Hong Kong secondary geography teachers' resilience in the testing time of the Covid-19: challenges and adaptations

The outbreak of Covid-19 has posed serious challenges to schools and teachers as it forced schools to close and traditional face-to-face teaching was suspended. How did Hong Kong geography teachers respond to these challenges in the first nine months of the outbreak? How did they adapt to the social distancing measures such as school closure? Why did they adapt in the way they did? The researchers interviewed 18 teachers with different lengths of teaching experiences and teaching students of different academic abilities to answer these questions. It was found that even though there were few specific suggestions from the Government and their schools, the teachers interviewed, as a whole, have taken self-initiated steps to adapt teaching strategies and proactively try various means to help their students continue to learn under the constraints of the Pandemic.

Pre-Avatar: An Automatic Presentation Generation Framework Leveraging Talking Avatar

Since the beginning of the COVID-19 pandemic, remote conferencing and school-teaching have become important tools. The previous applications aim to save the commuting cost with real-time interactions. However, our application is going to lower the production and reproduction costs when preparing the communication materials. This paper proposes a system called Pre-Avatar, generating a presentation video with a talking face of a target speaker with 1 front-face photo and a 3-minute voice recording. Technically, the system consists of three main modules, user experience interface (UEI), talking face module and few-shot text-to-speech (TTS) module. The system firstly clones the target speaker's voice, and then generates the speech, and finally generate an avatar with appropriate lip and head movements. Under any scenario, users only need to replace slides with different notes to generate another new video. The demo has been released here11https://pre-avatar.github.io/ and will be published as free software for use. © 2022 IEEE.

The US-China trade war and the volatility linkages between energy and agricultural commodities

Any disruptive changes in the competitive environment, such as the U.S.-China trade war, may influence the price volatility of crude oil and agricultural commodities. This study examines the volatility linkage between crude oil and agricultural commodity markets in the context of the U.S.-China trade war and compares the impact of the trade war with that of other exogenous shocks. The results show that the volatility of soybeans exhibits the highest level of responsiveness to the U.S.-China trade war - which is not surprising given that the U.S. agribusiness trade to China is dominated by soybeans - followed by coffee and cotton. The sizes and dynamics of the impacts of shocks are largely commodity-specific. Notably, the trade war impacts most agricultural commodities more extensively than other exogenous shocks, including the global financial crisis and the COVID-19 pandemic and associated recession. These findings matter not only for the decision-making of investors and portfolio managers but also for commodity-exporting and importing countries because changes in the volatility dynamics of crude oil and agricultural commodities often impact export revenues and import expenditures and consequently feed through exports to the global supply chain under exogenous shocks such as the U.S.-China trade war. © 2023 The Authors

Sports fear psychology in martial arts athletes' physical conflict psychology

This study aims to investigate the fear of sports psychology in the physical confrontation of Chinese Wushu athletes. This article profiles 40 Chinese students majoring in physical education, and social sports enrolled in a unique martial arts program. The age range is between 19 and 21. The causes of dread among 40 Sanda athletes were investigated using the research methodologies of literature data, interviews, and questionnaire survey. SPSS 14.0 statistical software was utilized to analyze the questionnaire data. Before two competitions following the experiment, students' psychological readiness was evaluated using a psychological exam. The length of the experiment was eighteen weeks. P < 0.05 indicated a substantial difference between the test and control groups to aid Sanda athletes in actual fighting. Provide theoretical support for the psychology of fear. Fear of harm, actual battle experience, and insufficient physical reserve are the causes of the fear of psychology in athletes, which can be overcome through a simulation-based training strategy. The management should develop the special sports quality of sanda athletes, rationalize combat and combat training, enhance technical and tactical skills, and bolster psychological training.

Ten measures to fight against the 2019-nCoV pneumonia in West China Hospital.

After the occurrence of public health emergencies, as the most direct front position, how to carry out medical treatment orderly, effectively, rapidly and safely in a short time has become the focus and difficulty of epidemic control. After the outbreak of 2019 novel coronavirus pneumonia (2019-nCoV), West China Hospital of Sichuan University, as a large-scale general hospital under the supervision of the CPC central committee, put people's life safety and health first, and attach great importance to the prevention and control of the epidemic. This paper introduces the ten measures taken by West China Hospital of Sichuan University to fight against the 2019-nCoV pneumonia, in order to provide reference for other hospitals. Copyright © 2020 West China University of Medical Science. All rights reserved.

Analysis of COVID-19 outbreak based on window-time-LSTM model

Objective To solve the data difference between COVID-19 confirmed cases and actual number of COVID-19 infections, a new model is proposed to predict the spread of the disease. The data difference has been mainly caused by insufficient understanding in the early stage of transmission, limited detection capabilities and the long incubation period. Methods The historical data of the number of confirmed cases are analyzed based on Window-Time. A Long Short-Term Memory (LSTM) network model is combined with the Window-Time strategy to analyze and predict the actual number of infections according to data published of various regions in the world. Results The LSTM network model with Window-Time strategy has higher accuracy than other models. Tuning the width of the Window-Time to the width of 5, the prediction result shows that it is closest to the real actual number of infections, which is consistent with the incubation period of COVID-19 generally known as 3-7 days. Conclusion This method provides a reference for the analysis of the transmission rate of COVID-19 and the incubation period of the epidemic. © 2021, Publication Centre of Anhui Medical University. All rights reserved.

Analysis of consumption behavior of college students during the novel coronavirus pneumonia epidemic based on GRI correlation analysis

As a special group of social consumption, college students have different consumer psychology and behaviors from other consumer groups in society. This paper proposes a multi-view GRI association model describing the relationship between multi-source entities. The model uses the GRI association model to describe the association constraints between entities, extracts features and attributes of the entities in each data source to form an entity feature GRI association graph, and aggregates the features of all entities in the data source. On the basis of mastering certain data, it conducts a descriptive GRI correlation analysis on college students' online consumption behavior indicators. In the process of evaluation and analysis, this article believes that during the novel coronavirus pneumonia epidemic, both internal and external factors act together on college students' online consumption behavior. External factors mainly include the construction of marketing scenarios, advertising and promotion activities, and the influence of reference groups during the novel coronavirus pneumonia epidemic. Internal factors mainly include the application of the "10,000 hours"law in online consumption and the influence of psychological factors such as the release of self-control, anticipatory regret purchases, and tasteful choices in the case of "hoarding purchases". © 2021 ACM.

Clinical features of patients with cryptogenic stroke and COVID-19

Introduction: While coronavirus disease 2019 (COVID-19) has been associated with acute ischemic stroke (AIS), the causal relationship has yet to be elucidated. Factors that likely confer increased stroke risk are COVID-19-associated coagulopathy and hyperinflammatory response. Studying clinical features of patients with otherwise undetermined cause of AIS could help better define COVID-19-associated stroke. Methods: We performed a multicenter cross-sectional study of consecutive patients presenting with AIS and COVID-19 to one of two large healthcare systems in New York City during the local COVID- 19 surge from March 1, 2020 to May 31, 2020. In-hospital stroke cases were excluded. We compared demographic and clinical features of patients with COVID-19 and a cryptogenic AIS subtype to patients with COVID-19 and a determined subtype. Baseline characteristics and clinical variables were compared using chi-squared and Fisher exact tests. Results: A total of 62 patients with AIS and COVID-19 at the time of hospital arrival were identified. Of these, 30 were classified as having a cryptogenic subtype (80% after complete diagnotics evaluation), and 32 had an identifiable stroke mechanism. Patients with cryptogenic AIS were significantly younger (p=0.011) and less likely to have co-morbid hypertension (p=0.019), coronary artery disease (p=0.024), heart failure (p=0.039), atrial fibrillation (<0.0001), and prior stroke or TIA (p=0.033) compared to those with defined mechanisms. Further, d-dimer, but not C-reactive protein, was significantly higher in patients with cryptogenic stroke compared to those with defined causes (p=0.009). Conclusion: Patients with AIS in the setting of COVID-19 and no other determined stroke mechanism were younger, less likely to have classic risk factors, and had higher d-dimer levels when compared to those with a determined mechanism. Further study of COVID-19-associated hypercoagulability as a mechanism of stroke is warranted.

A real-time robot-based auxiliary system for risk evaluation of COVID-19 infection

In this paper, we propose a real-time robot-based auxiliary system for risk evaluation of COVID-19 infection. It combines real-time speech recognition, temperature measurement, keyword detection, cough detection and other functions in order to convert live audio into actionable structured data to achieve the COVID-19 infection risk assessment function. In order to better evaluate the COVID-19 infection, we propose an end-to-end method for cough detection and classification for our proposed system. It is based on real conversation data from human-robot, which processes speech signals to detect cough and classifies it if detected. The structure of our model are maintained concise to be implemented for real-time applications. And we further embed this entire auxiliary diagnostic system in the robot and it is placed in the communities, hospitals and supermarkets to support COVID-19 testing. The system can be further leveraged within a business rules engine, thus serving as a foundation for real-time supervision and assistance applications. Our model utilizes a pretrained, robust training environment that allows for efficient creation and customization of customer-specific health states. Copyright © 2020 ISCA

Epidemic Guard: A COVID-19 Detection System for Elderly People

The global outbreak of the COVID-19 in the worldwide has drawn lots of attention recently. The elderly are more vulnerable to COVID-19 and tend to have severe conditions and higher mortality as their immune function decreased and they are prone to having multiple chronic diseases. Therefore, avoiding viral infection, early detection and treatment of viral infection in the elderly are important measures to protect the safety of the elderly. In this paper, we propose a real-time robot-based COVID-19 detection system: Epidemic Guard. It combines speech recognition, keyword detection, cough classification, and medical services to convert real-time audio into structured data to record the user’s real condition. These data can be further utilized by the rules engine to provide a basis for real-time supervision and medical services. In addition, Epidemic Guard comes with a powerful pre-training model to effectively customize the user’s health status. © 2020, Springer Nature Switzerland AG.

[Suggestions for thoracic surgery clinical practice in non-epidemic area of 2019 coronavirus disease].

In this paper, the mechanism of destroying human alveolar epithelial cells and pulmonary tissue by 2019 novel coronavirus (2019-nCoV) was discussed firstly. There may be multiple mechanisms including killing directly the target cells and hyperinflammatory responses. Secondly, the clinical features, CT imaging, short-term and long-term pulmonary function damage of the 2019 coronavirus disease (COVID-19) was analyzed. Finally, some suggestions for thoracic surgery clinical practice in non-epidemic area during and after the epidemic of COVID-19 were provided, to help all the thoracic surgery patients receive active and effective treatment.

The Impact of COVID-19 on Emergent Large-Vessel Occlusion: Delayed Presentation Confirmed by ASPECTS.

BACKGROUND AND PURPOSE: Our hypothesis is that the COVID-19 pandemic led to delayed presentations for patients with acute ischemic stroke. This study evaluates the impact of the coronavirus disease 2019 pandemic on presentation, treatment, and outcomes of patients with emergent large-vessel occlusion using data from a large health system in the Bronx, New York. MATERIALS AND METHODS: We performed a retrospective cohort study of 2 cohorts of consecutive patients with emergent large-vessel occlusion admitted to 3 Montefiore Health System hospitals in the Bronx from January 1 to February 17, 2020, (prepandemic) and March 1 to April 17, 2020 (pandemic). We abstracted data from the electronic health records on presenting biomarker profiles, admission and postprocedural NIHSS scores, time of symptom onset, time of hospital presentation, time of start of the thrombectomy procedure, time of revascularization, presenting ASPECTS, TICI recanalization score, mRS, functional outcomes, and mortality. RESULTS: Of 179 patients admitted with ischemic stroke during the study periods, 80 had emergent large-vessel occlusion, of whom 36 were in the pandemic group. Patients in the pandemic group were younger (66 versus 72 years, P < .061) and had lower ASPECTS (7 versus 9, P < .001) and took longer to arrive at the hospital (361 versus 152 minutes, P < .004) with no other major differences. There was a decreased rate of thrombolysis administration (22% versus 43%, P < .049) and a decreased number of patients treated with mechanical thrombectomy (33% versus 61%, P < .013). CONCLUSIONS: The pandemic led to delays in patients arriving at hospitals, leading to decreased patients eligible for treatment, while in-hospital evaluation and treatment times remain unchanged.

COVID-19-Associated Carotid Atherothrombosis and Stroke.

We present a radiology-pathology case series of 3 patients with coronavirus disease 2019 (COVID-19) with acute ischemic stroke due to fulminant carotid thrombosis overlying mild atherosclerotic plaque and propose a novel stroke mechanism: COVID-associated carotid atherothrombosis.