Online Language Learning Strategies in Institutes of Higher Learning (IPT) Malaysia Post Covid-19

The Covid-19 pandemic that spreaded around the world in March 2020 has changed the nation's education landscape. Standard Operating Procedures that demand presence at respective residences have made online learning one of the best platforms that replace face-to-face learning in educational institutions across the country. Thus, this study aims to propose an effective online language learning strategy to be a reference for educators and students to master language skills using post-Covid19 educational technology. This research employs quantitative methods cross sectional studies supported by qualitative data. The research instruments is questionnaires. A total of 280 respondents consisting of university students in the Arabic field at Malaysian universities answered the questionnaire. The results showed that the respondents know how to learn through online learning with a mean rate of 4.24 and the respondents agreed that the instructions given during online learning should be clear with a highest mean rate of 4.46. Among the online learning strategies used by students are always sharing opinions during online learning, responding using chat rooms to engage in discussions and making notes to improve understanding. Respondents are also satisfied with online learning platforms such as google meet, Webex and zoom © 2023, International Journal of Interactive Mobile Technologies.All Rights Reserved.

Prediction of Dropout Students in Massive Open Online Courses Using Ensemble Learning: A Pilot Study in Post-COVID Academic Session

High dropout rate is a critical problem in MOOCs. The prime objective of this study is to identify possible dropout students at the early stage of the course and reducing the number of dropouts providing proper feedback to address the relevant factor. A prediction model based on stacking ensemble machine learning is proposed to identify whether a learner is at risk of dropping a course. The proposed stacked ensemble model outperformed with an accuracy of 93.4% compared to other popular machine learning classifiers. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Predicting the Impact of Change in Air Quality Patterns Due to COVID-19 Lockdown Policies in Multiple Urban Cities of Henan: A Deep Learning Approach

Several countries implemented prevention and control measures in response to the 2019 new coronavirus virus (COVID-19) pandemic. To study the impact of the lockdown due to COVID-19 on multiple cities, this study utilized data from 18 cities of Henan to understand the air quality pattern change during COVID-19 from 2019 to 2021. It examined the temporal and spatial distribution impact. This study firstly utilized a deep learning bi-directional long-term short-term (Bi-LSTM) model to predict air quality patterns during 3 periods, i.e., COVID-A (before COVID-19, i.e., 2019), COVID-B (during COVID-19, i.e., 2020), COVID-C (after COVID-19 cases, i.e., 2021) and obtained the R-2 value of more than 72% average in each year and decreased MAE value, which was better than other studies' deep learning methods. This study secondly focused on the change of pollutants and observed an increase in Air Quality Index by 10%, a decrease in PM2.5 by 14%, PM10 by 18%, NO2 by 14%, and SO2 by 16% during the COVID-B period. This study found an increase in O-3 by 31% during the COVID-C period and observed a significant decrease in pollutants during the COVID-C period (PM10 by 42%, PM2.5 by 97%, NO2 by 89%, SO2 by 36%, CO by 58%, O-3 by 31%). Lastly, the impact of lockdown policies was studied during the COVID-B period and the results showed that Henan achieved the Grade I standards of air quality standards after lockdown was implemented. Although there were many severe effects of the COVID-19 pandemic on human health and the global economy, lockdowns likely resulted in significant short-term health advantages owing to reduced air pollution and significantly improved ambient air quality. Following COVID-19, the government must take action to address the environmental problems that contributed to the deteriorating air quality.

Caring Through COVID Findings from a Quality Improvement Project

This multisite quality improvement (QI) project reports on a psychotherapy group for family care partners of persons living with neurodegenerative conditions. Following the plan-do-study-act model, a team of geropsychologists iteratively developed, implemented, and refined the 8-week "Caring Through COVID" psychotherapy group across five cycles from January 2021 to April 2022. Participants were 21 spouses or adult children of persons living with neurodegenerative conditions. Across two clinics, participants evidenced moderate improvements in caregiver burden (d = .59), self-efficacy for caregiving (d = -.64), and self-efficacy for emotion regulation (d = -.60). The group was perceived positively by participants. This QI project demonstrates the real-world implementation of a psychotherapy group developed during the COVID-19 pandemic and refined to remain ongoing.

Backward Bifurcation and Hysteresis in a Mathematical Model of COVID19 with Imperfect Vaccine

Vaccination has been used as strategy to eradicate the spread of COVID-19. But imperfect vaccine has been reported to induce backward bifurcation and hysteresis in mathematical models of disease transmission. Backward bifurcation is a phenomenon whereby a stable endemic equilibrium exists contemporaneously with a stable disease-free equilibrium when the basic reproduction number is less than 1. This situation can cause difficulty in controlling an epidemic because the basic reproduction is no longer the only means of eradicating the disease. In this paper, we propose a mathematical model for the transmission of disease which includes imperfect vaccination. We show that our model is capable of capturing backward bifurcation under certain conditions. By using parameters that are relevant to COVID-19 transmission in Malaysia, our numerical analysis shows that low vaccine efficacy can trigger backward bifurcation.

PREPARATION OF AVIATION INDUSTRY TRANSITION ON COVID-19 FROM PANDEMIC TO ENDEMIC PHASE: A REVIEW

Purpose: The aim of this study is to examine the Malaysian government's actions towards the aviation industry to deal with the Covid-19 pandemic and the transition phase from pandemic to endemic. Transition phase refers to a temporary period before the country could fully enter the endemic phase which is subject to an announcement by the World Health Organisation (WHO). Theoretical framework:The study on air transport affected by pandemic and industry action toward the endemic phase. This study refers to the conceptual framework for emergency department design in a pandemic by Aujirapongpan (2023): Relationship between state, hospital and ED in pandemic preparedness planning and response. Design/methodology/approach: The approach used is qualitative research that are observation and literature review. Findings: The results demonstrate the Malaysian government's actions during the transition period from pandemic to endemic. Restrictions on travel between areas cause the public to be unable to move at will, causing passengers to be unable to buy plane tickets. The government's actions have indeed had an impact on the airline company's income. Among the significant effects are the workers who were laid off in the era of the pandemic. At the same time, the government is also trying to help airlines financially to survive while waiting for the endemic period. The Malaysian government does not have a specific framework for the airline industry to face the pandemic, however, the Malaysian government gives a quick reaction to control the situation. Research, Practical & Social implications: The study gives comparative responses on the aviation industry by the government when faced with a pandemic, as well as planning for the transition to the endemic phase. Originality/value: The result indicates the government participation and action changes of the air transport operation on the Covid-19 pandemic to endemic transition phase. © 2023 AOS-Estratagia and Inovacao. All rights reserved.

Production of Sars-Cov-2 Membrane Protein as Better Target Protein for Diagnostic Application

Intro: The COVID-19 pandemic is caused by the SARS-CoV-2 virus, an enveloped RNA of the coronavirus family. The advancement in molecular technology and biochemistry has accelerated the development of diagnostic reagents and assays. Much attention has been focused on the S protein, but the high mutation rate in this region could lead to false negative results. Thus, a better target protein for diagnostic application is needed for accurate detection. Method(s): Nucleotide sequences encoded for membrane (M) glycoprotein gene region of SARS-CoV-2 from Malaysian isolates were extracted from GISAID, aligned, and selected accordingly. The DNA plasmid was commercially synthesized with codon optimization for Escherichia coli (E. coli), and the presence of the M gene was confirmed by PCR. The plasmid was then transformed into E. coli. Later, the expression of M glycoprotein was induced, separated on an SDS-PAGE gel, and transferred onto a nitrocellulose membrane, followed by immunostaining. Finding(s): The analysis of the M glycoprotein against the Omicron strains demonstrated that the amino acid is conserved (99.5%). The M glycoprotein was successfully expressed and detected with antibodies from SARS-CoV-2 infected patients at ~26 kDa. The protein is currently upscale for the generation of monoclonal Ab (Mab). Discussion(s): The M protein of SARS-CoV-2 is more conserved among the virus and also has been reported to confer antigenic properties. Selection of M protein perhaps a better option compared to current detection assays that use spike (S) protein, which could lead to false negative results, as this gene region particularly the ribosome-binding domain (RBD) rapidly undergoes mutations. The utilization of M protein potentially improves negative predictive value (NPV) of the diagnostic test. Conclusion(s): Further development of diagnostic reagents is needed to improve the assay's specificity. The newly developed M protein and the MAb can be used to generate a more accurate viral detection assay.Copyright © 2023

Lipase Elevation in Patients With COVID-19.

INTRODUCTION: Although coronavirus disease (COVID-19) has been associated with gastrointestinal manifestations, its effect on the pancreas remains unclear. We aimed to assess the frequency and characteristics of hyperlipasemia in patients with COVID-19. METHODS: A retrospective cohort study of hospitalized patients across 6 US centers with COVID-19. RESULTS: Of 71 patients, 9 (12.1%) developed hyperlipasemia, with 2 (2.8%) greater than 3 times upper limit of normal. No patient developed acute pancreatitis. Hyperlipasemia was not associated with poor outcomes or symptoms. DISCUSSION: Although a mild elevation in serum lipase was observed in some patients with COVID-19, clinical acute pancreatitis was not seen.

Exploring Mental Health and Psychosocial Well-Being in Recovered Jordanian Individuals With COVID-19: A Phenomenological Study.

BACKGROUND: COVID-19-related healthcare services focus primarily on medical and physical treatments. Related treatments for psychosocial and mental health needs have not been a priority for healthcare professionals. Understanding the process by which individuals who have recovered from COVID-19 adapt psychologically will allow better planning for mental healthcare and healthcare outcomes. PURPOSE: The purpose of this study was to explore how recovered individuals with COVID-19 adapted to related psychological and social stressors during the infection period. METHODS: A descriptive phenomenological approach was used to investigate a purposive sample of 13 individuals in Jordan who had recovered from COVID-19. Data were collected using semistructured interviews. RESULTS: Perceptions related to being diagnosed with COVID-19 were distinguished into four major themes: conscious awareness (acceptance, victimization, and normalizing), uncertainty (apprehension and poor communication), sources of psychosocial support (caring family, healthcare professionals' support, and self-grieving), and resilience (optimism, positive thinking, and spirituality). CONCLUSIONS: The findings of this study indicate the need to integrate psychosocial and mental healthcare services into healthcare plans provided to individuals with COVID-19 and similar pandemic infections.

Systematic review on digital transformation among teachers in public schools

Radical changes across almost all areas, including education, due to the COVID-19 outbreak. One of the rapid transformations is digital learning, also known as e-learning. Digital learning transformation has been taking place for more than a decade. However, little comprehensive analysis of digital transformation in teaching in public schools. To the best of the authors' knowledge, no comprehensive analysis incorporates external and internal barriers and examines the prominent theories to study successful e-learning integration among teachers. The aim of this study was to provide a thematic and theoretical understanding of digital learning transformation among teachers in public schools. The data for the study was acquired from the Scopus databases. The study employed content and comparative analysis and advocated a grounded theory approach to inductively analyze and criticize the theme construction for answering two research questions. Based on a set of criteria to determine whether each derived study should be included or excluded, 42 articles were reviewed between 2010 and 2022. The analysis uncovered 10 themes of antecedents that were constructed as a framework based on the first-second-order barriers. Results also indicated that CHAT, TPACK, TAM, and UTAUT are the most prominent theories used to conduct digital transformation research. The findings offered significant implications for digital transformation and educational technology communities, especially for policymakers to strategize and reflect on the practice they implemented and improvised if necessary for future sustainable education and efficient teachers' performance in teaching. © Institute of Advanced Engineering and Science.

Connectedness analysis of price return index among Malaysian economic sectors

Purpose: This study aims to explore the connectedness of price return index spillovers across eight economic sectors in the Malaysian stock market (Bursa Malaysia). Design/methodology/approach: The analysis uses daily data of sectoral price index from 10 May 2005 to 24 February 2021. The study uses Bayesian time-varying parameter vector autoregressive. Findings: The degree of price return index spillovers varies over time, reaching unprecedented heights during the COVID-19 pandemic in 2020. The industrial economic sector is the main transmitter of price index return shock, whereas the utilities economic sector is the dominant receiver of index return spillovers. Originality/value: The findings are critical for investors, market participants, businesses and policymakers in developing action plans for the vulnerable sectors. It further enhances investors' confidence in making investment decisions. © 2023, Emerald Publishing Limited.

THE FUNDAMENTAL RIGHTS OF CHILDREN DEPRIVED OF LIBERTY IN DETENTION CENTRES IN MALAYSIA DURING THE COVID-19 PANDEMIC: A QUALITATIVE STUDY

The spread of the Covid-19 virus that initially surfaced in China in late 2019 eventually emerged as a global pandemic which adversely affected the worldwide population, including Malaysia. Consequently, the Malaysian government implemented many social and public health measures to help control the spread of Covid-19 in the country. The Covid-19 pandemic affected every level of society in Malaysia, including children who are susceptible to being emotionally, psychologically, and mentally affected due to lockdown measures, school closures, and loss of employment suffered by family members.There is a gap in existing research concerning the impact of Covid-19 on children deprived of liberty in detention centres in Malaysia. Hence, this study aims to identify whether the legal framework in Malaysia adequately protects the rights of children deprived of liberty in detention centres, in line with the international legal framework. A qualitative research design was adopted to explore the issues surrounding the impact of Covid-19 on children in detention centres. Library-based research and semi-structured interviews were carried out with officers from detention centres and the Department of Social Welfare. This research demonstrates that sound policies and guidelines and the availability of fully trained staff are essential in meeting the emotional, physical, and mental needs of children in detention centres. This research is significant for policymakers to strengthen the current legal framework in order to afford better protection for children in detention centres, in line with the Ministry of Women, Family and Community Development Policy (2021–2025) as well as the international legal framework. © 2023, UUM Journal of Legal Studies. All Rights Reserved.

Using Deep Transfer Learning to Predict Student Engagement in Online Courses

The use of online courses is growing worldwide that has opened the door for the interested students to learn comfortably from their locations especially, during Covid-19 pandemic. However, an important aspect of traditional classroom is real-time students' feedback for content delivery and interactive sessions, which is missing in online courses. The aim of this work is to bridge this gap by providing an automatic recognition system for engagement level of the students during online courses using deep transfer learning. In this paper, a CNN based method is proposed to predict the level of engagement while watching online class sessions. The CNN based method consists of two different modalities including: (1) pre-trained network based transfer learning for feature extraction from image data, (2) support vector machine (SVM) classifier for classification. Ten different pre-trained networks are used in the proposed method. The superiority of the method is evaluated on the dataset created using images of graduate students. Of all pre-trained networks, Resnet50 and VGG16 achieved highest classification accuracy of 72.34% and 71.77% using the proposed approach respectively. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Do oil shocks affect the green bond market?

This study examines the predictive power of oil shocks for the green bond markets. In line with this aim, we investigated the extent to which oil shocks could be used to accurately make in- and out-of-sample forecasts for green bond returns. Three striking findings emanated from our results: First, the three types of oil shock are reliable predictors for green bond indices. Second, the performances of the predictive models were consistent across the different forecasting horizons (i.e. H = 1 to H = 24). Third, our findings were sensitive to classifying the dataset into pre-COVID and COVID eras. For instance, the results confirmed that the predictive power of oil shocks declined during the crisis period. We also discuss some policy implications of this study's findings. © 2022 The Author(s)

Asymmetric spillover effects of Covid-19 on the performance of the Islamic finance industry: A wave analysis and forecasting

This paper investigates the spillover effects of the waves of Covid-19 that affected the performance of the Islamic financial sector index (KMI 30) concerning Pakistan's stock exchange. The daily data is used on confirmed registered cases of Covid-19 and the KMI 30 stock prices from February 2020 to June 2022. The data is distributed into five segments on the basis of Covid-19 waves. The asymmetric GJR-GARCH is used to capture the effect of Covid-19 during each wave and E-GARCH is used to see the positive and negative impacts of Covid-19 on KMI through spillover effects. The E-GARCH model also serves to forecast the conditional variance. The Chow structural break point and Bai and Perron tests identify the structural breaks in each wave. Results of structural break testing confirm the presence breaks in each wave. Meanwhile volatility modeling results indicate there is an asymmetric effect in the return series. The E-GARCH model results reveal that there is return and volatility spillover effect from Covid-19 to KMI 30 in each wave. In future the conditional volatility remains less than the expected volatility as predicted by the forecasting statistics. We respond to policy calls by sharing our novel research in not only combating, but also assisting the required urgency of planning for future of Covid-19 outbreaks. © 2022

Assessing the COVID-19 pandemic impact on tourism arrivals: The role of innovation to reshape the future work for sustainable development

The current COVID-19 pandemic has generated unprecedented disruption in the tourism sector, requiring innovative solutions to reshape future work for sustainability. Despite the several benefits of tourism and innovation, studies examining the interlinkages among tourism, pandemic uncertainty, and innovations for sustainability are rare. To fill this gap, this paper investigates the impact of the pandemic on tourism arrivals, and the effects of tourism arrivals and pandemic impacts on the sustainable development of France. The paper further considers the innovation influences on pandemic uncertainty to consider it key for the control of the pandemic. Autoregressive distributed lag results based on 25 years of historical data show that the immediate effects of pandemic discussion on tourism arrivals are insignificant. However, in the long run, such effects become significantly negative, revealing that a rise in pandemic discussion reduces tourism arrivals in France. We find that tourism arrivals and pandemic discussions have positive significant effects on the sustainability of France. The tourism arrivals and pandemic discussion interaction results reveal that tourists who are aware of the pandemic significantly contribute to sustainability. Significant evidence shows that a rise in innovation helps to reduce pandemic uncertainty. However, innovation's short-term effects are more prominent compared with the long-term effects, indicating that the pandemic can be countered in the short run with the help of innovative solutions. Thus, relying on innovation, especially innovations related to COVID-19 will reduce the pandemic's risk. Our results were robust to various econometric methodologies. We have drawn policy implications to focus on tourism development and constant innovations for sustainable recovery.

In silico evaluation of potential murine M49 DNA aptamer on ORF7a of SARS-COV-2: A similar target

DNA aptamers are short nucleotides with a high affinity for their target. However, the process of isolating aptamers via the systematic evolution of ligands by exponential enrichment (SELEX) procedure is laborious. Therefore, an in silico approach is used to screen potential DNA aptamer candidates as a kickstart specifically for ORF7a of SARSCOV-2. By applying the TM-align program, the murine receptor (CD200R) protein was found to have structural similarities with ORF7a. Based on the literature, this CD200R protein is successfully bound by M49 DNA aptamers experimentally. Herein, the 3D structure of the M49 DNA aptamer was generated using Mfold, RNA Composer webserver, Discovery Studio Visualizer, and UCSF Chimera software, and the docking simulation was predicted using the HDOCK webserver. The binding energy scores for the M49-CD200R complex were slightly higher than those for the M49-ORF7a complex with-233.78 and-220.11, respectively. The molecular interaction in the complexes was contributed by the hydrogen bond. In conclusion, the M49 aptamer of CD200R protein can bind to the other similar target, the ORF7a protein of SARS-COV-2. Even though CD200R and ORF7a proteins share structural similarities, the binding sites of the individual complex are distinct. The current study shows that two different proteins with structural similarities may have a possibility to share the same DNA aptamer. This strategy may result in efficient aptamer discovery using an in silico method as a first step. © 2022 Marmara University Press.

Understanding of Mosque Managements in Semarang City of Covid-19 Disease and Plague

The Covid-19 pandemic, which has been running for more than two years, has changed the fabric of people's lives, including religious life. This study aims to determine the extent of understanding of the Takmir Mosque Management in Semarang City about illness and the Covid-19 Pandemic Outbreak. The data were taken from documentation and questionnaires distributed to the selected Takmir Masjid management in Semarang Citysin a structured manner with an open-ended question model. The research subjects were determined through purposive sampling, with the criteria of the Takmir Masjid management in Semarang City. The collected data were analyzed by means of descriptive-qualitative. The results showed that the understanding of Takmir mosque administrators in the city of Semarang regarding the Covid outbreak was diverse. The research is expected to provide input for the government in implementing policies for regulating worship in mosques during the Covid-19 pandemic. © The Authors, published by EDP Sciences.

Working from home, COVID-19 and multi-dimensional model of well-being theory

The well-being theory (WBT) identifies five well-being variables: positive emotion, engagement, relationships, meaning, and accomplishment (PERMA). These variables are significantly empirically verified predictors of flourishing or optimum well-being. However, empirical research for WBT's multidimensional model in the context of work from home, particularly during COVID-19, is limited. This study is important in order to analyse any potentials or challenges that could significantly determine the well-being of workers during WFH, for both public and private sector considerations. As such, this paper aims to contribute to the extant knowledge and practice of WFH from the perspective of the well being theory. Adopting a qualitative methodology, this study identifies the perceived benefits of WFH, including increased productivity, job satisfaction, reduced stress, improved work life balance, and better mental health. Challenges identified include increased work intensity, communication issues, and disruptions to work life balance. Further investigation into the gendered dimension of WFH and its relationship to the life stages of workers revealed a perceived equal relationship between genders, downplaying existing traditional gender stereotypes within participants' households. These findings shed some light on the importance of further research into well-being, particularly for workers and organisations opting for WFH in the post pandemic era. Copyright © 2022 Inderscience Enterprises Ltd.

Numerical simulations on scale-free and random networks for the spread of COVID-19 in Pakistan

Epidemiology is the study of how and why an infectious disease occurs in a group of peo-ple. Several epidemiological models have been developed to get information on the spread of a dis-ease in society. That information is used to plan strategies to prevent illness and manage patients. But, most of these models consider only random diffusion of the disease and hence ignore the num-ber of interactions among people. To take into account the interactions among individuals, the net-work approach is becoming increasingly popular. It is novel to consider the dynamics of infectious disease using various networks rather than classical differential equation models. In this paper, we numerically simulate the Susceptible-Infected-Recoverd (SIR) model on Barabasi-Albert network and Erd delta s-Re acute accent nyi network to analyze the spread of COVID-19 in Pakistan so that we know the severity of the disease. We also show how a situation becomes alarming if hubs in a network get infected.(c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).