Daily Archives: February 13, 2026

Authors: Dr Amit Kumar Awasthi

Abstract: Nawabganj Bird Sanctuary, a Ramsar-designated wetland in the Unnao district of Uttar Pradesh, India, serves as a critical wintering habitat and stopover site for a multitude of migratory bird species traversing the Central Asian Flyway (CAF). This comprehensive review paper synthesizes four decades of ornithological data, ecological studies, and management reports to analyze the patterns, drivers, and conservation status of avian migration at this vital sanctuary. The analysis confirms Nawabganj’s role as a key refuge for over 250 bird species, with a significant influx of Palaearctic migrants between November and March. Dominant families include Anatidae (ducks, geese), Ardeidae (herons, egrets), Rallidae (coots, moorhens), and a diverse array of waders (Charadriiformes). Migration timing and species composition are primarily driven by photoperiodic cues in breeding grounds and the availability of wetland habitat, forage resources, and thermal cover in the sanctuary. However, the review identifies a multifaceted crisis threatening this ecological function. Severe anthropogenic pressuresincluding water scarcity due to upstream diversion and erratic rainfall, invasive plant species (Eichhornia crassipes, Prosopis juliflora) encroachment, agricultural runoff leading to eutrophication, unsustainable tourism, and increasing human-wildlife conflict in the surrounding landscapeare degrading habitat quality. Emerging evidence suggests shifts in arrival/departure timings and a potential decline in populations of certain diving ducks and sensitive waders, possibly linked to climate change and local habitat degradation. This paper concludes that while Nawabganj remains a biodiversity haven, its long-term viability as a migratory bird sanctuary is precarious. The review advocates for an urgent, science-based, and integrated management approach. Key recommendations include securing ecological water flows, implementing systematic habitat restoration (invasive species removal, creation of deeper zones), strengthening community-based conservation, establishing long-term ecological monitoring programs, and promoting regulated, eco-sensitive tourism. The findings underscore that the sanctuary's future is contingent on translating its protected status into effective, on-ground ecological security.

DOI: http://doi.org/10.5281/zenodo.18629460

Published by: vikaspatanker

Authors: Prof. Sonali Ingole, Mr. Rohit Rajpurohit, Mr. Kartikesh Pachkawade , Prof. Deepa Shivshimpi

Abstract: The rapid growth of technology and lifestyle modernization has significantly influenced the human mind, behavior, and emotional balance. This study investigates the impact of the modern lifestyle on the subconscious mind — the part of the human psyche that governs thoughts, emotions, and decisions beyond conscious awareness. A structured questionnaire was administered to 305 respondents, including students and professionals, to examine how daily habits such as screen time, sleep patterns, stress, and mindfulness practices affect subconscious stability. Findings show that excessive device use, irregular sleep, and frequent stress strongly affect subconscious calmness and self-awareness. Participants who maintained mindfulness routines reported greater emotional balance. The study concludes that while modernization improves efficiency, it disrupts subconscious harmony, emphasizing the need for balanced routines and conscious mental care.

DOI: http://doi.org/10.5281/zenodo.19182113

Published by: vikaspatanker

Authors: Anitha Rajathi, Pellakuru Mahathi, Bhavya G, B Harshitha Reddy

Abstract: Agriculture continues to face significant challenges due to crop diseases that result in reduced yield, economic losses, and delayed intervention, particularly in developing regions where access to expert diagnosis is limited. Traditional disease identification methods rely on manual inspection, which is time-consuming, subjective, and not scalable. This paper presents a Smart Crop Disease Detection System using Convolutional Neural Networks (CNNs) for automated and accurate identification of plant diseases from leaf images. The proposed system leverages deep learning techniques trained on real-world agricultural image data obtained from the PlantDoc dataset, which contains healthy and diseased crop leaves captured under diverse field conditions. A lightweight and efficient CNN architecture, MobileNetV2, is adopted to enable real-time disease detection with reduced computational overhead, making the system suitable for mobile and low-power devices. The model performs image classification to identify disease categories and assess plant health conditions. Experimental evaluation demonstrates that the proposed model achieves an accuracy of 85%, outperforming other baseline architectures. To enhance deployability, the trained model is converted into TensorFlow Lite, enabling seamless integration into mobile and web-based applications. The proposed framework facilitates early disease detection, supports timely preventive measures, and contributes to improved agricultural productivity through intelligent decision support.

Published by: vikaspatanker

Authors: Deepa Kumar M, Sutha K

Abstract: The systemic mismanagement of surplus food and clothing creates significant economic and social waste, necessitating a transition from manual, fragmented charity methods to automated, data-driven platforms. This paper analyzes a web-based Digital Redistribution System developed using PHP and MySQL to facilitate real-time resource allocation between donors (restaurants, individuals) and orphanages. By shifting from a "reactive" model—where surplus often spoils before discovery—to a "proactive" digital ecosystem, the system ensures timely collection and transparent tracking. The study highlights the effectiveness of Centralized Data Management and Validation Testing in reducing manual overhead and ensuring data integrity, ultimately proposing a scalable framework for minimizing waste in urban environments. By shifting from manual, often inefficient donation methods to an automated online system, this project aims to reduce hunger and minimize environmental waste.

Published by: vikaspatanker

Authors: Sourabh Upadhyay, Professor Jitendra Chouhan

Abstract: One of the main purposes of Highway bituminous pavement failure and its maintenance is to provide a better road surface for the road users and carry traffic smoothly and safely with minimum cost. Paved roads in tropical and sub-tropical climates often deteriorate in different ways to those in temperate regions, because of the harsh climatic conditions, lack of proper design and quality control, high loads and inadequate assessment for identifying causes of distresses before carrying out maintenance and rehabilitation. A pavement distress that occurs at the surface can have a number of different causes which must be properly identified before corrective action is taken. Proper maintenance is very essential for longer life of the road surface.

Published by: vikaspatanker

Authors: Jay-An T. Biscocho, Keanne R. Noval, Lebron F. Calunsag, Nathalie G. Tangonan

Abstract: The objective of this study is to develop an automated surface vehicle prototype called AQuaRIUSV (Aquatic Quality Real-Time Information Using Surface Vehicle) designed to monitor water quality in marine ecosystems. The sensor being utilized by the prototype consists of pH, turbidity, and TDS sensors measuring key water quality parameters in real time. The system consists of a pH, turbidity, and TDS sensor; an Arduino Uno R4 Wi-Fi microcontroller for data processing and control; a Neo-6M GPS module for location tracking; an L298N motor driver operating dual DC motors for movement; SG90 micro servo motors for steering; and an ultrasonic sensor for obstacle detection. Monitoring was enabled by Blynk through an IoT dashboard. Performance was evaluated for accuracy, consistency, and reliability. Results show effective real-time monitoring via the IoT platform. The study concludes that AQuaRIUSV is a reliable, efficient, and sustainable system for continuous marine water quality monitoring.

DOI: http://doi.org/10.5281/zenodo.18627861

Published by: vikaspatanker