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.
UNPACKING THE GLOBALIZATION AND TERRORISM INTERFACE IN SAARC: EMPIRICAL EVIDENCE ACROSS ECONOMIC, SOCIAL & POLITICAL DIMENSIONS
The primary objective of this study is to investigate the nexus between globalization and terrorism in South Asian countries from 2003 to 2017 using the PMG autoregressive distributed lag (ARDL) model. This study examines three components of globalization: economic, social, and political globalization. The empirical analysis is conducted in two steps. First, the panel ARDL model is estimated to derive short-run and long-run elasticities. Second, the Granger causality test is conducted to examine the causal relationships among the selected variables. The panel ARDL results indicate a long-run relationship between terrorism and the components of globalization. Political and economic globalization have a positive and statistically significant impact on terrorism, while total globalization also has a positive impact. Additionally, the Granger causality results reveal unidirectional causality running from terrorism to the Political Globalization Index (PGI), unidirectional causality from the Social Globalization Index (SGI) to terrorism, and unidirectional causality from the Total Globalization Index to terrorism.
CLIMATE-INDUCED MIGRATION AND BORDER MILITARIZATION IN SOUTH ASIA: A CRITICAL ANALYSIS OF SECURITIZATION DYNAMICS, STATE RESPONSES, AND HUMAN RIGHTS
The nexus between climate change, forced displacement, and state securitization constitutes one of the most complex and underexplored intersections in contemporary International Relations scholarship. In South Asia, a region that harbours nearly a quarter of the world's population and is classified by the Intergovernmental Panel on Climate Change (IPCC) as a "high-risk" zone for climate-related hazards, millions of individuals are being compelled to migrate due to sea-level rise, cyclonic intensification, riverine flooding, desertification, and glacial melt. Yet, rather than addressing this displacement as a humanitarian phenomenon, regional states have progressively adopted militarized border architectures, framing climate migrants as security threats through a process theorized in this study as eco-securitization. The study employs a mixed-methods approach combining qualitative document analysis of state policy instruments, bilateral treaty frameworks, and UN reports (2010–2025) with quantitative analysis of displacement data drawn from the Internal Displacement Monitoring Centre (IDMC), UNHCR, and the World Bank. Structured elite interviews with 24 policymakers, security officials, and civil society actors from Bangladesh, India, and Pakistan are integrated with critical discourse analysis of securitization narratives across all three nations. The study finds that between 2015 and 2024, climate-related displacement in South Asia increased by 218% while border infrastructure investment grew by 340% along the India-Bangladesh frontier alone. Paradoxically, militarization does not reduce irregular crossings but increases vulnerability, mortality, and documented human rights violations. A novel Securitization-Vulnerability Paradox (SVP) framework is developed and empirically validated across three country cases, demonstrating that enhanced border militarization inversely correlates with humanitarian outcomes for climate-displaced populations. This research advances a transformative policy architecture termed the Climate-Mobility Governance Framework (CMGF), calling for a paradigm shift from coercive border securitization to cooperative, rights-based regional mobility governance. The findings contribute three novel theoretical propositions to International Relations scholarship and carry direct implications for HEC-Priority research on climate diplomacy, South Asian regional security, and human rights law
IMPALED KNIFE IN NECK ZONE I — A CASE REPORT
Penetrating neck injuries are uncommon yet potentially fatal surgical emergencies due to the density of vital neurovascular and aerodigestive structures within a confined anatomical space. We present a rare case of a deeply impacted (approximately 15 cm) knife impalement injury in Zone I of the neck, successfully managed through meticulous surgical planning and multidisciplinary coordination. The case underscores the principle of controlled removal under direct vision and highlights the preservation of all major cervical structures, including the carotid artery, jugular vein, recurrent laryngeal nerve, vertebral arteries, spinal cord, and brachial plexus.
The nexus between climate change, forced displacement, and state securitization constitutes one of the most complex and underexplored intersections in contemporary International Relations scholarship. In South Asia, a region that harbours nearly a quarter of the world's population and is classified by the Intergovernmental Panel on Climate Change (IPCC) as a "high-risk" zone for climate-related hazards, millions of individuals are being compelled to migrate due to sea-level rise, cyclonic intensification, riverine flooding, desertification, and glacial melt. Yet, rather than addressing this displacement as a humanitarian phenomenon, regional states have progressively adopted militarized border architectures, framing climate migrants as security threats through a process theorized in this study as eco-securitization. The study employs a mixed-methods approach combining qualitative document analysis of state policy instruments, bilateral treaty frameworks, and UN reports (2010–2025) with quantitative analysis of displacement data drawn from the Internal Displacement Monitoring Centre (IDMC), UNHCR, and the World Bank. Structured elite interviews with 24 policymakers, security officials, and civil society actors from Bangladesh, India, and Pakistan are integrated with critical discourse analysis of securitization narratives across all three nations. The study finds that between 2015 and 2024, climate-related displacement in South Asia increased by 218% while border infrastructure investment grew by 340% along the India-Bangladesh frontier alone. Paradoxically, militarization does not reduce irregular crossings but increases vulnerability, mortality, and documented human rights violations. A novel Securitization-Vulnerability Paradox (SVP) framework is developed and empirically validated across three country cases, demonstrating that enhanced border militarization inversely correlates with humanitarian outcomes for climate-displaced populations. This research advances a transformative policy architecture termed the Climate-Mobility Governance Framework (CMGF), calling for a paradigm shift from coercive border securitization to cooperative, rights-based regional mobility governance. The findings contribute three novel theoretical propositions to International Relations scholarship and carry direct implications for HEC-Priority research on climate diplomacy, South Asian regional security, and human rights law.
THE SETTLEMENT OF INTERNATIONAL DISPUTES BY MEANS OF ADJUDICATIVE METHODS UNDER PUBLIC INTERNATIONAL LAW
This research examines how countries resolve their disputes through courts and tribunals in Public International Law. The focus is on how these neutral judicial bodies help maintain peace and legal order. It explains that approaching judicial institutions provides a mechanism for countries to settle disagreements using international law. Countries refer their disputes to judicial institutions to work them out amicably. The study also takes a look at the historical development of this system. It starts from arbitration and moves on to the creation of permanent bodies like the International Court of Justice. At the same time it examines the legal framework that supports dispute settlement. This includes treaties, customary international law and the UN system. The research also examines how these methods work in practice. There are problems, such as weak enforcement, political interference, limited jurisdiction and inconsistent state compliance. For example the Corfu Channel case and Nicaragua v. United States show both the power and limitations of adjudication. In the end the study concludes that while going to court promotes conflict resolution more needs to be done. It relies on enforcement, better country cooperation and improved adherence to judicial rulings for real impact. The International Court of Justice plays a central role in this process. Countries must work together to make international adjudication more effective.
METABOLOMIC AND PROTEOMIC CHARACTERIZATION OF INDIGENOUS MEDICINAL PLANTS FOR TARGETED ANTICANCER DRUG DISCOVERY IN PAKISTAN
Cancer remains a major global health burden characterized by genetic heterogeneity, therapeutic resistance, and dysregulation of multiple signaling pathways. Conventional anticancer therapies are often limited by toxicity, high cost, and lack of specificity, particularly in low- and middle-income countries. In this context, indigenous medicinal plants of Pakistan represent a promising yet underexplored source of bioactive compounds with potential anticancer properties. This study aimed to systematically characterize the metabolomic and proteomic profiles of selected medicinal plants and to identify multi-target anticancer mechanisms through integrated systems biology and network pharmacology approaches. A multi-omics analytical framework was employed, utilizing LC–MS/MS and GC–MS for metabolomic profiling and shotgun proteomics for protein identification and functional annotation. Bioinformatics tools were applied for data processing, differential analysis, and pathway enrichment. Identified metabolites and proteins were mapped onto cancer-related signaling networks, including PI3K/Akt, MAPK, p53, and NF-κB pathways. Network pharmacology analysis was conducted to construct compound–target–pathway interaction maps and to elucidate synergistic mechanisms of action. The integrated analysis revealed that selected medicinal plants possess diverse secondary metabolites, including flavonoids, alkaloids, terpenoids, and phenolic compounds, along with functionally active proteins associated with apoptosis, stress response, and detoxification processes. Pathway enrichment analysis demonstrated significant modulation of key oncogenic signaling cascades involved in cell proliferation, survival, and apoptosis regulation. The findings suggest that these plants exert anticancer effects through a multi-target, systems-level mechanism rather than single-compound activity. This study provides a comprehensive omics-based framework for anticancer drug discovery from indigenous medicinal plants of Pakistan and bridges the gap between ethnopharmacological knowledge and modern computational biology. The results offer a scientific basis for further experimental validation and potential development of novel, cost-effective anticancer therapeutics.
DEVELOPMENT, CHARACTERIZATION, AND THERAPEUTIC EVALUATION OF FUNCTIONAL COCOFEE GUMMIES FOR TYPE 2 DIABETES MANAGEMENT IN WISTAR ALBINO RATS
The present study was conducted to develop, characterize, and evaluate the therapeutic potential of functional Cocofee gummies for the management of type 2 diabetes mellitus. The gummies were formulated and analyzed for their proximate composition, revealing that the gummies contained 28.2% moisture, 6.0% crude fat, 3.3% crude protein, 2.8% crude fiber, 2.5% ash, and 42.8% nitrogen-free extract (NFE). Phytochemical evaluation demonstrated appreciable bioactive potential with total phenolic content of 23.6 mg GAE/100 g and total flavonoid content of 4.7 mg CE/100 g. Antioxidant activity, determined by the DPPH radical-scavenging assay, was 21.48%. Color analysis showed L*, a*, and b* values of 29.2, 5.7, and 10.5, respectively, with C*, WI, and ΔE values of 26.23, 14.12, and 22. Sensory evaluation indicated good consumer acceptability, with appearance, texture, taste, aroma, and overall acceptability scores of 8.5, 7.8, 6.2, 4.2, and 5.7, respectively. For therapeutic efficacy, diabetes was induced in Wistar albino rats using alloxan, and animals were supplemented with low-dose (1 gummy per day) and high-dose (2 gummies per day) cocofee gummies for 30 days. The high-dose treatment group exhibited the greatest reduction in body weight (6.2%) and random blood glucose levels (11.0%) compared with the diabetic control group. The outcomes suggest that functional Cocofee gummies possess hypoglycemic effects which attributed to the synergistic action of coffee-derived bioactive compounds and dietary fiber from coconut husk that improve glucose metabolism, metabolic regulation, and antidiabetic properties.
DIPLOMACY AND WAR: AN ANALYTICAL STUDY OF US-IRAN CONFLICT
Examining the US and Iran conflict with historical background till current situation by adopting the mixed methodology analysis case study approach. How the conflicted rooted in Israel because it is actual a US and Israel foreign policy. Role of Diplomates here’s it discussed in the case of US-Isreal and Iran conflict. Negotiations possible in war time or in normal situations shows the mediator countries relations with others states, here like Pakistan’s relations with US and Iran attracted both for trust. Iran is an oldest Islamic country of the world and become more prominent by their 1979 revolution. Israel become the Jewish State by the UNO Partition plan to resolve the issue between Arabs and Jewish people in 1948 but it changed the whole situation. We will discuss the major issues on both sides in the dispute which are the basis of the conflict. Proxies, IRGC to direct invasion. How the negotiators tried but failed to reach a deal or how the Islamabad talks were unable to reach a comprehensive deal. Role of Pakistan’s Prime Minister and CDF Asim Minur in Islamabad Talks. How make the situations worst the assassinations of Iranian’s and destruction in Iran and Iranian attacks on Isreal and gulf countries. Blockade of Straint of Hurmoz. Foreign policies of countries how affecting the whole scenario because of Iran foreign policy against US-Isreal and US-Isreal foreign policy against Islamic Iran. America is known for economy and power in the world and have the hegemonic style. In this paper it will be explain the entire background of the conflict, efforts for conflict resolution and temporary ceasefire, peace settlements between USA and Iran. Iran assets, sanctions on Iran and no nuclear deal are the major challenges and on the other hand US-Isreal policies for not reaching deal or peace settlements and it’s still a continuous situation.
XAI FOR INDUSTRIAL PROCESS MONITORING: APPLYING SHAP TO DETECT ANOMALIES IN CHEMICAL MANUFACTURING DATA
Industrial process monitoring is essential for maintaining operational safety, product quality, equipment reliability, and overall efficiency in chemical manufacturing environments. The growing adoption of Industry 4.0 technologies has enabled the collection of large volumes of real-time process data, creating opportunities for machine learning (ML)-based anomaly detection. While advanced ML models can accurately identify abnormal operating conditions, their black-box nature often limits transparency and trust among engineers and plant operators. To address this challenge, this research proposes an Explainable Artificial Intelligence (XAI)-driven anomaly detection framework that integrates machine learning with the Shapely Additive explanations (SHAP) method. The proposed framework uses SHAP values to explain model predictions by quantifying the contribution of individual process variables to detected anomalies. Experimental evaluation is performed using a benchmark chemical manufacturing dataset, where data preprocessing, feature engineering, and supervised learning techniques are employed to develop a robust anomaly detection model. Results demonstrate high detection performance in terms of accuracy, precision, recall, and F1-score while simultaneously providing meaningful explanations for abnormal process behavior. SHAP analysis identifies critical variables such as reactor temperature, reactor pressure, feed flow rate, and cooling system parameters as major contributors to anomaly predictions. Furthermore, the generated explanations support effective root-cause analysis, enabling engineers to diagnose faults more efficiently and make informed operational decisions. The findings indicate that integrating SHAP with machine learning significantly enhances model transparency, interpretability, and user trust without compromising predictive performance. Therefore, the proposed framework offers a practical and scalable solution for explainable industrial process monitoring and contributes to the adoption of trustworthy AI in chemical manufacturing systems.
RESPONSE OF DIFFERENT LENTIL CULTIVARS AGAINST APHIDS AT DISTRICT PESHAWAR, KHYBER PAKHTUNKHWA
The cowpea aphid (Aphis caraccivora) is a major pest of lentil crop in Pakistan and caused significant losses each year. The study was conducted under field condition at Newly zdevelopmental Farm, The University of Agriculture, Peshawar during 2022-23. Total three cultivars were selected for the trial namely, cultivar Sanli-bey, Atacan and Masoor-93 arranged in Randomized Complete Block design (RCBD) having three replications. The aphid population was consistently observed from two leaf stage till crop maturity/aphid disappeared. The aphids first invaded the tested plants during second week of February 2023. The black pea aphid (Aphis caraccivora) was first attracted by cultivar Atcan followed by Sanli-bey and Masoor-93. The local variety Masoor-93 showed strong response against aphid followed by cultivar Sanli-bey and Atacn. The cultivar Masoor-93 was found best with lowest aphids infestation (7.52) followed by Sanli-bey (10.61) which was found no-significant to Atcan (11.22). The population density was gradually decreased due to multiple factors and disappeared at end of March 2023. It is concluded that Masoor-93 is suitable for cultivation in Peshawar region due to high potential of well growth and has high resistance against aphid infestation.
RETHINKING CEMETERY ARCHITECTURE IN MUSLIM CITIES: A SUSTAINABLE FRAMEWORK FOR VERTICAL BURIAL DEVELOPMENT
The unprecedented rate of urbanization in developing countries has been putting pressure on land resources, which has made provision of services in the urban areas, including burial, a great challenge. Traditionally used for ground burial, Muslim cemeteries are experiencing problems of land scarcity, inefficient management, overcrowding and problems with grave identification. Such difficulties have been more noticeable in the more rapidly expanding cities where the growth of the cities has been in direct competition with the allocation of land within the cemeteries. The idea of vertical cemeteries is therefore born, as a possible architectural and planning solution to meet future requirements of burying the deceased with the conservation of precious urban space. This study focuses on the feasibility of vertical Muslim cemetery as sustainable urban burial solution in densely populated urban area. The research is based on secondary data, religious literature, scholarly publications, international case studies, and contemporary practice of cemetery design, and examines the connections between Islamic burial practices and the consumption of urban land, as well as the management of cemeteries and the innovation in architecture. Special consideration is paid to the compatibility of vertical burial methods and Islamic beliefs about death, burial and remembrance. The study also examines models from abroad and examines some of the examples of religious buildings from Brazil, India, the Philippines, Austria, Russia, and Bangladesh to identify design approaches that take into account religious requirements, environmental considerations and urban efficiency. The results suggest that if designed appropriately for religious needs, vertical cemeteries have the potential to use significantly less land, increase accessibility and management of the cemetery, improve its environmental aspects and promote sustainable urban development. The study concludes that vertical Muslim cemeteries are a promising solution for the future, which could be effective in solving the shortage of burial plots while maintaining the values and traditions related to Islamic burial
THE EMERGENCE OF CONSTITUTIONAL COURTS IN PAKISTAN: RESTRUCTURING JUDICIAL POWER AND CONSTITUTIONAL ADJUDICATION
This paper explores the role of the 26th and 27th Constitutional Amendments in reforming judicial power and constitutional adjudication in Pakistan, and how they have affected judicial independence, constitutional supremacy, and the balance of power among state institutions. This analysis will begin by explaining the pre-amendment status of the judiciary, in which the Supreme Court served as the main protector of the Constitution by reviewing its own decisions, appointing judges based on seniority, and exercising Suo motu power. The paper argues that, despite this model's drawbacks, particularly the persistent conflicts between the judiciary and the political branches, it has managed to retain a relatively cohesive system of constitutional checks and balances. It then reviews the 26th Amendment, noting four major changes: the tenure of the Chief Justice, the reconstitution of the Judicial Commission, the restriction of Suo motu powers, and the establishment of constitutional benches. The paper concludes that these reforms, though introduced to enhance institutional continuity, accountability, and specialization, also introduced political control over the appointment of judges and undermined the judiciary's independent checking role. The 27th Amendment was introduced as the next, more profound structural change, establishing the Federal Constitutional Court (FCC) and removing the Supreme Court's constitutional preeminence. The study notes that this development created parallel apex courts, heightened the risk of conflicting constitutional interpretations, and weakened the judicial hierarchy. The study finds that the two amendments were packaged as efficiency-based reforms but, in reality, reshaped judicial power in ways that can jeopardize fair adjudication and expose the courts to indirect executive influence.
IDENTIFICATION OF THE FACTORS PROMOTING THE ADOPTION OF ENERGY-EFFICIENT VEHICLES IN KARACHI, PAKISTAN
The main subject of this research paper is to examine the critical factors that encourage the use of energy-efficient vehicles in Karachi, which is the largest metropolitan city in Pakistan. The research adopts the Diffusion of Innovation Model by Rogers to examine the effect of perceived characteristics, social factors, and attitude toward behavior in influencing customer acceptance of energy-efficient vehicles. The survey was a structured survey of 104 respondents to analyze the socio-economic, environmental, and technological determinants in influencing purchase decisions. The results are expected to help the policy-makers, marketers, and urban planners to determine the strategic steps that will help to increase people's awareness, supportive policies, and speed up the internalization of energy-saving cars, helping to make the transportation system more sustainable and environmentally resilient in Karachi.
ALGORITHMIC GOVERNANCE AND CONSTITUTIONAL RIGHTS IN PAKISTAN: LEGAL IMPLICATIONS OF AI-BASED PUBLIC DECISION-MAKING
This study critically examines algorithmic governance and its constitutional implications in Pakistan with a focus on AI-based public decision-making systems. The increasing deployment of artificial intelligence in administrative processes has introduced new dimensions of efficiency and automation; however, it has simultaneously raised significant legal concerns regarding transparency, accountability, due process, and protection of fundamental rights. The research employed a qualitative doctrinal and comparative legal analysis to evaluate constitutional provisions, judicial precedents, policy frameworks, and international AI governance standards. The findings reveal that Pakistan’s existing legal framework lacks explicit provisions for regulating algorithmic decision-making, resulting in a governance gap between technological adoption and constitutional safeguards. Key issues identified include algorithmic opacity, risk of discriminatory outcomes, weak accountability mechanisms, and limited explainability of automated decisions. Comparative analysis with international frameworks such as the EU AI Act, OECD principles, and UNESCO guidelines highlights significant regulatory deficiencies in Pakistan’s approach to AI governance. The study concludes that algorithmic governance, while beneficial for administrative efficiency, poses substantial risks to constitutional rights unless accompanied by robust legal and regulatory safeguards. It recommends the development of a comprehensive AI governance framework incorporating transparency requirements, human oversight mechanisms, and enforceable rights to explanation.
CLIMATE CHANGE EFFECTS ON POLLINATOR DIVERSITY AND AGRICULTURAL PRODUCTIVITY IN PAKISTAN
This study investigates the impact of climate change on pollinator diversity and its subsequent effects on agricultural productivity in Pakistan. Increasing climatic variability, including rising temperatures, erratic rainfall patterns, and extreme weather events, has significantly disrupted ecological balance and threatened pollination services essential for crop production. The study employed a quantitative correlational research design using secondary time-series data on climatic indicators, pollinator diversity, and agricultural yield performance across major agro-ecological zones of Pakistan. The findings reveal a strong negative relationship between climate change variables and pollinator diversity, indicating that increasing temperature anomalies and rainfall variability significantly reduce pollinator populations. Moreover, pollinator diversity was found to have a strong positive effect on agricultural productivity, confirming its critical role in sustaining crop yields. Mediation analysis further demonstrated that pollinator diversity significantly mediates the relationship between climate change and agricultural productivity, highlighting its role as a key ecological link in climate-agriculture interactions. The study concludes that climate change poses a substantial threat to agricultural sustainability in Pakistan through its adverse effects on pollinator ecosystems. Strengthening biodiversity conservation and integrating pollinator protection into climate adaptation strategies are essential for ensuring long-term food security and ecological resilience.
THE DIGITAL MEDIATOR: POLICY FRAMEWORKS FOR INTEGRATING ARTIFICIAL INTELLIGENCE INTO ALTERNATIVE DISPUTE RESOLUTION
The international landscape of Alternative Dispute Resolution (ADR) finds itself on the cusp of a great technological paradigm shift. A successful mediation is always anchored entirely on the human element, such as a mediator’s ability to utilize emotional intelligence, empathy, and neutrality. However, the emergence of Generative Artificial Intelligence (AI) and its predictive power has firmly established itself in the mediation room. Algorithms are no longer passive “fourth party” instead, they have evolved into an active “fifth party agent” capable of guiding negotiations and suggesting settlement options independently. This paper examines the profound policy and regulatory gap created by AI advancement by focusing on procedural disclosure gap and algorithmic-ingestion paradox. While analyzing how the Large Language Models, (LLM) clashes with the key mediation principles under the EU AI Act, The UNCITRAL Model Law and domestic frameworks like Punjab ADR Act 2019 are also put to the test. What happens when a settlement under the Singapore Convention is mediated by an algorithm? This paper argues that the answer should worry us. Consequently, this paper argues that the integrity of the process cannot be compromised just for the sake of expeditious computational output. It proposes the solution by step-by-step framework positioned on algorithmic sandboxing, transparent disclosure rules, a mandatory human-in-the-loop standard to uphold the integrity of digital justice.
THE MODERATING ROLE OF FINANCIAL DEVELOPMENT IN THE HUMAN CAPITAL–GROWTH NEXUS: EVIDENCE FROM MIDDLE INCOME COUNTRIES
This study investigates the moderating role of financial development in the relationship between human capital and economic growth in middle-income countries. Using panel data from the World Development Indicators (WDI), the study employs Ordinary Least Squares (OLS), Fixed Effects (FE), Random Effects (RE), Structural Equation Modeling (SEM), and MEDSEM analysis. Human capital is measured through a PCA-based Human Capital Index (HCI) and the World Bank Human Capital Development Index (HCD), while financial development is proxied by domestic credit to the private sector. The findings reveal that both human capital and financial development positively and significantly influence economic growth. The interaction term between human capital and financial development is also positive and significant, indicating that financial development strengthens the growth-enhancing effect of human capital. Furthermore, mediation analysis shows that financial development partially transmits the impact of human capital on economic growth. The study concludes that human capital and financial development are complementary drivers of economic growth and recommends simultaneous investment in education and financial sector development to achieve sustainable economic growth in middle-income countries.
FIDELITY AND UTILITY OF SYNTHETIC TABULAR HEALTH DATA: A CROSS-PARADIGM BENCHMARKING OF A CORRELATION-PRESERVING STATISTICAL PIPELINE AND A CONDITIONAL GENERATIVE ADVERSARIAL NETWORK
Background: The generation of synthetic tabular health data has emerged as a pivotal methodology for statistical simulation, privacy preservation, and methodological validation. While classical statistical approaches offer interpretable, correlation-preserving synthesis through explicit parametric modeling, generative adversarial networks (GANs) provide a flexible, non-parametric alternative that learns the full joint distribution directly from empirical data. Despite the rapidly expanding application of both paradigms, a rigorous, cross-disciplinary empirical comparison tailored to the specific challenges of mixed-type health datasets with small-to-moderate sample sizes remains absent. Aims & Objective: This study evaluates whether a GAN-based approach (CTGAN) offers demonstrable advantages over a modern classical statistical pipeline for synthetic health data generation, and under which practical conditions each method excels. Methodology: Six publicly available tabular health datasets were selected, encompassing continuous, binary, and time-to-event outcomes with mixed continuous and categorical predictors. The statistical pipeline comprised the Modgo method for covariate matrix simulation, followed by parametric model-based outcome generation (linear, logistic, or Cox models). The CTGAN architecture was trained for 1000 epochs. Synthetic data quality was assessed through quantitative distributional similarity metrics (moments, Kullback–Leibler divergence, Kolmogorov–Smirnov statistic, Jensen–Shannon distance, Wasserstein distance), categorical concordance, pairwise correlation recovery, and downstream predictive utility measured via mean squared error, balanced accuracy, and concordance index. Sensitivity to variable scaling and training epoch selection was systematically examined. Results & Findings: Both methods successfully reproduced univariate distributions and joint dependence structures across all datasets. The statistical approach demonstrated superior fidelity in recovering pairwise linear correlations, attributable to its explicit correlation matrix estimation. Consequently, it yielded marginally higher prediction performance for binary classification (balanced accuracy 0.85 vs. 0.78) and survival analysis (C-index 0.71 vs. 0.65). The CTGAN approach achieved lower mean squared error in linear regression (1.02 vs. 2.82) and exhibited pronounced robustness to feature scaling, in contrast to the statistical method which failed catastrophically without prior standardization. CTGAN-generated densities occasionally displayed discretized artifacts, particularly in small samples. Both methods performed comparably in categorical distribution recovery and overall downstream utility. Conclusions: Classical statistical and GAN-based synthetic data generation methods are both viable tools for health simulation studies, each with distinct operational strengths. The statistical pipeline is recommended when the precise reproduction of known correlation structures or parametric outcome relationships is critical, provided that rigorous data preprocessing is undertaken. The CTGAN approach is preferable for datasets with complex multimodality, heavy tails, or when minimal preprocessing and automated implementation are desired. These findings sanction the principled integration of AI-based generators into the statistical simulation repertoire and underscore the importance of context-dependent method selection. Future research should prioritize the incorporation of privacy preservation mechanisms and the development of hybrid architectures that couple the interpretability of statistical models with the distributional flexibility of deep generative networks.
THERAPEUTIC POTENTIAL OF AJWAIN (TRACHIPTERUS AMMI) AGAINST DIET-INDUCED OBESITY AND DYSLIPIDEMIA IN RAT
The aim of present study was to assess the protective effect of carom seed powder against obesity and hyperlipidemia by using animal model. Sixteen rats were given high-fructose and high-fat diet to induce obesity, then powder of carom seeds was given to the treatment groups, G1, G2 and G3 according to their per kg body weight are about to 100 mg, 300 mg and 500 mg respectively. This trial period was continued for 6-weeks on daily basis. During this practice serum leptin, blood glucose and lipid profile were checked 0, 21 and 42 day and anthropometric measurements were taken 0, 21, 28, 42 days. The data thus obtain was analyzed statistically. The effect was seen in G3 (500 mg carom powder) that reduced low density lipoprotein cholesterol (69.75 mg/dl to 57.50 mg/dl), triglycerides (50.75 mg/dl to 39.50 mg/dl), total cholesterol (79.01 mg/dl to 42.25 mg/dl), serum leptin (19.20 ng/ml to 13.57 ng/ml), serum blood glucose (119.0 mg/dl to 78.75 mg/dl), body weight (213.9 g to 179.1 g) and body mass index (151.32 g/cm2 to 140.10 g/cm2). The data has shown significant decreased in LDL, triglycerides, cholesterol, blood glucose, serum leptin and body weight while significant increase in high density lipoprotein HDL (20.01 mg/dl to 25.06 mg/dl) due to uptake of carom powder. It is concluded from present study that carom powder has ability to influence the above-described obesity biomarkers. Concisely, carom powder has the quality to lower the causes of some metabolic ailments such as hyperlipidemia and hyperglycemia complications.
CYBERSECURITY FRAMEWORK FOR SECURE CLOUD COMPUTING USING BLOCKCHAIN AND FEDERATED DEEP LEARNING
Cloud computing is now a backbone of modern digital services because it offers scalable resources and reduced costs. Yet centralized cloud setups are easy targets for distributed denial-of-service (DDoS) attacks, data breaches, spoofing, insider threats, and malicious traffic. Most existing intrusion detection systems (IDS) train models on a single server, which creates privacy risks, bottlenecks, and poor scalability. This paper proposes a Cybersecurity Framework for Secure Cloud Computing Using Blockchain and Federated Deep Learning (CFSC-BFDL). The framework pairs blockchain-based trust management with a federated convolutional neural network (CNN) so that cloud nodes can detect attacks together without ever sharing raw data. Blockchain handles authentication, tamper-proof logging, and safe model aggregation, while each node trains its own CNN locally and sends only encrypted weight updates to a central aggregator. Experiments on the CICIDS2017 and UNSW-NB15 datasets, validated with 5-fold cross-validation, show an average detection accuracy of 98.4% (+/- 0.31), precision of 97.9%, recall of 97.5%, and F1-score of 97.7%. These numbers beat several existing centralized and blockchain-based IDS approaches. The framework also cut communication overhead by roughly 32% and kept detection latency at 14.2 ms per sample, confirming that combining blockchain with federated deep learning offers a practical path toward stronger cloud security.
A STUDY OF PROBLEMS FACED BY SENIOR CITIZENS AND THE REASONS OF JOINING OLD AGE HOMES
Population ageing has emerged as a significant social and public health concern worldwide. Rapid socio-economic transformations, including urbanization, migration, and the gradual weakening of traditional family support systems, have contributed to an increasing number of senior citizens residing in old age homes. The present study aimed to investigate the reasons for joining old age homes and the problems faced by senior citizens living in these institutional settings. A quantitative descriptive research design was employed. Data were collected from 95 senior citizens residing in five selected old age homes in Islamabad and Rawalpindi through a self-developed structured questionnaire. The collected data were analyzed using the Statistical Package for the Social Sciences (SPSS), and descriptive statistical techniques such as frequency distributions, bar charts, histograms, and pie charts were applied for data presentation. The findings revealed that the primary reasons for admission into old age homes included the absence of caregivers, family conflicts with children, lack of familial support, and personal choice. A substantial proportion of respondents reported infrequent or no visits from their children. Although most participants indicated satisfactory access to medical care, adequate nutrition, and generally stable physical health, many still experienced emotional loneliness, adjustment difficulties, chronic health conditions, and financial insecurity, particularly due to the absence of pension support. The study highlights the increasing vulnerabilities of older adults in contemporary society and underscores the need to strengthen family support systems, improve institutional elderly care services, and develop effective social welfare policies to enhance the overall quality of life of senior citizens residing in old age homes.
CORRELATION BETWEEN NURSING STUDENTS’ CLIMATE CHANGE KNOWLEDGE, ANXIETY, AND SUSTAINABILITY ATTITUDES: A CROSS-SECTIONAL STUDY
Background: Climate change is a growing public health concern affecting physical and mental health globally. Among nursing students, awareness, anxiety, and attitudes toward sustainability may influence future professional practice in healthcare. Methods: A descriptive cross-sectional study was conducted among 161 nursing students at Shalamar Nursing College, Lahore. Data were collected using a structured questionnaire assessing climate change awareness, climate change anxiety, and sustainability attitudes. Data were analyzed using SPSS version 23. Descriptive statistics, Pearson correlation, and multiple regression analysis were applied. Results: Most participants demonstrated good climate change awareness (49.1%) and high sustainability attitudes (61.5%), while moderate climate change anxiety was most common (67.1%). Significant positive correlations were found between awareness and sustainability attitudes (r = 0.559, p < 0.001), anxiety and awareness (r = 0.384, p < 0.001), and anxiety and sustainability attitudes (r = 0.310, p < 0.001). Regression analysis showed that climate change awareness significantly predicted sustainability attitudes (p < 0.001), whereas anxiety did not (p = 0.116). Conclusions: Climate change awareness is a key determinant of sustainability attitudes among nursing students, while anxiety plays a limited predictive role. Strengthening climate education in nursing curricula may enhance sustainable healthcare attitudes.
IMAGE-BASED CANOLA SEED DETECTION AND COUNTING USING YOLOV8N AND YOLO11N OBJECT DETECTION MODELS
Accurate seed counting is a key component in seed quality assessment, breeding programs, germination and crop productivity analysis, and counting canola (Brassica napus L.) seeds is essential. The traditional methods of seed counting are time-consuming, labor-intensive, and subject to human errors, particularly in the processing of large quantities of samples. The development of computer vision and deep learning techniques has been seen as a very promising approach to the automated recognition and counting of objects in agriculture in recent years. This paper proposes an image-based automatic canola seed detection and counting method based on YOLOv8n model and YOLO11n models. A customized dataset of 833 images of canola seeds in natural light was created. The images in the dataset comprised different numbers of seeds (from one to ten). Each image was annotated by hand in the Computer Vision Annotation Tool (CVAT) with only one class, “canola_seed”. The dataset was split into 666 train images and 167 validation images. Both YOLOv8n and YOLO11n models were trained for 50 epochs and evaluated using F1-score, mean average precision (mAP@50), and confusion matrix analysis. The results on the experimental set indicate that the YOLOv8n model had a mAP@50 of 0.965 and an optimal F1 score of 0.95, and the YOLO11n model had a mAP@50 of 0.969 and an optimal F1 score of 0.97. YOLOv8n and YOLO11n had mAP@50-95 of 0.270 and 0.266, respectively. Moreover, YOLO11n had fewer false-positive and false-negative results compared with YOLOv8n, demonstrating the reliability of the detection and counting process. The results show that YOLO11n was superior to automated canola seed detection and counting. The proposed framework is a solution that can be used for seed quality testing, agricultural phenotyping, and future smart agriculture applications, which is low-cost, accurate, and efficient.
HEAVY METAL TOXICITY IN CUCUMBER: AN OVERVIEW ON USING GROWTH AND BIOCHEMICAL PARADIGMS
Heavy metals (HMs) like cadmium (Cd), lead (Pb), copper (Cu) and zinc (Zn) are a major concern in agricultural soils, threatening global food security and ecosystem integrity. Fast-growing and physiologically well characterized cucumber (Cucumis sativus L.) is an excellent model species for assessing HM phytotoxicity because the plants are sensitive and exhibit a quantifiable stress response. This review aims to systematically compile existing information on toxicity due to HM exposure to cucumber for morphological, physiological and biochemical endpoints, providing a solid basis for HM ecotoxicology assessment. The results indicate that exposure to HM causes dose-dependent inhibition of seed germination, biomass and elongation of seedlings, root–shoot architecture impairments (stunted roots, necrotic lesions), water and nutrient imbalances, and a characteristic chlorosis or necrosis of leaves. The effects of HM stress at the subcellular level include a burst of reactive oxygen species (ROS), leading to lipid peroxidation, higher malondialdehyde (MDA) and electrolyte leakage, and substantial loss of photosynthetic pigments (chlorophyll a, b, and carotenoids). At the same time, affected plants regulate their antioxidant defense system, resulting in changes in the activity of superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), and glutathione S-transferase (GST). Along with relative water content and markers for membrane integrity, these biochemical changes indicate early and sensitive markers of oxidative injury. The review concludes that a combination of morpho-physiological growth traits with oxidation stress/antioxidant biomarkers is needed for a precise diagnosis of HM toxicity. These integrated solutions increase the diagnostic sensitivity and provide guidance for the screening of mitigation measures such as soil amendments, metal-tolerant breeding and application of bio stimulants that will make farming in contaminated environments safer.
ESTIMATION OF CONCENTRATION OF HEAVY METALS IN TURNIP PLANT (BRASSICA RAPA)
Agricultural soils contaminated with heavy metal has emerged as an undetectable threat to food safety and human well-being everywhere in the world. Turnip (Brassica rapa) is particularly vulnerable to the adverse impact of global warming due to its high bioaccumulation property of toxic metals such as cadmium, lead, chromium, arsenic and nickel. With at least small amounts of soil contamination, these contaminants can be transferred to the human food chain. Despite increased research on the estimation of heavy metal in turnip, there are still significant inconsistencies in sample preparation and digestion processes, and analysis methods, which continue to cause wide variation in reported concentrations and inconclusive conclusions on health hazards. This review technically summarizes information on how heavy metal concentrations in turnip can be estimated between 2010 and 2025. The general aims were to critically evaluate the current methodologies of analytical techniques like wet digestion, microwave assisted digestion, flame atomic absorption spectroscopy, graphite furnace AAS, and inductively coupled plasma mass spectrometry, to synthesize world data on metal accumulation patterns and health risks associated with them. The major results were that cadmium and lead are often found in excess of, and even exceeding, the permissible limits of the FAO WHO in turnips cultivated near industrial areas, urban farmland and wastewater irrigated lands. Microwave assisted digestion in combinations with ICP MS or GFAAS had the highest recovery rates of better than 92 percent and lowest limits of detection of microgram per kilogram. The variations in translocation factors between soil of various pH and organic matter content had significant variability with the accumulation of two to five times more metal on the turnip leaves than on the storage roots. Assessment of health risk through target hazard quotient showed that children are more at risk than the adults with chronic daily intake of lead and cadmium due to consumption of turnip being a potential non carcinogenic risk in the contaminated areas. The review finds that harmonized standard operating procedures of sample preparation, constant use of certified reference material and region-specific risk assessment framework are urgently needed to be able to rely on the use of heavy metal in the monitoring of turnip as a food safety regulation
BIOACCUMULATION OF TRACE METALS AND THE COMPROMISED NUTRITIONAL INTEGRITY OF TOMATO SOLANUM LYCOPERSICUM
Heavy metal contamination of soils and irrigation water is a major problem for food security and crop quality worldwide. Tomato (Solanum lycopersicum) is a high value vegetable fruit that is very popular in both fresh and processed forms and is readily contaminated by the uptake of toxic metals (cadmium, lead, arsenic and nickel) from contaminated growing media. This review aims to critically discuss the pathways of accumulating, translocating and accumulating heavy metals in tomato and to review the latest scientific data to assess the impact of metal stress on fruit quality attributes. More than 150 peer reviewed studies have shown that there is a specific pattern for heavy metal accumulation in the roots, leaves and fruits. Cadmium and lead, however, are mobile in the phloem and can be directly transported to developing fruits. Physiologically, metal-induced oxidative stress hinders the photosynthetic efficiency and affects phytohormone signaling. With respect to fruit quality, there have been a number of studies indicating that higher Cd and Pb levels significantly reduced the lycopene content by downregulating the expression of phytoene synthase gene. The soluble sugars and titratable acidity are also decreased which reduces the flavor. Cell wall pectin metabolism changes and causes fruit firmness to decrease. While this may be a stress response to some phenolic compounds, this does not counterbalance the loss of some important nutraceuticals. Fruit pulp critical threshold values are often less than maximum permissible limits for fruit quality degradation. Finally, high level of accumulation of heavy metals in tomato fruits represents a threat to human health because of their consumption as food and significantly reduces the organoleptic and nutritional quality. To ensure consumer health and marketable quality of tomatoes, integrated mitigation measures such as biochar amendments, resistant cultivars and microbial bioremediation are urgently required.
HEALTH RISKS FROM LETTUCE (LACTUCA SATIVA) FROM CONTAMINATED URBAN SOILS: A CRITICAL REVIEW OF METAL UPTAKE AND HUMAN EXPOSURE
Urban agriculture is emerging as an effective approach toward food security, social equity and green space utilization. Urban soils are, however, often polluted with old and current pollutants, including heavy metals (lead, cadmium, arsenic, mercury) and organic pollutants (polycyclic aromatic hydrocarbons [PAHs]). Lettuce, (Lactuca sativa), is a particular health issue among the commonly grown vegetables due to its high transpiration rate, strong tendency to uptake the contaminants in its edible parts and being eaten raw. This review summarizes the most recent science available on the human health risks from eating lettuce that is cultivated in contaminated urban soils. The various components of the human health risk assessment (HHRA) framework for applying it to this pathway are examined systematically: contaminant sources in urban soils, bioavailability and soil-to-plant transfer mechanisms (quantified by bioconcentration factors and translocation factors), exposure assessment (including ingestion rates, body weight parameters), risk characterization (Hazard Quotient (HQ), Hazard Index (HI) and cancer risk (CR) models). Results from a synthesis of lead, cadmium and arsenic values in global HQ/CR case-study cities across North America, Europe, Asia and Africa suggest a high prevalence of exposures above safe limits (HI > 1; CR > 10-4), especially for children who have lower body weights and consume more per kg of body weight. Most importantly, risk outcomes are influenced by soil conditions (pH, organic matter), cultivar of lettuce, and post-harvest conditions (washing and cooking). The review reveals that there are important gaps in knowledge, such as the lack of standardized protocols that consider contaminant bio accessibility and mixture toxicity. We believe that there is an urgent need to develop urban specific soil guideline values and evidence-based mitigation strategies to protect public health based on current evidence.
BRINJAL UNDER SIEGE: MECHANISMS AND MANAGEMENT OF HEAVY METAL CONTAMINATION
The pollution of agricultural soils with heavy metals has become an important problem for food security and human health, especially for vegetable crops grown in peri-urban and industrial regions. The solanaceous vegetable Brinjal (Solanum melongena L.) has a high tendency for root uptake and rapid translocational efficiency of toxic ions and thus is very sensitive to metal toxicity. The present review is an attempt to summarize the existing information regarding the sources, absorption of heavy metals, physiological disturbances and mitigation strategies under heavy metal stress in brinjal. The major toxic metals of concern are: Cadmium (Cd), Lead (Pb), Nickel (Ni), Copper (Cu), and Chromium (Cr) which are usually found in wastewater irrigation, industrial effluents and agrochemicals. Phytotoxic effects in the crop include inhibition of seed germination, stunted groweth, chlorosis, necrosis, and fruit yield and quality reduction, which are dose-dependent with regard to metal exposure. In the biochemical level, heavy metals induce overproduction of ROS which results in lipid peroxidation, loss of electrolytes and induction of antioxidant enzymes like superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD). Molecular responses include induction of phytochelatins (PCs) and metallothioneins (MTs); however, genetics understanding in brinjal is still in early stages as compared to model plants. Soil amendments such as biochar and chitosan, which bind metals and decrease bioavailability, and the use of biochar and foliar application of iron oxide nanoparticles (FeONPs), which boosts antioxidant defense, are some of the promising remediation strategies. Low-accumulating cultivars is a biological solution to the challenge of selection. There are still gaps in knowledge related to field scale testing of nano-remediation, interactions effects between multi-metal contamination, and the lack of molecular marker-assisted breeding programs. This review gives an in-depth account of the mechanism of heavy metal stress in brinjal and proposes future directions to grow brinjal safely.
WASTEWATER-INDUCED HEAVY METAL ACCUMULATION IN OKRA (ABELMOSCHUS ESCULENTUS L.) A COMPREHENSIVE REVIEW OF UPTAKE DYNAMICS AND HEALTH RISKS
Scarcity of fresh water around the world has motivated peri urban farmers to use untreated or partially treated waste water in irrigating vegetable crops such as okra. Nevertheless, toxic heavy metals (cadmium, lead, and chromium) are present in wastewater and accumulate in plant tissues and pose severe threats to human health. This review synthesizes the peer reviewed literature on the dynamics of uptake, distribution pattern of tissue, translocation mechanism and associated health risks of heavy metals in wastewater irrigated okra. The major findings show that roots do accumulate 60 to 85 percent of the total metal load, and fruits do contain lower but often unsafe levels of 0.5 to 3.0 milligrams per kilogram dry weight of cadmium and 1.0 to 8.0 milligrams per kilogram of lead. Cadmium is highly mobile with translocation factors ranging between 1.2 and 2.5, whilst lead is mostly immobile with translocation factors less than 0.5. Health risk assessment indicates that for children, it is more than 75 percent of studies on cadmium and 60 percent on lead, the health risk index is above safe values. The level of cadmium carcinogenic risk commonly surpasses the accepted level of 10-4 in okra in the peri urban areas. Some of the effective mitigation strategies involve waste water pretreatment using constructed wetlands that remove 35 to 60 percent of the metals, soil amendments such as biochar and lime that reduce the metals in fruit by 25 to 60 percent, and adoption of low accumulating cultivar. Boiling causes a reduction of 15-35 percent in the quantity of metals but does not eradicate danger. This review concludes that wastewater irrigated okra often fails to comply with the food safety regulations and presents a significant non carcinogenic and carcinogenic risk especially to children.
IMPACT OF WORKING CAPITAL MANAGEMENT ON FIRMS' PROFITABILITY: EVIDENCE FROM PAKISTAN'S OIL AND GAS EXPLORATION SECTOR
Working capital management plays a key role in determining how financially healthy and efficient a company is, especially in high-cost industries like oil and gas exploration. In Pakistan, this sector is extremely important for the country's energy supply and economic growth, yet it faces serious challenges such as high operational costs, long project timelines, unstable global oil prices, and significant financial risks. Despite its importance, very little research has explored how working capital management actually affects the profits of oil and gas companies in Pakistan, and this study aims to fill that gap. The study looks at key elements of working capital management including the cash conversion cycle, the time taken to collect payments from customers, how long inventory is held, and how long it takes to pay suppliers, and compares these against profitability measures like return on assets and return on equity. Data is taken from publicly listed oil and gas exploration companies in Pakistan and analyzed using statistical methods, while also accounting for factors like company size, debt levels, and growth opportunities. The findings are expected to be highly useful for company managers, investors, and government policymakers, helping them understand the best working capital practices that can boost profits without causing cash flow problems. Overall, this study highlights why smart and careful financial management matters deeply in capital intensive industries and provides a strong foundation for future research across Pakistan's energy sector and other emerging markets.
INVESTIGATING THE EFFECT OF TOURISM, FINANCIAL DEVELOPMENT, AND GLOBALIZATION ON ECOLOGICAL FOOTPRINT IN THE CONTEXT OF PAKISTAN
The purpose of this study to contribute to the existing literature by investigating at the impact of Globalization, Tourism, and Financial Development on Ecological footprint in the Pakistan over the period from 1995 to 2023. The theoretical and statistical framework has been developed to investigate the results. For this purpose, Time series data has been used and analyzed through E-views software by using Regression technique. Data was collected from authentic sources such as the World Bank, Global Footprint Network, and Globalization index. The Environmental Kuznets curve theory were used to explain the purpose of the study. The results of this study indicate significant and positive relationship exists between Ecological Footprint, Financial Development, Globalization, and Tourism. Policy makers should promote sustainable tourism and financial practices while applying regulations to reduce ecological impact. They should also encourage globalization strategies that support ecological protection.
BALOCHISTAN INSURGENCY AND STATE RESPONSE IN POST-MUSHARRAF PAKISTAN: DYNAMICS, CHALLENGES, AND IMPLICATIONS FOR NATIONAL SECURITY
This research analyzes the Balochistan insurgency and the state response in the post-Musharraf era. The main objective of this research is to explore the major aspects behind the creation and continuity of the Balochistan insurgency in Pakistan. They focus on the internal issues, governance challenges, corruption, weaken institution capacity, lack of accountability, and ineffective policy implementation. It also examines the grassroots challenges and the state's response to the Balochistan insurgency. The impact of development projects like the China-Pakistan Economic Corridor on the advancement. The study chooses a qualitative method and uses secondary data such as scholarly literature, articles, journals, and official reports. By using theoretical and analytical structures to demonstrate the evolving aspects of the Balochistan insurgency and its interconnection of internal and external causes. According to the theoretical framework informed by the fragile political system, perceived injustice and historical grievances provide a better understanding of the reasons for the insurgency in a rich resource region. General Pervaiz Musharraf's era shows that the ruling period created a hurdle for the Balochistan insurgency and a highly influential military presence in the Baloch regions. Many military operations were held in Balochistan to counter the Balochistan insurgency. The findings of this research explore governance weakness, unfair resource distribution, and poverty, which are not the only major reasons. The CPEC plays an important role in the development of Balochistan. The CPEC gives fewer opportunities to local people and limited participation in their policies. The role of India and Afghanistan is significant for the development of the Baloch Insurgents. The Gwadar port is also crucial for the development of Balochistan. In conclusion, the Balochistan insurgency in the post-Musharraf era has multifaceted and many aspects of governance issues, political instability, and unequal development, creating political marginalization and changing the local perception of Baloch nationalists. The state should adopt effective administrative policies, equal representation in decision-making, and fair distribution for the sustainable development of Balochistan and the security of Pakistan.
PERFORMANCE OF DISTRICT TEACHER EDUCATORS AND IMPLEMENTATION GAPS IN CONTINUOUS PROFESSIONAL DEVELOPMENT OF PRIMARY SCHOOL TEACHERS: EVIDENCE FROM PAKISTAN
Continuous professional development (CPD) is widely recognized as a key mechanism for improving teachers’ professional competence and classroom practices. However, the effectiveness of CPD programs largely depends on the role of instructional support providers who translate policy frameworks into school-level practices. This study evaluates the performance of District Teacher Educators (DTEs) in implementing CPD practices among primary school teachers in Pakistan. Using a quantitative survey design, data were collected from primary school teachers, DTEs, and cluster heads through a structured instrument based on nine CPD performance indicators, including lesson planning, assessment practices, classroom management, student interaction, and activity-based teaching. The findings reveal that DTE performance was above average but remained below the expected level of implementation. Significant gaps were identified between DTE self-reported practices and teachers’ perceptions regarding the execution of CPD activities. The results indicate a disconnect between the intended CPD framework and its practical implementation at the school level. The study highlights the need for strengthening mentoring systems, improving monitoring mechanisms, and enhancing district-level professional support structures to ensure effective teacher development. The findings contribute to understanding the challenges of translating teacher professional development policies into sustainable classroom practices in developing education systems.
PHARMACOGENOMICS AND ARTIFICIAL INTELLIGENCE FOR PRECISION DRUG THERAPY AND SURGICAL OUTCOME OPTIMIZATION IN PAKISTAN
The integration of pharmacogenomics and artificial intelligence (AI) has emerged as a transformative approach in precision medicine, enabling individualized drug therapy and enhanced surgical outcome optimization through genetic profiling and predictive analytics. This study examines the synergistic role of pharmacogenomics and AI in improving therapeutic efficacy, reducing adverse drug reactions, and supporting clinical decision-making within Pakistan’s healthcare system, where precision medicine adoption remains limited. A quantitative, cross-sectional research design was employed, using structured survey data from healthcare professionals to assess the influence of pharmacogenomics, AI adoption, and healthcare system readiness on precision drug therapy and surgical outcomes. Statistical techniques, including regression analysis and structural equation modeling, were applied to evaluate relationships among variables. The findings reveal that both pharmacogenomics and AI significantly and positively influence precision drug therapy and surgical outcome optimization. AI demonstrated a stronger predictive impact on surgical outcomes, while pharmacogenomics played a dominant role in drug response optimization. However, healthcare system readiness emerged as a critical moderating constraint, limiting the full implementation of precision medicine practices in Pakistan. The study concludes that effective integration of pharmacogenomics and AI can substantially enhance clinical outcomes, but requires strengthened genomic infrastructure, AI-enabled clinical systems, and workforce capacity development in Pakistan’s healthcare sector.
TRANSITION METAL NANOSTRUCTURED CATALYSTS FOR ENERGY CONVERSION AND STORAGE APPLICATIONS: A COMPREHENSIVE REVIEW
The global energy landscape is undergoing a significant transition due to increasing concerns over fossil fuel depletion, rising energy demands, and environmental pollution [27,28,36]. In this scenario, the development of efficient and sustainable energy conversion and storage systems has become a major scientific priority [29,36]. Among the various materials investigated, transition metal nanostructured catalysts have attracted considerable attention owing to their unique physicochemical properties and broad application potential [32,34,38]. These materials, particularly based on Fe, Co, Ni, Mn, and Cu and their corresponding compounds such as oxides, sulfides, phosphides, and carbides, offer a cost-effective alternative to noble metal catalysts [32,38]. Their nanoscale dimensions provide a high density of active sites, improved electron transfer behavior, and tunable surface chemistry, all of which directly influence catalytic performance [30,38]. In electrochemical energy systems, these catalysts play a central role in key reactions such as hydrogen evolution reaction (HER), oxygen evolution reaction (OER), and oxygen reduction reaction (ORR) [4–6,10,19]. These reactions are fundamental to technologies like water electrolysis, fuel cells, and metal–air batteries. In parallel, transition metal nanostructures have also shown promising results in energy storage devices, including lithium-ion batteries, sodium-ion batteries, and supercapacitors, where they enhance capacity, rate performance, and cycling stability [23,24,27]. Despite these advantages, several challenges still limit their large-scale application. Issues such as structural instability under operating conditions, particle agglomeration, and insufficient long-term durability remain critical concerns [30,31]. Recent research has therefore focused on improving material design through strategies such as heterostructure formation, doping, defect engineering, and development of single-atom catalysts [30,31,38]. Overall, transition metal nanostructured catalysts represent a rapidly evolving research area that bridges fundamental materials chemistry with practical energy technologies, offering promising pathways toward sustainable energy systems [32,34].
SMART SAFETY INTEGRATION IN TRADITIONAL CHAFF CUTTER MACHINES TO PREVENT UPPER LIMB AMPUTATIONS IN SOUTH ASIA
The use of chaff cutter machines is common in South Asia’s rural communities when harvesting food for animals. While chaff cutter machines are vital in agriculture, they are the leading contributor of severe upper limb injuries, which include amputations in the fingers and hands. According to epidemiological studies done in various parts of Pakistan, India, and Nepal, chaff cutters are responsible for 45% of injuries sustained in agricultural machinery. Chaff cutter injuries account for about 40% of 500 recorded injuries due to agricultural machinery in Pakistan within six months. These injuries result in amputations, the rate of which varies between 35% and 60%. Most of the people injured using chaff cutter machines are less than 30 years old. The main reason behind such injuries arises from faulty engineering designs of the machinery. Typically, the conventional chaff cutter functions with exposed feed rollers along with a rotating blade without having any automatic detecting device. After entrapment, due to the pull of the feed rollers and the momentum of the flywheel, release becomes highly unlikely, often leading to irreversible harm. In order to deal with the issue, this study combines evidence collected from epidemiology with an engineering approach to improve on safety design. Such an improvement comprises of a hand detecting system, an automatic braking system for stopping the blade rotation, an enhanced blade cover along with an emergency switch. This new design intends to interfere in the process