The Nexus of Sustainability,(ISSN Online:3106-907X; ISSN Print:3106-9061) is a multidisciplinary, open-access, quarterly, double-blind peer-reviewed publication. The Journal undertakes to complete the double-blind peer-review process within one (01) month of submission and to duly notify the author(s) of the decision. The Editorial Board, while maintaining academic rigor and integrity, endeavors to provide timely and constructive feedback within the stipulated period, thereby ensuring an efficient and transparent publication process. The Journal is published under the auspices of the International Institute of Modern Research [SMC – Private] Limited, a legal entity duly incorporated and registered with the Securities and Exchange Commission of Pakistan (SECP) under Registration # 0307037.
International Institute of Modern Research
JOB SATISFACTION AS A MEDIATOR IN THE RELATIONSHIP BETWEEN ABUSIVE SUPERVISION AND PARAMEDICS’ WELL-BEING
This study examines the relationship between abusive supervision and paramedics’ well-being, with a particular focus on the mediating role of job satisfaction, and also explores gender differences among paramedics. Given the hierarchical nature of healthcare organizations and the emotionally demanding aspects of paramedical work, understanding these dynamics in culturally specific contexts, such as Pakistan, is critical. A correlational research design was employed, using purposive sampling to include 154 male and 146 female paramedics aged 25–50 years. Data were collected using the Abusive Supervision Scale, the BBC Well-being Scale, and the Job Satisfaction Scale. Findings revealed a strong negative relationship between abusive supervision and paramedics’ physical and psychological well-being, which was mediated by job satisfaction. Specifically, higher levels of abusive supervision were associated with lower job satisfaction, resulting in reduced psychological and physical well-being. Independent t-tests indicated no significant gender differences in abusive supervision or job satisfaction; however, male paramedics reported significantly higher psychological (p = .040) and overall well-being (p = .016) compared to females. These results suggest that workplace stressors affecting well-being are shaped by gender-specific experiences and societal expectations. The study highlights the detrimental impact of abusive supervision on paramedics’ health and identifies job satisfaction as a protective factor, consistent with Conservation of Resources (COR) theory. The findings underscore the importance of leadership reform, supervisor accountability, staff well-being initiatives, and gender-inclusive support systems in Pakistani healthcare settings, offering valuable insights for policymakers and healthcare leaders.
Abusive Supervision, Job Satisfaction, Employee Well-Being, Paramedical Professionals
EVALUATING ACADEMIC PERFORMANCE DIFFERENCES USING PARAMETRIC AND NON-PARAMETRIC TESTS
This study examines the effectiveness of parametric and non-parametric methods in analyzing academic performance differences based on gender and study time, with GPA as the outcome measure. Independent t-tests and ANOVA were employed alongside Mann–Whitney U and Kruskal–Wallis tests. Descriptive analysis revealed that female students and those studying more than two hours daily tended to have slightly higher GPAs. Assumption tests confirmed normality and homogeneity of variances, supporting the appropriateness of parametric techniques. While no statistically significant differences were observed, both parametric and non-parametric methods consistently indicated a positive relationship between study time and GPA. These findings demonstrate methodological consistency across statistical approaches and highlight the practical importance of study habits in influencing academic performance, even when statistical significance is not evident.
Parametric Tests, Non-Parametric Tests, ANOVA, Kruskal–Wallis Test, Visual Diagnostics, Assumption Testing
EXAMINING THE EFFECTS OF GREEN SUPPLY CHAIN AND ORGANIZATIONAL PERFORMANCE METRICS ON BUSINESS SUCCESS
Green Supply Chain Management (GSCM), an environmentally conscious approach to traditional supply chain management (SCM), is gaining increasing attention in developing countries. This growth is driven by its recognized benefits for both the environment and the economy, alongside heightened awareness of environmental sustainability. Organizations are increasingly striving to demonstrate their commitment to sustainable practices. This study investigates the impact of implementing GSCM on environmental performance (EP), operational performance (OP), market performance (MP), and overall business performance in the context of a developing country, specifically Pakistan. Data were collected via a structured questionnaire administered to 101 supply chain professionals working in manufacturing companies. The conceptual framework was developed based on a review of existing literature, and Partial Least Squares-Structural Equation Modeling (PLS-SEM) was employed to test the hypotheses. Findings indicate that while GSCM positively influences overall business performance, this effect was not statistically significant. However, significant positive impacts were observed on market performance, environmental performance, and operational performance. These results suggest that improvements in MP, EP, and OP through GSCM practices present opportunities to enhance overall business performance. In the context of a developing country like Pakistan, this research contributes to the literature by exploring how GSCM affects key performance dimensions and overall business outcomes. The findings offer valuable insights for supply chain professionals aiming to implement sustainable practices and provide policy recommendations for organizations seeking to advance their GSCM initiatives
Green Supply Chain Management, Operational Performance, Market Performance, Environmental Performance, Business Performance
ENHANCING HOSPITAL EFFICIENCY AND REDUCING PATIENT WAITING TIMES THROUGH PUBLIC-PRIVATE PARTNERSHIPS
This policy paper proposes a Public-Private Partnership (PPP) as an effective model to address the critical challenges facing healthcare in Karachi. Public hospitals in the city experience severe overcrowding, often exceeding 120% occupancy, while trust-based healthcare facilities remain underutilized, with occupancy rates below 75%. To address this imbalance, the paper advocates an integrative model that redistributes patient loads, enhances operational efficiency, and ensures equitable access to healthcare services. Drawing on successful PPP experiences from countries such as Kenya, Lesotho, and Sri Lanka, the paper outlines a three-step implementation plan: stakeholder engagement, pilot testing, and scale-up, supported by digital integration and real-time monitoring systems. Key themes emerging from stakeholder interviews include operational feasibility, financial incentives, public-private coordination, quality assurance, and regulatory support. The proposed model seeks to optimize existing healthcare infrastructure, reduce patient turnaround times, and promote inclusive and sustainable services for marginalized communities. If implemented effectively, this initiative could serve as a replicable model for other high-density cities in the Global South.
Public-Private Partnerships, Healthcare Efficiency, Hospital Overcrowding, Trust-Based Hospitals, Access to Healthcare, Patient Outcomes, Bed Utilization, Health Policy Framework
AN ANALYSIS OF TEACHERS’ COLLABORATIVE EFFORTS AS A DETERMINANT OF EFFECTIVE SCHOOL MANAGEMENT
Teachers are key stakeholders in the education sector, entrusted with responsibilities encompassing teaching, leadership, and school management. This study examined the role of teachers’ collaboration in promoting effective management of secondary schools in Khyber Pakhtunkhwa, Pakistan. The objectives were to identify the impact of teachers’ collaboration on school management and to propose strategies for enhancing collaborative practices among school staff. A quantitative research design was employed, targeting a population of 3,419 secondary school teachers, from which a sample of 346 was selected through simple random sampling. A structured questionnaire was developed, validated, and piloted for data collection. Self-administered questionnaires were used, and the data were analyzed using mean scores, standard deviations, and chi-square tests. Findings indicated that teachers actively collaborate in managing academics, co-curricular activities, and school finances; overseeing material and human resources; maintaining school hygiene; and responding to emergencies. Based on these findings, the study recommends targeted professional development programs for both teachers and school heads to strengthen collaborative practices and enhance the management of secondary schools.
APPLICATION OF TIME SERIES MODELS TO PREDICT DAILY EMERGENCY DEPARTMENT VISITS
With the country’s growing population, the demand for healthcare services has increased, resulting in overcrowding in hospital Emergency Departments (EDs). Such overcrowding can adversely affect the healthcare system by diminishing patient satisfaction and quality of care, extending patient length of stay, and placing additional strain on hospital resources. To mitigate these challenges, researchers have emphasized the importance of forecasting ED patient arrivals—on hourly, daily, monthly, or yearly scales—to enable efficient resource planning and management. This study focuses on forecasting daily patient arrivals at the ED of District Headquarters (DHQ) Hospital Charsadda, with the aim of supporting hospital management in enhancing operational efficiency. Data on daily ED arrivals from January 2024 to January 2025 were collected from the hospital records. A Seasonal ARIMA (SARIMA) model was applied, with SARIMA (1, 0, 1) (2, 1, 3) _7 identified as the best-fit model based on the lowest values of the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). Model adequacy was confirmed through the Ljung-Box test for autocorrelation and the Jarque-Bera test for normality of residuals, validating the assumptions of the time series model. The selected SARIMA model produced an MAE of 13 and a MAPE of 2.15, demonstrating high forecasting accuracy. These results indicate that SARIMA is an effective tool for predicting daily ED arrivals and can assist hospital management in optimizing staff scheduling and resource allocation.
MECHANISMS AND MANAGEMENT OF SOIL ORGANIC MATTER AND NUTRIENT CYCLING IN AGRICULTURE
Soil organic matter (SOM) is a critical determinant of soil fertility and agricultural productivity, primarily through its regulation of nutrient cycling processes essential for plant growth. Comprising a spectrum of organic constituents—from fresh plant residues to highly decomposed humic substances—SOM modulates the dynamics of macro- and micronutrients via mechanisms such as mineralization, immobilization, complexation, and sorption. These processes govern the availability, mobility, and retention of key nutrients, including nitrogen (N), phosphorus (P), sulfur (S), and potassium (K), within the soil matrix. Additionally, SOM enhances cation exchange capacity, stabilizes soil pH, and improves soil structure, thereby optimizing the soil’s capacity to retain nutrients and moisture. This review explores the composition and classification of SOM, its biochemical interactions with essential nutrients, and the microbiological and physicochemical mechanisms underpinning SOM-mediated nutrient cycling. It further evaluates the influence of agricultural practices—including tillage, crop rotation, residue management, and organic amendments—on SOM dynamics and nutrient availability. While conventional practices may accelerate SOM depletion and disrupt nutrient cycling, conservation-oriented approaches offer effective strategies to enhance SOM levels and maintain nutrient balance. Emerging management techniques, such as integrated nutrient management, biochar application, and precision farming, are highlighted for their potential to sustain SOM and improve nutrient-use efficiency. Synthesizing current evidence, this review underscores the pivotal role of SOM-centered strategies in enhancing soil fertility, reinforcing agroecosystem resilience, and promoting sustainable intensification of agriculture
EXPLORING LANGUAGE AND THEMATIC FOREGROUNDING IN RICHARD CONNELL’S THE MOST DANGEROUS GAME
This study presents a stylistic analysis of Richard Connell’s short story The Most Dangerous Game through the lens of Foregrounding Theory, originally proposed by Jan Mukařovský (1964) and later expanded by Geoffrey Leech (1969). The research investigates the roles of linguistic deviation and parallelism as key foregrounding mechanisms that underscore the narrative’s central themes of violence, morality, and survival instinct. By identifying and categorizing lexical, syntactic, phonological, and semantic deviations, along with patterns of repetition and structural parallelism, the study demonstrates how stylistic choices capture reader attention and emphasize thematic tensions. Findings reveal that Connell’s strategic use of language not only heightens suspense and emotional intensity but also challenges conventional moral boundaries, prompting reflection on the dichotomy between civilization and savagery. This study affirms the relevance of Foregrounding Theory in literary analysis and provides valuable insights for future research in stylistics, comparative literature, and literary pedagogy.
EMPLOYER PERSPECTIVES ON ENGLISH COMMUNICATION SKILLS: AN INTER-INDUSTRY ANALYSIS IN PAKISTAN
English, as a global lingua franca, serves as a gateway to career advancement in today’s interconnected world. Proficiency in English is particularly crucial for new graduates aiming to succeed in their careers, as it remains the official language and primary mode of communication in professional settings within Pakistan’s competitive job market. Aligning educational outcomes with industry requirements necessitates a clear understanding of recruiters’ expectations. This study aims to investigate recruiters’ preferences for specific English language skills in the hiring process. Employing a quantitative repeated-measures design, data were collected from 19 companies in Karachi using a convenient sampling method. Hiring professionals from diverse sectors—including Information Technology, Manufacturing, Education, and Healthcare—participated in the study. Data analysis was conducted using IBM SPSS version 21, and a paired-sample t-test was applied to compare speaking and writing skills. Results showed a mean difference of 3.7894 (SD = 2.25) and a t-value of 7.340 (df = 18), indicating that recruiters highly value overall English proficiency. Factors such as pronunciation, general confidence, and enunciation significantly influence hiring decisions. The analysis further revealed that speaking skills are prioritized over writing skills in recruitment decisions.
EXAMINING THE MEDIATING ROLE OF TRANSPARENCY IN THE RELATIONSHIP BETWEEN JUSTICE AND CARBON REDUCTION: A GLOBAL COMPARATIVE ANALYSIS
This study explores the pivotal role of judicial effectiveness and access to information in mitigating greenhouse gas (GHG) emissions across countries. Utilizing cross-country panel data and employing both Ordinary Least Squares (OLS) regression and Structural Equation Modeling (SEM), the research examines how robust judicial systems and transparency mechanisms impact environmental outcomes. Findings indicate that judicial effectiveness significantly curbs GHG emissions by ensuring the enforcement of environmental regulations, while access to information enhances this effect by promoting accountability and public engagement. The analysis also identifies economic growth, population expansion, and trade as major contributors to emissions, whereas innovation acts as a mitigating factor. These results highlight the importance of reinforcing legal frameworks, improving transparency, and fostering innovation to achieve climate objectives. The study provides actionable policy insights for strengthening judicial institutions and enhancing access to information, enabling countries to implement climate policies more effectively and reduce their environmental footprint.
VISUAL ANALYSIS OF BORDER DECORATION IN MUGHAL MINIATURE PAINTINGS
The Mughal era is renowned for its rich cultural and artistic heritage, with miniature painting standing out as a key expression of its aesthetic values. Among its distinctive features, border decoration played a vital role—not only enhancing visual appeal and manuscript illumination but also offering physical and symbolic protection to the artwork. This paper presents a visual analysis of border decoration in Mughal miniature paintings, focusing on motifs, colors, layouts, and stylistic elements. By examining these often-overlooked details, the study highlights the artistic techniques and cultural significance embedded in Mughal border design.
AI-DRIVEN MODELING AND OPTIMIZATION OF DYNAMIC ELECTROCHEMICAL RESPONSES IN PEM WATER ELECTROLYSIS SYSTEMS
Proton Exchange Membrane (PEM) water electrolysis is key for sustainable hydrogen production, but optimizing dynamic electrochemical responses is challenging due to complex interactions among temperature, pressure, and current density. This study develops AI-driven models to predict and optimize PEM electrolyzer performance across various operating conditions to enhance hydrogen yield and energy efficiency. Data from ten PEM electrolysers were used to train models with machine learning techniques including Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Decision Trees. Hyperparameters were optimized via Grid Search and Genetic Algorithms, while PCA and SHAP were applied for feature selection. Reinforcement learning and evolutionary algorithms tuned operational parameters. The ANN model achieved high accuracy (R² = 0.93), and optimization improved hydrogen production by 30% and reduced energy consumption by 15%. These results demonstrate that AI-based modeling and optimization significantly boost PEM electrolyzer performance, advancing sustainable hydrogen generation
ACADEMIC COMPETENCE, PERCEIVED TEACHER-STUDENT RELATIONSHIP, AND PROCRASTINATION IN UNIVERSITY STUDENTS
This study examined the relationship between academic competence, perceived teacher-student relationship, and procrastination among university students. Two hypotheses were tested: (1) significant relationships exist between academic competence, perceived teacher-student relationship, and procrastination; (2) academic competence predicts perceived teacher-student relationship and procrastination. A total of 300 students (151 males, 149 females) from Gujranwala, Lahore, and Sialkot participated via convenience sampling. Data were collected using the Academic Competence Scale, Student-Instructor Relationship Scale, and Student Procrastination Scale. A cross-sectional design and regression analysis were employed. Results supported both hypotheses, showing significant correlations (p < .05) and that academic competence significantly predicts teacher-student relationship quality and procrastination (p < .05). These findings highlight the impact of psychological and psychosocial factors on student behavior.
LEADERSHIP IN INTERNATIONAL CONSTRUCTION PROJECTS: EFFECTS ON PAKISTAN’S ECONOMY AND DIPLOMACY
Leadership in international construction projects is vital for Pakistan’s economic growth and diplomatic relations. Effective leadership ensures the successful delivery of major infrastructure initiatives like the China-Pakistan Economic Corridor (CPEC), boosting trade, investment, and connectivity. It drives timely completion, cost efficiency, and quality, attracting foreign investment and strengthening Pakistan’s global reputation. Skilled leadership also enhances diplomatic ties—especially with China—by fostering trust and cooperation, while managing geopolitical and socio-political challenges through sustainable development and community engagement. Overall, strong leadership in these projects underpins Pakistan’s infrastructure progress and international partnerships
OPTIMIZED R-CNN FOR REAL-TIME PASSPORT VERIFICATION AND FORGERY DETECTION
Manual and semi-automated passport inspections at airports cause delays and are prone to human error, especially under high passenger volumes and challenging imaging conditions. We propose a fully automated, real-time passport verification system achieving over 90% accuracy with sub-second inference on commodity GPUs. Our dataset includes 65+ country-specific passport formats from public repositories, lab captures, and synthetic augmentations. A region-based CNN with a ResNet-50 backbone and feature pyramid network detects passport regions, while machine vision extracts the Machine Readable Zone (MRZ) for checksum validation. Evaluation metrics include precision, recall, F1 score, mean average precision (mAP) at IoU thresholds 0.50 and 0.75, and latency. The system processes images in 0.75s on average, attaining 95% accuracy and outperforming classical OCR pipelines by 13 percentage points in mAP@0.50. False acceptance rates remain below 1% under variable lighting, occlusion, and print artifact conditions. Ablation studies show geometric and color augmentations improve accuracy from 88% to 95%, with diminishing returns beyond 1024×768 input resolution. Improvements are statistically significant (p < 10⁻⁴, Cohen’s d > 0.8). This work demonstrates a robust, efficient passport verification solution integrating multi-scale detection, MRZ validation, and optimized inference, paving the way for fully autonomous smart gate ecosystems with multilingual MRZ parsing and face-passport matching.
INVESTIGATING CONTINUOUS PROFESSIONAL DEVELOPMENT OF PUBLIC SCHOOL TEACHERS TO ENHANCE EDUCATION QUALITY IN DISTRICT FAISALABAD
This study examines the impact of Continuing Professional Development (CPD) programs on teachers’ professional growth in public primary schools in District Faisalabad. A sample of 104 teachers from 31 randomly selected schools participated, with data collected via standardized questionnaires and analyzed using SPSS. Findings reveal that CPD activities, including training and mentoring, significantly enhance teaching methods, leading to improved student attitudes, learning outcomes, and academic performance. Statistical analysis using mean scores, standard deviation, and percentages identified key factors influencing teachers’ engagement in CPD. The results emphasize the importance of ongoing professional development in improving teaching quality and recommend expanding training opportunities to support educators' continuous growth.
Continuous Professional Development (CPD)
BOARD ATTRIBUTES AND AUDIT EFFECTIVENESS: GENDER DIVERSITY AS A MODERATOR
This study investigates the impact of board characteristics on audit quality, focusing on the moderating role of female directors in non-financial companies listed on the Karachi Stock Exchange (KSE-100) from 2019 to 2023. Using secondary data from 70 companies, the research examines board independence, female directors, and board size as key variables, with firm size and auditor fees as controls. Employing correlation analysis and GMM regression, results reveal that gender diversity significantly enhances the positive effect of board independence on audit quality. The findings highlight the importance of inclusive boards and recommend promoting female participation to strengthen governance and audit outcomes. This study offers valuable insights for policymakers and corporate leaders on fostering gender diversity to improve audit effectiveness. Future research could extend to financial firms, other governance factors, and the long-term impact of diverse boards on financial performance and stakeholder trust
GREEN-SOURCED METAL OXIDE NANOPARTICLES: SYNTHESIS AND CATALYTIC EFFICIENCY FOR ENVIRONMENTAL REMEDIATION IN WATER
Background: Synthetic dyes in industrial wastewater cause significant ecological pollution, and conventional remediation methods are often inefficient and unsustainable. Green nanotechnology offers an eco-friendly alternative for pollutant removal. Aim: This study focuses on the green synthesis of zinc oxide (ZnO) and iron oxide (Fe₂O₃) nanoparticles using leaf extracts from Azadirachta indica and Moringa oleifera, characterizing their physicochemical properties, and evaluating their catalytic efficiency in degrading methylene blue dye from aqueous solutions. Method: Nanoparticles were synthesized using aqueous leaf extracts as reducing and stabilizing agents. Characterization techniques included FTIR, XRD, SEM, TEM, and BET surface analysis. Catalytic activity was assessed via photodegradation of methylene blue under UV light, with recyclability tested over four cycles. Results: FTIR confirmed phytochemicals facilitating nanoparticle synthesis. XRD identified rhombohedral and wurtzite structures for Fe₂O₃ and ZnO, respectively. SEM and TEM showed uniform spherical nanoparticles at the nanoscale. BET analysis revealed larger surface areas for green-synthesized particles compared to commercial ones. Green ZnO degraded 96.5% of methylene blue within 60 minutes, outperforming commercial ZnO. Both nanoparticle types demonstrated excellent reusability with minimal activity loss. Conclusion: Green-synthesized ZnO and Fe₂O₃ nanoparticles exhibit superior physicochemical and catalytic properties compared to commercial counterparts, offering a sustainable, eco-friendly solution for wastewater treatment applications.
FACULTY PERCEPTIONS OF BARRIERS TO PROFESSIONAL DEVELOPMENT PARTICIPATION: A QUALITATIVE STUDY
Professional development is vital in education, as skilled and well-prepared teachers enhance the teaching-learning process. This qualitative study, grounded in an interpretivist and phenomenological approach, investigates faculty members’ perceptions of barriers hindering their participation in professional development activities at the University of Education. Using purposive sampling, 45 faculty members from various campuses were interviewed through semi-structured interviews until data saturation. Analysis with NVivo Plus revealed two main themes: Personal and Professional Barriers. Personal barriers included lack of family support, low motivation, financial constraints, and health issues. Professional barriers comprised heavy workload, additional administrative tasks, unsupportive attitudes, time constraints, inadequate financial incentives, limited facilities, restricted development opportunities, and favoritism. The study recommends that university administration increase professional development opportunities, reduce workloads, and provide support such as induction programs, workshops, higher education opportunities, and research grants. Implementing these strategies can foster a motivated, skilled faculty, ultimately enhancing the institution’s reputation and success.
EMOTIONALLY INTELLIGENT AI: IMPROVING HUMAN-COMPUTER INTERACTION WITH NLP AND SENTIMENT ANALYSIS
This study explores the development of emotionally intelligent AI systems that enhance human-computer interaction by recognizing and responding to user emotions using NLP and sentiment analysis. Unlike traditional AI tools with fixed responses, the proposed platform adapts its replies based on real-time emotion recognition, employing a transformer-based generative model that achieves 92% accuracy in detecting emotions. Evaluated for coherence, empathy, and relevance, the system produces realistic and empathetic conversations, marking a significant advancement in AI agents. Applications span customer service, healthcare, and psychological support, where the AI can detect frustration or stress and respond appropriately to improve user experience and trust. Ethical management of emotional data remains a priority as such systems become widespread. Future research will focus on detecting complex emotions, incorporating multimodal inputs, and enhancing intercultural communication. This work paves the way for more human-centric, empathetic AI, bridging effective task performance with meaningful emotional engagement.
Human computer interaction (HCI), Natural language processing (NLP), Sentiment analysis, Emotion recognition, Empathetic response generation, Transformer model, Ulti modal emotion analysis, Contest aware AI
DECODING DIGITAL HEURISTICS: MIXED-METHODS ANALYSIS OF PSYCHOLOGICAL DRIVERS IN GOOGLE SEARCH BEHAVIOR
This study uses a mixed-methods corpus analysis of Google search queries to explore how heuristic thinking influences users' language and query formulation. Combining quantitative linguistic analysis with qualitative thematic coding, it examines the interaction between fast, intuitive (System 1) and slow, deliberative (System 2) reasoning as described by Kahneman (2011). Findings reveal distinct lexical and syntactic patterns linked to cognitive biases like anchoring and availability. Integrating corpus linguistics with psychological theory, the study highlights how digital search behavior reflects underlying cognitive heuristics. The results have implications for designing more adaptive, user-centered search algorithms and advance interdisciplinary understanding between psycholinguistics and cognitive science. Additionally, the research examines how Google’s algorithms influence language use and can perpetuate societal biases, contributing valuable insights to computational linguistics, digital humanities, and information science
VENTURE CAPITAL CERTIFICATION AND FINANCIAL STABILITY: EVIDENCE FROM CHINESE IPOS
This study examines how venture capital (VC) certification reduces financial distress and lowers the cost of capital for Chinese IPOs. Analyzing 1,683 non-financial firms that went public from 2006 to 2016, the findings show that VC-backed firms face significantly less financial distress and benefit from better financing terms than non-VC-backed firms. Using propensity score matching to address endogeneity, the study confirms that VCs select firms with strong prospects and reduced financial risk. Notably, reputable and independent private VCs have a stronger impact on lowering financial distress and financing costs. Overall, the results highlight the critical certification role of VC backing in enhancing financial stability and capital efficiency for IPO firms.
TIME SERIES FORECASTING OF DAILY EMERGENCY DEPARTMENT ARRIVALS
Rising population pressures have led to overcrowding in hospital Emergency Departments (ED), impacting patient care and resource management. This study forecasts daily ED arrivals at District Headquarters (DHQ) Hospital Charsadda using data from January 2024 to January 2025. A seasonal ARIMA (SARIMA) model—specifically SARIMA (1,0,1)(2,1,3)₇—was identified as the best fit based on AIC, BIC, MAE, and MAPE criteria. Model diagnostics confirmed its validity, with an MAE of 13 and MAPE of 2.15, demonstrating high accuracy. These results suggest SARIMA is effective for predicting daily ED demand, enabling better staff scheduling and resource allocation to mitigate overcrowding.
SOIL ORGANIC MATTER AND NUTRIENT CYCLING IN AGRICULTURE: MECHANISMS AND MANAGEMENT
Soil organic matter (SOM) plays a vital role in maintaining soil fertility and supporting nutrient cycling essential for plant growth. Through processes like mineralization, immobilization, complexation, and sorption, SOM regulates the availability and retention of key nutrients such as nitrogen, phosphorus, sulfur, and potassium. It also enhances cation exchange capacity, buffers pH, and improves soil structure and moisture retention. This review explores the composition, classification, and nutrient interactions of SOM, along with the microbiological and physicochemical mechanisms driving SOM-mediated nutrient cycling. It also examines how agricultural practices—such as crop rotation, residue management, and organic amendments—affect SOM dynamics. While conventional practices can deplete SOM and disrupt nutrient cycles, conservation strategies like integrated nutrient management, biochar application, and precision farming can sustain SOM and improve nutrient-use efficiency. Overall, SOM-centered management is key to enhancing soil fertility, promoting agroecosystem resilience, and advancing sustainable agriculture.
FOREGROUNDING IN LANGUAGE AND THEME IN THE MOST DANGEROUS GAME
This study applies Foregrounding Theory to Richard Connell’s The Most Dangerous Game, focusing on linguistic deviation and parallelism to explore themes of violence, morality, and survival. Using examples of lexical, syntactic, phonological, and semantic deviation, along with repetition and structural parallelism, the analysis reveals how Connell’s stylistic choices heighten suspense and challenge moral boundaries. The findings underscore the role of language in deepening thematic impact and demonstrate the value of Foregrounding Theory in literary interpretation and stylistic analysis.
EMPLOYER PRIORITIES FOR ENGLISH COMMUNICATION SKILLS IN PAKISTAN: AN INTER-INDUSTRY HR SURVEY
In Pakistan’s competitive job market, English serves as the primary language of professional communication and is essential for career advancement. This study investigates employers’ preferences for specific English communication skills in recruitment. Using a quantitative repeated-measures design, data were collected from HR professionals across 19 companies in Karachi, spanning industries such as IT, manufacturing, education, and healthcare. A paired-sample t-test revealed that speaking skills are significantly more valued than writing skills (mean difference = 3.79, SD = 2.25, t(18) = 7.34). Recruiters prioritize overall English proficiency, with particular emphasis on pronunciation, confidence, and enunciation, all of which influence hiring decisions.
JUSTICE, TRANSPARENCY & CARBON REDUCTION: A GLOBAL PERSPECTIVE
This study explores how judicial effectiveness and access to information impact greenhouse gas (GHG) emissions across countries. Using cross-country panel data with OLS regression and Structural Equation Modeling, it finds that strong judicial systems and transparency significantly reduce emissions by enforcing environmental laws and promoting accountability. Economic growth, population, and trade drive emissions, while innovation mitigates them. The findings highlight the need to strengthen legal institutions, improve transparency, and foster innovation to support effective climate action and policy implementation.