Multi-Joint Unit Network for COVID-19 Diagnosis using X-Ray and CT Images

The global COVID-19 pandemic has caused a health crisis globally. Automated diagnostic methods can control the spread of the pandemic, as well as assists physicians to tackle high workload conditions through the quick treatment of affected patients. Owing to the scarcity of medical images and from different resources, the present image heterogeneity has raised challenges for achieving effective approaches to network training and effectively learning robust features. We propose a multi-joint unit network for the diagnosis of COVID-19 using the joint unit module, which leverages the receptive fields from multiple resolutions for learning rich representations. Existing approaches usually employ a large number of layers to learn the features, which consequently requires more computational power and increases the network complexity. To compensate, our joint unit module extracts low-, same-, and high-resolution feature maps simultaneously using different phases. Later, these learned feature maps are fused and utilized for classification layers. We observed that our model helps to learn sufficient information for classification without a performance loss and with faster convergence. We used three public benchmark datasets to demonstrate the performance of our network. Our proposed network consistently outperforms existing state-of-the-art approaches by demonstrating better accuracy, sensitivity, and specificity and F1-score across all datasets. © 2022 ACM.

Scada Web-Based Instrumentation and Control Laboratory with Real-Time Remote Monitoring and Control System for Columban College

This paper provides a remote access control experiment for students who can't go to the campus because of the COVID-19 pandemic. This paper utilizes the SCADA (supervisory control and data acquisition) using LabView with the Internet of things technology to control the laboratory remotely in real-time. Remote access experiments of a Linear actuator, PID algorithm, Dynamics and Control of Second-order system response, and survey questionnaires were applied and used as an example to show how effective the research study is. The safety of the SCADA system was also considered by using the Virtual Private Network as the primary connection between the student and the server. The remote access laboratory will give a solution to the current problem of the academe for not providing a real-time laboratory equipment experiment. © 2022 IEEE.

Rethinking our interpretation processes: Some evidence

This chapter reconstructs the research work developed within the volume, with the aim of bringing out new elements. Using the abductive process within this chapter, therefore starting from the facts-understood as the infodemic disorder that afflicted public institutions and citizens during the first period of the Covid-19 pandemic-the evidence is presented. It is therefore a question of inserting the six research into the nested case study. Through the technique of lexical worlds, the views of the crisis have been reconstructed. The chapter also traces the limits of this study by opening new avenues for the analysis of the communication crisis produced by the pandemic. © Springer Nature Switzerland AG 2023. All rights reserved.

Know an Emotion by the Company It Keeps: Word Embeddings from Reddit/Coronavirus

Social media is a crucial communication tool (e.g., with 430 million monthly active users in online forums such as Reddit), being an objective of Natural Language Processing (NLP) techniques. One of them (word embeddings) is based on the quotation, "You shall know a word by the company it keeps,” highlighting the importance of context in NLP. Meanwhile, "Context is everything in Emotion Research.” Therefore, we aimed to train a model (W2V) for generating word associations (also known as embeddings) using a popular Coronavirus Reddit forum, validate them using public evidence and apply them to the discovery of context for specific emotions previously reported as related to psychological resilience. We used Pushshiftr, quanteda, broom, wordVectors, and superheat R packages. We collected all 374,421 posts submitted by 104,351 users to Reddit/Coronavirus forum between January 2020 and July 2021. W2V identified 64 terms representing the context for seven positive emotions (gratitude, compassion, love, relief, hope, calm, and admiration) and 52 terms for seven negative emotions (anger, loneliness, boredom, fear, anxiety, confusion, sadness) all from valid experienced situations. We clustered them visually, highlighting contextual similarity. Although trained on a "small” dataset, W2V can be used for context discovery to expand on concepts such as psychological resilience.

COVID-19 Detection from Cough Recordings Using Bag-of-Words Classifiers.

Reliable detection of COVID-19 from cough recordings is evaluated using bag-of-words classifiers. The effect of using four distinct feature extraction procedures and four different encoding strategies is evaluated in terms of the Area Under Curve (AUC), accuracy, sensitivity, and F1-score. Additional studies include assessing the effect of both input and output fusion approaches and a comparative analysis against 2D solutions using Convolutional Neural Networks. Extensive experiments conducted on the COUGHVID and COVID-19 Sounds datasets indicate that sparse encoding yields the best performances, showing robustness against various combinations of feature type, encoding strategy, and codebook dimension parameters.

Fluid transitions – "weak” constellations of participation in the process of leaving care

This conceptual article describes how, in terms of organization theories, shifts in the chronological transition to adulthood produce "weak” constellations of participation during the process of leaving care. In contrast, the professional discourse on participation is dominated by concepts that ultimately call for "strong” constellations as a means of enabling participation. In that discourse, participation is seen as being governed by the organizational structure of the child and youth care services, which, for example, determine the chronology of the steps taken by care leavers (e.g., moving out of their residential home or the foster family) and thus also affect their opportunities for participation. Altogether, chrononormativities are seen to play a prominent guiding role. Research into participation relating to child and youth care generally pays little attention to emerging adulthood: the professional debate mainly relates to the UN Convention on the Rights of the Child (UNCRC), which focuses on the age of majority as its biographical milestone. For this reason, this article will start out by summarising the research on participation during the process of leaving care. Three analyses of contemporary society taken from youth studies will then be used to describe the chronological arrangements young people currently experience during this transition. First, we will examine the dynamics influencing young people's biographies during emerging adulthood in some countries and affecting their opportunities for participation. Second, we will focus on the varied range of life circumstances, coping situations and social disadvantages facing care leavers. Third, we will study how the "beyond Covid” situation is affecting care leavers. Finally, we will argue that in view of these unclear chronological transitional constellations during the process of leaving care, it would be fruitful for research on participation to examine "weak” constellations of as a means of identifying and analysing different signals through which people make their voices heard. This understanding of participation against the background of leaving care will make it possible to recognise not just "strong”, activating forms of participation, but also different degrees of participation and ways in which it is expressed.

Preparedness for an Isolation Unit during Covid-19 Pandemic in PICU of Minia University Hospital: Practical Considerations and Outcomes

Background: Admission to the pediatric intensive care unit (PICU) is compulsory for children with a severely complicated form of COVID-19, who are hemodynamically unstable. Our study determined the degree to which our PICU preparedness measures impacted patient outcomes and infection control management within the PICU of Minia University Hospital in Egypt. Methods: 179 pediatric patients, admitted to the PICU isolation unit with suspected or confirmed diagnosis of COVID-19, were studied retrospectively. We conducted descriptive analyses on the patients' characteristics and outcomes and the basic concepts and procedures for PICU readiness are discussed. Results: The patients ranged in age from one month to sixteen years, with an average age of 8.60 +/- 4.84 years, 44.69 % of whom were males. Fever, shortness of breath, and cough were the most common symptoms on admission. The most common comorbidities were neurological disorders, heart disease, and respiratory disease, with percentages of 27 %, 25 %, and 23 %, respectively. Overall, mortality was 22.9 %. Only 21 (0.5%) of the hospital's healthcare staff were infected. The infection did not spread to other non-COVID parts of the hospital. Conclusion: Our PICU strategies and preparation ensured adequate prevention of infection spreading to other units and HWCs, as well as lowering mortality and improving COVID-19 patients' outcomes.

Evaluation of the side effects of Sinopharm and PastoCovac COVID-19 vaccines in children aged 5-12 years in Iran

Background: Vaccination of children against COVID-19 in Iran was conducted for children 5-12 years on July 22, 2021, with PastoCovac and Sinopharm. This study aimed to evaluate the side effects following the administration of vaccines in children.Methods: This descriptive-analytical study was performed on 394 children aged 5-12 years who were referred to health centers in Bojnurd, Iran, and received PastoCoVac or Sinopharm COVID-19 vaccines from March to July 2022. After receiving the first dose of the vaccine, in health centers, the children's parents filled out sections of a COVID-19 vaccine questionnaire that included sociodemographic and clinical characteristics of children. After that, other sections of the questionnaire related to side effects following vaccination were filled out by parents of children at different time intervals after receiving the first or second dose of vaccines.Results: Our results showed that the incidence of vaccine side effects in children aged 5-12 years varies between 24%-37%, depending on the type and dose of vaccine. The most common side effects after getting the first and second doses of vaccines were injection site pain and swelling, fever, fatigue, and myalgia. No serious side effects were reported, and almost all side effects were resolved within a few days without special treatment.Conclusion: It can be concluded that the incidence of side effects following COVID-19 vaccination in children aged 5-12 years varies depending on the type and dose of the vaccine. However, no serious side effects were reported, and most were resolved within a few days without special treatment. These findings suggest that the vaccination of children against COVID-19 is generally safe and welltolerated.

Pandemic- a candidate for the word of the century? The linguistic image of the lexeme in contemporary Polish based on corpus data

The article presents the linguistic image of the noun pandemic in contemporary Polish. The aim of the analysis is to look at how the word is used today, in the COVID-19 era, and how it was used before the first cases of this disease were detected. The first part of the article discusses the current data available on the Words of the Day website, Google Trends and the MoncoPL corpus search engine, while the second part shows the occurrences of the lexeme in slightly older texts that were collected in the National Corpus of Polish (NKJP) before 2010. The analysis of the material extracted from the above sources indicates that that the noun pandemic was very rare in the NKJP and then became very popular with the appearance of the pathogen causing COVID-19. However, the analysis of the most common collocates shows that the mentioned event did not have a significant impact on the other aspects of the use of the lexeme by the users of modern Polish.

Trans/feminist collaborative autoethnographic storying of gender-based violence, during the COVID-19 pandemic

The COVID-19 crisis has spotlighted particular insidious social problems, including gender-based violence (GBV), and their relationship with movement and confinement. As well as changing configurations of GBV, the experience of the global pandemic and the immobilities of national lockdowns have created space to imagine GBV - to connect with past experiences in the context of our rethinking of current experiences across multiple spaces. In this article we explicate a transdisciplinary feminist collaborative autoethnographic storying of GBV during the COVID-19 pandemic. Based on the 'trans/feminist methodology' of Pryse (2000), we seek to contribute knowledge of GBV through the lens of COVID-19 using our own experiential life storying. In this article we show the potential of this method in understanding lived experiences over time that are situated in a specific context. Our experiences of GBV, as viewed through the pandemic, are presented as fragments, which then make up a collective narrative that illustrates our shared experiences of GBV in all its forms, across multiple spaces and throughout our life histories. In this common story, GBV is considered to im/mobilise - to stagnate our range of mobilities to varying degrees across these spaces and times.

Misinformation Detection Using Unsupervised Approach on CoAID Dataset

COVID-19 has had an impact on everyone's life. People have slowly moved online for information access regarding COVID-19. This resulted in a large amount of misinformation spread among the people. This has a widespread impact on business, economy, education, and various other factors of society. Recent research techniques have developed models to detect COVID-19 misinformation using a mainly supervised learning approach that demands a labeled dataset. Several datasets have been generated since the COVID-19 pandemic using social media and web platforms. However, considering the large amount of information generated online with unstructured, incomplete, and noisy data, it is difficult to obtain labeled data for supervised learning. Therefore, in this research authors have proposed an unsupervised learning technique using k-means with a domain-specific sentimental bagof-words on the CoAID dataset. CoAID dataset has been created during the initial stages of the COVID-19 pandemic and is popular and widely used. Initially, the authors have done an extensive analysis of the literature based on the CoAID dataset to explore the various techniques developed on this dataset. Further, a k-means clustering algorithm is employed with six different distance measures viz. Euclidean, Squared Euclidean, Chi-square, Canberra, Chebychav, and Manhattan. The Elbow method is used to identify the optimal number of clusters. To evaluate the performance of the proposed model authors have used various metrics like purity, precision, silhouette score, word clouds, and sentiment analysis. The model showed a purity score of 0.96 and a precision of 1 for k=2. © 2022 IEEE.

Would a Male Sounding Name for the Covid-19 be Perceived as More Serious than a Female Sounding Name? Impact of the Grammatical Gender Assigned to the Disease on its Perception and on the Protective Measures Taken to Avoid it

At first glance, debates about the gender of the definite article that should precede the term Covid-19 seem to be more about grammatical and linguistic considerations. Nevertheless, following recent work (Farrow et al. [2018]) inviting a closer look at words as levers for influencing human perceptions and behaviours, we experimentally test in France whether the choice of the article to precede the term Covid-19 could have contributed to more effective public policies. The results show that this seemingly innocuous choice is not and suggest that, in the context of a strategy to combat the spread of the virus, the masculine article might have been more relevant.

Cause-of-death statistics in 2020 in the Republic of Korea

Background: This study analyzed the causes of death in the Korean population in 2020.Methods: Cause-of-death data for 2020 from Statistics Korea were examined based on the Korean Standard Classification of Diseases and Causes of Death, 7th revision and the International Statistical Classification of Diseases and Related Health Problems, 10th revision.Results: In total, 304,948 deaths occurred, reflecting an increase of 9,838 (3.3%) from 2019. The crude death rate (the number of deaths per 100,000 people) was 593.9, corresponding to an increase of 19.0 (3.3%) from 2019. The 10 leading causes of death, in descending order, were malignant neoplasms, heart diseases, pneumonia, cerebrovascular diseases, intentional self-harm, diabetes mellitus, Alzheimer disease, liver diseases, hypertensive diseases, and sepsis. Cancer accounted for 27.0% of deaths. Within the category of malignant neoplasms, the top 5 leading organs of involvement were the lung, liver, colon, stomach, and pancreas. Sepsis was included in the 10 leading causes of death for the first time. Mortality due to pneumonia decreased to 43.3 (per 100,000 people) from 45.1 in 2019. The number of deaths due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was 950, of which 54.5% were in people aged 80 or older.Conclusion: These changes reflect the continuing increase in deaths due to diseases of old age, including sepsis. The decrease in deaths due to pneumonia may have been due to protective measures against SARS-CoV-2. With the concomitant decrease in fertility, 2020 became the first year in which Korea's natural total population decreased.

The Impact of Severe Acute Respiratory Syndrome Coronavirus 2 Vaccination and Infection on Neutralizing Antibodies: A Nation-wide Cross-sectional Analysis.

BACKGROUND: Neutralising antibodies (nAbs) play a critical role in the protection against severe COVID-19. In the era of vaccine boosters and repeated SARS-CoV-2 outbreaks, identifying individuals at risk represents a public health priority. METHODS: Relying on the Monaco COVID Public Health Programme, we evaluated nAbs from July 2021-June 2022 in 8,080 SARS-CoV-2 vaccinated and/or infected children and adults, at their inclusion visit. We stratified by infection status and investigated variables associated with nAbs using a generalised additive model. RESULTS: Infected and vaccinated participants had high and consistent nAbs (>800 IU/mL), which remained stable over time since injection, regardless of the number of vaccine doses, body mass index, sex, or age. By contrast, uninfected participants showed larger variability (two doses [V2] median 157.6; interquartile range [IQR] 43.3-439.1 IU/mL) versus three doses [V3] median 882.5; [829.5-914.8] IU/mL). NAbs decreased by 20% per month after V2 (adjusted ratio 0.80; 95%CI [0.79-0.82]), but remained stable after V3 (adjusted ratio 0.98; 95%CI [0.92-1.05]). CONCLUSIONS: Hybrid immunity provided stable, high and consistent nAbs over time. The benefit of boosters was marked to restore decaying nAbs in uninfected participants. NAbs could identify individuals at risk of severe COVID-19 and provide more targeted vaccine boosters' campaigns.

Covid-19 Influence on Travelers/ Commuters' Attitude towards Taxi Services in Saudi Arabia

With COVID-19, significant life events can alter how individuals perceive and employ transportation systems. The COVID-19 pandemic has disrupted people's lives for a considerable time and may impact how people see travel and use transportation services. Due to the COVID-19 pandemics' severe physiological and psychological effects and ongoing financial difficulties, critical personnel must continue traveling for necessary tasks. The main aim of this study was to explore the use of taxi services after the Covid 19 pandemic perceived by travelers and commuters. To analyze the factors that influenced how people behave while using taxis for necessary travel during the COVID-19 restrictions imposed in Makkah, Madinah, Riyadh, and other Saudi Arabian cities. Between October 30 and December 15, 2021, 524 Saudi travelers participated in the online questionnaire assessment. Respondents' attitudes, perceptions, and attentiveness regarding taxi services after the lockdown were measured using a categorical scale. Statistical analysis was performed using the IBM SPSS-20 version and the Chi-Square, Phi, and Cramer's V tests to analyze were applied. The results of this study revealed how the COVID-19 outbreak caused some people to rethink their travel. This allows behavior-change approaches to target motives, challenges, and attitudes about changing travel options. © 2023, World Scientific and Engineering Academy and Society. All rights reserved.

Work-Stress Content Analysis Using Social Media Data

Since its occurrence in December 2019, COVID-19 has adversely affected both the personal and professional lives of people across the world. The widespread continuance of the pandemic has increased feelings of stress among people. Focusing on content analysis of data collected from Twitter, a social media platform, the current article aims at identifying and analyzing job-related stress among the masses with a focus on two primary terms related to stress among working people—employment and unemployment. A total of 32,237 tweets were downloaded from locations of four major cities of India, namely, Delhi, Mumbai, Kolkata and Chennai based on the keywords used for the study. Content analysis using R was employed as the technique to study the correlation and association of terms to find linkages between feelings/sentiments shared by the masses. Two clusters (Speculative and Misfit-Originators) of job-related stress causes were identified and coping strategies were suggested based on the reasons for stress in the different clusters. The findings suggest that increasing the perception of volition and allaying fears act as coping strategies for employees. © 2023 Fortune Institute of International Business.

New Opportunities Model for Monitoring, Analyzing and Forecasting the Official Statistics on Coronavirus Disease Pandemic

At the beginning of 2020, it became obvious that the coronavirus disease 2019 (COVID-19) pandemic will have a fairly significant scale and duration. There was an unmet need for the analysis and forecast of the development of events. The forecast was needed to make the managerial decisions in terms of knowledge on the dynamics of the pandemic, considering and analyzing the incoming official statistics about the pandemic, modeling and predicting the behavior of this statistics. Due to the objective and subjective factors, the available statistics is far from the unknown true data regarding the pandemic. Therefore, strictly speaking, it was necessary to model and predict not the dynamics of the pandemic, but the dynamics of the official (i.e. government) statistics on the pandemic. This paper proposes a new model, referred to as the new opportunities model, to monitor, analyze and forecast the government statistics on COVID-19 pandemic. A modeling approach is offered in this regard. The modeling approach is important as it answers simple questions on what awaits us in the near future, which is the current phase of the pandemic and when all this will be over. The new opportunities model is applied to three different countries in terms of area, economy and population, namely Russia, Romania and Moldova, plus the Campania region in Italy, and proves to be efficient over other similar models including the classical Susceptible-Infected (SI) model. © 2023, Publishing House of the Romanian Academy. All rights reserved.

Emerging Trends of ICT in Airborne Disease Prevention

Information and Communication Technologies (ICT) are becoming indispensable nowadays for the healthcare industry. The utilization of ICT in healthcare services has accelerated even faster after the commencement of the COVID-19 outbreak. This study aims to perform a scientometric analysis of scholarly literature on airborne diseases in the discipline of science and technology. It explores the recent advancement of internet technologies in healthcare to control the prevalence of deadly airborne illnesses by applying analytical approaches. It presents publication trends, citation structure, influential sources, co-citation, and co-occurrence network analysis using the CiteSpace tool. It identifies the important research topics, current research hotspots, most active research areas, and leading technologies in this scientific knowledge domain. It inferred significant results from analyses that will benefit researchers and the academic fraternity across the globe to understand the evolving paths and recent scientific progress of ICT in airborne disease management. © 2022 Association for Computing Machinery.

"Economy Struggle to Escape Coronacoma”: Compound Word Formation Processes of COVID-19 Related Terms in Online English News Articles

This study aimed to uncover the types of compound word formation and how the compound word formation processes of related new terms in the COVID-19 pandemic's online English news articles were formed. This study used Lieber (2009) and Plag's (2002) compound word formation frameworks. The data were obtained from ten news articles related to the COVID-19 pandemic using a qualitative descriptive method. The results showed that there were so varied types of the derivation of compound word processes, namely coordinative, subordinative, and attributive. Meanwhile, based on the stress of compound, the study found that there were noun compound, endocentric compounds, exocentric compounds, and copulative compounds. The results of this study indicated that attributive compounds and subordinate compounds are equally dominant in the analysis. Besides, the findings revealed that noun is the most dominant words than verb or adverb. To conclude, the present study provides both theoretical and practical implications. © 2023 ACADEMY PUBLICATION.

A Comparative Study between the First and Second Waves of World Threatening Covid-19 Disease

The global pandemic caused by severe acute respiratory syndrome (Corona virus disease - COVID-19) is the major concern of mankind now. The tiny virus has wiped out million of lives and changed the total economic scenario of world. The present review is formulated with a view to study and analyse the epidemics of first and second wave of COVID-19 in relation to its effects on human health. The infection pattern has been changed and many countries have witnessed higher number of people infected in the second wave than the first one. The result of stimulation suggests that the second wave may occur in the mid July 2020 to the last week of December 2020. One of the main problems in managing the COVID-19 epidemic crisis in second wave is its effects on human health and disease syndrome as compared to the first wave of COVID-19 and also the technical and calculated capabilities of nations. According to scientists, 18 mutations in 7 genes have been observed as a result of mutation and the new variant has been named B.1.617. The pair of spike genes has been linked to amino acid deletion and the ability to evade vaccines. As a result, he is entering the receptor faster and infection is spreading rapidly. Corona virus enters the human body through this spike protein. In India RT-PCR tests are targeted at three genomic sequences of viruses. Only if three different genomic sequences match then there will be a positive report.Copyright © 2020 Ubiquity Press. All rights reserved.