Volume 13 | Issue 11 |

 Abstract

Ayurveda is one of the most ancient medical sciences of the world, which aims at promotion of health and treating the disease of an individual. In the last decades as suffering COVID situations, lot of interest has been generated in the medical world regarding Ayurveda and other contemporary medicines. Atharvaveda (around 1200 BC), Charak Samhita and Sushrut Samhita (1000-500 BC) are the main classics that give detailed descriptions of over 700 herbs. Ayurveda provides us the knowledge of overcoming the diseases. In Bhavprakash Nighantu, Acharya Bhavprakash has mentioned the herbs as Picrorhiza kurroa (Linn.) for its various activity. This potential drug has unique phytopharmacological properties.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Picrorhiza kurroa, perennial herb, phyto-constituents, Immunomodulatory activity, Anti-arthritic activity, Hypolipemic activity, Anti-inflammatory activity Hepato-protective, Anti-diabetic

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Saponin was extracted from Rice Husk through various steps of procedure:Extraction with Ethanol, Re-extraction, Separation of Aqeous and Organic Phase, Evaporation, Drying and Weight Determination: The Weight of Obtained Saponin was 1730 mg and % yield of Saponin was 86.50 %. Characterization of Physical Property was done by Determination of Surface Tension and CMC by using various analytical techniques i.e. Stalagmometer, Conductivitymeter, Absorbance by Spectrophotometer. The CMC of Saponin was found 0.04 gm/L and surface tension was 59.29 mN/m. The CMC of SLS was found 8.0 mM and surface tension was 32.55 mN/m. The Study of Anionic-nonionic mixed surfactant system: In present investigation, the interaction between sodium Lauryl Sulphate (SLS) as an anionic surfactant and Saponin as a nonionic surfactant is studied. Saponin is capable to reduce CMC of ( Anionic Surfactant-SLS) and as a result CMC of mixed Surfactant systems were also reduced up to 0.6 mM. As the ratio of Saponin is increasing in the mixed Surfactant systems, the CMC of mixed micelles are found reducing: The CMC of mix Surfactant 1:9 (Saponin + SLS) Solution is found 1.5 (mM). The CMC of mix Surfactant 3:7 (Saponin + SLS) Solution is found 0.9 (mM). The CMC of mix Surfactant 5:5 (Saponin + SLS) Solution is found 0.6 (mM).

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

% yield, CMC, Surface Tension, SLS, mixed surfactant system, mixed micelle.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper empirically tests the growth-sustainability paradox in India's construction sector using but realistic data. Adopting a mixed-methods approach, it combines input-output analysis, econometric modeling, life cycle assessment, and survey-based analysis. Findings confirm that construction drives GDP and employment while intensifying environmental degradation and labor precarity. Governance emerges as the key mediator. Scenario modeling shows that sustainability integration marginally reduces GDP share but enhances resilience by lowering emissions, increasing recycling, and improving labor protections.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

increasing recycling, and improving labor protection

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project presents a scalable retinal image processing system designed using the LSTM SHAKTI processor, leveraging a GUI-based model for efficient disease detection in retinal images. The system utilizes a Diabetic Retinal dataset, where images in .jpg or .png formats are pre-processed through resizing, noise removal, histogram equalization, gray conversion, normalization, and binary pattern extraction. The pre-processed images are then subjected to feature extraction using a Convolutional Neural Network (CNN) to capture essential patterns for classification. The dataset is divided into training (80%) and testing (20%) subsets to evaluate the model's performance The classification phase applies optimized machine learning algorithms, specifically the LSTM SHAKTI algorithm, for disease prediction. The final output is a classification of retinal images, implemented effectively on the LSTM SHAKTI processor. The performance of the system is analyzed based on various metrics such as area, power, delay, and RTL simulation synthesis reports. Additional performance evaluation includes PSNR, SSIM, MSE, MAE, as well as accuracy, precision, recall, ROC, and confusion metrics. This approach aims to provide a high-efficiency, scalable solution for retinal image processing, enabling real-time disease detection and prediction.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Area, Power Consumption, Delay, Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM)

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The growing number of online accounts has increased the risk of weak passwords, reuse of credentials, and cyber-attacks such as phishing and identity theft. Existing password managers either lack strong security or do not fully ensure zero-knowledge privacy. This paper presents KAGI - A Secure Password Manager, designed with client-side encryption to provide complete user data confidentiality. KAGI uses AES-256-GCM encryption and PBKDF2 for secure key derivation, ensuring that passwords are accessible only to the user. The system integrates a secure password generator, multi-factor authentication, and breach monitoring using a k-anonymity model. The proposed solution enhances password security, usability, and protection against unauthorized access

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Password Manager, Zero-Knowledge Architecture, AES-256-GCM Encryption, PBKDF2, Web Cryptography API, Data Privacy, Cybersecurity, Multi-Factor Authentication, Real-Time Breach Monitoring, User Interface Design

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The integration of Artificial Intelligence (AI) into virtual judicial systems marks a pivotal transformation in the evolution of global justice delivery. Beyond mere digitization, AI enables courts to harness computational intelligence for automated case management, intelligent document analysis, and data-driven decision support. These innovations promise to revolutionize judicial efficiency, accessibility, and consistency--offering a potential remedy to chronic challenges such as case backlogs and procedural delays. However, the rapid adoption of algorithmic systems also raises profound questions concerning accountability, transparency, and the preservation of judicial independence. This study critically examines the opportunities and challenges of incorporating AI into virtual courts, with particular emphasis on two emerging paradigms: automated case management and predictive justice. This analysis explores the intersection of automation, data governance, and constitutional safeguards in AI-assisted adjudication, drawing on comparative experiences from the European Union, China's Internet Courts, and India's e-Courts infrastructure. It uses a techno-legal doctrinal methodology to examine: (1) the functional gains of AI in judicial processes, (2) the methodological and ethical complexities of predictive analytics in legal reasoning, and (3) the normative frameworks required to ensure explainability, fairness, and human oversight. AI systems offer the potential to improve judicial efficiency, but their legitimacy hinges on algorithmic transparency, human oversight, and procedural accountability. The paper proposes a governance model for responsible AI in justice, aligning with OECD ethical principles and the growing global consensus on trustworthy AI. The goal is to develop a system of augmented judicial intelligence where technology enhances, but does not supplant, human judgment.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

VIRTUAL COURTS, ARTIFICIAL INTELLIGENCE

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper develops a conceptual framework to address the growth-sustainability paradox in India's construction sector. It integrates economic, environmental, social, and policy dimensions, highlighting how construction simultaneously drives GDP growth and employment while contributing to emissions, resource depletion, and labor precarity. Drawing on input-output economics, ecological economics, and governance theory, the framework proposes testable propositions and identifies pathways to reconcile growth imperatives with sustainability. The article contributes to theory by synthesizing siloed debates, to practice by reframing sustainability as resilience, and to policy by highlighting governance as a mediator.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

The article conceptual framework

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The COVID-19 pandemic pushed virtual courts to evolve quickly all over the world. Lawyers in today's world are now beyond simply presenting cases or examining witnesses online. This has changed into procedural rules, daily operations, and the roles that professionals play in litigation systems. Lawyers now in the present courtship are facing new challenges beyond presenting cases or examining witnesses online. It raises the concern about how they connect with clients, handle ethical duties, manage money matters, and build those casual networks that help young attorneys get ahead. Through this, they show how virtual courts are reshaping the legal field. It pays special attention to advocacy skills, the economics of the profession, ethical issues, and training needs. The research draws on a mixed approach with qualitative elements. Vidhi Centre and official notices from the Bar Council were the main sources of data collection. It also includes close doctrinal reviews. Through this, the work charts out real experiences that lawyers have shared. It points out gaps in how institutions are handling things. Some main shifts stand out. Risks have grown around keeping things confidential and talking to clients securely. Traditional day-to-day corridor chats that helped junior lawyers network are fading away.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

VIRTUAL COURTS , COVID-19 , ARTIFICIAL INTELLIGENCE

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

o Brahma Muhurta is the time about one and a half hours before sunrise. It is considered the best time for doing spiritual activities like meditation, yoga, and prayer. At this time, the mind is calm, and the body is in tune with nature. Practicing during Brahma Muhurta helps to get mental clarity, emotional balance, and inner peace. It also builds self-discipline and supports personal growth. o Modern studies show that waking up early improves focus, reduces stress, and makes a person feel happier and more energetic. This article explains the ancient background of Brahma Muhurta, its scientific benefits, and how we can include it in our daily life to live a more peaceful and balanced life.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Brahma Muhurta, Dincharya, Swasthavritta, Spiritual practices, Emotional balance, Mental clarity, Early morning routine, Ancient wisdom, Stress reduction, Nature's rhythm, Self-discipline, Mindbody balance

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Grassroots sports programs represent the foundation of a nation's sporting structure, playing a crucial role in developing fundamental skills, fostering performance efficiency, and nurturing talent. In India, where demographic diversity intersects with infrastructural disparity, the success of grassroots sports initiatives has varied significantly. This thematic paper provides a generalized yet critical overview of grassroots sports development, with an emphasis on its role in skill formation and performance enhancement. It discusses historical evolution, policy frameworks, implementation challenges, and innovative approaches while drawing upon relevant scholarly and institutional references. The paper aims to offer educators, policymakers, and sports practitioners a cohesive understanding of how grassroots-level interventions can influence long-term sporting excellence.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Grassroots Sports, Skill Development, Performance Efficiency, Youth Sports, Sports Policy, Talent Identification, Physical Literacy, India

  License

Creative Commons Attribution 4.0 and The Open Definition