Telemedicine in the Era of Covid-19: Teleconsultation Architecture Platform

Teleconsultation is a type of medical practice similar to face-to-face consultations, and it allows a health professional to give a consultation remotely through information and communication technologies. In the context of the management of the coronavirus epidemic, the use of teleconsultation practices can facilitate healthcare access and limit the risk of avoidable propagation in medical cabinets. This paper presents the monitoring of international teleconsultation referrals in the era of Covid-19 to facilitate and prevent the suspension of access to care, the most common architecture for teleconsultation, communication technologies and protocols, vital body signals, video transmission, and the conduct of teleconsultation. The aim is to develop a teleconsultation platform to diagnose the patient in real time, transmit data from the remote location to the doctor, and provide a teleconsultation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Comparison of Methods of Assessment and Results of Traditional Osce with Electronic-Osce

Introduction: The onset and rise of COVID-19 and its sudden progression to a worldwide pandemic lead medical and dental institutes to change their way of teaching and conducting assessments to distance learning as compared to the previously applied conventional approaches. Teaching and assessment during this era have changed vastly, earlier it was solely traditional/live Objective Structured Clinical Examination (OSCE) but due to the current circumstances electronic/online OSCE (E-OSCE) method was introduced. In Pakistan also, Pakistan Medical Council (PMC) and the College of Physicians and Surgeons of Pakistan (CPSP) conducted online exams so that the scheduled exams do not get delayed. Aim(s): The main objective of this paper is to measure the reliability of an E-OSCE and to compare it with the traditional OSCE. Methodology: This was a cross-sectional study which got conducted at the Rawal Institute of Health Sciences, Islamabad. Traditional OSCEs and E-OSCEs were conducted with 71 participants including final year students and house officers. Each OSCEs had 10 stations, including one interactive station in traditional OSCE. Students' scores in both the OSCEs were collected and paired t-test was used to compare the mean scores at p<0.05. Result(s): Total number of house officers were 27 and final year students were 44. The scores of 71 participants were collected. The difference between mean scores of house officers' traditional OSCE and E-OSCE was statistically significant (p=0.000). The difference between final year students traditional OSCE and E-OSCE was also statistically significant (p=0.020). Finally, the overall difference between traditional OSCE and E-OSCE was also statistically significant (p=0.000) Practical implication: The main objective of this study was to assess the reliability of an E-OSCE and to compare whether the electronic method of conducting OSCE is more reliable than the traditional method of conducting OSCE. Conclusion(s): Despite limitations and the biases, the results of E-OSCE proved to be better than traditional OSCE. Further research needs to be conducted on E-OSCE to control the factors causing biases and limitations.Copyright © 2023 Lahore Medical And Dental College. All rights reserved.

Evaluation of international logistics and supply chain disruption during the COVID-19 pandemic through scientometric techniques

This study unwraps the detailed literature review and highlights the development in growing research on behalf of the .supply chain in the era of COVID-19. Earlier research on different disasters shows that there is a lack of research on pandemics. Therefore, the present study signifies the multi-perspective literature review on behalf of the supply chain associated with COVID-19. Further, to analyze the literature of this study from a broad perspective, the science mapping approach and the quantitative analysis were conducted on the basis of bibliometric references that were extracted from the web of science. © 2023, IGI Global. All rights reserved.

Gamification in Online Learning: A Case Study among University Students in Malaysia

Online learning has become compulsory when the world was facing the Covid 19 outbreak. Accordingly, students' engagement and participation during online learning have been a major concern among teachers. By adapting the Technology Acceptance Model (TAM), the present study is carried out to examine influential factors towards the intention to use gamification during online classes. With the use of judgmental sampling, 283 usable responses have been gathered from undergraduate students in Malaysia. Results revealed that ‘authentic' positively affects three mediating variables of perceived value (PEU), perceived usefulness (PU) and perceived enjoyment (PE). Additionally, PEU, PU and PE posit positive responses towards the intention to use gamification in online learning. Furthermore, all three mediators also present positive effects in the relationship between authentic and intention to use. Thus, this study affirms the usability of TAM in the online learning context with the extension of authenticity as the external factor and perceived enjoyment as the mediating factor. The results give implications for educators and higher learning institutions to modify their learning outcomes and course content to be more interesting with the usage of online gamification tools. Perhaps, this study gives further insight for future research to apply other external factors, such as knowledge and trust to enrich the study in gamification context © 2023, Asian Journal of University Education.All Rights Reserved.

Intelligent ResNet-18 based Approach for Recognizing and Assessing Arabic Children's Handwriting

Studies tackling handwriting recognition and its applications using deep learning have been promoted by developing advanced machine learning techniques. Yet, a shortage in research that serves the Arabic language and helps develop teaching and learning processes still exists. Moreover, COVID-19 pandemic affected the education system considerably in many countries and yielded an immediate shift to distance learning and extensive use of e-learning tools. An intelligent system was proposed and used in this paper to recognize isolated Arabic handwritten characters. Particularly, pre-trained CNN models were exploited and fine-tuned to meet the requirements of the considered application. Specifically, the designed system automatically supports teaching Arabic letters and evaluating children's writing skills. The Arabic Handwritten Character Dataset (AHCD) was used to train the models built upon ResNet-18 and assess the overall system performance. Furthermore, several models were investigated using various hyper-parameter settings in order to determine the most accurate one. The best model with the highest accuracy rate of 99% was used and integrated into the proposed system to recognize the Arabic alphabets. © 2023 IEEE.

Assessment of Vitamin D Level as a Risk Factor and Illness Severity Indicator in COVID 19 Cases

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-COV2) viruses using angiotensin-converting enzyme 2 (ACE2) receptors, to enter human cells, these receptors are highly expressed in the lung alveolar cells, vascular endothelium, cardiac myocytes, and other cells. Inadequate vitamin D levels in the blood have been linked to a higher risk of COVID-19 severity. Objective: To determine the association between Vitamin D level and severity of COVID-19 infection. Materials and Method: A cross sectional study was conducted at Thumbay Hospital, Ajman, UAE. Enrolled 70 COVID-19 positive hospitalized patients with age group ≥ 18 years old of both genders. Patients taking vitamin D supplements were excluded from the study. The biochemical analysis for the collected blood samples was performed on the automated analyzer and assessed for significance analysis. Result: There is a statistically significant correlation between Vitamin D levels and disease severity (p < 0.05) as determined by Pearson's Chi-square test. Independent t-test shown that there is a statistically significant difference with regards to gender, age groups, and co morbidity (p < 0.05). Pearson's correlation revealed a moderate, positive correlation between Vitamin D levels and the severity of COVID-19 infection, which was statistically significant. Conclusion: Vitamin D levels affect COVID-19 severity, with more severe cases showing vitamin D levels lower than normal when compared to severe cases with sufficient vitamin D levels. Furthermore, blood vitamin D levels are linked to age groups in COVID-19 patients. Vitamin D insufficiency and deficiency, on the other hand, was not linked to a higher risk of death prognosis, and co morbidities. © Sabir SM, Ismail MK, Ibrahim EH, Khan ZA.

Mobile Malaysian Sign Language Application

Due to the Covid-19 plague, children with hearing misfortune have experienced challenges in learning and practicing sign language due to need of educational services and learning assets. The next considerations for creating an educational mobile learning application to help deaf kids learn Malaysian Sign Language (MSL). The investigation was conducted through gatherings based on inquire about and interviews with subject matter experts. Instructors recommend that within the current circumstance, versatile learning application are the foremost reasonable stage for understudies to memorize or as an extra learning strategy in arrange to educate them well. This research was conducted through research-based and interview sessions with subject matter experts and followed the Multimedia Mobile Content Development (MMCD) methodology as it was shown to help accelerate development activities and ensure that the application would work and execute as planned. Once the application is developed, students from Sekolah Kebangsaan Silabukan in Lahad Datu, Sabah, will participate in beta testing. Based on the results of user acceptance tests, the application has received positive reviews from its target users. As such, the project's goals are said to have been achieved. At the conclusion of the study, the advantages, limitations and future work of Pocket Sign Language were also identified. © 2022 IEEE.

MOBILISE-UTHM Resilient Tracker (RITTER) for Resilient Educational Communities in Malaysia During the COVID-19 Pandemic

Coronavirus disease has caused a pandemic across the globe and it is now representing a significant threat to global health. Certainly, managing COVID-19 as compared to other types of disasters comes with a lot of unique challenges to many sectors including the educational sector, especially to higher education institutions (HEI). Since the announcement of movement control orders by the government of Malaysia, most of the Malaysia HEI students, including UTHM, have left their campuses, but the problems wrought by COVID-19 have not. UTHM employees from academic and supporting staff are also worried about their future for not continuously working as usual. The aim of the paper is to propose a disaster decision support system by combining UTHM Tracker and MOBILISE Digital System named MOBILISE-UTHM Resilient Tracker (RITTER) for UTHM students to build resilience during the COVID-19 outbreak and further to provide real-time intelligence for rapid disaster response combining UTHM Tracker and MOBILISE system for UTHM students during the COVID-19 outbreak in UTHM. Copyright © 2021, IGI Global.

COVID-19 MORTALITY CASES IN KUBANG PASU DISTRICT

COVID-19 has rapidly impacted on mortality worldwide. Early identification of COVID-19 cases in community at high risk of death can enhance patient treatment and resource allocation. The goal of this study is to identify the characteristics of COVID-19 mortality cases in Kubang Pasu districts in 2021. Data on mortality cases in the year 2021 in Kubang Pasu district were collected, extracted and analyzed. There are 210 (1.9%) mortality cases had been recorded in 2021 due to COVID-19 infection form 11019 COVID-19 cases in Kubang Pasu district. The mortality cases consist of 108(51%) female and 102(49%) male. The highest mortality cases involved the age group of more than 70 years old with 73 (34.8%) cases. The highest race was Malay 193(91.9%), followed by non-Malaysian(2.9%), Chinese 4(1.9%), Siamese 4(1.9%) and Indian 3(1.4%) respectively. Most of the mortality cases are unvaccinated 153 (72.9%). The most coomon cause of death is due to COVID-19 pneumonia with 205 (97.5%) cases. Majority of the cases were screen through symptomatic screening and close contact screening 86 (40.9%) cases and 52 (24.8%) respectively. Among the mortality cases, there are 22(10.5%) brought-in-death cases which 19 (86%) cases are Malay. Most of the brought-in-death cases are unvaccinated, 19 (86%) cases, incomplete vaccine 1 (5%) case and 2 (9%) cases completed vaccine. The highest number of mortality cases occur among those with age more than 70. It involved mostly among Malay race and they were unvaccinated. Lung complication is the main cause of death since most of the mortality cases passed away due to pneumonia. This high number of mortality and BID cases might be attributed to poor health-seeking behaviour among the Kubang Pasu population with COVID-19. Promotion activities about COVID-19 and vaccine should be strengthened further to improve the knowledge and actions towards COVID-19 in community. © 2022, Malaysian Journal of Public Health Medicine. All Rights Reserved.

Zero-Inflated Time Series Model for Covid-19 Deaths in Kelantan Malaysia

The development of zero-inflated time series models is well known to account for excessive number of zeros and overdispersion in discrete count time series data. By using Zero-inflated models, we analyzed the daily count of COVID-19 deaths occurrence in Kelantan with excess zeros. Considering factors such as COVID-19 deaths in neighboring state and lag of 1 to 7 days of COVID-19 death in Kelantan, the Zero-Inflated models (Zero-Inflated Poisson (ZIP) and the Zero-Inflated Negative Binomial (ZINB)) were employed to predict the COVID-19 deaths in Kelantan. The ZIP and ZINB were compared with the basic Poisson and Negative Binomial models to find the significant contributing factors from the model. The final results show that the best model was the ZINB model with lag of 1,2,5 and lag of 6 days of Kelantan COVID-19 death, lag of 1-day COVID-19 deaths in neighboring State of Terengganu and Perak significantly influenced the COVID-19 deaths occurrence in Kelantan. The model gives the smallest value of AIC and BIC compared to the basic Poisson and Negative Binomial model. This indicate that the Zero Inflated model predict the excess zeros in the COVID-19 deaths occurrence well compared to the basic count model. Hence, the fitted models for COVID-19 deaths served as a novel understanding on the disease transmission and dissemination in a particular area. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Assessing Foundation Students' Acceptance in Using Video Conferencing Technologies (VCTs) as Online Learning Platforms during the Pandemic

The COVID-19 pandemic has significantly affected Higher Education Institutions (HEIs) in Malaysian education system. Due to this, the HEIs have implemented online learning to be replaced with physical classrooms to ensure that all students able to reach their learning potentials. As such, video conferencing technologies (VCTs) have been employed nationwide for effective learning activities. Previous research have shown that teaching and learning using VCTs are beneficial for online learning, however, not many studies focused on the student's acceptance of VCTs during unforeseen situations. This study intends to overcome this research gap by investigating the factors influencing the foundation students' acceptance of VCTs during the outbreak. Therefore, the facilitating conditions and computer self-efficacy factors are integrated into the Technology Acceptance Model (TAM) for analysis. For this purpose, the PLS-SEM was used to analyze the data collected from 231 participants of selected higher education institutions in Malaysia. The finding revealed that ‘attitude towards use' and ‘intention to use' VCTS have a positive relationship with the actual use of VCTs. Furthermore, the result indicated that facilitating condition has significantly impacted the ‘perceived ease of use' of the VCTs. However, ‘computer self-efficacy' has no significant impact on the ‘perceived usefulness' of the VCTs. It is also learned that using VCTs is acceptable for remote and online learning mode, particularly amid the current COVID-19 pandemic. The outcomes of this study are able to improve the existing knowledge on the student's acceptance of VCTs and provide useful insights into the curriculum designated for the HEIs. Hence, it can be concluded that our findings validated the model used in this study and offered valuable guidelines in developing online learning approaches that promote learning through varied platforms. © 2023,International Journal of Emerging Technologies in Learning. All Rights Reserved.

Using a web-based and stand-alone oscilloscope for physics experiment during Covid-19 pandemic

Teaching alternating currents, ac or sound waves, is incomplete without an introduction to the oscilloscope. An oscilloscope is a tool that graphically displays electrical signals and shows their time dependence. However, due to the pandemic, triggered by the SARS-CoV-2 virus, many students do not have the opportunity to master the use of an oscilloscope. Face-to-face teaching activity has been interrupted in both schools and higher institutions. The sudden change to online teaching created problems among educators, especially for laboratory activities. The central issue is creating laboratory activities without going into the labs for the students to acquire the required skills, especially the basics of how to operate an oscilloscope. In order to create an opportunity and engaging environment, we suggested the use of the ‘web-based and stand-alone oscilloscope'. The software consists of a low-frequency (signal) generator (LFG), a direct current power supply, and an oscilloscope. The LFG is capable of producing several types of signal and the software is designed to aid the undergraduate engineering and physics students in learning the operation and functions of a digital storage oscilloscope. It can be used as an alternative to face-to-face laboratory activity for physics experiments. It is free and easy to use. The experiments enable students to develop the experimental and measurement skills related to signal generators and oscilloscopes. Hence it opens the opportunity of ‘doing' virtual physics investigations individually at home. © 2022 IOP Publishing Ltd.

Drug Repurposing for SARS-COV-2 Using Molecular Docking

Drug repurposing is an unconventional approach that is used to investigate new therapeutic aids of existing and shelved drugs. Recent advancement in technologies and the availability of the data of genomics, proteomics, transcriptomics, etc., and with the accessibility of large and reliable database resources, there are abundantly of opportunities to discover drugs by drug repurposing in an efficient manner. The recent pandemic of SARS-COV-2, that caused the death of 6,245,750 human beings to date, has tremendously increase the exceptional usage of bioinformatics tools in interpreting the molecular characterizations of viral infections. In this paper, we have employed various bioinformatics tools such as AutoDock-Vina, PyMol etc. We have found a leading drug candidate Cepharanthine (CEP) that has shown better results and effectiveness than recently used antiviral drug candidates such as Favipiravir, IDX184, Remedesivir, Ribavirin and etc. This paper has analyzed CEP's potential therapeutic importance as a drug of choice in managing COVID-19 cases. It is anticipated that proposed study would be beneficial for researchers and medical practitioners in handling SARS-CoV-2 and its variant related diseases. © 2022 IEEE.

Investigating natural ventilation performance on apartment units in Jakarta based on field test measurements

The COVID-19 pandemic has changed the way of living of many people across the planet. In the beginning of the pandemic, when the strict lockdown was implemented, numbers of individual were encouraged to work from home. In the city living, high rise living was apparent and became a global phenomenon. This paper evaluates natural ventilation performances of existing apartment units in Jakarta, Indonesia by measuring the indoor temperature, indoor airflow and relative humidity. This research studied three different apartment units in Jakarta in the form of single-sided ventilation or cross ventilation. This study conducted by field test measurement on three different apartment units across Jakarta with various natural ventilation strategy and room volume. Statistical analysis was carried out to investigate the relationship and influence between the results of field test measurement and external weather data collected from ERA5. The results of the analysis suggested that external weather influence the indoor air condition, especially indoor temperature where significant influence was apparent. Furthermore, the field test data measurement in this paper contributed to validation study in predicting indoor airflow. © 2022, University of Malaya. All rights reserved.

Coronaviruses of the veterinary and socio-economic importance: classification, pathogenicity, transmission, and evolution of the coronaviruses

Most of the coronaviruses are known because they are pathogens of veterinary and economic importance or of social importance. The current knowledge on the origin, diversity, evolution of coronaviruses, as well as treatment and prevention strategies, and their impact on animal industries are discussed in this paper. The contribution factors for the outbreak of pathogenic coronaviruses and the potential of spill over of zoonotic coronaviruses to humans are also highlighted in this review paper.

Student Acceptance Towards Online Learning Management System based on UTAUT2 Model

Recently, education has changed from physical learning to online and hybrid learning. Furthermore, the outbreak of COVID-19 makes them more significant. An online learning management system (LMS) is one of the most prevalent approaches to online and distance learning. The acceptance of the students towards the LMS is significant and it can give either bad or good responses to ensure the success of LMS. However, the Universiti Tun Hussein Onn Malaysia (UTHM) has not yet implemented any study to examine their LMS. The Unified Theory of Acceptance and Usage of Technology (UTAUT2) model is used in this study to investigate students' Behavioral Intention and Use Behavior when using the LMS in UTHM. This study also introduces a new construct in UTAUT2 named Online Learning Value. 376 respondents took part in this survey. Descriptive Statistics, Reliability Analysis, Pearson Correlation Coefficient, and Multiple Linear Regression analysis were all used to analyze survey data. The outcome of this research is Performance Expectancy (β=0.129, p=0.014), Hedonic Motivation (β=0.221, p=0.000), Online Learning Value (β=0.109, p=0.036) and Habit (β=0.513, p=0.000) has influence on students' intention to use LMS. Besides that, Facilitating Conditions (β=0.481, p=0.000) are the most important factors in students' use behavior toward the LMS followed by Habit (β=0.343, p=0.000) and Behavioral Intention (β=0.239, p=0.000). By utilizing the UTAUT2 model, the constructs of technology acceptance related to students' adoption of LMS have been identified and may become a reference to the stakeholders for future enhancement. © 2022,International Journal of Advanced Computer Science and Applications. All Rights Reserved.

In silico study to find a potent inhibitor, Vilazodone, to cure COVID-19 using molecular docking

The pandemic caused by the coronavirus SARS-COVID-2 has had devastating impact on the world. It has caused a significant number of deaths across the world. Fast spread and lack of vaccine prompted academia to adopt new, fast and reliable methodologies to design new drugs. A combined approach of direct drug design and indirect drug design has been used for molecular docking. In the study, we found a compound, Vilazodone, with a binding energy of -8.40 kcal/mol. The druglikeness properties of this compound are investigated through SWISS ADMET analysis. In this in-silico study, we confirmed this compound is a potential drug candidate against SARS-CoV-2.However, in-vitro and in-vivo studies are required to prove its efficacy. © 2022 IEEE.

Post-Splenectomy Overwhelming Sepsis Syndrome in a 36-Year-Old Woman 26 Years after Splenectomy

INTRODUCTION: Post splenectomy sepsis syndrome usually occurs within the first 3 years of splenectomy however can occur several years later. Given the high mortality and morbidity, early diagnosis and prevention is key in reducing the deleterious clinical outcomes. METHOD(S): We report a 36 year old Caucasian female with a history of ITP treated with splenectomy 26 years prior, allergic to vancomycin and penicillin, who presented with confusion after 2 days of preceding flu like symptoms. On presentation, the patient was in septic shock with purpura fulminans requiring vasopressors. She subsequently developed hypoxic respiratory failure requiring emergent intubation. Initial labs revealed thrombocytopenia & lactic acidosis of 12.9 mmol/L. Daptomycin and clindamycin were started for possible toxic shock syndrome and azithromycin and cefepime for possible pneumonia. The patient was admitted to the MICU where she developed disseminated intravascular coagulation requiring multiple blood transfusions and platelets after blood smear ruled out TTP. Blood cultures grew Streptococcus Pneumoniae and sputum panel revealed coronavirus, adenovirus, haemophilus influenzae and staphylococcus aureus. Patient's course was further complicated by acute kidney injury requiring continuous renal replacement therapy. Within 48 hours of admission, the patient deteriorated further with worsening acidosis, hyperkalemia and lower limb ischemia and subsequently expired despite resuscitative efforts. RESULT(S): Overwhelming post splenectomy infection (OPSI) is most commonly due to strep pneumoniae, neisseria meningitidis and haemophilus influenzae and is characterized by flu-like symptoms succeeded by fulminant sepsis occurring within 24-48 hours. It has a 0.1-0.5% prevalence and a 50%-70% mortality rate. The incidence is highest within the first 3 years of splenectomy, however persons remain at risk throughout their lifetime, with cases reported as late as 65 years. Though no clear diagnostic criteria exists, clinicians must have a high index of suspicion from history of splenectomy and presenting signs & symptoms. CONCLUSION(S): Given the high mortality associated with OPSI even 26 years post splenectomy, OPSI action plan and early symptom recognition are paramount in reducing the risk of clinical decline while seeking medical attention.

COVID-19 Diagnosis on Chest Radiograph Using Artificial Intelligence.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has disrupted the world since 2019, causing significant morbidity and mortality in developed and developing countries alike. Although substantial resources have been diverted to developing diagnostic, preventative, and treatment measures, disparities in the availability and efficacy of these tools vary across countries. We seek to assess the ability of commercial artificial intelligence (AI) technology to diagnose COVID-19 by analyzing chest radiographs. MATERIALS AND METHODS: Chest radiographs taken from symptomatic patients within two days of polymerase chain reaction (PCR) tests were assessed for COVID-19 infection by board-certified radiologists and commercially available AI software. Sixty patients with negative and 60 with positive COVID reverse transcription-polymerase chain reaction (RT-PCR) tests were chosen. Results were compared against results of the PCR test for accuracy and statistically analyzed by receiver operating characteristic (ROC) curves along with area under the curve (AUC) values. RESULTS: A total of 120 chest radiographs (60 positive and 60 negative RT-PCR tests) radiographs were analyzed. The AI software performed significantly better than chance (p = 0.001) and did not differ significantly from the radiologist ROC curve (p = 0.78). CONCLUSION: Commercially available AI software was not inferior compared with trained radiologists in accurately identifying COVID-19 cases by analyzing radiographs. While RT-PCR testing remains the standard, current advances in AI help correctly analyze chest radiographs to diagnose COVID-19 infection.