Covering conflicts and risks: Chinese newspapers' peace-loving discourse and their use of risk language

The process through which people and society begin to see and frame something as risky is complex. As risk communication practitioners play a critical role in fostering real-world risk governance, this study emphasizes the performative role of language in mobilizing symbolic resources to build and control risks from a communication standpoint. Critical discourse analysis (CDA) was used to reveal patterns of how two events - the COVID-19 pandemic and the Russia-Ukraine dispute - were covered by the Chinese media, and speculate about the relationship between risk communication practice and its wider geopolitical context. Results revealed different frames were used for the two events, and that 'threat' was most frequently used when addressing the Russia-Ukraine dispute, whereas 'risk' was adopted for most COVID-19-related articles. Two themes were generated when interpreting the discourse through a critical geopolitical approach: 'From the COVID-19 Approach to the Political Systems' and 'China as a global Player through its peaceful Rise'. While China prefers to maintain peace in its interaction with other global actors, the Chinese government does not simply accept adversity, particularly when it comes to geopolitical conflicts derived from arbitrary ideological disagreements. The study adds to the current literature on the relationship between the practice and context of risk communication, as well as to the underrepresented regional online news coverage of risks and conflicts that focus on China.

Impact of participation in the belt and road initiative on regional economic resilience at province level

PurposeThis study aims to examine how participation in the Belt and Road Initiative (BRI) affects province-level regional economic resilience. In the context of dual circulation - the new development paradigm proposed by the Chinese Government - participating in the BRI is an important means of connecting both international and domestic circulations and achieving high economic resilience. The complex causal relationship between participation in the BRI and province-level regional economic resilience is investigated. Design/methodology/approachBased on the complex system view, this study uses fuzzy set qualitative comparative analysis (fsQCA) to examine the impact on regional economic resilience when provinces participate in the BRI through unimpeded trade, infrastructure connectivity, financial integration and people-to-people bonds under the two conditions of attention allocation and buffering capacity. Qualitative textual analysis is applied to analyse provincial work reports, and relevant statistical data are used to measure the economic resilience from 2013 to 2020. FindingsThe authors identified three condition configurations that lead to a high regional economic resilience at province-level and one condition configuration that lead to no high-level regional economic resilience. Research limitations/implicationsIn-depth analyses of qualitative materials should be conducted to explain the systematic relationships among the conditions. Originality/valueThis research is of practical significance to the development of the theoretical framework and practices of the BRI in the context of dual circulation.

A real-time monitoring platform of colorimetric LAMP for developing rapid visual detection kits of SARS-CoV-2

Visual detection of nucleic acids is important to diagnose the serious acute infectious diseases such as coronavirus disease 2019 (COVID-19). During this pandemic, reliable visual detection kits have been in high demand for screening and prevention of the virus. While developing these visual detection kits, a real-time monitoring platform is usually applied to study the amplification and detection processes of nucleic acids and optimize the detecting conditions. Herein, we developed a real-time monitoring platform of colorimetric loop-mediated isothermal amplification (LAMP) to investigate the amplification and detection processes of nucleic acids. Using this platform, we could obtain the real-time amplification curves, and optimize the reaction temperature, color change, and detection time. Based on the optimized conditions, a visual detection kit for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was successfully developed with a sensitivity of 102 copies µL−1 in 12 min. This real-time monitoring platform has advantages of simple construction, steady performance, high sensitivity, and outstanding anti-pollution capability, and could replace the traditional colorimetric methods by photographing and reading values. This platform would accelerate the development of visual detection kits for colorimetric LAMP, help to explore the amplification and transcription of nucleic acids, and provide support for the prevention of emerging biological threats. © 2023

A new method for accurate calculation of case fatality rates during a pandemic: Mathematical deduction based on population-level big data

Background: During the course of an epidemic of a potentially fatal disease, it is difficult to accurately estimate the case fatality rate (CFR) because many calculation methods do not account for the delay between case confirmation and disease outcome. Taking the coronavirus disease-2019 (COVID-19) as an example, this study aimed to develop a new method for CFR calculation while the pandemic was ongoing. Methods: We developed a new method for CFR calculation based on the following formula: number of deaths divided by the number of cases T days before, where T is the average delay between case confirmation and disease outcome. An objective law was found using simulated data that states if the hypothesized T is equal to the true T, the calculated real-time CFR remains constant;whereas if the hypothesized T is greater (or smaller) than the true T, the real-time CFR will gradually decrease (or increase) as the days progress until it approaches the true CFR. Results: Based on the discovered law, it was estimated that the true CFR of COVID-19 at the initial stage of the pandemic in China, excluding Hubei Province, was 0.8%;and in Hubei Province, it was 6.6%. The calculated CFRs predicted the death count with almost complete accuracy. Conclusions: The method could be used for the accurate calculation of the true CFR during a pandemic, instead of waiting until the end of the pandemic, whether the pandemic is under control or not. It could provide those involved in outbreak control a clear view of the timeliness of case confirmations. © 2023 The Author(s)

The current developments in oncology nursing: A review

Cancer has become one of the major causes of death in the growing world population, affecting people irrespective of their age, sex and culture. Cancer diagnosis and therapy is a distressing procedure and affects the physical, emotional and mental well-being of the patient. Many studies have reported that cancer has a long-term impact on patient's lives leading to mood dysfunction, heart problems and chemotherapy toxicity. Modern-day healthcare systems are moving towards a patient-oriented approach and are designed around the patient's well-being, needs and preferences. Oncology nurses form the fundamental part of this system and provide the patient with the much-needed care, support and hope for life. Oncology nursing has developed and evolved briefly in the recent few decades due to the advancement in treatment procedures. As cancer care continues to progress, nurses play a vital role in the field of oncology. Specialized oncology nurses are providing clinical care, or as nurse researchers leading revolutionary oncology research. The future of oncology nursing is optimistic. Nursing care for cancer patients not only requires guidance through medication and treatment, but also offers encouragement and motivation to the patients. The present review provides an insight into the nursing care of cancer patients, its brief history, advancements and the current practices of oncology nursing. Future prospects of oncology nursing have also been discussed in detail.Copyright © 2022, Kuwait Medical Association. All rights reserved.

Tea Culture Tourism Perception: A Study on the Harmony of Importance and Performance

Tea culture tourism is a product of the combination of agricultural tourism and ecotourism. After the COVID-19 period, this product is more and more popular. Tourism performance is an important index for measuring the development level of tourist destinations, and research on the influencing factors of tourism performance is an important way to promote the high-quality development of tea culture tourism. Using the tea tourism town of Wushan as a case study, 452 valid questionnaires were used as research data, and exploratory factor analysis, paired sample t-test and IPA analysis were applied. The results indicate that: (1) tourism performance is mainly divided into 5 dimensions and 22 specific indicators, including service quality, resource environment, tourism transportation, tourism-supporting facilities and tea tourism products;(2) there is a significant difference between the degree of importance and performance of visitors to each indicator, and the overall tourism performance of the case sites at an average level;(3) convenient service, professional service, business management, park traffic, parking conditions, environmental design, shopping environment, tea quality, and tea culture characteristics are potential advantageous factors, and ‘service with a smile', accessibility, trail layout, overall image, air quality, natural scenery, landscape vignettes, network communication, public toilets, sanitation facilities, tourist service centers, tea travel activities, and tourism souvenirs are areas in need of improvement. © 2023 by the authors.

The 2021 SIIM-FISABIO-RSNA Machine Learning COVID-19 Challenge: Annotation and Standard Exam Classification of COVID-19 Chest Radiographs.

We describe the curation, annotation methodology, and characteristics of the dataset used in an artificial intelligence challenge for detection and localization of COVID-19 on chest radiographs. The chest radiographs were annotated by an international group of radiologists into four mutually exclusive categories, including "typical," "indeterminate," and "atypical appearance" for COVID-19, or "negative for pneumonia," adapted from previously published guidelines, and bounding boxes were placed on airspace opacities. This dataset and respective annotations are available to researchers for academic and noncommercial use.

[Analysis on the household secondary attack rates of the SARS-CoV-2 Delta variant and the associated factors].

Objective: To evaluate the household secondary attack rates of the SARS-CoV-2 Delta variant and the associated factors. Methods: A COVID-19 outbreak caused by the Delta variant occurred in Nanjing in July 2021. A total of 235 cases with current addresses in Nanjing were reported from 171 households. The subjects in this study were selected from household close contact(s) of infected cases. The information on household index cases and their contacts were collected, and the household secondary attack rate (HSAR) and the risk factors were analyzed by the multi-factor logistic regression model. Results: A total of 234 cases of household close contacts and 64 household secondary cases were reported from 103 households, and the HSAR was 27.4% (64/234, 95%CI:22.0% to 33.4%). The proportions of household size for 2 to 3, 4 to 5, and 6 to 9 were 64.1% (66), 26.2% (27) and 9.7% (10), respectively. A total of 35 cases of household cluster outbreaks were reported (35/103, 34.0%). The number of the first case in the household (FCH) was 103 and males accounted for 27.2% (28 cases), with the median age (Q1, Q3) of 49 (9, 56). The number of household close contacts was 234 and males accounted for 59.0% (138 cases), with the median age (Q1, Q3) of 42 (20, 55) and the median exposure period (Q1, Q3) of 3 (1, 3) days. The multi-factor logistic regression model showed that the higher HSAR was observed in the FCH with the features of airport staff (OR=2.913, 95%CI:1.469-5.774), detection from home quarantine screening (OR=6.795, 95%CI:1.761-26.219) and detection from mass screening (OR=4.239, 95%CI:1.098-16.368). Meanwhile, higher HSAR was observed in cases with longer household exposure (OR=1.221, 95%CI:1.040-1.432), non-vaccination (OR=2.963, 95%CI:1.288-6.813) and incomplete vaccinations (OR=2.842, 95%CI:0.925-8.731). Conclusion: The generation interval of the Delta variant is shortened, and the ability of transmission within the household is enhanced. In the outbreak in Nanjing, the associated factors of HSAR are occupation, detection route, vaccination and exposure period.

Effectiveness of Different Control Measures on the Spread of COVID-19

The COVID-19 pandemic has influenced most of the population worldwide. It is essential to assess the effectiveness of different control measures on the spread of the virus. In this paper, the author uses an SEIR agent-based model on the NetLogo platform to establish a simulation model and define seven types of agents: susceptible, infectious, mask-wearing, quarantined, exposed, and vaccinated. We performed an analysis of four possible scenarios: (1) doing nothing, (2) quarantine, (3) using face masks, and (4) vaccination. It is concluded that the adoption of different control measures could quickly control the epidemic situation. The use of vaccination also has a huge impact on the pressure of epidemic control. Nevertheless, If control measures are not put in place, the duration of the epidemic will be significantly prolonged. © 2022 ACM.

The development and implementation of training mode for diabetes educators amid normalization stage of novel coronavirus pandemic prevention and control

Objective To develop an program for training diabetes educators amid normalization stage of novel coronavirus pandemic prevention and control, and provide reference for clinical teaching under special circumstances. Methods From January 2020 to June 2021, The head member of Diabetes Education and Management Committee of Hunan Health Management Association Xiangya Hospital of Central South University, developed and implemented a program based on core competencies of diabetes educators. It included 26 online courses, one to one education demonstration video with 7 themes, one diabetes conversation map and simulation, and three-week clinical practice. From April 2021 to June 2021, 55 health workers participated in the program. Theoretical tests, video feedback and questionnaires were used to evaluate the trainees′ diabetes knowledge, educational skills and satisfaction with the training program. Results A total of 55 health workers participated in the program. All the participants completed the online courses and passed the quizzes, the theoretical examination score was (92.93 ± 5.28). Fifty-four participants finished the tasks of clinical practice and obtained the certificate of diabetes educator. Their communication skills and strategies of behavior change were significantly improved (χ2 values were 4.17 - 26.34, all P＜0.05), and all of them were satisfied with the program. Conclusions The training mode based on online training is flexible, convenient and effective,which is suitable for stage of novel coronavirus pandemic prevention and control. © 2022 The authors.

Exploring Feature Genes for Ischemic Stroke Based on Bioinformatics and Machine Learning

Background and Aims: This study aims to screen the feature genes of ischemic stroke (IS) by bioinformatics and machine learning (ML) and explore the possible pathophysiological mechanism of the genes in IS. Method(s): Two RNA sequencing datasets were downloaded from NCBI Gene Expression Omnibus (GEO) database. The GSE122709 dataset with a larger sample size was used as the training set and analyzed for differentially expressed genes (DEGs), while the GSE140275 dataset was used as the test set. The DEGs were further analyzed for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Disease Ontology (DO) enrichment analyses. Then, feature genes selection was performed by two ML algorithms. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of the ML algorithms. Result(s): A total of 378 DEGs (Fold Change>=2 and p value<=0.05) were identified. The GO and KEGG analyses demonstrated that the majority of DEGs were associated with inflammatory response, immune regulation and COVID-19. The DO analysis revealed that the DEGs were mainly linked to demyelinating disease and cancer. The TVP23C and B3GAT1 were identified as feature genes by ML algorithms, and the AUCs of them were closer to 1 both in the training and test set. It is found that B3GAT1 may be involved in brain injury of IS by regulating AMRA glutamate receptors. Conclusion(s): The integrated approach of bioinformatics and ML could be a novel approaches for screening feature genes, and the B3GAT1 gene may be a possible therapeutic target in IS.

Design of epidemic detection system in railway station based on FPGA

Since the outbreak of COVID-19 in 2020, wearing masks and displaying green codes in and out of public places has become a habit. The identity verification of the existing railway station is mainly based on face recognition. Due to the outbreak and persistence of the epidemic, people often need to call out the green code on their mobile phones for staff verification, which takes a lot of time. At the same time, the existing face recognition equipment requires the inbound personnel to take off their masks, which also increases the infection risk of the inbound personnel. In order to reduce the above infection risk and speed up people's entry and exit speed, we have designed a system that can identify people wearing masks and judge whether they are confirmed or suspected cases at the same time. Firstly, the system measures the passenger's body temperature through the infrared temperature measurement module, carries out face detection and recognition at the same time, and queries the recognition results in the database to judge whether the passenger is diagnosed or in close contact. When the passenger is normal, it is allowed to pass, otherwise it is not allowed to pass, and updates the relevant data in the cloud database. The system uses Yolo algorithm as the face detection algorithm, and then carries out face recognition through FaceNet network, so as to judge its identity and query the relevant information of the person in the cloud database. After testing, the iterative loss rate of the system is basically below 0.1 and the accuracy is basically stable above 99%. Considering that we need to use it on embedded devices and the amount of calculation operation of deep learning algorithm is large, and FPGA can well build circuits according to the needs of the model because of its reconfigurability, and FPGA can realize hardware acceleration because it can run in parallel, so we finally choose to deploy the model to FPGA to complete face recognition. © 2022 IEEE.

Dynamic volatility connectedness among cryptocurrencies and China's financial assets in standard times and during the COVID-19 pandemic

In this paper, we use the time-varying parameter vector autoregressions (TVP-VAR) model to examine volatility connectedness among 5 cryptocurrencies and 5 China's financial assets in static and dynamic scenarios. We find that the dynamic total connectedness of the system exhibits large dynamic variability. When the total connectedness breaks through 50%, it will move down rapidly. Ethereum and Litecoin are increasing their influence, whereas Bitcoin is losing its leadership. The impact of the cryptocurrency market on China's financial market has become very small since 2022Q1. Furthermore, the COVID-19 outbreak has a long-term (short-term) impact on the gold market (the other markets).

Investigating Students' Experiences with Collaboration Analytics for Remote Group Meetings

Remote meetings have become the norm for most students learning synchronously at a distance during the ongoing coronavirus pandemic. This has motivated the use of artificial intelligence in education (AIED) solutions to support the teaching and learning practice in these settings. However, the use of such solutions requires new research particularly with regards to the human factors that ultimately shape the future design and implementations. In this paper, we build on the emerging literature on human-centredAIED and explore students' experiences after interacting with a tool that monitors their collaboration in remote meetings (i.e., using Zoom) during 10 weeks. Using the social translucence framework, we probed into the feedback provided by twenty students regarding the design and implementation requirements of the system after their exposure to the tool in their course. The results revealed valuable insights in terms of visibility (what should be made visible to students via the system), awareness (how can this information increase students' understanding of collaboration performance), and accountability (to what extent students take responsibility of changing their behaviours based on the system's feedback);as well as the ethical and privacy aspects related to the use of collaboration analytics tools in remote meetings. This study provides key suggestions for the future design and implementations of AIED systems for remote meetings in educational settings.

Facial Flap Necrosis From COVID-19 Face Mask Precautions

: Use of facial mask coverings has been a strong Centers for Disease Control and Prevention recommendation as an essential mitigation measure in the spread of the SARS-CoV-2 novel coronavirus (COVID)-19 virus. Face mask utilization has been shown to induce changes in the skin microclimate, especially around the perioral and perinasal regions. This results in increased mask adjustments and development of friction between masks and the underlying skin. The authors report novel findings of 2 individuals with skin cancer who underwent facial reconstruction during the COVID-19 pandemic. They encountered untoward sequelae of facial flap pressure necrosis due to the use of face mask coverings. These individuals were ultimately successfully treated with local wound care. One individual experienced auricular implant extrusion and flap loss. It is critical that reconstructive surgeons be aware of potential complications and the need for potential revision surgeries due to the use of face masks, and educate their patients to properly position the protective face masks based on the type of reconstruction performed. Plastic surgeons might also reconsider reconstructive management options in light of these additional obstacles.

Research on logistics UAV task assignment based on improved ant colony algorithm

Logistics UAV delivery has been well developed in the fight against COVID-19 pneumonia, and attracts more and more scholars to research. Ant Colony Optimization (ACO) is one of the effective solutions to solve the UAV task assignment problem. The algorithm adopts the principle of positive feedback to speed up the evolution process. However, the algorithm has some defects, such as long search time, easy to fall into local optimum and so on. Aiming at the defects of ACO, we put forward two improvements in this paper: On the one hand, differential distribution of initial pheromone is proposed to avoid blind search in the initial stage and improve the convergence speed. On the other hand, we will reduce the number of candidate nodes in the dynamic strategy, and ants choose the next node in the dynamic candidate list to reduce the calculation of local exploitation. Simulation results show that the improved ACO can significantly improve the convergence speed and has a good effect on solving the task assignment problem of logistics UAV. © 2022 SPIE.

Aerosol generation from tear film during non-contact tonometer measurement

Aerosols, generated and expelled during common human physiological activities or medical procedures, become a vital carrier for the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). During non-contact intraocular pressure measurements, aerosols can be produced from the tear film on eyes and potentially convey the SARS-CoV-2 in tears, creating a high risk for eye care practitioners and patients. Herein, we numerically investigate deformation and fragmentation of the tear films with various thicknesses and surface tensions that are impinged by an air jet. Evolution of the tear films manifests several types of breakup mechanisms, including both the bag breakup and ligament breakup of tear film on the eyeball, the ligament breakup of tear film on the eyelid margin, and the sheet breakup near the eyelid margin. The sheet near the eyelid margin is critical for generating large droplets and can be formed only if the jet velocity is high enough and the film is sufficiently thick. A criterion based on Weber number and capillary number is proposed for the breakup of tear film into droplets in which three regions are used to classify the film evolution. Our results indicate that eyes with excessive tears have a greater probability of generating aerosols than eyes under normal conditions. We recommend that enhanced protections should be adopted upon measurement for the patients with watery eyes, and the time interval between two adjacent measurements for the same individual should be also prolonged during the COVID-19 pandemic. Published under an exclusive license by AIP Publishing.

Ethical Dilemma in Global Vaccine Cooperation and Its Countermeasures: Taking the Global Eradication of Smallpox as an Example

Vaccine cooperation is an important means to deal with global infectious diseases. However, the cooperation cannot be achieved overnight. Ethical dilemma is one of the obstacles that hinders vaccine cooperation. Reviewing the history, the most successful vaccine collaboration to date has been the global smallpox eradication program. In the process of eradicating smallpox, there were also many ethical dilemmas, including the international pattern of the US-Soviet hegemony, which impacted the mutual help between countries, the ethical disputes of the vaccine itself hindering solidarity and cooperation among actors, and the vaccine coercion adopted to overcome vaccine hesitancy undermining the principle of proportionality among the freedom, equality and efficacy. The ethical dilemmas of vaccine cooperation were resolved by shaping professional and scientific consensus among medical professional groups, reaching consensus on cooperation between leading countries and developing countries, and integrating local culture to improve vaccination methods. Finally, in 1980, the world successfully eradicated smallpox. The case of smallpox eradication provides us lessons for vaccine cooperation against COVID-19 and the construction of a community of common health for mankind today. © 2022, Editorial department of Chinese Medical Ethics. All rights reserved.

Mechanisms of action (MOA) for proxalutamide, an androgen receptor (AR) antagonist, for the treatment of mild, moderate and severe COVID-19 patients

As of November 2021, there were 21 million confirmed active cases of COVID-19, including 77,016 patients in serious or critical condition (virusncov.com). However, there are no effective oral drugs for the treatment of severe COVID 19 patients. We here discuss the mechanism of action for Proxalutaminde to treat mild, moderate and severe COVID-19 Patients. Cellular entry and infection of SARS-CoV-2 virus are mediated by two key proteins in host cells, angiotensin converting enzyme 2 (ACE2), a host transmembrane protein, providing the binding sites for SARS-CoV-2 on the host cell surface, and transmembrane protease serine 2 protein (TMPRSS2), priming the S protein of SARS-Cov-2 to facilitate the viral entry into the host cells. Both ACE2 and TMPRSS2 proteins are regulated by androgen receptor (AR) signaling. Previously, Proxalutamide has been reported to downregulate the expression of ACE2 and TMPRSS2 in cells derived from prostate, lung cancer and normal lung epithelial cells. In this study, we demonstrate that Proxalutamide inhibited the infection of SARS-COV-2 wild type, alpha and delta variants, with IC50s of 69, 48 and 39 nM, respectively. Moreover, Proxalutamide reduced SARS-COV-2 viral load in outpatients with COVID-19 (82% viral RT-PCR negative rate in active group vs. 31% in placebo group after treatment for 7 days (p-value<0.0001). Severe COVID-19 disease leads to cytokine storm resulting in pulmonary inflammation and extensive damage in lung and other organs. Anti-inflammatory drugs, including Baricitinib and dexamethasone, have shown limited clinical benefit for hospitalized COVID-19 patients. Therefore, more effective drugs are in urgent need for patients suffering from severe COVID-19. Recently, Proxalutamide has been reported to reduce the mortality rate (HR=0.16) and lung injury (by 57%, active drug vs placebo groups) in hospitalized patients with COVID-19 in an IIT phase III study. We presented here the mechanism of action of Proxalutamide for targeting cytokine storm in severe COVID-19 patients. Proxalutamide was demonstrated to activate nuclear factor erythroid 2-related factor 2 (Nrf2) in macrophages, which stimulates the antioxidant response element (ARE) for reducing cytokine storm-induced organ damage in COVID-19. In addition, Proxalutamide inhibited TNF alpha and IL-6 expression and blocked INF gamma signaling by downregulating STAT1 expression in immune cells. Importantly, Proxalutamide reduced inflammatory cells in lungs in a Poly (I:C), pseudoviral induced-lung injury animal models. Further, Proxalutamide decreased C-reactive protein, D-Dimer and improved lymphocyte count, biomarkers for COVID-19 progression in clinical studies. Together, these results provide a strong rationale for the treatment of severe COVID-19 patients with Proxalutamide.