Volume 14 | Issue 1 |

 Abstract

The Biopharmaceutical Classification System (BCS) was created to minimise the need for in vivo bioequivalence studies and to enable in vitro dissolution experiments to be used as a proxy for in vivo bioequivalence studies. The biopharmaceutical classification system classifies pharmacological compounds based on their solubility ratio, dissolution, and intestinal permeability. It enables drug products' in vivo pharmacokinetic performance to be predicted. The BCS categorization system's concepts may be used to NDA and ANDA approvals, as well as scale-up and post-approval drug manufacturing adjustments. As a result, pharmaceutical businesses may save a substantial amount of time and money on product development. The drug can be classified into four classes of the BCS namely, high solubility high permeability, low solubility high permeability, high solubility low permeability, low solubility low permeability. The formulation scientist can use BCS knowledge to produce appropriate dose forms based on mechanistic rather than empirical methodologies. Solubility- and dissolution-enhancing formulation strategies based on the supersaturation principle to enhance the extent of drug absorption, along with the applications of the BDDCS to the understanding of disposition phenomena are reviewed. Finally, recent classification systems relevant either to the BCS or the BDDCS are presented.

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 Keywords

BCS, Metoprolol

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The E-Learning Platform is a large Java-based web application that aims to update and streamline online learning. It offers an online space for teachers to develop, administer and publish their courses while also giving students the possibility to register, enroll in courses and check study materials without limitation. The project is also a great example of the practical use of object-oriented programming concepts, such as Encapsulation, Inheritance and Polymorphism, in order to make your code readable, modular, testable and maintainable. The backend part of the system is written in Java and structured as a number of packages, such as API, models and services, taking care of different functionalities, including course management, user authentication and data manipulation. The application frontend is built with HTML, CSS and JavaScript making it a nicely end-user-oriented look. It enables a seamless collaboration between the client and the server for better reach of the platform. Basic API communication was integrated to handle requests such as login, registration, course creation, and enrollment. The initiative is to show how strong Java fundamentals can be used to solve real cases by applying them with the server-oriented and web-based techniques. It serves as a central and interactive platform for both teachers and students to enable digital learning. It also just illustrates the benefits of employing Java in secure, productive and object-oriented web development. In general, e-learning systems promote the development of educational technology by offering flexibility, adaptability and accessibility in learning at any time and everywhere.

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 Keywords

Keywords: E-Learning Platform, Java Web Application, Object-Oriented Programming (OOP), Educational Technology, Frontend Development, Backend Architecture, API Communication.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Since the advent of civilization, the environment has received various type of pollutants. The first record of anthropogenic pollution may well be traced back with the discovery of fire by humans that initiated adding up of toxic oxides of carbon, nitrogen and sulphur in the atmosphere. As civilization advanced, human activity contributes to creating new sources of environmental pollution. Atmospheric pollution is one of the major problems because it affects the fauna and flora, and people themselves. Nowadays the biggest provocative of atmospheric pollution is anthropogenic human activities and transport sector, main pollutants being heavy metals. A quick, cheap and easy way to investigate the state of the environment is to use Bryophytes which prove to be a potential bio-indicator of pollution. The habitat diversity, structural simplicity, totipotency, rapid rate of multiplication and high metal accumulation capacity make mosses an ideal organism for pollution studies. Bryophytes are reliable indicators of pollution as they are easy to handle and show a vast range of specific sensitivity and visible symptoms to pollutants. Mosses is one of the most popular bio-indicator of heavy metal pollution of atmosphere, perspective and cost-effective method to control, detect and evaluate pollution. Naturally-occurring mosses have been sampled across Europe to monitor the pollution. This study is made with anticipation of supporting the green city development with a natural, sustainable and low maintenance rate solution. For the work to identification of Potentially Toxic Elements in mosses Atomic Absorption Spectroscopy (AAS) technique used.

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 Keywords

Mosses, Bio-indicator, pollution, heavy metals.

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 Abstract

The relationship between economic growth, energy consumption, and environmental quality remains one of the most widely debated themes in environmental economics. Using insights from ten influential studies (1995-2021), this review consolidates evidence on the Environmental Kuznets Curve (EKC), the role of renewable versus non-renewable energy, causality between income and emissions, and the sectoral determinants affecting environmental outcomes. The reviewed literature offers mixed but insightful results: while certain developing and middle-income regions show EKC-consistent improvements at higher income levels, most global evidence refutes the notion that economic growth alone can solve environmental degradation. Renewable energy adoption emerges as a critical moderating factor capable of reducing greenhouse gas emissions without hindering GDP. The review concludes that structural economic reforms, clean-energy transitions, and regional policy considerations are essential for achieving sustainable development.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Environmental Kuznets Curve (EKC), Economic Growth, Energy Consumption, Renewable Energy, Non-renewable Energy

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Creative Commons Attribution 4.0 and The Open Definition

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Rapid urbanization and suburban expansion have driven a significant transformation in the spatial planning and social context of childhood, often failing to integrate Children's needs within housing design. This paper explores strategies to reshape child scale spaces in suburban housing, prioritising parameters like safety, individual exploration and community engagement. This paper also provides a holistic approach in the development of the child based on different age groups according to their needs.

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Creative Commons Attribution 4.0 and The Open Definition

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Child scale spaces, Safety & Accessibility, Re-creational spaces, Individual exploration, Community engagement & Social interaction

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Creative Commons Attribution 4.0 and The Open Definition

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The Election Commission of India is an autonomous, constitutionally established federal authority responsible for administering all the electoral processes in the Republic of India. Under the supervision of the commission, free and fair elections have been held in India at regular intervals as per the principles enshrine in the Constitution.

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political parties, election commission

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Creative Commons Attribution 4.0 and The Open Definition

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A revolutionary Web Application which will revolutionize the two wheeler servicing industry by online bike service booking with pickup and drop. Long queues, poor service transparency and booking woes are the usual pitfalls of a bike servicing. These problems are eliminated by offering a digital platform to register, schedule services, add more tasks, and pay online for the services and track vehicle online in real time throughout the service life. Customers receive milestone updates such as an e-commerce tracker, service centres receive revenue from automated request routing, real time status, and digital record keeping. Digital invoicing, multi-channel payments and ratings and feedback are user experience and trust. It connects consumers and service providers, ensuring openness, effectiveness and customer satisfaction for urban mobility. It is intended to scale and integrate with AI and IoT.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Online Bike Servicing, Pick-up and Drop Scheduling, Real-time Tracking, AI-driven Scheduling, IoT Integration, Customer Satisfaction, Web Application, Service Automation

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Creative Commons Attribution 4.0 and The Open Definition

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Gastric cancer remains a major cause of cancer-related mortality worldwide, largely due to late diagnosis and the systemic toxicity of conventional chemotherapy. Oral anticancer therapy is often limited by poor bioavailability, short gastric residence time, narrow absorption windows, and drug instability in the intestinal environment. Gastroretentive drug delivery systems (GRDDS) offer an effective approach to overcome these limitations by prolonging gastric retention and enabling controlled, site-specific drug release. This review summarizes recent advances in gastroretentive drug delivery systems for cancer chemotherapy, with emphasis on gastric cancer treatment. Various GRDDS strategies, including floating, mucoadhesive, swelling, magnetic, and expandable systems, are discussed along with the role of polymers and nanocarrier-based formulations. Recent studies involving anticancer agents such as 5-fluorouracil, capecitabine, curcumin, and doxorubicin are highlighted. Overall, GRDDS show strong potential for improving the safety and efficacy of oral cancer chemotherapy.

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 Keywords

Gastro retentive drug delivery system; Gastric cancer; Chemotherapy; Floating drug delivery system; Mucoadhesive system; Controlled drug release; Site-specific drug delivery; 5-Fluorouracil; Capecitabine; Polymer-based drug delivery

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Narcissistic abuse represents a distinct and severe form of psychological trauma characterized by coercive control, gaslighting, emotional manipulation, and systematic erosion of personal boundaries. Despite growing recognition of its clinical impact, existing assessment instruments inadequately capture boundary dysfunction the core mechanism through which narcissistic abuse operates. The present paper introduces the Empowerment & Boundaries Assessment (EBA) and Boundaries Enhancement Therapy (BET) as an integrated, empirically informed framework for assessment, intervention, and outcome evaluation among survivors of narcissistic abuse. The EBA is a multidimensional self-report measure assessing emotional, cognitive, behavioural, and relational boundary functioning, while BET is a structured, phase-based therapeutic model designed to restore autonomy, empowerment, and relational safety. This paper details the theoretical foundations, development, psychometric properties, administration, clinical applications, ethical considerations, and research implications of EBA and BET. Together, these tools provide a comprehensive, trauma-informed, and research-ready model for clinicians and scholars working in the field of narcissistic abuse recovery.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Narcissistic abuse, psychological boundaries, empowerment, trauma-informed care, assessment, psychotherapy

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Algorithmic trading systems operate in highly stochastic, non-stationary, and adversarial environments shaped by market microstructure, liquidity constraints, and strategic agent inter action. Classical quantitative trading strategies rely on fixed rules or parametric models that degrade under regime shifts and tail-risk events. Artificial intelligence (AI) offers a principled framework for learning predictive signals, optimizing sequential decisions, and managing risk under uncertainty. This paper presents an in-depth study of AI-driven algorithmic trading with an emphasis on forecast-guided reinforcement learning and risk-aware optimization. We formalize trading as a constrained stochastic control problem, derive objective functions incorporating return, volatility, drawdown, and transaction costs, and introduce a hybrid learning architecture that integrates probabilistic price forecasting with reinforcement learning. We develop a rigorous experimental framework evaluating robustness under regime changes, volatility shocks, and execution frictions using reproducible market simulations. Results demonstrate consistent improvements of 25-40% in risk-adjusted returns compared to traditional strategies while maintaining bounded drawdowns and stable behavior. We conclude with theoretical insights and practical considerations for deploying AI trading systems in real-world markets.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI, Optimization, Trading , Machine Learning , Neural Network

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Creative Commons Attribution 4.0 and The Open Definition