The role of IL-6, IL-8 and TNF-α in COVID-19 patients in Karbala Governorate

There are several viruses considered to be ecologically problematic, including COVID-19.The samples were collected from persons with middle and severe cases of patients with COVID-19 as well as other samples from patients who were appeared symptoms or recovered from infection of coronavirus, where the number of cases 100 and measured levels of cytokines in the serum of patients as IL-6, IL-8, and tumor necrosis factor-alpha (TNF-α), estimated by immune assay called enzyme-linked immunosorbent assay (ELISA). Where serum level of TNF-α in persons not illustrated a significant difference in all groups, while the interleukin 6 in severe and middle case groups of COVID-19 was high significantly compared with normal and recovered cases groups of COVID-19. Also, the concentration of interleukin 8 was low in the serum of patients infected by a coronavirus in the cases of severe and middle respectively compared with normal cases and recovered cases that healing from coronavirus infection which maybe gives a prediction for disease COVID-19, also showing different concentrations of cytokines in cases of the COVID-19 group than the normal group that may belong to several mechanisms of immunoregulatory detected in cases of COVID-19 pathogenesis. © The Authors, published by EDP Sciences, 2023.

Artificial Bee Colony for Logic Mining in Credit Scoring

During the SARS-CoV-2 (Covid-19) pandemic, credit applications skyrocketed unimaginably. Thus, creditors or financial entities were burdened with information overload to ensure they provided the proper credit to the right person. The existing methods employed by financial entities were prone to overfitting and did not provide any information regarding the behavior of the creditor. However, the outcome did not consider the attribute of the creditor that led to the default outcome. In this paper, a swarm intelligence-based algorithm named Artificial Bee Colony has been implemented to optimize the learning phase of the Hopfield Neural Network with 2 Satisfiability-based Reverse Analysis Methods. The proposed hybrid model will be used to extract logical information in the credit data with more than 80% accuracy compared to the existing method. The effectiveness of the proposed hybrid model was evaluated and showed superior results compared to other models.

Measuring Evidence Affecting the Financial Stability of Airport Operations in Malaysia

The indicator of bankruptcy exposure for airport operations in Malaysia is calculated by using Altman's Z'-score. Financial and non-financial attributes related to the bankruptcy exposure show multicollinearity, and the redundant information was identified and removed. The common period for the variables is from 1999-2021, which includes the period of COVID-19 pandemic. Models with a combination of financial and non-financial attributes further reduce the deviation between the estimated standard deviation of the residuals and the marginal standard deviation of the bankruptcy risk in comparison to models without the combination. The best model provides improvements in terms of the mean of the absolute errors (MAE), mean of absolute percentage errors (MAPE), and mean absolute scaled errors (MASE). Furthermore, all determinants in the best model are statistically significant. We suggest that the opportunity for optimisation, including total movements of passenger, cargo and mail, could reduce the company's bankruptcy exposure. Findings indicate that reducing the financial leverage could improve the financial distress risk while liquidity, net operating margin, and asset turnover are positively contributed to the financial stability of the largest airport operator in Malaysia. If the marginal average of annual exposures to bankruptcy of 4.04% continues linearly into the future, the company is expected to transition from being financially stable to experiencing financial distress in 2030. © 2022 IEEE.

Logistic Regression Model for Measuring Perception on Open and Distance Learning (ODL) during COVID-19 Pandemic based on Impeding Factors among Students

Authorities have suggested emergency remote instruction to guarantee that students are not left idle during the pandemic due to the sudden closing of educational facilities. Then for the time being, traditional methods (face-to-face) have been replaced by Open and Distance Learning (ODL). Face-to-face learning was preferred by the majority of students over online learning since students were not able transit to online learning and lacked inspiration. Hence, this study focuses on perception towards ODL during COVID-19 among statistics' students at FSKM UiTM Shah Alam based on some impeding factors such as social issue, lecturer issue, accessibility issue, academic issue, generic skills and learner intentions. The aim of this study is to investigate the perception of statistics' students on ODL based on impeding factors and to identify the significant impeding factors effect on statistics students' perception on ODL. There are 160 observations that are used in this study. The methods that are being used in this study are descriptive analysis and logistic regression. Overall, from the result obtained, students' perception on ODL are approximately to agree for social issue, academic issue and learner intentions variables. Meanwhile, the significance impeding factors in this study are social issue and learner intentions. This study may help higher education institution to improve and make a better strategy to improve the existing teaching method that have been applied by all lecturers. © 2022 IEEE.

Artificial Bee Colony for Logic Mining in Credit Scoring

During the SARS-CoV-2 (Covid-19) pandemic, credit applications skyrocketed unimaginably. Thus, creditors or financial entities were burdened with information overload to ensure they provided the proper credit to the right person. The existing methods employed by financial entities were prone to overfitting and did not provide any information regarding the behavior of the creditor. However, the outcome did not consider the attribute of the creditor that led to the default outcome. In this paper, a swarm intelligence-based algorithm named Artificial Bee Colony has been implemented to optimize the learning phase of the Hopfield Neural Network with 2 Satisfiability-based Reverse Analysis Methods. The proposed hybrid model will be used to extract logical information in the credit data with more than 80% accuracy compared to the existing method. The effectiveness of the proposed hybrid model was evaluated and showed superior results compared to other models. © 2022 Malaysian Journal of Fundamental and Applied Sciences.

Impact Assessment of COVID-19 Severity on Environment, Economy and Society towards Affecting Sustainable Development Goals

The COVID-19 pandemic has affected every sector in the world, ranging from the education sector to the health sector, administration sector, economic sector and others in different ways. Multiple kinds of research have been performed by research centres, education institutions and research groups to determine the extent of how huge of a threat the COVID-19 pandemic poses to each sector. However, detailed analysis and assessment of its impact on every single target within the 17 Sustainable Development Goals (SDGs) have not been discussed so far. We report an assessment of the impact of COVID-19 effect towards achieving the United Nations SDGs. In assessing the pandemic effects, an expert elicitation model is used to show how the COVID-19 severity affects the positive and negative impact on the 169 targets of 17 SDGs under environment, society and economy groups. We found that the COVID-19 pandemic has a low positive impact in achieving only 34 (20.12%) targets across the available SDGs and a high negative impact of 54 targets (31.95%) in which the most affected group is the economy and society. The environmental group is affected less;rather it helps to achieve a few targets within this group. Our elicitation model indicates that the assessment process effectively measures the mapping of the COVID-19 pandemic impact on achieving the SDGs. This assessment identifies that the COVID-19 pandemic acts mostly as a threat in enabling the targets of the SDGs.

COVID-19 in Singapore and Malaysia: Rising to the Challenges of Orthopaedic Practice in an Evolving Pandemic

@#With the increasing number of COVID-19 cases and related deaths worldwide, we decided to share the development of this condition in Singapore and Malaysia. First few cases were diagnosed in the two countries at the end of January 2020, and the numbers have surged to thousands by end of March 2020. We will focus on strategies adopted by the government and also the Orthopaedic community of the two countries up till the beginning of April 2020. We hope that by sharing of relevant information and knowledge on how we are managing the COVID-19 condition, we can help other communities, and health care workers to more effectively overcome this pandemic.

Document and Event Record Management System: A Prototype

Good record-keeping makes better reports and contributes to exceptional planning for the future. During the Covid-19 pandemic, most offices were operating from home. Having such a system would help to keep track of important documents and events. A small office may find such a system a lifesaver where it can provide a CRUD (create-read-update-delete) function, generate reports, serve as activity logs, and provide feedback. The prototype was developed as a web-based system, combining document and event management records. PHP and MySQL databases were the backbones of the system. A case study consisting of the ABC Department was used to illustrate the usage of the prototype. The prototype could be customized to client requirements. © 2022 IEEE.

Minimising operational costs during COVID-19 pandemic: Leveraging crowdsourcing business model for enhancing SMEs' performance

Uncertain business environment particularly during COVID 19 outbreak forced many enterprises including Small and Medium Enterprises (SMEs) need to change the business model. This rampant situation creates 'rubbing salt into the wound' for many enterprises in order to survival and sustain in the market. Enterprises should alter the business strategy from the traditional way of running the business to the new phenomenon of business strategy i.e. crowdsourcing practices. In view of the above, the aim of this study is to investigate how the SMEs could minimise the operating costs in order to boost business performance mainly COVID 19 pandemic. Specifically, the objectives of this study are to examine the impacts of crowdsourcing practices, crowdsourcing cost reduction towards business performance for SMEs in Malaysia. The findings revealed that, the crowdsourcing practices and crowdsourcing cost reduction positively significantly to the SMEs in Malaysia in order to enhance the business performance. This study also highlights practical and theoretical contributions, significant of study;limitations and future study as well as conclude the entire study. © 2021 Author(s).

The handling of safety concerns among anaesthetists when restarting full surgical lists during the COVID-19 pandemic.

Around June 2020, many institutions restarted full operating schedules to clear the backlog of postponed surgeries because of the first wave in the COVID-19 pandemic. In an online survey distributed among anaesthestists in Asian countries at that time, most of them described their safety concerns and recommendations related to the supply of personal protective equipment and its usage. The second concern was related to pre-operative screening for all elective surgical cases and its related issues. The new norm in practice was found to be non-standardized and involved untested devices or workflow that have since been phased out with growing evidence. Subsequent months after reinstating full elective surgeries tested the ability of many hospitals in handling the workload of non-COVID surgical cases together with rising COVID-19 positive cases in the second and third waves when stay-at-home orders eased.

Undergraduates’ learning habits amid covid-19 pandemic: A pilot study

The spread of Coronavirus disease (COVID-19) over the world has prompted a new wave of online learning in higher education. Regardless of the preparation for both educators and students, the online teaching and learning proceed to ensure a running institution. This sudden change of environment has caused a significant interruption in students’ learning. Thus, this study investigated the effects of COVID-19 pandemic on students’ performance based on their learning habits. A quantitative method was used to collect data from undergraduates with different sociodemographic and psychological attributes. The empirical evidence of this study could be utilized to develop a prediction model that is able to predict the students’ performance and a set of relevant features that contribute to student’s performance. The results also could be a foundation for higher education departments to produce more sustainable regulations and policies that may improve students’ self-learning and self-efficacy. © 2020, Institute of Advanced Scientific Research, Inc.. All rights reserved.

COVID-19 in Singapore and Malaysia: Rising to the Challenges of Orthopaedic Practice in an Evolving Pandemic.

With the increasing number of COVID-19 cases and related deaths worldwide, we decided to share the development of this condition in Singapore and Malaysia. First few cases were diagnosed in the two countries at the end of January 2020, and the numbers have surged to thousands by end of March 2020. We will focus on strategies adopted by the government and also the Orthopaedic community of the two countries up till the beginning of April 2020. We hope that by sharing of relevant information and knowledge on how we are managing the COVID-19 condition, we can help other communities, and health care workers to more effectively overcome this pandemic.