The COVID-19 epidemic has given rise to a new situation that requires the qualification and training of teachers to operate in educational crises. Amidst the pandemic, online training has emerged as the predominant approach for delivering teacher training. The COVID-19 pandemic has created potential opportunities and challenges for online training, which may have a long-lasting impact on online training procedures in the post-pandemic era. This study aims to determine the primary potential and constraints of online training as seen by instructors. The Technology Acceptance Model (TAM) identified online training opportunities and challenges by examining the to-be-applied behavioral intention variables that influence trainees. These variables include individual, system, social, and organizational factors. The study has applied the Phenomenological technique to address the research issues, using the Semi-structured interview tool to get a comprehensive knowledge of the online training phenomena amongst the pandemic. A total of seven participants were selected from a list of general education teachers at the Central Education Office of the Education Department in Bisha Governorate. These people were deliberately selected because of their high frequency of completing training sessions throughout the epidemic. A series of interviews was conducted with these participants. The findings indicated that the primary prospects included both equal opportunities and digital culture within the individual factors, enrollment in training programs and variation in training programs across organizational characteristics, the use of digital material and electronic archiving within the system variables, engaging in the exchange of personal experiences, providing constructive criticism, and fostering favorable communication within the realm of social factors. However, the primary obstacles included deficiencies in digital competencies, compatibility of trainees’ attributes, and dearth of desire as per individual factors, the temporal arrangement of training programs, as well as the lack of prior preparation and preparedness within the realm of organizational factors. Other challenges included the absence of trainer assessment, limited diversity of training exercises, and technological obstacles within the system factors, and ultimately the absence of engagement with the instructor, and lack of engagement with peers are within the social variable.

Abrupt changes in environmental temperature, wind and humidity can lead to great threats to human life safety. The Gansu marathon disaster of China highlights the importance of early warning of hypothermia from extremely low apparent temperature (AT). Here a deep convolutional neural network model together with a statistical downscaling framework is developed to forecast environmental factors for 1 to 12 h in advance to evaluate the effectiveness of deep learning for AT prediction at 1 km resolution. The experiments use data for temperature, wind speed and relative humidity in ERA-5 and the results show that the developed deep learning model can predict the upcoming extreme low temperature AT event in the Gansu marathon region several hours in advance with better accuracy than climatological and persistence forecasting methods. The hypothermia time estimated by the deep learning method with a heat loss model agrees well with the observed estimation at 3-hour lead. Therefore, the developed deep learning forecasting method is effective for short-term AT prediction and hypothermia warnings at local areas.

Shore line change is considered as one of the most dynamic processes, which were mapped along the coast of Tiruvallur district by using topographic maps of 1976 and multi-temporal satellite images. The satellite images pertaining to 1988, 1991, 2006, 2010, 2013 and 2016 were used to extract the shorelines. It is important to map and monitor the HTL (High Tide Line) at frequent time intervals as the shoreline was demarcated by using visual interpretation technique from satellite images and topographic maps. Followed by this, an overlay analysis was performed to calculate areas of erosion and accretion in the study area. The results revealed that the coast of Tiruvallur district lost 603 ha and gained 630 ha due to erosion and accretion respectively. It was confirmed after the ground truth survey carried out in the study area. The high accretion of 178 ha was found nearby Pulicat Lake and low accretion of 19 ha was seen between Pulicat Lake and Kattupali Port. The high erosion area was found along the Pulicat Lake, Kattupali and Ennore ports, and Ennore creek mouth and southern Ennore such as Periya Kuppam, Chinna Kuppam, Kasi Koil Kuppam, and Thyagarajapuram. It may be concluded that the coastal erosion and accretion in the study area were mainly caused by anthropogenic and natural factors, which altered the coastal environment.

In today’s rapidly evolving organizational landscape, understanding the dynamics of employee incentives is crucial for fostering high performance. This research delves into the intricate interplay between moral and financial incentives and their repercussions on employee performance within the dynamic context of healthcare organizations. Drawing upon a comprehensive analysis of 226 respondents from three healthcare organizations in Klang Valley, Peninsular Malaysia, the study employs a quantitative approach to explore the relationships between independent variables (career growth, recognition, decision-making, salary, bonus, promotion) and the dependent variable of employee performance. The research unveils that moral incentives, including career growth, recognition, and decision-making, significantly impact employee performance. Professionals motivated by opportunities for growth, acknowledgment, and participation in decision-making demonstrate heightened engagement and commitment. In the financial realm, competitive salaries, performance-based bonuses, and transparent promotion pathways are identified as crucial factors influencing employee performance. The study advocates a holistic approach, emphasizing the synergistic integration of both moral and financial incentives. Healthcare organizations are encouraged to tailor their incentive structures to create a supportive and rewarding workplace, addressing the multifaceted needs and motivations of healthcare professionals. The implications extend beyond academia, offering practical guidance for organizations seeking to optimize workforce dynamics, foster job satisfaction, and ensure the sustainability of healthcare organizations.

This study aims to evaluate the influence of population dependency ratio on the economic growth of Bangladesh, India, and Pakistan, the three members of the South Asian Association for Regional Cooperation (SAARC). The study covers the time from 1960 to 2021. It also analyses in detail how population aging and the youth dependency ratio affects the development of certain sectors, including industry, services and agriculture. This study uses panel data to determine the influence of population dependency ratios on economic growth. To estimate this effect, we use the Pooled Mean Group/Autoregressive Distributed Lag (PMG/ARDL) technique. Based on the results obtained from the ARDL analysis indicate the presence of a long-term relationship among these variables. These discoveries align with prior empirical research conducted by Lee and Shin, Mamun et al., and Rostiana and Rodesbi. Furthermore, the findings suggest that an increase in the old age population dependency ratio positively influences economic growth within these nations. The long-term relationship findings pertaining to the old and young dependency ratio and economic growth corroborate the conclusions of Bawazir et al., who proposed that the old population dependency ratio exerts a favorable impact, while the young population has an adverse effect on economic growth. Originality: This research focused on the population dependency ratio, a pivotal demographic metric that gauges the proportion of individuals relying on support (including children and the elderly) compared to those of working age. This investigation particularly explores the interconnection between the population dependency ratio and sectoral development, an essential aspect given that various sectors make distinct contributions to economic advancement. Examining how population dynamics affect sectoral development yields valuable insights into the overall economic performance of Pakistan, India, and Bangladesh.

This article explores the implications of directive change management, characterized by top-down leadership and minimal employee involvement, on organizational dynamics, employee morale, and job security. This approach's psychological and operational impacts are underscored, emphasizing the imperative of addressing employee perceptions and fostering trust. Strategies for rebuilding trust and enhancing morale post-directive change management are presented, including transparent communication, participative decision-making, and recognition of employee contributions. The significance of enhancing job security through clear policies, open dialogue, and robust mental health and well-being support systems is highlighted. Practices that encourage job dedication are introduced, emphasizing goal alignment, meaningful work design, and a culture of innovation and continuous improvement. Long-term strategies for cultivating a healthy workplace, such as establishing feedback mechanisms, investing in leadership development, and maintaining organizational adaptability, are also discussed. This brief article is an introductory resource for business leaders, managers, and change practitioners seeking to be better equipped with the necessary tools and strategies to navigate the post-implementation effects of directive change management. It is anticipated that this information can assist leaders and organizations in navigating the challenges of directive change management, promoting resilience, employee well-being, and sustainable organizational success.