Volume 13 | Issue 4

 Abstract

Alum is also known as the "Potash Alum" It is a naturally occurring compound known for its astringent, antiseptic, and hemostatic properties. Although traditionally used in medicine, alum has recently studied the possibility of wound-healing action, especially in the case of mouth ulcers. Its antibacterial, anti-inflammatory, and tissue-regenerating properties help it speed up recovery; therefore, it is a great medication. By comparing their potency with traditional therapies, this review analyses alum-based medicines' chemical composition, pharmacological action, dosage forms, and commercial formulations. Using mechanisms such as protein coagulation, vasoconstriction, bacterial inhibition, and epithelial regeneration, alum helps in damage control, blood reduction, and better tissue repair. Although it has many advantages, alum should be handled carefully since long-term use of alum raises possibilities of irritability and toxicity. Although historical evidence and early research suggest its effectiveness, more clinical trials are needed to set standard guidelines for secure and ideal applications. Alum-based treatments in wound care and oral medicine might have even better therapeutic value in the future with such developments as nano-formulations and bioactive enhancement.

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 Keywords

Alum, Hemostatic, Anti-inflammatory, Antibacterial Properties, Nanoformulations, Bioactive Enhancement

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Creative Commons Attribution 4.0 and The Open Definition

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Paan Masala poses persistent hygiene, health, and aesthetic challenges in Indian cities, imposing substantial cleaning costs. Existing manual enforcement under the Swachh Bharat Abhiyan remains inefficient and unsustainable. This paper proposes Swachh AI, an AI-based real-time surveillance and enforcement system for detecting public spitting incidents and identifying offenders. The system integrates (i) a YOLOv11-based instance segmentation model to detect spitting actions with pixel-level accuracy, and (ii) an OCR-based license plate recognition module for offender identification. Together, these modules enable automated evidence capture, offender tracking, and data logging for civic enforcement. Swachh AI is designed for modular integration, scalability, and privacy compliance, suitable for deployment in smart cities and public infrastructure. Experimental evaluations demonstrate high detection accuracy in varied outdoor conditions, affirming its potential for scalable urban hygiene management.

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 Keywords

Spitting detection, YOLOv11, instance segmentation, OCR, license plate recognition, public hygiene, AI surveillance, smart cities.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Human activity detection for video surveillance system is an automated way of processing video sequences and making an intelligent decision about the actions in the video. It is one of the growing areas of Computer vision and artificial intelligence. Suspicious Human Activity Detection is the process of detecting unwanted human activities in a crowded place and alerting the concerned authority about the activity. This is done by converting video into frames and analyzing the persons and their activities from the processed frames. This paper gives an overall idea of the development of the system that detects suspicious human activities.

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 Keywords

Suspicious crowd behavior, Video surveillance, Transfer learning, Anomaly detection, Computer vision

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Food waste reduction, as a major application area of the Internet of Things (IoT) and big data technologies, has become one of the most pressing issues. In recent years, there has been an unprecedented increase in food waste, which has had a negative impact on economic growth in many countries. Food waste has also caused serious environmental problems. Agricultural production, post-harvest handling, and storage, as well as food processing, distribution, and consumption, can all lead to food wastage. This wastage is primarily caused by inefficiencies in the food supply chain and a lack of information at each stage of the food cycle. In order to minimize such effects, the Internet of Things, data science, and various management models are used to reduce food waste in food supply chains. This paper provides a comprehensive review of IoT and data science based food waste management models, algorithms, and technologies with the aim of improving resource efficiency and highlights the key challenges and opportunities for future research. Food waste has become a critical global challenge, with significant economic, environmental, and social implications. This project focuses on developing a data-driven solution for food menu recommendation and waste management using data science. By leveraging historical data and predictive analytics, the system aims to optimize food utilization and minimize waste at the household and organizational levels. Machine learning models are employed for predicting waste and recommending efficient menus based on consumption patterns, ensuring resource efficiency and sustainability. This project presents a comprehensive solution to improve decision-making in food management while reducing waste.

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 Keywords

Food waste reduction Internet of Things (IoT) Data science Predictive analytics Machine learning Food supply chain optimization Resource efficiency Menu recommendation systems Waste management Consumption pattern analysis Sustainability Food utilization Decision support systems

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Creative Commons Attribution 4.0 and The Open Definition

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Education sector is the main pillar of social development of any Nation throughout the world wise. Teachers have a critical role in the development and transformation of the educational system and society as a whole. They functioned as a focal point for intentional, meaningful, and successful teaching and learning. The present study was planned to examine the relationship between Self-Esteem and Organizational Citizenship Behavior of teachers to Build Stronger Educational Environment. A purposive sample of 200 post graduate Government school teachers was taken in present study. A correlational research design was used to examine the relationship between Self-Esteem and Organizational Citizenship Behavior of teachers. Self-esteem scale by Rosenberg (1979) and Organizational Citizenship Behaviour scale by Podsakoff, MacKenzie, Moorman, and Fetter (1990) was used in present study. Correlational coefficient result of the study showed a significant positive relationship between Self-Esteem and Organizational Citizenship Behavior among school teachers. Results of the study revealed that more the teacher have self-esteem; also have high overall and various dimensions of organizational citizenship behaviour e.g. altruism, Conscientiousness, Sportsmanship, Courtesy and Civic Virtue. Present study suggested that if teachers were having more positive beliefs and appraisals about oneself are more efficacious and concerned about and connected or attached to their schools/ institutions.

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Self-Esteem, Organizational Citizenship Behavior altruism, Conscientiousness, Sportsmanship, Courtesy and Civic Virtue.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Phytic acid (myo-inositol hexakisphosphate or IP6) is a biochemical compound found abundantly in seeds, grains, and legumes. It plays multiple important role in plants such as in metabolism, defense, tolerance towards stress, including its crucial importance in phosphorus storage and germination of seed. Inspite of its significant potential in plants, phytic acid is not considered as favourable for animal and human nutrition due to its chelating interaction with minerals. This review intend to explore the biological importance of phytic acid in plants and environment as well associated challenges.

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phytate, antinutrient, chelate, pronutrient, bioavailability

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

bearings are vital components in rotating machinery, significantly impacting performance and reliability. As machines operate under increasingly demanding conditions, bearings must withstand higher loads and temperatures. However, these conditions can lead to increased vibration, accelerating fatigue failure. There are two primary types of bearings: radial hydrodynamic bearings, which rely on fluid film lubrication, and hydrostatic bearings, which utilize external pressure. Hydrodynamic bearings operate under elasto-hydrodynamic lubrication conditions, while journal bearings are prone to self-induced vibrations due to radial clearance. To ensure reliable operation, monitoring bearing performance is crucial. Vibration analysis has emerged as a popular method for detecting potential issues and predicting bearing health. This study focuses on the vibration and tribological analysis of various bearings.

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 Keywords

Vibration Analysis, Tribological Analysis, FFT Analyzer

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Creative Commons Attribution 4.0 and The Open Definition

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The Pradhan Mantri Yojana (PMY) encompasses a series of visionary welfare schemes launched by the Government of India under the leadership of the Prime Minister to address critical socio-economic challenges and promote inclusive growth. These schemes are designed to uplift various sections of society, particularly the poor, marginalized, and underprivileged, by providing them with access to basic necessities, financial support, and opportunities for self-reliance. A few of the major initiatives under this umbrella include the Pradhan Mantri Jan Dhan Yojana (PMJDY), which promotes financial inclusion by offering banking services to the unbanked population; India accounts for about 20% of the global count of those living on less than 1$ a person per day, so that what happen in india only a reflection of world wide trends, one of there major determinants. Pradhan Mantri Ujjwala Yojana (PMUY), which ensures clean cooking fuel access to below poverty line households; and Pradhan Mantri Kisan Samman Nidhi (PM-KISAN), offering direct income support to farmers to ease their financial burden. Ayushman Bharat - Pradhan Mantri Jan Arogya Yojana (AB-PMJAY) aims at providing health insurance coverage to economically vulnerable families. The holistic approach of these schemes reflects the government's commitment to "Sabka Saath, Sabka Vikas, Sabka Vishwas." These programs not only enhance the standard of living but also contribute to national development by empowering citizens through financial, social, and infrastructural support.

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Creative Commons Attribution 4.0 and The Open Definition

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Pradhan mantri awas yojana, rural development, housing scheme, Indra Awas Yojana

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract: Due to the growing acceptance of cloud computing, both consumers and businesses are quickly adopting cloud services for a variety of purposes. The primary driver behind this change is the abundance of advantages that cloud services offer, like cheap prices, processing power, and online storage. One of the key ideas when discussing storage devices, which serve as the foundation of the cloud infrastructure, is data recovery. Customers' private or confidential data can be recovered via data recovery techniques by someone who has access to such servers or devices, even after the customers have erased it from the cloud. Users' privacy is compromised and there is a security risk when such data is rebuilt. From the user's perspective, the data has already been removed from the cloud, but they are unaware that somebody else has access to it even after they have gained access. In this research, we investigate the potential security risk associated with users using data recovery tools on cloud servers after they have erased their data. Rename is a straightforward technique that we have suggested be used to solve this issue.

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Keywords: Cloud computing, Data recovery, Data security, Security issues, Cloud reconstruction

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Water assets are fundamental for supporting life, farming, businesses, and environments. Be that as it may, the developing weights of expanding populace, fast urbanization, and climate alter are straining the existing water framework. Precise determining of future water requests and a comprehensive evaluation of store capacity capacities are pivotal for successful water administration. Without these experiences, choice producers battle to arrange for maintainable advancement and relieve the dangers related with water shortage and extraordinary climate occasions. This venture centers on creating a prescient model that coordinating authentic information, climate projections, populace development patterns, and agrarian hones to figure future water necessities. It too assesses the supply capacity capacities and distinguishes potential holes and related dangers. By leveraging progressed information analytics and machine learning methods, this framework gives noteworthy experiences for policymakers, empowering proactive arranging and productive water asset administration. The Prescient Demonstrate for Water Emergency Administration particularly addresses challenges, such as extraordinary dry spells, wasteful supply administration, and eccentric climate designs. By combining vigorous data-driven strategies and user-friendly devices, the demonstrate points to guarantee feasible and strong water-management hones.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Water requirement, ARIMA Model, Machine Learning, water capacity, LSTM, future water requirement

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

What draws customers to a particular website includes aspects like the overall shopping experience--ranging from the site's layout and design to the variety of products offered, pricing, shipping methods, delivery costs, and how quickly items arrive. When it comes to switching between websites, key factors that influence this decision include the cost of products, delivery speed, shipping fees, and the availability of product options. While dissatisfaction with product quality does have some influence, its impact is relatively mild. This research, based on feedback from online shoppers, sheds light on the critical elements that shape customer satisfaction and loyalty in the digital shopping space. Such insights can be invaluable for e-commerce businesses looking to refine their customer experience and strengthen shopper retention.

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E-Commerce, Consumer Engagement

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the fast-developing country, people are facing many accidents; it would be undesirable for any nation to lose their life for an unwanted cause. Railways are one of the important transports in India. There is a need for manual checking to detect the crack on railway track and railway personnel always take care of this issue, even though the inspection is made regularly. Sometimes the crack may go unnoticed. Because of this the train accident or derailment may occur. Inorder to avoid this situation and automate the railway crack detection has been proposed. Here IR sensor is used to detect the crack in the railway track and detect the obstacle presence in the track. This project pertains to a process for monitoring the condition of rail on train tracks and more specifically has the object of the identification of defects detected by IR sensors on the tracks to be checked to allow maintenance crews to subsequently find these defects. All the components will be manufactured and the assembled together. After making the assembly, the experimental testing will be carried out. After the testing, the result and conclusion will be carried out.

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TRAIN TRACK OBSTACLE DETECTOR USING IR SENSOR

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 Abstract

The demand for lightweight, high-strength, and wear-resistant materials in industries such as automotive, aerospace, and defense has driven the development of aluminum metal matrix composites (AMMCs). This study focuses on the fabrication and tribo-mechanical analysis of Al6061 reinforced with titanium dioxide (TiO2) particles using the powder metallurgy technique. Composites with 0%, 2%, 4%, and 6% TiO2 weight fractions were synthesized and evaluated for tensile strength, compressive strength, hardness, and sliding wear behavior. The results indicate that the addition of 4% TiO2 significantly enhances mechanical properties, including a 19% increase in tensile strength, 25% increase in compressive strength, and 36% increase in hardness compared to pure Al6061. Sliding wear tests conducted using a pin-on-disc tester revealed that the 4% TiO2 composite exhibited the lowest wear rate and a high coefficient of friction (COF) of 0.35-0.45, outperforming existing brake pad materials by approximately 26% in wear resistance and 21% in COF. Finite element analysis (FEA) corroborated experimental findings, validating the structural integrity of the composites. The study highlights the potential of Al6061-TiO2 composites for high-temperature wear-resistant applications, such as automotive brake pads.

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Aluminum Metal Matrix Composites, TiO2 Reinforcement, Powder Metallurgy, Tribo-Mechanical Properties, Brake Pads

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Cosmetics play a vital role for everyone to have a joyful and sanguine life. In present scenario herbal cosmeceuticals have more demand because they have no side effects. People having oily skin suffer from acne, whiteheads and blackheads quite often so scrubbing become more essential. In our present study we formulated scrub in gel form for oily skin by using custard apple seed powder, sugar, turmeric powder, glycerine, aloevera gel, methyl paraben, citric acid and evaluated by using various parameters such as physical appearance, viscosity, pH, spreadability , irritability, washability, stability studies and got fruitful results with all the tests.

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Creative Commons Attribution 4.0 and The Open Definition

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Custard apple seed powder, facial scrub, natural exfoliant, skincare, Herbal scrub

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The paper examines how American rap music promoted cultural exchange with India in the context of globalization and the digital revolution. Since it arrived in the Bronx in the 1970s, rap music has become a global cultural force, transcending geographical, linguistic, and cultural boundaries. This study examines how American rap's subject, style, and cultural representations have influenced and intersected Indian music, identity, and social comments since 2014. It highlights the growth of the hip-hop underground movement from India. This study embraces an interdisciplinary approach that combines cultural studies, music, and international relations and analyzes the impact of American rap on Indian popular culture. Research into the main themes includes the movement of Gully Rap, the Bollywood film Gully Boy (2019), and the contributions of artists such as Naezi's Raja Kumari, who embody the fusion of American and Indian musical traditions. In this study, platforms such as YouTube, Spotify, and social networks served as channels for this cultural exchange that allows for the distribution and location of rap music in India. Research indicates that American rap has functioned as a source of motivation and a means for Indian artists to express their socio-political situations. Although the themes of marginalization, resistance, and urban existence are prevalent in both cultures, Indian rap enriches these stories by incorporating native languages, traditions, and local issues. The study also highlights the challenges of this cultural exchange, including debates around authenticity, commercialization, and the adaptation of a historically African-American art form in a diverse Indian context. This study contributes to the growing body of literature on global hip-hop culture and underscores the role of American rap music as a significant vehicle for cross-cultural dialogue, creativity, and identity formation in a rapidly globalizing world. According to this trip from American streets to Indian musical landscapes, this study illuminates rap's transformational power in combining culture and contributions to new artistic expression.

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 Keywords

American Rap Music, Indian Hip-Hop, Cultural Exchange, Youth Culture, Media & Technology

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Creative Commons Attribution 4.0 and The Open Definition

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In the digital age, online shopping has emerged as a fundamental pillar of the global economy, transforming traditional commerce models and enhancing accessibility for consumers. This study aims to establish a comprehensive theoretical framework for understanding the evolution, significance, and impact of e-commerce, with a particular focus on AI-driven negotiation techniques. Consumer behavior in online shopping is influenced by factors such as convenience, product variety, accessibility, and social interactions. However, several challenges persist, including security risks, fraudulent transactions, and inefficient dispute resolution. This research explores how artificial intelligence (AI)-driven negotiation algorithms can optimize pricing models, refine product recommendations, and enhance customer satisfaction by ensuring fair pricing and seamless transactions. AI-driven automation not only mitigates existing e-commerce challenges but also strengthens digital marketplaces by fostering trust and efficiency.

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Creative Commons Attribution 4.0 and The Open Definition

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e-commerce, AI negotiation, online shopping, digital marketplace, consumer behavior, dynamic pricing, dispute resolution

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The discourse around the concept of citizenship has been a center of discussion in both the liberal and the neo-liberal states. The theoretical discussion is primarily dominant in the civic republican and liberal debates. The civic republican notion of citizenship emphasizes the community participation while advocating active citizenry, political participation, and civic virtue. The emphasis is more on active participation in civic life. The liberal notion of citizenship believes in the capacity of the individuals themselves as an active citizen by emphasizing individual rights and private interests. The question arises as to whether these two concepts can encompass the marginalized sections of society, especially women. And is there a possibility of reaching a milieu of formal and substantive rights of a citizen? These are some of the issues in the concept of citizenship that demand a revision of the current definition of citizenship. However, there has been an attempt at re-theorization of the concept by recent scholars whose work focuses on the binary of the concept of citizenship. The binary of public-private gives space for discussion on women and their claim to citizenship. There is a notion that men are active participants in the public domain while women are mostly confined to the private domain (the insider-outsider debate). Therefore, in this context, the paper tries to look at the relationship between the concept of citizenship and how the concept is contested and negotiated when it comes to women. Women's oppression is exemplified in the way women experience citizenship rights. On the one hand, the state guarantees citizenship rights and on the other, it is the nature of the society to determine the extent to which citizenship rights can be exercised. The paper is an attempt to look at citizenship as a concept from the lens of women's experience and will mainly outline the theoretical implications of the concept of citizenship in the context of women in India while giving a general view of how discrimination and social exclusion can undermine the benefits of citizenship. The method used in this paper is qualitative and analytical while relying on theoretical discourse analysis and secondary research.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Women, Citizenship, Gender, Social exclusion, Inclusion, Rights

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Allergic rhinitis (AR) is a prevalent condition characterized by inflammation of the nasal mucosa due to allergic triggers, causing significant morbidity and impairment of quality of life. Accurate diagnosis is essential for effective management and treatment, but remains challenging due to the overlap of symptoms with other nasal disorders. This comprehensive review explores the diagnostic approach to allergic rhinitis, from patient history to advanced diagnostic testing. We begin by discussing the critical role of a thorough clinical history, including symptom onset, seasonal patterns, and potential allergen exposure, in differentiating AR from other causes of rhinitis. Physical examination findings, particularly the identification of allergic nasal mucosal changes, are also examined. The review then delves into diagnostic testing modalities, including skin prick tests (SPT), specific IgE blood tests, and emerging methods like nasal allergen provocation tests. By synthesizing current evidence, this review aims to provide a clear, updated framework for diagnosing allergic rhinitis, ensuring early and precise identification of the condition for optimal patient care.

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Allergic rhinitis, allergens, pruritis, nasal congestion, rhinorrhea, rhino conjunctivitis,IgE.

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Creative Commons Attribution 4.0 and The Open Definition

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The growing application of artificial intelligence (AI) in medical imaging has significantly improved diagnostic capabilities. However, the high computational demands of deep learning models have raised concerns regarding energy consumption and environmental sustainability. This paper explores an innovative green computing approach to optimizing AI-based medical imaging systems. By leveraging model pruning, quantization, and edge computing, this paper propose an energy-efficient framework that minimizes carbon footprints while maintaining diagnostic accuracy. The study evaluates the energy savings and performance trade-offs in MRI, CT scans, and X-rays, comparing traditional AI-based models with optimized green AI systems. Experimental results indicate that sustainable AI models can significantly reduce energy consumption without compromising diagnostic efficiency. This research provides a foundation for further advancements in eco-friendly AI applications in healthcare.

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Creative Commons Attribution 4.0 and The Open Definition

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Green computing, AI in medical imaging, energy-efficient deep learning, sustainable healthcare, edge computing

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Water assets are fundamental for supporting life, farming, businesses, and environments. Be that as it may, the developing weights of expanding populace, fast urbanization, and climate alter are straining the existing water framework. Precise determining of future water requests and a comprehensive evaluation of store capacity capacities are pivotal for successful water administration. Without these experiences, choice producers battle to arrange for maintainable advancement and relieve the dangers related with water shortage and extraordinary climate occasions. This venture centers on creating a prescient model that coordinating authentic information, climate projections, populace development patterns, and agrarian hones to figure future water necessities. It too assesses the supply capacity capacities and distinguishes potential holes and related dangers. By leveraging progressed information analytics and machine learning methods, this framework gives noteworthy experiences for policymakers, empowering proactive arranging and productive water asset administration. The Prescient Demonstrate for Water Emergency Administration particularly addresses challenges, such as extraordinary dry spells, wasteful supply administration, and eccentric climate designs. By combining vigorous data-driven strategies and user-friendly devices, the demonstrate points to guarantee feasible and strong water-management hones

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Water requirement, ARIMA Model, Machine Learning, water capacity, future water requirement.

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Creative Commons Attribution 4.0 and The Open Definition