The time between the onset of COVID-19 and the death

The main pandemic this year around the world can be regarded as COVID-19, an extremely serious virus that negatively affect many people. In order to better deal with the virus to save more lives, it is necessary to discover the relationship between the cases and deaths of COVID-19 to promote the plan to prevent and treat people in a desirable time. In this work, the research mainly focusses on the length of the apparent lag between cases and deaths to help governments and organizations in prevention and treatment. As the state with most cases and deaths, the study of the United States is deemed to be typical for the observation whole world. This work focuses on 4 representative states in the America (Michigan, Arizona, Hawaii, Connecticut) to conclude that the time between the onsite of COVID-19 to death is about one to two months through multiple data analysis techniques including linear regression model, time lag analysis to assist the formulation of the plan in prevention and treatment. © 2022 Author(s).

Revision of the child and adolescent COVID-19 stressors scale and Big Data-Based Analysis of Disparities in Urban and Rural Areas

The COVID-19 pandemic imposes a tremendous burden upon society. Several studies have documented stressors and fears of COVID-19 for adult populations, but few studies pay attention to the COVID-19 stressors on children and adolescents. Assessing the stressors of COVID-19 on children and adolescents can provide the basis for interventions to bring children and adolescents' mental health "out of the shadows."Entering the Era of "Big Data,"the psychological state can be assessed through integrative analysis of data. This study adopted a whole-group sampling method. After a new round of the COVID-19 epidemic caused by imported cases in Jiangsu and Fujian provinces of China, self-report questionnaires were sent to children and adolescents aged 10-18 years. 1815 valid questionnaires were collected. Data analysis was performed using SPSS and AMOS software (version 26). To revise and test the reliability and validity of the COVID-19 stressors scale for children and adolescents, as well as to investigate the differences in stressors between rural and urban based on Big-Data Mining. The results of this study indicate that the revised COVID-19 stressors scale, which includes a four-factor model of disease stressors, information stressors, measure stressors, and environmental stressors, has good reliability and validity for children and adolescents aged 10-18 years in a Chinese context. Big data-based demographic analysis showed that children and adolescents living in urban areas were generally less stressed about the COVID-19 epidemic than in rural areas. © 2022 Owner/Author.

Innovative System Design for Remote Air Traffic Control Simulation Training

Conventional ATC simulation training is practice-based training that aims to teach students hands-on experiences before handling real traffic situations in a stressful environment. However, COVID 19 has profoundly affected society and higher education in Australia. It brings enormous challenges to delivering this hands-on practical face-to-face training for students in a typical way. Hence, remote ATC simulation training is emerging in aviation education during COVID. This paper will present an innovative system design for remote ATC simulation training at an Australian university. Firstly, infrastructure upgrading of hardware and software from an existing stand-alone system to a remote network is discussed in detail with consideration of costs, cyber security, system compatibility with the university-wide network;Secondly, preliminary experiment results about the quality of remote ATC simulation training is present by compared with traditional face-to-face training to validate the whole system design;Last but not least, the enhancement of the current remote training system beyond COVID-19 regarding reliability and capacity is listed for future development. This foundation paper will support an understanding of how digital technology can transform STEM practical education during and beyond the COVID-19 pandemic, thereby providing an excellent example for the rest of the world by its leading role in developing advanced ATC training systems for application at a global level. © 2022 IEEE.

Federal Learning Based COVID-19 Fake News Detection With Deep Self-Attention Network

As social media becomes more and more popular, fake news spreads rapidly which is more likely to cause serious consequences, especially during the COVID-19 pandemic. On the premise of meeting data privacy and security requirements, federated learning uses multi-party heterogeneous data to further promote machine learning. This paper proposes a federal learning based COVID-19 fake news detection model with deep self-attention network (FL-FNDM). We construct a deep self-attention network for fake news detection, which combines self-attention-based pretrained model BERT and deep convolutional neural network to detect fake news. Moreover, the fake news detection model is learned under the framework of horizontal federated learning, aiming at protecting users' data security and privacy. The experimental results demonstrate that the proposed model can improve the performance of fake news detection on the COVID-19 dataset, which can achieve almost the same effect of sharing data without leaking user data. © 2021 IEEE.

Identifying Contingency Liability from P3 Contracts Using Rule-Based NLP

The COVID-19 pandemic has increased contractual concerns under contingencies for public- private partnership (P3) projects. Conventional manual contract extraction is time-consuming and error-prone. Devising a method for automatic contract extraction can support contract management in this aspect. This research proposes a rule-based natural language processing (NLP) approach to extracting contingency liabilities allocated between the public sector and the private sector in the contract. The model consists of a domain-specific lexicon developed based on 21 US transportation P3 concession agreements and a set of matching rules to identify target sentences which fall into five classes, namely remedy entitlement, remedy obligation, liability waiver, mitigation, and termination. This automatic process can reduce the time and cost of the contract review process and help identify issues that the contracting parties should consider going forward in drafting new contracts or in amending existing contracts to avoid potential disputes, in response to consequences of contingencies, including the COVID-19 pandemic.

Gynecologic oncology patients are ready for telemedicine in routine care: Results from a pre-COVID survey.

OBJECTIVES: To assess telemedicine readiness of gynecologic oncology patients, particularly those at risk for care access disparities (increased distance to care, rural populations.). METHODS: Patients at all disease/treatment stages completed an anonymous survey during in-person outpatient appointments at an academic comprehensive cancer center from 1/6/2020 to 2/28/2020, conducted prior to the COVID-19 pandemic, before the introduction of telemedicine in this practice. RESULTS: Of 180 patients approached, 170 completed the survey (94.4%). Mean age was 59.6 years; 73.4% identified as White, 23.7% Black, and 2.9% other race. Ovarian cancer was most common (41.2%), followed by endometrial (27.1%), cervical (20.6%), and vaginal/vulvar (7.1%). Most patients traveled > 50 miles for appointments (63.8%); they were more likely from rural counties with significantly higher travel costs/visit ($60.77 vs $37.98, p = 0.026.) The majority expressed interest in using telemedicine (75.7%) or a smartphone app (87.5%) in their care. The majority of patients with difficulty attending appointments (88.9 vs 70.2%, p = 0.02) or from rural counties (88.7% vs 69.6%, p = 0.03) were interested in telemedicine; those with both characteristics reported 100% interest. The majority in both urban and rural counties had home internet access, and reported similarly high rates of daily use (79% vs 75%). Race and age were not associated with differences in internet access or use or telemedicine interest. CONCLUSIONS: Telemedicine is attractive to the majority of patients and may offer financial/logistical advantages. Patients have high internet use rates and comfort with using technology for healthcare. Telemedicine should be incorporated into standard practice beyond the COVID-19 pandemic to reduce healthcare access disparities.

The influence of universal face mask use on endophthalmitis risk after intravitreal antivascular endothelial growth factor injections during the COVID-19 pandemic

Purpose : Routine use of face masks for both patients and physicians during intravitreal anti-vascular endothelial growth factor (VEGF) injections has increased with the emergence of the COVID-19 pandemic. This study evaluates the impact of physician, ancillary staff, and patient face mask use on rates and outcomes of post-injection endophthalmitis. Methods : In this retrospective comparative cohort study, all eye receiving intravitreal antiVEGF factor injections from 10/1/2019 to 7/31/2020 were included from twelve centers. Cases were divided into a no face mask group if no face masks were worn by the physician or patient during intravitreal injections or a universal face mask group if face masks were worn by the physician, ancillary staff, and patient during intravitreal injections. The main outcome measures were rate of endophthalmitis, visual acuity, and microbial spectrum. Results : Of 505,968 intravitreal injections administered, 85 of 294,514 (0.0289%;1 in 3,464 injections) cases of endophthalmitis occurred in the no face mask group, and 45 of 211,454 (0.0213%;1 in 4,699 injections) cases occurred in the universal face mask group (odds ratio, 0.74;95%CI, 0.51-1.18;p=0.097;Table 1). In the no face mask group, there were 27 cases (0.0092%;1 in 10,908 injections) of culture-positive endophthalmitis compared to 9 cases (0.004%;1 in 23,494 injections) in the universal face mask group (OR, 0.46;95%CI, 0.22-0.99;p=0.041). Three cases of oral flora-associated endophthalmitis occurred in the no face mask group (0.001%;1 in 98,171 injections) compared to one (0.0005%;1 in 211,454) in the universal face mask group (p=0.645). At endophthalmitis presentation, mean logMAR visual acuity was 2.04 for no face mask group compared to 1.65 for the universal face mask group (p=0.022), although no difference was observed three months after treatment (p=0.764;Table 2). Conclusions : Universal face mask use during intravitreal anti-VEGF injections did not show a statistically significant reduction in presumed endophthalmitis, but there was a reduced rate of culture-positive endophthalmitis. Future studies are warranted to assess the role of face mask use to reduce endophthalmitis risk, particularly that due to oral flora.

Early Detection of SARS-CoV-2 Seroconversion in Humans with Aggregation-Induced Near-Infrared Emission Nanoparticle-Labeled Lateral Flow Immunoassay

An outbreak of coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses great threats to human health and the international economy. To reduce large-scale infection and transmission risk of SARS-CoV-2, a simple, rapid, and sensitive serological diagnostic method is urgently needed. Herein, an aggregation-induced emission (AIE) nanoparticle (AIE₈₁₀NP, lambda_em = 810 nm)-labeled lateral flow immunoassay was designed for early detection of immunoglobulin M (IgM) and immunoglobulin G (IgG) against SARS-CoV-2 in clinical serum samples. Using a near-infrared (NIR) AIE nanoparticle as the fluorescent reporter (lambda = 145 nm), the autofluorescence from the nitrocellulose membrane and biosample and the excitation background noise were effectively eliminated. After optimization, the limit of detection of IgM and IgG is 0.236 and 0.125 mug mL^-1, respectively, commensurate with that of the enzyme-linked immunosorbent assay (ELISA) (0.040 and 0.039 mug mL^-1). The sensitivity of the proposed AIE₈₁₀NP-based test strip for detecting IgM and IgG is 78 and 95% (172 serum samples), commensurate with that of ELISA (85 and 95%) and better than that of a commercial colloidal gold nanoparticle (AuNP)-based test strip (41 and 85%). Importantly, the time of detecting IgM or IgG with an AIE₈₁₀NP-based test strip in sequential clinical samples is 1-7 days after symptom onset, which is significantly earlier than that with a AuNP-based test strip (8-15 days). Therefore, the NIR-emissive AIE nanoparticle-labeled lateral flow immunoassay holds great potential for early detection of IgM and IgG in a seroconversion window period.

Side effects of lopinavir/ritonavir for COVID-19

AIM: To study the regularity and characteristics of side effects of lopinavir/ritonavir for COVID-19. METHODS: The type of side effects, general information, medical history and prognosis in 61 confirmed and suspected COVID-19 patients with lopinavir/ritonavir were analyzed. RESULTS: Among the 61 patients, 41(67.21%) had lopinavir/ritonavir related side effects, mainly manifested as gastrointestinal reactions (82.93%) and liver function damage (53.66%). Old age, long course of disease and chronic gastrointestinal disease are independent risk factors for side effects. CONCLUSION: Lopinavir/ritonavir has a high incidence of side effects and can be used in COVID-19 patients under the condition of close observation of the patient's symptoms and test results. Special population should improve pharmaceutical care to ensure the safety of drug use.