Policy Research Journal (PRJ) , ISSN (E): 3006-7030 ISSN (P) : 3006-7022, published by the Pinnacle Academia Research & Education, serves as a distinguished platform for scholarly discourse. As a multidisciplinary, open-access, and quarterly journal, it stands at the forefront of academic inquiry. Policy Research Journal upholds rigorous standards of excellence. Committed to fostering a culture of academic integrity and transparency, Policy Research Journal prioritizes the expeditious completion of the double-blind peer-review process. With an unwavering dedication to scholarly rigor, our team endeavors to provide timely feedback to authors within one month of submission, ensuring a seamless and efficient publication experience. The journal welcomes papers of the highest quality in the following domains, both established and emerging; Business & Economics Education, Language, & Literature Journalism, Law, & Political Sciences History & Regional Studies Psychology & Sociology Arts & Humanities Sports Sciences Engineering Agriculture Sciences Earth Sciences Data Sciences [ Mathematics, Statistics, Computer Science, and Artificial Intelligence] The respective authors hold copyrights of all content published in the journal.
ASSESSING VULNERABILITY AND ADAPTIVE CAPACITY: CLIMATE CHANGE ADAPTATION STRATEGIES AMONG SMALLHOLDER FARMERS IN BANNU DISTRICT, PAKISTAN
This study explores the adaptation strategies to climate change adopted by smallholder farmers in District Bannu, Khyber Pakhtunkhwa, Pakistan. For this purpose, primary data were randomly gathered from 73 sampled smallholder farmers through a structured questionnaires and interviews schedule method. Descriptive statistics and binary logistic regression model were used to analyze the socio-economic characteristics of smallholder famers and factors effecting adaptation strategies. The findings revealed that middle aged, literate farmers with more farming experience and medium landholdings size are most probably to adopt climate adaptation strategies such as organic fertilizers, drought resilient crops, change planting periods and diversification of crop. The results further indicated that increase temperatures, Decrease/erratic rainfall, Crop diseases and Water shortage as a major climate related challenge faced to smallholder farmers. Moreover, major hurdles faces in adaptation strategies were comprises lack of funds, inadequate knowledge, and weak institutional support. The regression model analysis also indicated that the coefficient and P-value for Climate risk was (β = 0.269, P = .006), for Age was (β= .148, P = .022), for education (β = .223, P = .029), and for farming experience (β= 0.321, P = .046), while for landholding size (β= 0.481, P = .029) had significantly influenced adaptation strategies. This study emphasize the need for targeted interventions to support adaptive capability and promote sustainable agriculture among smallholder farmers. It is recommended that government and NGOs should improve farmer training programs and ensure regular, accessible extension services focused on climate resilient agricultural practices and financial institutions and agricultural support organizations should design accessible credit schemes and inputs subsidies to facilitate widespread adoption of climate adaptation strategies.
REGIONALISM FROM WITHIN: THE ENDOGENOUS CHALLENGES TO SOUTH ASIAN FUNCTIONAL INTEGRATION
As the world continues to reap benefits of effective regionalism especially in areas of low politics corroborated from the success stories of EU, ASEAN, NAFTA, GCC etc., it is the South Asian regionalism that continues to be moribund to the extent it seems to have come to an end particularly given the recent developments in South Asian regional context signified by the complete breakdown of regionalist schemes including SAARC. Despite continued efforts to reinvigorate regional integration, SAARC continues to experience comatose. Through employing an endogenous approach of regionalism to analyze South Asian functional integration, the paper attempts to critically delineate endogenous factors contributing to fracturing South Asian regionalism. The paper finds that the endogenous factors rooted in politico-security, economic and social/societal aspects play as causative catalysts in hindering successful development of South Asian functional integration. The paper also utilizes the theoretical framework of “regionness” to draw significant insights regarding the developmental limitations of South Asian functional integration. The study is imperative as it takes a comprehensive yet diagnostic analysis of the issue identified. Although much has been documented on the issues of South Asian regionalism, this study attempts to theorize the problem from an endogenous perspective of regionalism, especially from the perspective of “regionness” which remains the most effective paradigm for studying regional integration dynamics.
THE ROLE OF GREEN FINANCE AND FINANCIAL INCLUSION IN ADVANCING SUSTAINABLE DEVELOPMENT: INSIGHTS FROM A BIBLIOMETRIC ANALYSIS
The convergence of financial development objectives, green finance, and financial inclusion has attracted significant attention in the academic world amid challenging concerns about sustainable growth, economic inequalities, and climate change. This paper aims to thoroughly examine the current research in these interlinked fields by utilising advanced bibliometric tools to compile and review a large body of literature. By employing visualisation software such as "VOS-Viewer" and the "Biblioshiny" R package, this study examines literature from the Scopus database spanning 2009 to 2023. This study used the PRISMA statement to conduct a systematic, bibliometric analysis to reveal and understand knowledge structures, pinpoint research gaps, and identify emerging topics in sustainable growth, green finance, and financial inclusion. The results demonstrate an increasing amount of scholarly work acknowledging the potential of financial inclusion and green finance to contribute to achieving sustainable development goals. This study explores citation links between significant articles to provide valuable insights that guide researchers toward unexplored areas. Emphasising environmentally and socially responsible banking practices, the paper anticipates future trends, particularly in the context of China's financial influence, and underscores the importance of integrated approaches for harmonising economic development with environmental responsibility. Overall, the study aims to serve as a navigational tool for scholars, helping them understand the current research landscape and fostering further advancements across these interrelated areas.
EXPLORING BUSINESS SCHOOLS’ READINESS FOR SMART HRM 4.0: CURRICULUM TRANSFORMATION AND PEDAGOGICAL INNOVATION
The Age of Cyber-Physical or the Smart Industry eras are some other names for the Fourth Industrial Revolution. It has a significant impact on every aspect of life, particularly organizational management processes and practices. Smart technologies such as Big Data, the Internet of Things, Cloud Computing, and Artificial Intelligence-based automation have reshaped processes and practices of supply chain management, contributing to the emergence of the Fourth Industrial Revolution. Human Resources Management's traditional functions are going through a significant transformation. This cyber-physical revolution has enabled HRM functions and practices to be digitally integrated through smart technologies to collectively achieve organizational objectives. HRM professionals must be equipped with new skills sets in the era of Smart Industry. Universities have a responsibility to skill up the proposed professionals to fulfil the workforce market demands of the fourth industrial revolution. This study explores universities Readiness for offering Smart HRM 4.0 courses and their teaching in Khyber Pakhtunkhwa, Pakistan. The study unpacks the current status of university curriculum, and teaching-learning practices in light of Smart HRM4.0 course teaching and learning requirements. The findings and reflections highlighted the different universities' initiatives, making changes in the Business Curriculum by integrating smart technology embedded HRM courses, in addition to identifying various gaps in the curriculum to incorporate smart technology integration. The study also reveals gaps in teaching staff skills and competencies, besides strong enthusiasm for technology adoption. This study adopts a qualitative approach, grounded in relativist ontology and a subjectivist epistemology within a constructivist paradigm. Guided by a phenomenological methodology, this study sought to understand the lived experiences of university HRM teachers through in-depth interviews. The interviews data were analyzed using Braun and Clarke’s reflective thematic analysis, with themes developed through the researcher’s reflexive interpretation of participants’ accounts at a latent level of meaning. This study contributes to the existing literature by sharing in-depth contextual readiness level of Business Schools' Curriculum for Smart HRM 4.0 students’ preparedness. These findings will inform the development of strategies for universities to upgrade curricula, teaching staff competencies, and teaching practices to support modern technology-based teaching and learning environments.
IMPACT OF EMOTIONAL INTELLIGENCE ON SOFTWARE PROJECT LEADERSHIP AND TEAM PERFORMANCE
Software projects have appalling 68% failure rates even after decades of agile practices and technological improvements, and thus, it is necessary to explore human factors outside of coding competencies. This sample-sized mixed-methods analysis (n=250 Pakistani software workers; 25 interviews) demonstrates that emotional intelligence (EI) is the ultimate predictor, which elucidates 61% of the team performance variance (R 2=0.61) based on SEM-established mediation pathways through which EI improves leadership effectiveness ( B=0.45, p=0.01), which then transfers to multidimensional high performance in terms of sprint velocity, defect reduction, cohesion, stress resilience, Correlation analysis shows empathy (r=0.68) and social skills (r=0.72) to be the most important drivers, whereas NVivo thematic analysis (κ=0.82) shows that retrospective empathy (28% dominance) turns blame cycles into learning loops, eliminating typical low-EI failures of the weak link nature. Uniform performance is observed in high-EI teams without performance bottlenecks that plague technical-only interventions and they do not accept the paradigm of IQ which establishes no relation between leadership variance and any other factor (R 2 <0.30). In practice, each 1 SD EI gains 32% team uplift, twice that of automation ROI, making sprint-1 empathy training a 2.4M/year savior to Faisalabad IT firms with margin constraints, where 30-40% project pressures are forcing them to outsource. Theoretically, this triangulation addresses gaps in agile scholarship because it quantifies the so-called multiplier of soft skills that have failed to be quantified in maturity models, which makes EI a higher-order construct that mediates technical execution via emotional infrastructure. Such results force paradigm shift of outlying " nice to have" behavior of mission-key doctrine that provided blueprint reduction of industry failure rates by half. The generalizability of hierarchical cultures and the prescription of specific interventions are proven by the Pakistani contexts: the retrospective empathy coaching helps to avoid 68% human-factor cascades. This unified model, which combines SEM trajectories, correlation networks, radar superiority, and narrative mechanisms, is what will make emotionally intelligent leadership the ultimate success factor in software project.
AGILE VS. WATERFALL: COMPARATIVE ANALYSIS IN SOFTWARE PROJECT MANAGEMENT
One of the major problems in managing software projects is the choice of the correct software development methodology based on the degree of requirements stability, level of risks and expectations in the delivery of software projects. This paper gives a comparative evaluation of Agile and Waterfall methodologies along with the Decision Support Matrix (DSM) that is created to assist in choice of methodology based on factors of requirement volatility, documentation needs, stakeholder involvement, team expertise and urgency of need to deliver. Three real-life project situations are used to assess the applicability of Agile, Waterfall and Hybrid models through the use of DSM. Literature has shown that Agile is more effective in projects that change frequently and have more frequent release cycles whereas Waterfall is more effective in stable and highly controlled projects. Hybrid models are flexible enough and offer an organized approach in cases where there is need to achieve both. These results indicate that the proposed DSM is a useful, systematic and evidence-based model to be used when choosing the best development methodology.
MANAGING SOFTWARE PROJECT COSTS: TECHNIQUES AND BEST PRACTICES
Cost management has been a long-time issue in software project development where cost overruns have been recorded to be more than 30-50 percent of the original budget as a result of poor estimation, scope creep as well as poor practices. The paper proposes a hybrid Function Point Analysis (FPA) and Machine Learning (ML) model that is able to predict costs of software projects classified into low, medium, and high categories to respond to deficiencies in other traditional methods, including COCOMO II, most of which depends on outdated and historical data. The methodology uses the existing FPA to perform the accurate functional sizing step and then apply the ML algorithms, like Random Forest and Support Vector Machines (SVM), to learn the required predictions. The accuracy on the model was 88.33 with a 0.89 (low), 0.86 (medium), and 0.94 (high) precision rates and a 0.91, 0.82, and 0.94 recall respectively. It has been verified using confusion matrices and training graphs that high-cost projects are robust. A comparative analysis shows better results than benchmarks: 6-13% accuracy improvements compared to COCOMO II, FPA-ANN (Jorgensen, 2014), and Agile Cost Models, due to the adaptability of ML to current complexities such as AI/ML projects and hybrid Agile-Waterfall environments. Combining predictive analytics and structured sizing, the method allows identifying early risks, allocating resources in the most efficient way possible, and making improved decisions, minimizing overruns and maximizing ROI. The additions to be made to it in the future will incorporate AI-specific features, deep learning, and the application of hybrid methodology to achieve greater scalability.
HYBRIDITY AND AMBIVALENCE IN SAADAT HASAN MANTO’S TOBA TEK SINGH: A POSTCOLONIAL ANALYSIS OF PARTITION IDENTITY
The article uses Homi K Bhabha's hybridity and ambivalence concepts to study Saadat Hasan Manto's Toba Tek Singh because these concepts show how the story fits into present-day postcolonial discussions about national boundaries and identity development. The text has been treated by Partition scholarship as political satire and historical trauma depiction but this study shows that Manto presents a more radical critique which questions the knowledge basis of nationalist identity. The article uses textual analysis and critical analysis to show how the asylum functions as a Third Space which leads to the disintegration of territorial boundaries and the destruction of nationalist cultural claims through linguistic disintegration and Bishan Singh's final body paralysis which shows the hidden violence within sovereign mapping systems. The story uses hybridity to create a disruptive force which breaks down territorial boundaries while ambivalence demonstrates the fundamental instability which exists in postcolonial government structures. The article shows how Toba Tek Singh uses spatial and linguistic and psychological dislocation to create modern border politics and national essentialism critiques which extend Partition literature theoretical understanding beyond its historical context.
POLICY BRIEF ON PROMOTING SUSTAINABLE ASSEMBLY PRACTICES IN PAKISTAN: POLICY PATHWAYS FOR TRACTOR ENGINE TESTING AND ENERGY EFFICIENCY
The agricultural tractor has become important in the farming industry of Pakistan as it allows effective land clearing and lowers the cost of operation. However, the traditional methods of testing tractor engines applied in the assembly plants are based on long-term heavy-load dynamometer assessments that lead to excessive fuel consumption, heavy energy waste, and unnecessary greenhouse gas emission. This paper critically analyses the current methodologies of engine testing practiced by the tractor manufacturing industry in Pakistan and brings to the fore the implications of such methodologies on the environment and economy. A proposed hybrid testing framework is more advanced with the integration of simulation, to replace traditional one. The structure has focused on computer-aided engineering (CAE) instruments, IoT-based monitoring, integration of renewable energy and effective use of tried engines to produce electricity. Implementation of sustainable testing processes can cut down on the amount of waste in fuel each year, decrease the operational costs, decrease the emission of greenhouse gases, and towards Sustainable Development Goals (SDG 7, SDG 12, and SDG 13). The proposed solution also offers a viable avenue through which energy saving practices in industrial assembly can be promoted in Pakistan.
EXPLORING THE POTENTIAL KEY FACTORS TO ANALYZE THE IMPACT OF AI IN BUSINESS DECISION MAKING
Artificial intelligence (AI) plays a crucial role in business decision making while impacting the firm wide performance, organizational processes and overall reputation. This study explores the potential of AI as advance technological tool in transforming the strategic decision making thus enhancing the business outcomes. A systematic protocol has been followed for selection of relevant literature by utilizing the renowned search engines like Google Scholar and IEEE Xplore to identify the high quality published studies. After a thorough literature survey it has been assessed that AI significantly contributes to financial outcomes, productivity and sustainability thus driving a substantial business growth and adaptability. AI also influence the organizational reputation by shaping the customer’ trust but transparency is prior condition in AI driven systems which can be ensured by understanding the technical aspects of AI. Conclusively AI act as a powerful catalyst in decision making while delivering the measurable improvements, innovation and highlighting the critical need for transparency and trust to ensure the overall sustainability.
SEISMIC PERFORMANCE EVALUATION OF REINFORCED CONCRETE BUILDINGS IN HIGH-RISK ZONES
Reinforced concrete (RC) buildings remain the dominant structural form in seismically active high-risk zones, yet they continue to exhibit significant vulnerabilities during major earthquakes due to limitations in traditional design and evaluation approaches. This study presents a comprehensive review of contemporary seismic performance assessment methodologies for RC buildings, highlighting the shift from force-based to performance-based engineering paradigms. Key topics include the comparative advantages and limitations of linear (Equivalent Static and Response Spectrum) versus nonlinear (pushover, time-history, and incremental dynamic) analysis procedures; the critical influence of structural irregularities, masonry infill configurations (including soft-story and short-column effects), and soil-structure interaction (SSI); and the implications of mainshock-aftershock sequences on collapse capacity and residual drift. The paper examines international seismic evaluation standards (ASCE 41, Eurocode 8), forensic lessons from recent devastating events (Türkiye 2023, Japan 2024, Nepal 2015), and emerging resilience-enhancing technologies such as FRP/TRM jacketing, viscous dampers, shape memory alloys, and base isolation. Additionally, the transformative role of machine learning techniques (e.g., XGBoost, Random Forest, SVR) combined with interpretability tools (SHAP) for rapid regional vulnerability assessment is discussed. The synthesis underscores the necessity of holistic, nonlinear, and probabilistic frameworks that integrate structural, geotechnical, and non-structural factors to achieve improved seismic resilience in high-risk regions.
ELECTRONIC BAND STRUCTURE ENGINEERING OF TWO-DIMENSIONAL MATERIALS FOR HIGH-PERFORMANCE DEVICES
Two-dimensional (2D) materials have emerged as a cornerstone for next-generation nanoelectronics and optoelectronics, offering atomically thin channels, exceptional carrier mobilities, and unprecedented tunability of electronic band structures. This review comprehensively examines strategies for engineering the band structure of representative 2D systems including graphene and Xenes, transition metal dichalcogenides (TMDs), black phosphorus, and MXenes to overcome the limitations of conventional silicon-based devices in the sub-10 nm regime. Key approaches include straintronics (mechanical deformation inducing direct-to-indirect transitions and bandgap shifts of up to 100 meV per % strain), twistronics and moiré superlattice engineering (realization of flat bands, correlated states, unconventional superconductivity, and moiré excitons at magic angles), surface functionalization and charge-transfer doping (precise control of carrier type and density), and valleytronic manipulation (exploitation of spin-valley locking and Berry curvature dipoles for low-power information processing). These techniques enable high-performance field-effect transistors with on/off ratios exceeding 10⁸, subthreshold swings approaching the 60 mV/decade limit, ultra-sensitive photodetectors (responsivities >10⁵ A/W), and flexible energy-storage devices. Artificial intelligence-driven inverse design and high-throughput computational screening accelerate discovery of novel 2D phases and optimized heterostructures. Despite remarkable laboratory demonstrations, challenges in large-area synthesis, environmental stability, reliable transfer processes, and reproducible moiré-angle control remain critical barriers to commercialization. Addressing these bottlenecks through advances in direct-growth methods, robust encapsulation, and scalable strain/twist engineering will be essential to realize the full potential of band-structure-engineered 2D materials in energy-efficient logic, quantum devices, and wearable technologies.
IMPACT OF JUDICIAL ACTIVISM ON PUBLIC TRUST IN THE LEGAL SYSTEM: THE MODERATING ROLE OF MEDIA EXPOSURE IN PAKISTAN
This study examines the influence of judicial activism on public trust in Pakistan’s legal system, with media exposure conceptualized as a moderating variable. Utilizing survey-based quantitative data, the findings indicate that judicial activism exerts a significant positive effect on public trust, with approximately 56% of respondents reporting confidence in judicial institutions. Media exposure significantly moderates this relationship: when media coverage frames judicial decisions as rights-protective and constitutionally grounded, the positive impact of judicial activism on public trust is amplified, whereas negative or politicized framing attenuates trust. Regression analysis combined with a systematic review of media content demonstrates that balanced and ethical media reporting is essential for reinforcing the legitimacy of judicial interventions and sustaining public confidence in Pakistan’s judiciary.
HUMAN REGIONAL SECURITY IN SOUTH ASIA: A DECADE OF CHALLENGES AND PROSPECTS (2015-2025)
The current paper examines Human Regional Security within South Asia according to multidimensional mixed-method research design in order to integrate quantitative measures with qualitative research design. The study identifies four primary dimensions of human security, namely the economic, environmental, political and social dimensions of human security according to the statistics of the World Bank, UNDP, IPCC and Transparency International (2015-2025) in six South Asian countries, including India, Pakistan, Bangladesh, Nepal, Sri lanka, and Afghanistan. The findings show that the long term average economic growth of South Asia is 5.8 percent annually but the benefits have not been distributed equally hence resulting in high poverty and inequality rates. Environmental insecurity, particularly the lack of water and calamities brought about by climatic change, complements the socio-economic instability. There are also problems of governance like corruption, inefficient institutions, and deterioration of civil liberty that are also disincentives to development. Empirical results of statistical findings showed that there is a negative relationship between defense expenditure and human development (r = -0.47) and gender equality as well as human development (r = 0.68) which validates Human Security paradigm over the old state-centric paradigms. The analysis presents a proposal, namely, Integrated Human Regional Security Model (IHRS), as a definition of an understanding of the results founded on the theory of Realism, Liberal Institutionalism, Constructivism, and Human Security, which provides a linkage between the national stability and personal well-being with the collaboration between the regions. The researchers also point out the conclusion that it is not the militarization and economic growth of South Asia but investment in human development, inclusive governance, gender empowerment, and climate resilience that leads to the long term peace of South Asia.
COMPARATIVE PERFORMANCE ANALYSIS OF HIGH-STRENGTH CONCRETE AND NORMAL-STRENGTH CONCRETE: A COMPREHENSIVE REVIEW
This study presents a comprehensive comparative analysis of high-strength concrete (HSC) and normal-strength concrete (NSC) with respect to their mechanical properties, durability performance, structural applications, and sustainability aspects. Normal-strength concrete, typically ranging between 20–40 MPa compressive strength, has long been used in conventional construction; however, high-strength concrete, exceeding 60 MPa, has emerged as a superior material for modern infrastructure due to its enhanced strength, durability, and reduced permeability. The review examines key differences in compressive strength, tensile strength, elastic modulus, ductility, and long-term durability characteristics such as chloride penetration resistance, carbonation depth, and freeze–thaw performance. Furthermore, the role of supplementary cementitious materials, fiber reinforcement, recycled aggregates, and nanomaterials in improving concrete performance is discussed. The findings indicate that while HSC offers superior mechanical and durability properties suitable for high-rise buildings, bridges, and aggressive environmental conditions, NSC remains advantageous in terms of cost-effectiveness, workability, and construction simplicity. The study highlights the importance of selecting appropriate concrete types based on structural requirements, environmental exposure, and sustainability considerations, providing valuable insights for engineers, researchers, and construction professionals.
BARRIERS TO STRATEGIC HRM INTERVENTIONS AND THEIR INFLUENCE ON ORGANIZATIONAL PERFORMANCE: EVIDENCE FROM RECRUITMENT, TRAINING CURRICULUM, AND WORK-LIFE BALANCE PRACTICES IN PUNJAB POLICE
The paper has examined the major issues and obstacles involved in the application of the HRM intervention-based policies and analyzed the strategic HRM interventions that can be applied in order to increase employee performance and organizational performance in the Punjab Police. The research took the form of a qualitative study because it concentrated on three fundamental areas of HRM that include recruitment and selection, training curriculum and pedagogy, and work-life balance practices. Semi-structured interviews with 18 key informants purposely selected were used to gather the data, whose roles in the study included senior police officers, HR officials, training instructors, psychologists, welfare officers, as well as policy experts of the Bahawalpur region. Thematic analysis was utilized with the assistance of methodological triangulation to determine recurrent institutional, structural, and operational problems that impacted the implementation of HRM policy. The results to the first research question showed that the old and rigorous recruitment standards, post-selection psychological testing, low intake of recruits into the unit, and rigidity in the bureaucracy, training curricula that was traditional and relatively drill-based, poor experiential learning, heavy load, inconsistent duty hours, poor enforcement of welfare policies, and low mental support were significant obstacles to effective HRM interventions. All these issues led to burnout, skills gap, lack of motivation, operational exhaustion, and poor organizational performance. To answer the second research question, the study developed a group of context-specific strategic HRM strategies in accordance with the modern requirements of policing and the international benchmarks. These had a competency-based and merit-oriented recruitment process with pre-induction psychological evaluation, modernization of training programs by integrating cybercrime, community policing, and learning scenarios, ongoing professional development systems, work and shift scheduling, institutionalized work-life balance programs, and integrated psychological and welfare support. They highlighted that working to harmonize HRM reforms with international standards of policing and contextualizing them to local institutional realities might be of great help to increase workforce capacity, involvement, and professional strength. The credibility and validity of the findings were enhanced due to the triangulation of the multi-stakeholder perspectives with the current scholarly and policy literature. In general, the research finds that to address the issues of structural and implementation-level barriers, consistent strategic HRM reforms will be necessary to enhance the performance of both employees and the organization, its efficiency, and effectiveness to foster long-term organizational modernization and better service delivery to the population.
DEMOCRACY IN SOUTH ASIA: A COMPARATIVE STUDY OF PAKISTAN AND INDIA
This research aims to compare the democratic systems of India and Pakistan, with an emphasis on democratic stability, political institutions, and governance mechanisms. It identifies key variables that affect the functioning of democracy in both states. Despite having a similar colonial past, Pakistan and India have had distinct democratic paths since gaining their independence. Pakistan has endured several political upheavals and military interventions, whereas India has seen a rather stable democracy. Using secondary data from books, reports, and academic publications, the study takes a qualitative comparative approach. Important democratic metrics, such as the rule of law, civil-military relations, and electoral procedures, are examined. The findings show that civilian supremacy and institutional strength have aided in India's democratic consolidation. On the other hand, Pakistan's democratic progress has been impeded by weak institutions and political instability. Pakistan's democratic stability depends on bolstering democratic institutions and guaranteeing constitutional primacy. To strengthen democracy, both states should support inclusive government, judicial independence, and political accountability.
DOES PAKISTAN'S CONSTITUTIONALISM ORCHESTRATE LIMITED GOVERNMENT?
The essence of a constitutional system lies in two key aspects: limiting state power and ensuring the supremacy of rights, particularly the protection of human rights and freedoms. Without mechanisms to limit state power, the state inevitably encroaches on society and the private lives of individuals, threatening their rights and freedoms. Pakistan’s constitutionalism is designed to promote a limited government through a system of checks and balances. The 1973 Constitution establishes a parliamentary democracy with a bicameral legislature, ensuring separation of powers among the executive, legislature, and judiciary. The features of Constitution’s design show how the principles of limited government are implemented, including constitutional constraints, due process of law, a system of checks and balances, protection of individual rights as prescribed in the constitution, and mechanisms for holding government officials accountable for their actions. However, the implementation and interpretation of these principles can be complex and sometimes contentious. This research will carry the Doctrinal Method to explore how constitutionalism can be achieved by executing the tenets the limited Government in state apparatus of Pakistan.
IMPACT OF ENABLERS AND BARRIERS FOR COMPLIANCE WITH INTERNATIONALLY ACCEPTED QUALITY STANDARDS IN THE PHARMACEUTICAL INDUSTRY OF PAKISTAN
Introduction: Drug safety, product reliability, and international market access rely on compliance with internationally accepted pharmaceutical standards of quality. In the case of developing nations like Pakistan, the pharmaceutical companies tend to have issues with adoption of superior regulatory frameworks as a result of financial, technological and institutional limitations. It is hence important to come up with an understanding of what affects compliance in order to enhance quality assurance practice in the pharmaceutical industry. Purpose: The purpose of the study was to investigate the enablers and limitations influencing the adherence to internationally recognized quality standards in pharmaceutical industries in Karachi, Pakistan. Methodology: A qualitative research design was followed through replica study. The interviews showed that 20 professionals working in the quality assurance, production management, regulatory affairs, and quality control departments in pharmaceutical companies were interviewed semi-structurally and using interviews. Thematic analysis was adopted to analyse the obtained data, to reveal major patterns associated with the regulatory awareness, organisational practices, barriers, as well as enabling factors contributing to compliance. Findings: The findings revealed that the biggest barriers to compliance were financial constraints, lack of skilled labor force, technological constraints and regulatory delays. Meanwhile, organisational facilitators like employee education, executive buy-in, internal quality inspection and technology improvements were also significant towards the compliance with global standards. The familiarity with WHO GMP was rather high and the familiarity with more stringent international standards of GMP like EU GMP and US FDA standards was relatively low. Conclusion: The paper concludes that to enhance pharmaceutical quality compliance in Pakistan, it is important to enhance workforce training, as well as organisational quality management systems, and regulatory transparency and institutional support.
DELAY IN JUSTICE IN HIGH-PROFILE HOMICIDE TRIALS: EVIDENCE FROM THE NOOR MUKADAM CASE IN PAKISTAN
To start with, the issue of delay in criminal verdicts appears to be the most serious problem of the justice systems. This paper is the one that investigates the problem of justice delay at the systemic level by means of a detailed case study of the murder trial of Noor Mukadam in Pakistan. It was the Islamabad sessions court which sentenced Zahir Jaffer to death in February 2022, while his other two guards accused were sentenced to custodial terms. Besides the presence of compelling evidence and public attention, the case gives the main perspective through which the procedural impediments in the criminal courts may be dissected. This work is based on the qualitative case study method of research and uses court judgments, charge sheets, and procedural documents. An extensive timeline and process mapping technique is employed to identify major stages in the course of the investigation, prosecution, trial, and sentencing. The results indicate that besides the fact that the delivery of justice was delayed by several sources among which were the lack of coordination between the investigative and prosecutorial agencies, the repeated procedural adjournments, the delayed forensic processes, and the complexities around the treatment of the co-accused. The interview revealed that disregard to the management of cases, accountability mechanisms, and time-fixed trial practices for serious violent offenses were the areas that needed an immediate change. Through the research, it is revealed that the publicized cases do not always lead to systemic efficiency and rather, they expose the continued weaknesses of the criminal court system. The paper goes further to offer evidence, based insights that could be used for reforming courts and the correction system in the jurisdictions with similar justice structures.
PHYSICOCHEMICAL, PHYTOCHEMICAL, AND SENSORY EVALUATION OF COOKIES FORTIFIED WITH JUJUBE POWDER
The current study was conducted to fabricate cookies supplemented with various concentrations (0, 4, 8, 12, and 16%) of jujube powder. Cookies were analyzed for proximate composition, physical properties, phytochemical characterization, and sensory evaluation. Results showed that the addition of jujube powder significantly (p<0.05) affected the proximate composition, especially fiber and ash contents. Incorporation of jujube powder increased the total phenolic contents (18.5 to 51.3 mg GAE/100g), total flavonoid contents (6.2 to 19.4 mg QE/100g, and antioxidant activity (22.4 to 58.6%). Similarly, physical properties and color (change in color, chroma, and whiteness index) were significantly changed with the supplementation of jujube powder in cookies. Moreover, the sensorial attributes results indicated that adding 8% jujube powder to cookies was acceptable. Conclusively, the results suggest that the incorporation of jujube powder can successfully enhance the functional value of cookies while maintaining acceptable sensory quality.
A SYSTEMATIC REVIEW OF SHEAR STRENGTH PREDICTION MODELS FOR REINFORCED CONCRETE BEAM–COLUMN JOINTS UNDER CYCLIC SEISMIC LOADING CONSIDERING JOINT GEOMETRY, REINFORCEMENT DETAILING, AND AXIAL LOAD INTERACTION
Reinforced concrete (RC) beam-column joints are critical structural components that significantly influence the seismic performance and overall stability of buildings. The shear strength prediction of these joints under cyclic seismic loading is a complex problem that depends on multiple interconnected parameters including joint geometry, reinforcement detailing, and axial load ratios. This systematic review comprehensively examines existing shear strength prediction models for RC beam-column joints under cyclic seismic loading, with particular emphasis on design code provisions, experimental evidence, and analytical approaches. A critical evaluation of approaches including strut-and-tie models, design code formulations, and empirical equations reveals significant variations in prediction accuracy and safety margins across different methods. Recent advances in machine learning and finite element analysis have demonstrated improved prediction capabilities, with coefficient of determination (R²) values exceeding 0.99 for neural network models compared to 0.83-0.85 for conventional design codes. The analysis of 50+ peer-reviewed studies shows that reinforcement detailing, particularly the provision of transverse reinforcement, is paramount in controlling shear failure modes and enhancing joint ductility. Furthermore, axial load effects introduce nonlinear interactions that current design codes inadequately capture, potentially leading to unconservative designs. This review synthesizes findings on the influence of key parameters including joint aspect ratio, concrete strength, reinforcement ratio, and axial load ratio on joint shear strength. Recommendations are provided for improving design methodologies and implementing performance-based design approaches for seismic applications. The findings emphasize the critical need for unified design criteria and the potential benefits of integrating advanced computational methods with experimental validation.
SMARTER RISK, STRONGER BANKS: HOW MACHINE LEARNING, ACCURATE PREDICTIONS, AND BOARD OVERSIGHT ENHANCE BANKS FINANCIAL STABILITY
This study examines how machine learning based risk management influences bank financial stability, with risk prediction accuracy acting as a mediating mechanism and board oversight serving as a moderating factor. Drawing on agency theory, the research investigates how improved information processing and governance oversight contribute to more stable financial outcomes. A quantitative cross sectional research design was employed, and data were collected from managerial employees working in the banking sector. The data were analyzed using structural equation modeling through SmartPLS, enabling simultaneous evaluation of measurement and structural models. The findings reveal that machine learning based risk management significantly improves financial stability and enhances the accuracy of risk prediction. The results further demonstrate that prediction accuracy mediates the relationship between machine learning adoption and financial stability, indicating that predictive capability is a key mechanism through which technological tools influence financial outcomes. Additionally, board oversight significantly strengthens the relationship between prediction accuracy and financial stability, highlighting the importance of governance mechanisms in supervising technology driven decision systems. The study contributes to the literature on financial risk management and digital governance by integrating technological capabilities, predictive mechanisms, and governance oversight within a unified analytical framework. The findings offer valuable implications for financial institutions, policymakers, and scholars seeking to understand how advanced analytical technologies and governance structures can jointly enhance financial stability in modern banking systems.
DISTRIBUTED LEADERSHIP MODELS AND THEIR INFLUENCE ON COLLABORATIVE SCHOOL CULTURE AND TEACHER EMPOWERMENT
Distributed leadership has emerged as a transformative paradigm in educational administration, shifting the focus from heroic, hierarchical models to collective, interactive processes that stretch leadership practice across formal and informal roles within schools. This study synthesizes theoretical foundations (Spillane’s distributed perspective, activity theory, distributed cognition) and empirical evidence on how distributed leadership fosters collaborative school cultures and empowers teachers. Key mechanisms include shared decision-making, teacher leadership roles, professional learning communities, collective teacher efficacy, and relational trust, which collectively enhance teacher agency, job satisfaction, professional learning, and commitment. Cross-cultural studies from diverse contexts (North America, Asia, Europe, Middle East) demonstrate consistent positive associations between distributed leadership practices and improved organizational climate, instructional innovation, accountability, and student outcomes, with mediating roles played by collective efficacy and teacher professionalism. The model proves particularly effective in complex, reform-driven environments by building adaptive capacity and reducing reliance on individual leaders. Challenges such as role ambiguity, resistance to power redistribution, and implementation fidelity are acknowledged, alongside recommendations for principal support in cultivating distributed structures. Overall, distributed leadership offers a realistic and sustainable framework for cultivating empowered, collaborative school communities capable of sustained improvement.
EFFECT OF SPORTS AND EXERCISE ON THE PHYSICAL AND MENTAL HEALTH OF SCHOOL-GOING CHILDREN
Background: Sports and regular physical exercise are widely recognized as key determinants of physical and mental health during childhood and adolescence. The age range of 11–18 years represents a critical developmental stage marked by rapid physical growth and psychological changes. Despite this, reduced physical activity and increased sedentary behaviour among school-going children have raised concerns regarding health and well-being. This study aimed to examine the effect of sports and exercise on the physical and mental health of school-going children. Methods: A cross-sectional quantitative study was conducted among 2000 school-going children aged 11–18 years. Participants were selected using a multistage sampling technique from public and private schools. Data were collected using standardized questionnaires assessing sports and exercise participation, physical health indicators, and mental health status. Physical health outcomes included fitness and perceived health, while mental health was measured through validated scales assessing stress, anxiety, depression, and self-esteem. Data were analysed using descriptive statistics, Pearson correlation, and multiple linear regression analysis. Statistical significance was set at p < 0.05. Results: Regular participation in sports and exercise demonstrated a significant positive association with physical health (r = 0.62, p < 0.001) and mental health (r = 0.58, p < 0.001). Regression analysis indicated that sports and exercise significantly predicted physical health outcomes (β = 0.47, p < 0.001) and mental health outcomes (β = 0.42, p < 0.001), after controlling for age and gender. Students with higher levels of physical activity reported lower stress and anxiety scores (p< 0.01) and higher self-esteem (p < 0.001). Additionally, physical activity was positively associated with concentration and academic engagement (r = 0.39, p < 0.001). Conclusion: The findings indicate that sports and exercise have a significant and positive effect on both physical and mental health among school-going children aged 11–18 years. Regular participation in physical activity is associated with improved fitness, enhanced psychological well-being, and better academic engagement. The study highlights the importance of integrating structured sports and exercise programs into school curricula to promote holistic development and long-term health among children and adolescents.
MATHEMATICAL MODELING OF KNOWLEDGE TRANSMISSION IN A CLASSROOM USING THE SIR FRAMEWORK
This study presents a mathematical analysis of a Susceptible–Informed–Recovered (SIR) model to describe the spread of knowledge in a classroom environment. The model divides students into three compartments: susceptible students who have not yet understood a concept, informed students who have learned the concept and can assist others, and recovered students who have fully mastered the concept. The model incorporates learning transmission and knowledge mastery rates to represent realistic classroom interactions. The existence and uniqueness of solutions are established using the Lipschitz condition, ensuring that the model is mathematically well-posed. Positivity of solutions is proved to guarantee that all state variables remain non-negative over time. An invariant region is derived to demonstrate that the total number of students remains bounded. The knowledge-free equilibrium is determined and analyzed as the baseline state where no students have learned the concept. A threshold parameter analogous to the basic reproduction number is computed to measure the effectiveness of knowledge transmission in the classroom. Local stability of the equilibrium is examined through Jacobian matrix and eigenvalue analysis, showing stability when the threshold parameter is less than unity. Furthermore, a Lyapunov function is constructed to establish global stability under the same condition. The results provide theoretical insights into how knowledge spreads through peer interaction and instruction. Overall, the model offers a useful mathematical framework for understanding learning dynamics and improving teaching strategies in educational settings.
WOMEN’S RIGHTS AS HUMAN RIGHTS: A LEGAL FRAMEWORK FOR SOCIETAL UPLIFT IN PAKISTAN
This research article explores the intrinsic link between women's empowerment and societal progress. Despite international recognition, women's rights remain compromised globally. This study examines the legal frameworks and mechanisms for protecting women's rights, highlighting gaps and challenges. It argues that strengthening legal frameworks, enhancing access to justice, and promoting cultural shift are crucial for societal uplift. The research analyzes international human rights instruments, national legislation, and case studies, offering recommendations for policymakers, lawyers, and activists. By in streaming women's rights as human rights, societies can unlock sustainable development, peace, and prosperity, benefiting all. This article comprises of the doctrinal methodology to ascertain how the state ought to act to eliminate discrimination against women not only in the legal sense but also in the social sense.
SOIL SALINITY DYNAMICS AND CARBON SEQUESTRATION POTENTIAL UNDER CLIMATE CHANGE IN IRRIGATED AGROECOSYSTEMS OF PAKISTAN’S INDUS BASIN: A GEOSPATIAL AND BIOGEOCHEMICAL ASSESSMENT
Soil salinity is a major constraint to agricultural productivity and carbon sequestration in irrigated agroecosystems of Pakistan’s Indus Basin. This study assessed soil salinity dynamics and carbon sequestration potential under changing climatic conditions using an integrated geospatial and biogeochemical approach. A total of 300 soil samples were collected from five agro-ecological zones at 0–30 cm and 30–60 cm depths and analyzed for electrical conductivity (EC), pH, soil organic carbon (SOC), total nitrogen, and bulk density. Geospatial mapping using Landsat 8 imagery and statistical analyses (correlation and regression) were conducted to identify key determinants of salinity and carbon stocks. Results revealed that downstream and delta regions exhibited the highest salinity (EC up to 18.5 dS/m) and lowest SOC (0.5–1.0%), while upstream and reclaimed areas had lower EC and higher SOC. Soil salinity was significantly influenced by temperature, evapotranspiration, and groundwater salinity, and negatively affected SOC (r = -0.68, p < 0.01). Spatial analysis highlighted salinity hotspots and areas suitable for targeted soil reclamation and carbon-enhancing management. The findings underscore the importance of climate-informed soil management and organic amendments to mitigate salinity, enhance carbon sequestration, and sustain agricultural productivity under climate change.
ASSESSMENT OF CLIMATE-RESILIENT CROP VARIETIES THROUGH FUNCTIONAL GENE EXPRESSION AND YIELD PERFORMANCE IN DROUGHT-PRONE REGIONS OF PAKISTAN
Drought stress poses a significant challenge to crop productivity in Pakistan, particularly in arid and semi-arid regions. This study evaluated the drought tolerance of selected crop varieties through integrated assessments of physiological traits, functional gene expression, and yield performance. Field trials were conducted under water-limited conditions, and key drought-responsive genes, including DREB1, NAC, and dehydrins, were analyzed using qRT-PCR. Results indicated that certain varieties maintained higher relative water content, chlorophyll levels, root/shoot ratios, and biomass, while also exhibiting significant upregulation of stress-responsive genes. These traits were positively correlated with improved grain yield and yield stability. The study highlights the effectiveness of combining molecular, physiological, and agronomic evaluations for identifying climate-resilient crop varieties, providing actionable insights for breeding programs and sustainable agriculture in drought-prone regions of Pakistan.
STRATEGIC BALANCING IN SOUTH ASIA: PAKISTAN’S FOREIGN POLICY BEHAVIOR AMID U.S.–CHINA RIVALRY AND THE EXPANSION OF THE BELT AND ROAD INITIATIVE
This study examines Pakistan’s foreign policy behavior amid the intensifying U.S.–China rivalry and the expansion of the Belt and Road Initiative (BRI), with a focus on strategic balancing, economic imperatives, and regional security implications. Using a qualitative case study approach, data were collected from official documents, policy statements, and secondary sources, and analyzed through thematic content analysis. Findings indicate that Pakistan strategically aligns with China through CPEC for economic development while selectively engaging the U.S. to maintain security cooperation and diplomatic leverage. Domestic political and economic factors further moderate policy decisions, shaping the intensity and timing of strategic engagement. The study highlights Pakistan’s sophisticated hedging strategy, which enables it to preserve autonomy, maximize economic benefits, and manage regional security dynamics. The findings contribute to the literature on multipolar foreign policy behavior and offer policy insights for enhancing strategic decision-making in South Asia.
ALTRUISM, STRATEGIC VOTING, AND COLLECTIVE DECISION-MAKING: EXPERIMENTAL EVIDENCE FROM PUBLIC CHOICE GAMES
The paradox of voting where rational-choice theory predicts near-zero turnout in large elections due to negligible pivotality, yet millions consistently participate has prompted extensive research into the roles of altruism, strategic considerations, and institutional design in collective decision-making. This review synthesizes experimental evidence from laboratory public goods games, voter turnout experiments, and field studies of elections and referenda, alongside insights from neuroeconomics and agent-based modeling. Key findings demonstrate that other-regarding preferences (altruism, inequity aversion, warm-glow giving) significantly elevate turnout even when instrumental benefits are vanishingly small, with dictator-game variants and modified calculus-of-voting models showing altruism accounts for 30–60% of observed participation. Strategic voting sincere vs. tactical behavior, leader-follower dynamics, and coordination under incomplete information further modulates outcomes, particularly in multi-candidate or two-round systems. Institutional features (compulsory voting, expressive benefits, social norms, information provision via networks) interact with intrinsic motives to stabilize cooperative equilibria. Neuroeconomic studies reveal activation in reward and empathy-related brain regions during prosocial voting decisions, while computational simulations highlight how heterogeneous altruism and learning dynamics sustain turnout in large electorates. The synthesis reconciles apparent irrationality with persistent cooperation, underscoring that effective democratic design must harness both self-interest and other-regarding motivations to ensure robust civic engagement.
MACHINE LEARNING-ASSISTED COMPOSITION OPTIMIZATION OF TERNARY CHALCOGENIDES FOR ENHANCED THERMOELECTRIC EFFICIENCY
This Paper presents a machine learning approach for optimizing the power factor in ternary chalcogenide thermoelectric materials, using a dataset of 67,860 data points across 27 features. Key methodologies include data preprocessing, outlier removal via the IQR method, and feature importance analysis. The Random Forest model resulted in an R-squared value of 0.985 and effective predictive performance, particularly compared to linear regression. The top 10 influential parameters identified include electrical conductivity, Seebeck coefficient, temperature, and carrier concentration, which account for over 90% of the predictive importance. The models showcased robust generalization, validated through cross-validation and SHAP analysis to enhance interpretability by clarifying the nonlinear relationships between material features and power factor. This research establishes a comprehensive computational framework for the rapid screening of ternary chalcogenides, significantly reducing the experimental search space by over 95%. It demonstrates that machine learning models can predict power factor with high accuracy, facilitating virtual material screening. Additionally, feature importance analysis provides insights into power factor optimization mechanisms. The models identified promising candidates for experimental validation, while the methodology is generalizable to other thermoelectric materials, marking a significant advancement in the discovery and optimization of high-performance thermoelectric.
REVIEW OF MACHINE LEARNING APPLICATIONS FOR PREDICTING ULTIMATE LOAD CAPACITY OF REINFORCED CONCRETE COLUMNS CONFINED WITH FIBER REINFORCED POLYMER (FRP) JACKETS UNDER AXIAL COMPRESSION
The prediction of ultimate load capacity in fiber-reinforced polymer (FRP) confined reinforced concrete columns is a complex engineering challenge that has garnered significant research attention over the past two decades. Traditional empirical models and finite element analysis approaches have limitations in capturing the intricate nonlinear behavior of FRP-confined concrete under axial compression. Machine learning algorithms offer promising alternatives for improving prediction accuracy and efficiency. This review systematically examines the application of various machine learning techniques, including artificial neural networks, support vector machines, random forest, gradient boosting, and ensemble methods for predicting the ultimate load capacity of FRP-confined reinforced concrete columns. The paper analyzes 70+ peer-reviewed publications, evaluates model performance metrics, compares different machine learning approaches with conventional empirical methods, and identifies emerging trends in deep learning applications. Key findings indicate that machine learning models achieve superior prediction accuracy (R² values ranging from 0.92-0.95) compared to traditional empirical codes (R² values around 0.82-0.87). The review also presents a comprehensive bibliometric analysis of the research landscape and discusses future research directions including hybrid models, real-time prediction systems, and interpretability enhancements for machine learning-based prediction frameworks.
TOWARDS A GREEN INVESTMENT CORRIDOR: ENVIRONMENTAL GOVERNANCE, LEGAL SAFEGUARDS, AND STRATEGIC BENEFITS OF US-PAKISTAN SUSTAINABLE INVESTMENT PARTNERSHIP
This paper examines the renewed partnership between the U.S. and Pakistan on sustainable investments and how it addresses strategic advantages, environmental regulations, and legislation required to support green investments. Since the two countries have acute environmental issues, the necessity of creative green investments that will help to ensure sustainable economic development is becoming more pressing. This collaboration is a unique opportunity to address global environmental challenges through targeted investments in renewable energy, environmental protection, and green technologies. The paper critically examines the environmental governance systems that exist within Pakistan, the U.S influence in its formation and the laws that safeguard investments, societies and ecosystems. One aspect of the article that is also important is the establishment of the gaps in the current legal structures and policies that could impede the development of the green investments. Through the analysis of the literature concerning the subject under discussion, the article balances the achievements and the problems with the U.S.-Pakistan partnerships and by using the insights gained, the article proposes the improvements to use in the future sustainable investment. This article presents its arguments through a strategic analysis that bettering of the legal and governance structures can greatly prove beneficial to both nations not only in economic development but also in addressing their dedication towards the sustainability of the global environment. The research results provide the way to develop a strong green investment relationship between the U.S. and Pakistan which would guarantee the long-term environmental and economic advantages as well as ensure the solution of the climate crisis.
THE CULTURAL VALUE AND TEACHING PRACTICE OF INTEGRATING HENAN TRADITIONAL NURSERY RHYMES INTO EARLY CHILDHOOD EDUCATION PROGRAMS
This study explores the educational significance of integrating Henan traditional children’s songs into early childhood education. Drawing on the cultural features, musical forms, and pedagogical functions of Henan nursery rhymes, the paper proposes that their incorporation into preschool education can promote localized curriculum development, enhance the professional preparation of future kindergarten teachers, and foster young children’s aesthetic perception and cultural awareness. The study further discusses teaching strategies based on diversified, progressive, and thematic instruction, showing how traditional songs can be applied across vocal, instrumental, movement, and appreciation activities. The findings suggest that the integration of Henan children’s songs provides both a practical pathway for improving preschool music education and a meaningful approach to the inheritance of regional traditional culture.
THE INHERITANCE AND DISSEMINATION OF HENAN FOLK SONGS FROM THE PERSPECTIVE OF ONLINE MEDIA
Under the dual impact of globalization and the digital wave, the survival context of traditional music has undergone profound transformation. Henan folk songs, as an important carrier of Central Plains culture, bear the historical memory, folk customs, and public emotions of the Henan region. In the traditional communication context, Henan folk songs face difficulties such as the discontinuity of inheritors and limited dissemination scope. With the popularization of online media, short-video platforms, social media, and digital audio platforms have constructed a completely new communication ecology, providing new paths for the inheritance and dissemination of Henan folk songs. The fragmented dissemination of short-video platforms breaks temporal and spatial restrictions, live interactive broadcasting activates living inheritance, virtual technology empowers artistic innovation, and cross-platform linkage builds cultural identity. Based on the inheritance value and traditional dissemination dilemma of Henan folk songs, this paper analyzes their artistic characteristics and cultural value, combines them with the communication characteristics of online media, explores the reconstruction path of inheritance models, dissemination mechanisms, and cultural ecology under online media, and proposes optimization strategies for the risks of alienation in dissemination, aiming to provide theoretical and practical references for the modern transformation of traditional music.
DIGITAL VS. VERBAL STORYTELLING IN TOURISM MARKETING: EFFECTS ON EMOTIONAL AROUSAL AND DESTINATION CHOICE INTENTION
Storytelling has become an important communication strategy in tourism marketing. Destinations often use narratives to attract potential tourists and create emotional engagement with places. However, the influence of different storytelling formats on tourist responses is still not fully understood. This study examines the effect of storytelling format (digital vs. verbal) on tourists’ emotional arousal and destination choice intention. An experimental research design was employed in which participants were exposed to either digital storytelling or verbal storytelling related to a tourism destination. Data were collected from 768 participants and analyzed using independent samples t-tests. The results showed that storytelling format did not significantly influence destination choice intention. However, a significant difference was found in emotional arousal between the two storytelling formats. These findings suggest that storytelling format plays an important role in generating emotional engagement among potential tourists, but it may not directly influence their travel decisions. The study contributes to tourism marketing literature by providing empirical evidence on the comparative effects of storytelling formats. The findings also highlight the importance of emotional engagement in tourism communication strategies.
AI ALGORITHMS AND POLITICAL INFORMATION VISIBILITY ON X IN PAKISTAN
This research paper attempts to explore how artificial intelligence driven algorithmic ranking shapes political information visibility and opinion formation on X within the Pakistani digital environment. Drawing on insights from media ecology, the propaganda model, and critical discourse analysis, it examines how platform infrastructure’s structure political exposure, perceived bias, and user trust. Using a quantitative survey design, the research has analyzed user engagement behavior, perceptions of algorithmic ranking, and patterns of political information visibility. The findings of this inquiry suggest that algorithmic ranking strongly influences the prominence of political content, which subsequently shapes ideological exposure and opinion formation. Increased visibility of curated political material also appears to intensify perceptions of platform bias while reducing trust in platform neutrality in Pakistan. The study also argues that algorithmic governance reorganizes the digital public sphere by privileging engagement-oriented visibility over informational diversity. These findings highlight the growing role of platform infrastructures in shaping democratic communication in developing contexts such as Pakistan.
NUTRITIONAL, PHYTOCHEMICAL, AND SENSORY CHARACTERIZATION OF GLUTEN-FREE COOKIES DEVELOPED FROM RICE, CHICKPEA, AND BANANA PEEL COMPOSITE FLOUR
Cereal grains are widely consumed to meet human energy requirements; however, gluten proteins present in Wheat, Rye, Barley, and Triticale can trigger health issues such as Celiac Disease. This study aimed to develop nutritionally enriched gluten-free cookies using composite flours of Rice Flour, Chickpea Flour, and Banana Peel Powder in different proportions. Proximate analysis showed improved nutritional composition with increasing chickpea and banana peel flour, including higher protein (6.13–14.97%), fat (7.14–19.23%), fiber (1.82–7.38%), ash (1.03–4.48%), and moisture (2.44–5.43%). The health-promoting properties include total phenolic contents (50.01-125.55 mg GAE/100g), total flavonoid contents (20.40-60.54 mg QE/100g), and antioxidant activity (6.82-8.62%). Physical properties such as weight, diameter, thickness, and spread ratio significantly effect (p<0.05) with the addition of composite flour. Sensory evaluation showed the highest overall acceptability for cookies containing 40% rice flour, 50% chickpea flour, and 10% banana peel flour, demonstrating potential for nutritious and consumer-acceptable gluten-free products.
PERSONALIZED LEARNING AND ACADEMIC ACHIEVEMENT: AN EXPERIMENTAL STUDY OF HIGH, AVERAGE, AND LOW ACHIEVING SECONDARY SCHOOL STUDENTS
Personalized learning seeks to tailor instruction to students’ individual needs, goals, and skill levels; therefore, examining its effect on secondary school students’ academic achievement is of critical importance. This study aimed to investigate the effect of personalized learning on the academic achievement of high, average, and low achievers. A true experimental pretest–posttest equivalent group design was employed. The population comprised 9th-grade students from Govt. Madrissa Millia Islamia High School, F-Block, Satellite Town, Rawalpindi. Following the pretest, students were randomly assigned to experimental and control groups. A Subject Achievement Test (SAT), developed from three Mathematics chapters using a standardized questionnaire, was administered as both pretest and posttest. The experimental group was taught using personalized learning strategies based on the Essential Elements Model (Learner Profile, Student Agency, Flexible Learning Environment, Personal Learning Path, and Individual Mastery), whereas the control group received instruction through traditional teaching method. Both groups were taught by the same teacher over eight weeks. Results indicated that personalized learning significantly enhanced the academic achievement of high achievers (M = 38.65, SD = 13.73), while average achievers (M = 21.54, SD = 6.18) and low achievers (M = 9.67, SD = 1.44) showed comparatively limited gains. One-way ANOVA revealed statistically significant differences among the three achievement groups (F = 14.433, p = .000). Post hoc LSD tests confirmed that high achievers significantly outperformed both average and low achievers, whereas the difference between average and low achievers was not statistically significant. The findings of the study revealed that personalized learning significantly improved the academic achievement of secondary school students. The impact of personalized learning was particularly notable among high achievers, while average and low achievers also demonstrated measurable improvement in their academic performance. The results indicate that personalized learning provides opportunities for students to progress at their own pace, address individual learning needs, and enhance engagement in the learning process. In conclusion, personalized learning proved to be an effective instructional approach for enhancing academic achievement among secondary school students across different achievement levels. By accommodating individual differences in learning pace, style, and ability, personalized learning creates a more supportive and responsive learning environment. It is recommended that secondary schools integrate personalized learning strategies into classroom practices to support diverse learners. Additionally, teachers should receive continuous professional development to effectively implement personalized learning and provide appropriate scaffolding for students with varying academic abilities.
REVEALING HIDDEN ELECTRONIC AND OPTICAL POTENTIALS IN NOVEL DOPED MATERIALS VIA FIRST-PRINCIPLES CALCULATIONS
Background: Doping materials based on different elements has become a promising approach to the electronic and optical engineering of materials. Computation DFT helps to solve the problem of dopants at atomistic scales, especially first-principles calculations, which are especially important in understanding the effects of dopants on material behavior. Nevertheless, the detailed mechanisms and the ability to maximize such properties to be used in practice are not investigated fully. Purpose: This paper will explore the impact of doping of the electronic and optical characteristics of new materials through first-principles calculations to improve their usage in the field of optoelectronics like solar cells, light emitting diodes, and photo-detectors. Procedure: DFT calculations were done using Vienna Ab-initio Simulation Package (VASP) to calculate their band gap, density of states (DOS), optical absorption coefficients, and carrier mobility of the doped systems. Doping elements such as Ti, Mn, N and O were added to the host material and their effects on the electronic structure and optical characteristics of the material were studied. Findings: Doping lowered the band gap, increased optical absorption, and increased carrier mobility of most materials tremendously. The findings show that transition and non-metal doping of the material enhances the material in terms of its energy capture and electronic devices. Conclusion: Doping is a viable technique of controlling the electronic and optical characteristics of materials and thus rendering them more applicable to high-technological optoelectronic devices. These findings need to be proven experimentally in future work and the impacts of co-doping investigated.
DEVELOPMENT AND CHARACTERIZATION OF LOW-FAT MAYONNAISE INCORPORATING SOYBEAN PROTEIN AS A FAT REPLACER
The development of plant-based mayonnaise represents a significant innovation in the food industry, driven by increasing consumer demand for healthier, egg-free alternatives. This study focused on the formulation and optimization of soybean-based mayonnaise, evaluating its nutritional composition, sensory attributes, and shelf life. Soybean oil bodies (SOB) were used to replace egg yolk at varying levels (25–100%), resulting in reduced fat content and improved moisture retention. Proximate analysis showed that protein and fat decreased with increasing SOB, whereas carbohydrate content increased (p<0.05). Color analysis indicated higher lightness and reduced redness and yellowness in SOB-based treatments. Physicochemical properties and sensory evaluation confirmed the product's stability and acceptability during storage. The findings highlight soybean-based mayonnaise as a nutritious and sustainable alternative to conventional products.
A LATENCY-AWARE TASK OFFLOADING AND RESOURCE ALLOCATION FRAMEWORK FOR FOG-EDGE-CLOUD COLLABORATIVE COMPUTING IN REAL-TIME IOT APPLICATIONS
The exponential growth of latency-sensitive Internet of Things (IoT) applications such as autonomous vehicles, remote surgery, industrial automation, and real-time healthcare monitoring has exposed the limitations of centralized cloud computing, where geographic distance induces unacceptable transmission delays. This review presents a latency-aware task offloading and resource allocation framework for fog-edge-cloud collaborative computing, designed to minimize end-to-end latency while optimizing resource utilization in heterogeneous, multi-tier architectures. The proposed framework integrates dynamic offloading decisions based on task urgency, device mobility, network conditions, and computational load, employing predictive models (LSTM, spatio-temporal graph neural networks), deep reinforcement learning (DRL), and heuristic algorithms to orchestrate task partitioning, service migration, and proactive container relocation. Key mechanisms include mobility-aware service migration using Chebyshev graph convolutional networks, priority-based queuing at edge nodes, and adaptive resource provisioning that balances energy, bandwidth, and latency constraints. Simulation and real-world evaluations demonstrate 30–65% reductions in average latency, 20–45% improvements in task success rates under high mobility, and enhanced system throughput compared to baseline cloud-only or static offloading schemes. The framework addresses critical challenges such as intermittent connectivity, resource heterogeneity, and security in fog-edge environments, offering a scalable, proactive approach to support ultra-reliable low-latency communication (URLLC) requirements in 5G/6G-enabled IoT ecosystems.
JUDICIALIZATION OF POLITICS IN PAKISTAN: CONSTITUTIONAL COURTS, SEPARATION OF POWERS, AND DEMOCRATIC GOVERNANCE AFTER THE 18TH AMENDMENT
This study examines the judicialization of politics in Pakistan following the 18th Amendment, focusing on the role of constitutional courts in shaping the separation of powers and democratic governance. Through a qualitative doctrinal analysis of 15 landmark Supreme Court and High Court cases between 2010 and 2025, the study investigates how judicial interventions have influenced executive-legislative relations, provincial autonomy, and political accountability. Findings indicate that while judicialization has strengthened constitutional compliance and enhanced accountability, excessive judicial activism has occasionally blurred institutional boundaries, creating tensions between state organs. The study highlights the dual impact of judicialization on governance, offering insights for policymakers, legal scholars, and institutional reforms aimed at balancing judicial oversight with democratic functioning.
SHIFTING FROM NEUTRALITY TO EMPATHY: A CDA OF EU’S OFFICIAL RHETORIC ABOUT GAZA
This study explores how the European Union (EU) frames humanitarian empathy and neutrality in official discourse during the 2023-2024 Gaza crisis; and whether the EU's discourse shows transition from neutrality to empathy or not. Using Fairclough's three-dimensional model of Critical Discourse Analysis, the study analyses 30 statements by EU 0fficals, including press release statements, resolutions and speeches. The findings of the study revealed five relevant themes: Shift from Diplomatic Restraint to Affective Vocabulary, Strategic Pairing of Sympathy with Security Alignment, Moral Vocabulary Without Political Consequence, Emotional Urgency as a Rhetorical Substitute for Policy Shift, The Displacement of Agency Through Passive and Nominalized Constructions. This analysis unearths that while the EU successfully incorporated affective language to signal empathy, the EU consistently suppressed acts of agency and condemned the acts of violence through systemic ambiguity. The combination of empathy and uncertainty indicates an EU approach to symbolic action for reputational legitimacy in relation to moral disaster, but did not generate substantive diplomatic accountability. The study concludes by suggesting that while the EU humanitarian discourse is consecutively and performatively normative, it suggests a lack of substantive accountability for violence in the future. The initial research has implications for how critical discourse theory can inform our understanding of how institutional language internally manages developmental ethical claims in relation to moral disaster in protracted conflicts.
IMPROVING ORGANIZATIONAL PERFORMANCE THROUGH QUANTITATIVE MANAGEMENT TECHNIQUES
This study examines the role of quantitative management techniques in improving organizational performance through data-driven managerial practices. In modern organizations, the increasing complexity of operational activities requires managers to rely on analytical tools and statistical methods to support effective decision-making. Quantitative management techniques such as performance analytics, statistical evaluation, and operational optimization enable organizations to analyze large volumes of data and improve efficiency in resource utilization and strategic planning. The primary objective of this research is to analyze the relationship between quantitative management practices and key organizational performance indicators including productivity rate, operational efficiency, employee training investment, and decision-making effectiveness. The study utilizes a structured dataset containing 180 observations collected from multiple organizational departments across different time periods. Descriptive statistics, correlation analysis, and regression techniques are employed to examine relationships among the variables and to identify significant performance determinants. The findings indicate that departments utilizing quantitative management approaches demonstrate higher levels of operational efficiency and productivity. The results also highlight the importance of employee analytical training and timely managerial decision-making in enhancing performance outcomes. Overall, the study provides empirical evidence that the integration of quantitative management techniques contributes significantly to improving organizational effectiveness and operational performance.
COMMUNITY NETWORKS AND INFORMAL GOVERNANCE: WHAT PAKISTAN CAN LEARN FROM AFGHAN REFUGEE’S COMMUNITY BUILDING
Pakistan is host to one of the largest refugee populations in the world. This paper examines how Afghan refugee communities have relied on ethnolinguistic ties and social capital networks to build resilient informal governance structures through the assistance of the earlier generation of Afghan migrants who gained Pakistani nationality status in the 1970s and became the anchors. Based on the Social Capital Theory, this study shows how bonding, bridging, and linking social capital (through kinship networks and community hosting) have facilitated Afghan refugees to build resilient communities despite the lack of proper formal systems of governing them. Meanwhile, this paper does not ignore the valid national security concerns posed by in Pakistan posed by Tehrik-i-Taliban Pakistan (TTP) and Daesh which have led to its deportation policy as indicated in the National Action Plan, as well as the inability of the Afghan Taliban government to prevent cross-border terrorism. Based on academic sources and recent primary interview data gathered in 2025 among refugees in urban/rural settlements as well as in refugee villages in districts Pishin and Quetta, the findings reveal the need for formal good governance. The discussion suggests a governance framework that is realistic and aligns with the reality on the ground is needed: the porous borders will guarantee the deportee returns, the established communities will secure the undocumented population, and the effective governance will have to be facilitative as well as enforced.
TAILORING ELECTRONIC AND OPTICAL PROPERTIES OF TWO-DIMENSIONAL SEMICONDUCTORS FOR NEXT-GENERATION NANOELECTRONICS DEVICES
Two-dimensional (2D) semiconductors, including transition metal dichalcogenides (TMDs), black phosphorus, MXenes, and emerging 2D nitrides, are poised to overcome the fundamental scaling limits of silicon-based electronics by offering atomically thin channels with pristine surfaces, exceptional electrostatic control, and tunable electronic and optical properties. This review examines advanced strategies for tailoring these materials for next-generation nanoelectronic and optoelectronic devices, encompassing: (i) bandgap engineering via strain, electric-field gating, alloying, and heterostructure design; (ii) phase and defect control through doping, vacancy engineering, and twist-angle stacking; (iii) interface optimization in van der Waals heterostructures to suppress Fermi-level pinning and enhance carrier mobility; (iv) valleytronics and spintronics enabled by spin–valley locking in monolayer TMDs; and (v) integration into high-performance FETs, memristors, photodetectors, and neuromorphic synapses. Key performance metrics on/off ratios exceeding 10⁸, subthreshold swings approaching the 60 mV/decade limit, room-temperature mobilities >100 cm² V⁻¹ s⁻¹, and broadband photoresponse are highlighted alongside challenges such as contact resistance, environmental stability, and large-area synthesis. The convergence of these tailoring approaches positions 2D semiconductors as a versatile platform for post-CMOS logic, ultra-low-power electronics, flexible optoelectronics, and quantum-information technologies, with realistic pathways toward commercial viability discussed.
QUALITY OF EARLY CHILDHOOD EDUCATION: A GENDER-WISE COMPARISON OF ASSISTANT EDUCATION OFFICERS’ PERCEPTIONS IN GOVERNMENT SCHOOLS OF PUNJAB
Quality of Early Childhood Education (ECE) is essential for the overall development of a child because 80% of brain development occurs before the age of five. It improves cognitive, emotional and social skills and lays the foundation for good preparation for life such as (school, better long-term economic and social prospects). The study is aimed at comparing perceptions of male and female Assistant Education officers (AEOs) responsible for ensuring quality of ECE in public sector elementary schools of Punjab. The sample was comprised of 250 Assistant Education Officers (128 male and 122 female) employed as a sample from nine districts of Punjab province, Pakistan, selected using proportionate random sampling technique. Four main quality indicators of ECE - namely, physical environment, capable teachers and caregivers, support material, and parent and community engagement, were included in the study. The perceptions are measured with the help of a structured questionnaire on a five-point Likert-type scale. It was found that the overall quality of ECE was high; the perceptions of AEOs favoured to physical learning environment and access to support materials in comparison to other two indicators. The attitudes towards teachers and caregivers were also positive, but in comparison to classroom environment and materials, it was lower. Parent and community engagement, on the other hand were the lowest aspect, which also implies a lack of co-operation and involvement in school activities beyond the routine. Gender-wise comparison indicates that there were differences in perceptions in a variety of areas and this indicates the need to have uniform standards of supervision and mutual monitoring practices. The study concludes that while making efforts to enhance quality of ECE, issues to be resolved focusing family-school partnerships, community support, and in supervisory alignment, which seem to be more powerful when delivered in the classrooms.