Utilizing Sentiment Analysis to Enhance the Quality of Online Learning

The COVID-19 pandemic spread worldwide in the year 2020 and became a global health emergency. This pandemic has brought awareness that social distancing and quarantine are ideal ways to protect people in the community from infection. Therefore, Saudi Arabia used online learning instead of stopping it completely to continue the education process. This paper proposes to use machine-learning algorithms for Arabic sentiment analysis to find out what students and teaching staff thought about online learning during the COVID-19 outbreak. During the pandemic, a real-world data set was gathered that included about 100,000 Arabic tweets related to online learning. The overall goal is to use sentiment analysis of tweets to find patterns that help improve the quality of online learning. The data set that was collected has three classes: 'Positive,' 'Negative,' and 'Neutral.' Crossvalidation is used to run the experiments ten times. Precision, recall, and F-measure was used to measure how well the algorithms worked. Classifiers, such as Support Vector Machines, K nearest neighbors, and Random Forest, were used to classify the dataset. Moreover, a detailed analysis and comparison of the results are made in this research. Finally, a visual examination of the data is made using the word cloud technique. © 2022 IEEE.

Ambient Fine Particulate Matter and COVID-19 in India

We examine the correlation between COVID-19 case activity and air pollution in two cities of Delhi and Mumbai in India. Data regarding air quality index (AQI) of PM2.5 and PM10 from Delhi and Mumbai were collected between July and November 2020. Within the same time period, confirmed cases and daily deaths due to COVID-19 in these two cities were also recorded. AQI levels in Delhi were worst in November (PM2.5: 446 ± 144.6 µg/m3;PM10: 318 ± 131.7 µg/m3) and were significantly higher as compared to Mumbai (PM2.5: 130 ± 41.2 µg/m3;PM10: 86 ± 21.2 µg/m3). This correlated with greater number of cases and higher mortality in Delhi (cases: 6243;deaths: 85) relative to Mumbai (cases: 1526;deaths: 35) during the same time period. This observational study shows that air pollution is associated with poor outcomes in patients with COVID-19. There is an urgent unmet need for appropriate public health measures to decrease air pollution along with strict policy change. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Public Service Advertisements and Healthcare Attitudinal Changes in Developing Countries: Pakistanis’ Perspectives

Still, little is known about the role and contribution of media ads in healthcare communication and awareness during the Covid-19 outbreak. This study examines the role of public service ads in spreading healthcare awareness in Pakistan. Based on a quantitative approach through a sample of n = 200 participants from the Sahiwal city, the study proposed a self-designed model that used the Structural Equation Modelling to affirm the proposed relationship between the variables. The study found that media ads were not only disseminating the Covid-19 awareness but also changing the public attitudes toward taking precautionary measures to halt the transmission of the disease. Hence, the findings indicated that public service advertisements have substantial, positive impacts on people’s perceptions and actions regarding the current pandemic. The results discussed media context and healthcare awareness to highlight further the role of such media in bringing positive behavioral changes. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The use of advanced spectral imaging to reveal nanoparticle identity in biological samples.

Nanoparticles (NPs) have been used in drug delivery therapies, medical diagnostic strategies, and as current Covid-19 vaccine carriers. Many microscope-based imaging systems have been introduced to facilitate detection and visualization of NPs. Unfortunately, none can differentiate the core and the shell of NPs. Spectral imaging has been used to distinguish a drug molecule and its metabolite. We have recently integrated this technology to a resolution of 9 nm by using artificial intelligence-driven analyses. Such a resolution allowed us to collect many robust datapoints for each pixel of an image. Our analyses could recognize 45 spectral points within a pixel to detect unlabeled Ag-NPs and Au-NPs in single live cells and tissues (liver, heart, spleen and kidneys). The improved resolution and software provided a more specific fingerprinting for each single molecule, allowing simultaneous analyses of 990 complex interactions from the 45 points for each molecule within a pixel of an image. This in turn allowed us to detect surface-functionalization of Ag-NPs to distinguish the core from the shell of Ag-NPs for the first time. Our studies were validated using various laborious and time-consuming conventional techniques. We propose that spectral imaging has tremendous potential to study NP localization and identification in biological samples at a high temporal and spatial resolution, based primarily on spectral identity information.

An Improved Marine Predators Algorithm With Fuzzy Entropy for Multi-Level Thresholding: Real World Example of COVID-19 CT Image Segmentation.

Medical imaging techniques play a critical role in diagnosing diseases and patient healthcare. They help in treatment, diagnosis, and early detection. Image segmentation is one of the most important steps in processing medical images, and it has been widely used in many applications. Multi-level thresholding (MLT) is considered as one of the simplest and most effective image segmentation techniques. Traditional approaches apply histogram methods; however, these methods face some challenges. In recent years, swarm intelligence methods have been leveraged in MLT, which is considered an NP-hard problem. One of the main drawbacks of the SI methods is when searching for optimum solutions, and some may get stuck in local optima. This because during the run of SI methods, they create random sequences among different operators. In this study, we propose a hybrid SI based approach that combines the features of two SI methods, marine predators algorithm (MPA) and moth-?ame optimization (MFO). The proposed approach is called MPAMFO, in which, the MFO is utilized as a local search method for MPA to avoid trapping at local optima. The MPAMFO is proposed as an MLT approach for image segmentation, which showed excellent performance in all experiments. To test the performance of MPAMFO, two experiments were carried out. The first one is to segment ten natural gray-scale images. The second experiment tested the MPAMFO for a real-world application, such as CT images of COVID-19. Therefore, thirteen CT images were used to test the performance of MPAMFO. Furthermore, extensive comparisons with several SI methods have been implemented to examine the quality and the performance of the MPAMFO. Overall experimental results confirm that the MPAMFO is an efficient MLT approach that approved its superiority over other existing methods.

Sparse Crowd Flow Analysis of Tawaaf of Kaaba During the COVID-19 Pandemic

The advent of the COVID-19 pandemic has adversely affected the entire world and has put forth high demand for techniques that remotely manage crowd-related tasks. Video surveillance and crowd management using video analysis techniques have significantly impacted today's research, and numerous applications have been developed in this domain. This research proposed an anomaly detection technique applied to Umrah videos in Kaaba during the COVID-19 pandemic through sparse crowd analysis. Managing the Kaaba rituals is crucial since the crowd gathers from around the world and requires proper analysis during these days of the pandemic. The Umrah videos are analyzed, and a system is devised that can track and monitor the crowd flow in Kaaba. The crowd in these videos is sparse due to the pandemic, and we have developed a technique to track the maximum crowd flow and detect any object (person) moving in the direction unlikely of the major flow. We have detected abnormal movement by creating the histograms for the vertical and horizontal flows and applying thresholds to identify the non-majority flow. Our algorithm aims to analyze the crowd through video surveillance and timely detect any abnormal activity to maintain a smooth crowd flow in Kaaba during the pandemic. © 2022 Tech Science Press. All rights reserved.

Purulent pericarditis can be near fatal

A previously healthy 27 years-old male presented with 2 weeks of substernal chest pain, progressive dyspnea, palpitations, dizziness, and(&) fever. On exam, he had tachypnea & tachycardia, was hypotensive with an elevated JVP & muffled heart sounds. Labs showed elevated WBC, CRP, lactate & high sensitive troponin. Negative for COVID-19, flu. EKG showed sinus tachycardia. CT showed large pericardial effusion with gas in the pericardial space. Echo (Figure 1) revealed large pericardial effusion with tamponade. Emergent pericardiocentesis was performed draining a liter of straw-colored thick fluid (fluid: serum LDH >3) (Figure 2). Cultures grew Strep. Anginosus & Propionibacterium acnes. Extensive infectious & immunological workup returned negative. He had initially improved on broad-spectrum antibiotics however declined clinically on day 5. Repeat CT (Figures 3 & 4) showed recurrent pericardial effusion & mediastinal abscess with trace extravasation of contrast from the esophagus to posterior mediastinum. We present a case of esophageal perforation leading to Pyopneumopericardium. Stephenson et al. reported a case series of 13 patients with esophagopericardial fistulas & pyopneumopericardium with a 100% mortality rate. Another case series showed survival rates of only 17% in 60 patients with pyopneumopericardium secondary to esophageal perforation. Erosion of esophageal ulcers, ingestion of foreign body, iatrogenic, trauma, malignancy, localized inflammation can lead to esophageal perforation. Streptococcus pneumoniae & Staphylococcus aureus are common pathogens involved. Constrictive pericarditis is a possible complication in up to 20 to 30%. Our patient underwent pericardial window & surgical debridement followed by EGD-guided gastro-jejunal tube placement. He did well after 4 weeks of IV antibiotics. Our case demonstrates that early recognition & intervention can favorably alter the course of this potentially fatal cardiac condition.

A Bibliometric Analysis Of Coronavirus Research In Gulf Cooperation Council Countries

Covid-19 Was Declared A Pandemic By World Health Organization In March 2020. Since Then, It Has Attracted The Enormous Attention Of Researchers From Around The World. The World Has Gone Through Previous Instances Of Corona-Viruses Such As Severe Acute Respiratory Syndrome And Middle Eastern Respiratory Syndrome. Nevertheless, None Was Of These Were Of This Serious Nature As Covid-19. In This Research, We Carry Out A Bibliometric Analysis Of Coronavirus Research Using The Scopus Database. However, We Restricted Ourselves To The Gulf Cooperation Council Countries, Comprising Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, And The United Arab Emirates. The Analysis Was Performed Using Biblioshiny Software. We Analyzed 4288 Articles Written By 24226 Researchers From 1994 Till 2021, Published In 1429 Sources. The Number Of Authors Per Publication Is 5.65. A Bulk Of The Research (More Than 68%) Appeared In The Form Of Articles. More Than 43% Of The Publications Appeared In 2020 And More Than 44% In 2021. Saudi Arabia Appears The Most-Cited Country, Followed By Qatar. Journal Of Infection And Public Health Published The Most Number Of Papers, Whereas New England Journal Of Medicine Is The Most-Cited One. Memish, Z.A. Wrote The Maximum Number Of Papers. The Top Source, According To The H-Index, Is The Journal Of Virology. Furthermore, The Two Most Prolific Universities Are King Saud University And King Abdulaziz University, Both From Saudi Arabia. The Research Uncovered Deep Learning As A Niche Theme Used In Recent Publications. The Research Landscape Continues To Alter As The Pandemic Keeps On Evolving © 2021,International journal of online and biomedical engineering.All Rights Reserved

Large-scale bibliometric analysis of coronavirus

Coronavirus constitutes a family of RNA viruses causing respiratory tract infections in both humans and birds. A mild disease appears like the common cold, and in other cases, causes Severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), or COVID-19. As compared to COVID-19, SARS and MERS were limited to certain countries. On the other hand, COVID-19 was declared a pandemic by the World Health Organization on Mar. 11, 2020. In this research, we perform the bibliometric assessment of Coronavirus research using the Scopus database. We studied 27,824 articles written by 64,903 researchers from 1951 till June 20, 2020, published in 3,858 different sources. More than 65% of research appeared in the form of articles. More than 34% of publications appeared in 2020, coinciding with the appearance of COVID-19. This also resulted in a sharp increase in the average citation from 2.2 observed in 2019 to 14.5 seen in the year 2020. The USA is the most-cited country, followed by China. Nevertheless, Russia appears as the most-cited country per year. © 2021 WITPress. All rights reserved.

Measures of depressive symptoms using beck depression inventory-ii among healthcare professionals during a pandemic of covid-19

The present study was carried out to assess the level of depressive symptoms among health-care professionals (HCPs) during the unprecedented time of COVID-19 using Beck Depression Inventory-II (BDI-II) in Karachi, Pakistan. This descriptive, cross-sectional study was conducted using BDI-II containing 21 questionnaires for the determination of depressive symptoms among HCPs including physi-cians, pharmacists, dentists, and other healthcare personnel working in a metropolitan city of Karachi, from February 2020 to May 2020. The survey forms were distributed electronically after obtaining written consent of respondents. One-way ANOVA test was used to evaluate the association between independents variables and BDI-II items. In the current research, out of 500 HCPs, only 328 completed the form. The mean age of the respondents was 36.32 ± 5.23 years. The outcomes revealed that the respondents stated mild levels of depression (mean = 10.69 ± 9.4). Cronbach’s alpha or internal consistency reliability coeffi-cients for depression score was 0.903. Corrected item-total correlations were satisfactory. It was observed that the majority of BDI-II items were found to be significantly associated with the experience and profes-sion of respondents. The HCPs showed mild to moderate depression symptoms during the COVID-19. To avoid the switching of the psychological impact from moderate to severe, strategies should be designed and implemented by the government and health care bodies to overcome psychological distress among HCPs.

Mental Distress after 1st Wave of COVID-19 among Medical Students

Aim: The aim of the current study is to evaluate the mental distress facing by the MBBSs students during the first wave of COVID-19. Study Design: Cross-sectional. Place and Duration of Study: Study was conducted at Quaid-e Azam medical college Bahawalpur during the period of May 2020 to July 2020. Methodology: MBBS undergraduate students were included in the study. For assessing mental stress, the questionnaire used was the modified form of Impact of Event Scale Revised (IES-R). The proforma was prepared by using Google Docs and disseminated through the student's WhatsApp groups. Data was analyzed by using Special Package for Social Science version-20. Frequency and percentages were calculated for the qualitative variables while association was analyzed by using Chi-square test. p-value <= 0.05 was considered as significant. Results: About half of the participants were female students i.e. 55.2%. The frequency distribution of stress level among students showed that the majority of participants were facing mild level of stress i.e. 130 participants out of total 310 participants (41.9%), 112 participants were having moderate stress level (36.2%), followed by 53 participants with severe level of stress (17.1%) while 15 participants (4.8%) were having extremely severe intensity of stress. It was also found out that the gender and socioeconomic status have a significant association with the mental stress but the year of study has no any association with the mental stress as reported statistically non-significant p-value. Conclusion: The current study concluded that the mental distress experienced by medical undergraduate during COVID-19 is more severe than that of the general population and the female students are more prone to develop depressive symptoms. So there is a need of counselling session to improve the mental health of our medical under graduates as they are the future handlers of medical profession.

Coronavirus-past and present

Coronavirus infectious disease 2019 (COVID-19) caused by a new mutant strain of coronavirus (SARS-CoV-2) which is an ongoing global health pan-demic. However, you’ll have first become conversant in the term coron-avirus during the severe acute respiratory syndrome (SARS) outbreak in 2002. Here we summarize important distinguishing characteristics concerning both SARS-CoV and SARS-CoV2. SARS-Cov2, which is caused by the new novel coro-navirus, has been highlighting the news lately. The virus that causes SARS is entitled as SARS-CoV, while the virus that causes COVID-19 is entitled as SARS-CoV-2. SARS was declared a global pandemic in late 2002 in China, when a healthcare practitioner got infected with a virus and unknowingly travelled to Hong Kong, with rapid spread to other nearby countries by international travelling of people. But due to many other factors, SARS was restrained in around 30 countries with an estimated mortality rate of 10% by the end of the pandemic in mid-2003. The focal point of this current novel coronavirus outbreak is within Wuhan city of China. Animal host act as a reservoir for novel coronavirus and it can infect human by crossing this barrier. Hence, a seafood wholesale market in the city was thought to be one among the places from where the transmission of COVID-19 initiated. As we go further in this arti-cle, we will come across the differences in genomic structure, pathogenicity, clinical features and lab investigations among SARS-CoV2 and SARS-CoV.