Volume 13 | Issue 7

 Abstract

: Infertility (Uqr) is a major reproductive health issue affecting about 10-15% of couples, and Polycystic Ovarian Disease (PCOD) is one of its most common causes. PCOD leads to anovulation, menstrual irregularities, obesity, and hormonal imbalance, making conception difficult. In the Unani system of medicine, infertility is recognized as Uqr, and PCOD is described under Marz-e- Akyas Khusytur Rehem and Ihtibas-al-Tams (retention of menses), attributed to Sue Mizaj Barid Balghami (cold and phlegmatic temperament) that disturbs the function of the uterus and ovaries. To evaluate the therapeutic efficacy of Unani formulations in the management of infertility caused by PCOD, with emphasis on their role in inducing ovulation and restoring menstrual regularity. The study was conducted at the Department of Amraz-e-Niswan wa Qabalat (Gynecology & Obstetrics), Nizamia General Hospital, Hyderabad. A total of 30 female patients, aged 20-35 years, with infertility due to PCOD were enrolled and divided into two groups of 15 each: Group A received Ustukhuddoos (Lavandula stoechas), Gaouzaban (Borago officinalis), Gule-Tesu (Butea monosperma), Musli Safed (Chlorophytum borivilianum), and Musli Siyah (Curculigo orchioides) in decoction and powder form.Group B received Aftimoon (Cuscuta reflexa), Afsanteen (Artemisia absinthium), Sadab Khushk (Ruta chalepensis), Khulanjan (Alpinia galanga), Bozidan (Tanacetum umbelliferum), and Asgandh Nagori (Withania somnifera). Treatment was continued for three consecutive months, with follow-ups every 15 days. Clinical evaluation, hormonal assays, and follicular studies via ultrasonography (USG) were conducted to monitor ovulation and conception outcomes. The study concludes that Unani formulations are effective in inducing ovulation and regulating menstrual cycles in women suffering from PCOD-related infertility. The combination of herbs with emmenagogue, deobstruent, aphrodisiac, anti-inflammatory, and insulin-sensitizing actions plays a vital role in correcting hormonal imbalance and improving reproductive function. These findings reaffirm the Unani concept of restoring E-Tedal-e-Mizaj (temperamental balance) and Taqwiyat-e-Rahem (uterine tonicity) as key principles in treating infertility.

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 Keywords

Infertility; Uqr; PCOD; Ihtibas-e-Tams; Unani medicine; Ovulation induction; Ustukhuddoos; Gaouzaban; Musli Safed; Gule Tisu, Musli Siyah, Reproductive health.

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The purpose of the study was to find out the effect of combined ballistic training and yogic practices on psychomotor profiles among college men cricket players. To achieve the purpose of the study thirty cricket players have been randomly selected from PSG college of arts & science, coimbatore, Tamil Nadu and India. The age of the subjects were ranged from 18 to 25 years. The selected subjects were divided into two groups with fifteen subjects in each group. The experimental group underwent a combined ballistic training and yogic practices programme for six weeks. The control group was not participating in any other training during the course of the study. Reaction time was taken as criterion variable in this research. The selected subjects were tested on reaction time was measured through Stick drop method (Distance on ruler 20 centimeters). To determine whether there had been a significant improvement, the dependent't' test was used to analyse the data, and an ANCOVA was used to see whether there had been any significant differences between the groups. To examine the level of significance difference, if any, across groups, the.05 level of confidence was fixed. The difference is found due to effect of combined ballistic training and yogic practices given to the experimental group on reaction time when compared to control group.

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Ballistic training, yogic practices, reaction time

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In today's fast-paced apparel retail industry, data-driven decision-making is a critical competitive differentiator. While self-service business intelligence (SSBI) tools have empowered non-technical users with analytical capabilities, they have also introduced challenges related to data governance, consistency, and scalability. This review investigates the application of federated governance models to support scalable SSBI in apparel retail organizations. Drawing on academic literature, case studies, and industry reports, the review outlines a conceptual model that combines centralized policy enforcement with decentralized, domain-specific governance roles. Experimental data from leading retail case studies demonstrate significant improvements in time-to-insight, data quality, user adoption, and governance compliance post-implementation. The paper also explores future directions including AI-augmented governance, cross-enterprise collaboration, and the integration of data ethics. The findings suggest that federated governance, when implemented with cultural and technological alignment, can deliver sustainable agility and trust in self-service analytics environments.

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Self-Service BI (SSBI); Federated Governance; Apparel Retail; Data Governance; Business Intelligence; Data Stewardship; AI in Governance; Data Culture; Scalable Analytics; Organizational Agility.

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The advent of Big Data has revolutionized the way economic behavior is observed, analyzed, and predicted, offering transformative insights into the field of behavioral economics. Big Data encompasses vast, complex, and diverse datasets generated from digital interactions, social media, online transactions, sensors, and various digital platforms. Its integration with behavioral economics provides researchers with unprecedented opportunities to understand human decision-making processes at a granular level. Traditional behavioral economics relied heavily on controlled experiments and surveys to study biases, preferences, and irrational choices. However, the availability of Big Data enables the examination of real-world behaviors across large populations and varied contexts in real time. By applying advanced analytical tools such as machine learning, artificial intelligence, and predictive modeling, economists can uncover patterns of consumer behavior, financial decision-making, and social influence that were previously hidden. Big Data also enhances the predictive accuracy of behavioral models, helping policymakers and organizations design better interventions, such as nudging strategies, to promote desirable economic and social outcomes. Furthermore, it aids in refining theories of bounded rationality and prospect theory by validating them with large-scale empirical evidence. Despite these advantages, the fusion of Big Data with behavioral economics also raises critical ethical and methodological challenges. Issues such as data privacy, algorithmic bias, and the potential misuse of behavioral insights for manipulation must be addressed to ensure that data-driven economic policies remain transparent and equitable In today's digital world, we are constantly generating and collecting data. From social media posts to online shopping habits, the amount of data being created and stored is growing at an unprecedented rate. This phenomenon is known as "big data." Big data refers to the large and complex sets of data that are generated by various sources, such as social media, sensors, and other digital devices. These data sets can be analyzed to uncover patterns, trends, and insights that can inform decision-making in a variety of fields, including business, finance, healthcare, and government.

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Big Data, Behavioral Economics, Data Analytics, Artificial Intelligence (AI), Machine Learning (ML), Predictive Modeling, Human Decision-Making, Cognitive Bias, Data-Driven Policy, Real-Time Behavior Analysis, Economic Behavior, Ethical Data Use, Privacy and Security.

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An evaluation of Deendayal Upadhyay's 'Philosophical Thoughts - Holistic Happiness of Human Life'

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An evaluation of Deendayal Upadhyay's 'Philosophical Thoughts - Holistic Happiness of Human Life'

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The modern enterprise operates in a data-rich, insight-driven world where traditional data warehousing models no longer suffice. This review explored the architecture, performance, and design principles of scalable data warehouses built for the demands of real-time analytics, diverse workloads, and cross-platform data integration. Through detailed comparison of leading technologies such as Snowflake, BigQuery, Redshift, Synapse, and Databricks, we assessed critical factors including execution speed, storage efficiency, concurrency, and cloud elasticity. The paper introduced the F.L.E.X. framework, providing a theoretical model for architecting future-ready data warehousing systems that emphasize federation, elasticity, and governance. This review serves as a practical guide for practitioners and researchers committed to building scalable, compliant, and cost-effective analytical ecosystems.

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Data warehouse, scalability, analytics, cloud data platforms, query optimization, lakehouse, serverless architecture, governance, concurrency, performance engineering

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Clinical trials are the cornerstone of evidence-based medicine, and the validity of their outcomes depends heavily on the integrity of the underlying data. This review provides a comprehensive examination of how data integrity can be ensured within the framework of ICH Good Clinical Practice (GCP) guidelines, particularly through modern Clinical Data Management (CDM) practices. It explores emerging technologies such as artificial intelligence (AI), blockchain, cloud computing, and risk-based monitoring as tools to address longstanding challenges in data reliability, traceability, and compliance. A novel theoretical model is proposed, validated through experimental comparison with traditional approaches. Findings reveal significant improvements in data query resolution, error detection, and audit readiness. The review concludes with future directions for integrating real-world data, enhancing interoperability, and shaping regulatory frameworks to embrace digital innovation. This synthesis provides valuable insights for clinical researchers, data managers, and regulatory professionals navigating the evolving landscape of clinical trial governance.

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Clinical Data Management; Data Integrity; ICH GCP; Artificial Intelligence; Blockchain; Risk-Based Monitoring; Regulatory Compliance; Electronic Data Capture; Clinical Trials; Audit Trails.

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Privatisation and Education: An Overview

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Privatisation and Education: An Overview

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In the digital age, the growing volume of data generated across industries presents significant challenges for organizations in terms of data archival and decommissioning. Traditional methods of data management, while effective in certain contexts, often fail to integrate modern technologies such as artificial intelligence (AI), machine learning (ML), blockchain, and hybrid storage solutions. This review proposes a comprehensive data archival and decommissioning model designed to address the limitations of existing approaches. The model integrates AI-driven classification, blockchain for secure archiving, hybrid cloud-edge storage, and automated decommissioning processes to enhance data lifecycle management. By comparing the proposed model with traditional data management frameworks, cloud-based solutions, and data governance models, the review demonstrates how the new model improves efficiency, security, and compliance. Furthermore, the paper explores the implications of these advancements for practitioners, policymakers, and researchers, offering recommendations for future research in the area. The proposed framework not only improves operational practices but also aligns with sustainability goals, making it a valuable contribution to data governance in the digital age.

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Data Archival, Data Decommissioning, Digital Data Management, Artificial Intelligence, Blockchain, Hybrid Storage Solutions, Data Lifecycle, Machine Learning, Data Governance, Sustainability, Data Compliance, Cloud Computing, Data Security.

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As machine learning transitions from experimentation to large-scale deployment, ensuring the long-term reliability, transparency, and performance of models in production has become a critical challenge. This review explores the field of monitoring machine learning systems, focusing on model drift detection, real-time alerting, and governance frameworks. It presents the causes and types of drift, evaluates current detection methodologies, compares industry tools, and introduces a theoretical framework for adaptive monitoring. By analyzing experimental results across several open-source platforms, the review identifies key strengths, limitations, and opportunities for innovation. As regulatory expectations and operational risks grow, this review aims to guide data scientists, engineers, and policymakers toward building trustworthy, compliant, and scalable ML monitoring systems.

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Machine learning monitoring, model drift, MLOps, alerting systems, data governance, explainable AI, concept drift, compliance in AI, AI lifecycle, adaptive monitoring.

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In an era of explosive data growth and hybrid cloud adoption, integrating data from diverse, distributed sources at scale has become a strategic priority for organizations. This review presents a comprehensive analysis of scalable data integration practices, with a specific focus on Oracle Data Integrator (ODI) and AWS DataSync. It begins by contextualizing the importance of hybrid data pipelines and identifies the major challenges in latency, schema consistency, and system interoperability. A synthesis of recent literature and case studies demonstrates how combining ODI's metadata-driven transformation capabilities with DataSync's high-throughput, secure data movement yields a robust integration framework. The paper introduces a new Hybrid Data Integration Model (HDIM) that outperforms traditional ETL and schema-on-read architectures in predictive accuracy, latency reduction, and operational reliability. Comparative performance benchmarks and real-world applications in healthcare, manufacturing, and retail highlight the model's practical relevance. The review concludes by discussing implications for practitioners and policymakers, and it offers recommendations for future research in AI-enhanced data orchestration, governance, and edge-cloud integration.

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Data integration, Oracle Data Integrator, AWS DataSync, hybrid cloud, ELT, metadata-driven architecture, real-time analytics, data pipeline, interoperability, predictive analytics, cloud computing, data orchestration.

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Abstract: This paper explores Rabindranath Tagore's complex engagement with colonial rule and his powerful act of protest against the British government following the Jallianwala Bagh massacre. It also examines the profound impact of Gitanjali--both the original Bengali version and its English translation--on world literature and global audiences. By renouncing the knighthood and dedicating his poetic work to international readers, Tagore positioned himself as a global humanist. The paper highlights how Gitanjali functioned as a literary bridge between East and West, embodying Tagore's vision of spiritual unity and human connection beyond national boundaries.

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Keywords: Rabindranath Tagore, Gitanjali, knighthood renunciation, colonial protest, English translation, global literature, Indian aesthetics, Rosenstein, Nobel Prize.

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Abstract Abstract: The Present study is on Right to Education Act 2009 with special reference to infrastructure of Primary Schools. By 86th amendment Act 21-A was added as a new fundamental right in 2002. Right to Education Act (RTE) is an Act of the Parliament of India enacted on 4 August 2009, which describes the modalities of the importance of free and compulsory education for children between the age of 6 to 14 years in India under Article 21A of the Indian Constitution. Right to children to free compulsory education act 2009 was come in to force on 1 April 2010. The objective of the present study is found out the infrastructure of primary schools. The data was collected from 40 government schools and 40 private schools of Ghaziabad city of U.P. A Questionnaire was prepared by researcher. The data collected was systematically tabulated and analysed. The findings of the study shows that infrastructure of Primary Schools.

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RTE Act 2009, Infrastructure, Primary Education

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Clitoria ternatea, commonly known as butterfly pea, is a medicinal plant renowned for its vibrant blue flowers and diverse phytochemical profile. Butterfly Pea has been used for centuries in Ayurvedic and Southeast Asian Medicine and now recent studies have shown that it holds great promise in today's pharmaceutical field. The Plant is rich in bioactive compounds like flavonoids, anthocyanins, triterpenoids and peptides like cyclotides which contributes to its antioxidants, anti-inflammatory, antimicrobial, nootropic, and anticancer properties. This article reviews current findings on the pharmacological properties of butterfly pea, its mechanism of action, and emerging application in drug formulation and diseases treatment.

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Butterfly Pea, Clitoria ternatea, Ayurveda, anti-oxidant

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The construction industry has witnessed significant advancements in materials and methodologies over the past decades. Reinforced Cement Concrete (RCC) and Composite structures are two prominent systems widely used in building construction. This study provides a comparative analysis of these two structural systems, focusing on their design, performance, cost-efficiency, and environmental impact. RCC structures, known for their simplicity in construction and durability, are extensively utilized in conventional construction. Conversely, composite structures, which integrate steel and concrete, offer enhanced strength-to-weight ratios, flexibility in design, and faster construction timelines. The analysis explore into factors such as load-bearing capacity, seismic resistance, material consumption, construction speed, and lifecycle costs. Additionally, the environmental implications of both systems are examined to align with sustainable construction practices. The study aims to provide a comprehensive understanding for selecting the optimal structural system for different building requirements.

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R.C.C, High-rise Structures, Composite, Seismic Response, Shear Connectors.

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Folklore, Artisans, Handicraft, Doll makers, Culture

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The management of digital identity is undergoing a significant transformation, moving away from centralized and federated models towards the user-centric paradigm of Self-Sovereign Identity (SSI). SSI aims to empower individuals with greater control, privacy, and security over their personal data. This paper presents a comparative analysis of prominent SSI solutions and related platforms, including Privado ID, Hyperledger Indy, Sovrin, the uPort ecosystem (Serto and Veramo), Jolocom, Sora ID, ShoCard (as integrated by Ping Identity), Wipro Dice ID, and Curity Identity Server. The analysis employs a framework evaluating key criteria such as underlying architecture, governance models, adherence to standards (W3C DIDs and VCs), core features, security and privacy mechanisms, interoperability potential, scalability considerations, and ecosystem maturity. The research outcomes indicate a notable heterogeneity in technological methodologies, encompassing dedicated distributed ledger technology (DLT)-based networks as well as integrated functionalities within pre-existing identity and access management (IAM) platforms. The dynamics of the market, including the anticipated cessation of the Sovrin MainNet, the progressive development of uPort, and strategic acquisitions such as the procurement of ShoCard by Ping Identity, play a pivotal role in shaping the ecosystem. Notwithstanding advancements in standardization, obstacles pertaining to interoperability, user-friendliness, key management, governance, and regulatory compliance continue to endure. This manuscript provides a comprehensive analysis of the contemporary landscape of self-sovereign identity (SSI) solutions, elucidating their distinguishing characteristics and the challenges that hinder their extensive adoption.

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Digital Identity, Centralized Credentials, Federated Identity, Decentralized Identity, Self-Sovereign Identity, Literature Review, Historical Analysis, Comparative Analysis, Thematic Coding.

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Parcel Guard is a smart delivery box solution designed to securely receive parcels when no one is available at home .There are a lot of problems with internet shopping, missed deliveries, and package theft. User Parcel Guard addressed this by using a combination of IoT and embedded systems, allowing authorized household members to remotely control a secure, weatherresistant delivery box via a smartphone app Blynk. When a delivery person arrives, they contact the homeowner, who can then remotely unlock the box, allowing the package to be placed securely inside the compartment one of the box. The system leverages a Raspberry Pi Model 4 as the main controller, which manages the communication between the microcontroller for Wi-Fi connectivity and the smartphone app. A servomotor lock ensures that the box remains securely closed until the owner locks or unlocks it via the Blynk app. Upon a successful parcel deposit, the system sends a real-time notification to the owner, providing confirmation of delivery and enabling them to lock the box again for added security. This seamless solution allows the user to retrieve their parcel at their convenience, offering peace of mind by integrating the IoT, cloud connectivity, and mobile-based remote control for a secure and flexible delivery experience.

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IoT, Smartphone app, Smart Delivery box

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Validation of sterile and non-sterile pharmaceutical facilities is essential to ensure compliance with regulatory standards and maintain product quality. Sterile facilities require stringent validation to prevent contamination, including cleanroom design, HVAC systems, personnel gowning, and media fill simulations. Non-sterile facilities focus on contamination control with less stringent requirements, such as cleaning validation and bioburden control. Both types require thorough documentation, environmental monitoring, and risk-based assessments. This article discusses the validation processes, regulatory expectations, and common pitfalls, such as inadequate documentation and inconsistent cleaning cycles, emphasizing the importance of maintaining safety and compliance in pharmaceutical manufacturing.

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regulatory, cleanroom, gowning, room, medical (11 each) ensure, personnel, control, environmental, monitoring, qualification (10 each) facility, product, systems (9 each) pharmaceutical, facilities, documentation, devices (8 each) quality, media, fill, common, consistently (7 each)

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The present research has systematic approach to synthesized a series of benzothiazolyl and benzimidazolyl substituted derivatives and to study their antimicrobial activity. The compounds were synthesized by green chemistry technique. i.e. 2-(2-(5-methyl-2,4-dihydro-3H-pyrazol-3-ylidene) hydrazinyl)benzothiazole. , 5-methyl-N-(2-phenylthiazol-5-yl)-2,4-dihydro-3H-pyrazol-3-imine. , 5-methyl-N-Phenyl-2,4-dihydro-3H-pyrazol-3-imine. , N'-(5-methyl-2,4-dihydro-3H-pyrazol-3-ylidene)isonictinohydrazide., N'-(5-methyl-2,4-dihydro-3H-pyrazol-3-ylidene)benzohrdrazide., and 2-hydroxy-N'-(5-methyl-2,4-dihydro-3Hpyrazol-3-ylidene)benzohydrazide. Antimicrobial study of these series of compounds was implemented with respect to Klebsiella pneumoniae, Escherichia coli and Staphylococcus aureus. Structures of all the newly synthesized compounds were confirmed by their IR, 1H-NMR analysis. The selected compounds may be used to design more potent biologically active compounds.

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Heterocyclyl Compounds, Substituted Pyrazoles, Pharmaceuticals, Applicability study

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