Volume 14 | Issue 4 |

 Abstract

The Melmuri Massacre, which took place on October 25, 1921, in the Malappuram district of Kerala, is a deeply tragic yet often overlooked event in India's struggle for independence. Carried out by the Dorset Regiment of the British army, this brutal attack resulted in the deaths of 246 innocent civilians, including women, children, the elderly, and the sick. The massacre was part of a broader British crackdown on uprisings in Malabar during the Malabar Rebellion of 1921. Despite its significance, the Melmuri Massacre has not been adequately highlighted in historical records. This paper aims to delve into the events surrounding the massacre, its causes, the horrific acts of violence committed, the aftermath, and the lack of recognition it has received in mainstream historical narratives.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Melmuri Massacre, Dorset Regiment,Malabar Rebellion (Moplah Rebellion),Colonial Brutality, Khilafat Movement

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The project Mentra is an AI-powered career coach designed to transform traditional career counselling into a smart, data driven experience. The system helps users enhance their professional profiles through automated guidance and intelligent tools. It provides an interactive dashboard that highlights in-demand skills, salary trends, and market insights. Users can build ATS optimized resumes tailored to their industry and skill set, generate customized cover letters by analysing job descriptions, and take mock interviews with role-specific questions and AI-generated feedback. The platform also provides performance analytics, improvement tips, and a seamless user experience using Next.js and ShadCN UI, ensuring responsiveness and visual appeal. Overall, Mentra acts as a complete AI career development assistant, combining personalization, analytics, and automation to help individuals advance confidently in their careers.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

ShadCN UI, AI-generated, Next.js, ATS-optimized

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Kangaroo Mother Care, Knowledge, Practice, Teaching Programme, Postnatal Mothers

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Indian railway networks play a vital role in the movement of people and goods across the country, though there is a huge problem of congestion in most of the networks, inadequate schedule and under utilization of the infrastructure. The conventional rail traffic control is based on fixed schedules and manual decision making, which adds to the systemic congestion and delays [8]. The presented paper suggests a framework based on the Artificial Intelligence (AI)-driven one to optimise the rail input traffic with the help of predictive modelling and Deep Reinforcement Learning (DRL). The suggested solution combines a Deep Neural Network (DNN) to predict train arrival and delay with a reinforcement learning scheduling agent to do dynamic platform and track assignment [5]. The framework is tested in a simulation that is calibrated on the Indian Railways operating parameters [8]. Experimental data show that throughput (190 vs. 160 trains/day), average delay (9 vs. 18 minutes) and platform utilisation (82% vs. 64%), have improved by 18.75, 50, and 18 percentage points respectively. The framework has a lot of potential in large scale railway networks, which can be operated smarter, more efficiently, and in a manner that is environmentally sustainable.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Indian Railways; Rail Traffic Optimisation; Artificial Intelligence; Deep Reinforcement Learning; Deep Neural Network; Platform Scheduling; Predictive Modelling; Smart Railway Systems

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Open Cast Coal Mining, Environmental Degradation, Paschim Bardhaman, LST, Transect Profile

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Women safety is a major social concern in today's world due to the increasing number of crimes, harassment, and unsafe situations faced by women in public and private spaces. Immediate access to help and quick communication with trusted contacts can significantly reduce risk and improve response during emergencies. This project presents a Women Safety Mobile Application that enables users to trigger an emergency SOS alert using multiple methods such as a dedicated SOS button, shake detection, or volume button presses. Once activated, the system automatically shares the user's real-time location, sends alert messages, initiates emergency calls, and captures images for evidence. A backend server is used to store captured images and provide accessible links. The application ensures continuous updates until the SOS is stopped, making it a reliable and efficient safety solution.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Women Safety, SOS Alert System, Mobile Application, Real-Time Location Tracking, Emergency Response, Face Detection

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Earthworms are recognized as fundamental ecosystem engineers whose burrowing, feeding, and casting activities profoundly influence soil structure, nutrient cycling, and microbial communities. The increasing adoption of biopesticides as eco-friendly alternatives to synthetic chemical pesticides has raised questions about their potential non-target effects on beneficial soil organisms, particularly earthworms. While biopesticides are generally presumed safe, growing evidence suggests that high-dose or repeated applications may exert sub-lethal to lethal effects on earthworm populations. A controlled laboratory experiment was conducted using adult specimens of Eisenia fetida exposed to four treatment levels -- a control group (no biopesticide), a low-dose treatment (T1), a medium-dose treatment (T2), and a high-dose treatment (T3). Earthworm survival, weight changes, and four key soil parameters -- available nitrogen (N), phosphorus (P), potassium (K), and pH -- were measured at 7-day intervals over a 21-day experimental period. Earthworm survival declined progressively with increasing biopesticide concentration, from 100% in the control group to 60% in the T3 group by Day 21. Corresponding reductions in available soil nitrogen (120 to 95 mg/kg), phosphorus (35 to 28 mg/kg), and potassium (150 to 130 mg/kg) were recorded. Soil pH decreased from 7.2 (control) to 6.5 (T3). Earthworm biomass also declined in high-dose treatments, with T3 organisms losing weight relative to initial measurements. These findings demonstrate that while biopesticides present a substantially lower ecotoxicological risk than synthetic pesticides, dose-dependent adverse effects on earthworm survival and soil nutrient dynamics are clearly evident. Controlled application and dose optimization are critical to preserve soil ecosystem services in sustainable agricultural systems.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Biopesticides; Earthworms; Eisenia fetida; Soil Nutrients; Nitrogen Cycling; Ecotoxicology; Sustainable Agriculture; Soil pH

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Kangaroo Mother Care, Knowledge, Attitude, Educational Intervention, Postnatal Mothers

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Machine Learning, Water Quality Index, Water Quality Prediction, Historical Sensor Data, Regression Analysis, Random Forest.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents the design and implementation of an ESP32-CAM smart home security system with Gmail alert that provides real-time monitoring and instant alert mechanisms. The proposed system integrates a Passive Infrared (PIR) motion sensor, ESP32-CAM module, and Wi-Fi communication to detect human presence and capture images of intrusions. Upon detecting motion, the system automatically activates the camera, captures an image, and transmits it to the user through Gmail using the Simple Mail Transfer Protocol (SMTP). the system is developed as a compact and cost-effective embedded solution that eliminates the need for continuous human monitoring and expensive surveillance infrastructure. Unlike traditional CCTV systems, which rely on continuous recording and manual observation, the proposed system operates only when motion is detected, thereby reducing power consumption and storage requirements. The use of ESP32-CAM enables seamless integration of image processing and wireless communication within a single module Overall, the system is portable, scalable, and easy to deploy, making it suitable for residential, office, and small-scale security applications. Future enhancements may include night vision capability, cloud storage integration, and mobile application support to further improve functionality and user experience.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

ESP32-CAM, IoT, Smart Home Security, Motion Detection, Email Alert System, SMTP Protocol

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Creative Commons Attribution 4.0 and The Open Definition