A Novel Machine Learning-assisted Pairs Trading Approach for Trading Risk Reduction

The cryptocurrency market has been growing rapidly in recent years. The volume of transactions and the number of participants in the cryptocurrency market makes it huge enough that we cannot ignore it. At the same time, the global stock market has also reached a new height in the past two years. However, due to the COVID epidemic and other political and economic-related factors in the last two years, the uncertainty in the capital market remains high, and short-term large fluctuations occur frequently;thus, many investors have suffered substantial losses. Pairs trading, an advanced statistical arbitrage method, is believed to hedge the risk and profit off the market regardless of market condition. Amongst the vast literature on pairs trading, there have been investors trading a pair of cryptocurrencies or a pair of stocks using machine learning or empirical methods. This research probes the boundary of utilizing machine learning methods to do pairs trading with one stock asset and another cryptocurrency. Briefly, we built an assets pool with both stocks and cryptocurrencies to find the best trading pair. In addition, we applied mainstream machine learning models to the trading strategy. We finally evaluated the accuracy of the proposed method in prediction and compared their returns based on the actual U.S. Stock and Cryptocurrency Market data. The test results show that our method outperforms other state-of-the-art methods. © 2022 IEEE.

The merit of grit and emotions in L2 Chinese online language achievement: a case of Arabian students

The Covid-19 pandemic has provided second language (L2) learners with additional challenges regarding how to obtain an enjoyable experience while achieving a better learning attainment. Despite a growing body of studies that substantiated the predictive effect of grit, foreign language enjoyment (FLE), and foreign language classroom anxiety (FLA) on Chinese language achievement (CLA), no previous research has explored their predictive effects in online L2 Chinese learning. To address this gap, this study clarifies the nature of the complex correlation between grit, FLE, FLA, and online CLA by analyzing 169 responses from Arabic multilingual learners using structural equation modelling. The results indicate that: (i) FLE, not FLA, significantly predicts online L2 CLA;(ii) FLE acts as a positive mediator between grit and online L2 CLA;and (iii) FLE has a stronger impact in catalyzing an individual's online L2 success. This study enriches the applicability of the broaden-and-build and control-and-value theories in the field of Chinese language learning. We hope that this study will serve as a call for further attention to emotions and grit, especially for languages other than English, in order to advance the growth of positive psychology in L2 learning and teaching. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

The Pathogenesis and Treatment of COVID-19 and Long COVID with Traditional Chinese Medicine

According to the World Health Organization (WHO), COVID-19 and Long COVID will remain conditions of great concern for medical practitioners for the foreseeable future. Mainstream treatments recommended for less severe cases of COVID-19 infection include isolation and taking over-the-counter or prescription painkillers, while more severe cases may require hospitalization and treatments such as ventilation. The long-term impact of post-viral conditions such as Long COVID is only beginning to emerge, and so far no effective biomedical treatment methods have been identified. Mainstream treatment is effective, but to what extent? Is there another course of treatment available for patients who do not respond well to mainstream treatments? Traditional Chinese Medicine (TCM) is an alternative, due to its history of effectiveness in treating various viral infections such as hepatitis, mumps, the common cold, and herpes zoster. Yet although TCM has advantages in effectively regulating immunity, few practitioners have enough advanced knowledge in treating COVID-19 and Long COVID using TCM methods. This book aims to provide TCM practitioners with comprehensive, elaborate, and up-to-date information and training to manage COVID-19 and Long COVID complaints. Each chapter provides detailed discussions on complete clinical patterns of COVID-19, wide coverage on Long COVID treatments, Chinese herbs and its corresponding acupuncture treatment, provision of various clinical modifications and valuable clinical case studies. © 2023 by World Scientific Publishing Europe Ltd.

Integrated wearable smart sensor system for real-time multi-parameter respiration health monitoring

Monitoring respiration is vital for personal diagnosis of chronic diseases. However, the existing respiratory sensors have severe limitations, such as single function, finite detection parameters, and lack of smart signal analysis. Here, we present an integrated wearable and low-cost smart respiratory monitoring sensor (RMS) system with artificial intelligence (AI)-assisted diagnosis of respiratory abnormality by detecting multi-parameters of human respiration. Coupling with intelligent analysis and data mining algorithms embedded in a phone app, the lighter system of 7.3 g can acquire real-time self-calibrated parameters, including breathing frequency, apnea hypopnea index (AHI), vital capacity (VC), peak expiratory flow (PEF), and other respiratory indexes with an accuracy >95.21%. The data can be wirelessly transferred to the user's data cloud terminal. The RMS system enables comprehensive multi-physiological parameters analysis for auxiliary diagnosing and classifying diseases, including sleep apnea, rhinitis, and chronic lung diseases, as well as rehabilitation of COVID-19, and exhibits advantages of portable healthcare. © 2022 The Authors

Human IFN-κ Inhibited Respiratory RNA Virus Replication Dependent on Cell-to-Cell Interaction in the Early Phase

Background:Interferon kappa (IFN-κ) is a type I interferon (IFN-I) that inhibits virus replication by evoking interferon-stimulated genes (ISGs). However, as an evolutionarily ancient interferon, IFN-κ may function differently from the later emerged interferon-α and β.Methods:Conventional molecular biology methods were used to determine the localization of IFN-κ and its structure and function. In addition, we employed RT-PCR, western blot, and RNA-Seq technologies to characterize the ISGs expression profile and antiviral activities exerted by IFN-κ or IFN-α2.Results:Human IFN-κ exists in two forms upon ectopic expression, one located on the cell membrane and the other secreted outside the cells. The membrane-anchored IFN-κ showed the ability to induce ISGs and curtail RNA virus replication, whereas the secreted IFN-κ failed to do so. Structural analyses indicated that 1-27aa at the N-terminus was the signal peptide, and 28-37aa was predicted as the transmembrane region. However, our data demonstrated that both of them were not associated with membrane localization of IFN-κ;the former influenced the expression and secretion of IFN-κ, and the latter had an impact on the induction of ISGs. In addition, prokaryotic purified soluble mature human IFN-κ was also capable of inducing ISGs and inhibiting RNA virus replication. Importantly, human IFN-κ induced a faster ISG response but with a lower intensity and a shorter half-life than the response of IFN-α2. In contrast, IFN-α2 started to function later but was stronger and more durable than IFN-κ.Conclusions:Human IFN-κ-induced ISG response and inhibited respiratory RNA virus replication dependent on cell-to-cell interactions. In addition, compared with IFN-α2, IFN-κ exerted effects more rapidly in the early phase, with less intensity and a shorter half-life. Therefore, IFN-κ may constitute the first line of IFN-I against respiratory virus infections. © 2022 Journal of Bone and Joint Surgery Inc.. All rights reserved.

VARIATIONS IN BENEFITS OF INTERGENERATIONAL TUTORING IN THE "NEW NORMAL”

This study explored variations in self-perceived benefits of intergenerational tutoring. The study's sample consisted of 329 older adults who tutored children in-person in the 2021–2022 school year. Due to the COVID-19 pandemic, some of the respondents had experienced a period in which volunteering was remote, virtual, or not possible. Demographic information was collected in a fall pre-test survey, identifying first-time volunteers (first time volunteering in ten years), caregivers (100 or more hours in the last two years helping someone who needed assistance), and male volunteers. Self-perceived benefits of tutoring (physical, emotional, and cognitive health, increased social activities, use time more productively, contribute to the well-being of children, and feel better about myself) were collected in a spring post-test survey. Being a first-time volunteer was significantly associated with improved health (X2 = 4.17, p = 0.041, Cramer's V = 0.11), even after controlling for baseline self-reported health (p = 0.020). A larger proportion of first-time volunteers (34.2%) reported improvements in at least two areas of health (physical, emotional, and cognitive) due to their involvement in the intergenerational tutoring program, compared to non-first-time volunteers (18.5%). There were no significant differences in perceived benefits for caregivers or males. These findings suggest that targeting non-volunteers for involvement in tutoring programs may maximize health benefits of engagement. Specifically targeting males and caregivers may not be necessary, given that they benefit similarly to other populations.

Understanding Chinese second language learners' foreign language learning boredom in online classes: its conceptual structure and sources

Scholarly attention to foreign language learning boredom (FLLB) has surged in recent years. However, little is known about L2 learners' online FLLB experience prompted by the COVID-19 pandemic. To fill this gap, the present mixed-methods study explores the conceptual structure and sources of FLLB in an online learning environment. A corpus of 348 Chinese as second language (CSL) learners participated in a questionnaire survey and 10 of them attended follow-up interviews. Exploratory factor analysis revealed a three-factor structure underlying CSL learners' FLLB: classroom boredom, content boredom and teacher/learner boredom. Qualitative data enriched our understanding of the three-factor construct of FLLB and boredom sources in online classes. Results were discussed with reliance on the control-value theory of achievement emotions, previous findings, as well as their theoretical and practical implications for L2 teaching and learning. The newly found three-factor structure coincides with the long-lasting '3T' difficulties ['3T' difficulties refer to three major concerns in teaching CSL. They are connected with how to implement effective teaching strategies, develop high-quality teaching materials and build qualified and capable teaching teams] in International Chinese education;therefore, it inspires CSL researchers and teachers to attach more importance to the negative emotion of FLLB in the future.

A Novel Machine Learning-Assisted Policy Recommendation Method on COVID-19 Vaccination Campaign

As the most serious global infectious disease in the past 100 years, it has caused severe loss of life and property to countries and their people worldwide in the past year. As the most powerful tool in the fight against the epidemic, how to quickly promote the COVID-19 vaccine administration plays a vital role in gradually establishing an immune barrier in the population as soon as possible and blocking the COVID-19 epidemic. In this paper, we provide a machine learning-based policy recommendation method on the vaccination campaign of COVID-19 by minimizing three different cost factors: the duration of the pandemic, the budget of the COVID-19 battle as well as the death toll. To generate a more efficient vaccination policy, we construct an Age-stratified Susceptible-Infected-Recovered (ASSIR) model. We validate our method based on the real-world dataset of India by comparing our simulated results with the government's vaccination plan from machine learning prediction. Our approach shows a 13% decrease in disease control time and government budget. At the same time, we find out that vaccination based on each province's population leads to a 12.4% decrease in the death toll than on infection cases. The model developed in this study has practical implications for COVID-19 vaccination campaigns and the infection control of other infectious diseases. © 2021 IEEE.

Development of a SYBR Green I real-time PCR assay for detection of novel porcine parvovirus 7.

In this study, we developed a SYBR Green I real-time PCR method for the rapid and sensitive detection of novel porcine parvovirus 7 (PPV7). Specific primers were designed based on the highly conserved region within the Capsid gene of PPV7. The established method was 1,000 times more sensitive than the conventional PCR method and had a detection limit of 35.6 copies. This method was specific and had no cross-reactions with PCV2, PCV3, PRV, PEDV, PPV1, and PPV6. Experiments testing the intra and interassay precision demonstrated a high reproducibility. Testing the newly established method with 200 clinical samples revealed a detection rate up to 17.5% higher than that of the conventional PCR assay. The established method could provide technical support for clinical diagnosis and epidemiological investigation of PPV7.

TCM management of side-effects of COVID-19 vaccination

At the time of writing, the number of patients infected by COVID-19 and resulting deaths are still increasing worldwide, although the effectiveness of the available vaccines bodes well. However, side-effects of these vaccines have been reported, attracting expert and public attention. Although most of these side-effects are minor and transient, some can be more serious and long-term, and need medical intervention. According to traditional Chinese medicine (TCM) theory, most of these side-effects are the result of an invasion of external pathogenic wind-cold or toxic heat, exacerbated in some instances by underlying chronic illness or constitutional weakness. All of these factors need to be considered and treatment applied correctly in order to relieve symptoms and prevent long-term side-effects. This article describes the pathomechanism of vaccine side-effects and their treatment with TCM.

Expert consensus on emergency medicine procedure optimization guided by routine prevention and control strategy for COVID-19

The outbreak of coronavirus disease 2019 (COVID-19) was declared a global public health emergency on 31 January 2020. Emergency medicine procedures in Emergency Department should be optimized to cope with the current COVID-19 pandemic by providing subspecialty services, reducing the spread of nosocomial infections, and promoting its capabilities to handle emerging diseases. Thus, the Chinese Society of Emergency Medicine and Wuhan Society of Emergency Medicine drafted this consensus together to address concerns of medical staffs who work in Emergency Department. Based on in-depth review of COVID-19 diagnosis and treatment plans, literatures, as well as management approval, this consensus proposes recommendations for improving the rationalization and efficiency of emergency processes, reducing the risk of nosocomial infections, preventing hospital viral transmission, and ensuring patient safety. © 2021 Asian Pacific Journal of Tropical Medicine Produced by Wolters KluwerMedknow. All rights reserved.

An SEIR Model for Assessment of COVID-19 Pandemic Situation

The ongoing COVID-19 pandemic spread to the UK in early 2020 with the first few cases being identified in late January. A rapid increase in confirmed cases started in March, and the number of infected people is however unknown, largely due to the rather limited testing scale. A number of reports published so far reveal that the COVID-19 has long incubation period, high fatality ratio and non-specific symptoms, making this novel coronavirus far different from common seasonal influenza. In this note, we present a modified SEIR model which takes into account the latency effect and probability distribution of model states. Based on the proposed model, it was estimated in April 2020 that the actual total number of infected people by 1 April in the UK might have already exceeded 610,000. Average fatality rates under different assumptions at the beginning of April 2020 were also estimated. Our model also revealed that the R0 value was between 7.5–9 which is much larger than most of the previously reported values. The proposed model has a potential to be used for assessing future epidemic situations under different intervention strategies. © 2020, Springer Nature Singapore Pte Ltd.

The effects of psychological intervention on anxiety symptoms of COVID19-positive patients isolated in hospital wards.

OBJECTIVE: The study aimed to explore the effects of psychological intervention on alleviating anxiety in patients in novel coronavirus (2019-nCoV) isolation wards. PATIENTS AND METHODS: Between January 24th, 2020 and March 5th, 2020, 103 patients were studied. Among these, 32 were patients in the isolation ward of the Infectious Disease Department in Baoding Second Hospital with suspected 2019-nCoV, and 71 patients diagnosed with 2019-nCoV were in the Tangshan Infectious Disease Hospital. Of the 103 patients included, 97 cases were observed in isolation. Using a self-control study design, each patient's anxiety was scored on a self-rating anxiety scale before receiving the psychological intervention (on the 7th day of isolation) and after receiving the intervention (on the 14th day of isolation). The severity of anxiety was evaluated based on the anxiety score before receiving the intervention. The anxiety scores before and after receiving the intervention were then compared using the paired t-test, and p<0.05 was considered statistically significant. RESULTS: After receiving the psychological intervention once or twice a week, the anxiety of the patients improved significantly after one week. CONCLUSIONS: The anxiety of patients with 2019-nCoV in isolation wards can be alleviated through psychological intervention. By alleviating patient anxiety, this intervention also helps patients maintain their psychological wellbeing, which promotes rehabilitation and helps with the control of 2019-nCoV.

An analysis of the differences in anxiety and educational background among patients isolating due to COVID-19

Introduction: The present study intends to explore the relationship between anxiety and the educational background of patients in two isolation wards on day 7 of isolation during the epidemic of COVID-19. Materials and methods: Between January 24 and March 5, 2020, 32 patients admitted to the isolation ward of the Infectious Diseases Department of Baoding Second Hospital with suspected COVID-19, and 71 patients in isolation in Tangshan Infectious Disease Hospital with a confirmed diagnosis of COVID-19 were enrolled as the main research subjects, but the actual number of cases analyzed in the present study was 97. Their anxiety was measured by an anxiety scale (SAS scale) on day seven of their isolation. A t-test was used to compare the anxiety score data of the two groups, combined with a scatter plot analysis. P<0.01 was considered statistically significant. Results: There was a total of 97 patients, in two isolation wards, in the study, of whom 47 were male and 50 female. Nineteen of them had a degree above college level, while seventy-eight of them only had a college degree or lower. The results showed that there existed a correlation between the anxiety of patients in isolation during the COVID-19 epidemic and educational background, and that those with a degree above college level were more likely to develop anxiety. Conclusion: During the quarantine period, COVID-19 patients with a degree above college level were more likely to develop anxiety, and the degree of anxiety was more noticeable, while those with a lower level of education were relatively less anxious.

Implementation of a Computer Vision Framework for Tracking and Visualizing Face Mask Usage in Urban Environments

The COVID-19 pandemic is an evolving situation in the United States and is spreading at alarming rates. The adoption of public health-informed hygienic practices can have a large impact on community transmission of COVID-19 including the wearing of face masks in public settings. Convolutional Neural Networks (CNN) can be trained to classify people wearing face masks with impressive accuracy. However, current face mask datasets contain clear, high-resolution close-up images of individuals with face masks which is unrepresentative of the lower fidelity images of distant faces more prominent in urban camera images. This paper proposes a practical deep learning computer vision framework for detection and tracking of people in public spaces and the use of face masks. A custom 6,000 image face mask dataset curated from over 50 hours of urban surveillance camera footage is created in this work. CNN-based detectors trained using the dataset are used to perform person detection and face mask classification. Then, a multi-target tracking module extracts individual trajectories from frame-by-frame detection. By associating detected face masks with tracked individuals, overall face mask usage can be estimated. The framework is implemented on several surveillance cameras along the Detroit RiverWalk, a 5-kilometer pedestrian park connecting various greenways, plazas, pavilions, and open green spaces along the Detroit River in Detroit, Michigan. The detection of park user types is shown to have an average precision of 89% and higher for most person classes with the mask detector having an accuracy of 96%. An interactive web application visualizes the data and is used by park managers to inform management decisions and assess strategies used to increase face mask usage rates. © 2020 IEEE.

Acupuncture strategies to tackle post covid-19 psychological and neuropsychiatric disorders

From the perspective of traditional Chinese medicine, COVID-19 poses significant challenges to a human’s xing (physical body, internal organs), qi (气, vital energy) and shen (mind, spirit). This article explains the close relationship of these three aspects of the human being and how they are affected by COVID-19 to cause neuropsychiatric disorders. The authors explain how acupuncture can be utilised to adjust xing, regulate qi and balance shen in order to effectively treat post-COVID-19 psychological and neuropsychiatric symptoms.