Volume 13 | Issue 4 |

 Abstract

This study focuses on analyzing Total Dissolved Solids (TDS), biological activity, and key physiological indicators across various regions surrounding Raipur. TDS is one of the primary impurities found in mixing water, and its concentration must adhere to specific limits as outlined in construction codes, given its potential to affect concrete properties. The research examines how variations in TDS levels influence both the fresh and hardened states of concrete. TDS, characterized by its low signal-to-noise ratio and optical inertness, is typically detected indirectly through changes in optically active water quality parameters (WQPs) within the visible, near-infrared, and infrared spectra. The findings suggest elevated TDS concentrations in contaminated sites, with marked vertical variations in TDS and bulk conductivity, indicating significant spatial and depth-related variability. Beyond its effects on construction materials, elevated TDS levels adversely impact ecosystems and human health, influencing organs such as the gastrointestinal system, heart, lungs, skin, liver, and reproductive system. Furthermore, water with TDS levels exceeding 500 ppm can cause excessive scaling in household appliances like boilers, heaters, and pipelines. To mitigate the risks associated with high TDS levels, various removal techniques have been developed, including ion exchange, electrochemical methods, precipitation, desalination, nanofiltration, distillation, ultrafiltration, forward osmosis, and reverse osmosis. However, each method has its own limitations regarding efficiency and applicability across different water matrices. This review explores the relationship between TDS and other physicochemical parameters based on an analysis of fifteen water samples collected from multiple locations within Raipur city. The primary objective of the research is to assess the quality of drinking water available to residents. The results demonstrate that many water samples exhibit TDS concentrations within the permissible limits set by the Bureau of Indian Standards (BIS), with detailed observations presented in the discussion section. The study emphasizes the importance of public awareness regarding the long-term health risks associated with consuming water from various regions.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

KEYWORDS: Total Dissolve Solids, Conductivity, Temperature, Raipur

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The potential of artificial intelligence (AI) to automate data collection, analysis, and interpretation from multiple sources is the main topic of this paper, which examines the integration of AI into pharmacovigilance (PV) systems. In addition to discussing difficulties and moral issues including algorithmic prejudice and data privacy, it offers suggestions for further study and application in this important area.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Pharmacovigilance, Artificial Intelligence, Adverse drug reactions.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study presents an explainable artificial intelligence (XAI)-driven framework for lithium-ion battery prognostics, addressing the dual challenges of prediction accuracy and interpretability in battery management systems (BMS). Using publicly available datasets from NASA and CALCE, Gradient Boosting, LSTM, and Transformer models were developed, with the Transformer model achieving the best results (MAE: 0.0275, RMSE: 0.0356). To ensure transparency, SHAP and LIME were applied for global and local feature attribution, while attention mechanisms revealed critical temporal patterns. Key degradation indicators such as internal resistance growth and voltage variation were consistently identified. The proposed framework offers a practical and trustworthy solution for accurate and interpretable RUL and SOH prediction, supporting real-world deployment in electric vehicles and energy storage applications.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

XAI, Lithium-ion Battery, SHAP, LIME, RUL/SOH

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Nowadays, people are interested in hair preparations and conditioner materials, such as shampoos, hair tonic and conditioner formulations containing herbal extracts. The Aim of present study involves preparation of herbal hair tonic by using Fenugreek leaves, Tulsi leaves, Hibiscus flower, Curry leaves and coconut oil, Almond oil, Clove oil, Eucalyptus Using the Direct Method, oil and a crude medication mixture were made into herbal hair tonic, and their antifungal and antibacterial properties were assessed. Batches F1, F2, and F3 with varying concentrations are used to construct the final preparation of these substances. F1, F2, F3 formulation is tested for antibacterial and antifungal activity. The formulation of different concentrations was characterized for analysis including Moisture content, Acid value, Saponification value, Specific gravity. The formulation exhibits favorable organoleptic qualities, no grittiness, good consistency, good spread ability, homogeneity, appearance, and pH, as well as good antifungal and antibacterial activity. Result was determined and are reported in this work.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Herbal formulations, anti-fungal activity, anti- bacterial activity, hair tonic, coconut oil and almond oil

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents the design, development, and evaluation of an intelligent mock interview platform aimed at improving career readiness through real-time, AI-driven simulations. Leveraging Google's Gemini (PALM) large language model, the system dynamically generates domain-specific interview questions and evaluates user responses based on contextual relevance, fluency, and delivery. Built using JavaScript, Tailwind CSS, Firebase, and WebRTC, the platform delivers an immersive, role-based experience simulating real-world interviews. Users select a job role to receive customized sessions, during which their audio or video responses are analysed in real time. Gemini's semantic understanding enables automated feedback across articulation, content depth, confidence, and role alignment, with session data stored securely in Firebase for review and iterative learning. The architecture comprises a user interface layer, an AI services layer powered by Gemini APIs, and a data services layer. Evaluation with 75 participants from fields such as software engineering, marketing, and data science showed a 38% improvement in performance over three sessions, validated through both automated and expert assessments. User feedback emphasized the platform's realism and adaptability. This study demonstrates the effectiveness of large language models in enhancing communication skills and proposes future enhancements including emotion analysis, multilingual support, and longitudinal impact studies.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Mock Interview, Gemini PALM, Real-time Feedback, Career Development, Audio-video AI, Firebase, Google Gemini PALM, AI-based Interview Training, Job Interview Practice Platform

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

India's competition law framework has undergone significant reforms with the Competition (Amendment) Act, 2023, and new regulatory updates that aim to improve penalty structures, streamline merger control, and strengthen enforcement. These changes indicate a shift toward improved dispute resolution procedures, increased regulatory transparency, and stricter control of anti-competitive activities. These reforms align India's competition legislation with worldwide best practices by encouraging fair competition and protecting consumer interests, but they also raise new compliance concerns for businesses. Among the significant changes that will guarantee speedier and more comprehensive regulatory oversight are the Deal Value Threshold (DVT) for M&A transactions, a revised definition of "control," and shortened merger review timelines. The 2024 CCI regulations also introduce settlement and commitment mechanisms, revised turnover-based penalties, and formal recognition of 'hub and spoke' cartels, expanding the scope of anti-competitive conduct enforcement. This paper explores the key regulatory developments, their broader implications for market participants, and the evolving role of the Competition Commission of India in shaping a competitive and transparent economic environment.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Competition Law, Antitrust Regulation, Market Competition, Merger Control, Abuse of Dominance

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Listened fed people face important challenges in the urban environment, as it is an inability to detect important hearing signs such as vehicle horns, emergency sirens and other traffic -related sounds. Navigating in busy roads without awareness of going to vehicles leads to a serious security risk that limits their dynamics and freedom. To solve the problem, the project suggests an IoT-based Help Smartwatch designed to detect real-time vehicle sounds and provide intuitive alerts through light signals and vibrations.The system includes a sound detection sensor, an ESP32 microcontroller and a machine learning-based classification models, which accurately identify the sound of the vehicle when filtering the background noise. A hybrid CNN- SVM model is used to ensure accurate sound classification, and separates a variety of traffic sounds such as car horns, ambulance sirens and heavy vehicle engines. When you detect a possible danger, the smart watch activates LED indicators and vibrates with different intensity depending on the urgency of the detected sound.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

IoT, Assistive Technology, Hearing Impairment, Smart Wearables, Sound Detection, Vibration Alerts, Urban Safety.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The safety of railway transportation systems largely depends on the condition of the tracks. Track damages, especially cracks, can result in severe operational hazards if not detected in time. Traditional inspection techniques often fall short due to their manual nature and inefficiency in covering long distances. With the emergence of image processing and sensor-based technologies, several automated systems have been developed for crack detection. This paper presents a detailed overview of recent innovations in this field, including methods involving LED-LDR sensors, image analysis, infrared and ultrasonic sensors, and data analytics. Each method's architecture, effectiveness, and real-world feasibility are discussed to aid future implementations in railway infrastructure maintenance. Automated crack detection systems significantly reduce the need for human intervention and enable continuous monitoring. These systems offer high accuracy, reliability, and the capability to operate under varying environmental conditions. Sensor-based techniques such as ultrasonic testing and infrared thermography provide real-time data on track integrity, while image processing algorithms enable the identification of micro-cracks that are otherwise difficult to detect. Deep learning and machine learning models further enhance the precision of detection systems by learning from large datasets and identifying complex patterns. The integration of GPS and IoT modules allows for real-time tracking and remote monitoring, further optimizing maintenance schedules and resource allocation. Several experimental and commercial systems have been reviewed, highlighting their design considerations, implementation challenges, and cost-effectiveness. A comparative analysis of different detection techniques is also provided to evaluate their suitability across diverse railway environments. The paper emphasizes the need for hybrid systems that combine multiple technologies for improved accuracy and robustness. Future research directions include the development of lightweight, energy-efficient systems and the integration of AI for predictive maintenance.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

IOT

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The quick demand for electric vehicles (EVs) results in the development of effective, environmentally friendly, and user-friendly charging infrastructure necessary. This study investigates the design and optimization of an EV wireless rapid charging system that uses solar electricity and state-of-the-art wireless power transfer (WPT) technology. Photovoltaic (PV) panels serve as the main energy source in the suggested system, which also includes a high-frequency inductive coupling for wireless charging and an effective power management unit. To improve system performance, a multi-layered optimization technique is used, with a particular emphasis on three important areas: overall system reliability, wireless transmission efficacy, and solar energy harvesting efficiency. Energy conversion efficiency, charging time, system losses, and operating cost are examples of key performance metrics. The findings show that the suggested system can achieve high energy efficiency while lowering reliance on grid electricity with the right optimization, supporting green transportation alternatives. The system's wireless nature also improves user convenience and safety, which makes it appropriate for installation at highway charging stations and smart cities.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Wireless Power Transfer , Power Management Unit , Solar Powered , Electric Vehicles

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Most of us spend a large part of our lives at work, so it plays a big role in our overall well-being. Because of this, it's very important to have a job that supports both our mental health and general health. Workplaces that support employees' mental health and help those going through tough times usually see their teams work better and get more done. Mental health refers to how someone thinks and feels about themselves and their life. It also includes a person's ability to do their best and stay connected with family, friends, coworkers, and their community (Mental Health Foundation, 2008). Today, one of the main reasons people struggle at work is because of mental health challenges caused by their job. Issues like anxiety,stress and depression are becoming more common in the workplace. In fact, depression is expected to become the second most common health issue in the world, right after heart disease (Murray & Lopez, 1996). This paper aims to explore and highlight the key factors--based on existing research--that are most likely to affect mental health at work.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

mental health, workplace, employees, anxiety, depression

  License

Creative Commons Attribution 4.0 and The Open Definition