Chinese Gen Z's emotional dimensions for fashion design during the pandemic

Known for being passionate about fashion, Chinese Generation Z (CGZ) is a powerful consumer group in the China fashion market today, but a psychological shift in their perceptions has been driven by COVID-19, arousing the attention of the fashion field. As visual product, fashion product elicits consumers' emotional reactions. Existing research in fashion design has noted consumers' emotional needs but still lacks focus on them in specific cultural contexts. To fill the gap, we employed a Kansei Engineering (KE) method to detect consumers' emotional responses to fashion design. This study uncovered CGZ's preferences, perceptions of fashion styles, and demographic influence. Further, we clustered CGZ's emotional needs into four classifications based on the relationship between the participants and dressing, others, and the environment. This study serves as a theoretical guideline for fashion design by translating consumers' emotional needs into a conceptual framework.

Assessment of residual chlorine in soil microbial community using metagenomics

Chlorine-containing disinfectants have been widely used around the world for the prevention and control of the COVID-19 pandemic. However, at present, little is known about the impact of residual chlorine on the soil micro-ecological environment. Herein, we treated an experimental soil-plant-microbiome microcosm system by continuous irrigation with a low concentration of chlorine-containing water, and then analyzed the influence on the soil microbial community using metagenomics. After 14-d continuous chlorine treatment, there were no significant lasting effect on soil microbial community diversity and composition either in the rhizosphere or in bulk soil. Although metabolic functions of the rhizosphere microbial community were affected slightly by continuous chlorine treatment, it recovered to the original status. The abundance of several resistance genes changed by 7 d and recovered by 14 d. According to our results, the chlorine residue resulting from daily disinfection may present a slight long-term effect on plant growth (shoot length and fresh weight) and soil micro-ecology. In general, our study assisted with environmental risk assessments relating to the application ofchlorine-containing disinfectants and minimization of risks to the environment during disease control, such as COVID-19. © 2022, Higher Education Press.

Deep learning-based recognition of Chinese dishes in a waiterless restaurant

The outbreak of COVID-19 makes it danger going out dining. Building waiterless restaurants becomes meaningful and urgent. Because automate and accurate recognition of dishes is indispensable for ordering and charging self-served food, this study investigates the feasibility of a prototype system that uses deep networks for recognizing Chinese dishes in a self-serving restaurant. Specifically, ≈ 17,000 images and 45,000 instances of 28 categories of dishes are collected using a fixed micro-camera equipment, and 5 deep learning networks are explored for dish recognition. Experimental results on the prototype system reveal that 3 transferred deep learning networks achieve high performance, and the accuracy, mean average precision and recall are larger than 97.0%. Real-time, accurate dish recognition in an automate fashion is highly related to a great customer experience, and the real-life evaluation in this study suggests that transferred deep networks are promising to fulfill this task. © 2022 IEEE.

Impact of Metabolic Syndrome on Mortality Among COVID-19 Patients

Background: Metabolic syndrome (MS) has been suggested related to severity of coronavirus disease 2019 (COVID-19). We aimed to identify the association between the presence of MetS and mortality among COVID-19 patients. Methods: We analyzed 3876 adults, confirmed with COVID-19 from January to June, 2020, based on the Korean National Health Insurance Service-COVID-19 data. Participants underwent a health examination provided by the NHIS between 2015 and 2017. The hazard ratios (HRs) of the mortality in COVID-19 patients according to MS were calculated by a multivariable Cox proportional hazards regression analysis. Results: During a follow-up, 3.1% (n = 120) died. The mortality rate was 3.8-fold higher in individuals with MS compared to those without it. The presence of MS was significantly associated with increased risks of mortality in COVID-19 patients even after adjusting for all confounding variables (HR: 1.68, 95% confidence interval [CI]: 1.142.47 in model 3). Of MS components, low high-density lipoprotein cholesterol was prominently associated with a greater mortality risk (HR: 1.63, 95% CI: 1.12-2.37 in model 3). The HRs of mortality increased in individuals with more numbers of MS components (p for trend <0.009 in model 3). Conclusions: The presence of MS and greater number of MS components were associated with increased mortality risk among COVID-19 patients.

COVID-19 smart surveillance: Examination of Knowledge of Apps and mobile thermometer detectors (MTDs) in a high-risk society.

Background: Technological innovations gained momentum and supported COVID-19 intelligence surveillance among high-risk populations globally. We examined technology surveillance using mobile thermometer detectors (MTDs), knowledge of App, and self-efficacy as a means of sensing body temperature as a measure of COVID-19 risk mitigation. In a cross-sectional survey, we explored COVID-19 risk mitigation, mobile temperature detectable by network syndromic surveillance mobility, detachable from clinicians, and laboratory diagnoses to elucidate the magnitude of community monitoring. Materials and Methods: In a cross-sectional survey, we create in-depth comprehension of risk mitigation, mobile temperature Thermometer detector, and other variables for surveillance and monitoring among 850 university students and healthcare workers. An applied structural equation model was adopted for analysis with Amos v.24. We established that mobile usability knowledge of APP could effectively aid in COVID-19 intelligence risk mitigation. Moreover, both self-efficacy and mobile temperature positively strengthened data visualization for public health decision-making. Results: The algorithms utilize a validated point-of-center test to ascertain the HealthCode scanning system for a positive or negative COVID-19 notification. The MTD is an alternative personal self-testing procedure used to verify temperature rates based on previous SARS-CoV-2 and future mobility digital health. Personal self-care of MTD mobility and knowledge of mHealth apps can specifically manage COVID-19 mitigation in high or low terrestrial areas. We found mobile usability, mobile self-efficacy, and app knowledge were statistically significant to COVID-19 mitigation. Additionally, interaction strengthened the positive relationship between self-efficacy and COVID-19. Data aggregation is entrusted with government database agencies, using natural language processing and machine learning mechanisms to validate and analyze. Conclusion: The study shows that temperature thermometer detectors, mobile usability, and knowledge of App enhanced COVID-19 risk mitigation in a high or low-risk environment. The standardizing dataset is necessary to ensure privacy and security preservation of data ethics.

Sudden Hearing Loss in Patients With COVID-19: Case Series and Analysis of the Literature

This study reports on patients with severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) presenting with sudden sensorineural hearing loss (SSNHL) during the coronavirus disease 2019 (COVID-19) pandemic. The study included four adult patients who presented with the complaint of unilateral SSNHL after testing positive for SARS-CoV-2 by RT-PCR from January to April 2022. Of the four patients, only one young adult recovered his hearing following a combination of oral and intratympanic steroid therapy. It is a challenge to confirm evidence of association between COVID-19 and SSNHL. Nevertheless, the early screening and diagnosis for SSNHL following COVID-19 enables prompt treatment with steroids, which offers the best chance of hearing recovery. Copyright © 2022 Korean Society of Otorhinolaryngology-Head and Neck Surgery.

The application value of orthopedics' operating room nursing model based on evidence-based nursing and PDCA circulation during the COVID-19 outbreak

Background: The Coronavirus pandemic has resulted in an extreme challenge for humanity in recent times, like the challenges faced during World War II. Its origin has been pointed out, and the speculation made on its source directly points towards Wuhan in China. Since then, it has spread across the globe. The pandemic has resulted in more than one million deaths, which is a considerable challenge for humanity. Objective: With the pandemic of COVID-19, prevention of patient infection is crucial. This research focused on the orthopedic operating room nursing model effect based on evidence-based nursing and PDCA (Plan-Do-Check-act) cycle during the COVID-19 outbreak. Materials and Methods: From February 2020 to May 2020, 146 patients were admitted and received orthopedic surgery at Xuanwu Chunshu Hospital, Beijing, China, these admissions were grouped into control and intervention groups, which was based on the treatment provided. Satisfaction, time to bed and hospitalization, postoperative incision infection, and the occurrence of deep venous thrombosis of lower extremities, pain degree score, surgical treatment effect, anxiety, and depression scores were compared for all the admissions between the control and intervention groups. Results: In the control group, nursing satisfaction was less than in the intervention group. The time of getting out of bed and hospitalization was less in the intervention group;The total incidence of postoperative incision infection and lower limb deep vein thrombosis in the intervention group decreased. In the first postoperative day, the pain level in the intervention group was less than the control group. The effectiveness rate in the observation group is higher than that of the control group. Anxiety and depression scores of both groups tended to decrease with time and there was an interactive effect between grouping and time, where these differences were found to be statistically significant (P-value<0.05). Conclusion: The clinical application of the orthopedics operating room nursing model based on evidence-based nursing and PDCA cycle is remarkable and worth implementing during the COVID-19 outbreak.

Study on elderly's satisfaction with bus travel before and after COVID-19

This paper aims to discuss whether there is heterogeneity in the elderly's satisfaction with bus travel before and after COVID-19. Based on the survey data of the elderly in Taiyuan, this paper subdivides 10 dependent variables of bus travel satisfaction considering the general environment of the pandemic. And the Multi-Categorical and Ordered Logit(MCOL) model and Structural Equation Model(SEM) are adopted to study the impact of personal attributes, travel attributes as well as psychological attributes on the elderly's satisfaction with bus travel before and after COVID-19. The results show that regarding personal attributes, household registration, gender, occupation, disability, and degree of disability all have significant effects on different satisfaction indicators. Among the travel attributes, if the travel purpose was to work before the pandemic, it would have a negative impact on waiting time and arrival time;while the non-work trip would have a negative impact on indicators regarding the inner-bus condition;after the pandemic, only non-work trip has a significant positive impact on the pandemic-related safety warning information. The influence of travel distance and travel time on the elderly's satisfaction with bus travel before and after the pandemic is consistent. In the psychological attributes, before the pandemic, the degree of attention has a strong positive effect on psychological anxiety with an effect value of 0.758;while after the pandemic, the degree of attention produces a significant negative effect of psychological anxiety on bus travel satisfaction, with an effect value of -0.119. This study can serve as a reference for improving the bus transportation environment for the elderly when similar major public health emergencies happen in the future. © 2022, Editorial Department of Journal of Beijing Jiaotong University. All right reserved.

Performance Evaluation of Travel Security System for Low-mobility Individuals Under the Epidemic

In order to guarantee travel service quality of low-mobility individuals under the public health emergency, this paper was set in the COVID-19, compared travel behavior characteristics of low-mobility individuals and general public between before and during the epidemic, defined evaluation indexes of travel security system for low-mobility individuals, built the performance evaluation model of travel security system for low-mobility individuals based on the matter element analysis. The results of travel behavior analysis find that the travel service quality of low-mobility individuals is necessary to get guarantee, because they have many travel difficulties during the epidemic. The results of performance evaluation verify that evaluation indexes and evaluation model are reasonable and effective. Research findings can be used as a reference for government departments to formulate travel security strategies under the public health emergency, and can provide practical guidance for the construction and performance evaluation of travel service security system for low-mobility individuals during the epidemic. © 2021, Editorial Department of Wuhan University of Technology. All right reserved.

Study on the risk of death of coagulation index in patients with covid-19

Objective: The aim of this study was to elucidate the association of COVID-19 prognosis with the indexes of inflammation and coagulation. Methods: The clinical data of 103 cases of COVID-19 were retrospectively analyzed. COX regression models and 95% confidence intervals (CIs) were applied to estimate the COVID-19 prognosis. Results: The results showed that C-reactive protein (HR=1.007, p<0.001), procalcitonin (HR=1.013, p=0.006), prothrombin time (HR=1.190, p<0.001), Fibrinogen (HR=0.784, p=0.002) and D-dimer (HR=1.078, p<0.001) is associated with an increased risk of COVID-19 death. Among the inflammation indicators, the maximum area under the ROC curve of NLR is 0.87. In the coagulation index, the maximum area under the ROC curve of PT is 0.84. For the combined indicators of inflammation and coagulation, the area under the ROC curve is 0.89. Conclusions: In conclusion, we found that the length of PT at admission and the level of fibrinogen and D-dimer were related to the risk of COVID-19 death. It may be considered to jointly predict the risk of death of COVID-19 with inflammation and coagulation indicators. © 2021 A. CARBONE Editore. All rights reserved.

Analysis of the Relationship among College Students' Coping Strategies, Psychological Resilience, and Anxiety during COVID-19

This study aims to use a grounded theory approach to explore the relationship among coping strategies, psychological resilience, and anxiety for college students during the COVID-19. The investigators conducted in-depth semi-structured interviews with eight college students in Wuhan city who reported negative emotions, such as tension, anxiety, and depression during the COVID-19 outbreak. MAXQDA 2020 was used to store, transcribe, code, and analyze the data. An open coding process generalized thirty- eight concepts and nine categories such as "self-regulation,""threat to Survival,"and "positive emotions."Three core themes have emerged through axial and selective coding, and a theoretical framework was constructed. The theory that emerged from participants' experiences demonstrates that a) most college students chose positive coping strategies to relieve their anxiety, b) different causes of anxiety may lead to different types of coping strategies, and c) college students' psychological resilience is related to positive coping strategies during the COVID-19 epidemic. © 2021 IEEE.

Establishment of prediction models for COVID-19 patients in different age groups based on Random Forest algorithm.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has rapidly become a global pandemic. Age is an independent factor in death from the disease, and predictive models to stratify patients according to their mortality risk are needed. AIM: To compare the laboratory parameters of the younger (≤70) and the elderly (>70) groups, and develop death prediction models for the two groups according to age stratification. DESIGN: A retrospective, single-center observational study. METHODS: This study included 437 hospitalized patients with laboratory-confirmed COVID-19 from Tongji Hospital in Wuhan, China, 2020. Epidemiological information, laboratory data and outcomes were extracted from electronic medical records and compared between elderly patients and younger patients. First, recursive feature elimination (RFE) was used to select the optimal subset. Then, two random forest (RF) algorithms models were built to predict the prognoses of COVID-19 patients and identify the optimal diagnostic predictors for patients' clinical prognoses. RESULTS: Comparisons of the laboratory data of the two age groups revealed many different laboratory indicators. RFE was used to select the optimal subset for analysis, from which 11 variables were screened out for the two groups. The RF algorithm were built to predict the prognoses of COVID-19 patients based on the best subset, and the area under ROC curve (AUC) of the two groups is 0.874 (95% CI: 0.833-0.915) and 0.842 (95% CI: 0.765-0.920). CONCLUSION: Two prediction models for COVID-19 were developed in the patients with COVID-19 based on random forest algorithm, which provides a simple tool for the early prediction of COVID-19 mortality.

[Fitting and predicting trend of COVID-19 by SVEPIUHDR dynamic model].

Objective: To fit and predict the trend of COVID-19 epidemics in the United States (USA) and the United Kingdom (UK), and analyze the effect of vaccination. Methods: Based on the SEIR dynamic model, considering the presymptomatic infections, isolation measures, vaccine vaccination coverage, etc., we developed a SEIR with vaccine inoculation, Presymptomatic infectious, unconfirmed infectious, hospital isolation and domiciliary isolation dynamics model. The publicly released incidence data of COVID-19 from November 6, 2020 to January 31, 2021 in USA and from November 23, 2020 to January 31, 2021 in UK were used to fit the model and the publicly released incidence data of COVID-19 from February 1, 2021 to April 1 were used to evaluate the predicting power of the model by software R 4.0.3 and predict changes in the daily new cases in the context of different vaccination coverage. Results: According to the cumulative confirmed cases, the fitting bias and the predicting bias of the SVEPIUHDR model for USA and UK were less than 5%, respectively. From the model prediction results, the cumulative cases after COVID-19 vaccination in USA in early April reached 31 864 970. If there had not had such vaccination, the cumulative cases of COVID-19 would have reached to 35 317 082, with a gap of more than 3.4 million cases. In UK, the cumulative cases of COVID-19 after the vaccination was estimated to be 4 195 538 in early April, compared with 4 268 786 cases if no COVID-19 vaccination had been provided, there would have heen a gap of more than 70 000 cases. Conclusion: SVEPIUHDR model shows a good prediction effect on the epidemic of COVID-19 in both USA and UK.

Construction and Empirical Study of Comprehensive Evaluation Index System of Online Teaching in the Period of COVID-19

The occurence of COVID-19 has directly led to the development of large-scale online teaching in China, and the quality of online teaching has become the focus of public attention. From the two dimensions of "evaluation of teaching"and "evaluation of learning", the article establishes an comprehensive evaluation index system of online teaching that includes three secondary indicators of "pre-class preparation", "in-class teaching"and "after-class feedback"with 12 evaluation factors. The empirical research on the online teaching of tourism and hotel majors shows that students both highly evaluate the online teaching platform and the effect of online teaching. It can be seen that teachers are fully prepared before class, they are responsible during the class, feedback is effective after class, and students have reached their learning goals and expectations. After COVID-19 is over, the "PAD + BOPPPS"teaching mode can be used to achieve a seamless connection from "online teaching"to "offline teaching". © 2021 IEEE.

Liver injury could be associated with severe disease in COVID-19 patients: A meta-analysis

Objective: To assess the association between liver injury and the severity of Corona Virus Disease 2019 (COVID-19) disease. Methods: Articles including severe vs non-severe or dead vs surviving COVID-19 patients were identified by searching the electronic database including PubMed, Embase and the Cochrane Library database. The meta-analysis was carried out using software RevMan 5.3. A fixed- or random-effects model was used depending on the heterogeneity between studies. Furthermore, publication bias was evaluated by the visual inspection of funnel plot. Results: Thirty-six studies involving 7083 patients were taken into analysis. The incidence of patients with chronic liver disease was not significantly associated with an enhanced risk of severe COVID-19 (OR: 1.36, 95% CI: 0.89-2.07, P = .16). The total bilirubin (TB), lactate dehydrogenase (LDH), alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were found to be obviously elevated in COVID-19 patients with severe group [TB: MD: 1.68, 95% CI: 1.17-2.19, P < .0001;LDH: MD: 122.66, 95% CI: 86.50-158.81, P < .0001;ALT: MD = 5.73, 95% CI (4.32, 7.14), P < .0001;AST: MD = 9.41, 95% CI (6.51, 12.31), P < .0001] and mortality group [TB: MD: 3.90, 95% CI: 2.63-5.18, P < .0001;LDH: MD: 246.30, 95% CI: 176.78-315.82, P < .0001;ALT: MD = 5.64, 95% CI (0.52, 10.75), P = .03;AST: MD = 12.93, 95% CI (4.95, 20.91), P = .002]. Albumin was significantly lower in COVID-19 patients with severe group (MD: -4.48, 95% CI: -6.51, -2.44, P < .0001) and mortality group (MD: -4.80, 95% CI: -5.94, -3.67, P < .0001). Based on visual inspection of funnel plots, no evidence of publication bias was found. Conclusions: According to our results, liver injury may be an important sign of COVID-19 associated to a severe form of disease, which can guide the clinicians in recognizing critically ill patients earlier and faster. However, due to the limitations of this study, more high-quality research is required.

Multimodal approach to analysing big social and news media data

Multimodal analysis traditionally involves conceptualising abstract frameworks for language, images, and other resources and their intersemiotic relations (e.g. text and image relations) and then demonstrating these frameworks with some examples. This scenario has changed with the recent move towards multimodal approaches to big data analytics which will involve empirically testing and validating multimodal theory and frameworks through the analysis of large data sets. However, large training sets of analysed texts are required to develop computational models based on multimodal theory. Therefore, an alternative approach which involves integrating multimodal frameworks with existing computational models for big data, cloud computing, natural language processing, image processing, video processing, and contextual metadata is proposed. The integration of these disparate fields has the potential to dramatically improve computational tools and techniques, thus placing multimodality at the forefront of research aimed at mapping and understanding multimodal communication. As a step forward in this direction, we explore how existing computational tools and approaches can be integrated into a multimodal analysis platform (MAP) with facilities for searching, storing and analysing text, images and videos in online media, together with dashboards for visualising the results. Preliminary analyses and classifications of text and images about COVID-19 and George Floyd in five online newspapers and Twitter postings show how media patterns can be studied using existing computational tools. The study highlights (a) the benefits and current limitations of big data approach to multimodal discourse analysis and (b) the need to incorporate knowledge about language, images, metadata, and other resources as semiotic systems (rather simply sets of symbols and pixels) to improve computational techniques for big data analytics. © 2021 Elsevier Ltd

Application of multi-disciplinary team based on prevention and control management mode under online in outpatient follow-up of children with Kawasaki disease and complicated with coronary artery lesion during COVID-19 epidemic period

Objective: To explore effect and safety of multi-disciplinary team (MDT) based on prevention and control management mode under online (PCM-online) in outpatient follow-up of children with Kawasaki disease and complicated with coronary artery lesion (CAL) during the epidemic outbreak period of corona virus disease 2019 (COVID-19). Methods: From 21 January, 2020 to 19 February, 2020, a total of 35 children with Kawasaki disease and complicated with CAL who received long-term treatment in the Department of Cardiovascular of Chengdu Women's and Children's Central Hospital and needed to go to the hospital for referral during epidemic outbreak period were selected as research subjects. By setting up an MDT based on PCM-online covering medical care, nursing, cardiac ultrasound, pharmacy, nutrition and psychology, and adopting the "Internet +" method, online consultations were provided to children with Kawasaki disease and complicated with CAL who needed to go to the hospital for referral, such as professional consultation of Kawasaki disease with CAL, psychological intervention, guidance on medication, nutrition diet and home care, and health education of COVID-19 and guidance on protective measures when going out for medical treatment. For some family members of children with relatively tense and anxious emotions, the Symptom Checklist 90 (SCL-90) was used for psychological evaluation, and online psychological counseling was conducted based on the psychological evaluation results. A self-made satisfaction questionnaire of our hospital was used to investigate the satisfaction of family members of children before and after intervention of MDT based on PCM-online. The scores of SCL-90 factors and satisfaction scores of family members of the children before and after intervention of MDT based on PCM-online were compared by paired t test. The procedures followed in this study were in accordance with the requirements of newly revised World Medical Association Declaration of Helsinki in 2013. Results: ①Among the 35 children with Kawasaki disease and complicated with CAL, 26 children canceled on-site outpatient visits after intervention of MDT based on PCM-online, thus avoiding the risk of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at least 52 people going out for medical treatment;9 patients required on-site follow-up due to their pathogenetic conditions. ②A total of 11 cases of family members of children received SCL-90 for psychological evaluation by mental intervention subgroup in MDT, and all of them were with positive results. After receiving psychological counseling in mental intervention subgroup, anxiety and fear factor scores in SCL-90 of the family members of these 11 children were (1.38±0.44) scores and (1.23±0.42) scores, respectively, which were higher than those before receiving psychological counseling (1.64±0.25) scores and (1.38±0.13) scores, and both the differences were statistically significant (t=3.285, 2.853;P=0.010, 0.024). ③After intervention of MDT based on PCM-online, the satisfaction score of 35 children's family members was (98.6±1.4) scores, which was significantly higher than (94.3±4.7) scores before intervention, and the difference was statistically significant (t=4.369, P=0.031). Conclusions: During COVID-19 epidemic period, intervention of MDT based on PCM-online achieves the purpose of epidemic prevention and control of COVID-19 and promotes the recovery of children with Kawasaki disease and complicated with CAL which is a new model for prevention and control of COVID-19 with low-risk, low-cost and high-efficiency under severe epidemic situation. Due to the relatively small sample-size and relatively short period of time enrolled in this study, whether this model is worthy of clinical popularization and application remains to be further studied and confirmed. Copyright © 2020 by the Chinese Medical Association.