Volume 13 | Issue 4

 Abstract

- Railway level crossings are critical points where road traffic intersects with railway tracks, often leading to accidents due to human error or malfunctioning systems. This review paper explores existing technologies and approaches for enhancing safety at these crossings, focusing on automated systems for real-time obstacle detection and gate management. Various sensor-based solutions, including infrared, ultrasonic, and image processing techniques, are examined for their effectiveness in detecting obstacles such as vehicles, pedestrians, or debris. These systems aim to alert both road users and trains through alarms, flashing lights, and barrier controls to prevent collisions. Additionally, the review discusses automation of level crossing gates using GPS or track-based sensors to open and close gates without human intervention. Such automation reduces reliance on manual operations and minimizes the risk of errors, improving overall safety. The paper highlights the potential for integrating these systems into existing infrastructure, offering a cost-effective approach to modernizing railway crossings. Through the review of current technologies and studies, this paper aims to provide insights into the future development of automated, real-time safety systems at railway intersections.

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Safety system, Level crossing system, Real-time Obstacle Detection, train

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This paper presents the development of CreativeNexusAI, a novel platform for multimodal content generation powered by Large Language Models (LLMs). The project aimed to integrate theoretical knowledge with practical application, focusing on the deployment, scalability, and optimization of LLMs. The methodology involved a phased approach, starting with foundational research on LLM architectures like BERT and GPT, progressing to practical implementations with tokenization, vector databases, and Retrieval-Augmented Generation (RAG). We utilized Google Gemini and Hugging Face APIs for text, image, video, and meme generation, integrated within a modular architecture using FastAPI and MongoDB. Results demonstrate the platform's capability to generate context-aware, high-quality content across various media types, with preliminary user testing (n=30) showing 89% satisfaction with blog content quality and 83% with image-text coherence. Response times averaged 3.4 seconds for text generation and 4.8 seconds for image creation, demonstrating the system's efficiency. This research contributes to the field by providing a practical demonstration of how advanced AI techniques can be applied to real-world content creation, offering insights into the scalability and efficiency of LLM-driven platforms.

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Content generation, Large Language Models, Multimodal AI, CreativeNexusAI, Natural Language Processing, Vector Databases, Retrieval-Augmented Generation

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Harpreet Kaur Research Scholar, Faculty of Nursing, DBU, Mandi Gobindgarh, Punjab Sukhmanpreet Kaur Associate Professor, Faculty of Nursing, DBU, Mandi Gobindgarh, Punjab ABSTRACT: Background-Critical care nurses are playing an essential role in care of patients of intensive care units. They are frequently involved in taking ABG but for analyzing the report they regularly dependent on doctors. They need to be aware regarding the Interpretation. Objective-To assess the knowledge of critical care nurses regarding ABG Procedure and ABG analysis interpretation. Material and Method-A descriptive design was conceded for the present study. Total 200 Critical care nurses were working different critical care units were enrolled. Non randomized convenient sampling technique was used. A pre validated self-structured questionnaire including of 10 questions related to knowledge about the ABG procedure and 20 ABG analysis interpretations was developed and administered to assess the knowledge of critical care nurses. Results- The majority of the Critical Care Nurses are between 20-30 years i.e. 74%, the next main group is 31-40 i.e.91% of the critical were nurses are female (61% of the working were GNM, 27% were B.Sc. and 9% were P.B.BSc and 3% were M.Sc. Nursing A significant majority have 0-5 year experience 84%- 59% of them had knowledge about Allen Test. 70% of critical care nurses correctly knew about pH normal range 38 percent knew about respiratory acidosis and only 20% nurses were able to solve the equation of ABG interpretation. According to category the Good, Average and poor. The majority of participants (88%) score in the "Poor" category range i.e. (0-49), with 10% scoring in the "Average" range i.e. (50-79) and only 2% achieving a "Good" range score i.e. (80-100) This indicates that critical care nurses have lower knowledge of ABG analysis interpretation. Conclusion-Critical care had gap in ABG procedure and ABG Analysis interpretation knowledge. They need to be taught regarding ABG procedure and ABG Analysis interpretation.

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Key Words -Critical care nurses, ABG Analysis interpretation.

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Six distinct colonies were isolated from the intestine of Mickey Mouse molly Xiphophorus maculatus through serial dilution, pour plate, spread plate and streak plate methods. Based on the biochemical tests, the isolated bacteria were S1 (Leuconostoc sp.,) S2 (Bacillus sp.,) S3 (Lactobacillus sp.,) S4 (Paracoccus sp.,) S5 (Lactobacillus sp.,) and S6 (Bacillus sp.). Enzymatic productivity (Amylase, Protease and Lipase) of the isolated bacteria were carried out. Mass multiplication of Leuconostoc sp., Bacillus sp., Lactobacillus sp., Paracoccus sp., Lactobacillus sp., Bacillus sp., was done in nutrient broth. Antibacterial activity of the intestinal bacteria of Mickey Mouse Molly was carried out with the help of selective media along with a commercial antibiotic (Streptomycin).Five different feeds having different bacteria such as control ( without bacteria) Feed I(1ml of Bacillus sp), Feed II (1 ml of each Bacillus sp., and Lactobacillus sp.,), Feed III (Bacillus sp., Lactobacillus sp., Paracoccus sp.,), Feed IV (1 ml of each Bacillus sp., Lactobacillus sp., and Paracoccus sp.,)Feed V (1ml of each Bacillus sp., Lactobacillus sp., Paracoccus sp., and Leuconastoc sp.,) were prepared. Feed utilisation parameters of Mickey Mouse Molly were estimated after 21 days. Based on the antibacterial test, the Bacillus sp., Lactobacillus sp., Paracoccus sp., and Leuconostoc sp. have higher inhibition. The feed consumption, feed conversion efficiency and growth, assimilation, metabolism Gross and net growth efficiency were higher in Feed V.

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Intestinal bacteria, biochemical, antibacterial, growth, Micky mouse molly

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 Abstract

Mahilao ka sashkt evam atamnirbharta mein gramin mahila vikas yojana ka mahtav ek adhyayan

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Mahilao ka sashkt evam atamnirbharta mein gramin mahila vikas yojana ka mahtav ek adhyayan

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This study aims to benchmark the financial performance of two major players in the Indian power sector Tata Power Limited and Adani Power Limited using key financial analysis over a year. The power sector in India plays a vital role in economic development and understanding the financial health of its leading companies is essential for investors, stakeholders and policymakers. The research employs a comparative analytical methodology focusing on various financial parameters. Analysis is used to examine the growth patterns and performance consistency of both companies.The findings reveal significant differences in financial strategies and risk management approaches adopted by Tata Power and Adani Power. While one company demonstrates stability and consistent returns, the other reflects aggressive expansion backed by higher leverage. This benchmarking offers a clear picture of each company's financial strengths and vulnerabilities, thus helping in informed decision-making for stakeholders.The study concludes with key insights and suggestions to enhance financial performance and maintain sustainable growth in a competitive and evolving energy market.

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Tata Power, Adani Power, Financial Performance, Ratio Analysis, Trend Analysis

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Aim and Objective: To assess the knowledge regarding teenage pregnancy among adolescent girls in selected school, Coimbatore. Materials and Methods: A descriptive study was adopted to assess the knowledge among adolescent (13-17 years) school students (40 Samples) studying in 9th standard in school at Ashokapuram Village, Coimbatore who filled the inclusion and exclusion criteria. Convenient purposive sampling technique used to select the samples. Tool was prepared and validity of the tool was obtained from Subject experts. Descriptive and inferential statistics was administered to assess the knowledge among adolescent (13-17 years) school students. Results: The study finding revealed that among 40 samples, majority of the adolescent 36 (90%) are in the age group 16-17, 4 (10%) are in the age group of 13-15 years. Conclusion: The study results revealed that most of the adolescent girls possess a basic understanding of teenage pregnancy, there remain sufficient significant gaps in knowledge regarding its causes, consequences and method of prevention

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Keywords: Teenage, Pregnancy, adolescent.

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A smart grid includes a variety of intelligent control systems for power generation and also for increasing the energy efficiency of the system. These systems include smart power converters, but also renewable energy and highly efficient resources. Multilevel inverters are considered modern and basic elements of high voltage power supply systems; however, the failure of electronic power components strongly affects the reliability of the entire system. The important goal in defining and dimensioning of smart grids is the measuring and determining of the boundary conditions and operating regimes of the power components. This paper presents an innovative technique for the fault detection of power components for a three-phase multilevel inverter, which is one of the typical components of a smart grid. Single, double and triple switch failures can be diagnosed by this method. The detection mechanism is based on the analysis of the stator current, with the possibility to differentiate between the simple and multiple switching failures. Also, these models can achieve the harmonic analysis to verify the system correctness and can simulate different operational scenarios to test the functioning of the control system.

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Simulation and Fault Detection Techniques for Multilevel Inverters used in Smart Grids

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This abstract highlights about Vehicle headlights have long been a critical safety component, but their technology has remained relatively stagnant despite advancements in smart cars. The issue of blindingly bright headlights causing accidents persists. The intense glare from high beams poses risks, leading to temporary blindness and potentially fatal collisions.To address this, we propose an innovative automatic headlight intensity control system. Our prototype employs Light Dependent Resistors (LDR) to detect oncoming vehicles and adjust headlight intensity accordingly, dimming them to reduce glare and enhance safety. This system eliminates the need for manual adjustments by drivers, significantly reducing the risk of accidents caused by dazzling headlights. According to the regulations of the Indian Roads and Transport Council, vehicles should primarily use low-intensity lights. However, drivers often misuse high beams due to poor visibility with low beams. Our automatic dipper system intelligently manages headlight intensity, optimizing visibility while ensuring compliance with regulations.

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 Keywords

SMART VEHICLE HEAD LIGHT AUTO SWITCHING AND INTENSITY CONTROL

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Train collisions pose a significant threat to railway safety, often resulting from signal failures, human error, or poor communication. This research presents a comprehensive solution integrating RFID technology with ultrasonic sensors, GSM modules, ESP32 microcontrollers, and motor driver systems to create an automatic train collision prevention system. The proposed system identifies train positions using RFID, detects proximity threats via ultrasonic sensors, communicates real-time alerts through GSM, and controls train movement using motor drivers--all orchestrated by an ESP32 controller. The design emphasizes cost-effectiveness, scalability, and real-time responsiveness, particularly suited for developing countries

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RFID Technology, Ultrasonic Sensor, ESP32, Automatic braking system

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AIDS stand for acquired immune deficiency syndrome. It is a disease of the human immune system caused by Human Immunodeficiency Virus AIDS was first report in the United State in 1981 and the HIV virus isolated in 1983.AIDS is the most advanced state of HIV infection A study was conducted using quantitative research approach, descriptive research design at Era College of Nursing, Hayat Institute of Nursing, Bora Institute of Nursing. The total sample size was 150 samples selected by convenience sampling technique. The data was collected by administering structured knowledge questionnaire. Finding related to assessment of knowledge on HIV/AIDS and its prevention among ANM 2nd year students, study finding reveals-26.7% ANM 2nd year students having adequate knowledge regarding HIV/AIDS and its prevention.73.3% ANM 2nd year students having inadequate knowledge regarding HIV/AIDS and its prevention.

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S.NO. ABBREVIATIONS EXPANDED FORM 1 AIDS Acquired Immune Deficiency Syndrome 2 HIV Human immunodeficiency Virus 3 ART Antiretroviral Therapy 4 ARV Antiretroviral 5 FSW Female Sex Worker 6 > Greater than 7 < Less than 8 STI/STD Sexually Transmitted Infection/Sexually Transmitted Disease 9 % Percentage 10 N Number of subjects 11 S.D. Standard Deviation 12 R Reliability 13 S Significant 14 ANM Auxiliary Nurse and Midwife

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This project introduces a Smart Shoe system paired with a Pocket Device that enables offline voice-based interaction using the ESP32 Dev Module. It incorporates wake word recognition via TensorFlow Lite Micro, local command processing using ESP-SR, and voice feedback through ESP-TTS, with audio delivered over Bluetooth--completely independent of internet connectivity or cloud services. The Pocket Device serves as the processing hub, interpreting data from sensors embedded in the shoe and providing instant auditory responses through connected wireless earphones. Designed for energy efficiency and compactness, the system enhances mobility, safety, and accessibility--particularly for individuals with visual impairments.

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ESP32, Smart Shoe, Pocket Device, Wake Word Detection, Offline Voice Assistant, Bluetooth TTS, ESP-SR.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Wireless sensor networks (WSNs) represent a sophisticated technology that faces challenges in managing numerous sensor nodes, data collection, transmission, and enabling actions across diverse applications, including tracking, surveillance, and forest fire detection, in both civilian and military sectors. This architecture is considerably more vulnerable to threats, hacking, and exploitation due to the distribution context, features of the sensor-equipped nodes, and their transmission procedures, in contrast to traditional networks. Consequently, an ideal strategy is necessary to provide protection in these networks while considering essential limits related to energy conservation and data protection. This research presents an energy-efficient secure multipath transmission method for grid-based wireless sensor networks (EESMPT). The proposed approach contains three phases. The initial phase involves the creation of the grid-based network. At this stage, a grid header was chosen via the multi-criteria optimization technique. The second stage involves the development of a lightweight cryptographic method for secure data transport. In the third stage, multiple paths are chosen to identify the quickest route for secure data transmission. The subsequent measures are employed to evaluate the efficacy of the suggested approach: energy usage, packet delivery ratio, and the count of active and dead nodes.

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Wireless Sensor Network, Energy Efficient, Secure data transmission, Light weight cryptography, Multi-path transmission, Grid based network.

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The rapid spread of fire in remote, elevated, or structurally compromised locations poses a substantial risk to both property and lives. Traditional firefighting approaches, while effective on the ground, are often restricted by physical and environmental limitations. This project presents the development of a cost-effective, manually operated Fire-Fighting Drone (FFD) capable of deploying fire extinguisher balls over targeted fire zones. The drone is equipped with a basic mechanical payload dropping mechanism triggered by a switch on the remote controller, enabling safe operation at a distance. Unlike autonomous UAVs, the proposed FFD is simple, affordable, and accessible for emergency services in rural or low-resource settings. The system is tested under controlled fire conditions and shown to effectively suppress small-scale fires with improved targeting accuracy and safe operational distance. The paper discusses the design process, mechanical integration, performance analysis, and potential applications, along with the limitations and suggestions for future enhancements.

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Fire-Fighting Drone, Manual UAV, Fire Extinguisher Ball, Payload Mechanism, Remote Operation, Emergency Suppression

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Phishing attacks continue to dominate the global cyber threat landscape, exploiting newly registered and visually deceptive domains to lure users into compromising sensitive information. This review examines how artificial intelligence (AI) and machine learning (ML), when combined with open-source intelligence (OSINT) and content similarity techniques, offer a powerful, proactive defense against such threats. By leveraging domain metadata, web content features, and visual analysis, modern detection frameworks can identify phishing domains at the time of or shortly after their registration. This article synthesizes state-of-the-art research, evaluates AI model performance, and introduces a lifecycle-based theoretical model for AI-powered phishing detection. The review also highlights current gaps in explainability, scalability, and integration, providing a roadmap for future development in this critical domain of cybersecurity

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Phishing Detection, AI in Cybersecurity, WHOIS Data, Domain Intelligence, Machine Learning, Webpage Similarity, OSINT, CNN, LSTM, Visual Phishing, Explainable AI, Federated Detection.

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 Abstract

The lip serum with SPF is a concentrated product that provides protection from sunlight, hydration, plumping, and healing effect on lips upon application. This also provides a brown tint to the lips. Lip serums contain smaller molecules when compared to lip oils which helps to penetrate deeper into the skin. The projects aim to formulate a Herbal lip serum with SPF that provides protection from sunlight, heals sunburn, and prevents Actinic cheilitis. The objective of the project was to formulate a multifunctional lip product that provides protection, hydration, and healing effect. The Herbal lip serum with SPF was prepared by using carrot seed oil, coconut oil and other ingredients in specific quantity. The formulation was prepared by incorporating Carrot seed oil and Coconut oil into melted shea butter and beeswax and is stabilized by vitamin E. Five formulations (F1-F5) was prepared with varying concentrations of ingredients The formulations were evaluated for organoleptic properties, SPF, pH, irritancy and spreadability to ensure product quality and consistency. The formulation F4 was found to be the best among the five preparations as it showed greater consistency, SPF, and homogeneity. The results demonstrated the successful development of a Lip serum with sun protection, uniform brown tint, smooth texture, ideal pH and good spreadability. The findings suggest that the developed Lip serum to be a stable, safe, and effective lip care product which can deliver multiple benefits. The formulation successfully meets the intended objectives, providing moisturization, soothing, sun protection and healing effect, making it suitable for diverse lip types. The developed formulation holds promise as a natural, effective, and high-quality addition to lip care routines, which can be used both day and night and whenever required. Further higher studies are required to explore the efficacy and safety of this formulation in larger population.

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Lip serum, Protection, sunlight, SPF

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Creative Commons Attribution 4.0 and The Open Definition

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In financial engineering, stock market prediction is a crucial subject, particularly given the ongoing advancement of innovative methods and strategies in this area. In this study, we look into how sentiment exhibited in Twitter tweets affects the ability to predict stock prices. Twitter is the social networking site that gives everyone a free forum to publicly share their opinions. In specifically, we use the API to retrieve the company's live Twitter tweets. Every special character and stop word in the dataset is taken out. The Random Forest classifier is used to analyze sentiment in the filtered data. As a result, the tweets are categorized as neutral, negative, and positive. To get the outcome, the machine learning model receives the stock data and the tweet data as input. The stock market price is predicted using the ML classifier as a model. The real stock market value is contrasted with the predicted value that was obtained. Experiments employing real-time Twitter data and daily stock data from a number of businesses. The project's objective is to forecast the future price of a stock of interest by combining sentiment analysis of news headlines and Twitter tweets with previous stock data.

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Stock Market, Data Analysis, Machine Learning, Stock price Prediction, Social Media.

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Mahamanjisthadi Kwatha is mainly indicated in the management of skin disorders and blood related disorders. This review compiles evidence from texts like Sharangdharsamhita to under score Mahamanjisthadi Kwatha's potential as a safe and holistic approach to manage skin diseases. It contains a synergistic combination of herbs such as Manjishtha (Rubiacordifolia), Neem (Azadirachtaindica), Guduchi (Tinosporacordifolia), Sariva (Hemidesmusindicus), and Triphala (Amalaki, Haritaki, Bibhitaki), which together provide detoxifying, anti-inflammatory, and antimicrobial actions. The pharmacological properties of individual ingredients have been validated in various experimental and clinical settings, supporting skin healing, immune modulation, and microbial control. Several case studies and small-scale clinical reports demonstrate positive outcomes in chronic and relapsing Kushta diseases, showing reductions in inflammation, lesion severity, and recurrence rates. One study involving acne management highlighted its effectiveness in combination with leech therapy, while another showed notable improvement in psoriasis severity scores following its administration.

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Therapeutic Review of Mahamanjishthadi Kwatha in skin disorders.

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Electric wheelchairs help people with disabilities move around more easily, giving them more freedom and a better quality of life. Adding joystick controls has made it easier to drive the wheelchair, making users more independent. In recent years, health monitoring systems have been added to track important health signs like heart rate and oxygen levels. This paper explains how joystick-controlled electric wheelchairs work, how health monitoring is added, their benefits, challenges.

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Electric wheelchairs, joystick control, assistive technology, health monitoring systems, heart rate tracking, oxygen saturation, user independence, smart mobility devices, biomedical sensors, accessibility solutions

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The semi-arid landscapes of Pandharpur, Sangola, and Mangalwedha in Solapur district, Maharashtra, represent a unique intersection of biodiversity and human activity. This study investigates mammalian diversity and the conservation challenges faced in these ecologically sensitive regions. Over a six-month period (Oct 2023-May 2024), systematic field surveys and community interviews were conducted across varied habitats--ranging from farmlands to urban fringes. We documented 20 mammalian species spanning seven taxonomic orders, including the endangered blackbuck (Antilope cervicapra), Indian gray wolf (Canis lupus), and Indian leopard (Panthera pardus). Analysis reveals stable populations for most generalist species, while larger carnivores and grazers are in decline due to habitat fragmentation, urban sprawl, and conflict with agriculture. Human-wildlife interactions are intensifying, with 54% of local respondents reporting direct conflicts. However, the study also reveals encouraging signs of coexistence: 74% of respondents expressed willingness to support conservation initiatives. These findings highlight both the threats and opportunities in fostering community-based conservation and call for targeted awareness, legal literacy, and habitat restoration in this overlooked dryland ecosystem of peninsular India.

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Community-based conservation, Conservation challenges, Dryland ecosystem, Habitat fragmentation, Human-wildlife conflict, India, Mammal diversity, Solapur district, Urban-wildlife interface, Wildlife Protection Act

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