The Digital Revolution in Higher Education: Transforming Teaching and Learning

Digital transformation in higher education has greatly disrupted conventional teaching and learning models. This review traces the evolution of educational technology over the past few decades. It analyzes how tools such as learning management systems, data analytics, online learning, and artificial intelligence impact pedagogy, student experience, educator roles, and institutional learning. The great potential of technology to enhance learning is also discussed, along with the ongoing challenges of justice, ethics, and human relations in its application. Current and emerging technologies are examined, with their implications for key stakeholders. This study uses a multi-faceted methodology to investigate digital transformation in higher education: Historical Analysis, Technology Review Case Studies, Stakeholder Surveys, and Ethical and Social Implications. Predictive modeling and trend analysis are performed to project higher education's future digital transformation trajectory. This includes analysis of new technologies, potential disruptions, and the evolving needs of the education sector. The review brings together insights from academic literature, industry publications, and the digital transformation of higher education over the past few decades, which has been widespread and measurable.  Early adopters of technologies such as analytics, AI, and immersive media will be best positioned to improve the student experience in the future. However, carefully applying and considering students' needs and equality is essential to avoid marginalized groups

Study On Ergonomic Of Working Posture And Workstation Design In Meyer Burger Factory

Manufacturing sector is one of the highest risk industries contributing to the development of work-related musculoskeletal disorders (WMSDs). These problems have attracted much attention in recent years and is becoming more and more wide-spread. The source of concern is in most industrialized countries. The phenomenon of WMSDs must be treated very seriously as it can have a considerable social-economic impact. The study is conducted at Meyer Burger (MB) Sdn Bhd in Malaysia where its general manufacturing activities involve cleaning, loading and unloading, turning process, grooving process, measuring process, collecting data and packing activities. Different employees are exposed to risk factors depending on their job and task. The objectives of this research are to identify the critical activities that affect to the musculoskeletal disorder among MB employees by observation and evaluation of the critical activities, to perform the analysis work posture and to propose and improve posture and workplace design at MB Sdn Bhd. The data for this study are collected via observation and discomfort survey to the MB employees. Other informal data such as experience-posture with photos are been taken during their task. While further analysis based on RULA and REBA are implemented by entering the scores according to the initial degree of body position. Lastly, RULA and REBA tables on the form are then used to compile the risk factor variables, generating a single score that represents the optimum solution of the correct working posture for MB employee. In addition, the finding of the study will provide as useful information and reference to the potential researchers, especially in the manufacturing industry. Nevertheless, employer must take serious action to implementing effective improvements in ergonomics in the workplace in future such by expanding education and training programs to assist employees and employers in understanding and utilizing the range possible workplace designed to reduce work-related musculoskeletal disorders. This may indirectly help to optimize human efficiency, effectiveness, health, safety, and well-being within the context of system performance

Review of the Effectiveness of UV-C for Disinfection of High Touch Objects

General wellbeing dangers like bioterrorism, multi-and unnecessary medication safe tuberculosis, pandemic flu, and outrageous intense respiratory problem have heightened attempts to use environmental measures to deter infection spread that is entirely or partly airborne. UV germicidal irradiation (UVGI) is one such control that has gained renewed recognition following quite a while of under-implementation and negligence. With renewed interest, however, come new concerns, especially about effectiveness and protection. Proof shows that the condition of the patient care system has a significant effect on the risk of hospital acquired infections among hospitalized patients. The new launch of its use for surface decontamination has piqued the attention of medical facilities. Nonetheless, the worldwide scattering of the novel Covid-19 (SARS-CoV-2) brought about a shortage of filtering facepiece respirators (FFR) among medical services experts. This has raised the issue of whether FFRs can be safely sanitized for reuse without endangering primary strength or viability by utilizing UV light. There is a long history of studies reasoning that, when utilized appropriately, UVGI can be both sound and successful in sanitizing surfaces, keeping away from the spread of various airborne microorganisms

Green strategic leadership capability: Construct development and measurement validation

Green strategic leadership capability (GSLC) has emerged as a major study topic in strategic management in light of urgent global crises such as climate change. There is, however, a paucity of theoretically conceptualised and empirically validated measurement models evaluating the various leadership capabilities of top managers. GSLC implies that top managers endorse green management practices in organisational operations to minimise their environmental impact. Our research conceptualises GSLC from a natural-resource-based view by considering top managers’ capabilities to develop GSLC measurement models. We used a multi-study, multi-method approach to develop GSLC multidimensional scales using field interviews, thematic analysis and bulk surveys. GSLC is operationalised as a hierarchical and multidimensional scale consisting of three core dimensions, namely green foresight capability, green adaptive capability and green absorptive capability, along with nine subdimensions – resulting in 31 measurement items. The developed and validated scales may be applied to extend the theory and practice of green management, while offering a valuable source for organisations to assess their GSLC and identify and prioritise areas for green growth

Density-functional description of materials for topological qubits and superconducting spintronics

Interfacing superconductors with magnetic or topological materials offers a playground where novel phenomena like topological superconductivity, Majorana zero modes, or superconducting spintronics are emerging. In this work, we discuss recent developments in the Kohn-Sham Bogoliubov-de Gennes method, which allows to perform material-specific simulations of complex superconducting heterostructures on the basis of density functional theory. As a model system we study magnetically-doped Pb. In our analysis we focus on the interplay of magnetism and superconductivity. This combination leads to Yu-Shiba-Rusinov (YSR) in-gap bound states at magnetic defects and the breakdown of superconductivity at larger impurity concentrations. Moreover, the influence of spin-orbit coupling and on orbital splitting of YSR states as well as the appearance of a triplet component in the order parameter is discussed. These effects can be exploited in S/F/S-type devices (S=superconductor, F=ferromagnet) in the field of superconducting spintronics

Fake news on Facebook and their impact on supply chain disruption during COVID-19

Social media (SM) fake news has become a serious concern especially during COVID-19. In this study, we develop a research model to investigate to what extent SM fake news contributes to supply chain disruption (SCD), and what are the different SM affordances that contribute to SM fake news. To test the derived hypotheses with survey data, we have applied partial least square based structural equation modelling (PLS-SEM) technique. Further, to identify how different configurations of SC resilience (SCR) capabilities reduce SCD, we have used fuzzy set qualitative comparative analysis (fsQCA). The results show that SM affordances lead to fake news, which increases consumer panic buying (CPB); CPB in turn increases SCD. In addition, SM fake news directly increases SCD. The moderation test suggests that, SCR capability, as a higher-order construct, decreases the effect of CPB on SCD; however, neither of the capabilities individually moderates. Complimentarily, the fsQCA results suggest that no single capability but their three specific configurations reduce SCD. This work offers a new theoretical perspective to study SCD through SM fake news. Our research advances the knowledge of SCR from a configurational lens by adopting an equifinal means towards mitigating disruption. This research will also assist the operations and SC managers to strategize and understand which combination of resilience capabilities is the most effective in tackling disruptions during a crisis e.g., COVID-19. In addition, by identifying the relative role of different SM affordances, this study provides pragmatic insights into SM affordance measures that combat fake news on SM.publishedVersionPaid Open Acces

Data analytics for sustainable global supply chains

Based on the key metrics to monitor energy sector improvements from the International Energy Agency (IEA), transport emissions must decrease 43% by 2030. Freight logistics operations in Europe are struggling with ways to reduce their carbon footprints in order to adhere to regulations on governing logistics, while providing the increasing demand for sustainable products from the customers. This study investigates the anonymised microdata from the European Road Freight Transport Survey (2011–2014) to acquire patterns in logistic operations based on over 11 million journeys within 27 EU and EFTA countries involved. Different algorithms were implemented (Horizontal Cooperation, Pooling and Physical Internet) to analyse efficiency, in terms of vehicle utilisation, degree of vehicles’ loading during each journey and sustainability in terms of the amount of emissions per journey. This study shows that existing data can provide invaluable information on the efficiency of logistics operations and the positive effects data analytics can provide. Physical Internet algorithm has performed better in terms of reducing emissions and improving the logistics’ efficiency, especially when the sample sizes are large, but this would require a shift to an open global supply web

A modified routine analysis of arsenic content in drinking-water in Bangladesh by hydride generation-atomic absorption spectrophotometry.

The high prevalence of elevated levels of arsenic in drinking-water in many countries, including Bangladesh, has necessitated the development of reliable and rapid methods for the determination of a wide range of arsenic concentrations in water. A simple hydride generation-atomic absorption spectrometry (HG-AAS) method for the determination of arsenic in the range of microg/L to mg/L concentrations in water is reported here. The method showed linearity over concentrations ranging from 1 to 30 microg/L, but requires dilution of samples with higher concentrations. The detection limit ranged from 0.3 to 0.5 microg/L. Evaluation of the method, using internal quality-control (QC) samples (pooled water samples) and spiked internal QC samples throughout the study, and Standard Reference Material in certain lots, showed good accuracy and precision. Analysis of duplicate water samples at another laboratory also showed good agreement. In total, 13,286 tubewell water samples from Matlab, a rural area in Bangladesh, were analyzed. Thirty-seven percent of the water samples had concentrations below 50 microg/L, 29% below the WHO guideline value of 10 microg/L, and 17% below 1 microg/L. The HG-AAS was found to be a precise, sensitive, and reasonably fast and simple method for analysis of arsenic concentrations in water samples

Influence of Antioxidant-Enhanced Polymers in Bitumen Rheology and Bituminous Concrete Mixtures Mechanical Performance

This paper evaluates the effect of polymer enhancement with antioxidant in the rheological properties of bitumen and mechanical properties of bituminous concrete mixture (BCM). In this study, two antioxidant-enhanced polymers were utilized in mitigating bitumen hardening due to aging. The rheological testing consists of temperature sweep using Dynamic Shear Rheometer at various aging conditions. Critical stiffness temperature data from the sweep test suggested that enhanced polymer exhibits less long-term hardening and brittleness compared to standard polymer. The mechanical testing consists of dynamic modulus, indirect tensile, flow number, and beam fatigue tests on BCM exposed to short-term aging. Hamburg wheel tracking test was also performed to assess moisture-damage susceptibility. It is found that the enhanced-polymer BCM exhibited higher modulus, higher tensile strength ratio, improved rutting resistance, lower moisture-damage susceptibility, and slightly increased fatigue life as compared to standard-polymer BCM