Volume 13 | Issue 4

 Abstract

The present study focuses on the formulation and evaluation of herbal paper soap enriched with natural extracts to provide effective cleansing while offering medicinal and skincare benefits. Herbal extracts such as, Marigold (Calendula) and other ingredients were incorporated into the soap formulation to enhance its antibacterial, antifungal, and moisturizing properties. The soap was prepared by impregnating the herbal formulation onto a biodegradable paper base to create a portable and eco-friendly alternative to conventional soaps. The formulated herbal paper soap was evaluated based on various parameters, including physical appearance, folding endurance, weight variation, pH, foam stability, and microbial efficacy. The results indicated that the herbal paper soap exhibited good cleansing properties, appropriate pH for skin compatibility, and effective microbial activity. Additionally, the paper soap showed uniformity in weight and excellent folding endurance, ensuring ease of handling and use. In conclusion, the herbal paper soap formulation demonstrated promising results as an ecofriendly, cost-effective, and convenient alternative for maintaining personal hygiene while offering therapeutic benefits. This innovative approach provides a sustainable solution to promote natural skincare and environmental safety.

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 Keywords

Herbal paper soap, formulation, evaluation, natural extracts, Calendula, and other ingredients antibacterial, antifungal, eco-friendly.

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 Abstract

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Renewable Energy, Sustainable , Solar Power, Green Metro

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Creative Commons Attribution 4.0 and The Open Definition

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The Lokpalsagar pond in Panna district of Madhya Pradesh holds significant ecological and hydrological importance as a key element of the local ecosystem. This study aims to evaluate the hydro-edaphic (soil-water) characteristics of the pond to better understand its ecological role. Parameters such as water quality, soil texture, and nutrient availability were assessed to determine their impact on biodiversity and ecosystem functions. The findings indicate that the pond serves as an important water source, especially during dry periods, and acts as a reservoir of nutrients and moisture. Water quality with balanced pH, adequate dissolved oxygen, and low contamination indicate that the pond is healthy and supportive of aquatic life. The pond plays an important role in maintaining the local ecosystem, contributing to biodiversity, and maintaining ecological balance in the area.

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 Keywords

Lokpalsagar pond, Hydro-Edaphic, Ecology, Biodiversity,

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In industrial, commercial, or institutional settings, the Scrap Management System is a digital solution that optimises and streamlines the collecting, sorting, tracking, and disposal of scrap materials. Scrap production is an unavoidable aspect of industrial and manufacturing operations. Ineffective operations, higher expenses, and adverse environmental effects might result from improper scrap management. In order to effectively track, manage, and reduce the amount of scrap materials generated during production, this project focusses on the creation and implementation of a scrap management system. In order to facilitate improved monitoring and decision-making, the system attempts to offer an organised method for documenting the kind, amount, and source of scrap. Additionally, it promotes recycling and appropriate disposal methods, which help to maintain a sustainable environment. The solution supports adherence to industry standards, enhances operational efficiency, and lowers manual error rates by combining digital tools and automation. Conventional scrap processing frequently has environmental non-compliance, inefficiencies, and a lack of responsibility. It reduces human error, enhances resource recovery, and promotes sustainable practices by automating critical operations. In the end, this initiative helps to conserve the environment, cut costs, and manage trash effectively

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 Keywords

Scrap management, Disposal

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Blood tests that show your group type support both medical testing and blood transfusions while responding to emergencies. The performance of standard blood typing assessments needs specialized laboratory equipment alongside technical specialists and takes significant processing duration. The proposed research presents a non-invasive approach to forecast blood groups directly from fingerprints which cuts down testing expenses and speeds up identification processes. The study employs Inception V3 on fingerprint samples from Kaggle to detect blood group information. The study evaluates depth learning enhancements caused by RMSprop SGD alongside Adam through their performance in blood group predictions along with reduced training durations. The procedural method demonstrates successful blood type identification from fingerprint pictures according to experimental validation results. Our method provides a blood type testing transformation that advances low-resourced medical facilities. The research team aims to develop models that perform effectively with various population groups through system implementation for healthcare facilities.

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 Keywords

Blood Group Identification, Inception V3 Model, Finger Print Detection, Blood Tranfusions, Healthcare Environment.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Sustainable fashion has begun to attract the attention of contemporary consumers amidst the growing discussions on environmental protection and ethical production. The present study was conducted in Coimbatore city to investigate the awareness of consumers regarding sustainable fashion apparel and how their views can be related to the growth of this niche. It aimed to examine consumer perceptions, needs, and expectations and identify the factors that affect their purchasing behavior. A sample size of 120 respondents was selected using convenience sampling, and data were then collected using a structured questionnaire. To analyze the findings, simple percentage analysis was employed to interpret the distribution of responses, while Chi-square testing was used to test for relationships among variables, such as level of education and acceptance of feedback. The findings illustrated that people are becoming more aware of sustainability in fashion, yet price, product availability, and convenience of access remain important factors driving their decision-making. Interestingly, the Chi-square test found no significant relationship between educational background and whether consumers believed their feedback is acted upon by companies. It could thus be concluded that while people are somewhat aware of sustainable fashion, awareness has, however, not yet been translated into sustained buying behavior. There is an urgent need for companies to communicate better, create personalized experiences, and adopt visible sustainability initiatives to gain trust and loyalty from consumers.

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Consumer Awareness, Sustainable Fashion, Consumer Feedback

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Linum usitatissimum L. (flaxseed/linseed) is an important medicinal crop of family linaceace grown for its edible seed, the oil from the seed and for the fibres obtained from the caffeine. Induce mutagenesis plays a vital role in crop improvement by inferring variations in germplasm and is preferred over hybridization and recombination because it improves a defect in an otherwise elite cultivar, without losing its agronomic and quality characteristics. In present investigation Linum usitatissimum var. Shekhar was exposed with five different mutagenic dose of four mutagens viz caffeine and Sodium azide (SA) i.e, 0.10%, 0.25%, 0.50%, 0.75% and 1.00% and heavy metals lead nitrate and cadmium nitrate i.e. 20, 40, 60, 80 and 100 ppm. Seed germination, plant survival and pollen fertility was found to be decreased in treated population than control in all the mutagens. The higher concentrations of mutagens significantly reduced plant height, branches per plant and various yield parameters. The present study reveals moderate concentrations of each mutagen induce mutagenic damage in Linum usitatissimum var. Shekhar which can facilitates screening of desirable mutant in M2 and M3 generations. On the basis of these results, it was concluded that lower concentrations of mutagen did not significantly affect the morphology of Linum, while higher concentrations of four mutagen were found to be more mutagenic.

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 Keywords

Linum usitatissimum L., linseed, chemical mutagen, caffeine, SA, Pb(NO3)2, Cd(NO3)2

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study has been done to study the impact of integrated education of arts in Hindi and Hindi subjects in council primary schools of Pilibhit district.The purpose of this study is to explore how incorporating the arts into educational programs improves students' academic achievement.The study compared students receiving and not receiving arts integrated education in digital and digital subjects. The second hypothesis predicted that arts integrated education would have no significant impact on students' academic achievement.

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Art integrated education, primary level school, achievement of students, Art integrated education in language, Art integrated education in music

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract: Affecting 1% of those over 55, Parkinson's disease [PD] is the second most prevalent neurological illness after Alzheimer's disease. Lewy bodies and a gradual loss of dopaminergic neurons in the substantia nigra pars compacta are hallmarks of the underlying neuropathology observed in Parkinson's disease. The Lewy bodies are made up of ?-synuclein aggregates. Bradykinesia, muscle rigidity, and resting tremor are among the motor symptoms of Parkinson's disease. Parkinson's disease (PD) patients typically exhibit bradykinesia, rigidity, rest tremor, and stooping posture, among other motor and non-motor symptoms. PD is also linked to autonomic dysfunction (such as orthostatic and Hyperhidrosis), cognitive impairment (dementia), and neurobehavioral disorders (such as anxiety and sadness).Medical pharmacologic treatments and cutting-edge surgical procedures like deep brain stimulation (DBS) have proliferated in recent decades. The mainstays of Parkinson disease treatment include deep brain stimulation for patients experiencing uncontrollable LDOPA-related motor complications, non-dopaminergic methods to treat both motor and non-motor symptoms, and medication replacement of striatal dopamine. Lifestyle changes are helping to avoid Parkinson's disease. Yoga and other physical exercises lower the risk of Parkinson's disease.

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Bradykinesia, muscle rigidity, cognitive impairment, orthostatic, Parkinson's disease.

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Floods are one of the major natural hazards across the globe. They have devastating consequences, impacting livelihoods, businesses, agriculture, and more. Therefore, effective flood management is essential to handle such crises. One crucial aspect of effective management is the early identification of submerged regions. This enables timely alerts to responsible authorities and citizens. This article presents an approach for segmenting flooded areas in satellite images using a hybrid neural network architecture built upon the U-Net framework. By analyzing images of pre-disaster and post-disaster events, the model can effectively identify changes in water bodies and land cover. This research has the potential to make a significant impact on flood mitigation strategies within the Indian subcontinent.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

U-net, Deep Learning, neural networks, satellite images, flood

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Artificial Intelligence has rapidly become an integral part our daily lives, transforming various aspects of society and opening up new possibilities and opportunities. However, the growth of AI also raises concerns about its impact on society and the potential consequences of its widespread adoption. This research paper provides a comprehensive overview of the impact of AI on varies aspects of society, including the economy, education, healthcare, employment, and ethics. To achieve this goal thorough review of existing research and data on the impact of AI was conducted. The literature review focused on the economic, social ,and ethical implications of AI ,as well as the challenges associated with its implementation .The review found that while AI has the potential to bring significant benefits to society ,it also poses challenges and risks that need to be addressed .The paper also presents a discussion of the impact of AI on different sectors of society ,including healthcare ,education, and employment .The analysis found that AI has the potential to improve patient outcomes and provide more efficient and effective healthcare services .It can also transform education by providing personalized and adaptive learning experiences .At the same time ,he implementation of AI in the workplace raises concerns about job displacement and the potential for economic inequality .In addition ,the paper evaluates the ethical implications of AI and identifies the need of responsible development and development of AI systems. This includes the need for ethical frameworks and guidelines to address issues such as bias, privacy, and transparency.Overall, this research paper provides a comprehensive overview of the impact of AI on various aspects of society by doing so, this paper helps to guide policy -makers, technology experts and the public towards the responsible and equitable development of AI.

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 Keywords

Artificial intelligence, Technology, Society, Innovations, Computers, Productivity, Machines.

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Creative Commons Attribution 4.0 and The Open Definition

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The growing number of space debris threatens operational satellites and upcoming space missions significantly. Existing Space Situational Awareness (SSA) infrastructure is challenged in precisely tracking, predicting, and characterizing the debris environment, especially small, large numbers of objects. The challenges stem from sensor coverage gaps, the intricacy of orbital perturbations, data processing bottlenecks, and the inability to estimate object characteristics important for precise risk assessment. In this paper, the state-of-the-art in tracking space debris is comprehensively covered, highlighting the constraints of classic techniques and new emerging possibilities for Artificial Intelligence (AI) that can be improved through radar data analysis. The common usage of Kalman Filters and the extensive body of studies employing AI/ML algorithms such as LSTMs and CNNs for determining orbits, predictions, and characterization are reviewed by us. Principal areas of research lacuna were seen to include sparse application of deep learning into direct radar data streams, an absence of rigorous focus on real-time identification, and the demand for comprehensive and meaningful comparisons among AI and non-AI alternatives in realistic situations. This study establishes the precursor for next-generation SSA systems employing AI by recognizing imperative challenges and lucrative areas of research that collectively would lead toward enhancing the security and sustainability of space activities.

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Space Debris, Space Situational Awareness (SSA), Artificial Intelligence (AI), Machine Learning (ML), Radar Data Analysis, Orbit Determination, Trajectory Prediction, Kalman Filter, LSTM, CNN, Deep Learning, Space Surveillance and Tracking (SST)

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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AI, Crop prediction, Random Forest, Gradient boosting.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Rehabilitation assistive devices are necessary for stroke patients, muscle trauma patients, or patients with age-related muscle atrophy. In this research, a 3D-printed upper limb assistive device was developed with simplicity, customization, and enhanced muscle rehabilitation in mind. With the use of FDM technology and biocompatible materials like PLA and TPU, the device provides light, ergonomic, and patient-specified support. Its modular design enables easy personalization, making it suitable for diverse therapy needs. Preliminary tests on physical therapy patients showed enhanced comfort, usability, and adherence to rehabilitation. The results highlight 3D printing's cost-effectiveness and potential for scalable application in clinical and home settings.

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Upper limb rehabilitation, 3D printing, Assistive device, FDM technology, PLA and TPU materials, Stroke recovery, Modular design, Patient-specific therapy

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Creative Commons Attribution 4.0 and The Open Definition

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The COVID-19 pandemic has significantly impacted research activities and publications across academic disciplines, including Library and Information Science (LIS). This study presents a bibliometric analysis of LIS research publications from India during the COVID-19 period, examining publication patterns, research trends, and scholarly collaboration. The analysis covers research articles published in peer-reviewed journals from March 2020 to December 2022. Using data extracted from major bibliographic databases, the study evaluates various parameters including publication volume, authorship patterns, institutional contributions, and thematic focus areas. Findings reveal a notable surge in digital library services, information literacy, and remote learning-related research during this period. The study identified key research clusters centered around digital transformation of libraries, information-seeking behavior during lockdowns, and emerging technologies in library services. Collaboration patterns show an increase in multi-institutional research partnerships, possibly facilitated by remote working conditions. The research output demonstrates the LIS community's rapid response to unprecedented challenges, with particular emphasis on technological adaptation and service innovation. This study contributes to understanding how the Indian LIS research landscape evolved during the pandemic, offering insights for future research directions and crisis preparedness in library and information services.

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 Keywords

Bibliometric, COVID-19, Library Science, Information Science, Research Output, India

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This is a well-established fact now that the avowed object of Ghosh as a writer has been to put to the centre stage the hitherto neglected facets of history. He in all his novels evinces his tenacious efforts to delineate such aspects of history as have been relegated to the margins in the traditional historiography. One such institution of the colonial past is the British army formed largely of Indians soldiers that have always been a little-discussed subject in the conventional history. Ghosh in The Glass Palace directs his attention to delineate the history of the British institution of the colonial army. His representation of the Indian British army is distinctive in so far as he seeks to underline the traumas and mental anguish of the Indian soldiers serving in the British army. There is no gainsaying the fact that the constitution and structure of the colonial army was racialized. Indian soldiers as subalterns had to bear racial discrimination at the hands of their white superiors or British counterparts that culminated in a sense of dissatisfaction and discontent amongst them. Ghosh here aims at projecting the inside view of the army and his portrayal of this colonial institution is unique in so far as he seeks to foreground the dilemmas and predicament of Indian soldiers. This paper seeks to present the ever-present discontent and ever-lurking dissent amongst the British Indian soldiers who suffered constant humiliation at the hands of their British superiors and counterparts. Their predicament was further aggravated by the sense of displacement, dislocation and rootlessness caused by the peculiar circumstances of their lives.

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Alienation, Displacement, Subaltern, Dislocation, Migration, Dissent, Identity Crisis, Dilemma, Self-realization

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The classification of fruits is an essential task in agriculture, food processing, and retail industries, ensuring quality control and efficient sorting. Conventional methods depend on inspection, which is often slow, labor-intensive, and inconsistent. To address these limitations, this study employs Transfer Learning with pre-trained Convolutional Neural Network to develop an fruit classification system. In this research, deep learning models such as MobileNetV2 are fine-tuned to classify fruit images with high accuracy. The pre-trained networks are adapted to recognize different fruit categories by leveraging their feature extraction capabilities while significantly reducing training time. A Flask-based web application is developed to allow real-time classification, enabling user to upload fruit images and get instant predictions, making it ideal for real-time applications. The findings demonstrate that Transfer Learning is a highly effective approach for fruit classification, offering a scalable and reliable solution for automating the process. This system has potential applications in smart agriculture, automated food inspection, and digital marketplaces, enhancing efficiency and reducing human effort.

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Transfer Learning, Convolutional Neural Networks, , MobileNetV2, Flask, Smart Agriculture.

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Creative Commons Attribution 4.0 and The Open Definition

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The proliferation of deceptive and computer-generated reviews constitutes a major challenge in e-commerce, social media, and digital marketing domains. To address this critical issue, the current work introduces an innovative ensemble-based methodology integrating linguistic analysis and reviewer behavioural profiling for accurate differentiation between authentic and fabricated textual reviews. Employing a diverse dataset comprising real and artificially generated reviews and using an ensemble of Logistic Regression, Random Forest, and Long Short-Term Memory (LSTM) networks collaboratively analyse linguistic patterns indicative of fraudulent textual review. Complementing textual analysis, a novel meta-feature engineering strategy assesses reviewer credibility through parameters such as review frequency, rating variance, and burst activity metrics. This meta-data-based approach simultaneously finds reviewer authenticity probabilities as new reviews are posted, indicating evolving behavioural patterns. The system computes an integrated probability score, effectively combining textual and meta-behavioural data. Overall evaluation demonstrates robust performance, effectively capturing emergent spam behaviours in real-time. The proposed methodology shows significant potential for practical deployment in automated moderation, digital content verification, and online fraud prevention applications.

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Creative Commons Attribution 4.0 and The Open Definition

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Fake review detection, Ensemble modelling, LSTM, Behavioural meta-analysis, Dynamic classification

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Creative Commons Attribution 4.0 and The Open Definition

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When fuel prices rise and environmental pollution turns into a crying need, hybrids have become an economically viable substitute for conventional gasoline cars. Hybrid technology combines electric motors and internal combustion engines to provide efficiency with low emissions. The present research effort tries to investigate the extent of awareness and satisfaction of hybrid car owners within the city of Coimbatore. It formulates the main determinant factors, disadvantages, and extent of increase in adoption by consumers.

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Creative Commons Attribution 4.0 and The Open Definition

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Hybrid Cars, Fuel Efficiency, Customer Satisfaction, Awareness, Green Mobility.

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Creative Commons Attribution 4.0 and The Open Definition

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The rapid growth of e-healthcare, fueled by IoT devices and wearables, has introduced significant privacy challenges, particularly in securing sensitive patient data collected and transmitted across distributed environments. To address these concerns, a novel Nomadic Agent System (NAS) architecture is proposed, combining edge computing, a central node with Kafka-based request management and ElasticSearch data indexing, and cloud storage. This architecture aims to enhance privacy protection by leveraging advanced technologies to secure data at multiple levels. A key innovation is the integration of Large Language Models (LLMs) within the nomadic agents at the central node, which are employed to improve data anonymization techniques. By utilizing LLMs, the system provides a more robust defense against re-identification attacks, ensuring that sensitive patient data is anonymized effectively while remaining usable for analysis and decision-making. The NAS architecture operates across multiple layers, with edge computing handling data collection and preprocessing, the central node managing data requests and indexing, and cloud storage ensuring scalable and secure data retention. The use of Kafka and ElasticSearch at the central node enables efficient data processing and retrieval, while the LLM-based anonymization process adds an additional layer of privacy protection. Potential benefits of this approach include enhanced data security, improved anonymization, and scalability for large-scale e-healthcare systems.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

E-healthcare, Privacy, Nomadic Agent, Edge Computing, Anonymization, Large Language Models, Kafka, ElasticSearch

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Creative Commons Attribution 4.0 and The Open Definition