PQSCT: Pseudo-Siamese BERT for Concept Tagging With Both Questions and Solutions

The global outbreak of the new coronavirus epidemic has promoted the development of intelligent education and the utilization of online learning systems. In order to provide students with intelligent services such as cognitive diagnosis and personalized exercises recommendation, a fundamental task is the concept tagging for exercises, which extracts knowledge index structures and knowledge representations for exercises. Unfortunately, to the best of our knowledge, existing tagging approaches based on exercise content either ignore multiple components of exercises, or ignore that exercises may contain multiple concepts. To this end, in this paper, we present a study of concept tagging. First, we propose an improved pre-trained BERT for concept tagging with both questions and solutions (QSCT). Specifically, we design a question-solution prediction task and apply the BERT encoder to combine questions and solutions, ultimately obtaining the final exercise representation through feature augmentation. Then, to further explore the relationship between questions and solutions, we extend the QSCT to a pseudo-siamese BERT for concept tagging with both questions and solutions (PQSCT). We optimize the feature fusion strategy, which integrates five different vector features from local and global into the final exercise representation. Finally, we conduct extensive experiments on real-world datasets, which clearly demonstrate the effectiveness of our proposed models for concept tagging. IEEE

The impact of oxygen supply flow rates on the distribution of aerosols between the patient and the surgeon during lung intubation

The outbreak of COVID-19 has caused a worldwide pandemic. The widespread infection of the medical staff has caused great attention from all quarters of society. There is a particular concern when considering intubation treatment in the emergency operating room, where a significant amount of virus droplets are typically spread within the room, exposing the medical staff to a high risk of infection. Hence, there is currently a pressing need to develop an effective protection mechanism for the medical staff to prevent them from being infected during routine work. In order to understand the spread of droplets and aerosols when different oxygen supply devices are used for intubation therapy, this study uses particle image velocimetry (PIV) technology to analyze the airflow distribution between the medical staff and the patient. In the experiment, a simple version of the respirator was established to reproduce the breathing of human lungs. This model used oil to create smoke as a tracer aerosol, then a high-sensitivity camera was used to record the scattering light from this smoke (which is irradiated by the green laser sheet). Ultimately, after applying post-processing techniques, the airflow distribution is analyzed. PAO aerosol is the primary aerosol source in this experiment, and it is used to quantify the patient's breathing;the concentration of PAO aerosol was measured at three different points: head, trunk, and feet. In addition, flow field visualization can effectively present the flow field distribution of the entire operating room;also, the results can be mutually verified with the PAO concentration measurement results. Aerosol concentrations were measured for six different oxygen supply devices with various tidal volumes of the artificial respirator, and the results were ranked from high to low concentrations for different oxygen supply devices and their operational oxygen supply flowrates: HFNC (70 l/min) > CPAP (40 l/min) > HFNC (30 l/min) > nasal cannula (15 l/min) > NRM (15 l/min) > VAPOX (28 l/min). © 2022, The Author(s).

Humoral immune responses to SARS-CoV-2 vaccines in an ozanimod open-label extension study

Background: Ozanimod, an oral sphingosine 1-phosphate receptor modulator, is approved in the European Union and United States for the treatment of moderately to severely active ulcerative colitis (UC) and relapsing multiple sclerosis (RMS). A previous analysis of data from UC and multiple sclerosis (MS) open-label extension (OLE) studies showed that most patients with confirmed coronavirus infection (COVID-19) had nonserious infections, recovered, and did not require ozanimod discontinuation. Some immunomodulators and biologics may attenuate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine response;therefore, this analysis evaluated humoral immune responses and predictors of response to SARS-CoV-2 vaccination in patients with RMS treated with ozanimod. Method(s): RMS participants who completed a phase 1-3 ozanimod trial could enter an OLE trial (DAYBREAK;NCT02576717) of ozanimod 0.92 mg/d. This analysis (January 2020-October 2021) included DAYBREAK participants receiving mRNA or non-mRNA SARS-CoV-2 vaccines (1-2 doses, vaccine-dependent) with no evidence of recent infection (ie, nucleocapsid antibody negative). Receptor binding domain (RBD) antibody titers were analysed (Elecsys Anti-SARS-CoV-2 assay;Roche Diagnostics, Basel, Switzerland) prevaccination, after 1 dose, and <4, 4-8, 8-12, and >12 weeks after full vaccination. Fisher's exact tests and regression models determined association with seroconversion and log2 antibody levels. Result(s): Demographics were similar between the mRNA and nonmRNA vaccine recipients (Table). Seroconversion (>=0.8 U/mL spike RBD antibody) occurred in 100% (80/80) of fully vaccinated mRNA recipients and 62% (18/29) of fully vaccinated non-mRNA vaccine recipients. Higher spike RBD antibody levels were seen with mRNA (grand mean: 512.6 U/mL, range: 1.3-4572.0) vs non-mRNA (grand mean: 39.3 U/mL, range: 0.4-368.5) vaccines at all time points studied. Vaccination with a non-mRNA vaccine predicted lower antibody levels (beta: -5.90 [95% CI: -6.99 to -4.82];P<0.0001) and less seroconversion (Fisher's exact: P<0.0001), whereas age, sex, body mass index, and absolute lymphocyte count (ALC) did not. Conclusion(s): Participants receiving ozanimod developed humoral immune response to SARS-CoV-2 vaccines, with 100% seroconversion after mRNA vaccination;this was independent of demographic characteristics and ALC levels at time of vaccination. However, some participants developed lower antibody concentrations and may benefit from booster doses. These findings provide important information for physicians managing ozanimod-treated patients with UC or MS.

Lipid-Based Poly(I:C) Adjuvants Strongly Enhance the Immunogenicity of SARS-CoV-2 Receptor-Binding Domain Vaccine

Background The outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has greatly threatened public health. Recent studies have revealed that the spike receptor-binding domain (RBD) of SARS-CoV-2 is a potent target for vaccine development. However, adjuvants are usually required to strengthen the immunogenicity of recombinant antigens. Different types of adjuvants can elicit different immune responses. Methods We developed an RBD recombinant protein vaccine with a polyriboinosinic acid-polyribocytidylic acid [poly(I:C)] adjuvant to evoke a strong immune response. The delivery of poly(I:C) was optimized in two steps. First, poly(I:C) was complexed with a cationic polymer, poly-l-lysine (PLL), to form poly(I:C)-PLL, a polyplex core. Thereafter, it was loaded into five different lipid shells (group II, III-1,2-distearoyl-sn-glycero-3-phosphocholine [DSPC], III-1,2-dioleoyl-sn-glycero-3-phosphoethanolamine [DOPE], IV-DOPE, and IV-DSPC). We performed an enzyme-linked immunosorbent assay and enzyme-linked immunosorbent spot assay to compare the ability of the five lipopolyplex adjuvants to enhance the immunogenicity of the SARS-CoV-2 RBD protein, including humoral and cellular immune responses. Finally, the adjuvant with the highest immunogenicity was selected to verify the protective immunity of the vaccine through animal challenge experiments. Results Recombinant RBD protein has low immunogenicity. The different adjuvants we developed enhanced the immunogenicity of the RBD protein in different ways. Among the lipopolyplexes, those containing DOPE (III-DOPE and IV-DOPE) elicited RBD-specific immunoglobulin G antibody responses, and adjuvants with four components elicited better RBD-specific immunoglobulin G antibody responses than those containing three components (P < 0.05). The IC50 and IC90 titers indicated that the IV-DOPE lipopolyplex had the greatest neutralization ability, with IC50 titers of 1/117,490. Furthermore, in the challenge study, IV-DOPE lipopolyplex protected mice from SARS-CoV-2 infection. On the fourth day after infection, the average animal body weights were reduced by 18.56% (24.164 ± 0.665 g vs. 19.678 ± 0.455 g) and 0.06% (24.249 ± 0.683 g vs. 24.235 ± 0.681 g) in the MOCK and vaccine groups, respectively. In addition, the relative expression of viral RNA in the vaccinated group was significantly lower than that in the MOCK group (P < 0.05). Interstitial inflammatory cell infiltration was observed in the MOCK group, whereas no obvious damage was observed in the vaccinated group. Conclusions The IV-DOPE-adjuvanted SARS-CoV-2 recombinant RBD protein vaccine efficiently protected mice from SARS-CoV-2 in the animal challenge study. Therefore, IV-DOPE is considered an exceptional adjuvant for SARS-CoV-2 recombinant RBD protein-based vaccines and has the potential to be further developed into a SARS-CoV-2 recombinant RBD protein-based vaccine. © Wolters Kluwer Health, Inc. All rights reserved.

Pandemic, tourism, and the economy: a tourism-revenue target zone approach

The COVID-19 pandemic has negatively affected the tourist markets of many countries. This study develops a small, open macro model of tourism to analyze the price and revenue effects of establishing tourism target zones on tourism revenue in response to industry disturbances resulting from the pandemic. Such target zones improve tourism revenue and stabilize the economy by stabilizing tourism goods prices and exchange rates when domestic or foreign demand is strong and regardless of whether national borders are open. A tourism goods price subsidy can be employed to revitalize the tourism industry and improve tourism revenue after the pandemic. © 2023 City University of Hong Kong and National Taiwan University.

Research on user satisfaction of sports and healthcare integration system in post-pandemic era

After COVID-19, some initiatives such as Healthy China, and Smart Living have been widely mentioned. This study explored the factors influencing user satisfaction in sports and healthcare integration services to help system builders and interaction designers better seek opportunities and directions for systems construction. Based on grounded theory method, conducted semi-structured interviews with people who have home exercise needs, and then summarised the influencing factors after coding the raw information level by level. It applied the user experience honeycomb to classify potential variables, used principal component analysis (PCA) to extract representative evaluation indicators as observed variables, and followed the construction of a theoretical model of the satisfaction factors. The structural equation model (SEM) was validated and analyzed to prove its scientific validity and reasonableness. Research showed that the core factors affecting the user experience of sports and healthcare integration system include usefulness, interactivity, usability, credibility, and findability, all of which have a positive and significant impact on user satisfaction. According to the results of empirical analysis, A multidimensional design strategy for sports and healthcare integration system is proposed to provide a reference for improving user satisfaction. © 2023 - IOS Press. All rights reserved.

Impact of Survey Setting on Current Tobacco Product Use: National Youth Tobacco Survey, 2021.

PURPOSE: To examine whether survey setting was associated with youth reporting of current (past 30-day) use of any tobacco product, e-cigarettes, cigarettes, and cigars. METHODS: Data from the 2021 National Youth Tobacco Survey (NYTS) were used to estimate the prevalence of current use of any tobacco product, e-cigarettes, cigarettes, and cigars by survey setting, sociodemographic characteristics, peer tobacco use, and other tobacco product use. Multivariable regression was used to test the impact of survey setting on current tobacco use. Tobacco access sources among current users were compared by survey setting. RESULTS: Among students who participated in the 2021 NYTS, 50.8% reported taking the survey on school campus and 49.2% at home/other place. The prevalence of current use of any tobacco product, e-cigarettes, cigarettes, and cigars was higher among students completing the survey on school campus than at home/other place. After adjusting for covariates, this association persisted only for current use of any tobacco product (adjusted odds ratio = 1.57; 95% confidence interval, 1.28-1.91) and e-cigarettes (adjusted odds ratio = 1.43; 95% confidence interval, 1.20-1.71). Current users reported similar sources of access to tobacco products, regardless of survey setting. DISCUSSION: The likelihood of youth reporting current use of any tobacco product and e-cigarettes differed by survey setting. Such differences could be due to lack of privacy at home, peer influence in school settings, and other unmeasured characteristics. Methodological changes were made due to COVID-19; caution is warranted in comparing results from the 2021 NYTS with those of previous or future NYTS conducted primarily on school campus.

A Study on Functional Satisfaction with Smart Health Care Air Purification Product in the Post-epidemic Era

In the context of the COVID-19, respiratory diseases have become the focus of social attention, and the elderly, as a susceptible population, is more significantly affected by the epidemic. In order to fully protect the respiratory system of the elderly and enhance their satisfaction with the function of smart products, this study proposes a design method for smart health care product based on the cognitive behavior of elderly users. Firstly, the user demand gap is explored and determined by using the A-Kano model;secondly, a functional model is created based on the FAST functional theory. After converting the user demand into function, and then the TRIZ theory is applied to choose to use 40 invention principles and 39 general engineering parameters to analyze the problem and get conflict domain solutions, so as to filter out the most ideal solution and innovate its function;Finally, by the design and practice of the smart health care air purification product, its purification range, monitoring data and wearing method will be effectively optimized, and the feasibility of the design solution will be verified by the user interaction satisfaction questionnaire. The study provides new ideas for the design of smart health care products and the solutions of contradictory problems, which would also be a theoretical guidance for relevant designer and researchers. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Serologic Response and Clinical Outcomes of SARSCoV-2 Infection and Vaccination in Ozanimod-Treated Participants With Relapsing Multiple Sclerosis

Introduction: Multiple sclerosis disease-modifying therapies, including sphingosine 1-phosphate receptor modulators, may attenuate the response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or vaccination. Objective(s): To describe the serological response and clinical outcomes of SARS-CoV-2 infection and vaccination in ozanimodtreated participants with relapsing multiple sclerosis (RMS) in an open-label extension (OLE) trial. Method(s): Participants with RMS who completed a phase 1-3 ozanimod trial could enter an OLE trial (DAYBREAK-NCT02576717) of ozanimod 0.92 mg/d. This analysis (January 2020-October 2021 [serology] and January 2022 [clinical outcomes]) included DAYBREAK participants who received SARSCoV-2 vaccines (fully vaccinated) and/or had COVID-19 adverse events. Receptor binding domain (RBD) antibody levels and nucleocapsid antibody positivity were analysed using Roche Elecsys assays. Log2 RBD antibody levels were compared between groups using t-tests. Result(s): Among the 148 vaccinated participants with serological data, 39 participants had serologically confirmed SARS-CoV-2 exposure. After full vaccination, RBD seroconversion occurred in 100% (n=39/39) of nucleocapsid antibody positive and most (n=98/109) nucleocapsid antibody negative participants (with 100% seroconversion in nucleocapsid antibody negative participants receiving mRNA vaccines [n=80/80]). Significantly higher RBD antibody levels were observed in the vaccinated nucleocapsid antibody positive vs negative vaccinated participants (median [range], U/mL: 2259 [12.4-44260.0] vs 138 [0.4-4572.0], respectively, P<0.0001). COVID-19 adverse events were reported in 15/148 participants, all nonserious events (confirmed=12, suspected= 3). Ozanimod treatment was continued in 9 participants and interrupted in 5 (1 unknown). Eleven participants recovered by the time of data cut off, and one recovered with sequelae (cough and loss of sense of smell). Conclusion(s): Participants with RMS receiving ozanimod mount a serologic response to SARS-CoV-2 infection and vaccination. COVID-19 events in these fully vaccinated participants were nonserious. A limitation of this research is its retrospective nature and the potential for selection bias towards higher-risk individuals.

Measurements of Exhaled Airflow Velocity Via Human Coughs Using Particle Image Velocimetry (PIV)

The sudden global outbreak of coronavirus diseases 2019 (COVID-19) has infected over seventy million people and resulted in over one million deaths by the end of 2020, posing a significant threat to human health. As potential carries of the novel coronavirus, exhaled airflow of infected individuals via coughs, are significant in virus transmission. This study measures human coughs' airflow velocity in a chamber filled with stage fog employing a particle image velocimetry (PIV) system. The purpose of this study is to examine and provide accurate boundary conditions for the prediction of the virus transmission routes using computational fluid dynamics (CFD) simulations. Sixty cough cases from ten healthy nonsmoking volunteers (five male and five female, averaged age of 29.3 +/- 4.0) are taken respectively, and ensemble-average operations are conducted to eliminate individual variations. Velocity distribution measurements are obtained in the vertical and horizontal planes around the mouth area. Temporal and spatial cough flow ensemble-averaged velocity profiles and standard deviations, cough duration time (CDT), peak velocity time (PVT), maximum cough velocities, and average spread angle of the cough jet are measured. Results show that the CDT of the cough airflow is 520-560 ms, and PVT is 20 ms. The male/ female averaged maximum velocity is 15.2/13.1 m/s, respectively. The average vertical/horizontal spread angle from the mouth is 15.3 degrees/13.3 degrees for males and 15.6 degrees/14.2 degrees for females, respectively. With the measurement data, it is possible to refine the initial boundary conditions of a simulated cough and model cough flows more accurately.

When Edge Computing Meets Agile Software Development

Agile development has been a common methodology in software development. In response to the covid-19, most software development teams choose to work remotely. As a result of the different network environments, the company cloud center network load cannot meet the requirements of remote development and fault tolerance requirements of the agile development process. We designed a mixed-method called the Edge Development approach for improving Agile software development during the decision-making process. The extensive literature review provided us with three categories of challenges as well as solutions to support Edge Development's decision-support process. In the light of the survey, Five main software development decision-making challenges were identified in this study. In addition, we made a series of recommendations to improve the decision-making process of Edge Development from a variety of perspectives. © 2022 IEEE.

Investigating the First Robotic Nurses: Humanoid Robot Nightingale and Partners for COVID-19 Preventive Design

Responding to these global COVID-19 changes for daily healthcare services clinic, while maintaining safe social distancing, the paper reports the human-centred iterative design with real-fields feasibility inquiries to investigate the first robotic nurse and her partners in Wales. The research adapted the ancient Eastern human nature of seven emotions and six biological wills for the selection criteria and novel design principles for the care robots. We report the preliminary work for integrating, customising, implementing and evaluating three novel robotic nurses: Robot Nightingale, Robot Almeida and Robot Eureka in a care home and a hospital. Bionic Scenarios Definition with 5 merging principles are extracted from the Feasibility Inquiries 1–3. Limitations are discussed from the stakeholders’ experiences. Our research has no intension to replace human nurses, but a thoughtful feasibility and interdisciplinary study for bionic robotic nurses for conventional engineers’ and practitioners’ references. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Detection of SARS-CoV-2 Variants of Concern with Tiling Amplicon Sequencing from Wastewater

The emerging variants of concern (VOCs) of SARS-CoV-2, e.g., Alpha, Beta, Gamma, Delta, and Omicron, have constrained the global response to the COVID-19 pandemic. They challenge our current capability to identify and distinguish variants from wastewater, due to the high likelihood of viral RNA degradation and the prior knowledge required for primer design. This study focused on the detection of multiple VOCs of SARS-CoV-2 using a high-throughput, multiplexed, amplicon-based sequencing technology, namely, ATOPlex. We first demonstrated that this method can discern multiple variants from artificial samples consisting of four synthetic strains of SARS-CoV-2. The ability of ATOPlex to identify VOCs was further validated using real wastewater samples collected from both an international passenger flight and local wastewater treatment plants. On the basis of phylogenetic analysis and the identification of single-nucleotide polymorphism on the genomes, the ATOPlex method was shown to be effective in detecting three VOCs, including two Beta variants and one Delta variant from either local wastewater or flight sewage samples, which were phylogenetically close to the variants that originated from France, Philippines, and the United States. We found this method is mutation-independent, rendering it a tool for proactive detection of SARS-CoV-2 VOCs in wastewater for the application of wastewater-based epidemiology.

Employer requirements and COVID-19 vaccination and attitudes among healthcare personnel in the U.S.: Findings from National Immunization Survey Adult COVID Module, August - September 2021.

INTRODUCTION: Employer vaccination requirements have been used to increase vaccination uptake among healthcare personnel (HCP). In summer 2021, HCP were the group most likely to have employer requirements for COVID-19 vaccinations as healthcare facilities led the implementation of such requirements. This study examined the association between employer requirements and HCP's COVID-19 vaccination status and attitudes about the vaccine. METHODS: Participants were a national representative sample of United States (US) adults who completed the National Immunization Survey Adult COVID Module (NIS-ACM) during August-September 2021. Respondents were asked about COVID-19 vaccination and intent, requirements for vaccination, place of work, attitudes surrounding vaccinations, and sociodemographic variables. This analysis focused on HCP respondents. We first calculated the weighted proportion reporting COVID-19 vaccination for HCP by sociodemographic variables. Then we computed unadjusted and adjusted prevalence ratios for vaccination coverage and key indicators on vaccine attitudes, comparing HCP based on individual self-report of vaccination requirements. RESULTS: Of 12,875 HCP respondents, 41.5% reported COVID-19 vaccination employer requirements. Among HCP with vaccination requirements, 90.5% had been vaccinated against COVID-19, as compared to 73.3% of HCP without vaccination requirements-a pattern consistent across sociodemographic groups. Notably, the greatest differences in uptake between HCP with and without employee requirements were seen in sociodemographic subgroups with the lowest vaccination uptake, e.g., HCP aged 18-29 years, HCP with high school or less education, HCP living below poverty, and uninsured HCP. In every sociodemographic subgroup examined, vaccine uptake was more equitable among HCP with vaccination requirements than in HCP without. Finally, HCP with vaccination requirements were also more likely to express confidence in the vaccine's safety (68.3% vs. 60.1%) and importance (89.6% vs 79.6%). CONCLUSION: In a large national US sample, employer requirements were associated with higher and more equitable HCP vaccination uptake across all sociodemographic groups examined. Our findings suggest that employer requirements can contribute to improving COVID-19 vaccination coverage, similar to patterns seen for other vaccines.

Aerosol presence reduces the diurnal temperature range: An interval when the COVID-19 pandemic reduced aerosols revealing the effect on climate

The immense reduction in aerosol levels during the COVID-19 pandemic provides an opportunity to reveal how atmospheric chemistry is regulating our climate, among which the effect of aerosols on climate is a phenomenon of great interest but still in hot debate. The Intergovernmental Panel on Climate Change (IPCC) has continually identified the effect of aerosols on climate to have the largest uncertainty among the factors contributing to global climate change. Several studies indicate an inverse relationship between aerosol presence in the atmosphere and the diurnal surface air temperature range (DTR). Herein, we test this relationship by analyzing the DTR values from in situ weather station records for periods before and during the COVID-19 epidemic in Chinawhere aerosol levels have substantially reduced, compared with the climatological mean levels for a 19 year period.Our analyses find that DTRs fromFebruary to June during the COVID-19 pandemic are greater than 3 standard deviations above the climatological mean DTR. This anomaly has never occurred before in the 21st century and is at least in part associated with the observed reduction in aerosols. © 2021 The Author(s).

Two Applications of Machine Learning on COVID-19

In December 2019, a new virus called COVID-19 broke out, and in 2020, it rapidly spread all over the world. The fast rate of the spread of the virus and high mortality have brought severe harm to the health of people and the economy of almost all countries around the world. Therefore, the virus has become the object of much researches. As the study moving on, treatment and vaccine have become the leading research directions at present. For treatment, measures should be taken to protect the most severe patients to reduce the death rate, and thus we are supposed to find patients with more serious illnesses. The decision tree and Xgboost are used to get the mathematical model about protease (an essential index in judging the severity of the disease) and realize the visualization of protease data. For vaccine, we solve the problem of predicting COVID-19 Vaccination Progress in the world in 2021 using the ARIMA model, which is obtained through the mean of time-series. Eventually, we got 10-day and 3-month vaccination forecasts. © 2022 SPIE

Medical image feature extraction and visualization based on principal component analysis

In view of the problem that it is difficult to extract and analyze the medical image feature information, this paper investigates a feature extraction and visualization method of medical image based on principal component analysis. Firstly, the medical image feature extraction and space conversion mechanism is analyzed, and the feature information from the original spatial dimensions of medical images is extracted by using PCA technology. Then the extracted feature image is effectively reconstructed and visualized. The method is verification through COVID-19 CT images, results show that when the cumulative contribution rate of the principal component reaches 85%, the principal component analysis method can restore the information of the original image more clearly, and realize the feature extraction and visual reconstruction of medical images. © 2021 IEEE.