Volume 14 | Issue 5 |

 Abstract

Small and medium-sized businesses (SMEs) are crucial to the expansion of the economy and the creation of jobs, but they frequently struggle to get loans because of their inadequate credit history, lack of collateral, and incomplete financial documents. Many SMEs are financially opaque in the financing ecosystem since traditional credit scoring systems mostly rely on formal financial statements. In order to enhance SME loan default prediction in data-sparse settings, this study suggests an explainable multi-source machine learning architecture that incorporates alternative data sources such GST filings, digital payment behavior, cash-flow patterns, and transaction activities. To guarantee both forecast accuracy and transparency in lending decisions, the suggested system integrates Explainable Artificial Intelligence (XAI) methodologies with machine learning algorithms. While SHAP and LIME algorithms offer comprehensible explanations for loan approvals and rejections, models like Random Forest and XGBoost are employed for default prediction. The goal of the project is to develop a credit evaluation system that is transparent, dependable, and compliant with regulations in order to improve SME financial inclusion while upholding efficient risk management standards.

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 Keywords

Explainable AI (XAI), machine learning, loan default prediction, data sparsity, financial inclusion, credit risk analytics, multi-source data fusion, fintech, predictive analytics, and SME credit scoring

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Creative Commons Attribution 4.0 and The Open Definition

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Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the most common cause of dementia among elderly individuals worldwide. This review provides a comprehensive overview of the pathophysiology, stages, symptoms, diagnosis, and treatment strategies associated with AD. The disease is characterized by the accumulation of amyloid-? (A?) plaques and neurofibrillary tangles, leading to neuronal degeneration, cortical atrophy, and cognitive decline. The amyloid cascade hypothesis explains the role of A? accumulation in triggering tau hyperphosphorylation, neuroinflammation, oxidative stress, and synaptic dysfunction. Alzheimers disease progresses through multiple stages, including preclinical stage, mild cognitive impairment, mild-to-moderate AD, and severe AD. Common symptoms include memory loss, language impairment, behavioral disturbances, and reduced spatial awareness. Diagnostic approaches involve clinical examination, neurocognitive assessment, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid biomarker analysis.Currently available pharmacological therapies include cholinesterase inhibitors such as donepezil, rivastigmine, and galantamine, along with the NMDA receptor antagonist memantine. India faces major challenges in the management of AD because of its rapidly increasing elderly population, lack of awareness, social stigma, and limited healthcare access. Recent advances in immune therapeutics, gene therapy, stem cell therapy, artificial intelligence, and machine learning offer promising future directions for early diagnosis and disease-modifying treatment strategies. However, challenges related to disease heterogeneity, drug delivery, and ethical concerns still remain. Continued research is essential for improving the diagnosis, treatment, and overall management of Alzheimer's disease.

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 Keywords

Alzheimer's disease, Amyloid-? plaques, Neurofibrillary tangles, Dementia, Cognitive decline, Biomarkers, Neurodegeneration, Cholinesterase inhibitors.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Acne vulgaris is a common chronic inflammatory disorder of the pilosebaceous units, primarily caused by excess sebum production, microbial colonisation (Cutibacterium acnes), follicular blockage, and inflammation. Conventional therapies such as antibiotics and retinoids are associated with adverse effects, including irritation, dryness, and microbial resistance. Polyherbal formulations have gained increasing attention due to their synergistic therapeutic effects, safety, and reduced toxicity. The present study focuses on the formulation and evaluation of a polyherbal anti-acne gel, incorporating natural ingredients with proven anti-acne properties. Neem (Azadirachta indica) and Aloe vera (Aloe barbadensis Miller) were selected as key herbal components due to their antimicrobial, anti-inflammatory, and healing properties. Multiple gel formulations were developed by varying the concentration of these herbal extracts, and a comparative evaluation was carried out. The prepared formulations were evaluated for physicochemical parameters such as pH, viscosity, spreadability, extrudability, drug content, and antimicrobial activity. Stability studies were also conducted. Among the formulations, F2 exhibited optimal characteristics in terms of consistency, stability, and antimicrobial activity. The study concludes that polyherbal anti-acne gel is a safe and effective alternative to conventional treatments, and the combination of neem and aloe vera provides enhanced therapeutic benefits.

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 Keywords

Polyherbal Anti-Acne Gel, Acne Vulgaris, Azadirachta indica, Aloe barbadensis Miller, neem, aloe vera, herbal formulation, topical gel, antimicrobial activity, Carbopol gel, comparative study, phytoconstituents, skin disorders. Natural Therapy, Gel Formulation.

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 Abstract

Impact of Soil Physico-Chemical Variability on the Incidence and Population Build-up of Brown Planthopper (Nilaparvata lugens Stål) in Paddy Fields of Kafen, Muzaffarpur, Bihar

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 Keywords

Impact of Soil Physico-Chemical Variability on the Incidence and Population Build-up of Brown Planthopper (Nilaparvata lugens Stål) in Paddy Fields of Kafen, Muzaffarpur, Bihar

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the ever-evolving field of education, Computational Thinking (CT) has emerged as a pivotal instructional pedagogy. Computational Thinking (CT) has become a key component of contemporary education, promoting problem-solving abilities that are essential for navigating in a technology-focused world. Computational thinking is a problem-solving approach that draws on techniques and strategies from computer science. It encompasses skills such as decomposition, pattern recognition, abstraction, and algorithmic thinking, allowing individuals to address complex problems by breaking them into smaller, more manageable parts, recognizing patterns, and creating step-by-step solutions. This way of thinking is not limited to programming; it is a core skill applicable across many fields, enhancing critical and analytical thinking.As technology becomes increasingly intertwined with all aspects of life, developing computational thinking skills from an early age prepares students to meet the demands of the modern workforce. By incorporating computational thinking into education, teachers can help students systematically and creatively handle problems, making them better equipped to handle the challenges of the digital world. In this line this theme paper introduces Computational Thinking (CT) as an Innovative Pedagogy along with its Origin, Theoretical framework, Components of Computational thinking and its application in the classroom for student community.

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 Keywords

Computational thinking, Innovative pedagogy, decomposition, pattern recognition, abstraction, algorithmic thinking.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Most common cause of knee joint pain is osteoarthritis specially in old age patients. It is a degenerative condition which cause the disability in old age people. Even though Osteoarthritis is considered as a non-inflammatory arthritis, increasing evidence has shown that inflammation tends to occur as agents such as cytokines and metalloproteinases are released into the joint. It is characterised by growth of osteophytes at the articular ends, which make movements limited and painful. Patients present with pain and stiffness in joints, worsened activity and relieved by rest. Nearest correlation of this disease is janugata sandhivata, in which there is a manifestation of vitiation in vata dosha along with anubandha of Kapha dosha. Agnikarma can be considered as the best line of management of this disease as it mitigates both vata and kapha dosha. This paper is an effort to show the usefulness of Agnikarma in osteoarthritis. For this, the paper includes a case study of 68-year-old female patient who came with complaints of pain in both knees with having difficulty in walking, standing, not able to climb stairs, felt stiffness in joint after sitting and standing for some time for 5 years. Patient had taken various treatment including allopathic, physiotherapy treatments but got only temporary relief. Agnikarma was planned for her management. And in 3 sittings of 7 days interval she had shown marked improvement in her symptoms.

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 Keywords

Osteoarthritis, janugata sandhivata, Agnikarma

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Language is not merely a system of words but a living expression of culture, identity, and human connection. In a country like India, where linguistic diversity reflects centuries of civilization and tradition, the significance of Indian languages becomes profound. They serve as vessels of emotion, philosophy, and collective memory. However, globalization and the growing dominance of English have created a gap between cultural inheritance and contemporary communication. This paper explores the importance of Indian languages in shaping thought and preserving cultural integrity, while also analyzing how modern Indian author Preeti Shenoy employs English as a tool to express Indian values, emotions, and relationships. Although her works are written in English, they echo the rhythm, simplicity, and warmth of Indian linguistic traditions. Through her novels, Shenoy successfully bridges the local and the global--demonstrating that language, regardless of its medium, can retain the essence of Indian identity when rooted in authentic emotion and cultural consciousness.

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 Keywords

Language, Indian Literature, Preeti Shenoy, Cultural Identity, Indian English, Communication, Indian Languages, Globalization

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Creative Commons Attribution 4.0 and The Open Definition

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Ovarian cysts are among the most common gynecological disorders affecting women across various age groups and may lead to serious health complications if not detected and classified at an early stage. Accurate identification of cyst types such as simple, complex, and polycystic ovarian conditions plays a critical role in determining appropriate treatment strategies and improving patient outcomes. However, conventional diagnostic approaches primarily depend on manual interpretation of ultrasound images by radiologists, which can be time-consuming, subjective, and prone to inter-observer variability. To address these challenges, this research proposes OvaSense, an intelligent deep learning-based diagnostic framework designed for automated detection and classification of ovarian cysts using ultrasound imaging. Furthermore, the OvaSense system is designed with scalability and usability in mind, allowing integration into clinical workflows and assisting healthcare professionals in early diagnosis and treatment planning. The results highlight the effectiveness of combining object detection and deep learning-based classification techniques for medical image analysis, making the proposed framework a promising decision-support tool for modern intelligent healthcare systems.

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 Keywords

Ovarian Cyst Detection, Deep Learning, YOLOv8, CNN, VGG16, Ultrasound Imaging, Medical Image Analysis, Artificial Intelligence in Healthcare.

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Creative Commons Attribution 4.0 and The Open Definition

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This paper focuses on the importance of the inclusion of the Indian Knowledge System into the concept of the New Education Policy 2020 aimed at changing the education system in India by introducing inclusiveness, interdisciplinary, and contextual learning. Although the importance of indigenous knowledge traditions in policy has increased, academic studies of how these are being incorporated in the modern educational reforms are scarce. In this gap, this paper intends on critically evaluating the applicability, extents, and consequences of integrating the Indian Knowledge System into mainstream curricula and pedagogy. The study presents, based on a qualitative policy and document analysis of the New Education Policy 2020 and supporting academic literature, that the incorporation of indigenous knowledge improves epistemic diversity and cultural sustainability and leads to holistic and learner-centered education. The results also indicate that integrating the Indian Knowledge System has a potential to close the gap between the traditional wisdom and the contemporary science, which will enhance curriculum design, pedagogical methods, and teacher education. The research enhances the literature on the topic by providing a theoretically informed and policy-based approach to understanding the process of indigenous knowledge integration in higher education. It finds that proper implementation of Indian Knowledge System with New Education Policy 2020 has far-reaching consequences to the governance of education, innovative knowledge curricula, and the sustainability of the knowledge ecosystem in India in the long run.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Indian Knowledge System, New Education Policy 2020, Indigenous Knowledge, Higher Education Reform, Curriculum Integration, Educational Policy

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Creative Commons Attribution 4.0 and The Open Definition

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This research presents the design and implementation of a Real-Time Face Recognition System for CCTV Surveillance using deep learning techniques to enhance public safety and surveillance efficiency. The system automatically detects and identifies individuals from live video streams, enabling reliable recognition of suspects or missing persons in real time. It integrates face detection, feature extraction, and similarity matching to achieve high recognition accuracy while handling variations in pose, lighting, and orientation. Additionally, the system supports dual-mode surveillance by incorporating vehicle detection and license plate recognition, allowing comprehensive monitoring of both individuals and vehicles. The proposed approach is capable of processing multiple camera feeds simultaneously while maintaining low latency and real-time performance. It generates instant alerts upon successful identification, ensuring quick response and decision-making. Overall, the system reduces dependence on manual monitoring, minimizes human error, and provides an efficient, scalable solution for modern intelligent surveillance applications.

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 Keywords

Keywords: Face Recognition, CCTV Surveillance, FaceNet, MTCNN, YOLOv8, License Plate Recognition, Real-Time Alert, Deep Learning.

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Creative Commons Attribution 4.0 and The Open Definition