Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online)
The Journal of Knowledge Learning and Science Technology (JKLST) is a reputable, peer-reviewed academic journal that operates on an Open Access model. The journal aims to provide a comprehensive and reliable source of information on groundbreaking discoveries and the latest advancements in various areas of the field. It welcomes original research papers, review papers, case reports, short communications, and other relevant contributions. The review process of JKLST is rigorous and ensures the highest quality of published content. Manuscripts are reviewed by the journal's editorial board members or external experts who are knowledgeable in the respective fields. The review process involves obtaining approval from at least three independent reviewers, followed by final approval from the editor. This meticulous evaluation guarantees the validity, significance, and credibility of the published work. The editorial team of JKLST is committed to managing the entire submission, review, revision, and publication process efficiently. They work closely with authors to ensure a smooth and timely publication experience. The journal's online platform provides unrestricted access to its content, allowing researchers and scholars from around the world to benefit from valuable insights and findings without any barriers or subscription requirements. JKLST strives to maintain its reputation as a reliable and influential platform for disseminating knowledge and promoting scholarly discussions in the fields of knowledge acquisition, learning methodologies, and science and technology. By fostering collaboration and facilitating the exchange of ideas, the journal contributes to the advancement of the scientific community and the development of innovative solutions in these domains.
Journal of Knowledge Learning and Science Technology
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EXTRACURRICULAR ACTIVITIES IN ENGLISH LANGUAGE TEACHING AS A PATHWAY TO SUSTAINABLE DEVELOPMENT GOAL 4 IN HIGHER EDUCATION
The incorporation of extracurricular activities into English language teaching (ELT) in higher education is increasingly important because such activities provide students with opportunities for authentic communication, learner autonomy, and intercultural interaction while also supporting their academic and professional development.This review looks at the role of extracurricular activities in achieving Sustainable Development Goal 4 (SDG 4) in higher education and ELT. Drawing on recent studies in the Asian and European sectors, the review reviews literature on the aspects of language development, employability, soft skills development, intercultural communication and sustainable learning. The study shows that extracurricular activities (speaking forums, cultural events, exchange programs and ESP workshops) and student publications can enhance student engagement and self-directed learning. However, the literature also demonstrates significant challenges with regard to unequal participation, financial accessibility, institutional support and the growing instrumentalization of extracurricular learning for employability purposes. In addition, Vietnamese higher education and selected extracurricular activities are discussed in the review at Ho Chi Minh City University of Economics and Finance (UEF). The research indicates that well-organized extracurricular activities can contribute to sustainable and holistic language education in the context of SDG 4. Keywords: extracurricular activities; English language teaching; higher education; learner autonomy; sustainable development goal 4
Copyright (c) 2026 Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) https://creativecommons.org/licenses/by/4.0
Cardiac Device Therapy in US Patients with Chronic Kidney Disease: Current Outcomes, Complications, and National Trends
Background: Chronic kidney disease (CKD) and end-stage renal disease (ESRD) are associated with high cardiovascular morbidity. Cardiac device therapy, including pacemakers, CRT, leadless pacemakers, and LVADs, is increasingly used, yet real-world outcomes, complications, and trends in these renal populations remain incompletely characterized. Aims: To analyze outcomes, procedural complications, and national trends of cardiac device therapy in US CKD and ESRD patients. Methods: Data were extracted from 16 published studies and national registries, aggregated, and analyzed using Python (VS Code), SPSS v27. Patient demographics, comorbidities, procedural complications, mortality, and hospital utilization were summarized with descriptive statistics. Categorical variables were reported as frequencies/percentages, and continuous variables as means/ranges. Comparative analyses assessed differences between CKD and ESRD across device types. Results: Among 29,005 patients, 5,245 had CKD (stages 3–5) and 3,790 had ESRD. ESRD patients exhibited higher procedural complications: infections (12% vs 7%), bleeding (8% vs 6%), lead dislodgement (5% vs 3%), central vein stenosis (15% vs 10%), and peripheral vascular complications (13% vs 7%). Mortality was higher in ESRD, with inpatient rates 14% versus 6.4% in CKD, and 1-year mortality 50% versus 31%. LVAD recipients had the highest risk, while CRT and leadless pacemakers showed reduced complication rates in selected populations. Hospital cost and length of stay were also elevated in ESRD. Conclusion: ESRD patients experience higher complications, mortality, and hospital utilization than CKD patients. These findings inform risk assessment, device selection, and future clinical strategies.
Copyright (c) 2025 Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) https://creativecommons.org/licenses/by/4.0
The Use of Generative AI by Students with Disabilities in UK Higher Education: A Mixed-Methods Survey of 125 Students
Higher education's response to generative artificial intelligence (AI) has moved quickly from curiosity to policy, yet questions of who benefits from these tools and who is excluded remain under-examined. Students with disabilities — a population long under-represented in higher education and demonstrably reliant on assistive technologies — may have much to gain from generative AI, but also face specific risks from it; empirical evidence on their actual practices is scarce. This study asks how students with disabilities at a UK university use generative AI in academic writing, what concerns they hold about it, and what institutional support they want. A mixed-methods online survey, anchored in a five-element generative AI literacy framework, was distributed to all 1,797 students registered as disabled at one UK university during February and March 2024. The survey returned 125 valid responses, a 7.0 % response rate. Closed items were analysed descriptively; open-text responses were coded inductively through content analysis. Seventy-eight percent of respondents reported using generative AI in their studies, with ChatGPT (53 %) the dominant tool, supplemented by rewriting applications such as Grammarly (10 %) and translation services. Respondents used these tools across the full writing pipeline — explaining concepts, structuring arguments, summarising readings, and refining prose. Concerns clustered around the accuracy of AI outputs, threats to academic integrity, and the inequity introduced by paid subscriptions. Participants voiced strong demand for involvement in institutional AI policy (M = 4.03 on a five-point scale) and for university-provided training (M = 3.95). The paper closes with policy and pedagogical recommendations for building a more inclusive institutional response to generative AI.
Digital Governance and Transparency in Asset Disposal: Evidence from The Gcc Region
Purpose: This study investigates the role of digital governance and transparency mechanisms in transforming the used vehicle and equipment asset disposal market across the Gulf Cooperation Council (GCC) region. The research seeks to identify prevailing governance deficiencies in the sector and evaluate how digital tools, including secure digital verification systems, integrated regulatory compliance platforms, and digital auction marketplaces, address these shortcomings within the context of the region's ongoing national reform and digital transformation agendas. Design/Methodology/Approach: The study adopts a qualitative, systematic secondary research methodology, synthesising evidence from peer-reviewed academic literature, multilateral policy reports, government publications, and international industry assessments. A conceptual framework integrating institutional theory and digital transformation theory is developed to structure the analysis across input, process, and output dimensions of digital governance adoption. Findings: The findings demonstrate that the GCC used vehicle and equipment disposal sector is characterised by significant informality, valuation inconsistencies, documentation deficiencies, and cash transaction governance risks. Digital governance mechanisms demonstrably reduce information asymmetry, improve price discovery, and enhance regulatory compliance, generating material improvements in resale optimisation outcomes. A five-stage Digital Governance Maturity Model is proposed to guide the sector's progressive digitalisation. Practical Implications: The paper provides actionable recommendations for GCC government agencies, private sector asset managers, and policymakers seeking to leverage existing digital infrastructure to strengthen governance and market efficiency in the asset disposal sector. Originality/Value: This study is among the first to systematically examine digital governance in the GCC asset disposal market, bridging institutional theory, digital transformation research, and asset management practice in an underexplored regional context.
Digital Video-Supported Flipped Instruction And Efl Writing Development
This study investigated the use of digital video-supported flipped instruction to enhance EFL writing development among first-year English majors in Vietnamese higher education. An action research design was employed with 45 first-year English-major students at Hanoi University of Natural Resources and Environment. The intervention lasted ten weeks and integrated pre-class digital videos with in-class writing practice, peer interaction, and teacher feedback. Data were collected through pre- and post-writing tests, a student questionnaire, and semi-structured interviews. Quantitative results showed significant improvements in students’ overall writing performance, particularly in content development, organization, vocabulary use, and grammatical accuracy. Qualitative findings further revealed that students perceived the videos as useful for understanding writing structure, preparing ideas before class, and revising their drafts more effectively. The questionnaire and interview data also indicated positive learner attitudes, especially regarding flexibility, motivation, confidence, and engagement. The findings suggest that digital video-supported flipped instruction can be a promising approach for improving EFL writing instruction in Vietnamese university contexts.
Integrating Machine Learning into Financial Systems to Improve Risk Management and Economic Stability
Background: Machine learning systems now operate in financial environments which have transformed all risk management operations and fraud detection systems and economic stability maintenance methods. Financial institutions now use intelligent algorithms to strengthen their decision processes which produces better predictions and lowers their operational risks. Methods: The study used a cross-sectional quantitative design to study machine learning affects the development of financial systems. The study collected primary data through a structured questionnaire which 215 professionals from banking and insurance and regulatory sectors answered using a five-point Likert scale. Machine learning implementation together with risk management system performance and fraud detection capabilities and their impact on economic stability. Descriptive statistical methods to analyze their data by calculating frequency distributions and percentage values and average scores. Results: Machine learning delivers improved financial risk prediction results through its ability to reach 84.7% accuracy while it simultaneously helps organizations cut down their operational financial losses by 79.5%. The fraud detection system achieved its highest performance level when it successfully detected suspicious transactions within 86.0% of cases. The research findings reveal that 81.4% of participants experienced a decrease in cyber financial fraud incidents while 83.7% of them reported better financial security which led to economic stability. Conclusion: Machine learning serves as an essential tool which researchers discovered to enhance financial system security through its ability to improve risk assessment and detect fraudulent activities and maintain economic stability.
Blockchain and AI Integration in Supply Chain Management: Transforming Transparency, Security, and Efficiency in Material Flow Systems
Background: Over the last few years, blockchain and artificial intelligence (AI) applications in supply chain management (SCM) have become a transformational solution to increase transparency, security, and efficiency. Conventional supply chain systems are associated with inefficiencies, information silos, faddiness, and deficiency of traceability, which greatly impede efficiency. The synergies of a decentralized and safe data format of blockchain and predictive performance of AI have the chance to resolve these issues and streamline supply chain processes. Methods: The study employed the mixed-methods approach, which included secondary data gathering based on peer-reviewed articles, industry reports, and case studies related to blockchain and AI integration. The study utilizes statistical analysis to investigate current trends and associations and machine learning algorithms are used to examine how blockchain and AI can influence supply chain performance indicators, including demand forecasting, inventory management, and operational effectiveness. The data on different industries such as food, pharmaceuticals and logistics were studied to have a glimpse of the real-world uses of such technologies. Results: The findings indicate that blockchain and AI integration have a significant positive impact on transparency as it creates an unalterable and up-to-date version of each transaction and improves operational efficiency since it allows for the optimization of resource distribution, demand forecasting, and inventory control. Blockchain offers verifiable data, which is reassured, and AI can make predictive analytics and automation that can decrease errors and enhance decision-making initiatives within supply chains. Conclusion: A combination of blockchain and AI is an exciting option to revolutionize supply chain management. Although other issues such as scalability and system integration are still facing challenges, the benefits of these technologies are enormous in terms of security, transparency and efficiency.
Design and Implementation of Digital Protection Systems for High-Voltage Transmission Lines and Power Transformers
Background: High-voltage transmission lines and power transformers need dependable protection systems which maintain their operational status to deliver continuous power distribution. Methods: The research used a quantitative cross-sectional survey design which gathered data from 250 power sector employees who worked as engineers and technicians and operators. The research employed descriptive statistics together with Pearson's correlation and multiple regression and ANOVA to study how people understood things and how they performed and used what they learned. The research team used Cronbach's alpha to evaluate instrument reliability for their study. Results: People view fast fault detection at 22 % and reduced downtime at 20 % and improved accuracy at 18 % as their main advantages. The main obstacles for system implementation consist of expensive startup expenses which affect 24 % of cases and complex technical requirements that impact 20 % and insufficient trained staff members who represent 18 percent. The evaluation of performance demonstrates that fault detection speed has improved by 20 % and reliability has improved by 19 %. The analysis shows that people who understand a system tend to adopt it more (r = 0.45) and those who receive training develop better implementation skills (r = 0.41) but the cost factor creates a negative impact on adoption rates (r = −0.38). Conclusion: Digital protection systems provide power systems with better performance and enhanced reliability through their operation. Strategic investment along with capacity building and supportive policies need to exist for power systems to achieve successful implementation and modernization.
Development of a system-multi criteria analysis on erosion and sediment control in construction industry
Background: The construction industry faces erosion and sediment control (ESC) as its main environmental problem because urban areas of the United States experience fast population growth. The natural soil structure faces disruption during construction work which leads to elevated risks of water erosion that carries sediment particles which then harm both water quality and drainage systems and environmental balance. Methods: The research establishes a system-based Multi-Criteria Decision Analysis (MCDA) framework which evaluates different ESC practices. The research team distributed structured questionnaires to 175 construction industry workers who included engineers and contractors and project managers and environmental consultants based in the USA. The research team used descriptive statistics together with reliability testing (Cronbach’s Alpha) and correlation analysis and weighted MCDA techniques to analyze the data. Results: The research shows that storm water Management functions as the leading factor with a mean score of 4.41 followed by Regulatory Compliance which scored 4.35 and Site Stability received 4.29. The reliability measurements showed values between 0.79 and 0.88 which proved the instrument maintained strong consistency between its elements. The correlation analysis revealed that all variables maintained strong connections with each other while storm water Management and Site Stability showed the strongest connection at r = 0.73. Conclusion: ESC performance in American construction sector depends most on environmental factors and regulatory requirements instead of financial elements. MCDA framework solution provides a functional decision-support system which helps sustainable construction practices move forward while decreasing their negative impact on the environment.
Comparative Analysis of Postgraduate Clinical Integration Pathways for MedicalGraduates: Lessons from the United Kingdomand Europe for the United States
The persistent mismatch between medical school graduates and available postgraduate training positions continues to challenge healthcare systems worldwide. This comparative analysis examines how the United States, the United Kingdom, and Europe manage the transition from medical education to supervised clinical practice. Data were drawn from the Association of American Medical Colleges (AAMC), General Medical Council (GMC), Organisation for Economic Co-operation and Development (OECD), and European Commission to compare regulatory structures, supervision mechanisms, and workforce integration outcomes. Findings reveal significant disparities in post-graduation employment rates. In the United States, the 2025 National Resident Matching Program recorded 44,853 applicants for 41,403 positions, leaving over 3,400 unmatched graduates (7–8 percent) and an estimated 10,000 inactive physicians from prior years. Conversely, the U.K. Foundation Programme placed 99.5 percent of eligible graduates in supervised practice within three months, while European systems such as Germany’s Arzt in Weiterbildung and France’s Internat achieved 93–96 percent integration within the first year. These structured frameworks ensure that nearly all qualified physicians enter paid supervised employment, effectively eliminating post-graduation inactivity. The comparative evidence indicates that nations with centralized postgraduate supervision achieve faster workforce absorption, better skill retention, and improved healthcare service continuity. The study concludes that the United States could mitigate its ongoing physician shortage by adopting a national supervised clinical licensure framework, harmonizing state-level policies, and expanding structured employment opportunities for unmatched medical graduates.
Integrating Renewable Energy into Sustainable Development Pathways for Climate Change Mitigation
Renewable energy has now emerged as one of the main focuses of sustainability development worldwide in order to reduce climate change. With the ever-increasing energy demands globally, the restrictions and environmental consequences of the use of fossil fuels energy systems have aggravated the necessity to use cleaner, more sustainable energy systems. Ecologically sustainable sources of energy like solar, wind, hydroelectric, biomass, geothermal and ocean energy are sources of renewable energy that can be utilized to supply electricity and energy to the environment. These energy systems greatly lower the greenhouse gas emissions and air pollution, hence enhancing the quality of environment and people health. Besides this renewable energy technologies increase energy security by lessening dependence on imported fossil fuels and stabilization of long-term energy prices. Although these are the advantages, transitioning to renewable energy is associated with a number of challenges such as the high-start-up costs, lack of access to the funds, regulatory barriers, inadequate infrastructure, and technological considerations. Despite most developing countries having large amounts of renewable energy, they usually have low allocations of clean energy investment in the world. Case studies conducted in nations like Denmark, Uruguay and Namibia over the years have shown that high political commitment, good policy schemes, and good governance are key to effective renewable energy development. In addition, international collaboration and international climate treaties are useful in enhancing the use of renewable energy through the provision of financial incentives, technology sharing and collective effort.
Translation Quality Assessment of the Vietnamese Translation of The Da Vinci Code Using House’s Model
This study investigates the interplay of overt and covert translation in the Vietnamese translation of The Da Vinci Code by Dan Brown, rendered into Vietnamese by Đỗ Thu Hà, within the framework of Juliane House’s Translation Quality Assessment model. It aims to identify the dominant translational orientation of the Vietnamese version and to examine how source-text features are preserved or adjusted across the dimensions of Field, Tenor, and Mode. Employing a mixed-methods approach, the study combines qualitative textual analysis with quantitative support through the comparison of selected source-text and target-text pairs. The findings indicate that the Vietnamese translation is predominantly oriented towards overt translation, as it largely retains the cultural specificity, interpersonal meanings, and discourse organization of the original text. At the same time, certain covert adjustments are observable in order to enhance naturalness, readability, and accessibility for Vietnamese readers. Overall, the translation reflects a careful negotiation between fidelity to the source text and adaptation to the linguistic and cultural expectations of the target readership. The study highlights the applicability of House’s model to literary translation assessment and contributes to a more nuanced understanding of how culturally embedded and stylistically marked texts are mediated in translation.
The Role of Circular RNAs in Hepatocellular Carcinoma: Mechanisms, Implications, and Therapeutic Potential
Background: Hepatocellular carcinoma (HCC) is one of the most common malignancies and a predominant cause of cancer-related death worldwide, featuring high metastasis potential and resistance to chemotherapeutic agents. Both early diagnosis and good treatment options remain major challenges of HCC management. Recent studies have shown that exosomal circRNAs (circular RNAs) can serve as promising diagnostic and therapeutic markers for cancers, given their stability in biological fluids and the involvement of many oncogenic pathways through which they regulate cancer progression. Methods: This review focuses specifically on exosomal circRNAs, examining their functions during tumor progression, metastasis, and chemoresistance in HCC. We also describe the ways circRNAs are involved in miRNA-mediator interactions and epigenetic regulation of HCC. We performed a systematic review of the literature, including articles published up to 2015-2025, in the databases of PubMed, Google Scholar, and Web of Science. We selected relevant studies focusing on circRNAs and their involvement in HCC along with miRNA interactions. Outcomes: The extensive involvement of exosomal circRNAs in modulating miRNA signaling pathways leads to modulation of processes such as angiogenesis, epithelial-mesenchymal transition (EMT), and metastasis in HCC. They further also promote chemoresistance by modulating the processes of drug resistance and immune evasion. Moreover, circRNA87th53-derived CE-Ang1 is a promising therapy for HCC. Conclusion: Exosomal circRNAs present potential as promising biomarkers and therapeutic targets for HCC. More studies should be performed to investigate their clinical implications and to resolve problems with circRNA identification and functional delivery.
Enhancing English Vocabulary for Kindergarten Learners Through Game-Based Activities: A Case Study of AlphaTUB
Vocabulary acquisition is the cornerstone of early language development, yet traditional rote-learning methods often fail to engage the limited attention spans of young learners. This study investigates the impact of Game-Based Learning (GBL) on English vocabulary acquisition among kindergarteners (ages 3–6), specifically focusing on the integration of the AlphaTUB platform. Utilizing a case study methodology across 10 bilingual and international classes, the research triangulates data from classroom observations, semi-structured teacher interviews, and digital performance reports. The findings suggest that gamified interactions—characterized by immediate feedback, multisensory engagement, and physical movement—significantly enhance word retention and learner motivation. The study concludes that digital-physical hybrid tools like AlphaTUB provide a "low-anxiety" environment that facilitates natural language uptake.
TEACHER PERCEPTIONS OF ENGLISH AS A COMMUNICATIVE MEDIUM VERSUS AN ACADEMIC DISCIPLINE: A LITERATURE REVIEW
The shift toward viewing English as a global communicative tool has become a central focus in English language teaching (ELT), yet a significant tension remains between its role as a functional medium and a traditional academic discipline. This paper addresses this gap by investigating teacher perceptions in Vietnamese contexts where communicative policy mandates often conflict with classroom realities. The study examines the pedagogical and institutional factors, including high-stakes assessment and negative washback, that shape educators’ beliefs and classroom practices. It further explores how the emergence of English as a lingua franca (ELF) and artificial intelligence (AI) influences teacher identities and professional development within these systems. Utilizing a desk-based literature review to synthesize theories, concepts, and empirical research, the paper therefore intends to provide a theoretical roadmap for bridging the binary between social fluency and academic proficiency, offering analysis and implications for systemic reforms in assessment and infrastructure to align educational outcomes with twenty-first-century global demands.
English-Majors’ Self-Study Practices in Reading Skills at Quy Nhon University
This study examines English-majored students’ self-study practices in reading skills at Quy Nhon University in response to the growing demand in learner autonomy in the expanded education system, especially in higher education. A mixed-methods approach was used, collecting quantitative and qualitative data from 160 English pedagogy students (K45 and K48) through a Likert-scale questionnaire analyzed with Cronbach’s Alpha, descriptive statistics along with semi-structured interviews. The results show differences in self-study levels, patterns, and challenges, as well as the influence of motivation on autonomous learning. K45 senior students demonstrate more structured and effective self-study strategies, leading to higher reading performance, while K48 junior students participate more actively in self-learning activities but achieve lower scores. This suggests that junior students may lack strategic direction and academic maturity. The study recommends the introduction of reading strategies at the beginning of the curriculum for the future junior students as well as early training for K48 students, along with mentoring programs that connect junior students with seniors to promote effective learning practices.
English Majors’ Perceptions of Multiple Intelligences in Learning Speaking Skills at Quy Nhon University
This study aims to investigate how English-majors’ dominant intelligences and their perceptions of applying these intelligences in developing their speaking skills. The study used a mixed-method design, which involved 100 participants who were all third-year English majors at Quy Nhon University, Vietnam. Quantitative data were collected through an MI inventory and a perception questionnaire, while qualitative data were gathered from semi-structured interviews with 8 participants. Thematic analysis was used to complement descriptive statistical data analysis. The findings show that students possess a balanced MI profile, particularly with intrapersonal and musical intelligences as the most dominant. Although students demonstrated a moderate to high awareness rate of MI, their perceptions towards MI-based classroom activities were generally positive yet varied across different academic achievement levels. Qualitative insights also highlighted that students actively utilize self-regulated learning strategies aligned with their dominant intelligences. These findings have pedagogical implications to design more learner-centred EFL speaking instruction in Vietnamese higher education. The study highlights that nurturing the consciousness of the learners of their MI profiles and diversifying classroom activities can enhance self-interest and autonomy in speaking.
Addressing the “Silent Classroom”: A theoretical perspective on language anxiety and communicative readiness among Vietnamese primary learners
This paper presents a comprehensive theoretical perspective on the complex interplay between Foreign Language Classroom Anxiety (FLCA) and Willingness to Communicate (WTC) within the landscape of Vietnamese primary education. Amidst the nationwide implementation of the 2018 General Education Program, the pervasive phenomenon of the “silent classroom” has emerged as a critical pedagogical challenge, where learners possess linguistic knowledge but lack the psychological readiness to engage in discourse. Drawing upon a multi-dimensional synthesis of Krashen’s (1982) Affective Filter Hypothesis, Horwitz et al.’s (1986) tripartite construct of FLCA, and MacIntyre et al.’s (1998) Heuristic Model of WTC, this article analyzes how socio-cultural stressors specifically the collectivist imperative of “face-saving” and the fear of peer evaluation-act as psychological blockades. The study demonstrates that high levels of state anxiety effectively thicken the affective filter, causing a situational collapse of the WTC pyramid at the communicative antecedent level. To address these barriers, the paper proposes a localized conceptual framework for pedagogical interventions, including the cultivation of “mistake-friendly” environments, gamification, and the strategic use of recasts. By establishing this robust theoretical foundation, the study provides a strategic roadmap for future empirical investigations including longitudinal and parental influence studies and offers actionable strategies for educators to transform the “silent classroom” into a dynamic, “low filter” environment conducive to natural language acquisition.
Artificial Intelligence in Strategic Talent Development: A Literature Review of Frameworks for Workforce Readiness and Organizational Resilience (2020–2025)
The accelerated digitalization of high-risk sectors, including the oil and gas industry, has put a strain on superior workforce skills uniting the aspects of artificial intelligence (AI), big-data analytics, and cybersecurity skills. With the burgeoning skills gaps, cyber threats, and pressure to maintain organisational resilience because of Industry 4.0 and 5.0 technologies changing the landscape of operating spaces, organisations stand to face more challenges. This paper examines the way in which AI-based strategic talent development (STD) models can be used to improve workforce readiness and resilience in critical infrastructure environments. The systematic literature review (SLR) was performed based on PRISMA guidelines that utilised peer-reviewed articles published from 2020 to 2025. The IEEE Xplore, Scopus, ScienceDirect, and ACM Digital Library databases were searched to find the relevant research. High-quality studies amounting to seventy-five were chosen and followed up on the premise of industry applicability, technological depth and empirical rigor. The synthesis covers models of AI adoption, practices of working with the workforce, and the use of cybersecurity in high-risk industries, the oil and gas industry being primarily discussed. The review shows that AI-based skill mapping, custom learning opportunities, and human-AI interaction play a vital role in improving the level of workforce preparedness. All adoption models (TOE, TAM, UTAUT, and AI-readiness indices) have a complementary role in transforming technological competence into effective talent results. The alignment between the big-data analytics and AI-enhanced cybersecurity comforts predictive threat detection and contributes to the active organisational resilience. The results also indicate that a new Resilience Loop has emerged where adoption of AI, talent preparedness, resilient cybersecurity, and resilient organisational performance are connected.
Revitalizing Television Advertisement Markets: Insights and Model Development through Systematic Review
Television advertising is facing declining revenue and audience engagement due to digital intervention and unstable viewer performance. This systematic review searches key issues manipulating TV advertisement income and offers approaches to regenerate the market, with specific consequences for Bangladeshi TV channels and national policymakers. A complete search across over 170 million research papers in Consensus, and identified 950 intellectual outputs. After screening, 133 documents were found to be qualified, and the 50 most relevant studies were observed. The study was directed by specific questions organized into eight thematic clusters that enclosed theories, trends, content strategies, digital transformation, and innovation. The findings specify that electronic convergence, AI, and analytics are snowballing marketing competence; however, there are still lacks in durable behavioral analysis, theoretical incorporation, and moral regulation. Although they have a lot of probable, mixture operations that combine electrical and television media are hardly used in underdeveloped nations like Bangladesh. Finally, data-driven improvement, cross-media incorporation, and moral regulation are compulsory for stimulating the TV publicity industry. In order to appeal in advertising agency and upsurge revenue, the authority should squeeze audience analytics, vary its content, and cooperate with electronic platforms. The government should also support in modernization and fair competition. The advertising market of national television can grow durably with a united, innovation-focused model. Keywords Television channel, advertisement, audience engagement, revenue expand, Television channel, media innovation, Bangladesh Television (BTV)
Financial Risk Management Challenges and the Strategic Role of MIS and Accounting in Modern Business Systems
Financial risk management serves as a vital element for organizational stability which becomes essential for organizations that face multiple regulatory and market and operational uncertainties. Organizations implement MIS together with accounting practices to track and reduce financial risks but their performance and organizational impact need thorough evaluation. This study collected data from 310 professionals who worked in finance and banking and manufacturing and healthcare and retail industries. FRM difficulties together with MIS operations and accounting systems and their combined influence on business results. This study used descriptive statistics to describe participant demographics together with organizational features and employed Pearson correlation and regression analysis to detect connections between FRM, MIS, ACC, INT and BP. The survey results revealed that regulatory compliance at 55.2% and market volatility at 52.6% emerged as the primary financial risk challenges according to the participants. Management information system functions reporting accuracy (59.1%) and real time data availability (57.4%) were identified as the most effective. Pearson correlations revealed that FRM, MIS, ACC, INT and BP share moderate to strong positive connections yet integration stands out as the most influential factor for performance results (r = 0.74, p = 0.01). This study demonstrates that organizations achieve better financial risk management and performance results through effective MIS systems and accounting practices which need to work together as integrated units. Integration of these systems enables management to match risk indicators with performance metrics which leads to better and faster strategic decision-making.
The impact of Artificial Intelligence (AI) applications on teaching quality and learner satisfaction at foreign language centers in Ho Chi Minh City
In the context of the strong educational digital transformation, mastering digital platforms and the application of Artificial Intelligence (AI) at foreign language centers in Vietnam, especially in Ho Chi Minh City (HCMC), is becoming an inevitable trend. Many nations globally have identified education as a top priority sector for AI application. In the United States, according to the 2024 educational technology report, 60% of teachers use AI tools in teaching management. In South Korea, since 2023, the Ministry of Education has piloted the use of AI for primary school students and recorded that 30% of students achieved effectiveness in personalization. In Vietnam, the Ministry of Education and Training is implementing two crucial projects: one involves digital transformation and AI application in teaching and learning; the second is to establish English as the second language in schools. However, quantitative studies assessing the impact of AI on teaching quality and learner satisfaction at foreign language centers in HCMC remain limited. This research will construct and propose a Structural Equation Model (SEM) to test the relationship between AI application, teaching quality, and learner satisfaction. Drawing upon the SERVQUAL theory, TAM, and international research on AI in education, the study proposes four hypotheses regarding the direct and mediating effects among the variables. The paper is expected to provide a crucial reference framework for foreign language centers in their strategy to integrate AI into teaching effectively, humanely, and sustainably.
Socratic Political Heritage - Ethical Challenges and the Role of Dialogue in Contemporary Society
Western philosophy has failed to find a successor to Socrates in political and ethical thought. Contemporary political ethics and civic engagement debates would still depend on his commitment to questioning, moral inquiry, and civic engagement. This paper portrays Socrates' political heritage in terms of ethical challenges and the dialogue as a means for dealing with the modern sociological predicament. It examines how the works of 20th-century philosophers such as Hannah Arendt, Michel Foucault, and Hans-Georg Gadamer reveal that the living Socratic principle is as much of a problem to be solved. This research paper evaluates the Socratic dialogue's role in resisting authoritarianism and developing democratic deliberation in contemporary politics. Finally, the paper affirms that Socratic ethics, concentrating on self-examination and critical dialogue, continues to be a strong instrument for working out contemporary political and ethical difficulties.
The Impact of Basel II Regulations on Firms' Access To Credit: Empirical Evidence From Asian Countries
This study evaluates the impact of Basel II on corporate credit access based on credit ratings, using panel data of 1,295 firms across 17 Asian countries from 2004-2015. System GMM estimation results show that after Basel II implementation, firms with high credit risk (rated BB- and below) experienced a 19.94%-23.30% reduction in credit access compared to higher-rated firms. The study also finds that factors such as operating cash flow, financial leverage, and revenue size significantly impact firms' borrowing decisions in the Basel II context. Based on these findings, the author proposes policy implications including establishing a government credit guarantee system, adjusting risk weights appropriate to Asian market characteristics, reforming the credit rating system, and encouraging banks to develop internal risk assessment capabilities.
The Role of Intelligent ERP Systems in Preventing Corporate Fraud and Strengthening Financial Governance
In an era marked by increasing corporate fraud and financial misconduct, organizations are under mounting pressure to adopt advanced technological solutions that enhance transparency and accountability. This study investigates the role of intelligent Enterprise Resource Planning (ERP) systems, integrated with artificial intelligence (AI), machine learning (ML), and real-time analytics, in preventing corporate fraud and strengthening financial governance. Drawing on both theoretical and empirical insights, the research explores how intelligent ERP systems contribute to early fraud detection, internal control enhancement, and compliance with governance standards. Using a mixed-method approach that combines a review of recent literature with data obtained from finance professionals and ERP users across various industries, the study identifies critical features such as automated anomaly detection, predictive risk modeling, and continuous auditing mechanisms that significantly reduce opportunities for fraudulent activities. Findings indicate that organizations leveraging intelligent ERP systems report improved financial integrity, better decision-making, and stronger adherence to governance policies. The study concludes that intelligent ERP systems not only serve as technological tools but also as strategic enablers of ethical and sustainable financial management. Practical and policy recommendations are provided to guide organizations and regulators in leveraging intelligent ERP capabilities for enhanced corporate governance and fraud mitigation.
Integration of Nanomaterial-Based Filtration and Smart Gas Sensing Systems for Enhanced Safety in Aviation Maintenance Environments
Maintenance workers in aviation constantly work with dangerous substances like hydrazine, JP-8, and AVGAS. The exposure to these chemicals over a long period of time can lead to the development of serious health problems. The current safety regulations in the field are still inadequate to provide complete protection for the workers during refueling and maintenance activities. This study explores how wearable technologies equipped with nanomaterial filters and gas detection sensors can improve both safety and productivity in the aviation industry. Nanomaterials such as graphene, carbon nanotubes (CNTs), and titanium dioxide (TiO₂) provide superior filtration performance because of their large surface area and ability to neutralize toxic compounds. In combination with electrochemical and metal-oxide sensors, these systems can continuously monitor air quality and instantly alert users when harmful gases are detected. The literature review and the available technologies are the major sources of information that this paper uses to justify the benefits of hybrid systems in aviation workplaces in terms of safety, efficiency, and eco-friendliness. It also presents the challenges that are still faced in the areas of weight, power consumption, and reliability over the long term, which are the reasons for the small-scale adoption. The main point is that when one combines nanomaterial filtration with advanced detection technology, the result will be a great reduction of occupational hazards and the increase of aviation safety equipment's lifespan.
Assessing the Factors of Knowledge Management Practice in Banking Systems of Bangladesh
Purpose: This study investigates the factors influencing knowledge management (KM) practices in the banking sector of Bangladesh using exploratory factor analysis (EFA). The research aims to identify the underlying dimensions of KM perceptions and agreements among bank managers. Design/methodology/approach: Data were collected from 174 respondents through a structured questionnaire and analyzed using principal component analysis. The Kaiser-Meyer-Olkin (KMO) measure confirmed sampling adequacy (KMO = 0.951), and Bartlett’s test of sphericity was significant (χ2 = 1635.549, p < 0.001). Findings: The study identified 3 key factors, including “management support and alignment”, “collaboration and culture”, and “resources and documentation”. The ANOVA results reveal statistically significant differences among bank types in perceptions of access to KM resources (p = .024) and the impact of KM culture on employee performance (p = .035). The findings reveal a moderate agreement on KM’s role in improving operations, though gaps remain in alignment and collaboration practices. Originality: This is the first initiative in Bangladesh that can guide banks in enhancing KM practices to achieve organizational objectives.
ENHANCING STUDENTS’ ENGLISH ORAL COMMUNICATION SKILLS THROUGH ROLE-PLAY ACTIVITIES: A CASE STUDY AT HANOI UNIVERSITY OF NATURAL RESOURCES AND ENVIRONMENT
Abstract: Developing oral communication competence remains a persistent challenge for Vietnamese university students, particularly among non-English majors who often exhibit limited fluency despite years of instruction. This study investigates the effectiveness of role-play activities in enhancing students’ English speaking skills at Hanoi University of Natural Resources and Environment (HUNRE). A quantitative case study design was employed with 56 first-year students at the A2 CEFR level. Data were collected through pre- and post-intervention speaking tests, assessed with an adapted analytic rubric, and a post-intervention questionnaire. Findings revealed a statistically significant improvement in students’ speaking performance after an eight-week intervention (t(55) = -5.16, p < .001), with mean scores increasing from 7.02 to 7.35. Questionnaire results further indicated that students perceived role play as engaging, motivating, and beneficial for vocabulary development and communicative confidence. However, challenges such as limited vocabulary, insufficient background knowledge, time constraints, and nervousness were also reported. The results highlight the dual nature of role play: while it fosters measurable gains in oral proficiency, its effectiveness depends on appropriate scaffolding, contextual preparation, and sufficient classroom time. The study contributes empirical evidence on role play in tertiary EFL contexts, offering practical implications for curriculum design, teacher training, and the integration of communicative tasks in general English courses. Future research should explore long-term effects and technology-enhanced role play to broaden its pedagogical impact.
Advertising as a Linguistic Tool: A Syntactic Study of English and Vietnamese Brand Slogans
Advertising slogans are one of the most influential tools for building brand identity and attracting consumer attention in today’s competitive market. Despite their widespread use, many marketing professionals continue to face challenges in crafting effective slogans, often leading to weak associations between brands and their slogans. This study aims to investigate the distinctive syntactic features of English and Vietnamese advertising slogans, with the purpose of identifying both similarities and differences between the two languages. A descriptive and comparative research design was employed, analyzing a corpus of advertising slogans collected from English and Vietnamese newspapers and magazines. The findings reveal that slogans in both languages frequently employ simplicity, brevity, and elliptical structures—such as noun phrases, adjective phrases, and verb phrases—though English slogans show a greater tendency toward ellipsis and dynamic expressions. Additionally, repetition at the syntactic level emerges as a significant device in both languages, enhancing memorability and persuasive power. These results provide valuable implications for teaching and learning business English, offering learners and teachers deeper insights into the linguistic mechanisms of advertising language. Furthermore, the study proposes practical guidelines for advertisers and copywriters to design effective slogans that strengthen brand recognition and consumer engagement.
Reinforcement Learning for Autonomous Data Pipeline Optimization in Cloud-Native Architectures
Efficient data pipeline management is critical for cloud-native architectures, where data velocity, volume, and variety challenge traditional orchestration methods. This study proposes a Reinforcement Learning (RL)-based framework for autonomous optimization of data pipelines, enabling dynamic task scheduling, resource allocation, and failure recovery without human intervention. The framework models pipeline operations as a sequential decision-making problem, where an RL agent learns optimal policies to maximize throughput, minimize latency, and reduce operational costs. Experiments conducted on simulated and real-world cloud-native workloads demonstrate that the RL-optimized pipelines achieve significant performance improvements compared to conventional static and heuristic-based scheduling strategies. This approach highlights the potential of intelligent, self-adaptive data pipelines for scalable, resilient, and cost-efficient cloud-native data processing.