DBF-Net: a semi-supervised dual-task balanced fusion network for segmenting infected regions from lung CT images.

Accurate segmentation of infected regions in lung computed tomography (CT) images is essential to improve the timeliness and effectiveness of treatment for coronavirus disease 2019 (COVID-19). However, the main difficulties in developing of lung lesion segmentation in COVID-19 are still the fuzzy boundary of the lung-infected region, the low contrast between the infected region and the normal trend region, and the difficulty in obtaining labeled data. To this end, we propose a novel dual-task consistent network framework that uses multiple inputs to continuously learn and extract lung infection region features, which is used to generate reliable label images (pseudo-labels) and expand the dataset. Specifically, we periodically feed multiple sets of raw and data-enhanced images into two trunk branches of the network; the characteristics of the lung infection region are extracted by a lightweight double convolution (LDC) module and fusiform equilibrium fusion pyramid (FEFP) convolution in the backbone. According to the learned features, the infected regions are segmented, and pseudo-labels are made based on the semi-supervised learning strategy, which effectively alleviates the semi-supervised problem of unlabeled data. Our proposed semi-supervised dual-task balanced fusion network (DBF-Net) creates pseudo-labels on the COVID-SemiSeg dataset and the COVID-19 CT segmentation dataset. Furthermore, we perform lung infection segmentation on the DBF-Net model, with a segmentation sensitivity of 70.6% and specificity of 92.8%. The results of the investigation indicate that the proposed network greatly enhances the segmentation ability of COVID-19 infection.

Understanding citizens' satisfaction with the government response during the COVID-19 pandemic in China: comprehensive analysis of the government hotline

PurposeThe objective of this study was to analyse the influencing factors of citizens' dissatisfaction with government services during the COVID-19 pandemic to help government departments identify problems in the service process and possible countermeasures.Design/methodology/approachThe authors first used cosine interesting pattern mining (CIPM) to analyse citizens' complaints in different periods of the pandemic. Second, the potential evaluation indices of customer satisfaction were extracted from the hotline business system through a hypothesis analysis and modelled using multiple regression analysis. During the index transformation and standardization process, a machine-learning algorithm of clustering and emotion analysis was adopted. Finally, the authors used the random forest algorithm to evaluate the importance of the indicators and obtain the indicators more important to citizen satisfaction.FindingsThe authors found that the complaint topic, appeal time, urgency of citizens' complaints, citizens' emotions, level of detail in the case record, and processing timeliness and efficiency significantly influenced citizens' satisfaction. When the government addresses complaints in a more standardized and efficient manner, citizens are more satisfied.Originality/valueDuring the pandemic, government departments should be more patient with citizens, increase the speed of the case circulation and shorten the processing period of appeals. Staff should record appeals in a more standardized manner, highlighting themes and prioritizing urgent cases to appease citizens and relieve their anxiety.

Understanding changing public transit travel patterns of urban visitors during COVID-19: A multi-stage study

COVID-19 has caused huge disruptions to urban travel and mobility. As a critical transportation mode in cities, public transit was hit hardest. In this study, we analyze public transit usage of urban visitors with a nearly two-year smart card dataset collected in Jeju, South Korea – a major tourism city in the Asia Pacific. The dataset captures transit usage behavior of millions of domestic visitors who traveled to Jeju between January 1, 2019 and September 30, 2020. By identifying a few key pandemic stages based on COVID-19 timeline, we employ ridge regression models to investigate the impact of pandemic severity on transit ridership. We then derive a set of mobility indicators – from perspectives of trip frequency, spatial diversity, and travel range – to quantify how individual visitors used the transit system during their stay in Jeju. By further employing time series decomposition, we extract the trend component for each mobility indicator to study long-term dynamics of visitors' mobility behavior. According to the regression analysis, the pandemic had a dampening effect on public transit ridership. The overall ridership was jointly affected by national and local pandemic situations. The time series decomposition result reveals a long-term decay of individual transit usage, hinting that visitors in Jeju tended to use the transit system more conservatively as the pandemic endured. The study provides critical insights into urban visitors' transit usage behavior during the pandemic and sheds light on how to restore tourism, public transit usage, and overall urban vibrancy with some policy suggestions.

Exploring the audiovisual effects on sport viewer satisfaction through the lens of the psychological continuum model

As the source of one of the largest revenue streams for professional sport franchises, the viewership of sport broadcasts has plummeted in recent years (Bode, 2018). This declining trend has been further exacerbated by the global COVID-19 pandemic (Crupi, 2021). According to Deloitte's Fan Engagement survey, the average fan satisfaction across sports broadcast programs was only 39 percent (Deloitte, 2019).Research has been devoted to investigating the determinants of sport viewer satisfaction, including various audio and visual conditions of sport broadcasts. However, these works assume that media design effects are equally effective among all viewers and fail to account for potential heterogeneities in people's psychological connection to the mediated sport. To address this gap, the Psychological Continuum Model (PCM;Funk & James, 2001;2006) was introduced as the theoretical foundation for understanding the formation of viewer satisfaction with a focal sport (e.g., college football).The current dissertation examines whether and how the strength of psychological connection to college football overrides the effects of varying audiovisual presentations on viewer satisfaction with a televised college football game. A 2 (presence of commentary: With commentary vs. Without commentary) x 2 (presence of audience: High vs. Low) between-subjects online experiment was administered via Prolific (n = 338). The relationship between psychological connection and viewer satisfaction and the moderation effects of the two selected audiovisual conditions were tested using the ANCOVA. Results showed a significant positive association between psychological connection to college football and viewer satisfaction. However, the manipulated audiovisual conditions did not moderate the aforementioned relationship between psychological connection and viewer satisfaction. The presence of audience had a significant positive effect on viewer satisfaction. In contrast, the presence of commentary exerted no significant effect on viewer satisfaction regardless of people's PCM staging.The findings provide empirical evidence to support the seminal PCM framework that the strength of an individual's psychological connection to the focal sport object was a more deterministic factor that drives the sport media consumption experience than the audiovisual media presentation. For those interested in watching but have not yet formed a strong attitude towards the broadcasted sport object, the viewing experience can be optimized by maximizing the visual presence of a live audience. The null effect of commentary presence and sonic ambiance on viewer satisfaction reinforces the proposition that what is seen might be more influential than what is heard in sport media consumption (Cummins et al., 2019). (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Remdesivir for COVID-19 and acute kidney injury: disproportionality analysis of data from the U.S. Food and Drug Administration Adverse Event Reporting System.

BACKGROUND: Evidence about remdesivir-associated acute kidney injury (AKI) among patients with novel coronavirus disease 2019 (COVID-19) was controversial. AIM: To investigate the signal of disproportionate reporting of remdesivir-related AKI in COVID-19 patients over time with data from US Food and Drug Administration Adverse Event Reporting System. METHOD: Adverse events in COVID-19 patients reported between April 2020 and September 2022 were included. Reporting odds ratios (RORs) of AKI and renal disorders (a more sensitive definition for AKI) were estimated to compare remdesivir with other medications prescribed in comparable situations of COVID-19. RESULTS: During the entire study period, significant signals were identified for remdesivir-related AKI (ROR 2.00, 95% CI: 1.83-2.18) and renal disorder (ROR 2.35, 95% CI: 2.17-2.54) when compared to all comparable drugs. However, in the third quarter of 2022 (the most recent quarter) signals disappeared as the ROR of AKI was 1.50 (95% CI 0.91-2.45) and ROR of renal disorder was 1.69 (95% CI 1.06-2.70). Number of signals in sensitivity analyses and the proportion of AKI in remdesivir-associated events decreased over time. CONCLUSION: In COVID-19 patients, we observed diminishing signals of remdesivir-associated AKI over time and no significant signal in the most recent quarter, suggesting remdesivir might not be nephrotoxic.

Impact of primary emission variations on secondary inorganic aerosol formation: Prospective from COVID-19 lockdown in a typical northern China city.

Hourly observations in northern China city of Taiyuan were performed to compare secondary inorganic aerosol (SIA) reaction mechanisms, and emission effects on SIA during the pre-lock and COVID-19 lock days. Emission control implemented and meteorological conditions during lock days both caused beneficial impact on air quality. NO2 showed the highest decrease ratio of -49.5%, while the relative fraction of NO3- in PM2.5 increased the most (2.7%). Source apportionment revealed the top three contributors to PM2.5 were secondary formation (SF), coal combustion (CC), and vehicle exhaust (VE) during both pre-lock and lock days. EC lock/pre were all lower than 1, suggesting the overall reduction of primary emissions during lock days, while the higher ratio of (SIA/EC) lock/pre (1.01-1.36) indicated the enhanced secondary formation in lock days. The ratio of SIA of pollution to clean days during lock periods considerably higher by 23.7% compared with that in pre-lock periods, which was indicated SIA secondary formation was more pronounced and contributed great to pollution days in lock periods though secondary formation existed in pre-lock and lock periods. Enhanced secondary formation of NO3- and SO42- during lock days might be mainly due to the increased in aqueous and gas-phase reactions, respectively. Except for SF, high contribution of VE and CC were also important for high SIA concentration in pre-lock and lock days, respectively. The decreased contribution of VE weakens its contribution to SIA formation, indicating the effectiveness of VE emission control, as confirmed during the COVID-19 pandemic. This study highlights the aqueous and gas-phase reactions for nitrate and sulfate, respectively, which contributed to heavy pollution, as well as indicated the important role of VE on SIA formation, suggesting the urgent need to further strengthen controls on vehicle emissions.

Pembrolizumab combined with axitinib in the treatment of skin metastasis of renal clear cell carcinoma to nasal ala: A case report.

BACKGROUND: Renal clear cell carcinoma (RCC) is a malignant tumor of the genitourinary system with a predilection for males. The most common metastatic sites are the lung, liver, lymph nodes, contralateral kidney or adrenal gland, however, skin metastasis has only been seen in 1.0%-3.3% of cases. The most common site of skin metastasis is the scalp, and metastasis to the nasal ala region is rare. CASE SUMMARY: A 55-year-old man with clear cell carcinoma of the left kidney was treated with pembrolizumab and axitinib for half a year after surgery and was found to have a red mass on his right nasal ala for 3 mo. The skin lesion of the patient grew rapidly to the size of 2.0 cm × 2.0 cm × 1.2 cm after discontinuation of targeted drug therapy due to the coronavirus disease 2019 epidemic. The patient was finally diagnosed with skin metastasis of RCC in our hospital. The patient refused to undergo surgical resection and the tumor shrank rapidly after resuming target therapy for 2 wk. CONCLUSION: It is rare for an RCC to metastasize to the skin of the nasal ala region. The tumor size change of this patient before and after treatment with targeted drugs shows the effectiveness of combination therapy for skin metastasis.

Immunological Findings in a Group of Individuals Who Were Poor or Non-Responders to Standard Two-Dose SARS-CoV-2 Vaccines.

Coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been declared a pandemic. However, data on the poor or non-responders to SARS-CoV-2 vaccines in the general population are limited. The objective of this study was to comprehensively compare the immunological characteristics of poor or non-responders to SARS-CoV-2 vaccines in the 18-59-year group with those in the ≥60-year group using internationally recognized cut-off values. The main outcome was effective seroconversion characterized by an anti-SARS-CoV-2 spike IgG level of at least a four-fold increase from baseline. Profiling of naïve immune cells was analyzed prior to vaccination to demonstrate baseline immunity. The outcomes of effective seroconversion in patients aged 18-59 years with those in patients aged ≥60 years were compared. The quantitative level of anti-spike IgG was significantly lower in individuals aged ≥60 and men aged 18-59 years. There were 7.5% of poor or non-responders among the 18-59 years and 11.7% of poor or non-responders in the ≥60 years using a four-fold increase parameter. There were 37.0-58.1% with low lymphocyte count (<1000/mm3), 33.3-45.2% with low CD4 cell counts (<500/mm3), and 74.1-96.8% with low B cell counts (<100/mm3) in the non-seroconversion group. An individual with an anti-SARS-CoV-2 spike IgG titer below 50 BAU/mL might be considered a poor or non-responder between 14 and 90 days after the last vaccine dose. Booster vaccination or additional protective measures should be recommended to poor or non-responders as soon as possible to reduce disease severity and mortality.

Fiscal Pressure and Public–Private Partnership Investment: Based on Evidence from Prefecture-Level Cities in China

Public–private partnership (PPP) policy is essential to alleviating the local government debt burden and improving resource allocation efficiency. This paper empirically examines the impact of fiscal pressure on PPP investment in Chinese prefecture-level cities from 2014 to 2019 using the ordinary least-squares (OLS) module. Moreover, we also investigate how fiscal pressure influences PPP investment and test the influenced mechanism from other perspectives. The results show the following. (1) Fiscal pressure on the government has a significant positive effect on PPP investment at the prefectural level. (2) The marketization process is the mediated effect of the relationship between fiscal pressure and PPP investment. Fiscal pressure will stimulate the regional marketization process, thus promoting PPP investment. (3) Fiscal pressure has a significant positive effect on PPP investment in the middle region, while the effect is not significant in the eastern and western regions. Meanwhile, the effect is not significant in central cities, but there is a significant positive effect in ordinary cities. (4) The effect of fiscal pressure on PPP investment is not significant in the private reward mode of government payment, but there is a significant positive effect in the mode of user payment and feasibly insufficient subsidies. Our studies could also provide practical suggestions for sustainable development of PPP policy and solving the fiscal pressure of the current economic recession under the COVID-19 pandemic.

Prevalence of and relevant factors for depression and anxiety symptoms among pregnant women on the eastern seaboard of China in the post-COVID-19 era (preprint)

Background Antenatal depression and anxiety symptoms may have negative consequences for both mothers and offspring, and upward trends in the prevalence of these symptoms were especially apparent during the COVID-19 epidemic. The purpose of this study was to evaluate the prevalence of and relevant factors influencing depressive and anxiety symptoms in Chinese pregnant women in the post-COVID-19 era.Methods We conducted an online survey of 1,963 pregnant women in Jiangsu Province, using a cross-sectional design, and collected their general demographic data. The nine-item Patient Health Questionnaire 9 (PHQ-9) was used to evaluate depression symptoms, and the seven-item Generalized Anxiety Disorder 7 (GAD-7) was used to measure anxiety symptoms.Results The prevalence of reported antenatal depressive symptoms, anxiety symptoms, and depression combined with anxiety symptoms was 25.2%, 27.9%, and 18.6%, respectively. Of the respondents, prevalence of moderate to severe depression, anxiety, and combined symptoms was 7.9%, 7.7%, and 4.7%, respectively. Binary logistic regression analysis demonstrated that age, low level of education, rural area, unemployment, pregnancy complications, poor marital relationship, and fair household income were positively association with both depressive and anxiety symptoms (all P < 0.05). The proportion of women reporting anxiety symptoms in the third trimester was 1.895-fold higher than in first trimester. Parity was not a relevant factor for depression and anxiety symptoms (all P > 0.05).Conclusions In the post-COVID-19 era, the prevalence of depression and anxiety symptoms in pregnant women was higher than expected, and it is vital to establish hospital, community, and family psychological health screening systems based on relevant factors and enhance early preventive measures.

DBF-Net: a semi-supervised dual-task balanced fusion network for segmenting infected regions from lung CT images

Accurate segmentation of infected regions in lung computed tomography (CT) images is essential to improve the timeliness and effectiveness of treatment for coronavirus disease 2019 (COVID-19). However, the main difficulties in developing of lung lesion segmentation in COVID-19 are still the fuzzy boundary of the lung-infected region, the low contrast between the infected region and the normal trend region, and the difficulty in obtaining labeled data. To this end, we propose a novel dual-task consistent network framework that uses multiple inputs to continuously learn and extract lung infection region features, which is used to generate reliable label images (pseudo-labels) and expand the dataset. Specifically, we periodically feed multiple sets of raw and data-enhanced images into two trunk branches of the network;the characteristics of the lung infection region are extracted by a lightweight double convolution (LDC) module and fusiform equilibrium fusion pyramid (FEFP) convolution in the backbone. According to the learned features, the infected regions are segmented, and pseudo-labels are made based on the semi-supervised learning strategy, which effectively alleviates the semi-supervised problem of unlabeled data. Our proposed semi-supervised dual-task balanced fusion network (DBF-Net) creates pseudo-labels on the COVID-SemiSeg dataset and the COVID-19 CT segmentation dataset. Furthermore, we perform lung infection segmentation on the DBF-Net model, with a segmentation sensitivity of 70.6% and specificity of 92.8%. The results of the investigation indicate that the proposed network greatly enhances the segmentation ability of COVID-19 infection.

Analysis of intermediate hosts and susceptible animals of SARS-CoV-2 by computational methods

COVID-19, a disease caused by SARS-CoV-2 that produces major symptoms of pneumonia, has been a disaster worldwide. The traceability of SARSCoV- 2 and the discovery of susceptible animal species is crucial to halt viral transmission and explore the mechanism of cross-species transmission. We selected 82 representative ACE2 sequences from the 1000 sequences with the closest homology to the hACE2 protein. All selected ACE2 proteins were subjected to homology modeling. Potential natural and intermediate hosts, as well as animal species susceptible to SARS-CoV-2, were analyzed systematically by calculation of the binding free energy of ACE2 protein to the RBD of SARSCoV- 2. Primates, some wild Felidae, civets, goats, spotted hyenas and golden hamsters are susceptible to SARS-CoV-2 and may be potential intermediate hosts, whereas pangolins, birds and reptiles are unlikely to be intermediate hosts. Mice, rats and guinea pig are not susceptible to SARS-CoV-2. Given their possible susceptibility, non-human primates, goats and golden hamsters could potentially be used as experimental models to examine SARS-CoV-2 infection without transgenesis. Herein, possible candidates for the natural and intermediate hosts of SARS-CoV-2 are suggested, to provide guidance for subsequent studies.

Symptomatic and Asymptomatic Transmission of SARS-CoV-2 in K-12 Schools, British Columbia, Canada April to June 2021.

We prospectively studied SARS-CoV-2 transmission at schools in an era of variants of concern, offering all close contacts serial viral asymptomatic testing up to 14 days. From the 69 primary cases detected in schools, 392 close contacts were identified and offered asymptomatic testing. A total of 229 (58%) were close school contacts, and of these, 3 tested positive (1.3%), 2 of which were detected through asymptomatic testing. This is in contrast to the 117 household contacts, where 43 (37%) went on to become secondary cases. Routine asymptomatic testing of close contacts should be examined in the context of local testing rates, preventive measures, programmatic costs, and health impacts of asymptomatic transmission. IMPORTANCE There is concern that schools may be a setting where asymptomatic infections might result in significant "silent" transmission of SARS-CoV-2, particularly after the emergence of more transmissible variants of concern. After the programmatic implementation of a strategy of asymptomatic testing of close COVID-19 contacts as part of contact tracing in the school setting, the majority of the secondary cases were still found to have occurred in home or social contacts. However, for the 6.2% of secondary cases that occurred in close school contacts, the majority were detected through asymptomatic testing. The potential added yield of this approach needs to be considered within the overall setting, including consideration of the local epidemiology, ongoing goals of case and contact management, additional costs, logistical challenges for families, and possible health impacts of asymptomatic transmission.

The AST/ALT Ratio (De Ritis Ratio) Represents an Unfavorable Prognosis in Patients in Early-Stage SFTS: An Observational Cohort Study.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS), a widely prevalent infectious disease caused by severe fever with thrombocytopenia syndrome virus (SFTSV) that carries with it a high mortality rate, has emerged to be a public health concern. This study aimed to investigate the epidemiological and clinical characteristics of patients infected with SFTSV, seeking novel prognostic risk factors for SFTS. METHODS: In this retrospective and cross-sectional study, confirmed SFTS patients from the First Affiliated Hospital of Anhui Medical University were enrolled from September 1, 2019, to December 12, 2020. Cases were analyzed for epidemiological, demographic, clinical, and laboratory data. Logistic regression models were used to assess the association between predictors and outcome variables. A generalized additive mixed model (GAMM) was conducted to analyze the trending shift of aspartate aminotransferase/alanine transaminase-ratio (AST/ALT-ratio) and platelet (PLT) in SFTS patients treated with ribavirin. p values ≤ 0.05 were considered statistically significant. RESULTS: Clinical and laboratory results of 107 hospitalized patients with SFTSV infection were retrospectively described. The mean age at onset of disease was 60.38 ± 11.29 years old and the ratio between male and female was 1:1.2. Fever and thrombocytopenia are hallmark features of SFTS. Furthermore, multiple cases also experienced neurological complications, gastrointestinal/skeletal muscle symptoms together with other non-specific clinical manifestations; laboratory dataset outcomes reported dysregulated levels for routine blood biomarkers, coagulation function, and biochemistry. Overall, 107 patients were segregated into two groups according to patient condition at the clinical endpoint (survivors/non-survivors). SFTS survivors had a higher level of PLT- counts, total protein (TP), and estimated glomerular filtration rate (eGFR), while levels of activated partial thromboplastin time (APTT), thrombin time (TT), D-dimer (D-D), fibrinogen degradation products (FDP), ALT, AST, AST/ALT-ratio, creatinine (Cr), creatine phosphokinase (CK) and procalcitonin (PCT) was higher in non-survivors. Results from univariate Cox regression revealed that elevated levels of FDP, TT, AST/ALT-ratio, PCT, as well as decreased eGFR level and presence of central nervous system symptoms (CNS), were significant predictors for SFTS prognostic, results from multivariate logistic regression analysis in three adjusted models showed AST/ALT-ratio and PCT were independent risk factors for the prognosis of SFTS patients. Kaplan-Meier survival analysis showed that SFTS patients with AST/ALT-ratio >2.683 were associated with a shorter futime (means survival time), therefore indicating an unfavorable prognosis. Treatment with ribavirin could increase PLT count while decreasing AST/ALT-ratio within SFTS patients. CONCLUSION: SFTS is an emerging infectious disease, possibly leading to multiple-organ injury; AST/ALT-ratio was an independent risk factor for the prognosis of SFTS patients. Further investigation should be performed in order to gain more knowledge on this disease and guide clinical management.

Current status and influential factors for family health management during quarantine: A latent category analysis.

OBJECTIVE: We aimed to explore factors affecting family health management during home quarantine as well as the effects of variations in family health management (FHM) on individuals' health status. METHODS: Using stratified random sampling, 618 families in Wuhan as well as cities within its surrounding provinces were recruited and surveyed online. Latent class variables were extracted from four modules: disinfection, space layout, physical exercise, and food reserves. The analysis was conducted using the poLCA package in R software (v.4.1.0). Chi-squared tests, Fisher's exact tests, and non-parametric Kruskal-Wallis tests were used to compare groups as appropriate. RESULTS: We found an overall questionnaire reliability of 0.77 and a total omega of 0.92, indicating that the survey results were credible. The Bayesian information criterion and Akaike information criterion were used to identified four latent class variables, namely latent non-family health management (18.9%) and latent low, medium, and advanced FHM (30.93%, 29.49%, and 20.59%, respectively). Gender, household income level, body mass index, the presence of a nearby community hospital, and self-rated health status showed statistically significant differences with respect to latent FHM. Moreover, we found a statistically significant difference in emotional reactions when comparing latent advanced and low to mid-level latent FHM. Compared with latent non-family health managers, we detected statistically significant differences in individual energy levels between potential family health managers at latent low and medium levels. Additionally, we found statistically significant differences in individual energy levels between latent advanced and low level family health managers. CONCLUSIONS: We found that multiple factors, including gender, household income, and body mass index, were correlated with latent FHM during home quarantine. We conclude that FHM can meaningfully improve individuals' health. Thus, increasing social support for individuals can improve FHM as well as individuals' health during home quarantine.

iExam: A Novel Online Exam Monitoring and Analysis System Based on Face Detection and Recognition (preprint)

Online exams via video conference software like Zoom have been adopted in many schools due to COVID-19. While it is convenient, it is challenging for teachers to supervise online exams from simultaneously displayed student Zoom windows. In this paper, we propose iExam, an intelligent online exam monitoring and analysis system that can not only use face detection to assist invigilators in real-time student identification, but also be able to detect common abnormal behaviors (including face disappearing, rotating faces, and replacing with a different person during the exams) via a face recognition-based post-exam video analysis. To build such a novel system in its first kind, we overcome three challenges. First, we discover a lightweight approach to capturing exam video streams and analyzing them in real time. Second, we utilize the left-corner names that are displayed on each student's Zoom window and propose an improved OCR (optical character recognition) technique to automatically gather the ground truth for the student faces with dynamic positions. Third, we perform several experimental comparisons and optimizations to efficiently shorten the training and testing time required on teachers' PC. Our evaluation shows that iExam achieves high accuracy, 90.4% for real-time face detection and 98.4% for post-exam face recognition, while maintaining acceptable runtime performance. We have made iExam's source code available at https://github.com/VPRLab/iExam.

A recombinant infectious bronchitis virus from a chicken with a spike gene closely related to that of a turkey coronavirus

Using viral metagenomics, the complete genome sequence of an infectious bronchitis virus (IBV) strain (named ahysx-1) from a fecal sample from a healthy chicken in Anhui province, China, was determined. The genome sequence of ahysx-1 was found to be very similar to that of IBV strain ck/CH/LLN/131040 (KX252787), except for the spike gene region, which is similar to that of a turkey coronavirus strain (EU022526), suggesting that ahysx-1 is a recombinant. Recombination analysis and phylogenetic analysis based on the genomic sequences of ahysx-1 and other related strains confirmed that ahysx-1 appears to be a recombinant resulting from a recombination event that occurred between a chicken coronavirus and a turkey coronavirus. Further studies need to be performed to determine whether this recombinant IBV strain is pathogenic and whether it is transmitted between chickens and turkeys.

Metabolomic analyses reveal new stage-specific features of COVID-19.

The current pandemic of coronavirus disease 2019 (COVID-19) has affected >160 million individuals to date, and has caused millions of deaths worldwide, at least in part due to the unclarified pathophysiology of this disease. Identifying the underlying molecular mechanisms of COVID-19 is critical to overcome this pandemic. Metabolites mirror the disease progression of an individual and can provide extensive insights into their pathophysiological significance at each stage of disease. We provide a comprehensive view of metabolic characterisation of sera from COVID-19 patients at all stages using untargeted and targeted metabolomic analysis. As compared with the healthy controls, we observed different alteration patterns of circulating metabolites from the mild, severe and recovery stages, in both the discovery cohort and the validation cohort, which suggests that metabolic reprogramming of glucose metabolism and the urea cycle are potential pathological mechanisms for COVID-19 progression. Our findings suggest that targeting glucose metabolism and the urea cycle may be a viable approach to fight COVID-19 at various stages along the disease course.

Impact of the COVID-19 pandemic on travel behavior: A case study of domestic inbound travelers in Jeju, Korea.

This study analyzes a large-scale navigation dataset that captures travel activities of domestic inbound visitors in Jeju, Korea in the first nine months of 2020. A collection of regression models are introduced to quantify the dynamic effects of local and national COVID-19 indicators on their travel behavior. Results suggest that behavior of inbound travelers was jointly affected by pandemic severity locally and remotely. The daily number of new cases in Jeju has a greater impact on reducing travel activities than the national-level daily new cases of COVID-19. The impacts of the pandemic did not diminish over time but produced heterogeneous effects on travels with different trip purposes. Our findings reveal the persistence of COVID-19's effects on travel behavior and the variability in travelers' responses across tourism activities with different levels of perceived health risks. The implications for crisis management and recovery strategies are also discussed.