The relationship between social distancing and interpersonal communication through pandemic COVID-19

Throughout the pandemic COVID - 19, interpersonal communication could not be practiced in our daily routine as the COVID-19 virus is easily spread between people within close contact. This research aims to identify the relationship between social distancing and interpersonal communication during pandemic COVID - 19. This study applies the Social Exchange Theory. Quantitative method is applied in this study and data were collected through the distribution of questionnaire to 131 respondents. In addition, the findings showed that there is no significant difference on social distancing between male and female. This study discovered that there is relationship between social distancing and interpersonal communication during pandemic COVID - 19. Hence, this study contributes to the field of communication through the establishment of a more comprehensive variable related to participation in benefit of social distancing and help to develop the Social Exchange Theory. © 2023 Author(s).

Prevalence of temporomandibular disorders among psychoactive substances abusers: A systematic review and meta-analysis.

INTRODUCTION: The COVID-19 pandemic has had a significant impact on substance abuse patterns in recent times. Many people have experienced increased stress, anxiety, and social isolation, which has led to higher rates of substance abuse and addiction. It impacts on the orofacial region, particularly temporomandibular joint (TMJ). This review was undertaken to assess the association between substance abuse and temporomandibular disorders. (TMDs). MATERIALS AND METHODS: The databases of PubMed, Google Scholar, Web of Science and Cochrane were searched for articles based of set PECO criteria. A comprehensive search using keywords of "Psychoactive substances", "Illegal substances", "substance abuse", "narcotics", "temporomandibular joint" and "temporomandibular joint disorders" yielded a total of 1405 articles. Modified Newcastle-Ottawa Scale for observational studies assessed the risk of bias of included studies. RESULTS: Two studies were reviewed. Samples recruited were either from rehabilitation centres or prisoners and fell in the second to fourth decade. A definite association was noted between psychoactive substance and TMDs. Moderate to low risk of bias was noted in all the studies evaluated. CONCLUSION: Further research is needed to better understand the nature of this relationship and the underlying mechanisms involved. It is important for healthcare providers to be aware of this potential association and to screen for substance abuse in patients with TMD symptoms.

Utilizing Deep Learning in Arabic Text Classification Sentiment Analysis of Twitter

The number of social media users has increased. These users share and reshare their ideas in posts and this information can be mined and used by decision-makers in different domains, who analyse and study user opinions on social media networks to improve the quality of products or study specific phenomena. During the COVID-19 pandemic, social media was used to make decisions to limit the spread of the disease using sentiment analysis. Substantial research on this topic has been done;however, there are limited Arabic textual resources on social media. This has resulted in fewer quality sentiment analyses on Arabic texts. This study proposes a model for Arabic sentiment analysis using a Twitter dataset and deep learning models with Arabic word embedding. It uses the supervised deep learning algorithms on the proposed dataset. The dataset contains 51,000 tweets, of which 8,820 are classified as positive, 37,360 neutral, and 8,820 as negative. After cleaning it will contain 31,413. The experiment has been carried out by applying the deep learning models, Convolutional Neural Network and Long Short-Term Memory while comparing the results of different machine learning techniques such as Naive Bayes and Support Vector Machine. The accuracy of the AraBERT model is 0.92% when applying the test on 3,505 tweets.

Food Insecurity and Coping Strategies amongst Undergraduate Students during the COVID-19 pandemic in Malaysia

Introduction: Undergraduate students are at a high risk for food insecurity and knowledge on relevant coping strategies is the key issue in dealing with food insecurity. Therefore, this study is aimed at determining the food insecurity status, coping strategies, and the factors associated with food insecurity and coping strategies during the COVID-19 pandemic. Methods: This cross-sectional study involved 383 undergraduate students from health-related courses at the International Islamic University Malaysia Kuantan campus. The participants were selected by convenience sampling. The instrument used for data collection was a self-administered questionnaire consisting of three parts: socio-demographic background, food insecurity, and coping strategies. The data were analysed as descriptive and inferential analyses, such as Chi-Square, Mann-Whitney, and Kruskal-Wallis. Results: It was found that 21.41% of the participants reported experiencing food insecurity. There were significant associations between parents' income (p<0.001), financial status (p<0.001), academic performance (p = 0.04) and working part-time (p = 0.01) with food insecurity. It was also discovered that there were significant associations between working part-time (p<0.001), faculty of study (p<0.001), academic year (p<0.001), financial status (p<0.001), academic cumulative grade point average (CGPA) (p<0.001) and monthly expenses (p = 0.01) with Malaysian Coping Strategies Instruments (MCSI) score. A significant association between food insecurity and MCSI score (p<0.001) was also found in this study. Conclusion: The prevalence of food insecurity was consistent with previous studies, which is considered high in Malaysia. The findings could assist university authorities to identify the characteristics of the students that are related to food insecurity. © 2023 Authors. All rights reserved.

Design and Development i-AVEN;GER as High-Tech Virtual Remote Teaching and Learning Platform with Experienced Based Learning and Self-regulated Learning Approaches in facilitating STEAM Education

With centuries-old lecture-based teaching methods, ingrained institutional biases, and obsolete classrooms, the slow pace of change in global education and academic institutions is lamentable. COVID-19, on the other hand, has acted as a catalyst for educational institutions worldwide to seek out novel solutions within a short or long timeframe. It is critical for countries to address the situation in such a way that the crisis fosters innovation and inclusion rather than exacerbating learning disparities. Schools are utilising distance learning programmes, educational apps, and platforms such as radio and the internet to reach students who live in remote areas. However, closing the so-called 'digital divide' - the divide between those with access to computers and the internet and those with limited or no access - is a difficult task. We propose in this paper the Interactive Accessible Virtual Education Network - Grand Educational Repository (i-AVEN$\vert$ GER), the world's first comprehensive futuristic hi-tech, comprehensive, and inclusive online structured learning platform with all types of interactivity, namely, educational app and portal. We've discussed the architecture and all of the associated functionalities thus far with recommended implementation. This proposed app and portal will be enhanced to ensure inclusivity for all people without regard for prejudice, as well as the incorporation of cutting-edge technology such as augmented reality, virtual reality, and artificial intelligence. © 2022 IEEE.

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.

Persistent respiratory failure in severe COVID-19 patients - A tertiary centre experience in Kuala Lumpur, Malaysia

Background: The evidence for management of severe COVID-19 with persistent respiratory failure (PRF) after acute treatment is scarce, despite some authors reported a good response to corticosteroid in histological proven secondary organising pneumonia (OP). Objective(s): This study aimed to study the disease course of COVID-19 patients with persistent respiratory failure, and its radiological pattern. Method(s): A single centre retrospective cohort study on severe COVID-19 patients was conducted from January 2021 to June 2021. All radiological imaging and data were retrieved from electronic database. Result(s): Severe COVID-19 pneumonia had a 78% (584/750) survival in our cohort. Among the survival, 48% (279/584) had PRF beyond 14 days of illness and 10% of them required oxygen therapy upon discharge. Eighty-six percent (240/279) of patients with PRF had a HRCT performed. Eighty percent (187/240) of them attended clinic follow up with 81% had a radiological pattern consistent with OP. The mean severity CT score was 10 (SD+/-3). [Jin C et al. Front Public Heal.2020;8] Seventy-eight percent of patients were perceived with WHO functional class of 1-2. Sixty-eight percent of patients (128/187) were given short course of prednisolone during admission with tapering doses. The mean prednisolone dose was 0.69mg/kg/day with a mean duration of 47 days (SD+/-18). Seventy-eight percent (146/187) had a follow up chest x-ray (CXR) at 12+/-8 weeks. Only 6.4% (12/187) of them had abnormal CXR findings whereby two patients were later confirmed to have pulmonary tuberculosis. Conclusion(s): Radiological pattern of OP is common in COVID-19 with PRF. HRCT is a non-invasive tool to assess this entity.

Surgical Protocols before and after COVID-19—A Narrative Review

The COVID-19 epidemic has affected not only people's daily lives but also the working methods of clinicians, surgical procedures, open/minimally invasive procedures, operating room management, patient and healthcare worker safety, education and training. The main objective of this study was to review selected articles and determine the changes in the general surgery protocols/procedures before and after the emergence of the COVID-19 pandemic. The literature was carried out in PubMed-Medline, Cochrane Library, Embase, Scopus and Google Scholar. The terms utilised for the searches were "SARS-CoV-2”, "Surgery”, "COVID-19”, "Surgical protocol”, "Surgical recommendations” and "before and after”. A total of 236 studies were identified, out of which 41 studies were included for data extraction. Significant changes in all the articles were observed with respect to the surgeries done before, during and after the COVID-19 pandemic. Specifically, the number of elective surgeries were considerably fewer in comparison to the pre-pandemic period. Since the COVID-19 pandemic started, hospitals all throughout the world have conducted significantly fewer procedures, particularly elective/non-urgent surgeries.

BIG DATA FRAMEWORK TO EVALUATE AND ANALYSE NOTATIONAL COVID-19 IMMUNIZATION PROGRAMMED (NCIP) IN MALAYSIA: A COMPARATIVE STUDY

Many governments around the world have launched their open government data (OGD) portal to improve the government's transparency by sharing their data with the public such as National Covid-19 Immunization Programmed (NCIP), which has been published at https://github.com/CITF-Malaysia/citf-public. However, increasing the number of datasets, data types, volume and complexity will be raised the integration issues. There-fore, it is essential to evaluate and analyses those huge amounts of these datasets. NCIP provides multiple data sources and datasets. These may raise the Big Data (BD) issues and pose various evaluation and analysis problems to produce valuable information. To generate meaningful linked data to support the purposes of this research study, the relationship between these disparate datasets needs to be identified and construct a comprehensive framework. In order to understand the causes of OGD development of big data, this study involves a detailed examination and comparison of existing theories and actual approaches to handle public sector open data concerns. According to the review, the framework was dominantly adopted over architecture, infrastructures, theoretical and conceptual framework in previous research to examine the revolution of government public accessible data. According to the findings, most existing frameworks do not con-sider the demand for public open data in health such as NCPI. Previous re-search on OGD for health has a lesser number of advanced BD frameworks. In the public sector, there is still a lack of investment and use of Big Data. The findings will aid academics in doing empirical research on the revealed need, as well as offer decision-makers with a better understanding of how to leverage OGD adoption in health by taking relevant actions. © School of Engineering, Taylor's University.

Robust and Fragile Determinants of the Severity of Covid-19 in Developing and Developed Countries: A Comparative Analysis (preprint)

By using the Sala-i-Martin version of extreme bounds analysis, which is based on the cumulative density function, cross-sectional evidence is presented on the robust determinants of the infection and case mortality rates of Covid-19. The results show that, for most part, different factors determine the infection and mortality rates in developed and developing countries. However, common factors are also apparent, including the risk environment, the number of tests per million and the percentage of population over 65. Notwithstanding the possibility that the official data represent a partial reflection of the truth, it is concluded that the results presented in this study provide useful information that may aid decision-making in the fight against the pandemic.

Active transportation in high density residential areas in Lembah Pantai during pandemic COVID 19

Before the pandemic, most studies on active transportation focused on socioeconomic factors, how many cars people had, and how much it cost to own a car. Comfort, safety, and accessibility are the aspects of active transportation that have been talked about the most in previous studies. However, none of them have looked at active transportation as a way to increase the value of residential properties, whether or not the people who live there use active transportation. So, the right neighbourhood, which would have benefited from good planning and infrastructure, couldn't take advantage of the chance. With restrictions on movement and orders to work from home, the question is raised of whether different socioeconomic groups are well represented in active transportation. Even though residential developers and governments are putting more effort into making better amenities and infrastructure for active mobility, there is no evidence that the two are related. Nonetheless, active transportation is utilized to promote an active lifestyle and market properties. This study adds to an original case study evaluation of walkability and active transportation in Lembah Pantai by adding to what we know about active transportation. © 2023 The Authors

Surgical Protocols before and after COVID-19-A Narrative Review.

The COVID-19 epidemic has affected not only people's daily lives but also the working methods of clinicians, surgical procedures, open/minimally invasive procedures, operating room management, patient and healthcare worker safety, education and training. The main objective of this study was to review selected articles and determine the changes in the general surgery protocols/procedures before and after the emergence of the COVID-19 pandemic. The literature was carried out in PubMed-Medline, Cochrane Library, Embase, Scopus and Google Scholar. The terms utilised for the searches were "SARS-CoV-2", "Surgery", "COVID-19", "Surgical protocol", "Surgical recommendations" and "before and after". A total of 236 studies were identified, out of which 41 studies were included for data extraction. Significant changes in all the articles were observed with respect to the surgeries done before, during and after the COVID-19 pandemic. Specifically, the number of elective surgeries were considerably fewer in comparison to the pre-pandemic period. Since the COVID-19 pandemic started, hospitals all throughout the world have conducted significantly fewer procedures, particularly elective/non-urgent surgeries.

Impact of Infections in Patients Receiving Pembrolizumab-Based Therapies for Non-Small Cell Lung Cancer.

Background: Immune checkpoint inhibitor (ICI) therapy has significantly improved outcomes across a range of malignancies. While infections are a well-known contributor to morbidity and mortality amongst patients receiving systemic chemotherapy regimens, little is known about the impact of infections on patients receiving ICI therapy. This study aims to assess incidence, risk factors, and outcomes in patients who develop infections while on pembrolizumab-based therapies for non-small cell lung cancer (NSCLC). Methods: Patients receiving pembrolizumab for stage III/IV NSCLC from 1/1/2017-8/1/2021 across seven hospitals were identified. Incidence and type of infection were characterized. Covariates including baseline demographics, treatment information, treatment toxicities, and immunosuppressive use were collected and compared between infected and non-infected patients. Outcomes included the rate of infections, all-cause hospital admissions, median number of treatment cycles, overall survival (OS), and progression free survival (PFS). Univariable and multivariable analysis with reported odds ratio (OR) and 95% confidence intervals (CI) were utilized to evaluate infection risks. OS and PFS were analyzed by Kaplan−Meier analysis and tested by log-rank test. p-value < 0.05 was considered statistically significant. Results: There were 243 NSCLC patients that met the inclusion criteria. Of these, 111 (45.7%) had one documented infection, and 36 (14.8%) had two or more. Compared to non-infected patients, infected patients had significantly more all-cause Emergency Department (ED) [37 (33.3%) vs. 26 (19.7%), p = 0.016], hospital [87 (78.4%) vs. 53 (40.1%), p < 0.001], and ICU visits [26 (23.4%) vs. 5 (3.8%), p < 0.001], and had poorer median OS (11.53 [95% CI 6.4−16.7] vs. 21.03 [95% CI: 14.7−24.2] months, p = 0.033). On multivariable analysis, anti-infective therapy (OR 3.32, [95% CI: 1.26−8.76], p = 0.015) and ECOG of >1 (OR 5.79, [95% CI 1.72−19.47], p = 0.005) at ICI initiation conferred an increased risk for infections. At last evaluation, 74 (66.7%) infected and 70 (53.0%) non-infected patients died (p = 0.041). Conclusion: Infections occurred in nearly half of patients receiving pembrolizumab-based therapies for NSCLC. Infected patients had frequent hospitalizations, treatment delays, and poorer survival. ECOG status and anti-infective use at ICI initiation conferred a higher infection risk. Infection prevention and control strategies are needed to ameliorate the risk for infections in patients receiving ICIs.

Green Synthesized Zinc Oxide Nanoparticles Based on Cestrum diurnum L. of Potential Antiviral Activity against Human Corona 229-E Virus.

SARS-CoV-2 has caused more than 596 million infections and 6 million fatalities globally. Looking for urgent medication for prevention, treatment, and rehabilitation is obligatory. Plant extracts and green synthesized nanoparticles have numerous biological activities, including antiviral activity. HPLC analysis of C. dirnum L. leaf extract showed that catechin, ferulic acid, chlorogenic acid, and syringic acid were the most major compounds, with concentrations of 1425.16, 1004.68, 207.46, and 158.95 µg/g, respectively. Zinc nanoparticles were biosynthesized using zinc acetate and C. dirnum extract. TEM analysis revealed that the particle size of ZnO-NPs varied between 3.406 and 4.857 nm. An XRD study showed the existence of hexagonal crystals of ZnO-NPs with an average size of 12.11 nm. Both ZnO-NPs (IC50 = 7.01 and CC50 = 145.77) and C. dirnum L. extract (IC50 = 61.15 and CC50 = 145.87 µg/mL) showed antiviral activity against HCOV-229E, but their combination (IC50 = 2.41 and CC50 = 179.23) showed higher activity than both. Molecular docking was used to investigate the affinity of some metabolites against the HCOV-229E main protease. Chlorogenic acid, solanidine, and catchin showed high affinity (-7.13, -6.95, and -6.52), compared to the ligand MDP (-5.66 Kcal/mol). Cestrum dinurum extract and ZnO-NPs combination should be subjected to further studies to be used as an antiviral drug.

Challenges of Online Learning Environment Faced by Undergraduate Medical Students during Covid 19 Pandemic

Objective: This study aimed to define the challenges faced by medical students rotating in the orthopedics department and their suggestions regarding improvement during covid-19 pandemic. Study Design: A mixed method cross sectional study design. Place and Duration of Study: It was conducted on 4th and 5th year MBBS students at Shifa college of Medicine with clerkship rotation in the department of orthopedics from 16th March 2020 to 23rd August 2021. Materials and Methods: Students were enquired about their comfort levels while using the internet and computer for online sessions. Data was collected through an online questionnaire and analyzed using Google forms. Frequencies, percentages, and standard deviations were calculated for qualitative variables. Results: Out of 147 study participants, 64(43.4%) students strongly agreed that they had no difficulty and were extremely comfortable using internet and computer during covid-19 pandemic. Eighty-five (58%) students used online available reading material shared on Google classrooms and what's app groups. While only 23(16%) agreed to concentrate during online sessions. One hundred and eighteen (80%) agreed with a lesser desire to study for online classes as compared to on campus. Major problems faced by the students during the pandemic included very limited patient centered learning, limited hands-on experience, less interactive sessions, problems with internet connections, technology handling and class timing issues due to time zone differences. Conclusion: We conclude that our students faced lot of challenges during Covid-19 pandemic including internet issues, lack of awareness of technology, distractions because of family, siblings and homely environment and lack of conducive learning environment like learning at bedside. Flexible class timings, multiple breaks, recorded lectures and online interaction of real patients can improve online clinical learning. © 2022 by the Author(s).

COVID-19 prediction using machine learning based on the patient's vital signs: A case for Saudi Arabia

The world faces a rapidly spreading of COVID19 globally, for several countries around the world mitigating the consequences and spread of the pandemic remains a top priority. Researchers work to find a smart and rational solution to limit the spread of this epidemic and its repercussions. The goal of this research is to produce an early and accurate COVID-19 prediction, as well as a comparative analysis of the performance of several machine learning (ML) models based on patient vital signs, dataset balancing, and feature selection. The cases dataset was provided by King Fahad Hospital University in Al-Khobar, Saudi Arabia. The current study used the WEKA 3.8.5 and Python programming language (SKLEARN) to decide which method generated the highest level of accuracy while using fewer features. Random forest with grid search (RF with grid search), Artificial Neural Networks (ANN), Support Vector Machine (SVM), Random Forest (RF), J48, XGB Classifier, and XGB Classifier with grid search were the techniques that were compared. The highest level of accuracy obtained with seven features was 84% achieved with the RF using grid search technique, while ANN, SVM, RF, J48, XGB Classifier, and XGB Classifier with grid search obtained 82.85%, 79%, 82.93%, 82.5%,82.21%, and 83.4% accuracy, respectively. © 2022 IEEE.

Effectiveness of Counseling Program to Cope with Psychosocial Effects of Crises (COVID-19 Model)

The current research aims to reveal the effectiveness of a counseling program to relieve the negative psychological and social effects created by the Covid-19 pandemic among a sample of female students at Al-Jouf University, by designing a counseling program based on psychological counseling techniques to mitigate these psychosocial repercussions. To achieve this goal, the researchers prepared a questionnaire on the psychological and social repercussions of the emerging coronavirus. The current research relied on the quasi-experimental approach with a one-group experimental design with pre-post-and, follow-up measurements to reveal the effectiveness of an indicative program which was applied to the experimental sample of (80) female students between the ages of (21.25±3.10). The program consisted of (16) sessions;It includes some methods and techniques, including psychodrama, lecture, dialogue and group discussion. In addition, cognitive techniques such as problem-solving and homework, and behavioral techniques, including modeling, reporting, and relaxation. The data were processed using statistical methods (means and standard deviations-T-test-Wilcoxon test). The results demonstrated the effectiveness of the counseling program in mitigating the psychosocial repercussions of the pandemic. © 2023 NSP Natural Sciences Publishing Cor.

Online Project-Based Learning with Integration of STEAM in Chemistry: Challenges and Opportunities to Create 21st Century Skills

The COVID-19 pandemic has forced Malaysian schools to change their learning model from face-to-face learning to online distance learning. This is what chemistry teachers and students cope with and achieve. However, online teaching and learning commonly did not make students pertain to the required 21st century skills. Having this in mind, a new approach with the STEAM integration in teaching chemistry project-based learning was suggested as one of the potential ways to develop 21st century students’ competencies. Hence, this study discusses the prospects and challenges of STEAM incorporation in online project-based learning aimed at the development of 21st century skills in chemistry classrooms. The paper outlined that, there is a prospect for the chemistry students to advance the ability and competencies of various skills such as hard and soft skills in the course of the online learning process. Skills are expected to be developed for the search for the real problem. It was however revealed that the students’ challenges faced relating to the steps had become a serious issue in this learning approach while establishing connections concerning subjects and general real-world implementation. Since it is impossible to predict when the pandemic will end, this is a challenge and an opportunity, and online chemistry learning can be considered from time to time. © 2022 American Institute of Physics Inc.. All rights reserved.