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The U.S. confronts an unprecedented public health crisis, the COVID-19 pandemic, in the presidential election year in 2020. In such a compound situation, a real-time dynamic examination of how the general public ascribe the crisis responsibilities taking account to their political ideologies is helpful for developing effective strategies to manage the crisis and diminish hostility toward particular groups caused by polarization. Social media, such as Twitter, provide platforms for the public's COVID-related discourse to form, accumulate, and visibly present. Meanwhile, those features also make social media a window to monitor the public responses in real-time. This research conducted a computational text analysis of 2,918,376 tweets sent by 829,686 different U.S. users regarding COVID-19 from January 24 to May 25, 2020. Results indicate that the public's crisis attribution and attitude toward governmental crisis responses are driven by their political identities. One crisis factor identified by this study (i.e., threat level) also affects the public's attribution and attitude polarization. Additionally, we note that pandemic fatigue was identified in our findings as early as in March 2020. This study has theoretical, practical, and methodological implications informing further health communication in a heated political environment. [ FROM AUTHOR] Copyright of Social Science Computer Review is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Intuitionistic fuzzy set (IFS) theory can be applied for multi-aspect systems due to its capability to address uncertainty and incomplete information in terms of membership and non-membership degrees. Unfortunately, classical Γ -structures cannot handle fuzzy and imprecise information in real problems. In fact, there is no rigorous base to practically express the effectiveness of multi-attribute systems in IFS environment. Here, we develop a generalized IFS with the notion of Γ -module called intuitionistic fuzzy Γ -submodule (IF Γ M) to establish a novel " Global electronic (e)-Commerce (GeC) Theory ". To simplify the analysis of parameters, (α , β) -cut representation is proposed in terms of comprehensive distribution of fuzzy number for the classification of components. On the other hand, Cartesian product is implemented to correspond the elements. Substantial properties of IF Γ M including (α , β) -cut, Cartesian product and t -intuitionistic fuzzy Γ -submodule (t -IF Γ M) are characterized with illustrative examples to extend the framework of IF Γ M, where (α , β) -cut and support t -IF Γ M are verified to be Γ -submodules based on the properties of IF Γ M. Through Γ -module homomorphism, image and inverse image, the parametric connections between (α , β) -cuts are systematically investigated. In addition, a mathematical relationship between the Cartesian product and (α , β) -cut is determined. The overlapping intersection of a collection of t -IF Γ M is proved to be t -IF Γ M, and the image and inverse image are preserved under Γ -module homomorphism. As global e -trades are increasingly expanding after the recent coronavirus disease 2019 (COVID-19) hit, with the growth of 26.7-trillion dollars, businesses are required to transform their traditional functional natures to online (or blended) strategies for cost efficiency and self-survival in the present competitive environment. Therefore, compared to recent studies on IFS in the context of Γ -structures, the main contribution of this study is to provide a theoretical basis for the establishment of a new GeC Theory through the developed IF Γ M method and Γ -module M which targets the purchasing rate of customers through e -commerce companies. In the end, the performance of the proposed method in terms of upper and lower cut, t -intuitionistic fuzzy set, support and IF Γ M model, is analyzed in the developed GeC Theory. The proposed GeC Theory is validated using real datasets of e -commerce mega companies, i.e., Amazon, Alibaba, eBay, Shopify. They are characterized based on the amount of online shopping by samples (individuals). Compared to the existing methods, the GeC approach is an effective IFS-based method for complex systems with uncertainty. [ FROM AUTHOR] Copyright of Engineering Applications of Artificial Intelligence is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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In this paper, we examine transborder commuters' experiences (i.e. individuals who commute between U.S. and Mexican border cities frequently) during the Covid-19 pandemic, with keen attention to the links between racial capitalism and temporality. We address two interrelated issues: first, we unpack how the United States framed the pandemic through the metaphor of war and the production of the categories of 'essential work(er)' and 'essential travel' to ensure racial capitalism's surplus labor and continuation. These categories function like a double-edged sword, tying racialized populations to racial capitalism's temporality to exploit them while excluding privileged others. We argue that Covid-19's temporality conflicts with racial capitalism's temporality. While the former relies on the deceleration of everyday life, the latter depends on constant acceleration driven by profit-seeking. Using queer and feminist theoretical lenses, we then demonstrate how U.S. Covid-19 border restrictions at land ports of entry exacerbated transborder commuters' cross-border travels and privileged some based on legal status. As a result, they used public Facebook groups to navigate and comprehend new commuting conditions, disidentifying with the United States' official pandemic framing and producing their own. This shared experience catalyzed 'digital transborder kinships' or temporally-bound socialities rooted in relational care, advocacy, and knowledge production. [ FROM AUTHOR] Copyright of Mobilities is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Purpose: Home-based workouts via fitness YouTube channels have become more popular during the pandemic era. However, few studies have examined the role of social media personae related to intention to exercise. The purpose of this study was to investigate the structural relationships between fitness YouTuber attributes: perceived physical attractiveness (PPA), perceived social attractiveness (PSA), perceived similarity (PS), parasocial relationships (PSRs), wishful identification (WI), physical outcome expectations (POEs), and continuous intention to work out with fitness YouTubers (CIWFY). Design/methodology/approach: This study considered fitness YouTube channel viewers as the unit of analysis. An online survey was conducted to empirically develop and test the research model using structural equation modeling (SEM). Findings: The SEM empirical findings revealed that the PSRs were significantly influenced by PSA, PPA, and PS. Also, WI was significantly affected by PPA and PS. Furthermore, POEs were significantly impacted by PPA and PSRs. POEs affected the CIWFY. Lastly, PSRs and POEs mediated the influence of PSA and PPA on the CIWFY. Originality/value: The psychological impacts of exercising to online fitness videos in the era of COVID-19, with its untact (no contact) social norms is timely. The study model demonstrated the fitness YouTube viewers' cognitive path from perceptions toward fitness YouTubers' attributes to behavioral intention. To be specific, the current study demonstrated how three attribution types (i.e. PPA, PSA, and PS) of fitness YouTubers affect viewers' PSRs and WI with fitness YouTubers, along with POEs and CIWFY. Along with health practitioners, fitness YouTubers who want to captivate viewers on their channels might need to consider self-attributes from their viewers' standpoint and should build psychological bonding with viewers. [ FROM AUTHOR] Copyright of Internet Research is the property of Emerald Publishing Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
BACKGROUND: A safe and effective vaccine against COVID-19 has become a public health priority. However only a few studies have been conducted to investigate the post vaccination symptoms and awareness among the public about the vaccination. This study aimed to assess the COVID-19 vaccination literacy and post vaccination effects among the vaccinated population in India. METHODOLOGY: A descriptive cross-sectional study was conducted with a convenience sample of the adult population in India. Data was collected through an online anonymous questionnaire. We used Google forms an online survey platform, to publish the questionnaire and manually generated the answer URL link to the eligible candidates. RESULTS: A total of 533 responses were collected. Among the participants, 463 (86.90%) were aged between 18 and 40 years old. Of which 289 (54.2%) were male and 244 (45.8%) were female participants. Among the respondents 374 (70.2%) completed both the doses of vaccine. 498 (93.4%) participants took the vaccination willingly and 35 (6.6%) participants were forced to get vaccinated. Body ache 327 (61.4%), Fever 307 (57.6%), headache 211 (39.6%) and alopecia 70 (14%) were the most commonly reported post vaccination symptoms. CONCLUSION: Overall, our study demonstrated that there was a high willingness to accept COVID-19 vaccine in India and the rate of infection with COVID-19 has been reduced after vaccination which proves that the vaccine is efficient. The rate of people getting hospitalized due COVID-19 has been drastically reduced. Cold, cough, mild hypersensitivity reactions were also been reported as post vaccination symptoms and no serious adverse effects were reported so far due to vaccination which proves that the vaccine is safe. [ FROM AUTHOR] Copyright of Journal of Pharmaceutical Negative Results is the property of ResearchTrentz and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Coronavirus disease of 2019 (COVID-19) has affected the globe terribly. The rapid spread of this virus and the precautionary measures to prevent it have impacted the lives of all human beings around the world in all dimensions. The anxieties over the virus along with the social restrictions have challenged the mental health and might have acute psychological consequences. In this study, our aim is to analyze whether COVID-19 has done any significant changes to very well-known five-factor personality traits of all the humans all over the world from social media text, such as Twitter. We first train and validate five machine learning models on the benchmark essays dataset and then those models are tested on the preprocessed Twitter dataset, consisting of pre_covid and post_covid tweets. The novelty of this study is to analyze and establish the fact that in this short period of time, COVID-19 cannot make very significant changes in the human personality all over the world. We have compared the performances of five machine learning models and what we have found is that the result provided by one model is also justified by the other models. [ FROM AUTHOR] Copyright of Computer Journal is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Aiming at the multi-attribute group decision-making problem with interval-valued probabilistic uncertain linguistic term set (IVPULTS) and unknown expert weights, this paper proposed a decision-making method combining distance and similarity. Firstly, it employed the interval dominance degree method to rank interval-valued probabilities to form an ordered IVPULTS since the disorder of elements in IVPULTS causes the existing distance measure and decision-making result to be non-unique. At the same time, it expanded the existing distance by using the interval linguistic term distance measuring method considering the poor discriminative power. Secondly, based on the dual relationship between distance and similarity measures, this paper defined the distance similarity formula and determined the weights of different experts using the improved similarity-trust network analysis method. Next, it designed a TOPSIS decision-making method based on improved distance and similarity-trust network (IDSTN-TOPSIS) to obtain a unique and stable ranking of the alternatives. Finally, taking the selection of resilient suppliers of a medical supplies manufacturing company under COVID-19 as an example, experimental results verify the effectiveness and superiority of the proposed method. (English) [ FROM AUTHOR] 针对属性值为区间值概率不确定语言术语集（interval-valued probabilistic uncertain linguistic term set, IVPULTS）、专家权重未知的多属性群决策问题，提出一种融合距离和相似度的决策方法。首先，由于现有的 IVPULTS中元素的无序性导致距离测度及决策结果不唯一，利用区间优势度方法对区间值概率进行排序，从而 形成有序的IVPULTS；同时考虑到现有距离测度区分能力不高，利用不确定语言距离度量方法扩充现有距离公 式。其次，基于距离与相似测度存在的对偶关系，为IVPULTS定义了距离相似度公式，并利用改进的相似—信 任网络分析法确定不同专家的权重。再次，设计了基于改进距离和相似—信任网络的TOPSIS决策方法（improved distance and similarity-trust network TOPSIS，IDSTN-TOPSIS），从而得到唯一且稳定的方案排序。最后，以新 冠疫情下某医疗用品制造公司熔喷布弹性供应商选择为例，验证了所提方法的有效性和优越性。 (Chinese) [ FROM AUTHOR] Copyright of Application Research of Computers / Jisuanji Yingyong Yanjiu is the property of Application Research of Computers Edition and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Due to the COVID-19 pandemic, many robot competitions have been canceled in the past years. To address this problem, we proposed a cloud-based VR platform for the crowdsourcing of embodied human-robot interactions. However, this system only suggested the feasibility of the competition application, and actual competitions had not yet been held and implemented. Therefore, through demonstration experiments in the RoboCup Asia Pacific (RCAP) conducted in a hybrid format with on-site and remote participation, we evaluated the usefulness of using cloud computing on AWS from whether the latency time causes problems in human-robot interaction in a virtual reality environment. [ FROM AUTHOR] Copyright of Advanced Robotics is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Objective: To find the effectiveness of online teaching and its reflection on their academics during COVID19 pandemic in basic medical science. Study Design: Cross Sectional Descriptive study. Setting: University Medical and Dental College, Faisalabad. Period: March 2019 to November 2021. Material & Methods: A total of 531 undergraduate MBBS & BDS (1st & 2nd year) students were included. A questionnaire was designed and shared online in Google classroom to get students' feedback. The data obtained was analyzed on SPSS 25 by using ANOVA and Chi-Square Tests. Results: 62.76% students declared that learning in physical classrooms is more understandable than e-learning, while 58% students were satisfied with this transformation of online teaching and secured better grades in e-assessments, while 69% students agreed with the fact that on campus assessment is more productive. According to our results 68.24% students preferred physical teaching and assessment methodology and 67.11% students agreed that team work with peers is more productive in on campus classes than e-classes. Conclusion: We investigated various aspects of e-learning experience of medical students and found a mixed opinion. By improving our infrastructure and using modern techniques we can make online medical education system more effective and productive for our students in future. [ABSTRACT FROM AUTHOR] Copyright of Professional Medical Journal is the property of Professional Medical Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
ABSTRACT
Social Network Sites provide a venue for people worldwide to share their point of view and interact with each other, offering a virtual space with freedom for expressing ideas and opinions. The interaction dynamics often creates clusters of users sharing similar interest and opinions, thus creating an information bubble or echo chamber. In certain topics, such as politics, different groups tend to collide and start arguments characterized by conflicts of opinion. This fact has been increasingly observed during the COVID-19 pandemic, fed by misinformation and anti-science movements. One approach to address these issues is to use statistical measures of the posts revolving around the topic of interest, such as the number of shares, likes , and replies. In this paper we propose a methodology to extract a feature set from trending topics of the Twitter social network and apply two white-box models, a Symbolic Regression, named ITEA, and a Decision Tree, for the automated detection and understanding of conflicts. Our experiments show that both models obtain close extrapolation accuracy to the baseline black-box model (Random Forest). As a highlight of this paper, both white-box models are fully described to be used by any practitioner. Additionally, the model created by ITEA allows us to extract some insights from the generated models. Although these models do not allow for a complete comprehension of the dynamics of a conflict, it certainly points towards a direction for a more thorough investigation. • Classifiers to detect conflicts of opinion on Twitter using statistical metrics. • Use of transparent models capable of helping to understand the dynamics of conflicts. • Analysis of the conflict dynamics using the generated transparent models. [ FROM AUTHOR]
ABSTRACT
Aim/Introduction: Vaccines against SARS-CoV-2 virus were developed due to the impetuous coronavirus pandemic. Vaccines hold a possibility to provoke side effects. The aim of our study was to examine the impact of COVID-19 vaccination on the incidence and duration of false-positive FDG-avid lymphadenopathy after vaccination with different types of vaccines and to determine its relationship with age, gender, and vaccine type. Material(s) and Method(s): The retrospective study included 103 patients who met the following criteria:18F-FDG PET/CT scan performed (in the period from August 2021 to December 2021) for staging or restaging of diagnosed oncological diseases at different time periods after vaccination Pfizer-BioNTech, Moderna-BioNTech and Oxford-AstraZeneca. Exclusion criteria were incomplete information about vaccination, patients with a diagnosed malignant lymphoproliferative disease, concomitant benign pathology of the lymphatic system, history of acute viral infection up to 3 months from the date of PET/CT. Result(s): False-positive reactive lymphadenopathy was identified in 35 (34%) of 103 patients included in our study cohort, which occurred during the first 2 weeks to 12 weeks after vaccination and manifested as increased metabolic activity in regional non-enlarged lymph nodes: ipsilateral axillary lymph nodes of levels I-III, as well as cervical LN of levels IV and VB). A significant moderate decline in metabolic activity in the LN over time was reported, as well as a decrease in the detection rate of PET-positive reactive findings with time. The results showed a trend of a positive relationship - the occurrence of reactive lymphadenopathy more often in women than in men. The detection rate, as well as the intensity of the activity of glucose metabolism, were higher in patients under the age of 50 compared to those >= 50 years. However, we did not find significant differences between the studied types of vaccines (p >0.05). Conclusion(s): Multidisciplinary physician awareness is essential regarding the possibility of false-positive FDG lymphadenopathy in relation to local inflammation and as a manifestation of the immune response due to COVID-19 RNA vaccination and adenoviral vector-based vaccine up to 12 weeks after injection, in order to optimize the clinical interpretation of hybrid scan results that determine the subsequent therapeutic approach of cancer patients. The results of the present study demonstrate the importance of vaccination on the contralateral side of the tumor drainage, as well as taking a thorough anamnesis. Keywords: FDG PET/CT, false positive lymphadenopathy, vaccination.
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This article presents the framework of the intersectional health/livelihoods paradox to analyse how political economic processes incur land use change to create vulnerability to infectious disease, but that in contending with these risks rural people negotiate conflicts with livelihoods. The conflicts and trade-offs people make in deliberating over health and livelihood outcomes because of ecological degradation are distributed unevenly through lines of social difference, such as gender and class. While the health/livelihoods paradox is evident within contexts of vulnerability to infectious disease, it is poignant when considering the impacts of interventions and containment strategies to control outbreaks in rural settings. Despite considerable attention on the urban context of disease surveillance, spread and containment due to the Covid-19 pandemic, this article refocuses analysis of the impacts of emerging infectious disease (EID) in rural contexts. The article shifts attention away from analysis of the problematic practices of rural households that undertake livelihood activities such as harvesting of wildlife for consumption, to a nexus between land use change, ecologies, livelihoods and health. The literature is fragmented in terms of the landscapes explored, developmental processes, species dynamics, diseases and social contexts. Therefore, this article presents a framework that enables complex dynamics such as these, that lead people to make compromises between competing health and livelihood outcomes to be examined.
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Objective: The incidence of bloodstream fungal infection is on the rise and Candida species remains responsible for the majority of the cases. Candidemia is frequently associated with a high rate of mortality and morbidity. The purpose of this study was to characterize Candidemia, its epidemiology, species distribution, and antifungal susceptibility pattern in a tertiary care hospital. Methods and Material: Candida species isolated from the blood culture of 51 patients in a tertiary care hospital during the period from 2016 to 2021 were included in the study. The growth on SDA was confirmed by Gram staining and speciation and antifungal susceptibility were performed with Automated system VITEK 2.0. Result(s): Out of51 isolates, Candida auris wasthe most common speciesaccounting for about 37.2% followedby C.albicans 19.7%, C. tropicalis 17.6%, and C. famata 9.8%. Candida auris has emerged as the predominant species during severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) pandemic.The incidence has risen from 22% to 60% during the pandemi C. Candida specieswere foundto be96.08% sensitiveto flucytosine, 94.12% tovoricanazole, 90.19%to casp ofungin/micafungin, 60.78% to amphoterecin B, and 56.86% to fluconazole. Conclusion(s): Candida auris has emerged as the predominant species in ICU setup and during SARS-CoV-2 pandemi C. Empirical treatment with echinocandines would be appropriate in high-risk patients with suspected Candidemia.
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Study Objectives: Restraint use in the emergency department (ED) has been shown to pose significant physical, psychological, and medicolegal risk to both patients and health care workers. Recent studies have demonstrated racial disparities in restraint application in the ED setting. This study aimed to evaluate the effectiveness of Code De-escalation, a standardized team-based approach for agitation management and assessment of perception of threatening behaviors, in reducing restraint use and racial disparities in restraint application in a community hospital emergency department. Study Design/Methods: We performed a retrospective observational study of the effect of introduction of the Code De-escalation pathway on violent restraint use among ED patients who had been placed on an involuntary psychiatric hold in a community emergency department. This new pathway includes a built-in step for the team members to systematically assess the perception of threat related to the patient behavior and the threat perceived by the patient. We used a Chi-squared test to compare incidence of restraints per ED encounter during the eight- month period after the intervention (May 2021-Dec 2021) with an eight-month period pre-intervention. We used a Cochran-Mantel- Haenszel test to look for differences in restraint use among racial and ethnic groups. To avoid confounding by the dramatic changes in patient volume and type during the peak of the COVID pandemic, we chose a pre-intervention period that pre-dated this (May 2019-Dec 2019). We compared our results to rates at neighboring community hospitals within the same hospital network during the same period. Results/Findings: Our sample size included 434 ED encounters pre intervention and 535 ED encounters post intervention. Over the study period, we observed a significant decrease in the violent restraint use among patients on an involuntary psychiatric hold from a rate of 7.4% to 3.7% (p=0.02). This was despite an overall increase in the number of patients requiring an involuntary psychiatric hold over the same period. This decrease was observed across all racial and ethnic groups. The same decrease in violent restraint use was not observed at the two other community hospitals within our hospital network and in the same metro area. Conclusion(s): A standardized de-escalation algorithm may be an effective tool in helping EDs decrease their use of restraints and may be one tool to help close the racial gap in restraint use among patients experiencing agitation. * Note Dana Im and Alice Bukhman contributed equally to conception and writing of this No, authors do not have interests to disclose Copyright © 2022
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The present study sought to investigate social network rumors and their function in affecting a citizen's desire to get vaccinated with the Corona Vaccine, as well as to evaluate the social networks that are most commonly utilized in disseminating rumors regarding the Corona Vaccine. Furthermore, this study looked at the vaccinations that were most influenced by the misinformation. The current study involved 400 individuals via internet questionnaires. The survey revealed that the majority of respondents (95.2 %) believe that rumors circulate on social networks and that the degree of diffusion of these rumors is considerable (66.8 %). While other social networks were significantly affected, Facebook had the most at (68.9 %). According to the study, periods when rumors propagate on social media are when diseases and epidemics spread. It was discovered that the purpose of disseminating rumors about the vaccination on social media was to instill fear in residents and lead to a misunderstanding of the genuine scientific truth. According to the study, the most rumored vaccination via social networks was AstraZeneca at (65.1 %). The most widely circulated rumor regarding the vaccine on social networks was that it "causes sterility”. [ FROM AUTHOR]
ABSTRACT
The study dealt with the relationship between the Yemeni public's seeking of information from traditional and modern means of communication about the Corona pandemic and the achieved cognitive, emotional and behavioural responses, and it monitored the role of some important variables such as demographic variables, fear variables and risk perception. The study concluded that the public's interest in information about Corona was average, and that the communication activity of nearly half of the respondents was low, especially among females, and the most important communication sources about the pandemic were family, friends and doctors, then some social networking applications and websites, especially WhatsApp and then television, and it was the most important The information that the public is seeking about the Corona epidemic is about preventive methods, then about the symptoms, then about the causes, and the motive to protect oneself and the family from the danger of the epidemic is the public's motives in seeking information, then the motive to get rid of the feeling of anxiety and fear, and the respondents showed a good level of knowledge about information about symptoms. And how to prevent, and one of the most important psychological effects caused by the spread of the epidemic: anxiety and fear, and the level of the respondents' behavioural response towards precautionary measures against the Corona epidemic was high, and the study showed a positive and significant correlation between the rate of public seeking information from modern and traditional means of communication and their positive behavioural responses. [ FROM AUTHOR]
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This paper aims to explore key pillars of supply chain competitiveness (SCC) and understand how top supply chains remain competitive in the long term. The research design is divided into two phases. First, an extensive review of the scholarly SCC literature is conducted to identify the core pillars that help achieve SCC. Second, the literature published in practitioner outlets on the five selected companies of Gartner's Supply Chain Top 25 is scrutinized to understand how top supply chains apply the core pillars of SCC in practice. A total of 193 scientific and practitioner articles were analyzed to develop the key pillars of SCC. This study identified six key pillars of SCC in the literature: innovation, sustainability, collaboration, information technology, agility, and flexibility. It has been found that a combination of these pillars, if not all, will be required to remain competitive in the post-COVID-19 era.
ABSTRACT
INTRODUCTION: Prolonged COVID-19 symptoms is one of the major challenges in the management of the disease. As the number of COVID-19 cases increased drastically, the number of those with prolonged symptoms are also accumulating, either diagnosed or undiagnosed. This study aimed to identify the long-term clinical symptoms of COVID-19 and the associated risk factors among Malaysian populations. MATERIALS AND METHODS: A cross-sectional survey using Google Form link for distribution of a selfadministered questionnaire was shared and disseminated via online platforms such as Facebook, WhatsApp, and Telegram. The inclusion criteria included those with a history of positive COVID-19 from 1st March 2020 until one month prior to the survey, and age above 18 years old. RESULTS: A total of 215 Malaysians participated, with 74% female respondents and a mean age of 36.4 years. Twenty-seven (12.6%) were asymptomatic when diagnosed with COVID-19. More than half (56%) still had symptoms at one-month of diagnosis, while 39% and 18% still had symptoms at the second and third months respectively. The most reported symptoms were lethargy (45.1%), difficult concentrating (22.3%) and cough (21.9%). Female, chronic lung disease and hypertension were significantly associated with prolonged symptoms at one month of COVID-19 infection. CONCLUSIONS: Lethargy, difficulty to concentrate and cough were the most common symptoms reported months after COVID-19 diagnosis. Apart from treating acute conditions, physicians should also be able to recognize and manage those symptoms. The findings of this study will help policymakers better grasp the social and economic consequences of long-term post-COVID-19 symptoms. [ FROM AUTHOR] Copyright of IIUM Medical Journal Malaysia is the property of International Islamic University Malaysia, Faculty of Medicine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
The aim was to investigate and assess the acceptance of virtual classes among Arabic language student teachers during and beyond covid-19. Quantitative research is carried out with the aim to assess the acceptance of virtual classes among Arabic language student teachers during and beyond covid-19. It uses a survey-based methodology to obtain data from the respondents. An online questionnaire was used to collect data via Facebook and WhatsApp groups. 450 questionnaire responses were received. They were 300 males (66.6%), and 150 females (33.4%). Results indicated that the student behavioral intention to use educational technology is positively affected by perceived usefulness, perceived ease of use. PU, PEOU yielded a coefficient of multiple regression (R) of 0. 450 and a multiple correlation square of 0. 435. This shows that 43.5% of the total variance in student behavioral intention to use educational technology is accounted for by the combination of PU, PEOU. Efforts to integrate educational technology into teacher education and Arabic language student teachers education programs are necessary. [ FROM AUTHOR] Copyright of Postmodern Openings / Deschideri Postmoderne is the property of Lumen Publishing House and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)