Innovations in Science, Technology, and Society
type: channel
description: Innovations in Science, Technology, and Society is a peer-reviewed, multidisciplinary journal that explores the dynamic relationship between scientific advancement, technological innovation, and societal change. It publishes original research articles, reviews, case studies, and critical perspectives from diverse disciplines, fostering dialogue between researchers, practitioners, and policymakers. The journal emphasizes evidence-based approaches, interdisciplinary collaboration, and the societal implications of emerging technologies, providing a platform for both theoretical analysis and practical applications. The scope of the journal covers, but is not limited to: Social Sciences and Humanities – sociology, psychology, education, language, literature, history, philosophy, cultural studies. Business, Economics, and Management – finance, entrepreneurship, marketing, strategic management, and related fields. Natural and Applied Sciences – environmental studies, agricultural sciences, mathematics, physics, chemistry, biological sciences. Engineering, Technology, and Computer Sciences – information technology, artificial intelligence, data science, and emerging technologies. Health and Life Sciences – public health, medical sciences, biotechnology, and allied health disciplines.
publisher: THE ACADEMIC CONFLUENCE (SMC-PRIVATE) LIMITED
language: en
publication name: Innovations in Science, Technology, and Society
issn: 3105-7381
items: THE IMPACT OF 3D PRINTING ON THE CONSTRUCTION INDUSTRY: ANALYZING THE POTENTIAL FOR SUSTAINABLE BUILDING PRACTICES
items: EXPLORING THE ROLE OF ARTIFICIAL INTELLIGENCE IN OPTIMIZING SUPPLY CHAIN MANAGEMENT: A CASE STUDY OF MANUFACTURING INDUSTRIES
items: ANALYZING THE ENVIRONMENTAL IMPACT OF RENEWABLE ENERGY SOURCES: A COMPARATIVE STUDY OF SOLAR, WIND, AND HYDROPOWER
items: THE ROLE OF GENOMIC MEDICINE IN PERSONALIZED HEALTHCARE: A STUDY ON CRISPR-CAS9 AND ITS APPLICATIONS IN GENE THERAPY
items: ADVANCEMENTS IN QUANTUM COMPUTING: EXPLORING THE POTENTIAL OF QUANTUM ALGORITHMS FOR SOLVING COMPLEX PROBLEMS IN PHYSICS
items: THE ROLE OF MUSIC IN SOCIAL MOVEMENTS: A CASE STUDY OF PROTEST SONGS IN THE CIVIL RIGHTS MOVEMENT
items: ANALYZING THE IMPACT OF URBANIZATION ON THE PRESERVATION OF HISTORIC ARCHITECTURE: A GLOBAL PERSPECTIVE
items: AI-Powered Digital Twins for Optimizing Smart City Infrastructure and Energy Management
items: Sustainable Water Management Practices in Arid Regions
items: AI in Electoral Prediction: Ethical and Political Analysis
items: Artificial Intelligence Applications in Personalized Cognitive Behavioral Therapy
items: The Relationship Between Leadership Styles and Employee Motivation
items: Advanced Robotics for Disaster Response and Humanitarian Engineering in Hazard-Prone Regions
items: Engineering Ethical and Safe Deployment Frameworks for Autonomous Vehicles in Urban Mobility
items: The Evolution of Gender Roles in 20th-Century Wars
items: Industrial Revolution and Its Influence on Urban Social Inequalities
items: Determinants of Start-Up Survival in Emerging Markets
items: Global Trade Wars and Their Impact on Emerging Economies
items: The Role of One Health Approaches in Addressing Zoonotic Diseases in a Globalized World
items: Mental Health Crises in Post-Conflict Regions: Interdisciplinary Approaches to Trauma Healing
items: Nanotechnology Applications in Water Purification for Addressing Global Freshwater Scarcity
items: Price Sensitivity and Its Impact on Brand Switching Behavior
items: The Role of Sovereign Debt in International Financial Stability
items: Engineering Climate-Resilient Infrastructure for Coastal Mega-Cities under Rising Sea Levels
items: The Role of Circular Economy Principles in Reducing Electronic Waste in Global Supply Chains
items: The Role of High-Temperature Superconductors in Next-Generation Energy Transmission
items: Intersections of Feminism and Narrative Voice in Modern Fiction
items: The Relationship Between Social Media Use and Adolescent Self-Esteem
items: Determinants of Working Capital Management Efficiency
items: Exploring the Role of Gut Microbiota in the Development of Autoimmune and Metabolic Disorders

THE IMPACT OF 3D PRINTING ON THE CONSTRUCTION INDUSTRY: ANALYZING THE POTENTIAL FOR SUSTAINABLE BUILDING PRACTICES
type: item
description: The emergence of 3D printing technology, formally known as Additive Manufacturing (AM), represents a paradigm shift in construction methodologies with significant implications for sustainability, efficiency, and design innovation. This study provides a comprehensive quantitative analysis of 3D printing applications in construction, examining environmental impacts, economic viability, and technological capabilities through a mixed-methods investigation of 180 projects across 35 countries from 2015-2023. Results demonstrate that 3D printed construction reduces material waste by 30-60% compared to conventional methods, decreases construction time by 50-80%, and lowers labor requirements by 45-70% through automation integration. Life Cycle Assessment (LCA) reveals that 3D printed concrete structures achieve 15-35% lower embodied carbon emissions when incorporating geopolymer or recycled materials, though energy consumption during printing operations remains 20-40% higher than traditional methods. Structural performance analysis indicates that printed concrete achieves compressive strengths of 35-65 MPa with controlled layer adhesion, though anisotropic properties result in 20-30% reduced strength perpendicular to printing direction compared to conventional casting. Economic assessment shows initial equipment investment of $150,000-$500,000, with project-level cost savings of 15-40% primarily from reduced formwork (eliminating 95% of temporary structures), labor reductions, and material optimization. However, regulatory frameworks lag behind technological innovation, with only 12 countries establishing formal codes for 3D printed construction, creating barriers to widespread adoption. Case studies of residential, commercial, and infrastructure applications reveal that design freedom enables 40-60% material reduction through topology optimization while maintaining structural integrity. The technology demonstrates particular promise for disaster relief housing, with printi…
subject: Engineering And Technology
  topic: section
subject: 3D printing
  topic: keywords
subject: additive manufacturing
  topic: keywords
subject: sustainable construction
  topic: keywords
subject: digital fabrication
  topic: keywords
subject: concrete printing
  topic: keywords
subject: construction automation
  topic: keywords
subject: circular economy
  topic: keywords
creator: Irfan Qadeer
creator: Nadia Shafique
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 13
ending page: 23

EXPLORING THE ROLE OF ARTIFICIAL INTELLIGENCE IN OPTIMIZING SUPPLY CHAIN MANAGEMENT: A CASE STUDY OF MANUFACTURING INDUSTRIES
type: item
description: The integration of Artificial Intelligence (AI) in supply chain management represents a transformative shift in how manufacturing industries optimize operations, reduce costs, and enhance resilience. This study provides a comprehensive analysis of AI applications across the manufacturing supply chain, examining implementation patterns, performance outcomes, and adoption barriers through a mixed-methods investigation of 500 manufacturing firms across North America, Europe, and Asia from 2018-2023. Results demonstrate that AI-driven supply chain optimization reduces operational costs by 22-35%, decreases inventory carrying costs by 28-42%, and improves forecast accuracy by 45-67% compared to traditional methods. Machine learning algorithms for demand forecasting achieved mean absolute percentage errors (MAPE) of 8.7% versus 21.3% for statistical methods, while reinforcement learning for logistics optimization reduced transportation costs by 19-31% through dynamic routing. Computer vision systems for quality inspection increased defect detection rates from 85% to 98.7% while reducing inspection time by 72%. Natural language processing applications in procurement reduced supplier selection time by 65% and improved contract compliance monitoring by 54%. However, implementation challenges persist: data quality issues affect 58% of AI initiatives, integration complexity with legacy systems hinders 42% of deployments, and skill shortages impact 67% of manufacturing firms. Return on investment analysis reveals an average payback period of 18-36 months for AI implementations, with predictive maintenance applications yielding the highest ROI (3.8:1) followed by demand forecasting (2.9:1) and inventory optimization (2.4:1). The study identifies critical success factors including executive sponsorship (increasing implementation success by 3.2 times), data infrastructure maturity (correlating with AI effectiveness at r=0.71), and change management processes (reducing resistance b…
subject: Engineering And Technology
  topic: section
subject: Artificial Intelligence
  topic: keywords
subject: Supply Chain Management
  topic: keywords
subject: Manufacturing Optimization
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: Predictive Analytics
  topic: keywords
subject: Logistics Optimization
  topic: keywords
subject: Digital Transformation
  topic: keywords
creator: Faisal Mehmood
creator: Huma Sarwar
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 1
ending page: 12

ANALYZING THE ENVIRONMENTAL IMPACT OF RENEWABLE ENERGY SOURCES: A COMPARATIVE STUDY OF SOLAR, WIND, AND HYDROPOWER
type: item
description: The global transition from fossil fuels to renewable energy is essential for mitigating climate change, but it necessitates a comprehensive understanding of the environmental trade-offs associated with different renewable technologies. This study provides a quantitative comparative analysis of the lifecycle environmental impacts of three dominant renewable energy sources: solar photovoltaic (PV), wind, and hydropower. Employing a problem-based research methodology, the analysis integrates lifecycle assessment (LCA) data, land-use metrics, material intensity, and ecosystem impact indicators from over 150 global projects commissioned between 2010 and 2023. Results indicate that while all three sources offer substantial carbon emission reductions (92-99%) compared to conventional coal, their environmental footprints differ markedly across impact categories. Hydropower exhibits the lowest median greenhouse gas (GHG) emissions at 12 g CO₂-eq/kWh but has the most significant ecosystem disruption and land-use change impacts. Utility-scale solar PV has a higher median carbon intensity (42 g CO₂-eq/kWh), primarily due to manufacturing, but demonstrates lower ecosystem impact per unit of energy generated. Wind power, particularly onshore, shows a favorable balance with a median GHG emission of 15 g CO₂-eq/kWh and moderate land use, though it poses notable challenges for avian and bat populations. The study identifies critical problem areas, including the mineral resource scarcity for solar PV, the biodiversity loss associated with large hydropower reservoirs, and the end-of-life management of composite materials for wind turbines. The findings underscore that there is no single "lowest-impact" source; optimal deployment depends on localized environmental constraints and the specific impact category prioritized. This research concludes that a diversified, spatially optimized renewable energy portfolio, informed by robust local and global environmental impact assessments, is cr…
subject: Natural and Applied Sciences
  topic: section
subject: Lifecycle Assessment
  topic: keywords
subject: Renewable Energy
  topic: keywords
subject: Environmental Impact
  topic: keywords
subject: Solar Photovoltaic
  topic: keywords
subject: Wind Power
  topic: keywords
subject: Hydropower
  topic: keywords
subject: Sustainable Transition
  topic: keywords
creator: Salman Raza
creator: Komal Yousaf
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 25
ending page: 38

THE ROLE OF GENOMIC MEDICINE IN PERSONALIZED HEALTHCARE: A STUDY ON CRISPR-CAS9 AND ITS APPLICATIONS IN GENE THERAPY
type: item
description: Genomic medicine represents a transformative approach to healthcare that utilizes an individual's genomic information to guide clinical decision-making. This research investigates the revolutionary CRISPR-Cas9 gene-editing system and its applications in gene therapy for personalized healthcare. The study employs quantitative problem-based methodology to analyze clinical outcomes, efficacy rates, and safety profiles of CRISPR-based therapies across various genetic disorders. Our comprehensive analysis demonstrates that CRISPR-Cas9 technology has achieved significant breakthroughs in treating monogenic disorders, with an average efficacy rate of 78.3% across completed clinical trials. The research identifies key therapeutic areas including hemoglobinopathies (sickle cell disease and β-thalassemia), inherited retinal diseases, and metabolic disorders where CRISPR interventions show particular promise. However, challenges persist, including off-target effects (observed in approximately 12.7% of cases), immune responses to Cas9 proteins, and ethical considerations surrounding germline editing. The study further reveals that personalized CRISPR approaches, which consider individual genetic variations and patient-specific mutations, yield 34.2% better outcomes compared to standardized protocols. Emerging delivery systems, particularly lipid nanoparticles and adeno-associated virus vectors, have improved targeting efficiency to 89.4% in recent trials. This research concludes that while CRISPR-Cas9 represents a paradigm shift in personalized medicine, successful integration into clinical practice requires addressing technical limitations, establishing robust regulatory frameworks, and ensuring equitable access. The findings underscore the necessity for continued innovation in delivery mechanisms, specificity enhancement, and long-term safety monitoring to realize the full potential of genomic medicine.
subject: Natural and Applied Sciences
  topic: section
subject: CRISPR-Cas9
  topic: keywords
subject: Genomic Medicine
  topic: keywords
subject: Personalized Healthcare
  topic: keywords
subject: Gene Therapy
  topic: keywords
subject: Gene Editing
  topic: keywords
subject: Precision Medicine
  topic: keywords
subject: Therapeutic Applications
  topic: keywords
creator: Shahbaz Ahmed
creator: Laiba Noor
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 13
ending page: 24

ADVANCEMENTS IN QUANTUM COMPUTING: EXPLORING THE POTENTIAL OF QUANTUM ALGORITHMS FOR SOLVING COMPLEX PROBLEMS IN PHYSICS
type: item
description: Quantum computing has emerged as a promising paradigm for addressing computational challenges in physics that remain intractable for classical methods. This study presents a quantitative benchmarking analysis of prominent quantum algorithms applied to representative physics problem classes, with the objective of evaluating their computational performance relative to state-of-the-art classical algorithms. Using standardized performance metrics—including execution time, algorithmic complexity, resource utilization, accuracy, scalability, and quantum advantage ratios—the study systematically compares quantum and classical approaches across multiple experimental configurations. The results demonstrate that quantum algorithms exhibit measurable performance gains for specific problem types, particularly in terms of runtime efficiency and scaling behavior, while also highlighting practical constraints related to qubit requirements and circuit depth. Visual and tabulated analyses further reveal that quantum advantage is highly problem-dependent and influenced by algorithmic structure and system size. Overall, the findings provide empirical evidence that quantum algorithms can offer substantial computational benefits for selected physics applications, while underscoring the importance of quantitative benchmarking in distinguishing theoretical promise from practical performance. This work contributes to ongoing efforts to objectively assess quantum advantage and informs future research directions in quantum algorithm development and physics-based applications.
subject: Natural and Applied Sciences
  topic: section
subject: Quantum Computing
  topic: keywords
subject: Quantum Algorithms
  topic: keywords
subject: Physics Simulations
  topic: keywords
subject: Computational Benchmarking
  topic: keywords
subject: Quantum Advantage
  topic: keywords
subject: Algorithmic Scalability
  topic: keywords
subject: Performance Analysis
  topic: keywords
creator: Hamza Farid
creator: Amina Siddiq
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 1
ending page: 12

THE ROLE OF MUSIC IN SOCIAL MOVEMENTS: A CASE STUDY OF PROTEST SONGS IN THE CIVIL RIGHTS MOVEMENT
type: item
description: Music has long served as a powerful instrument of collective expression within social movements, shaping emotions, identities, and political action. This study examines the role of protest songs in the American Civil Rights Movement, focusing on how music functioned as a mechanism for mobilization, emotional synchronization, and collective identity formation. Employing a mixed-methods approach, the research integrates qualitative lyrical analysis with quantitative content analysis of protest songs and participant engagement indicators. The findings demonstrate that protest music played a central role in sustaining morale, reinforcing shared purpose, and facilitating emotional alignment among movement participants. Dominant lyrical themes of freedom, unity, faith, and resistance were consistently associated with heightened engagement and collective efficacy. Quantitative results further reveal strong associations between musical repetition, emotional tone, and mobilization intensity across different performance contexts. By foregrounding the emotional and social dimensions of music, this study highlights protest songs as critical cultural resources that enabled sustained participation and resilience within the Civil Rights Movement. The research contributes to social movement studies and ethnomusicology by providing empirical evidence of music’s capacity to transform individual emotion into collective political action.
subject: Social Sciences and Humanities
  topic: section
subject: Music And Social Movements
  topic: keywords
subject: Protest Songs
  topic: keywords
subject: Civil Rights Movement
  topic: keywords
subject: Collective Identity
  topic: keywords
subject: Emotional Mobilization
  topic: keywords
subject: Political Music
  topic: keywords
subject: Cultural Resistance
  topic: keywords
creator: Hassan Rauf
creator: Nida Saleem
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 14
ending page: 26

ANALYZING THE IMPACT OF URBANIZATION ON THE PRESERVATION OF HISTORIC ARCHITECTURE: A GLOBAL PERSPECTIVE
type: item
description: Rapid urbanization has emerged as one of the most significant challenges to the preservation of historic architecture worldwide, often placing modernization pressures in direct conflict with cultural continuity and architectural authenticity. This study examines the global impact of urbanization on the preservation of historic architecture by integrating qualitative field observations, stakeholder interviews, and quantitative assessments across diverse geographical contexts. Using a mixed-methods approach, the research evaluates urbanization intensity, preservation challenges, architectural alterations, policy effectiveness, and socio-economic outcomes associated with heritage areas. The findings reveal that high levels of urban growth and globalization-driven development are strongly associated with material substitution, façade modification, and loss of visual integrity in historic urban landscapes. While adaptive reuse and heritage tourism generate measurable economic benefits, these gains are frequently accompanied by increased vulnerability of architectural authenticity when governance and community participation mechanisms are weak. The results further demonstrate that integrated preservation frameworks, particularly the Historic Urban Landscape approach, show greater potential for balancing development pressures with heritage conservation. Overall, the study highlights the necessity of dynamic, context-sensitive urban management strategies that reconcile economic growth with the long-term safeguarding of historic architectural identity. The research contributes to global heritage and urban studies by providing empirical evidence to inform sustainable policy, planning, and conservation practices in rapidly urbanizing cities.
subject: Social Sciences and Humanities
  topic: section
subject: Urbanization
  topic: keywords
subject: Historic Architecture
  topic: keywords
subject: Heritage Preservation
  topic: keywords
subject: Globalization
  topic: keywords
subject: Historic Urban Landscape
  topic: keywords
subject: Sustainable Urban Development
  topic: keywords
subject: Cultural Identity
  topic: keywords
creator: Saadullah Khan
creator: Mehwish Akhtar
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 1
ending page: 13

AI-Powered Digital Twins for Optimizing Smart City Infrastructure and Energy Management
type: item
description: This study explores the application of AI-powered digital twins in optimizing smart city infrastructure and energy management. By integrating real-time data from IoT-enabled systems with advanced machine learning models, the research demonstrates significant improvements in key urban systems, including energy demand forecasting, traffic optimization, and infrastructure resilience. The AI-driven digital twin models achieved up to a 30% reduction in traffic congestion, 15% peak demand reduction in energy grids, and enhanced system resilience during demand surge events by 40%. These results are supported by simulations and optimization models that reduced energy consumption, improved renewable energy integration, and minimized traffic congestion through predictive modeling. Additionally, the digital twin models optimized water distribution systems and enabled better management of critical urban assets, contributing to more efficient resource utilization. Expert feedback on these models highlighted their practical applicability, showcasing positive reception from urban planners and infrastructure managers. The findings underscore the transformative potential of AI and digital twins in creating more sustainable, resilient, and efficient urban environments. However, the study also identifies challenges such as data privacy concerns and scalability issues, which need to be addressed in future developments. Overall, this research contributes to the evolving field of smart cities, demonstrating how AI-powered digital twins can play a crucial role in urban management and sustainability.
subject: Engineering And Technology
  topic: section
subject: urban infrastructure
  topic: keywords
subject: system resilience
  topic: keywords
subject: traffic flow
  topic: keywords
subject: energy management
  topic: keywords
subject: smart city optimization
  topic: keywords
subject: AI-powered digital twins
  topic: keywords
creator: Syed Ali Khayam
creator: Imran Razzak
rights: Copyright (c) 2025 Syed Ali Khayam, Imran Razzak (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-30
publication date: 2025-06-30
starting page: 1
ending page: 17

Sustainable Water Management Practices in Arid Regions
type: item
description: Water scarcity in arid and semi-arid regions represents one of the most urgent sustainability challenges of the 21st century, driven by climate variability, population growth, agricultural expansion, and unsustainable extraction of groundwater. This study employed a mixed-methods experimental approach, integrating quantitative analyses of efficiency indices and statistical modeling with qualitative insights from case studies and policy frameworks, to evaluate sustainable water management practices. Results from nine tables and twelve figures highlight that advanced interventions—such as drip irrigation, wastewater reuse, mulched drip systems, and precision agriculture—consistently outperformed conventional methods, enhancing water-use efficiency by up to 40–60% and improving soil health and crop resilience. Spatial analyses using GIS-based hydrological mapping identified critical recharge zones and stress hotspots, while policy evaluations revealed that community engagement, transparent governance, and justice-oriented frameworks are indispensable for long-term resilience. Importantly, traditional systems such as qanats, liman irrigation, chauka embankments, and taanka cisterns were found to complement modern technologies, demonstrating that cultural heritage knowledge remains relevant when integrated with innovation. Discussion of global and regional case studies further reinforced the multidimensional nature of sustainability, where environmental gains must align with economic feasibility and social equity. The findings conclude that comprehensive strategies—bridging scientific innovation, indigenous practices, and inclusive governance—are essential for transforming water scarcity from a vulnerability into an opportunity for resilience and sustainable development. This research contributes to advancing water security discourse by emphasizing the need for holistic, context-sensitive solutions that prioritize ecological integrity, food security, and intergenerationa…
subject: Natural and Applied Sciences
  topic: section
subject: Sustainable Water Management
  topic: keywords
subject: Arid Regions
  topic: keywords
subject: Drip Irrigation
  topic: keywords
subject: Wastewater Reuse
  topic: keywords
subject: Hydrological Modeling
  topic: keywords
subject: Traditional Water Systems
  topic: keywords
subject: Climate Resilience
  topic: keywords
subject: Groundwater Conservation
  topic: keywords
subject: Integrated Governance
  topic: keywords
subject: Water-Use Efficiency
  topic: keywords
creator: M. Iqbal Choudhary
creator: Muhammad Raza Shah
rights: Copyright (c) 2025 M. Iqbal Choudhary, Muhammad Raza Shah (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-30
publication date: 2025-06-30
starting page: 1
ending page: 18

AI in Electoral Prediction: Ethical and Political Analysis
type: item
description: This work is the analysis of artificial intelligence (AI) use to predict elections, the focus of which is on the technical capabilities and the ethical and political implications of AI forecasts. We use a mixed-methods approach, consisting of the qualitative study of the political and societal implications of these technologies and the state-of-the-art machine learning frameworks, such as Logistic Regression, Random Forest, and XGBoost. The quantitative part of the study consists in the application of these models to the historical electoral data which include socioeconomic variables, voting pattern, and demographic characteristics. The prediction models demonstrate a high ability to predict the election outcomes as measured on the basis of accuracy, precision, recall, F1-score, and area under the ROC curve (AUC).
subject: Social Sciences and Humanities
  topic: section
subject: Artificial Intelligence
  topic: keywords
subject: Electoral Prediction
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: Ethical Implications
  topic: keywords
subject: Political Analysis
  topic: keywords
subject: Democratic Values
  topic: keywords
creator: Ali Cheema
creator: Usman Qamar
rights: Copyright (c) 2025 Ali Cheema, Usman Qamar (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-30
publication date: 2025-06-30
starting page: 19
ending page: 33

Artificial Intelligence Applications in Personalized Cognitive Behavioral Therapy
type: item
description: This research is a mixed-method experimental investigation into the ways in which Artificial Intelligence (AI) can enhance Personalized Cognitive Behavioural Therapy (AI-CBT). A reinforcement learning framework to dynamically adjust CBT sessions to individual patient characteristics was proposed, supported by multimodal psychometric and natural language processing of therapy transcripts. A randomized controlled trial was carried out (N=120) in three groups: psychoeducational controls, therapist-led CBT, and AI-CBT. The quantitative results indicated that during the baseline, mid-intervention, and post-intervention, participants in the AI-CBT group significantly minimized the symptoms of anxiety and depression measured with the BDI-II and GAD-7 (p < 0.05). Effect size estimates confirmed the high level of AI-motivated personalization impact, and the consistency of therapeutic outcomes was confirmed with repeated measures ANOVA. The presence of positive patient experiences with the involvement, accessibility, and personalization were highlighted through the provision of the complementary qualitative analysis, however, the concerns with the lack of human empathy were also brought up. The thematic insights and the quantitative clinical measures served to enhance the validity of the results and proved AI-CBT to be a successful and scalable intervention. Altogether, the present study provides empirical evidence that AI can transform the method by which therapy is provided by making the interventions context-aware, data-driven, and flexible. This will assist in addressing the growing demand of mental health solutions globally that are readily available. The conclusion of the study addresses implications of human-AI hybrid therapeutic models in the future, as well as ethical issues surrounding digital health, in terms of its acceptance by clinicians.
subject: Social Sciences and Humanities
  topic: section
subject: Human-AI Interaction
  topic: keywords
subject: Digital Mental Health
  topic: keywords
subject: Reinforcement Learning
  topic: keywords
subject: Cognitive Behavioral Therapy
  topic: keywords
subject: Personalized Therapy
  topic: keywords
subject: Artificial Intelligence
  topic: keywords
creator: Ayesha Mian
creator: Usman Qamar
rights: Copyright (c) 2025 Ayesha Mian, Usman Qamar (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-30
publication date: 2025-06-30
starting page: 1
ending page: 18

The Relationship Between Leadership Styles and Employee Motivation
type: item
description: This study investigates the relationship between leadership styles and employee motivation through a mixed-methods approach combining quantitative surveys and qualitative interviews across diverse organizational sectors. The analysis focused on transformational, transactional, and laissez-faire leadership styles, examining their respective impacts on intrinsic and extrinsic motivation. Quantitative results revealed that transformational leadership demonstrated the strongest positive correlation with intrinsic motivation, significantly enhancing empowerment, creativity, and engagement. Transactional leadership exhibited moderate associations, primarily influencing extrinsic motivation through structured rewards and performance monitoring, while laissez-faire leadership consistently showed weak or negative effects on motivation and job satisfaction. Regression analysis confirmed transformational leadership as the most significant predictor of motivational outcomes, supported by ANOVA results showing significant differences across leadership styles. Departmental-level analysis indicated that healthcare and education employees reported the highest motivational responses, while generational differences highlighted younger employees’ stronger alignment with transformational practices. Qualitative findings reinforced these results, identifying recognition, communication, and psychological safety as central themes driving motivation under effective leadership. The integration of quantitative and qualitative insights provided a comprehensive perspective, underscoring that motivation is context-dependent and mediated by demographic, cultural, and organizational factors. Overall, the study concludes that transformational leadership is the most effective style in fostering sustainable motivation, though situational adaptability is essential for optimizing outcomes across diverse workforce segments. These findings have significant implications for leadership development, organiz…
subject: Business And Finance
  topic: section
subject: Leadership Styles
  topic: keywords
subject: Employee Motivation
  topic: keywords
subject: Transformational Leadership
  topic: keywords
subject: Transactional Leadership
  topic: keywords
subject: Organizational Behavior
  topic: keywords
subject: Workplace Engagement
  topic: keywords
creator: Ather H. Akhlaq
creator: Uzma Javed
rights: Copyright (c) 2025 Ather H. Akhlaq, Uzma Javed (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-30
publication date: 2025-06-30
starting page: 1
ending page: 16

Advanced Robotics for Disaster Response and Humanitarian Engineering in Hazard-Prone Regions
type: item
description: The integration of advanced robotics into disaster response has the potential to revolutionize humanitarian engineering in hazard-prone regions. This study introduces and evaluates the Advanced Robotics for Disaster Response and Humanitarian Engineering Framework (ARDR-HEF), designed to enhance safety, efficiency, and ethical deployment in complex disaster scenarios. Through quantitative simulation experiments and qualitative stakeholder analysis, the framework was rigorously tested across multiple hazard environments, including earthquakes, floods, and wildfires. Results from nine experimental tables revealed significant performance improvements: baseline robot performance across terrains demonstrated enhanced navigation speed, detection accuracy increased by over 25% with AI-IoT integration, and fairness metrics in victim detection improved notably in low-visibility conditions. Liability modeling showed balanced distribution of responsibility among agencies, while safety margins were consistently maintained even under stress-tested conditions. Twelve diverse figures further visualized the robustness of the framework, including reductions in disaster response time, improved stakeholder trust indices, and clear correlations between hazard intensity and robotic efficiency. Importantly, multi-agent and hybrid robotic systems showed superior coverage efficiency and ethical compliance compared to traditional approaches. The study concludes that ARDR-HEF provides a resilient, ethically informed, and scalable methodology for robotics deployment in disaster response. By aligning engineering advances with humanitarian imperatives, this framework paves the way for safer, faster, and more transparent disaster management operations in regions most vulnerable to catastrophic events.
subject: Engineering And Technology
  topic: section
subject: Advanced Robotics
  topic: keywords
subject: Disaster Response
  topic: keywords
subject: Humanitarian Engineering
  topic: keywords
subject: Hazard-Prone Regions
  topic: keywords
subject: Ethical Ai
  topic: keywords
subject: Safety Framework
  topic: keywords
creator: Faisal Riaz
creator: Khurram Bhatti
rights: Copyright (c) 2024 Faisal Riaz, Khurram Bhatti (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-12-31
publication date: 2024-12-31
starting page: 17
ending page: 32

Engineering Ethical and Safe Deployment Frameworks for Autonomous Vehicles in Urban Mobility
type: item
description: The deployment of autonomous vehicles (AVs) in urban mobility systems presents both transformative opportunities and complex challenges, requiring frameworks that integrate engineering safety with ethical accountability. This study proposes and validates an Engineering Ethical and Safe Deployment Framework (EESDF) that combines quantitative simulations, ethical reasoning, and stakeholder engagement. Using high-fidelity urban driving simulations, we observed that ethically guided algorithms reduced the probability of high-severity collisions by 37% compared to baseline rule-based models. Pedestrian detection accuracy improved by 21% through fairness-oriented perception models, while liability distribution models highlighted the importance of transparent governance mechanisms. Qualitative insights from policymakers, engineers, and planners reinforced the significance of explainability, accountability, and regulatory harmonization for public trust. Results from twelve distinct visualization analyses and nine extensive datasets confirmed that the integration of ethical reasoning modules not only enhanced safety margins but also aligned with international standards such as ISO 21448 and UNECE Regulation 157. The EESDF thus provides a robust, adaptable, and socially responsible framework for AV deployment in diverse urban contexts. By embedding fairness, transparency, and explainability into engineering systems, the study demonstrates that the safe integration of AVs depends not only on technical robustness but equally on ethical and governance dimensions, thereby paving the way for sustainable and equitable urban transportation systems.
subject: Engineering And Technology
  topic: section
subject: Autonomous Vehicles
  topic: keywords
subject: Urban Mobility
  topic: keywords
subject: Safety Framework
  topic: keywords
subject: Ethical Ai
  topic: keywords
subject: Governance
  topic: keywords
subject: Transparency
  topic: keywords
creator: Imran Razzak
creator: Naveed Arshad
rights: Copyright (c) 2024 Imran Razzak, Naveed Arshad (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-12-31
publication date: 2024-12-31
starting page: 1
ending page: 16

The Evolution of Gender Roles in 20th-Century Wars
type: item
description: The paper explores the changing role of gender in light of the 20 th century wars with particular attention on the role played by women in the military industry sector resistance and spy activities as well as politics. The study reveals major shifts in popular opinion about gender roles by reviewing statistics about women enlistment, employment rate, political empowerment, and wartime input into intelligence units. Women have long-term consequences because women who were transferred to defence and industries during the warfare, later contributed on active duties thus helping them gain equal position in the society. The study actually shows that even though many women went back to traditional roles following the war, the changes that happened during the war provided the necessary grounds on which the gender equality movements of the future would build on. As the results indicate, the upheavals caused by the war granted women the opportunity to challenge the gender traditions and occupied themselves with the new roles vital to the efforts of war as well as influenced how genders would interact in the future. This work has built a better understanding of how gender and warfare interact as well as how social change occurs, in that the work shows how the role in which women played during these turbulent times were radical in addition to being highly formative in the course of future feminism.
subject: Social Sciences and Humanities
  topic: section
subject: Gender Roles
  topic: keywords
subject: Women In Wartime
  topic: keywords
subject: Resistance Movements
  topic: keywords
subject: Espionage
  topic: keywords
subject: Industrial Workforce
  topic: keywords
subject: Gender Equality
  topic: keywords
creator: Nukhbah Langah
creator: Farzana Bari
rights: Copyright (c) 2024 Nukhbah Langah, Farzana Bari (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-12-31
publication date: 2024-12-31
starting page: 20
ending page: 40

Industrial Revolution and Its Influence on Urban Social Inequalities
type: item
description: The paper undertakes a mixed-design study of the effects of industrial revolution on urban social inequality by combining a qualitative and a quantitative study. The study focuses on the growth of employment in the manufacturing sector, the wage gap between unskilled an skilled laborers, and on how urbanization impacted housing, healthcare, education, and crime by researching historical archives, censuses, and historical economic statistics of the 19 th century. The results indicate high disparities between socioeconomic groups in that the skilled labourers were better paid, the working population had poor living conditions, limited access to basic amenities and the lifespan deteriorated. Regression analysis and factor analysis, just to name a few of the statistical methods, confirm the extent of income inequality and its relation to poor living conditions i.e. overcrowding and the lack of social amenities. The thematic analysis of historical writings puts historical discoveries into perspective and gives a better understanding of the social consequences of the subject of industrialization. This study broadens the understanding of structural inequalities that occurred during the Industrial Revolution and its continued effects on the current cities.
subject: Social Sciences and Humanities
  topic: section
subject: Industrial Revolution
  topic: keywords
subject: Urban Inequality
  topic: keywords
subject: Wage Disparities
  topic: keywords
subject: Social Class
  topic: keywords
subject: Urbanization
  topic: keywords
subject: Socioeconomic Disparities
  topic: keywords
creator: Tahir Kamran
creator: Ali Khan
rights: Copyright (c) 2024 Tahir Kamran, Ali Khan (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-12-31
publication date: 2024-12-31
starting page: 1
ending page: 19

Determinants of Start-Up Survival in Emerging Markets
type: item
description: This study investigates the determinants of start-up survival in emerging markets, adopting a mixed-methods approach that integrates econometric modeling with qualitative insights from entrepreneurs and ecosystem actors. Drawing on data from multiple emerging economies, the research examines firm-level characteristics, institutional quality, and ecosystem support as key drivers of entrepreneurial resilience. The findings indicate that larger firms and those led by experienced founders are more likely to survive, while innovation and digital adoption further enhance competitiveness. Access to finance emerges as one of the most critical predictors of survival, although its effectiveness is moderated by institutional environments. The study also highlights the vital role of entrepreneurial ecosystems, such as incubators and accelerators, in compensating for weak formal institutions. Sectoral analysis reveals that technology-based ventures display greater longevity than traditional industries. Overall, the results underscore that start-up survival is shaped by systemic interactions between resources, institutions, and networks, rather than by single determinants. The study offers theoretical contributions to entrepreneurship literature by contextualizing survival within emerging market dynamics, and practical implications for policymakers and investors aiming to strengthen entrepreneurial ecosystems and improve long-term sustainability of start-ups.
subject: Business And Finance
  topic: section
subject: Start-Up Survival
  topic: keywords
subject: Emerging Markets
  topic: keywords
subject: Entrepreneurial Ecosystems
  topic: keywords
subject: Institutional Quality
  topic: keywords
subject: Innovation
  topic: keywords
subject: Access To Finance
  topic: keywords
creator: Shahzad Khurram
creator: Faisal Bari
rights: Copyright (c) 2024 Shahzad Khurram, Faisal Bari (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-12-31
publication date: 2024-12-31
starting page: 19
ending page: 34

Global Trade Wars and Their Impact on Emerging Economies
type: item
description: This paper investigates the impact of global trade wars on emerging economies using a mixed-methods approach that combines econometric analysis with qualitative evidence. Drawing on panel data from 2018 to 2024, the study finds that tariff escalations and trade policy uncertainty significantly reduce GDP growth, increase inflation, deter foreign direct investment, and destabilize exchange rates. Sectoral evidence highlights that export-oriented industries and household consumption patterns are particularly vulnerable, with downstream effects on industrial performance and social welfare. Additionally, trade wars exacerbate sovereign debt stress in economies with fragile fiscal structures. Visualizations confirm these relationships, illustrating how trade policy uncertainty and tariff intensity amplify macroeconomic instability. At the same time, regional integration emerges as a partial buffer, mitigating some of the adverse consequences through intra-regional trade flows and institutional cooperation. The study concludes that trade wars are systemic shocks that disproportionately affect developing economies, underscoring the urgency of structural reforms, industrial diversification, and resilience-oriented trade strategies. These insights not only contribute to academic debates but also provide actionable policy implications for governments and international financial institutions navigating the current era of global protectionism.
subject: Business And Finance
  topic: section
subject: Global Trade Wars
  topic: keywords
subject: Emerging Economies
  topic: keywords
subject: Protectionism
  topic: keywords
subject: Foreign Direct Investment
  topic: keywords
subject: Regional Integration
  topic: keywords
subject: Macroeconomic Stability
  topic: keywords
creator: Syed Nawab Haider Naqvi
creator: Naved Hamid
rights: Copyright (c) 2024 Syed Nawab Haider Naqvi, Naved Hamid (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-12-31
publication date: 2024-12-31
starting page: 1
ending page: 18

The Role of One Health Approaches in Addressing Zoonotic Diseases in a Globalized World
type: item
description: Zoonotic diseases remain among the most pressing global health challenges of the twenty-first century, accounting for the majority of emerging infectious diseases and representing a critical threat in the context of globalization. The accelerated pace of international travel, global trade, urbanization, and ecological disruption has amplified the risk of zoonotic spillover and cross-border transmission, as illustrated by outbreaks of COVID-19, Ebola, avian influenza, and Nipah virus. This study employed a mixed-method experimental design to evaluate the role of One Health approaches in preventing, detecting, and managing zoonotic diseases between 2020 and 2022. Quantitative analyses of outbreak incidence, mortality rates, and economic impacts were combined with qualitative thematic synthesis of policy frameworks and case studies, enabling a comprehensive assessment of One Health’s effectiveness. Results, presented in nine structured tables and twelve figures, reveal that countries adopting integrated One Health frameworks achieved earlier detection of outbreaks, reduced case fatality ratios, and enhanced cost-effectiveness compared to those relying on siloed health systems. The analysis also highlighted antimicrobial resistance as a critical cross-cutting issue requiring One Health stewardship across human, animal, and environmental domains. While evidence strongly supports the value of One Health in mitigating zoonotic threats, persistent challenges include limited adoption in low- and middle-income countries, governance gaps, and underinvestment in environmental health. Nevertheless, the findings affirm that operationalizing One Health is not only a scientific imperative but also an economic and ethical necessity. By aligning human, animal, and ecosystem health under a unified framework, One Health provides a transformative pathway for global pandemic preparedness, equitable health outcomes, and sustainable coexistence in a rapidly globalizing world.
subject: Health and Life Sciences
  topic: section
subject: One Health, Zoonotic Diseases
  topic: keywords
subject: Globalization
  topic: keywords
subject: Pandemic Preparedness
  topic: keywords
subject: Antimicrobial Resistance
  topic: keywords
subject: Cross-Sectoral Collaboration
  topic: keywords
subject: Outbreak Surveillance
  topic: keywords
subject: Ecosystem Health
  topic: keywords
subject: Emerging Infections
  topic: keywords
subject: Global Health Security
  topic: keywords
creator: Aftab Ahmed
creator: Saad Abdullah
creator: Rabia Nasir
rights: Copyright (c) 2024 Aftab Ahmed, Saad Abdullah, Rabia Nasir (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-06-30
publication date: 2024-06-30
starting page: 67
ending page: 88

Mental Health Crises in Post-Conflict Regions: Interdisciplinary Approaches to Trauma Healing
type: item
description: Post-conflict regions face a dual burden of rebuilding social infrastructures while addressing widespread mental health crises driven by trauma, displacement, and chronic stressors. This study applied a mixed-methods experimental design to evaluate interdisciplinary approaches to trauma healing, combining quantitative assessments of psychological outcomes with qualitative insights from affected communities. Quantitative findings revealed significant reductions in PTSD, depression, and anxiety symptoms among participants engaged in layered psychosocial interventions, with statistical models showing that community-based care integrated with livelihood support produced stronger recovery trajectories than stand-alone treatments. Functional outcomes, such as resilience and daily living capacity, also improved markedly across diverse demographic groups. Cost-effectiveness analysis indicated that integrated interventions yielded favorable incremental cost-effectiveness ratios, underscoring both clinical impact and economic sustainability. Qualitative data highlighted the importance of cultural adaptation, stigma reduction, and gender-sensitive programming, revealing that healing is often experienced not only as symptom relief but as restoration of dignity, social connection, and community trust. The integration of these findings confirmed that interdisciplinary interventions are most effective when clinical care is embedded within social protection, livelihood development, and participatory community structures. However, persistent challenges remain, including limited workforce capacity, inconsistent implementation fidelity, and inequitable access for marginalized groups. Overall, the results demonstrate that trauma healing in post-conflict regions is best advanced through interdisciplinary, context-sensitive strategies that link psychological recovery with broader peacebuilding and development goals.
subject: Health and Life Sciences
  topic: section
subject: Post-Conflict Mental Health
  topic: keywords
subject: Trauma Healing
  topic: keywords
subject: Interdisciplinary Interventions
  topic: keywords
subject: Psychosocial Support
  topic: keywords
subject: Resilience
  topic: keywords
subject: Community Recovery
  topic: keywords
creator: Ayesha Mian
creator: Farah Malik
rights: Copyright (c) 2024 Ayesha Mian, Farah Malik (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-06-30
publication date: 2024-06-30
starting page: 50
ending page: 66

Nanotechnology Applications in Water Purification for Addressing Global Freshwater Scarcity
type: item
description: Freshwater scarcity is a mounting global crisis, affecting billions and threatening socio-economic and ecological stability. This study investigates the application of nanotechnology in water purification as a sustainable solution to mitigate this challenge. A mixed-method experimental design was employed, integrating quantitative performance analysis and qualitative evaluation of nanomaterials including graphene oxide, carbon nanotubes, silver nanoparticles, titanium dioxide, and zeolite nanocomposites. The results demonstrate that graphene oxide exhibited the highest adsorption efficiency for heavy metals, achieving over 95% removal under optimized pH conditions. Silver nanoparticles displayed superior antimicrobial performance, eliminating more than 99.9% of E. coli and S. aureus colonies. Titanium dioxide achieved 90–95% degradation of organic dyes through photocatalysis under solar-simulated conditions. Zeolite-based composites provided promising results in desalination, showing a significant reduction in total dissolved solids. Comparative cost-efficiency analysis indicated that carbon nanotubes, despite high production costs, offer excellent regeneration and reuse potential. Twelve complex visualizations—including line plots, bar graphs, pie charts, scatter matrices, heatmaps, and hybrid plots—confirmed the statistical robustness of the findings. Additionally, the pseudo-second-order kinetic model and Langmuir isotherm confirmed strong correlation (R² > 0.98) in adsorption behavior, indicating rapid equilibrium and high surface specificity. While the laboratory-scale data affirm nanomaterials' superior performance, the study also highlights challenges in scalability, material safety, and environmental impact. Ultimately, this research provides compelling evidence that nanotechnology, if guided by safe and cost-effective implementation strategies, can revolutionize global water treatment frameworks and significantly contribute to achieving sustainable developm…
subject: Engineering And Technology
  topic: section
subject: Nanotechnology
  topic: keywords
subject: Water Purification
  topic: keywords
subject: Graphene Oxide
  topic: keywords
subject: Silver Nanoparticles
  topic: keywords
subject: Photocatalysis
  topic: keywords
subject: Freshwater Scarcity
  topic: keywords
creator: Muhammad Aslam Chaudhry
creator: Rukhsana Kausar
rights: Copyright (c) 2024 Muhammad Aslam Chaudhry, Rukhsana Kausar (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-06-30
publication date: 2024-06-30
starting page: 32
ending page: 49

Price Sensitivity and Its Impact on Brand Switching Behavior
type: item
description: This study investigates the impact of price sensitivity on brand switching behavior by employing a mixed-methods experimental design that integrates quantitative surveys and qualitative interviews. A structured survey of 500 consumers across multiple retail categories, complemented by 30 in-depth interviews, provides robust evidence on how price-related factors shape switching intentions. The quantitative findings reveal that price sensitivity exerts a significant positive influence on brand switching, as confirmed by regression and structural equation modeling, while brand loyalty demonstrates a moderating effect that dampens sensitivity-driven defection. Perceived value emerges as a critical mediator, with consumers perceiving low value more likely to abandon established brands even at marginal price differences. The results further indicate that demographic characteristics strongly influence sensitivity, with younger and lower-income consumers displaying higher switching rates than older or more affluent segments.Visual analyses from twelve figures and nine data tables underscore the robustness of these relationships, showing consistent patterns across consumer segments and product categories. Time-series and hybrid plots highlight the role of discounts and promotional strategies in amplifying switching, while scatter and correlation analyses confirm the interactive influence of loyalty and perceived value. The thematic analysis of interviews enriches these findings, revealing psychological underpinnings such as loss aversion, fairness perceptions, and reference pricing that shape switching behavior.Theoretically, this study contributes to the literature by integrating behavioral economics with marketing models to explain the dynamics of price sensitivity. Managerially, the findings suggest that while competitive pricing and promotions can attract high-sensitivity consumers, long-term loyalty requires value-added strategies, emotional branding, and trust-building…
subject: Social Sciences and Humanities
  topic: section
subject: Price Sensitivity
  topic: keywords
subject: Brand Switching
  topic: keywords
subject: Perceived Value
  topic: keywords
subject: Brand Loyalty
  topic: keywords
subject: Consumer Behavior
  topic: keywords
subject: Promotional Strategies
  topic: keywords
creator: Samira Azmat
creator: Naeem Akhtar
creator: Kamran Siddiqui
rights: Copyright (c) 2024 Samira Azmat, Naeem Akhtar, Kamran Siddiqui (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-06-30
publication date: 2024-06-30
starting page: 16
ending page: 31

The Role of Sovereign Debt in International Financial Stability
type: item
description: This study investigates the pivotal role of sovereign debt in shaping international financial stability, employing a mixed-method approach that integrates quantitative econometric analysis with qualitative case studies. Using panel data from both advanced and emerging economies between , the research explores the effects of debt-to-GDP ratios, fiscal deficits, inflation, and credit spreads on global financial stability indices. The econometric findings reveal that excessive sovereign debt significantly increases credit spreads and undermines investor confidence, while Granger causality tests confirm a bidirectional relationship between debt accumulation and financial stability. Complementary qualitative analyses of Greece, Argentina, and Sri Lanka further illustrate how political constraints, weak fiscal institutions, and negotiation dynamics exacerbate crises, leading to systemic contagion across international markets. The results, summarized in nine tables and twelve figures, consistently demonstrate that sovereign debt sustainability depends not only on fiscal metrics but also on institutional quality, governance transparency, and macroeconomic credibility. Importantly, the study highlights the vulnerabilities of emerging markets, which face heightened risks due to limited fiscal buffers and exposure to global capital flows. At the same time, the analysis underscores the necessity of international coordination and the role of multilateral institutions in mitigating spillovers and facilitating orderly debt restructuring. Overall, the research contributes to the literature by offering an integrated perspective on sovereign debt management, providing evidence that prudent borrowing, credible fiscal discipline, and cooperative global frameworks are essential for preserving international financial stability.
subject: Business And Finance
  topic: section
subject: Sovereign Debt
  topic: keywords
subject: Financial Stability
  topic: keywords
subject: Debt Sustainability
  topic: keywords
subject: Fiscal Policy
  topic: keywords
subject: Credit Spreads
  topic: keywords
subject: International Coordination
  topic: keywords
creator: Eatzaz Ahmad
creator: Muhammad Bilal
rights: Copyright (c) 2024 Eatzaz Ahmad, Muhammad Bilal (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-06-30
publication date: 2024-06-30
starting page: 1
ending page: 15

Engineering Climate-Resilient Infrastructure for Coastal Mega-Cities under Rising Sea Levels
type: item
description: This study investigates the engineering of climate-resilient infrastructure for coastal mega-cities facing the escalating threat of rising sea levels. Employing a mixed-methods framework that combined quantitative flood modeling, resilience index formulation, and qualitative governance analysis, the research evaluated the comparative performance of gray, green, and hybrid infrastructure strategies across multiple case study cities. The results demonstrated that hybrid green–gray approaches, which integrate engineered structures with ecosystem-based defenses, achieved consistently higher resilience indices compared to traditional gray infrastructure. For example, New York City’s integrated flood barrier designs showed improved adaptive capacity, while Jakarta revealed compounded risks due to land subsidence, necessitating multi-layered interventions. Quantitative simulations further indicated that hybrid systems reduced long-term vulnerability coefficients by up to 35% while lowering projected economic losses relative to singular engineering projects. Technological enhancements, including digital twins and IoT-based flood monitoring, further strengthened adaptability by enabling real-time scenario testing. However, findings highlighted that governance capacity, institutional effectiveness, and financial inclusivity were decisive in determining the sustainability of resilience interventions, with Shanghai’s sponge city initiatives exemplifying successful policy integration. The study concludes that resilient infrastructure must be understood as a dynamic socio-technical system requiring not only engineering innovation but also adaptive governance and community participation. These findings reinforce the need for proactive, multi-disciplinary investments to secure sustainable urban futures in the face of accelerating climate risks.
subject: Engineering And Technology
  topic: section
subject: Climate Resilience
  topic: keywords
subject: Coastal Mega-Cities
  topic: keywords
subject: Sea Level Rise
  topic: keywords
subject: Hybrid Infrastructure
  topic: keywords
subject: Adaptive Governance
  topic: keywords
subject: Sustainable Urban Design
  topic: keywords
creator: Aqsa Bano
creator: Rimsha Tariq
rights: Copyright (c) 2023 Aqsa Bano, Rimsha Tariq (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2023-12-31
publication date: 2023-12-31
starting page: 83
ending page: 100

The Role of Circular Economy Principles in Reducing Electronic Waste in Global Supply Chains
type: item
description: This study examines the role of circular economy (CE) principles in reducing electronic waste (e-waste) within global supply chains, addressing one of the most pressing sustainability challenges of the digital age. Through a mixed-methods approach combining quantitative modeling, case study analysis, and qualitative assessment of corporate and policy frameworks, the research highlights how CE practices contribute to waste minimization, resource conservation, and supply chain resilience. The findings reveal that eco-design and modularity extended electronic product lifecycles by up to 25%, while reverse logistics and take-back systems increased collection rates by nearly 40%. Remanufacturing and refurbishment programs reduced net waste volumes by more than 30%, and advanced recycling technologies achieved recovery efficiencies of over 95% for critical materials such as copper, gold, and rare earth elements. These outcomes underscore the economic and environmental benefits of embedding CE strategies into supply chains, including reduced dependency on virgin resource extraction, stabilization of raw material costs, and the creation of secondary markets. However, the study also identifies persistent barriers such as high initial investment costs, uneven regulatory enforcement, and consumer resistance to non-ownership business models. The analysis concludes that although challenges remain, CE adoption represents both an environmental necessity and a strategic pathway to global supply chain competitiveness. The results affirm that a systemic transition toward circular supply chains is achievable through innovation, collaboration, and harmonized international policy frameworks, thereby contributing significantly to global sustainability targets.
subject: Engineering And Technology
  topic: section
subject: Circular Economy
  topic: keywords
subject: Electronic Waste
  topic: keywords
subject: Global Supply Chains
  topic: keywords
subject: Reverse Logistics
  topic: keywords
subject: Remanufacturing
  topic: keywords
subject: Sustainability
  topic: keywords
creator: Sajid Anwar
creator: M. Arif Khan
rights: Copyright (c) 2023 Sajid Anwar, M. Arif Khan (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2023-12-31
publication date: 2023-12-31
starting page: 66
ending page: 82

The Role of High-Temperature Superconductors in Next-Generation Energy Transmission
type: item
description: This paper researches the possibility of high-temperature superconductors (HTS) becoming the basis of the next generation transmission system by combining expertise insights, modelling, and experimental testing. YBCO-based coated conductors were tested under varying load conditions and cooled by cryogenic systems using four-point probe techniques that has enabled the determination of the critical current density and the quench behaviour. The grid-like electromagnetic and thermal responses were simulated with complementary finite element models and results were compared, finding a good match (RMSE < 5%). HTS conductors show vast improvements over conventional metallic conductors with a current-carrying capacity and energy loss performance that is increased by over 20 percent with large currents and recording gains of 20 percent or more in case of high currents. Also, the qualitative perceptions of power grid engineers demonstrated the mechanical durability, cooling costs, and scalability problems that trigger the need of multidisciplinary optimization. The results of quantitative and qualitative analysis show that HTS is transforming energy networks into sustainable, compact and efficient networks that can support the absorption of renewable energies in future. This discussion indicates that HTS technology is a viable solution to remodel the world power transmission infrastructures, although there are still engineering and economic issues.
subject: Natural and Applied Sciences
  topic: section
subject: High-Temperature Superconductors
  topic: keywords
subject: Energy Transmission
  topic: keywords
subject: YBCO Conductors
  topic: keywords
subject: Critical Current Density
  topic: keywords
subject: Finite Element Modeling
  topic: keywords
subject: Power Grid Efficiency
  topic: keywords
creator: Asim K. Joarder
creator: Zulfiqar Ali
rights: Copyright (c) 2023 Asim K. Joarder, Zulfiqar Ali (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2023-12-31
publication date: 2023-12-31
starting page: 47
ending page: 65

Intersections of Feminism and Narrative Voice in Modern Fiction
type: item
description: The paper explores the interplay between feminism and narrative voice in present-day literature and how the contemporary writers are using the new narrative techniques to challenge the present gender roles and accounts and give more space to the female voices. This paper examines the works where authors apply polyphonic, unreliable and fragmented narrative voices to construct complex and multifaceted portraits of female experiences The works that will be analysed are such as Girl, Woman, Other (Evaristo, 2019) The Silence of the Girls (Barker, 2018) and The List (Adegoke, 2023). The study explores how speculative fiction and magical realism in feminist writing are used to challenge typical societal norms and gender realities by using the works of Helen Oyeyemi and Natsuo Kirino as an example. It also underlines the significance of an intersectional feminist approach taking into consideration race, class and sexuality in the representations of women issues and identities in literature. In this paper, it has been explained that modern-day feminist writings do not only denounce the patriarchal condition but also offer new, incorporative ways of recounting the experiences of women. These findings illustrate the importance of narrative voice in feminist texts as a means of self-examination and of subversion to challenge literary conventions and further evolve feminist practices.
subject: Social Sciences and Humanities
  topic: section
subject: Feminism
  topic: keywords
subject: Narrative Voice
  topic: keywords
subject: Intersectionality
  topic: keywords
subject: Modern Fiction
  topic: keywords
subject: Gender Norms
  topic: keywords
subject: Women’s Voices
  topic: keywords
creator: Hafsa Bilqees
creator: Shahid Siddiqui
rights: Copyright (c) 2023 Hafsa Bilqees, Shahid Siddiqui (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2023-12-31
publication date: 2023-12-31
starting page: 33
ending page: 46

The Relationship Between Social Media Use and Adolescent Self-Esteem
type: item
description: This study examined the relationship between social media use and adolescent self-esteem through a mixed-methods design that integrated quantitative analyses with qualitative insights. Quantitative findings indicated a significant negative association between hours of daily social media use and self-esteem scores, with regression models confirming social media use as a predictor of diminished self-worth. Structural equation modeling further revealed that body image concerns and upward social comparison mediated this relationship, highlighting the indirect pathways through which digital engagement influences adolescent well-being. Gender- and age-based analyses demonstrated that adolescent girls and younger cohorts were particularly vulnerable, reporting lower self-esteem levels when exposed to appearance-driven content. Conversely, boys displayed relatively greater resilience to self-image pressures. Qualitative interviews reinforced these patterns, as participants reported experiences of body dissatisfaction, peer validation pressure, and self-comparison online. However, some adolescents also described positive effects of social media when used for supportive peer interactions, creative expression, and connection, suggesting a dual nature in its influence. Visual data trends confirmed consistent associations across subgroups, with line, bar, scatter, and hybrid plots illustrating stronger resilience in moderate users and decreased outcomes in heavy users. Together, these findings demonstrate that while social media can provide temporary benefits, excessive and appearance-focused use undermines adolescent self-esteem, necessitating interventions that foster digital literacy, encourage mindful engagement, and strengthen protective psychosocial resources.
subject: Social Sciences and Humanities
  topic: section
subject: Social Media
  topic: keywords
subject: Adolescents
  topic: keywords
subject: Self-Esteem
  topic: keywords
subject: Body Image
  topic: keywords
subject: Social Comparison
  topic: keywords
subject: Digital Literacy
  topic: keywords
creator: Niaz Muhammad
creator: Farhat Nisar
rights: Copyright (c) 2023 Niaz Muhammad, Farhat Nisar (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2023-12-31
publication date: 2023-12-31
starting page: 18
ending page: 32

Determinants of Working Capital Management Efficiency
type: item
description: This study investigates the determinants of Working Capital Management Efficiency (WCME) by integrating firm-level, institutional, technological, and macroeconomic factors within a mixed-method framework. Using a balanced panel of firms across emerging and developed economies , the analysis employs System GMM estimations complemented by Fixed and Random Effects models to mitigate endogeneity concerns. The results demonstrate that profitability, liquidity, and firm size significantly improve WCME by reducing the Cash Conversion Cycle (CCC), while leverage and financial constraints act as barriers. Governance quality and ESG practices emerge as critical enablers, moderating the adverse effects of debt and institutional weaknesses. Furthermore, technological adoption, particularly FinTech integration, enhances efficiency by optimizing receivables and payables management. Comparative results reveal that developed economies consistently outperform emerging markets, though technology adoption enables emerging-market firms to partially close the efficiency gap. Macroeconomic conditions, including inflation, GDP growth, and exchange rate volatility, are also shown to exert significant influence on WCME. The study’s novelty lies in its holistic perspective that incorporates digital transformation and sustainability dimensions, extending beyond conventional financial determinants. The findings provide important implications for managers to align liquidity strategies with profitability and technological innovation, and for policymakers to strengthen institutional frameworks and ensure macroeconomic stability. Overall, the study contributes to theory and practice by offering integrated evidence on the multidimensional drivers of WCME, paving the way for future research on the role of governance, sustainability, and digitalization in short-term financial management.
subject: Business And Finance
  topic: section
subject: Working Capital Management
  topic: keywords
subject: Cash Conversion Cycle
  topic: keywords
subject: Profitability
  topic: keywords
subject: Governance
  topic: keywords
subject: Fintech
  topic: keywords
subject: Sustainability
  topic: keywords
creator: Muhammad Waqar
creator: Rabeel Shaikh
rights: Copyright (c) 2023 Muhammad Waqar, Rabeel Shaikh (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2023-12-31
publication date: 2023-12-31
starting page: 1
ending page: 17

Exploring the Role of Gut Microbiota in the Development of Autoimmune and Metabolic Disorders
type: item
description: This study investigates the role of gut microbiota in the development of autoimmune and metabolic disorders, with a focus on understanding how microbial imbalances contribute to disease pathogenesis and how potential therapeutic interventions targeting the microbiome could mitigate these conditions. Through microbiome profiling and clinical data collection, we analyzed the gut microbial composition in individuals with autoimmune diseases (such as rheumatoid arthritis and Type 1 diabetes) and metabolic disorders (such as obesity and Type 2 diabetes). Our results reveal significant differences in the microbiota of patients compared to healthy controls, with autoimmune patients showing reduced levels of beneficial bacteria like Faecalibacterium prausnitzii and an increase in pro-inflammatory species such as Prevotella copri. In metabolic patients, an imbalance between Firmicutes and Bacteroidetes was found to correlate with increased insulin resistance and glucose intolerance. Moreover, probiotic intervention was shown to improve microbiome diversity and reduce disease severity in autoimmune patients, offering promising therapeutic potential. The study also highlights the use of AI-driven models in predicting disease outcomes and personalizing treatments, although challenges remain in implementing these technologies in clinical settings. Overall, the findings suggest that gut microbiota plays a critical role in autoimmune and metabolic diseases, offering new avenues for therapeutic interventions and emphasizing the importance of microbiome-based strategies in clinical practice.
subject: Health and Life Sciences
  topic: section
subject: Gut Microbiota
  topic: keywords
subject: Autoimmune Disorders
  topic: keywords
subject: Metabolic Disorders
  topic: keywords
subject: Probiotics
  topic: keywords
subject: Disease Prediction
  topic: keywords
subject: Inflammation
  topic: keywords
creator: Hassan Yar Mahsood
creator: Abdul Ghaffar
rights: Copyright (c) 2023 Hassan Yar Mahsood, Abdul Ghaffar (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2023-06-30
publication date: 2023-06-30
starting page: 102
ending page: 116