Corrosion Management, ISSN:1355-5243 is an international, interdisciplinary, open-access, peer-reviewed journal that publishes original research and review articles on the interface between Chemistry and Management and Social Sciences. The journal focuses on the exploration of the neural mechanisms underlying consciousness, cognition, perception, and behavior from a quantum perspective. Corrosion Management is published half-yearly. A journal of the Institute of Corrosion Corrosion Management aims to promote scientific dialogue and collaboration among researchers, practitioners, and scholars in the fields of Chemistry and Management and Social Sciences, psychology, philosophy, and related disciplines. The journal welcomes empirical, theoretical, and methodological contributions that enhance our understanding of the mind-brain relationship and the fundamental principles of quantum mechanics that apply to the study of cognition and behavior. Some of the key topics covered in Corrosion Management include quantum information processing in the brain, quantum coherence and entanglement in neural networks, quantum-inspired models of brain function, quantum-inspired models of perception and decision making, quantum consciousness, and the philosophical and ethical implications of quantum approaches . Corrosion Management is committed to providing high-quality, rigorous, and timely peer review and publication services to authors worldwide. The journal operates on a continuous publishing model, with accepted articles Peer Review Corrosion Management has a blind review process. All manuscripts submitted to Corrosion Management are circulated to two field referees after initial screening process. If the referee's report contradict one another, a further expert opinion will be sought. Throughout the review process, all submissions satisfying the basic requirements will be subject to a blind review by at least two independent reviewers who will not have knowledge of the name of the author or of other reviewers. Likewise, the Corrosion Management does not inform the author(s) about the reviewers in any phase of the review process. If the number of the manuscripts that were credited as publishable by the reviewers were higher than the number of the articles that prescribed by the Corrosion Management’s publication policy, the editorial board of the Corrosion Management makes the final acceptance decision. The editors reserve the right to modify typescripts to eliminate ambiguity and repetition, and to improve communication between author and reader. In following this practice, the scientific content and message will not be changed. If extensive alterations are required, the manuscript will be returned to the author for revision and/or approval. Manuscripts will be subjected to peer review process to determine their suitability for publication provided they fulfill the requirements of the journal as laid out in the instructions to authors. After the review, manuscripts will be returned for revision along with reviewer’s and/or editor’s comments. Prepare the manuscript in Times New Roman font using a font size of 12. There shall not be any decorative borders anywhere in the text including the title page. All the tables and figures should be in the text at suitable place. Submission of a manuscript to Journal for publication implies that the same work has not been either published or under consideration for publication in another Journal. Authors, in their cover note to the Editor, have to clearly mention field/stream of review article. Should be about 18 pages long, contain up-to-date information, comprehensively cover relevant literature and preferably be written by scientists who have in-depth knowledge on the topic. 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References cited only in tables or figure legends should be numbered in accordance with the sequence established by the first identification in the text of the particular table or figure. Use the style of the examples below. Use complete name of the journal for non-indexed journals. Avoid using abstracts as references. Information from manuscripts submitted but not accepted should be cited in the text as “unpublished observations” with written permission from the source. Avoid citing a “personal communication” unless it provides essential information not available from a public source, in which case the name of the person and date of communication should be cited in parentheses in the text. For scientific articles, contributors should obtain written permission and confirmation of accuracy from the source of a personal communication. Note: Publication from 1990 to 2018 is available on our official website: http://icorr.org/ Submit Research paper on : irjeditor@gmail.com Publisher:Square One Advertising and Design Limited
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SPATIAL BLUEPRINTING OF PLAY INFRASTRUCTURE: OPTIMIZING RESOURCES AND SUSTAINABLE CONSTRUCTION METHODOLOGIES
Modern urban development increasingly seeks outdoor spaces that harmonize aesthetic appeal with ecological sustainability. This paper presents a multi-disciplinary approach to the design and construction of a sustainable amusement park. The research focuses on minimizing natural resource depletion through the integration of Green Building principles and cost-effective engineering strategies. The technical workflow includes site-condition analysis, soil strength assessment, and high-precision surveying via Total Station. The proposed design was developed using AutoCAD, Revit, and Lumion to ensure structural efficiency and environmental compatibility. The findings demonstrate that sustainable design can mitigate the negative environmental footprints of large-scale recreational projects.
Copyright (c) 2024 Corrosion Management ISSN:1355-5243 Scopus https://corrosion-management.com/
ENHANCING CLOUD RESOURCE ALLOCATION WITH VISION TRANSFORMER, DEEP REINFORCEMENT LEARNING, AND IMPROVED SHRIKE OPTIMIZATION ALGORITHM
Cloud computing relies on efficient resource management to deliver scalable, on-demand services while minimizing costs, energy consumption, and response delays in Infrastructure as a Service (IaaS) environments. Traditional approaches often struggle with dynamic workloads, leading to resource underutilization, high migration overheads, and suboptimal Quality of Service (QoS). This paper introduces a novel hybrid framework that synergistically combines Vision Transformer (ViT) for adaptive load pattern recognition and balancing, Deep Reinforcement Learning (DRL) integrated with an Enhanced Shrike Optimization Algorithm (ESOA) for intelligent resource allocation, and Twin Fold Moth Flame Optimization (TFMFO) for cost-effective virtual machine (VM) migration. The ESOA improves upon the standard Shrike Optimization Algorithm by incorporating adaptive pheromone evaporation, Lévy flights for better global exploration, and stagnation detection to escape local optima, enabling faster convergence and superior handling of multimodal optimization problems typical in cloud scenarios. Extensive simulations using CloudSim with heterogeneous workloads (100–500 tasks) demonstrate significant performance gains: makespan reduced to 770 ms (26–36% improvement), average response time to 280 ms, energy consumption to 6160 J (30–35% savings), operational cost to $9.1, and throughput increased to 119 tasks/sec (20–25% higher) compared to state-of-the-art methods such as DRL-based placement, dual-threshold MBFD, multi-objective RL for edge, and VMP-ER. The proposed framework offers a robust, sustainable solution for modern cloud data centers, advancing efficient load balancing, resource utilization, and energy-aware operations.
Copyright (c) 2026 Corrosion Management ISSN:1355-5243 Scopus https://corrosion-management.com/
Assessment of Livelihood Vulnerability and Adoption of Climate Smart Agriculture among the Farmers in Ghaziabad, Uttar Pradesh
Climate change is posing serious risks for human beings and the environment, and it is affecting agriculture and food security around the world. Food security will be impacted by changes in the climate and agricultural production systems, but farmers will bear the burden of these changes first. For most of the years, Uttar Pradesh’s agricultural growth has continuously lagged behind the national average. From 2005–06 to 2018–19, the agricultural growth rate increased by 3.0% annually (at constant prices of 2011-12). The paper examined the livelihood vulnerability among the farmers and adoption of climate-smart agriculture. The study is based on a primary survey conducted in Ghaziabad district’s four blocks, i.e., Bhojpur, Rajapur, Loni and Murad Nagar. There were 100 responses collected from each block, and a total of 400 responses were collected from the study area. The data has been analyzed using techniques such as the Livelihood Vulnerability Index (LVI), which is a balanced weighted average approach, indexing based on UNDP, and climate-wise agriculture practices based on composite score. The study also used multiple linear regression and the ordered logistic regression model. The areas of Loni and Muradnagar are the most vulnerable, have the least potential for adaptation, and are most exposed to socio-environmental stresses. More people are using cost-effective techniques like mulching and composting. The results imply that adoption of CSA practices is significantly influenced by economic viability.
Copyright (c) 2025 Corrosion Management ISSN:1355-5243 https://corrosion-management.com/
SYNTHESIS AND UTILIZING NANOPOROUS MATERIAL FROM PARTIALLY LATERISED KHONDALITE ROCK FOR CORROSION STUDIES
Partially Laterised Khondalite (PLK) rocks are a bauxite mining waste generated during the mining of the bauxite for the production of alumina. This waste can be transformed into a nanoporous material after a suitable physical beneficiation followed by a chemical activation process. In this paper, the nanoporous material was synthesized from the partially laterised khondalite (PLK) rocks, which was applied to a mild steel in the medium of hydrochloric acid of one molar (1 M) concentration. The characterisation study has been carried out on the raw material and the nanoporous material. The characterisation study included XRD, FTIR, SEM, TEM, BET. It was observed that the structural transformation occurs with an increase in surface area from 8.4 m²/g to 162.7 m²/g. The different experiments were carried out to reveal that the material acts as an efficient corrosion inhibitor by using electrochemical impedance spectroscopy (EIS), potentiodynamic polarization, and weight-loss experiments. It is found that the maximum inhibition efficiency of 92.5% achieved after dipping in the sea water for 72 hours. The resulting material improves performance and environmental impact while providing a more economical and sustainable option for creating anticorrosive coatings.
The Role of Forensic Accounting in Fraud Detection and Prevention
This paper examines the role of forensic accounting in the detection and prevention of fraud within contemporary organisational environments. Drawing on secondary data from peer-reviewed studies published since 2015, the study analyses how forensic accounting extends beyond traditional auditing by integrating investigative techniques, legal awareness and advanced data analytics. The review highlights that forensic accounting significantly enhances the identification of complex and concealed fraud schemes, particularly those involving management override, collusion and digital transactions. The findings further indicate that forensic accounting contributes to fraud prevention by supporting stronger internal controls, improving governance practices and creating deterrence effects through increased detection likelihood. The study also discusses the influence of technological innovation, professional competence and institutional support on the effectiveness of forensic accounting practices. While acknowledging challenges such as cost constraints and skill gaps, the paper underscores the growing strategic importance of forensic accounting as an integral component of modern fraud risk management frameworks.
ASSESSMENT OF PROTECTIVE COATINGS FOR CORROSION PREVENTION OF CARBON STEEL IN HIGH-CONCENTRATION SULFURIC ACID ENVIRONMENTS
This study evaluates the performance of three advanced protective coatings—Belzona 4341, Carboline Plasite 4550, and DuraPol UHT—on carbon steel subjected to the aggressive conditions of 98% sulfuric acid. The primary objective is to determine the effectiveness of these coatings in preventing corrosion and extending the lifespan of carbon steel in highly corrosive environments.To achieve this, a series of tests were conducted to assess key performance indicators, including adhesion strength, chemical resistance, hardness retention, and weight loss over time. Adhesion strength was measured to evaluate how well each coating bonded to the carbon steel substrate, which is critical for maintaining protective properties under corrosive conditions. Chemical resistance tests were performed to determine the coatings' ability to withstand the harsh effects of concentrated sulfuric acid, while hardness retention assessments provided insights into the coatings' durability and resistance to mechanical wear. Weight loss measurements were taken to quantify the extent of corrosion that occurred over the testing period.The results of the study revealed that Belzona 4341 outperformed the other coatings in all evaluated parameters, demonstrating superior adhesion strength and exceptional chemical resistance. Additionally, it exhibited minimal weight loss, indicating its effectiveness in preventing corrosion. Carboline Plasite 4550 and DuraPol UHT showed varying degrees of performance, but neither matched the overall effectiveness of Belzona 4341.These findings underscore the importance of selecting appropriate protective coatings for carbon steel in industrial applications, particularly in environments characterized by high acidity. By identifying Belzona 4341 as the most effective solution, this research provides valuable insights for industries seeking to enhance the longevity and reliability of their materials in corrosive settings. The study aims to inform future strategies for corrosion prevention and material selection, ultimately contributing to improved operational efficiency and reduced maintenance costs in industrial applications.
OPTIMIZATION OF PROCESS PARAMETERS TO ENHANCE INHIBITION EFFICIENCY IN CORROSION PREVENTION THROUGH SIO2 COATING
This study thoroughly investigates the inhibition of corrosion efficiency using silica sand (SiO2), specifically tailored for coating applications in aerospace, marine, and industrial sectors. The primary objective was to enhance corrosion efficiency beyond 90%, making it suitable for various industrial applications. To further ensure the reliability of this result, the Box-Behnken statistical design, implemented in Minitab, was used to optimize and refine the process parameters to improve corrosion efficiency. Various influencing factors, such as particle size, concentration, and pH, were systematically analyzed to determine their impact on corrosion resistance. Experimental validation confirmed that silica sand (SiO2), coatings significantly enhance durability and performance under harsh environmental conditions. This research provides a foundation for developing advanced protective coatings with enhanced longevity, contributing to cost-effective and sustainable corrosion prevention solutions across multiple industries.
NANO-ZIRCONIA COMPOSITE COATINGS AS EFFECTIVE BARRIERS FOR CORROSION MITIGATION
This work examines the corrosion resistance of nano zircon or zirconia-silica (ZrO₂-SiO₂) composite coatings on metal surfaces opened to corrosive ambient, comprised of acids, salts, and moisture. Looking at the traditional coatings, nano-scale composites upgrade reliability via augmenting hardness, wear resistance, and adhesion aspects. The synthesized zircon, provide greater cleanliness and steadiness over natural zircon, bring forth remarkable benefits toward industrial usages like aerospace and automotive sectors, diminishing maintenance costs and expanding service span. The ZrO₂-SiO₂ composite was artificially produced by extracting nano ZrO₂ out of zircon concentrate and mixing it with fumed SiO₂ in a 1:1 molar ratio, subsequently calcination at temperatures ranging 1000°C to 1400°C. X-ray diffraction (XRD) study established the configuration of monoclinic ZrO₂ and tetragonal ZrSiO₄, with finest crystallinity at 1400°C. Scanning Electron Microscopy (SEM) exposed a dense, regular, and crack-free coating with tough adhesion. The corrosion rate of mild steel coated with ZrO₂-SiO₂ composite is 0.001mm/year in sea water and .004mm/yr in 0.1M H2SO4solution. The results emphasize the prospective of ZrO₂-SiO₂ coatings as a useful resolution for corrosion defence in considerate manufacturing atmospheres.
LIGHTWEIGHT MACHINE LEARNING FOR RAPID AND ACCURATE CORROSION DETECTION
The deterioration of metallic structures due to corrosion presents substantial economic and safety concerns, contributing to nearly 4% of the global GDP. Despite the promise of machine learning in corrosion detection, progress is hindered by the scarcity of standardized datasets. In this research, the ARL-WPI corrosion dataset has been utilized to refine multi-label classification models through computationally efficient feature extraction and optimized machine learning techniques. However, Colour descriptors such as mean and standard deviation of Red, Green, and Blue (RGB) and Hue, Saturation, and Value (HSV) channels have been extracted for enhanced illumination invariance, along with texture-based attributes Histogram of Oriented Gradients (HOG), Local Binary Pattern (LBP), and Gray Level Co-occurrence Matrix (GLCM) to encapsulate structural patterns and wavelet-derived features (DWT) for multiresolution frequency analysis. Additionally, Principal Component Analysis (PCA) has been applied to preserve 99% of the variance while significantly reducing computational overhead. The optimization of machine learning models, particularly K-Nearest Neighbour(KNN) with 98.6% accuracy and 28.27s execution time and ensemble methods with 97.2% accuracy and 67.24s execution time has demonstrated superior performance over deep learning frameworks, which exhibit higher computational demands. The findings underscore the efficacy of lightweight classifiers with domain-specific feature representations in expediting corrosion assessment. This study fosters a robust synergy between AI-driven material diagnostics and industrial applications, offering a scalable, high-precision, and computationally viable approach for real-world corrosion monitoring.
Copyright (c) 2025 Corrosion Management ISSN:1355-5243 Scopus https://corrosion-management.com/
NEXT-GEN CORROSION ANALYTICS: INTELLIGENT FORECASTING FOR OIL PIPELINE INTEGRITY
Effective monitoring and precise forecasting of internal CO₂ corrosion are paramount for safeguarding the structural integrity of oil pipelines. This research employs an array of advanced machine learning and deep learning methodologies to predict corrosion progression, leveraging a comprehensive dataset encapsulating critical environmental and operational factors. Various regression techniques, including Support Vector Regression (SVR), Decision Trees, Random Forest, K-Nearest Neighbours (KNN), and Polynomial Regression, were meticulously evaluated. Among linear models, the Random Forest Regressor exhibited superior predictive accuracy with an R² of 0.9936 and an MSE of 0.0080. Notably, third-degree polynomial regression emerged as the most effective nonlinear approach (R² = 0.9988). Regularized regression models underscored Ridge Regression as the optimal choice, achieving an R² of 0.9989. Within deep learning paradigms, the Feed-Forward Neural Network (FNN) and ResNet models demonstrated remarkable efficacy, attaining a R² score of 0.9928. Furthermore, ensemble learning, particularly a hybridized CNN-CNN Forecaster model, exhibited commendable predictive precision. The study emphasizes the necessity of model selection for accurate corrosion forecasting and facilitating proactive maintenance.
CORROSION DETECTION IN CONCRETE USING PHASE-BASED SPEECH ENHANCEMENT AND RECOGNITION TECHNIQUES WITH AI FRAMEWORK
Automatic Speech Recognition (ASR) is one of the oldest signal processing techniques which deals with detecting different types of speech including spoken words, emotions, disease, speaker identity, languages, music, and noise levels. Recently, these standard ASR methods have been adopted into the fields of acoustics, bioinformatics, wildlife, and environmental audio detection. One of the upcoming applications of ASR is in civil engineering which deals with the hammer sound test. This test is one of the non-destructive tests which is performed to detect the concrete quality and surface defects. This research problem has been taken in this paper and investigated with various phase-based audio and statistical features along with speech enhancement techniques to reduce unwanted noises. Phase of the audio signal plays a crucial role in extracting relevant audio information which is less explored in the audio signal processing. The proposed phase-based method has been tested with standard hammer sound datasets and other environmental sound datasets. It has been observed from the analysis of the simulated results that the proposed method has been demonstrating superior performance.
Fuzzy Logic-Based Robustness Assessment of Complex Engineering Systems: Methodologies, Case Studies, and Comparative Analysis
Robustness assessment of engineering systems under uncertainty is a critical factor for ensuring operational reliability and minimizing costly downtime. Traditional probabilistic methods often fall short in addressing the vagueness and ambiguity inherent in real-world data and expert judgments. This study presents an in-depth application of fuzzy logic approaches—including Fuzzy Fault Tree Analysis (FFTA), Fuzzy Reliability Block Diagrams (FRBD), and Fuzzy Bayesian Networks (FBN)—to model and evaluate the robustness of complex engineering systems. Detailed case studies on an automated manufacturing plant and a power distribution system demonstrate how fuzzy models effectively capture uncertainty through membership functions and fuzzy arithmetic, providing a richer reliability assessment than classical methods. Sensitivity analyses identify the most influential parameters affecting system robustness, guiding targeted maintenance and risk mitigation. A comparative evaluation of the fuzzy methods highlights their respective strengths and limitations, informing model selection based on application requirements. The results underscore fuzzy logic’s potential to enhance fault diagnosis, maintenance prioritization, and decision-making under uncertainty. Finally, future research directions emphasize real-time fuzzy monitoring and hybrid AI integration to meet the demands of increasingly complex and interconnected systems.
Legal Responses to Pipeline Bombings and Sabotage as Tools of Domestic Terrorism in Nigeria
Pipeline bombings and sabotage have become prominent forms of domestic terrorism in Nigeria, threatening national security, economic stability, and public safety. This paper examines Nigeria's legal frameworks and judicial responses to pipeline attacks, especially in the Niger Delta region, where insurgent groups and criminal gangs have systematically targeted oil and gas infrastructure. The analysis reveals that while Nigeria has enacted comprehensive counterterrorism laws, significant challenges remain in effectively prosecuting offenders and preventing future attacks. The legal framework includes various statutes, such as the Terrorism Prevention Act, which designates infrastructure sabotage as terrorism, yet enforcement is hampered by weak mechanisms, corruption, and socioeconomic factors underlying the violence. The paper evaluates how courts have interpreted and applied terrorism laws in pipeline sabotage cases and explores the intersection of counterterrorism measures with human rights protections, noting concerns about potential abuses during security operations. The study concludes that Nigeria's legal response, although theoretically robust, requires improvements through enhanced investigative capacity, witness protection, specialized terrorism courts, and addressing root causes like resource conflicts, poverty, and governance issues. Effective strategies should balance punitive legal actions with conflict resolution, community involvement, and equitable resource sharing. This research contributes to understanding how developing nations handle the complex legal challenges of combating domestic terrorism while safeguarding the rule of law and fundamental rights in resource-rich, conflict-affected areas.
Tobiloba AWOTOYE(PhD) Femi Adeoye Alabi (PhD) Dolapo Olutayo(PhD)
An Application of Erikson’s Psychosocial Theory to Anita Desai’s Voices in the City
This paper employs the psychologist Erik Erikson’s psychosocial theory of development, the theoretical framework that represents the psychosocial dimensions of alienation in Anita Desai’s novel Voices in the City are examined. The study analyses resolved undevelopmental problems, related to identity and intimacy, resulting in existential disconnection, emotional isolation, and a fractured sense of self while focusing on the psychological paths of the main characters-Nirode, Monisha, and Amla. Desai’s portrayal of contemporary urban life in post-independence India serves as a crucial background for these psychological conflicts. This paper demonstrates how Desai’s characters represent the psychosocial consequences of alienation by applying Erikson’s stages of Identity vs. Role Confusion and Intimacy vs. Isolation. In addition to providing a deeper understanding of Desai's narrative technique, this interdisciplinary approach reveals the psychological theories enduring significance in literary analysis.
Pardeep kaur and Asst. Prof. Dr. Kanchan Sharma
MAPPING THE LANDSCAPE OF INDIVIDUAL-LEVEL POVERTY ANALYSIS (2012–2025): A SCIENTOMETRIC STUDY
The individual-level poverty analysis is a significant step forward in poverty assessment, highlighting intra-household differences that are often overlooked by traditional household-based measurements. This scientometric study examines the intellectual and collaborative landscape of individual poverty research. This scientometric study uses data from the Scopus database to examine the organization and development of research on individual-level poverty analysis from 2012 to 2025. The study analyzed 73 peer-reviewed papers to map publication trends, identify key authors, and track theme developments. The results show a growing interest in gender-sensitive and multifaceted responses to poverty, with notable international cooperation and thematic shifts toward the capabilities approach, time poverty, and empowerment. In addition to outlining potential research avenues, this work advances our knowledge of the development of individual-level poverty analysis.
"AN ANALYTICAL STUDY OF PATRIOTIC THEMES IN ADVERTISING ART"
This research investigates how patriotic elements are integrated into advertising art and how these elements—such as national symbols, historical imagery, and culturally rooted narratives—influence both consumer behaviour and brand interpretation. Drawing on a mixed-method research framework that blends content analysis, interviews, and survey findings, the study identifies the visual and emotional devices most commonly used to evoke national pride. The results reveal clear generational differences: older audiences tend to interpret patriotic advertisements with warmth and trust, whereas younger individuals are more cautious and often question the sincerity behind such messages. Although patriotic themes can reinforce loyalty and enhance brand credibility—particularly around national celebrations—the study also highlights concerns about the ethical implications of commercialising patriotic sentiment. Overall, the research guides advertisers seeking to employ patriotic themes with authenticity and cultural sensitivity to ensure positive and lasting consumer relationships.
Copyright (c) 2024 Corrosion Management ISSN:1355-5243 https://corrosion-management.com/
Assessment of Drinking Water Quality level in Narnaul, City of Haryana
Human existence depends on water accessibility, as well as quantity and quality. Over 50% of water is wasted in the home, agricultural, and industrial sectors as a result of extensive water extraction for these uses. A large portion of the accessible water is becoming unfit to drink due to water contamination. Surface water is the primary source of drinking water for most of Indians. The WQI, or Water Quality Index, calculates an individual value that measures the overall state of the water at a given location and time. The Indian Council of Medical Research (ICMR) and the Bureau of Indian Standards (BIS) provide a standardized method for computing the Water Quality Index, which is used in this work. The aim of this work, is to assess the Water Quality Index (WQI) of drinking water in the Narnaul city, which is based upon both primary and secondary data, The analyzed data is contrasted with the standard values that the ICMR and BIS recommend. Number of water quality parameters, including pH, total alkalinity, calcium, magnesium, chloride, sulfate, and nitrate, are taken into account in this work in order to compute the WQI. Additionally, the periodical, fluctuations of the Physicochemical characteristics of the quality of water Narnaul city are calculated. The results shows According to the WQI values, the east of the city had a higher percentage of drinking water in the excellent water quality category, while the south had neutral water quality.The water quality index (WQI) is different everywhere in the city . The lowest variation was in Sample4 (Rewari Rode bore-well) 15.144339, and the highest variation was in Sample10 (Nalapur bore-well) 222.7897. A more methodical approach, the WQI method makes it easier to compare the drinking water quality of multiple sampling locations.It is clearly visible from the view that only about 50% samples in the city have suitable quality for drinking water. It is very important to treat the remaining 50% sampling stations before use. The quality of water is poor in most parts of the study area.
NAVIGATING LIFE’S CHALLENGES: A JOURNEY TO INNER PEACE AND STRESS MANAGEMENT
Stress triggers a series of physiological and psychological responses that impact both the body and mind. When faced with a stressor, the body activates the fight-or-flight response, a primal survival mechanism designed to prepare for danger. During this response, the body releases stress hormones such as cortsisol and adrenaline, which increase heart rate, elevate blood pressure, and boost energy levels to facilitate quick action. While this response can be lifesaving in emergencies, chronic exposure to stress can have detrimental effects on physical and mental health. Prolonged activation of the stress response can weaken the immune system, disrupt sleep patterns, contribute to digestive issues, and increase the risk of developing anxiety, depression, and other mental health disorders.
Dr P Rajeswari, Dr. P. Sankara Rao, P. Saritha, And Dr S. Naresh kumar Goud
MARGARET ATWOOD’S SURFACING: FEMINISM AND SEXUAL POLITICS
Feminism and Gender inequality are not natural but embedded. They primarily explained Women who were confined to the patriarchal culture-defined roles. Girl-child social conditioning, gender discrimination, and self abnegation facilitate stereotyped roles. Feminism and Sexual Politics in general employed to describe political, social and economic movements. It seeks to give more rights and adequate protection to women. It does not have a single key definition in the context of the American radical feminist author Gloria Steinem , intellectual background is stressed. "The goal of feminism is to liberate the individuality of the person and understand that in every one of us there is a unique human being who is a mixture of heredity and environment."
Historical to Contemporary Urban Services in Narnaul City (1991–2022): A Spatial and Statistical Analysis Priyanka Yadav Dr. Salahuddin Mohd Urban services play a crucial role in determining the quality of life and sustainability of cities. Narnaul, a h
Urban services play a crucial role in determining the quality of life and sustainability of cities. Narnaul, a historic city in Haryana, has witnessed significant demographic and spatial changes since 1991. This paper analyzes the evolution of urban services in Narnaul from 1991 to 2022, combining secondary data with field-based household surveys. The study highlights disparities between the old core city, intermediate zones, and newly developed extensions. Services such as water supply, sanitation, drainage, solid waste management, health, housing, and transportation are examined through statistical comparisons and ward-level observations. Findings reveal that while new colonies enjoy better-planned infrastructure, service delivery remains irregular. Conversely, old wards face infrastructural stress and overcrowding, reflecting inadequate modernization. The analysis emphasizes the need for integrated and participatory urban planning to address spatial inequalities in service delivery.
Effects of Size, Shape, and Polarity of Components in the Binary Mixture of Ionic Liquid ([C₄mim][Cl]) and Cyclic Ether ((1,4-dioxane)) on Speed of Sound at Different Temperatures
The molecular size, shape, and polarity of ionic liquids (ILs) and cyclic ethers significantly influence the acoustic and thermodynamic properties of their binary mixtures. This study investigates the variation in the speed of sound in IL–cyclic ether binary mixtures as a function of temperature (298–328 K) and composition. The ionic liquid 1-butyl-3-methylimidazolium chloride ([C₄mim][Cl]) was mixed with the cyclic ether (1,4-dioxane). Speed of sound measurements were performed using an ultrasonic interferometer. Results demonstrate that structural parameters and dipole interactions affect compressibility and, consequently, the speed of sound. Stronger hydrogen bonding and denser packing led to higher values at lower temperatures, while temperature rise generally decreased sound velocity due to reduced interaction strength. The findings provide insights into molecular-scale interactions and their impact on bulk acoustic behavior.
Kuldeep Kumar Solanki, Dr Arpna, Dr Sunil Kumar Jangra, Sanju
MANAGEMENT STRATEGIES FOR DEALING WITH OCCUPATIONAL STRESS OF WORKING WOMEN OF DELHI-NCR
In this study, researchers attempted to determine which stress-reduction mechanisms were being used by the 300 respondents who said that they were employing various coping techniques provided by their separate businesses. In addition to organizational coping techniques, respondents were asked whether individual or personal coping strategies they utilized to handle stress. In the study, the researcher identified the stress management techniques provided by the firms chosen for the study. This information was obtained through casual interactions with management and certain organizational personnel, as well as from the literature given by the aforementioned organizations.
Multi-Material Shield Design for Nuclear Reactors: A Study on Chemical Composition and Functionality
The safe and efficient operation of nuclear reactors heavily relies on robust radiation shielding systems. This research investigates the formation and performance of nuclear reactor shields with varying chemical compositions to understand their role in attenuating different types of ionizing radiation. By analysing the interaction mechanisms between radiation particles (particularly neutrons and gamma rays) and shielding materials, this study highlights the importance of material selection based on atomic number, density, neutron cross-section, and thermal stability. Through comparative evaluation of traditional materials like lead, concrete, and borated polyethylene, alongside advanced composites and nanomaterials, the research demonstrates how tailored chemical formulations can significantly enhance shielding efficiency in both conventional and next-generation reactors. The findings offer insight into optimizing reactor design, enhancing safety standards, and guiding material innovation in nuclear shielding applications.
Perceived Influence of Psychological Wellbeing and Workplace Environment on Job Fruition among the Employees of Mountaintop University, Ogun State Nigeria
This study explores the perceived influence of psychological well-being and workplace environment on job fruition among employees of Mountaintop University, Ogun State, Nigeria. The research emphasizes the interconnectedness of job satisfaction, employee engagement, and the sense of meaningful work as central elements of job fruition. Psychological well-being, defined as the mental and emotional health of employees, and the workplace environment, including organizational support, job demands, and interpersonal relationships, are evaluated as key determinants of job satisfaction. Using a quantitative approach, the study employs a survey methodology, collecting data from a stratified random sample of university staff. Statistical analyses, including multiple regression and correlation analyses, reveal complex relationships between these variables, highlighting the role of psychological well-being and workplace environment in shaping job fruition. Findings suggest that while psychological well-being has a significant impact, workplace environment factors such as rewards and efforts require further scrutiny due to potential data anomalies. This research contributes to understanding how these factors collectively influence employee satisfaction, offering practical recommendations for enhancing organizational effectiveness and improving employee morale. The study underscores the importance of fostering a supportive workplace culture and promoting mental health initiatives to achieve optimal job fruition.
1.Aanuoluwapo Adekunle 2.Ojo Adeshina Akinwumi (PhD).
Federalism and Judiciary of India: An Analysis of Landmark Judgments
Indian federalism operates within a quasi-federal constitutional framework that balances unity with diversity. The Supreme Court of India has played a pivotal role in interpreting and reshaping this federal structure through landmark judgments. This study critically examines the evolving nature of Centre–State relations, focusing on key cases such as State of West Bengal v. Union of India, S.R. Bommai v. Union of India, and Government of NCT of Delhi v. Union of India. These judgments illustrate the judiciary’s shifting stance—from reinforcing central dominance to affirming the autonomy of states. The emergence of doctrines such as the Basic Structure and the emphasis on cooperative federalism reflect an ongoing negotiation between legal interpretation and political reality. The analysis highlights how the Supreme Court, through judicial review, functions as a vital mediator in India's federal structure, striving to maintain constitutional balance amid changing socio-political dynamics.
Influence of Sociocultural Values on Gender Role Expectation Among Youth in Ibadan Metropolis Oyo State Nigeria
This study explores the influence of traditional cultural practices on gender role expectations among youth in the Ibadan metropolis of Oyo State, Nigeria. Amidst growing global conversations on gender equity and evolving social norms, the research investigates how entrenched sociocultural beliefs shape youths’ perceptions of gender roles in a rapidly urbanizing Nigerian context. Adopting a descriptive survey design, a structured questionnaire was administered to 384 respondents aged 15–35, selected through Fisher’s formula for infinite population. The instrument measured engagement with traditional practices, and rigidity in gender role expectations. Findings from multiple regression analysis revealed that traditional practices significantly predicted rigid gender role expectations (β = .28, p < .001), while higher levels of education were associated with more egalitarian views (β = –.12, p < .001). Age and gender were not significant predictors. The full model accounted for 35% of the variance in gender role expectations (R² = .35, F = 30.27, p < .001). The results indicate that while traditional practices still exert considerable influence, education serves as a moderating force, promoting more flexible gender ideologies. The study concludes that addressing gender inequality in Nigerian society requires a dual approach: confronting rigid cultural norms while expanding educational access and content. Recommendations include integrating gender-sensitive curricula in schools, community engagement with cultural and religious leaders, and youth-led forums that encourage critical reflection on tradition and modernity.
(1). Arubuola Ayomipo Emmanuel (2). Adegboyega Temitayo Omolade
Employee Resistance to Change and Workplace Incivility as Predictors of Job Crafting Among Workers in Expand Global Industry
This study examines the influence of employee resistance to change and workplace incivility on job crafting among workers at Expand Global Industries Limited in Oyo State, Nigeria. Job crafting, defined as proactive modifications employees make to their tasks, relationships, or cognitive perceptions of work, is increasingly recognized as a vital strategy for enhancing job satisfaction, engagement, and performance. However, contextual factors such as resistance to change and workplace incivility may hinder employees' ability to engage in job crafting behaviors. Guided by the Job Demands-Resources (JD-R) Model, Social Exchange Theory, and Conservation of Resources (COR) Theory, this research employs a quantitative cross-sectional design with a sample of 353 workers selected via convenience sampling. Standardized instruments, including the Job Crafting Questionnaire, Workplace Incivility Scale, and Openness Toward Organizational Change Scale, were used to collect data. Pearson correlation, regression analysis, and independent t-tests were applied to analyze the data. The findings reveal that both employee resistance to change (β = -0.37, p < 0.01) and workplace incivility (β = -0.31, p < 0.01) significantly and negatively predict job crafting. Together, these factors account for 17.7% of the variance in job crafting behaviors (R² = 0.177, p < 0.001). No significant gender differences in job crafting were observed (t = -1.23, p > 0.05). The results align with theoretical frameworks, suggesting that resistance and incivility deplete psychological resources and disrupt social exchange relationships, thereby reducing proactive job adjustments. Recommendations include transparent communication during organizational changes, civility training programs, and leadership initiatives to empower employees. These interventions can enhance resilience, engagement, and organizational adaptability, particularly in dynamic and challenging work settings.
Handsworth Olayinka Sodimu and Ojo Adeshina Akinwumi (PhD).
Z-Score Normalized Machine Learning Approach for Predictive Maintenance Optimization in Gas Treatment Plants
The increasing global demand for cleaner energy has positioned natural gas as a vital resource, requiring gas treatment plants (GTPs) to operate efficiently and reliably. However, the harsh operational conditions of GTPs—characterized by high pressures, temperatures, and corrosive gases—expose critical equipment to frequent wear and tear, leading to unexpected failures and costly downtimes. Traditional maintenance strategies such as reactive and preventive maintenance have proven inadequate in addressing these challenges due to their reliance on failure occurrence and fixed service intervals, respectively. This study aimed to evaluate the performance of selected machine learning (ML) models—Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), and K-Nearest Neighbors (KNN)—for predictive maintenance using operational datasets processed through z-score normalization. Historical metering data obtained from Total Energies EP Nigeria Limited (2019–2024) was preprocessed to remove outliers, engineered to create predictive features, and scaled for uniformity. The models were assessed based on accuracy, precision, recall, and F1-score. Results revealed that all four models performed optimally after z-score normalization, with SVM achieving the highest and most consistent performance across all metrics. KNN also demonstrated robust results, particularly in adapting to different feature scaling methods. Based on these findings, the study concludes that SVM is the most effective model for predicting maintenance needs in GTPs. It is recommended that gas treatment facilities adopt SVM-based predictive maintenance systems to enhance reliability, reduce operational costs, and improve equipment lifespan.
Femi Adeoye Alabi1 Bamidele Stephen Omoyajowo2 Nkolika O. Nwazor (Ph.D)3
Predicting Quality of Life Among Ibadan Residents: The Influence of Self-Esteem, Religious Commitment, Transportation, and Disaster Lifelines In Ibadan, Oyo State
Quality of Life (QoL) is a vital indicator of societal well-being, shaped by the interplay of psychological factors and access to supportive infrastructure. While QoL is influenced by a combination of psychological factors, there is a gap in understanding how transportation access, and disaster lifelines interplay with self-esteem and religious commitment to influence perceived QoL in rapidly urbanizing city. This study examined how self-esteem, religious commitment, transportation, and disaster lifelines predict perceived QoL among residents of Ibadan, a rapidly urbanizing city in Ibadan, Oyo state, Nigeria. Using a cross-sectional survey design, data were randomly collected from 200 participants across diverse localities. Self-esteem and religious commitment were measured with standardized psychological instruments, while spatial accessibility to health services, emergency response facilities, communal spaces, and transportation networks was assessed via geospatial mapping. Male respondents were in the majority 107 (55.4%), average age was 38.01 (SD:9.62), 67.4% were single while 60 (31.1%) were married, Data shows 128 (66.3%) and 65 (33.7%) respectively were from monogamous and polygamous background. Analyses reveal significant positive correlations between QoL and independent variables (self-esteem {r=0.35, p<0.01}) and transportation access (r=0.28, p<0.01). Results of Multiple Regression Analysis indicate that Transportation access (β=0.19,p<0.05), Disaster lifelines (β=0.21,p<0.05), religious commitment (β=0.31, p<0.01) and Self-esteem (β=0.23, p<0.01) significantly predicted QoL. These findings highlight the need for urban interventions that integrate psychological resilience with investments in accessible (transportation), disaster-resilient infrastructure to enhance life satisfaction. This study advocates for planning models that balance emotional well-being with spatial justice to foster sustainable urban communities.
An Integrated Deteriorating Inventory Model with Imperfection Inspection, Variable Demand, and Trade-Credit under Inflation
This study develops an inventory model addressing the complexities of deteriorating items under an imperfection inspection policy, variable demand influenced by time and selling price, and trade-credit financing in the presence of inflation. Imperfections in inventory are identified through a comprehensive inspection process, minimizing the impact of defective items on overall operations. Demand is assumed to vary dynamically, reflecting dependencies on temporal factors and pricing strategies. The trade-credit policy, allowing for delayed payments, introduces additional flexibility for retailers while influencing inventory decisions. Inflation is incorporated to reflect its impact on cost structures and purchasing power, further enriching the model's practical relevance. Through mathematical formulations and numerical analyses, the model provides actionable insights into optimizing inventory policies, balancing the costs of deterioration, inspection, and trade-credit, and adapting to market conditions. The findings offer valuable strategies for businesses managing deteriorating inventories in fluctuating economic environments.
Monu Kumar, Prof Anil Kumar , Prof Shiv Raj Singh