Factors Determining the Acceptance of E-Wallet among Gen Z from the Lens of the Extended Technology Acceptance Model

E-wallets are one of the breakthroughs brought forth by the evolution of FinTech, which has been accentuated by the global outbreak of COVID-19. Therefore, it is critical to comprehend the factor of e-wallet acceptance. As this technology advances, substantial knowledge and research gaps become apparent. Previous studies on e-wallet acceptance have overlooked the importance of motivation and self-efficacy. There is a dearth of focus on certain age groups, such as Gen Z, which is currently the trendsetter of new technologies. This study aims to close the gaps regarding the lack of focus toward Gen Z, motivation, and self-efficacy in understanding e-wallet acceptance by combining the Technology Acceptance Model (TAM) with Self-Determination Theory (SDT), Self-Efficacy (SE), and Digital Media Self-Efficacy (DMSE) to fully understand the factors influencing e-wallet acceptance among Gen Z, using 233 samples to test 16 hypotheses derived from the identified research and knowledge gaps. External Regulation (ER), SE, and DMSE are the determinants of acceptance, according to Structural Equation Model analysis conducted. Mediation analysis reveals that Attitude toward Use (AT) is the full mediator of Perceived Usefulness (PU) and Perceived Ease of Use (PEU). The quintessential outcome of this research is the Model of E-Wallet Acceptance among Gen Z, which is significant for FinTech industries looking to strategically roll out e-wallet initiatives as well as a point of exploration for numerous future academic research and development. © 2023 by the authors.

The Current Regulations in Handling Autopsy of COVID-19 Corpses: A Narrative Review.

The COVID-19 pandemic has affected millions of people around the world either directly or indirectly. Deaths have been attributed to COVID-19 as the underlying cause of death or as a contributing cause of death. It is estimated that millions of excess deaths were associated with the COVID-19 pandemic in 2020 and 2021. The importance of a clinical autopsy on COVID-19 corpses lies in understanding the pathogenesis of the disease better. Moreover, a forensic autopsy may be performed on a COVID-19-infected corpse when indicated for medico-legal purposes. From the autopsy perspective, handling COVID-19-infected corpses requires specific guidelines and safety measures to be followed to limit the transmission of SARS-CoV-2, the causative virus. This is essential as COVID-19 is an emerging infectious disease caused by a newly discovered virus. This review narrates the safety measures that should be followed at different stages of handling COVID-19 corpses, starting from the death scene to burial and funeral. Ethical issues in handling COVID-19 corpses are also briefed in this review. As COVID-19 can be transmitted through infected bodies, it is crucial to wear recommended personal protective equipment, specifically for aerosol-generating procedures. There are specific safety measures to be considered before transporting the body to the mortuary, with particular requirements to be implemented there, such as specific engineering controls, staff training, and autopsy room precautions. After conducting the autopsy, disinfection of the tools and equipment, body bags, transport vehicles, and the autopsy room should be considered.

Obstacles and Solutions of Implementing E-Learning in Palestine: Teachers’ Perspective During the COVID19 Pandemic

The study investigated the obstacles facing the application of e-learning and ways to overcome them in Palestine from the teachers’ point of view during the COVID 19 pandemic. The study adopted the descriptive-analytical approach, and the researchers prepared a questionnaire which was conducted on a sample of (182) teachers from the North Gaza Governorate in Palestine. The results showed that teachers’ consensus on the obstacles of implementing e-learning is 76.55%, while they agreed on the ways of overcoming those obstacles with a percentage of 96.44%. The results also presented that there are no statistically significant differences between the average of the teachers’ attitudes in the North Governorate concerning the obstacles of implementing e-learning due to the gender variable, however, there are statistically significant differences in the averages of teachers’ attitudes due to the variable years of work in favor of teachers with less than 5 years of experience besides those with only11–15 years of experience. Finally, the findings showed statistically significant differences between the average of North Governorate teachers’ attitudes in terms of the e-learning obstacles due to the educational qualification variable. In light of these results, the study recommends the need to develop a plan for education during emergencies, and to equip classrooms with computers connected to the Internet. The study also invites the educational authorities to train school administrations, students and teachers to deal with the e-learning tools. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Hybrid Conceptual Modeling for Simulation: An Ontology Approach during Covid-19

The recent outbreak of Covid-19 caused by SARS-CoV-2 infection that started in Wuhan, China, has quickly spread worldwide. Due to the aggressive number of cases, the entire healthcare system has to respond and make decisions promptly to ensure it does not fail. Researchers have investigated the integration between ontology, algorithms and process modeling to facilitate simulation modeling in emergency departments and have produced a Minimal-Viable Simulation Ontology (MVSimO). However, the 'minimalism' of the ontology has yet to be explored to cover pandemic settings. Responding to this, modelers must redesign services that are Covid-19 safe and better reflect changing realities. This study proposes a novel method that conceptualizes processes within the domain from a Discrete-Event Simulation (DES) perspective and utilizes prediction data from an Agent-Based Simulation (ABS) model to improve the accuracy of existing models. This hybrid approach can be helpful to support local decision making around resources allocation. © 2021 IEEE.

Screen Time Effect on Insomnia, Depression, or Anxiety Symptoms and Physical Activity of School Students During COVID-19 Lockdown in Lebanon: A Cross Sectional Study

Background and ObjectiveaaOur aim is to investigate the impact of COVID-19 on screen time among Lebanese high school students (grades 9–12).MethodsaaAn anonymous online questionnaire was distributed among 510 school students fromdifferent governorates in Lebanon;this included questions regarding screen time, food habits, andphysical activity. Psychological symptoms were assessed using the Generalized Anxiety Disorder-7items and Patient Health Questionnaire-9 items. Effects of screen time on sleep was evaluated usingthe Insomnia Severity Index and Bedtime Procrastination Scale.ResultsaaFemale students reported higher depression (p = 0.018) and anxiety (p = 0.023) thanmale students;however, there was no difference in their sleep. Insomnia, depression, and anxietywere highest among phone users. A screen time of more than 7 hours per day was significantly associatedwith higher depression (67.9%), anxiety (61.6%), insomnia (82.1%), and bedtime procrastination.It also indicated a shift toward a less healthy diet and light exercise.ConclusionsaaSeven hours of screen was found to develop depression and anxiety, exercisingless, eating a less healthy diet, and experiencing disturbed sleep among school adolescents

User Behavioral Intention to Use Online Distance Learning (ODL): The Role of Self-Efficacy and Domain Knowledge

The rise of novel coronavirus 2019 has shifted the roles of education industry. Face-to-face have become a distant memory;students and educators are now heavily relying on the digital communication. Application such as Google Meet, Webex, Webinar, Stream Yard, Zoom, and many more have become the new norm among educators and students. However, the sudden dependency on the digital technologies raises a question on the user intention to use this new digital technology. Therefore, the objective of this study is to determine the role of self-efficacy and domain knowledge towards user behavioral intention to use online distance learning. An instrument was developed by adopting to previous instruments and was analyze using Statistical Package for Social Science and SmartPLS for inferential analysis. Findings shows that the exogenous variables are capable to explained between 47.8% to 68.1% of the endogenous variables. © 2021. All Rights Reserved.

Potential benefits of using hydrogen sulfide, vitamin E and necrostatin-1 to counteract acetaminophen­induced hepatotoxicity in rats.

BACKGROUND: The use of acetaminophen (APAP) is increasing recently, especially with COVID-19 outbreaks. APAP is safe at therapeutic levels, however, an overdose can cause severe liver injury. This study aims to explore possible mechanisms involved in APAP­induced hepatotoxicity and compare different hepatoprotective agents, namely vitamin E, hydrogen sulfide (H2S) and necrostatin-1 (NEC-1). METHODS: Adult male albino rats were divided into groups: Control group, APAP­induced hepatotoxicity group, Vitamin E­treated group, H2S­treated group and NEC-1­treated group. Serum levels for aspartate aminotransferase (AST), alanine aminotransferase (ALT), interleukin-33 (IL-33), tumor necrosis factor alpha (TNF-α), reduced glutathione (GSH) and lipid profile were measured. Histopathological examinations of liver tissue with H(et)E stain and immunohistochemistry for activated caspase-3 were also done. RESULTS: APAP­treated group showed elevated liver transaminases, hyperlipidemia, and deficient liver anti-oxidative response together with disturbed hepatic architecture and increased immune-expression of activated caspase-3 in hepatic tissue. Pretreatment with vitamin E, H2S or NEC-1 reversed the affected parameters. Vitamin E and H2S showed greater improvement when compared to NEC-1. CONCLUSION: Vitamin E, H2S and NEC-1 showed protective effects against APAP-induced hepatotoxicity, thus they may be used as an adjuvant therapy when APAP is indicated for long periods as is the case in COVID-19 patients (Tab. 2, Fig. 2, Ref. 45). Text in PDF www.elis.sk Keywords: acetaminophen, hepatotoxicity, apoptosis, necrostatin-1, vitamin E, H2S.

A Simple Mask Detection Model Based on A Multi-Layer Perception Neural Network

A global health crisis is appeared due to the rapid transmission of the COVID-19 pandemic. According to the World Health Organization (WHO), one of the effective ways to decrease this transmission is wearing masks in crowded places. However, monitoring people by police is a weary and difficult process. Thanks to the improvement in technology and artificial intelligence that make task became easier. In this paper, a simple mask recognition model based on texture and color moments features is proposed. This model is deployed in two stages: first, texture and color moments features from the face image (31 features) are extracted using a hybridization between texture features and color moments features techniques. In order to extract the texture features, the image transformed into Gray Level Co-Occurrence Matrix (GLCM) then 22 statistical metrics were calculated. So as to extract the color moments features, the first, second and third moments have been calculated from each layer of the RGB image. Second, based on the extracted features, the images are classified using a Multi-Layer Perceptron model (MLP). The dataset used in this research consists of 1787 real images with masks and 1918 without masks. The obtained results showed that the accuracy achieved by the proposed model is 90.58% and the time complexity is 6.7379 seconds for training and 0.0023 seconds for prediction. © 2021 IEEE.

Prediction of COVID-19 Cases Using Machine Learning for Effective Public Health Management

COVID-19 is a pandemic that has affected nearly every country in the world. At present, sustainable development in the area of public health is considered vital to securing a promising and prosperous future for humans. However, widespread diseases, such as COVID-19, create numerous challenges to this goal, and some of those challenges are not yet defined. In this study, a Shallow Single-Layer Perceptron Neural Network (SSLPNN) and Gaussian Process Regression (GPR) model were used for the classification and prediction of confirmed COVID-19 cases in five geographically distributed regions of Asia with diverse settings and environmental conditions: namely, China, South Korea, Japan, Saudi Arabia, and Pakistan. Significant environmental and non-environmental features were taken as the input dataset, and confirmed COVID-19 cases were taken as the output dataset. A correlation analysis was done to identify patterns in the cases related to fluctuations in the associated variables. The results of this study established that the population and air quality index of a region had a statistically significant influence on the cases. However, age and the human development index had a negative influence on the cases. The proposed SSLPNN-based classification model performed well when predicting the classes of confirmed cases. During training, the binary classification model was highly accurate, with a Root Mean Square Error (RMSE) of 0.91. Likewise, the results of the regression analysis using the GPR technique with Matern 5/2 were highly accurate (RMSE = 0.95239) when predicting the number of confirmed COVID-19 cases in an area. However, dynamic management has occupied a core place in studies on the sustainable development of public health but dynamic management depends on proactive strategies based on statistically verified approaches, like Artificial Intelligence (AI). In this study, an SSLPNN model has been trained to fit public health associated data into an appropriate class, allowing GPR to predict the number of confirmed COVID-19 cases in an area based on the given values of selected parameters. Therefore, this tool can help authorities in different ecological settings effectively manage COVID-19.