Volume 14 | Issue 4 |

 Abstract

Chandigarh, a Union Territory designated as a model city has consistently demonstrated competence in urban sanitation and solid waste management (SWM). This research assesses its SWM performance using Swachh Survekshan (SS) ranks and ratings from 2016 to 2024-25. Using secondary data from official MoHUA reports, city report cards and the District Environment Plan 2026, the research identifies strengths in waste processing (100% score), dumpsite restoration, door-to-door pickup (93%) as well as recurring shortcomings in source segregation (14%).The report builds on historical trends, evaluates literature on SS and SWM in India. The Chandigarh approach provides essential insights for long-term urban waste management under the Swachh Bharat Mission 2.0.

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 Keywords

Solid waste management, Swachh Survekshan rankings, Chandigarh Municipal Corporation, source segregation at source, door-to-door waste collection, waste processing capacity

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--Long waiting times and overcrowded outpatient departments are problems that almost every hospital deals with. The traditional methods--paper tokens, fixed appointment slots--simply do not work well when patient volumes keep changing throughout the day. In this paper, we present CareBridge AI, a queue optimization system that uses machine learning to make hospital queues smarter. The system has three ML models working together: one that predicts whether a patient will actually show up for their appointment (binary classification using XGBoost), one that estimates how long an ER patient will have to wait (regression using Gradient Boosting), and one that classifies patients into triage priority levels (multiclass Random Forest). All three models are trained on publicly available healthcare datasets and go through a standardized preprocessing pipeline. Their outputs are combined into a single Queue Priority Score that reorders the queue in real time. In our experiments, the no-show model achieved an AUC-ROC of 0.81, the wait-time model got an RMSE of 12.4 minutes, and the triage classifier reached a weighted F1 score of 0.88. When compared against a basic first-come-first-served system, CareBridge AI showed a projected 35-42% reduction in average waiting time. These results show that combining multiple focused ML models through a unified scoring formula is a practical way to improve how hospitals manage patient flow.

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 Keywords

Hospital queue optimization, machine learning, patient no-show prediction, triage classification, wait-time estimation, XGBoost, healthcare informatics

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The primary aim of the paper is to find the impact of the lit fests on the reading public in the city. The various socio-cultural, eco-political implications of the literature festivals are studied. How the city of Nagpur is upcoming with these lit fests organised as a factor for literary tourism; how intellectual stimulation and brainstorming is inculcating a socio-cultural ethos in the city with these lit fests. Acting as a pilot study it definitely has the potential to reach beyond the confines of a city broadening the spectrum to national levels. This paper assumes a notable proportion in the overall scheme of things going beyond the confines of conventional research as the study is impacting the socio, cultural, economic, political, psychological as well the literary aspects targeting the reading culture inculcated in the 21st century.

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 Keywords

Evolution of Lit Fest, Festivalisation of Culture, Nagpur, Literary tourism, Trans literary Space.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Design and Fabrication of a Smart Wheel Chair aim to develop an intelligent mobility system that assists physically challenged and elderly users in moving independently with minimal effort. The mechanical structure is designed using lightweight and strong materials to ensure stability, durability, and user comfort. Control inputs such as a joystick and voice-based commands allow easy operation, while the sensor system continuously monitors the surrounding environment and prevents collisions, thereby improving safety during movement. The fabrication process involves mechanical assembly of the wheelchair frame, installation of motors and wheels, and interfacing of electronic components with embedded software. The control program regulates speed, direction, and obstacle avoidance to provide smooth and reliable navigation. Testing results indicate that the smart wheelchair operates effectively in indoor environments and reduces physical strain on users. The proposed system is cost-effective, user-friendly, and adaptable, making it suitable for hospitals, rehabilitation centres and personal mobility applications, with scope for future upgrades such as IoT connectivity and health monitoring.

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 Keywords

Smart Wheelchair, IOT, joy stick, Embedded Systems, DC Motor, Obstacle Detection, Assistive Technology, Arduino Microcontroller, Automation, Sensor-Based Control .

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Creative Commons Attribution 4.0 and The Open Definition

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Young adults are increasingly delegating written communication to artificial intelligence tools, yet the psychological consequences of this habit have received limited empirical attention. This study tested whether habitual AI-assisted communication dependency erodes expressive cognitive confidence, which refers to an individual's belief in their capacity to think, formulate, and express ideas without assistance, and whether that erosion elevates communication apprehension. A theoretically grounded mediation model, termed the Crutch Effect, was tested using a quantitative cross-sectional correlational design with 105 young adults aged 18 to 35 years (Female n = 60, 57.1%; Male n = 44, 41.9%; M = 25.7 years, SD = 4.9) recruited through an online survey in urban India. Three validated instruments were administered: an adapted AI Communication Dependency Scale (AI-CDS; ? = .936), the General Self-Efficacy Scale (GSE; Schwarzer and Jerusalem, 1995; ? = .884), and the Personal Report of Communication Apprehension (PRCA-24; McCroskey, 1982; ? = .964). All four hypotheses were supported. AI dependency correlated negatively with self-efficacy (r = .257, p = .008) and positively with communication apprehension (r = .427, p < .001); self-efficacy correlated negatively with apprehension (r = .442, p < .001). Self-efficacy significantly mediated the dependency-apprehension relationship, confirming the Crutch Effect (indirect B = 0.211, 95% CI [0.020, 0.443], p = .022), accounting for 21.4% of the total effect. Participants using AI for more than three hours daily reported apprehension scores above the high-apprehension threshold (M = 81.6, SD = 23.08). These findings offer early empirical evidence for a mediated pathway from AI communication dependency through eroded self-efficacy to elevated communication apprehension.

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 Keywords

AI communication dependency, expressive cognitive confidence, communication apprehension, Crutch Effect, self-efficacy, cognitive offloading, young adults

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The widespread circulation of counterfeit pharma-ceutical products poses a critical threat to public health, patient safety, and the integrity of medicine supply chains worldwide. Sophisticated counterfeit products are visually indistinguishable from genuine medicines, as illustrated in Fig. 1, making manual verification by consumers and pharmacists practically infeasible at scale. Existing verification methods that rely on manual packaging inspection or trust-based purchasing are inherently unreliable and inadequate to detect modern counterfeiting techniques. This paper presents a comprehensive Fake Medicine Detection System leveraging QR code technology, integrating role-based access control, real-time UUID-based verification, and intelligent administrative analytics within a unified web platform. The proposed architecture comprises three functional modules: a Mobile Application Frontend enabling QR code scanning and verification; a Backend Processing System executing QR validation, authentication logic, and the Fake Detection Algorithm; and an Admin Dashboard providing monitoring, reporting, and counterfeit trend analysis. A centralized Identity and Access Management (IAM) layer enforces Role-Based Access Control (RBAC) across consumer and administrator roles. Each medicine batch is assigned a Universally Unique Identifier (UUID) upon registration, encoded into a cryptographically secured QR code, and stored in a centralized database. Upon scanning, the system performs real-time UUID validation through a secure Verification API and returns an immediate authenticity verdict-- Genuine or Fake--with full batch metadata. Training and validation accuracy curves confirm stable model convergence, and confusion matrix analysis validates balanced classification without systematic class bias. Evaluation on 500 simulated scan events demonstrates 99.2% overall verification accuracy with 106 ms average end-to-end latency, demonstrating the efficacy of the proposed platform for pharmaceutical safety.

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 Keywords

Fake Medicine Detection, QR Code, Drug Authentication, Pharmaceutical Safety, Role-Based Access Control, UUID Verification, Flask, SQLite, Counterfeit Detection, Real-Time Verification, Supply Chain Security, Mobile Application

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract The ecosystems of cities place wildlife at risk of a combination of anthropogenic stressors, where artificial night-time light (ALAN) and man-made noise are two examples of chemically mediated pollutants that have quantifiable biochemical effects on fauna. In this paper, we will discuss, in a chemistry way the science behind how light and noise pollution dysregulate endocrine signalling, favor oxidative stress and inhibit immune competence in urban wildlife. Light pollution interferes with the synthesis of melatonin by the pineal gland involving the action of N-acetyltransferase, phase-shifts the expression of circadian clock genes (BMAL1, CLOCK, Per2, Cry1) and increases reactive oxygen species (ROS) by mitochondrial uncoupling. The chronic effect of noise pollution is the activation of the hypothalamic-pituitary-adrenal (HPA) axis, which increases the levels of glucocorticoids and inhibits the pulsatility of the gonadotropin-releasing hormone (GnRH) and stimulates lipid peroxidation. Symbiotic environmental pollutants, such as polycyclic aromatic hydrocarbons (PAHs), volatile organic compounds (VOCs) and nitrogen oxides (NOx) amplify these biochemical insults by stimulating the cytochrome P450 enzymes and producing the actions of secondary oxidative intermediates. An overview of published biochemical and Eco physiological evidence in avian, amphibian, and mammalian taxa has shown convergent evidence of hormonal perturbation and genotoxic stress. The results of this study demonstrate that incorporating environmental chemistry within urban wildlife management is critical, and such biomarkers as urinary 8-hydroxy-2'-deoxyguanosine (8-OHdG) in a 2-hydroxydeoxyuridine (H2O) form, plasma malondialdehyde (MDA), and faecal corticosterone metabolites are logical as routine surveillance tools of urban wildlife health.

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 Keywords

Keywords: Melatonin, Cortisol, Circadian Disruption, Oxidative stress, HPA Axis,

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Creative Commons Attribution 4.0 and The Open Definition

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The rapid proliferation of Unified Payments Interface (UPI) transactions in India has been accompanied by a significant rise in digital payment fraud, exposing millions of users to financial risk. Existing fraud prevention mechanisms are predominantly reactive, triggering only after transaction authorization, thereby failing to prevent losses in real time. This paper presents an AI-based real-time UPI fraud detection system that operates as a proactive pre-authorization security layer, intercepting transactions between the amount entry and PIN authentication stages. The proposed system employs a

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

UPI Fraud Detection, Real-Time Payment Security, XGBoost, Isolation Forest, Anomaly Detection, Explainable AI, Feature Engineering, Pre-Authorization Security, Digital Payments, Machine Learning

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Creative Commons Attribution 4.0 and The Open Definition

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The rapid growth of electric vehicles (EVs) has increased the need for an efficient and reliable Battery Management System (BMS) to ensure safe battery operation. The lithium-ion battery used in EVs is highly sensitive to variations in voltage, current, and temperature. Improper monitoring of these parameters can lead to reduced battery life, performance degradation, or safety hazards. This project presents the design and implementation of an Electric Vehicle Battery Backup System integrated with essential components such as a lithium-ion battery pack, BMS, voltage sensor, current sensor, and temperature sensor for accurate real- time monitoring and protection. The proposed system uses a lithium-ion battery as the primary energy storage source due to its high energy density, lightweight structure, and long cycle life. A dedicated BMS is employed to continuously monitor battery parameters and maintain safe operating limits. The voltage sensor measures the battery voltage to prevent overcharging and deep discharge conditions. The current sensor tracks charging and discharging currents to avoid overload and short-circuit faults. Additionally, a temperature sensor monitors battery temperature to detect overheating and ensure thermal safety. A microcontroller-based control unit processes the data collected from these sensors and makes intelligent decisions for power management and protection. When abnormal conditions such as overvoltage, undervoltage, overcurrent, or excessive temperature are detected, the system automatically activates protective mechanisms. These include disconnecting the load, stopping the charging process, or limiting current flow to prevent battery damage. The developed prototype is cost-effective, compact, and suitable for electric two-wheelers and small EV applications. By integrating voltage, current, and temperature sensing within the BMS framework, the system significantly improves battery safety, operational, and lifespan. This project contributes to enhancing EV reliability while promoting sustainable and energy-efficient transportation solutions.

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 Keywords

Battery Management System (BMS), Lithium-ion Battery, Voltage Sensor, , Temperature Sensor, Battery Protection Real-time Monitoring, Arduino Nano, Thing Speak , SolidWorks.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

There are many studies about internet use and internet and social media addiction and it is one of the thing that influence our daily life. The usage of internet and social media is very common in this generation. The study is aimed to understand the main purpose of usage of social media and understand the positive and negative opinion and negative effects of over utilization of internet and social media. Data were collected through in depth interviews from 25 students who are using internet and social media. Thematic analysis revealed that the factors that makes person to addict were fashion, publicity, curiosity, technology, and physical and mental health problems were eyesight, obesity, social phobia, depression, and time management. Various awareness programs, individual realization and informational support can help to reduce the addiction and usage of internet and social media. These findings have important applications in formulating appropriate preventive strategies and actions in the future. Key words: internet, social media, addiction, fashion, publicity, mental and physical health problems.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Internet, social media, addiction, fashion, publicity, mental and physical health problems.

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Creative Commons Attribution 4.0 and The Open Definition