Articles

The Heat-Affected Zone (HAZ) is one of the major parameters which determines the structural integrity in welded API 5L X52 pipelines, especially in a sour gas service containing Hydrogen Sulphide (H2S) [1]. This thorough review paper performed the analysis of different international standards including Det Norske Veritas Germanischer Lloyd DNVGL-ST-F101, American Petroleum Institute API 1104, National Association of Corrosion Engineers NACE MR0175 and American Society of Mechanical Engineers ASME B31.8. The researcher analysed the governing and regulation of Heat Affected Zone microstructure and associated properties including strength, hardness and toughness through the specifications like heat values, time between passes and Post Weld Heat Treatment (PWHT), welding specifications and qualification of welding procedures, welders and consumables [2]. By collecting and analysing the data from recent studies (2018-2025), the researchers found out that the standards focusing on prescribing strict recipes for welding and qualification procedures like DNVGL-ST-F101, including explicit heat input limits (typically 1.0-2.0 kJ/mm), obligatory post-weld heat treatment (PWHT), and rigorous consumable qualifications, perform well in Heat Affected Zone in sour gas service. The maximum hardness retirement i.e. 22 HRC (248 HV) obligated for sour media creates a critical limitation that forces optimization of welding procedures. The standards which focus on final quality or the end results rather than prescribing any specific method for producing the weld (Performance-based standards) like API 1104 remains less stringent which results in greater variation in properties around the weld i.e. the HAZ area impacting the service reliability in a worse manner during the sour media [3]. Contemporary world adopting new digital welding techniques for monitoring during weld production, prediction of the microstructural properties of HAZ based on machine learning and other advanced methods like hybrid welding processes which combines different precision welding techniques provide promising results for production of high quality and reliable welds which offer enhanced safety and reliability during sour service [4].

<b>Background:</b> Building Information Modelling (BIM) improves safety planning in construction by enabling visualization and simulation to identify and reduce risks. However, its adoption in Nigeria is limited. This study examines the application of BIM in enhancing safety and environmental performance on construction sites in Nigeria. <b>Methodology:</b> A quantitative cross-sectional survey was conducted using a structured online questionnaire distributed to professionals in Nigeria’s construction industry. A purposive sampling method was employed to target respondents with relevant BIM experience. Data were analysed using SPSS version 28, applying descriptive statistics, chi-square tests, and logistic regression at a 5% significance level. <b>Result:</b> Findings show that BIM was fully adopted by 7.0% of organizations, with only 19.8% of respondents using it to identify safety hazards during planning. While 76.8% reported no notable safety benefit, 19.5% identified improved risk management as the key benefit. Most respondents (80.2%) reported no noticeable environmental benefits. Among those who did, improved energy efficiency was the most cited benefit (16.4%). Respondents with 10 or more years of experience were significantly more likely to report enhanced safety and environmental outcomes (AOR = 4.555; p = 0.003) and adequate BIM utilization (AOR = 3.255; p = 0.023). Those with intermediate BIM experience were also more likely to report high enhancement (AOR = 2.857; p = 0.039) and effective tool use (AOR = 2.881; p = 0.050). <b>Conclusion:</b> This study revealed that BIM has the potential to improve construction outcomes in Nigeria if supported by training, experience, and structured implementation.

<b>Objective:</b> To identify and evaluate the main functional assessment tools applied in the postoperative monitoring of patients undergoing total knee arthroplasty (TKA), and to synthesize the functional outcomes reported through these instruments in the current scientific literature. <b>Method</b><b>ology</b><b>:</b> A structured review was conducted following PRISMA 2020 guidelines. Thirty-one peer-reviewed studies were selected through a targeted manual search based on predefined eligibility criteria. Included studies evaluated functional recovery following TKA using validated outcome measures such as the WOMAC, KSS, KOOS, IKDC, SF-36, and SANE. Data extraction focused on the instruments used, patient population characteristics, and reported outcomes. A descriptive synthesis was compiled in Table 1. Additionally, 15 studies with quantitative data were analyzed using a forest plot to illustrate risk ratios (RR) and 95% confidence intervals (CI) for functional improvement. Risk of bias was assessed qualitatively based on methodological rigor, clarity of reporting, and validation of the outcome tools. <b>Results:</b> All included studies reported improvements in functional status following TKA. Most risk ratios ranged from 0.66 to 0.85, indicating a consistent reduction in the risk of postoperative functional limitation. High-quality studies demonstrated more precise effect estimates and greater internal validity. The SANE scale emerged as a valid and practical tool with high responsiveness, including in its culturally adapted Brazilian version. Despite heterogeneity in study design, the direction of effect remained consistent across all included studies. <b>Conclusion:</b> Validated functional assessment tools are essential for monitoring recovery after total knee arthroplasty. Instruments such as WOMAC and SANE demonstrate strong clinical utility and psychometric validity. Their systematic use enhances outcome comparability, supports individualized rehabilitation planning, and improves decision-making in orthopedic care.

This systematic review aimed to evaluate the biomechanical properties, functional performance, and clinical outcomes of different hip prosthesis materials and designs used in total hip arthroplasty (THA). A comprehensive search strategy identified 34 peer-reviewed studies published between 2015 and 2024. The materials investigated included cobalt-chromium-molybdenum (CoCrMo), titanium alloys, PEEK, ceramics, and advanced surface coatings such as polycrystalline diamond (PCD). In addition, dual mobility systems, lattice structures, and additively manufactured and patient-specific implants were assessed. The studies utilized clinical trials, finite element analysis, and biomechanical testing to compare outcomes such as wear resistance, stress distribution, osseointegration, and range of motion. The findings demonstrated that titanium alloys and porous lattice structures reduce stress shielding, while ceramics and CoCrMo provide superior wear resistance. Dual mobility implants improved joint stability and range of motion, particularly in high-risk patients. PEEK and PCD showed promising properties but lacked robust long-term data. The integration of advanced manufacturing technologies and material innovations has led to more personalized and biomechanically efficient solutions for THA. Further longitudinal studies are needed to validate these developments. This review provides a critical synthesis of the biomechanical, functional, and clinical implications of contemporary hip prosthetic systems.

This exploratory review article synthesizes existing literature on the evolution and increasing significance of women's soccer, particularly in the United States. While acknowledging the sport's progress and the achievements of the U.S. Women's National Team (USWNT), it critically examines two key challenges that impede further advancement: the alarmingly high incidence of knee injuries among female players and the persistent underrepresentation of Black women. The review highlights the biomechanical factors contributing to these issues, emphasizing the need for footwear designed to accommodate the specific anatomical and functional requirements of female athletes. Furthermore, it explores the systemic barriers that contribute to the lack of diversity within the sport, advocating for equitable opportunities and support for Black women. This review concludes by underscoring the necessity for innovative, interdisciplinary approaches to ensure the continued growth and well-being of all participants in women's soccer, and identifies critical areas for future research in kinesiology and related fields.

Data acquisition serves as a critical component of modern data architecture, with REST API integration emerging as one of the most common approaches for sourcing external data. This study evaluates the efficiency of various methodologies for collecting data via REST APIs and benchmark their performance. It explores how leveraging the Spark distributed computing platform can optimize large scale REST API calls, enabling enhanced scalability and improved processing speeds to meet the demands of high volume data workflows.

<b>Background:</b> Parental education is a key determinant of academic performance, yet its protective effects may differ by race and ethnicity. The concept of Minorities’ Diminished Returns (MDRs) highlights the weaker association between socioeconomic resources and outcomes for marginalized populations, including Black and Latino youth. <b>Objective:</b><b> </b>To investigate whether the positive association between parental education and school performance (letter grades) is weaker for Black and Latino youth compared to non-Latino White youth. <b>Methods:</b><b> </b>Data were drawn from the Monitoring the Future (MTF) 2023 study. The sample included Black, Latino, and non-Latino White youth. The outcome was a nine-level continuous measure of academic performance based on self-reported letter grades, with higher scores indicating better performance. Multivariate regression models tested interactions between parental education and race/ethnicity in predicting grades, adjusting for confounders such as family income, gender, and school characteristics. <b>Results:</b><b> </b>A total number of<b> </b>7584 12<SUP>th</SUP> graders entered the study.<b> </b>Parental education was positively associated with school performance across all groups, but the magnitude of this association was significantly smaller for Black and Latino youth compared to non-Latino White youth. Even after controlling for socioeconomic and contextual factors, the racial and ethnic differences in the strength of this association persisted. <b>Conclusions:</b><b> </b>Our findings provide evidence of Minorities’ Diminished Returns (MDRs) in the academic domain, with Black and Latino youth experiencing weaker benefits of parental education on school performance. These disparities suggest that structural barriers and systemic inequities undermine the translation of parental educational attainment into academic success for marginalized groups. Policy interventions must address these structural barriers to promote equity in educational outcomes.

<b>Background</b>: Disasters such as typhoons, floods, and earthquakes frequently impact the Philippines, placing nurses at the forefront of response and care. Given these recurring threats, ensuring that nurses possess adequate awareness, knowledge, and skills is crucial to mitigate risks, enhance preparedness, and promote effective disaster management. <b>Aim/Objectives</b>: This study sought to (1) assess the current levels of awareness, knowledge, skills, and involvement of private hospital nurses in Rizal Province across four phases of disaster management—mitigation and prevention, preparedness, response, and rehabilitation and recovery; and (2) propose a contingency and training plan based on identified gaps. <b>Methods</b>: A descriptive correlational design was employed. A total of 350 nurses from Level 1, 2, and 3 hospitals participated by completing a validated questionnaire. Data were analyzed using descriptive statistics, analysis of variance, and correlation tests to identify differences and relationships among variables. <b>Results</b>: Overall, the nurses reported very high levels of awareness and skills, coupled with a high level of knowledge and significant involvement in disaster-related activities. Nurses in larger (Level 3) hospitals exhibited higher practical readiness and engagement, while those in Level 1 and 2 facilities had comparatively lower scores. Positive correlations emerged between higher levels of awareness, knowledge, and skills and increased engagement in disaster initiatives. <b>Conclusion</b>: Building on these findings, a targeted contingency and training plan was designed using Pucel’s Performance-based Instructional Design, emphasizing hands-on simulations, structured policy briefings, and collaborative efforts with local disaster risk reduction offices. Addressing these specific gaps can bolster hospital preparedness, strengthen community resilience, and ensure more effective disaster response and patient care.

Over the past few decades, cardiovascular disease and related complications have surpassed all others as the important causes of death on a universal scale. At the moment, they are the important cause of mortality universal, including in India. It is important to know how to find cardiovascular problems early so that patients get better care and prices go down. This project utilizes the UCI Heart Disease Dataset to develop ML and DL models capable of detecting cardiac diseases. Heart illness was categorized using Convolutional Neural Network (CNN) models, which are able to detect intricate patterns in supplied data. A confusion matrix rating, an F1-score, a ROC curve, accuracy, precision, and recall were some of the measures used to grade the model. It did much better than the Neural Network, Deep Neural Network (DNN), and Gradient Boosted Trees (GBT) models, with 91.71% accuracy, 88.88% precision, 82.75% memory, and 85.70% F1-score. Comparative study showed that CNN was the most accurate model. Other models had different balances between accuracy and recall. The experiment results show that the optional CNN model is a decent way to identify cardiovascular disease. This means that it could be used in healthcare systems to find diseases earlier and treat patients better.

The theme of the study that catches our attention is the initial conceptions of learners in Science and school performance; this theme is based on the competency-based approach in force in Cameroon, which is implemented in several African countries. Insofar as learning is not the accumulation of new knowledge but a cognitive reorganization of old knowledge experienced, it is therefore a question of knowing what is the influence of initial conceptions on the academic performance of learners in science. The objective of this research was to show that taking into account the initial conceptions of learners, Biology “SVT” has a lasting influence on learning and thus on the academic performance of learners. To achieve this objective, the study uses the mixed and quasi-experimental method, where two groups of learners were used: a control group and an experimental group. The experimental group was subjected to the teaching-learning system designed for this purpose, and in which the initial conceptions of the learners were taken into account according to do with or go against. In the light of the different hypotheses adopted and the different results of this study, it can be observed that the didactic consideration of the learners' initial conceptions improves their academic performance through the data of the experimental group. In relation to the field of education, this study shows that in order to enable learners to learn and build knowledge in the long term, their initial conceptions must be taken into account in concrete didactics; Otherwise, learning will be sporadic, learners' conceptions will be significant, which will lead to a learning defect perceptible by school failure.

Extracurricular activities and academic performance are connected in every aspect of the education system. Daffodil International University is one of the top universities in Bangladesh that focuses on student improvement through extracurricular activities. Extracurricular activities help students improve skills like leadership, teamwork, and analytical abilities. Do extracurricular activities help English as a Foreign Language (EFL) students improve their academic performance? This evaluation aims to find out this question among Daffodil International University students. The study focused on both qualitative and quantitative data. Therefore, the data analysis followed a mixed method. The quantitative data focused on the students' participation in extracurricular activities. Respectively, the comparison between their participation and EFL course improvement. On the other hand, the qualitative data focused on the interviewee's experience. However, it's been proven that though extracurricular activities help students improve their other soft skills, they actually don't have as much impact on improving their EFL course curriculum performance.

High-Performance Computing (HPC) is indispensable for large-scale scientific simulations, but achieving optimal performance on modern supercomputers is increasingly challenging. As HPC systems scale toward exascale, they face escalating complexity in hardware, software, and workloads. Traditional optimization methods (manual tuning and heuristic algorithms) struggle to cope with dynamic workloads and intricate system behaviors. Artificial Intelligence (AI) techniques offer a promising approach to address these challenges. This article provides an overview of AI-powered optimization in HPC, focusing on how machine learning and related AI methods enhance performance, efficiency, and scalability of scientific simulations. We survey key AI techniques applied to HPC optimization including machine learning for performance modeling, deep reinforcement learning for resource management, and AI-driven surrogate models for accelerating simulations and illustrate their impact through case studies in domains such as job scheduling and fluid dynamics. We discuss the practical applications of these techniques, highlighting reported performance gains (e.g., substantial reductions in simulation run time and improved resource utilization). We also examine the challenges in integrating AI with HPC (such as training overhead, data movement, and reliability concerns) and outline future directions for research. The convergence of AI and HPC is poised to produce “smart” simulation workflows that intelligently adapt and optimize in real time, pushing the frontiers of scientific computing.

This study investigates the relationship between teacher-trainees' academic self-concept and performance in Colleges of Education in Ghana. Utilizing a mixed-methods approach, data were collected from teacher-trainees in Ada and Accra Colleges of Education through surveys and interviews. The study hypothesised that there is no significant relationship between academic self-concept and academic performance among teacher-trainees. Results revealed a statistically significant positive relationship between academic self-concept and performance, indicating that teacher-trainees with higher academic self-concepts tend to perform better academically. Furthermore, gender differences in academic self-concept and performance were explored, with findings suggesting no significant gender disparities in either domain. Institutional factors, such as school climate and resources, were also found to influence academic performance. Recommendations include promoting positive academic self-concept, implementing gender-responsive pedagogy, and creating supportive learning environments in Colleges of Education. By addressing these factors, teacher education programs can better prepare future educators for success in the classroom and contribute to the improvement of educational quality in Ghana.

The recent development of Mobile System-on-Chip (SoC) has completely changed the functionality of the contemporary smartphones, wearables, and IoT devices through enhanced computational strength but with stringent power and heat constraints. Mobile applications are becoming more complex (e.g., real-time computer vision, high-resolution imaging, on-device artificial intelligence, etc.) and SoCs have to provide high throughput, good work load distribution, and responsive multitasking without sacrificing battery life. To overcome these issues, modern SoCs are based on heterogeneous multicore designs, with big. LITTLE designs, special purpose accelerators, like NPUs and ISPs, and memory arranged hierarchies and backed with high bandwidth buses. Also, more sophisticated power-management approaches like Dynamic Voltage and Frequency Scaling (DVFS), clock gating, and power gating provide fine-tuning energy management in the active and idle conditions. Most recently, scheduling and thermal sensitivity resource allocation using AI has become a promising approach in increasing real-time refinement and flexibility. This paper gives a detailed discussion of performance-driven and power-efficient design methods in mobile SoCs, including architectural innovations, workload optimization, and built-in AI-assisted energy management. The discussion identifies major research trends, system-level developments, and new challenges defining next-generation mobile computing systems.

The management of supply chains is increasingly complex. This study provides a comparative analysis of the cost-benefit analysis for managing various risks. It identifies the financial implications of leveraging artificial intelligence in supply chains to better address risk. Empirical results show a business case for managing some sources of risk more proactively facilitated through predictive modeling techniques offered by AI. Across investigation streams, the use of AI results in an average total cost saving ranging from 41,254 to 4,099,617. Findings from our research can be used to inform managers and theorists about the implications of integrating AI technologies to manage risks in the supply chain. Our work also highlights areas for future research. Given the growing interest in studying sub-second forecasting, our research could be a point of departure for future investigations aimed at considering the impact of forecasting horizons such as an intra-day basis. We formulate a conceptual framework that considers how and to what extent performance evaluation metrics vary according to differences in the fidelity of predictive models and factor importance for identifying risks. We also utilize a mixed-method approach to demonstrate the applicability of our ideas in practice. Our results illustrate the financial implications of integrating AI predictive tools with business processes. Results suggest that real-world companies can circumvent inefficiencies associated with trying to manage many classes of risk via the use of AI-enhanced predictive analytics. As managers need to justify investment to top management, our work supports decision-making by providing a means of conducting a trade-off analysis at the tactical level.

The purpose of this study was to examine coping strategies for managing the effects of work-family conflict on the management staff of hotels in the Accra metropolis of Ghana. The study adopted a Convergent parallel mixed methods research technique. The population of the study is all-star-rated management staff of star-rated hotels in the Accra metropolis. multi-stage sampling. The estimation of the sample size for the hotel managers was based on Krejcie and Morgan’s table for the determination of the sample size for a given population. The population of 100 managers were stratified and randomly sampled out of the 182 managers. The main instruments for data collection were questionnaires and an interview. Statistical Package for Social Sciences (SPSS) version 22.0 was used to determine simple percentages and frequencies of responses. Pearson product-moment Correlation and structural equation model were used to determine the consequences of work-family conflict as well as coping strategies adopted by managers. Amos PLS was used to determine the moderating effect of coping strategies on work-family conflict and job performance. Hotel managers in the Accra metropolis combine the strategies of structural role redefinition, personal role redefinition, cognitive restructuring and reactive role redefinition to curb work-family conflict. The study demonstrated a positive relationship between coping strategies and job performance. Coping strategies had a moderating effect on the relationship between work-family conflict and the job performance of hotel managers. Thus, to improve the job performance of hotel managers, there should be the application of coping interventions to help them perform on the job. The study also determined that work-family conflict had a significant positive relationship with job performance. Similarly, the study established that coping strategies significantly moderate the relationship between work-family conflict and job performance among hotel managers in the Accra metropolis. Although coping strategies were employed by hotel managers in the Accra metropolis, it is recommended that training sessions on the use of coping strategies and stress management techniques should be considered by management to address psychological and emotional work environment stressors since they have been proven to reduce stress and WFC. It is also recommended that there should be an inter-hotel collaboration to offer smaller hotels which do not have the resources some leverage the impact of work-family conflict. This platform can be provided by the Ghana hotels association to impact knowledge of coping strategies in smaller hotels. The government must be encouraged to liaise with the Ghana hotels association to enforce the mandatory eight-hour work per day to avoid overworking of hotel managers.

Quantitatively, the study adopted a descriptive research design. The population of this study comprised two thousand (2000) students in the four (4) senior high schools (Edinaman Senior High, Eguafo Senior High, Peter Hold Book Senior High and Komenda Senior Technical Institute) in Komenda Edina Eguafo Abirem municipality. Purposive, simple random and stratified sampling techniques were used to select two hundred students from the four for this study. A questionnaire was the main instrument for data collection. There are more adverse effects of social media network participation on academic performance than positive effects. Social media network sites serve as a useful medium for enhancing students’ academic performance if properly used. Therefore, SHS students should be guided to use social media properly to enhance their academic performance. It is recommended that regular counselling by school authorities and parents for students who participate in social media networks should be done to prevent improper use of social media and avoid addiction and its consequences. It is also recommended that teachers should encourage students to use the right grammar and correct spelling of words when participating in social networks to help stop the negative effect it has on students’ academic performance. It is once again recommended that all stakeholders should be involved in educating students on the proper use of social media networks for their academic work as well as the dangers of improper use on their academic performance and social well-being.

The purpose of the study was to design and develop performance-based tasks to assess laboratory observing skills of biology students in senior high schools. The target population was all students in the nine schools within Sekondi-Takoradi Metropolis reading biology as an elective subject. The accessible population was 753 SHS 2 biology students in six schools. 261 students were randomly selected from each of the six schools. These schools were of three different types, single-sex males, single-sex females, and mixed. Mean, standard deviations, frequencies, and percentages were calculated while independent sample t-tests were performed. No significant difference was noticed in levels of proficiency shown for males and females in the various schools surveyed. It is recommended that students from all types of schools and both sexes must be given an opportunity to engage in more activities at the SHS level to sharpen their observing skills.

The purpose of this study was to examine Religious and Moral<b> </b>Eduction teachers’ usage of the flipped classroom model Model and its Influence on JHS Students’ Academic Performance in the Nzema-East Municipality of Ghana.The study adopted the quasi-experimental research design. The population for this study comprised all JHS Religious and Moral Education students and teachers within the Nzema-East Municipality of the Western Region. With the help of the Krejcie and Morgan’s sample determination table, a sample of 110 comprising 10 teachers and 100 students were selected for the study through multi-stage sampling. The instruments used for data collection were tests and questionnaires. The study indicated that, the flipped classroom is a very potent method of teaching RME. This is so because the study provides enough evidence that the flipped classroom significantly improves the performance of learners more than the traditional approaches to teaching. This is even more appropriate in a technological era such as ours. The study also revealed that, teachers have a positive view of the use of the flipped classroom in teaching RME. Junior High School RME teachers are ready to adopt the flipped classroom model in their teaching provided challenges students face are eliminated. It is recommended that, School Improvement Support Officers and Headteachers should ensure that teachers use the flipped classroom to bring variations in lesson delivery so as to improve the academic achievements of learners. It is also recommended that government should provide technological devices to schools and teachers and ensure that teachers employ the various technological devices at their disposal to the benefit of their students.

Generative AI refers to deep learning technology that can automatically produce original text, images, audio, video, and other outputs. With its emerging capabilities, Generative AI can radically change the dynamics of key operational processes in most industries. In this document, we illustrate how it is possible to integrate Generative AI technologies into the Financial Reporting System (FRS) of a corporation. The integration will allow the FRS to deliver on demand concise and lucid insights to its associated users on what is happening in the corporation and different aspects of the corporation performance assessment, such as its liquidity, solvency, profitability, organizational structure, and share buy back decision. The integration will also facilitate the delivery of what-if analyses associated with different strategic and tactical decisions taken by the corporation management, such as capital budgeting and profit distribution decisions. The unique added value of several attributes of these insightful analytics is automating the responses to ongoing requests of the FRS users on the corporation. Generative AI capabilities are rapidly expanding. The integration can be applied not only for the corporate FRS but any FRS at the national or global levels delivered by a central bank or an accounting standards setter. Any of these FRS can be made into a unique “hub” for the integrated Generative AI technologies. An equally innovative possible generalized integration could put any corporate process at the center and its supporting FRS tasks and deliverables in its periphery.