Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 60
Filter
Add filters

Journal
Year range
2.
9th IEEE International Conference on Communications and Electronics, ICCE 2022 ; : 349-354, 2022.
Article in English | Scopus | ID: covidwho-2078211

ABSTRACT

Physical exercises are important for a healthy life. However, many people do the exercises without professional assistance, especially when practicing at home during Covid-19. Inappropriate exercising can negatively impact and even result in muscle pain. In this paper, an exercise coaching application is developed to understand what the user is doing and provide useful assessments and guidelines to assist the users. The proposed application takes RGB image sequences from any off-the-shelf cameras widely integrated into smartphones or laptops as input. First, skeleton sequences are extracted from RGB images using the public tool Google MediaPipe. Then, a real-time action recognition based on the temporal sliding window and DD-Net model is proposed to determine the action class. Two frame-based and sequence-based scores are estimated to provide a quantitative assessment. Finally, a tool with GUI and a database are developed. © 2022 IEEE.

3.
Annals of Allergy, Asthma & Immunology ; 129(5):S49-S49, 2022.
Article in English | CINAHL | ID: covidwho-2075891
4.
Chest ; 162(4):A397-A398, 2022.
Article in English | EMBASE | ID: covidwho-2060583

ABSTRACT

SESSION TITLE: Extraordinary Cardiovascular Reports SESSION TYPE: Rapid Fire Case Reports PRESENTED ON: 10/18/2022 01:35 pm - 02:35 pm INTRODUCTION: Hypercoagulability is a well-known complication of COVID-19, with the most common vascular events being pulmonary embolism and deep vein thrombosis (1). Arterial thrombotic events, specifically aortic thrombosis, are rarely observed in COVID-19 infections. Literature review reveals less than 10 cases of aortic thrombosis have been reported in patients with COVID-19 infection. Here, we report a unique case of acute aortic thrombosis despite administration of therapeutic anticoagulation. CASE PRESENTATION: A 77 y.o. female with no known medical history presented to the hospital after a diagnosis of COVID-19 five days prior. Upon arrival, she was hypoxic requiring supplemental oxygen via non-rebreather (NRB) mask. CT chest with contrast revealed bilateral ground-glass opacities without evidence of pulmonary embolism or aortic thrombus. She was treated with remdesivir, dexamethasone, baricitinib and enoxaparin 40mg BID (essentially therapeutic dosing based on patient's body weight of 45kg). Adequate oxygenation was maintained with nasal cannula and NRB. However, on day eight of admission she was noted to desaturate to 80% requiring BiPAP. D-dimer and CRP drastically increased from 0.36ug/ml to 1.75ug/ml and 13.0 to 102.2, respectively. Repeat CT chest with contrast revealed multiple intraluminal thrombi in the distal thoracic aorta. Treatment with clopidogrel was initiated, however patient remained BiPAP dependent. Due to DNR/DNI status, intubation was not pursued. Ultimately, patient was transitioned to comfort care and expired. DISCUSSION: Thrombotic events are poorly understood but remain a well-documented sequela of COVID-19 infection. The pathophysiology of thrombosis in COVID-19 patients has not been fully elucidated, however, it likely involves amplification of the hypercoagulable state due to viral infection. Some of the proposed theories regarding this effect include endothelial dysfunction secondary to direct virus invasion and immuno-thrombosis due to viral mediated endothelial inflammation with resultant platelet activation (2,3). Regarding COVID-19 associated arterial thrombi, myocardial infarction and stroke are the most commonly encountered events. The few reported cases of aortic thrombi occurred almost exclusively in males with significant cardiovascular risk factors and not on anticoagulation (1,3). CONCLUSIONS: Due to the increased risk of venous thromboembolic events, prophylaxis is routinely used in patients with COVID-19. However, in our case, the patient developed multiple aortic thrombi without any typical risk factors for endothelial lesions despite being fully anticoagulated. This case highlights the need for continued research and trials related to appropriate anticoagulation therapies in hospitalized patients with COVID-19. Additionally, physicians should be aware of potential arterial thrombi in patients infected with COVID-19. Reference #1: de Carranza M, Salazar DE, Troya J, et al. Aortic thrombus in patients with severe COVID-19: review of three cases. J Thromb Thrombolysis. 2021;51(1):237-242. doi:10.1007/s11239-020-02219-z Reference #2: Loo J, Spittle DA, Newnham MCOVID-19, immunothrombosis and venous thromboembolism: biological mechanismsThorax 2021;76:412-420. doi:10.1136/ thoraxjnl-2020-216243 Reference #3: Woehl B, Lawson B, Jambert L, Tousch J, Ghassani A, Hamade A. 4 Cases of Aortic Thrombosis in Patients With COVID-19. JACC Case Rep. 2020;2(9):1397-1401. doi:10.1016/j.jaccas.2020.06.003 DISCLOSURES: No relevant relationships by Chelsey Bertrand- Hemmings No relevant relationships by Alyssa Foster No relevant relationships by Kyle Foster No relevant relationships by Yelena Galumyan No relevant relationships by Veronica Jacome No relevant relationships by Viet Nguyen

5.
Australian Journal of Primary Health ; 28(4):xliv, 2022.
Article in English | EMBASE | ID: covidwho-2058253

ABSTRACT

Background: The COVID-19 pandemic has created social and medical disruptions to the Australian community. The introduction of telehealth Medicare Benefits Schedule (MBS) item numbers in early March 2020 has shifted mental health consultations from face-to-face to telehealth. There is a literature gap pertaining to the ongoing trends that extend past the initial 'first wave' of the pandemic in the context of an Australian landscape. Aim/Objective: To describe the pattern of mental health care consultations in a university-based general practice in Sydney, specifically, the distribution of face-to-face, telephone and tele-video consultations, according to the change in socio-political landscape and lockdowns. The secondary aim is to explore the effect of age, ethnicity, birth sex and student status, and the severity of patient symptoms via K10/DASS21 scores. Method(s): Retrospective data will be obtained from records of 456 patients attending a university-based general practice in Sydney, Australia between four different 35-day time periods: baseline pre- COVID-19 (1st February 2019 to 8th March 2019);first COVID-19 lockdown (31st March 2020 to 5th May 2020);second COVID-19 lockdown (20th August 2021 to 24th September 2021);post COVID-19 lockdown (1st February 2022 to 8th March 2022). Attendances will be defined by mental health MBS codes that correspond to mental health consultations, mental health care plans, and mental health care plan reviews, for face-to-face, telephone and tele-video consultations. K10/DASS21 scores will also be obtained. Statistical analysis will be performed using the two-sample t-test on SPSS. Finding(s): Data analysis is currently in progress. Results will be available by July 2022. Implications: Given the recent temporary telehealth extension announced by the Australian Government on 16th January 2022, the findings of our study will illustrate the impact of the COVID-19 pandemic on mental health consultations in various subgroups and provide additional data for policymakers to facilitate further examination in continuing MBS subsidisation.

6.
Australasian Journal of Information Systems ; 26, 2022.
Article in English | Scopus | ID: covidwho-2054876

ABSTRACT

Instagram has gained the attention of hundreds of millions of users and evolved quickly into a critical customer engagement tool for businesses worldwide, more so during Covid-19. Impacts of Covid-19 have fundamentally changed the market, and therefore, this paper explores the relationship between Instagram practices and the engagement of 20 Australian SMEs (Small medium enterprises) pre and during Covid-19. This study aims to answer the following questions: (1) How should user-generated content (UGC) and call to act content (CTA) be included as Instagram posts? (2) How to use #Hashtags and @Tagging in Instagram posts to keep a campaign going? (3) How Instagram can be utilised to mitigate the effect of Covid-19? Findings revealed a statistically significant relationship between the number of UGCs to Instagram engagement, while CTA content performance recorded a mixed result. However, both UGCs and CTA positively affect the engagement when used to build a virtual community and engage with followers rather than redirecting customers to online selling locations. Also, diversity in @Tagging and #Hashtag uses are found to be effective drivers of engagement. The results imply that addressing the Covid-19 related concerns of followers while showing genuine brand social responsibility can be rewarded by extra engagement © 2022 authors. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 3.0 Australia License, which permits non-commercial use, distribution, and reproduction in any medium, provided the original author and AJIS are credited

7.
31st International Joint Conference on Artificial Intelligence, IJCAI 2022 ; : 5199-5205, 2022.
Article in English | Scopus | ID: covidwho-2047062

ABSTRACT

In this work we consider the problem of how to best allocate a limited supply of vaccines in the aftermath of an infectious disease outbreak by viewing the problem as a sequential game between a learner and an environment (specifically, a bandit problem). The difficulty of this problem lies in the fact that the payoff of vaccination cannot be directly observed, making it difficult to compare the relative effectiveness of vaccination on different population groups. Currently used vaccination policies make recommendations based on mathematical modelling and ethical considerations. These policies are static, and do not adapt as conditions change. Our aim is to design and evaluate an algorithm which can make use of routine surveillance data to dynamically adjust its recommendation. We evaluate the performance of our approach by applying it to a simulated epidemic of a disease based on real-world COVID-19 data, and show that our vaccination policy was able to perform better than existing vaccine allocation policies. In particular, we show that with our allocation method, we can reduce the number of required vaccination by at least 50% in order to keep the peak number of hospitalised patients below a certain threshold. Also, when the same batch sizes are used, our method can reduce the peak number of hospitalisation by up to 20%. We also demonstrate that our vaccine allocation does not vary the number of batches per group much, making it socially more acceptable (as it reduces uncertainty, hence results in better and more interpretable communication). © 2022 International Joint Conferences on Artificial Intelligence. All rights reserved.

8.
Indonesian Journal of Electrical Engineering and Computer Science ; 28(1):328-338, 2022.
Article in English | Scopus | ID: covidwho-2040408

ABSTRACT

The purpose of this study is to present a comprehensive review of the use of structural equation modeling (SEM) in augmented reality (AR) studies in the context of the COVID-19 pandemic. IEEE Xplore Scopus, Wiley Online Library, Emerald Insight, and ScienceDirect are the main five data sources for data collection from Jan 2020 to May 2021. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach was used to conduct the analysis. At the final stage, 53 relevant publications were included for analysis. Variables such as the number of participants in the study, original or derived hypothesized model, latent variables, direct/indirect contact with users, country, limitation/suggestion, and keywords were extracted. The results showed that a variety of external factors were used to construct the SEM models rather than using the parsimonious ones. The reports showed a fair balance between the direct and indirect methods to contact participants. Despite the COVID-19 pandemic, few publications addressed the issue of data collection and evaluation methods, whereas video demonstrations of the augmented reality (AR) apps were utilized. The current work influences new AR researchers who are searching for a theory-based research model in their studies. © 2022 Institute of Advanced Engineering and Science. All rights reserved.

9.
Journal of Information Technology Education-Research ; 21:297-335, 2022.
Article in English | Web of Science | ID: covidwho-1979916

ABSTRACT

Aim/Purpose The purpose of this study is to assess the factors that have significant influences on students' adoption of e-learning systems and to what extent these factors affect them. Background E-learning has become an essential tool and makes it an inevitable option for education in the future. E-learning has received considerable attention in recent times as a global spread of the COVID-19 pandemic. Nevertheless, developing countries, including Vietnam, are facing many difficulties when adopting e-learning systems. Therefore, it is essential to comprehensively evaluate the factors that influence the intention of students to use e-learning to enhance the implementation process and also improve educational quality. Methodology Initially, the authors synthesized a literature review from 112 related studies to complete the proposed research model including the combination of C-TAM-TPB model and external variables impacting students' adoption of e-learning systems. After that, a sample of 172 students at FPT University Vietnam was collected to test the proposed model and explain students' intentions. The dataset was investigated and analyzed with PLS-SEM using the SmartPLS 3.3.3 tool. Contribution The study has made a valuable contribution to the current literature by proposing an extended model between C-TAM-TPB and three external variables to provide a better understanding of learners' intentions with e-learning systems. Furthermore, the research findings also provide useful guidelines for innovating and improving the e-learning system more effectively to advance students' learning motivation in the educational environment. Findings The findings demonstrate that Computer Self-efficacy and Perceived Accessibility have an important influence on Perceived Ease of Use by learners of an e-learning system. Furthermore, Perceived Enjoyment affects the Perceived Usefulness of e-learning systems. For the TAM, Perceived Usefulness and Perceived Ease of Use both have a positive impact on Attitude toward Use, and Attitude has a positive relationship with the Behavioral Intention of students. In addition, the factors from the TPB model (i.e., Perceived Behavioral Control and Subjective Norm) were identified as having a significant positive effect on Behavioral Intention to use e-learning. Recommendations for Practitioners Firstly, educational institutions should help along with the culture of using e-learning among students and lecturers. A supportive team should be accessible to help students use e-learning by providing instructions and addressing their questions. Secondly, system developers should concentrate on system-related aspects that have a significant influence on learners' attitudes and intentions to utilize, as well as build the most appropriate e-learning system for students. Recommendations for Researchers Firstly, the study fulfills a significant literature gap on evaluating e-learning effectiveness for learners in private institutions as they are focusing on developing quality education to gain competitive advantages. Secondly, based on research findings, the researchers may be able to advance studies to improve and innovate a quality system for ensuring the long-term usage of e-learning. Finally, this paper contributes to the theoretical foundation and development of an extended model for future studies to assess the intention when employing new technologies in education and other fields. Impact on Society E-learning will become a necessary tool and an unavoidable possibility in the next period of education. Therefore, this study presents an overview of the factors that have a notable influence on students' intention to adopt e-learning systems. This study then proposes to develop an optimal system for the teaching and learning process, as well as to adapt to future demands. Future Research Firstly, there are just three external variables that are considered to have an impact on learners' intention via TAM. However, other external factors could be exploited in future research. Secondly, the participants in this study are only students. If the lecturers could take part in this survey, the comparisons between faculty and students may have more usefulness for assessment. Thirdly, this model just interprets the results at a certain time, which is the COVID-19 outbreak and e-learning is an urgent response to maintain the process of teaching and learning. The perception, attitude, and performance of students may change over time. Therefore, as other researchers have recommended, longitudinal surveys should be considered here. Finally, the differences between majors may appear. Future studies can divide groups of learners according to their majors for a more significant test.

10.
International Conference on Intelligent Systems and Networks, ICISN 2022 ; 471 LNNS:158-167, 2022.
Article in English | Scopus | ID: covidwho-1971631

ABSTRACT

Wearing masks in public places is an efficient strategy to prevent infection and slow the spread of COVID-19. However, masked face recognition is challenging due to a lack of information about facial features in the masked area. We present a unique Switching Replacement Attention Network (SRAN) for robust face identification based on attention mechanism, which is inspired by the human visual system, which exclusively focuses on non-occluded facial areas. Firstly, a replacement module is established by training a segmentation network to segment the location of the occlusion item. To exclude the corrupted feature components from recognition, we multiply the occluded object’s segmentation mask with the original image features. To determine when the replacement module is applied, we use a lightweight switch module that is both fast and accurate. The proposed technique outperforms state-of-the-art systems on a variety of occluded and non-occluded facial recognition datasets, according to test results. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

11.
Gastroenterology ; 162(7):S-1246, 2022.
Article in English | EMBASE | ID: covidwho-1967426

ABSTRACT

Background Frailty is defined as a clinical state of increased vulnerability to health and age associated stressors. The liver frailty index (LFI), composed of grip strength, chair stand and balance testing, is an accepted predictor of morbidity and mortality in cirrhosis. With the need for COVID-19 related social distancing, many appointments are being carried out virtually. The chair stand subcomponent of the LFI has the potential to be evaluated virtually, with a high reliability as compared to in-person testing noted in other disease populations. Objective To determine if the chair stand test is an independent predictor of morbidity and mortality in patients with cirrhosis. Methods 822 adult patients with cirrhosis were prospectively enrolled from five centers (3 in Canada, 1 in the United States, and 1 in India). Inclusion criteria included adult patients with cirrhosis. 787 of these patients completed a chair stand test at baseline, measured as the time (seconds) a patient takes to rise from sitting with their arms folded across their chest five times (measured in-person). The times were divided into 3 categories: >15 seconds, between 10 and 15 seconds, and <10 seconds. Patients who could not complete 5 chair stands were classified in the >15 seconds category. Primary outcome was all-cause mortality. Secondary outcome was unplanned all-cause hospital admission. Fine-Gray proportional hazard regression models were used to evaluate the association between the chair stand time and the outcomes. We adjusted for baseline age, sex, and MELD score and accounted for liver transplantation as a competing risk. Cumulative incidence functions were used to create a graphical representation of the survival analysis. Results Patients were divided into three groups: group 1, <10 seconds (n = 276);group 2, 10-15 seconds (n = 290);and group 3, >15 seconds (n = 221). Mortality was increased in group 3 in comparison to group 1 (HR 3.21, 95% CI: 2.16-4.78, p<0.001). Similarly, the hazard of non-elective hospitalizations was higher in group 3 in comparison to group 1 (HR 2.24, 95% CI: 1.73-2.91, p<0.001). Overall, patients with chair stand times greater than 15 seconds had increased all-cause mortality (HR 2.78, 95% CI 2.01-3.83, p<0.001) and non-elective hospitalizations (HR 1.84, 95% CI 1.48-2.29, p<0.001) when compared to patients with times less than 15 seconds. Conclusion A time to complete 5 chair stands of >15 seconds predicts morbidity and mortality in patients with cirrhosis. This test shows promise as a frailty measure that could be evaluated over a virtual platform. (Figure Presented)

12.
Dig Dis Sci ; 67(9): 4574-4580, 2022 09.
Article in English | MEDLINE | ID: covidwho-1942113

ABSTRACT

OBJECTIVES: During the summer of 2021, case reports began to emerge documenting a small number of individuals who developed autoimmune hepatitis (AIH) following COVID-19 vaccination. These cases are rare and novel, and very little is known. In our systematic review, we analyzed every published case of AIH and reviewed their characteristic findings, treatment, and outcomes. METHODS: We searched PubMed, Embase, and Web of Science from December 1, 2019, to November 1, 2021. Two researchers independently extracted information from the articles about vaccine type, patient history, laboratory values, histology results, treatment regimens, and disease course. RESULTS: Thirty-two patients developed AIH-like syndromes after receiving a COVID-19 vaccine. Jaundice was the most frequently reported symptom (81%), and 19% of patients were initially asymptomatic and presented with elevated liver enzymes found during routine bloodwork. Mean alanine transaminase, aspartate transaminase, and total bilirubin were 1231 U/L, 921 U/L, and 14 mg/dL, respectively. Anti-nuclear antibody was positive in 56%, and anti-smooth muscle antibody in 28% of patients. Steroids were used in 75% of patients. Improvement or complete resolution was seen in 97% of patients. One patient died despite aggressive steroid treatment. CONCLUSION: COVID-19 vaccine-induced AIH is an uncommon association with just 32 documented cases in the literature. Clinicians should be vigilant for AIH in patients who present with liver injury following vaccination. These new findings should under not deter individuals from getting vaccinated, as the benefits of vaccination far outweigh the risks. Fortunately, COVID-19 vaccine-induced AIH appears amendable to corticosteroid therapy and appears to have a favorable outcome.


Subject(s)
COVID-19 Vaccines , COVID-19 , Hepatitis, Autoimmune , COVID-19/prevention & control , COVID-19 Vaccines/adverse effects , Hepatitis, Autoimmune/diagnosis , Hepatitis, Autoimmune/drug therapy , Hepatitis, Autoimmune/etiology , Humans , Vaccination
13.
European Stroke Journal ; 7(1 SUPPL):172, 2022.
Article in English | EMBASE | ID: covidwho-1928140

ABSTRACT

Background and aims: Administration of thrombolytics (tPA) within the first 60 minutes of presentation for acute Ischemic Stroke is recommended. We utilized a computerized clinical decision support (CCDS) software to identify such patients and created timely alerts to coordinate teams and optimize workflow through a plan-do-study-act (PDSA) based approach. Methods: We reviewed all patients who received thrombolytics for Ischemic Stroke after prospectively implementing the DECISIOInsight software which digitized our institutional stroke protocol in acute Ischemic Stroke patients. The software displayed a countdown doorto- needle (DTN) timer at bedside while sending out automated alerts via TigerConnect (a HIPAA compliant communication tool) every 15 minutes to key patient care providers. We performed PDSA cycles to address systemic issues affecting the delay of care in real time using this CCDS software and workflow modification tool. The primary outcome was DTN time. The secondary outcome was DTN <30 or <45 minutes. Results: 76 patients (46% females, 50% African American, average age of 67 years, median NIHSS of 7.5 and ASPECTS score of 10) received tPA between January 2020 and November 2021. The average time to tPA decreased from 84 minutes (1st Quarter 2020) to 39 minutes (3rd Quarter 2021) (p for trend =0.01). Similarly, the proportion of patients receiving tPA within 45 minutes and within 30 minutes improved from 27.3% to 83.3% (p for trend =0.01) and 0.0% to 41.7% (p for trend =0.006), respectively. Conclusions: Despite the COVID-19 pandemic, the CCDS-based stroke identification and alerting system significantly improved DTN time in ischemic stroke patients.

14.
American Journal of Respiratory and Critical Care Medicine ; 205(1), 2022.
Article in English | EMBASE | ID: covidwho-1927874

ABSTRACT

RATIONALE: Some biomarkers of host response to viral infection are associated with COVID-19 outcomes, but these biomarkers do not directly measure viral burden. The association between plasma viral antigen levels and clinical outcomes has not been previously studied. Our aim was to investigate the relationship between plasma SARS-CoV-2 viral antigen concentration and proximal clinical deterioration in hospitalized patients. METHODS: SARS-CoV-2 nucleocapsid antigen concentrations were measured using a validated microbead immunoassay (Quanterix, NIH/NIAID laboratory) in plasma collected at enrollment from 256 subjects in a prospective observational cohort of hospitalized patients with COVID-19 from 3 hospitals, admitted between March 2020 and August 2021. Relationships between viral antigen concentration and clinical status at 1 week as measured by the World Health Organization (WHO) ordinal scale as well as ICU admission were assessed. Models were adjusted for age and sex, baseline comorbidities including immunosuppression, endogenous neutralizing antibodies, baseline COVID-19 severity, smoking status, remdesivir therapy, steroid therapy, and vaccine status. Missing covariate data were imputed using multiple imputation by chained equations. RESULTS: The median viral antigen concentration for the 35 subjects who deteriorated by 1 week was 4507 (IQR 1225-9665) pg/mL compared to 494 (IQR 18-3882) pg/mL in the 212 subjects who did not (p = 0.0004 Figure a). Using ordinal regression, each doubling in viral antigen concentration was significantly associated with a worse WHO ordinal scale at 1 week (unadjusted OR 1.07, 95% CI 1.02-1.13;adjusted OR 1.10, 95% CI 1.02-1.18). Among 168 patients not in the ICU at baseline, the median viral antigen concentration for the 40 patients who progressed to the ICU was 4697 (IQR 482- 10410) pg/mL vs. 459 (IQR 15-3062) pg/mL in the 128 patients who did not progress to require ICU care (p = 0.0001 Figure b). Using logistic regression, each doubling in viral antigen concentration was significantly associated with ICU admission (unadjusted OR 1.18, 95% CI 1.06-1.32, adjusted OR 1.40, 95% CI 1.11-1.76). CONCLUSIONS: Higher plasma viral antigen concentration at hospital admission is independently associated with a significantly worse clinical status at 1 week and a higher odds of ICU admission among hospitalized patients with COVID-19. This novel finding indicates that plasma viral antigen concentration may identify hospitalized COVID-19 patients at highest risk of short-term clinical deterioration in both clinical practice and research. Results of plasma antigen tests are available within 2-3 hours and could be integrated for identifying hospitalized COVID-19 patients who might benefit from early intervention.

15.
Polymer Composites ; 2022.
Article in English | Scopus | ID: covidwho-1919440

ABSTRACT

With respect to the explosion of single-use plastic packaging consumption during the COVID-19 pandemic, environmentally friendly substitutes are critically needful for sustainable development. Therefore, the present work focuses on the functional properties of bioplastic blends prepared through hot compressing molding of thermoplastic starch (TPS) and spent coffee grounds (SCG) in different ratios (0%–20% SCG) as the potential features of SCG were extensively employed in biocomposites for the first time. The insertion of dark brown SCG into TPS hindered UV transmission by 100% at 320 nm and 99.2% at 400 nm. Moreover, the samples with 15% and 20% SCG induced a surge in radical scavenging activity from 7.95% to over 92% at a concentration of 0.1 g/ml owing to the rich source of antioxidants in SCG. The lignin component and high carbon content also improved the thermal performance of TPS/SCG blends, enhancing thermal stability, delaying onset and maximum degradation temperatures, and achieving the HB rating in the UL-94 test. Compared to a pure TPS matrix, TPS blends incorporating up to 10% SCG exhibited improvement in elastic modulus without deterioration of tensile strength. © 2022 Society of Plastics Engineers.

16.
Journal of Computer Science ; 18(6):453-462, 2022.
Article in English | Scopus | ID: covidwho-1911782

ABSTRACT

Due to the emergence of the COVID-19 pandemic, governments have implemented several urgent steps to minimize the disease’s effect and transmission. Supportive measures to trace contacts and warn people infected with COVID-19 were also implemented such as the COVID-19 contact tracing application. This study investigated the effects of variables influencing the intention to use the COVID-19 tracker. The extended Unified Theory of Acceptance and Use of Technology model was used to investigate user behavior using the COVID-19 tracker application. Google Form was used to construct and distribute the online survey to participants. Experiment results from 224 individuals revealed that performance expectations, trust, and privacy all have an impact on app usage intention. However, social impact, effort expectation, and facilitating conditions were not shown to be statistically significant. The conceptual model explained 60.07% of the amount of variation, suggesting that software developers, service providers, and policymakers should consider performance expectations, trust, and privacy as viable factors to encourage citizens to use the app. This study work’s recommendations and limitations are thoroughly discussed. © 2022. Vinh T. Nguyen and Chuyen T. H. Nguyen. This open-access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.

18.
Journal of Heart and Lung Transplantation ; 41(4):S446-S447, 2022.
Article in English | Web of Science | ID: covidwho-1849046
19.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-334615

ABSTRACT

INTRODUCTION: Assessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment. This study systematically reviewed the strength of evidence in the published COVID-19 policy impact evaluation literature. METHODS: We included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on November 26, 2020 or earlier and screening, all studies were reviewed by three reviewers first independently and then to consensus. The review tool was based on previously developed and released review guidance for COVID-19 policy impact evaluation, assessing what impact evaluation method was used, graphical display of outcomes data, functional form for the outcomes, timing between policy and impact, concurrent changes to the outcomes, and an overall rating. RESULTS: After 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. The majority (n=23/36) of studies in our sample examined the impact of stay-at-home requirements. Nine studies were set aside because the study design was considered inappropriate for COVID-19 policy impact evaluation (n=8 pre/post;n=1 cross-section), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 1/27 studies passed all of the above checks, and 4/27 were rated as overall appropriate. Including the 9 studies set aside, reviewers found that only four of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes. DISCUSSION: The reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigor to be actionable by policymakers. This was largely driven by the circumstances under which policies were passed making it difficult to attribute changes in COVID-19 outcomes to particular policies. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible.

20.
Lecture Notes on Data Engineering and Communications Technologies ; 113:60-67, 2022.
Article in English | Scopus | ID: covidwho-1826246

ABSTRACT

The ongoing COVID-19 has caused a great amount of serious troubles for people around the world. Even though vaccination has been proven to be safe and highly effective against the COVID-19, it is far away to prevent thoroughly the spread of the disease and truly halt the pandemic. Therefore, we need to apply additional methods aside from vaccine injection, such as keeping the distance between people and always using the face masks during the ordinary conversations, in efforts to further reduce the COVID-19 contagion rate. To implement such methods, this research aims to investigate an efficient approach to detect and warn people that they should wear mask whenever they go to public places. Our proposed system studies the benefits of Local Binary Pattern (LBP) and deep learning model to provide accurate face mask detection and classification system. After comprehensive testing, we found that our system provided the detection rate up to 90% with the Kaggle, Face-Mask-Net, and our own datasets. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

SELECTION OF CITATIONS
SEARCH DETAIL