledge, like science, medicine, or technology. Recently, India introduced a new law called the Bharatiya Sakshya Adhiniyam, 2023, which updates the old Indian Evidence Act of 1872. This paper looks at how the new law handles expert evidence, focusing on its scope, reliability, and its judicial evaluation. Using a framework that considers the role of institutions in shaping public policy, this study argues that expert evidence is only effective if the institutions that support it, such as courts, forensic labs, police, and regulatory bodies, are functioning well. The paper also examines how courts use expert opinions, showing that they are often seen as advisory rather than definitive. It highlights current challenges, including inadequate forensic infrastructure, delays in getting expert reports, questionable scientific methods, and judges relying too heavily on specialized evidence. In conclusion, while the new law strengthens the framework for using scientific and digital evidence, its success depends on significant reforms to institutions, professional training, and judges' ability to critically evaluate expert evidence. This is essential to ensure that justice is served and that expert evidence is used effectively in court. The new law is a step in the right direction, but it requires a broader effort to build a durable well-designed system that supports the use of expert evidence in India's justice system.

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Expert Evidence, Bharatiya Sakshya Adhiniyam,2023, Judicial Evaluation, Reliability of Evidence, Forensic Science, Opinion Evidence, Indian Evidence Law, Institutional Model, Digital Evidence, Criminal Justice Reform.

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This paper presents a proposed web-based employee performance tracking system designed to improve organizational efficiency and productivity. The system allows administrators to monitor employee activities, evaluate performance, and generate reports in real time. It provides features such as task assignment, progress tracking, attendance management, and performance analysis. The proposed solution is user-friendly, scalable, and helps organizations make data-driven decisions. By digitizing the performance evaluation process, the system reduces manual effort and enhances transparency and accuracy in employee assessment.

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Web-Based System, Employee Performance, Performance Tracking, Web Development, Data Management, Productivity, Monitoring System

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Traditional drug discovery is a costly, time-intensive, and high-risk process, with a single approved therapy requiring over $2.6 billion and more than a decade of research. Artificial Intelligence (AI) has emerged as a transformative force with the potential to fundamentally reshape every stage of the pharmaceutical pipeline -- from target identification and protein structure prediction to molecular design, ADMET profiling, and clinical trial optimisation. This paper presents a comprehensive review of AI applications, techniques, and real-world case studies in drug discovery. We examine core AI methodologies including deep learning, graph neural networks (GNNs), generative models, reinforcement learning, and transformer-based architectures, alongside landmark tools such as DeepMind's AlphaFold 3, Insilico Medicine's GENTRL, and BenevolentAI's knowledge-graph platform. Six structured tables map current limitations, technique comparisons, pipeline stages, real-world deployments, projected metrics, and known challenges. A four-phase experimental roadmap is proposed as a falsifiable path to empirical validation. Despite demonstrated successes, the field faces persistent barriers: data quality, model interpretability, wet-lab integration, and evolving regulatory frameworks. This review concludes that AI's role in drug discovery is transitioning from speculative promise to early clinical validation, and that multimodal foundation models, self-driving laboratories, and physics-informed AI will define the next era of pharmaceutical innovation.

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artificial intelligence, drug discovery, machine learning, deep learning, AlphaFold, generative models, ADMET prediction, graph neural networks, clinical trials, drug repurposing, reinforcement learning

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This study investigates the nutritional potential and functional properties of Fucus vesiculosus, a brown macroalga recognized for its bioactive compounds, including phlorotannins, fucoidan, and fucoxanthin. F. vesiculosus demonstrates significant ecological, pharmaceutical, and industrial relevance, particularly in marine ecosystems and animal nutrition. The research highlights its seasonal ecophysiological variations driven by environmental factors, emphasizing the importance of its nutrient profile, which includes essential amino acids, minerals, and antioxidants beneficial for animal health and growth. The study further explores the hypolipidemic effects of phlorotannin-rich extracts, which have shown promise in improving lipid metabolism and mitigating hyperlipidemia in animal models, thereby potentially reducing atherosclerosis risk. Additionally, the antioxidant and anti-inflammatory properties of fucoidan are examined, revealing its role in modulating immune responses and preventing chronic inflammation-related diseases. Despite the limited research on F. vesiculosus in animal nutrition, its unique bioactive profile positions it as a valuable candidate for further exploration. This comprehensive characterization of F. vesiculosus aims to bridge existing gaps in literature and facilitate its empirical application in enhancing animal productivity and health, setting the stage for subsequent in vivo studies.

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Fucus vesiculosus, Fucoidan, Fucoxanthin, Phlorotannins, Anti-cancer activity.

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The overwhelming success of molecular engineering in controlling nonlinear optical properties in last decade has prompted better initiative in crystal engineering. In the present study a new inorganic nonlinear optical single crystal has been successfully grown form aqueous solution by the slow evaporation technique at room temperature. The crystals obtained by the above technique were subjected to different characterization analysis. The crystalline nature of the grown crystal was analyzed by powder X-ray diffraction. Single crystal X-ray diffraction study reveals that the crystal belongs to orthorhombic system with non-centrosymmetric space group Pbam. Optical transmission study on crystal shows high transmittance in the entire UV-Vis region and the lower cutoff wavelength is found to be 240 nm. The mechanical strength of the grown crystal was estimated by Vicker's micro hardness test. The second harmonic generation (SHG) efficiency of the crystal was measured by Kurtz's powder technique infers that the crystal has nonlinear optical (NLO) efficiency 1.32 times that of KDP.The dielectric constant and dielectric loss of the compound were measured at different temperature with varying frequencies. Photoconductivity study confirms that the title compound possesses a negative photoconducting nature. Growth mechanism and surface features of the as grown crystals were analyzed by chemical etching analyzing.

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nonlinear optics, XRD, second harmonic generation

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The increasing integration of digital technologies into everyday life has significantly transformed patterns of human interaction, raising concerns regarding their influence on interpersonal relationships and emotional well-being. The present study examines the relationship between digital dependence, interpersonal relationship quality, and loneliness among individuals across different age groups.

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digital dependence, interpersonal relationships, loneliness, emotional well-being, social media use.

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Schiff base have appreciable recognition in literature . It is a part of organic chemistry. It shows nitrogen with double bond in stereochemistry. It belongs to azomethine group with structural formula RHC=NR1. Primary amines and carbonyl compounds react to derived Schiff base from condensation reaction. In 1864 schiff reported this reaction. It attracts the attention in literature. A number of studies represented SP2 hybridized orbital of nitrogen atom with lone pair with electrons. The stable molecule of Schiff base with metal indicates medicinal properties as anticancer , antimicrobial , anti inflammatory and anti fungal properties.

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Schiff base ; Stereochemistry ; Condensation ; Hybridized orbital ; Medicinal properties.

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Crop Disease Detection, Deep Learning, EffiecientNetB4, Transfer Learning, PlantVillage Dataset, Image Classification, Precision Agriculture.

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