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Tribo-tests play a crucial role in the evaluation of the material performance of tribo-pairs. Traditionally, tribo-tests are performed onsite and tightly depend on experienced human operators. However, some public health emergencies such as covid-19 have a substantial impact on daily human life, including product and service systems. Therefore, this chapter aims to develop a new tribo-test service pattern, that is, digital twin enhanced remote tribo-test. A digital twin enhanced tribo-test service framework is proposed, which includes the modeling stage and the application stage of tribo-test service. A case study is presented to showcase how to implement the proposed framework. © 2022 Elsevier Inc. All rights reserved.
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The immune system is developed to preserve its hosts from an ever-expanding cluster of pathogenic microbes. The elimination of toxic substances, allergens, or any other harmful existences that come in, passing the mucosal surfaces, is as well the responsibility of this special system. Its ability to distinguish self (our bodies' functioning cells and tissues) from non-self is the key aspect to its ability to mobilize some reaction to an invasion initiated by the stranger substances listed above. To identify and kill unsafe microorganisms, the host applies both natural and versatile systems, our innate and adaptive immune systems. Vaccines are used to combat the current SARS-CoV-2 strain by utilizing immune system mechanisms, specifically the adaptive immune system. Vectored vaccines, protein vaccines, genetic vaccine, and monoclonal antibody for passive vaccination are among the vaccine platforms under consideration for SARS-CoV-2. Each vaccine has its own benefits and drawbacks. This paper is written to describe the three major forms of COVID-19 vaccines, as well as the unique mechanisms of elements of the immune system associated with the virus. © 2023 SPIE.
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At present, due to the COVID-19, China's social and economic development has slowed down. Some life service e-commerce platforms have successively launched "contactless delivery" services, which can effectively curb the spread of the epidemic. Robot distribution is the current mainstream, but robots are different from people and need to have accurate program settings. Both path planning and obstacle avoidance are currently top issues. This requires the mobile robot to successfully arrive at the destination while minimizing the impact on the surrounding environment and pedestrians, and avoiding encroachment on the movement space of pedestrians. Therefore, the mobile robot needs to be able to actively avoid moving pedestrians in a dynamic environment, in addition to avoiding static obstacles, and safely and efficiently integrate into the pedestrian movement environment. In this paper, the path planning problem of unmanned delivery robot is studied, and the path of mobile robot in the crowd is determined by global planning and local planning, and the matlab simulation is used for verification. © The Authors. Published under a Creative Commons Attribution CC-BY 3.0 License.
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Background & Aim: The long-term effects of human mesenchymal stem cell (MSC) treatment on COVID-19 patients have not been fully characterized. The aim of this study was to evaluate the safety and efficacy of a MSC treatment administered to severe COVID-19 patients enrolled in a randomized, double-blind, placebo-controlled clinical trial (NCT 04288102). Methods, Results & Conclusion(s): A total of 100 patients experiencing severe COVID-19 received either MSC treatment (n = 65, 4x107 cells per infusion) or a placebo (n = 35) combined with standard of care on days 0, 3, and 6. Patients were subsequently evaluated 18 and 24 months after treatment to evaluate the long-term safety and efficacy of the MSC treatment. The outcomes measured included: 6-minute walking distance (6-MWD), lung imaging, quality of life according to the Short Form 36 questionnaire, COVID-19-related symptoms, titers of SARS-CoV-2 neutralizing antibodies, MSC-related adverse events (AEs), and tumor markers. Two years after treatment, a marginally smaller proportion of patients had a 6-MWD below the lower limit of the normal range in the MSC group than in the placebo group (OR = 0.19, 95% CI: 0.04-0.80, Fisher's exact test, p = 0.015). On the SF-36 questionnaire, a marginally higher general health score was received by the MSC group at month 18 compared with the placebo group (50.00 vs. 35.00;95% CI: 0.00-20.00, Wilcoxon rank sum test, p = 0.016). In contrast, there were no differences in the total severity score of lung imaging or the titer of neutralizing antibodies between the two groups. Meanwhile, there were no MSC-related AEs reported at the 18- or 24-month follow-ups. The serum levels of most of the tumor markers examined remained within normal ranges and were similar between the MSC and placebo groups. Long-term safety was observed for the COVID-19 patients who received MSC treatment. Yet few sustained efficacy of MSC treatment was observed at the end of the 2-year follow-up period. Funding(s): The National Key Research and Development Program of China (2022YFA1105604, 2020YFC0860900), the specific research fund of The Innovation Platform for Academicians of Hainan Province (YSPTZX202216) and the Fund of National Clinical Center for Infectious Diseases, PLA General Hospital (NCRCID202105,413FZT6). [Figure presented]Copyright © 2023 International Society for Cell & Gene Therapy
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To assess a Smart Imagery Framing and Truthing (SIFT) system in automatically labeling and annotating chest X-ray (CXR) images with multiple diseases as an assist to radiologists on multi-disease CXRs. SIFT system was developed by integrating a convolutional neural network based-augmented MaskR-CNN and a multi-layer perceptron neural network. It is trained with images containing 307,415 ROIs representing 69 different abnormalities and 67,071 normal CXRs. SIFT automatically labels ROIs with a specific type of abnormality, annotates fine-grained boundary, gives confidence score, and recommends other possible types of abnormality. An independent set of 178 CXRs containing 272 ROIs depicting five different abnormalities including pulmonary tuberculosis, pulmonary nodule, pneumonia, COVID-19, and fibrogenesis was used to evaluate radiologists' performance based on three radiologists in a double-blinded study. The radiologist first manually annotated each ROI without SIFT. Two weeks later, the radiologist annotated the same ROIs with SIFT aid to generate final results. Evaluation of consistency, efficiency and accuracy for radiologists with and without SIFT was conducted. After using SIFT, radiologists accept 93% SIFT annotated area, and variation across annotated area reduce by 28.23%. Inter-observer variation improves by 25.27% on averaged IOU. The consensus true positive rate increases by 5.00% (p=0.16), and false positive rate decreases by 27.70% (p<0.001). The radiologist's time to annotate these cases decreases by 42.30%. Performance in labelling abnormalities statistically remains the same. Independent observer study showed that SIFT is a promising step toward improving the consistency and efficiency of annotation, which is important for improving clinical X-ray diagnostic and monitoring efficiency. © 2023 SPIE.
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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as COVID-19, is much more difficult to transmit through the ocular surface than that through the mouth and nose. However, the available evidence has suggested the possibility of ocular surface transmission, especially in medical staff. In this paper, we describe the existing SARS-CoV-2 ocular surface symptoms, the possible mechanism of SARS-COV-2 entering ocular surface cells and SARS-COV-2 transmission through ocular surface. In addition, the existing and future possible research directions of SARS-CoV-2 transmission through ocular surface were analyzed, so as to provide new ideas and methods for clinical treatment of SARS-CoV-2 from the perspective of ocular surface.Copyright © 2021, Xinxiang Medical University. All rights reserved.
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In light of the fast-spreading number of COVID-19 cases worldwide, contact tracing proved to be an effective measure to slow down the infection rate and mitigate the casualties caused by this virus. However, because of several concerns in terms of privacy, as well as security, several countries and their population around the globe are reluctant to adopt contact tracing solutions to contain the spread of the virus. Because of its distributed, public, and auditable nature, blockchain can be a groundbreaking solution contact tracing, given that it would provide a privacy-oriented contact tracing solution. Therefore, in this chapter, we discuss and compare the two alternatives proposed by the BeepTrace framework, active and passive, and also present some initial results based on an early implementation of it. As it can be seen, by utilizing blockchain together with contact tracing, user privacy, security, and decentralization can be guaranteed, giving back the trust needed for these applications to work. © 2022 by John Wiley & Sons Ltd. All rights reserved.
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COVID-19's impacts have spread widely in all directions such as economy, people's lifestyles and well-being. Though existing studies have highlighted such an impact, it remains unclear how the current COVID-19 situation has affected the retrenchment, vaccination and global happiness. In this paper, we present an automated tool enables the public to view various insight. In particular, we integrate and analyze the data from various data sources and show how the COVID19 has impacted Singapore and globally. We employ the regression models to identify the correlation between Human Development Index, Stringency Index, Gross Domestic Product per Capita, Total Deaths from COVID-19, and Total Cases of COVID-19;the rate of vaccination and vaccine hesitancy;and the factors to positively correlate to the global happiness. The insight provided adds values to better fight against the COVID-19 pandemic and future global crisis. © 2023 IEEE.
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The COVID-19 pandemic has exacerbated the tension and underscores the importance of cooperation between the United States and China on shared interests even as they compete ferociously on almost all fronts. While a duopoly with China and the United States working in tandem is unlikely because of their increasingly competitive relationship, a large-scale conflict shall be extremely costly as neither is strong enough to prevail. Under above background, this paper describes the grim nature of the current Sino-US relations and the expected trend of Sino-US rivalry in the post-pandemic era. We expect that both United States and China can mutually prevent deeper and larger conflicts from happening, as well as maintain rational economic and political interactions under an integrated and effective global governance mechanism. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.
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The immune system is developed to preserve its hosts from an ever-expanding cluster of pathogenic microbes. The elimination of toxic substances, allergens, or any other harmful existences that come in, passing the mucosal surfaces, is as well the responsibility of this special system. Its ability to distinguish self (our bodies' functioning cells and tissues) from non-self is the key aspect to its ability to mobilize some reaction to an invasion initiated by the stranger substances listed above. To identify and kill unsafe microorganisms, the host applies both natural and versatile systems, our innate and adaptive immune systems. Vaccines are used to combat the current SARS-CoV-2 strain by utilizing immune system mechanisms, specifically the adaptive immune system. Vectored vaccines, protein vaccines, genetic vaccine, and monoclonal antibody for passive vaccination are among the vaccine platforms under consideration for SARS-CoV-2. Each vaccine has its own benefits and drawbacks. This paper is written to describe the three major forms of COVID-19 vaccines, as well as the unique mechanisms of elements of the immune system associated with the virus. © 2023 SPIE.
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At present, the Covid-19 epidemic is still spreading globally. Although the domestic epidemic has been well controlled, the prevention and control of the epidemic must not be taken lightly. Being able to count the number of people in public places in real time has played a vital role in the prevention and control of the epidemic. Deep learning networks usually cannot be directly deployed on embedded devices with low computing power due to the huge amount of parameters of convolutional neural networks. This article is based on the YOLOv5 object detection algorithm and Jetson Nano embedded platform with TensorRT and C++ accelerating, it can realize the function of counting the number of people in the classroom, on the elevator entrance, and other scenes. © 2022 SPIE.
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Objective To explore the teaching effect of the teaching mode changed from traditional teaching to online teaching after the outbreak of coronavirus disease 2019 (COVID-19) pandemic. Methods Relying on the Beijing Women's Health Care Technology Improvement Project, the online and offline continuing medical education was carried out, to train the obstetrician and gynecologist working in 16 maternal and child health care hospitals in 16 administrative regions of Beijing, which was planned from September 2020 to December 2025. This study retrospectively collected the assessment results of the two teaching modes from March 2021 to December 2021 (the first year of the teaching plan), and compared the teaching effects. Results Online teaching completed three sessions of 30 live online conference courses, with about 25 000 participants, including 4757 obstetricians and gynecologists from 16 maternal and child health care hospitals in Beijing. A total of 82 on-site teaching courses were held for offline teaching, and 1771 gynecologists and obstetricians from 16 maternity and child care hospitals in Beijing participated in the study. The scores of online teaching and offline teaching were 90.88+/-4.88 and 88.65+/-4.35, respectively. Conclusions Online teaching maybe has similar teaching effects as offline teaching. Compared with offline teaching, online teaching has more advantages, such as convenience, efficiency and economy, which is worthy of promotion and application in the context of the COVID-19 pandemic.Copyright © 2022, Peking Union Medical College Hospital. All rights reserved.
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State and local governments have imposed health policies to contain the spread of COVID-19 since it had a serious impact on human daily life. However, the public stance on these measures may be time-varying. It is likely to escalate the infection in the area where the public is negative or resistant. To take advantage of the correlation between public stance on health policies and the COVID-19 statistics, we propose a novel framework, Multitask Learning Neural Networks for Pandemic Prediction with Public Stance Enhancement (MP3), which is composed of three modules: (1) Stance awareness module to make stance detection on health policies from users' tweets in social media and convert them into a stance time series. (2) Temporal feature extraction module that applies Convolution Neural Network and Recurrent Neural Network to extract and fuse local patterns and long-term correlations from COVID-19 statistics. Moreover, a Stance Latency-aware Attention is proposed to capture dynamic social effects and fuse them with temporal features. (3) Multi-task prediction module to adopt Graph Convolution Network to model the spread of pandemic and employ multi-task learning to simultaneously predict COVID-19 statistics and the trend of public stance on health policies. The proposed framework outperforms state-of-the-art baselines on both confirmed cases and deaths prediction tasks. © 2022 IEEE.
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Objective: To explore the guidance value of "treatment of disease in accordance with three conditions" theory in the prevention and treatment of corona virus disease 2019 (COVID-19) based on the differences of syndromes and traditional Chinese medicine (TCM) treatments in COVID-19 patients from Xingtai Hospital of Chinese Medicine of Hebei province and Ruili Hospital of Chinese Medicine and Dai Medicine of Yunnan province and discuss its significance in the prevention and treatment of the unexpected acute infectious diseases. Method(s): Demographics data and clinical characteristics of COVID-19 patients from the two hospitals were collected retrospectively and analyzed by SPSS 18.0. The information on formulas was obtained from the hospital information system (HIS) of the two hospitals and analyzed by the big data intelligent processing and knowledge service system of Guangdong Hospital of Chinese Medicine for frequency statistics and association rules analysis. Heat map-hierarchical clustering analysis was used to explore the correlation between clinical characteristics and formulas. Result(s): A total of 175 patients with COVID-19 were included in this study. The 70 patients in Xingtai, dominated by young and middle-aged males, had clinical symptoms of fever, abnormal sweating, and fatigue. The main pathogenesis is stagnant cold-dampness in the exterior and impaired yin by depressed heat, with manifest cold, dampness, and deficiency syndromes. The therapeutic methods highlight relieving exterior syndrome and resolving dampness, accompanied by draining depressed heat. The core Chinese medicines used are Poria, Armeniacae Semen Amarum, Gypsum Fibrosum, Citri Reticulatae Pericarpium, and Pogostemonis Herba. By contrast, the 105 patients in Ruili, dominated by young females, had atypical clinical symptoms, and most of them were asymptomatic patients or mild cases. The main pathogenesis is dampness obstructing the lung and the stomach, with obvious dampness and heat syndromes. The therapeutic methods are mainly invigorating the spleen, resolving dampness, and dispersing Qi with light drugs. The core Chinese medicines used are Poria, Atractylodis Macrocephalae Rhizoma, Glycyrrhizae Radix et Rhizoma, Coicis Semen, Platycodonis Radix, Lonicerae Japonicae Flos, and Pogostemonis Herba. Conclusion(s): The differences in clinical characteristics, TCM syndromes, and medication of COVID-19 patients from the two places may result from different regions, population characteristics, and the time point of the COVID-19 outbreak. The "treatment of disease in accordance with three conditions" theory can help to understand the internal correlation and guide the treatments.Copyright © 2022, China Academy of Chinese Medical Sciences Institute of Chinese Materia Medica. All rights reserved.
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Increasing amounts of surfactants are used and emitted into the environment due to the COVID-19 pandemic, posing potential threats to ecological health. Algal-bacterial aerobic granular sludge (A-BAGS), with the advantages of compact structure, high-efficient nutrient uptake, and high tolerance to harsh conditions, was attempted in this study to treat surfactant-containing wastewater at relatively high concentrations. The treatment performance was also compared to bacterial AGS (BAGS). Results showed that A-BAGS is preferable for treating wastewater containing a high SDS concentration (30 mg/L), achieving nutrient removal efficiency of 86.3 % for organic carbon, 60.5 % for total nitrogen, and 58.7 % for total phosphorus within a short duration, compared to 70.1 %, 52.8 % and 42.3 % in BAGS reactor. Besides, the removal rate of ammonia nitrogen by A-BAGS was much faster than that of BAGS. The above results confirmed that A-BAGS is a promising technology for treating surfactant-containing wastewater with high nutrient removal efficiency being maintained.Copyright © 2023 Elsevier Ltd
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Objective To explore the effects of perceived risk of COVID-19 of college students on their anxiety and depression, as well as the roles of attention to negative information and perceived social support, so as to provide theoretical basis for colleges and universities to formulate corresponding intervention measures. Methods By the convenience sampling method, totally 1 404 college students from Shaanxi and Henan provinces were investigated online by using General Information Questionnaire, Perceived Risk of COVID-19 Pandemic Scale, Attention to Negative Information Scale, Patient Health Questionnaire, Generalized Anxiety Disorder and Perceived Social Support Scale. SPSS 20. 0 was used for data analysis, Pearson correlation method was used to explore the correlation between variables. The mediating effect of attention to negative information and the moderating effect of perceived social support were analyzed by PROCESS. Results The scores of anxiety and depression of the 1 404 college students included in the study were 4.03 +/- 4.48 and 6.21 +/- 5.41, respectively. The detection rate of anxiety symptom was 29.9%, and that of depression symptom was 44.4%. The risk perception of COVID-19 epidemic of the college students was positively correlated with attention to negative information (r = 0.373, P<0.001), anxiety (r = 0.227, P<0.001), and depression (r = 0.226, P<0.001). Anxiety (r = 0.553, P<0.001) and depression 0 = 0.497, P<0.001) were positively correlated with attention to negative information, while perceived social support was negatively correlated with the risk perception of the COVID-19 (r = - 0.154, P<0.001), attention to negative information (r= - 0.259, P<0.001), anxiety (r = - 0.321, P<0.001) and depression (r=- 0.278, P<0.001). The risk perception of COVID-19 affected the anxiety and depression of the students mainly through the mediating effect of attention to negative information. The total effect of risk perception of COVID-19 and anxiety was 0. 227, and the mediating effect accounted for 80. 18% of the total effect. The total effect of risk perception of COVID-19 and depression was 0. 228, and the mediating effect accounted for 90. 35% of the total effect. Perceived social support played a moderating role in the last half of this mediating model. Conclusion Risk perception of COVID-19 indirectly affects the occurrence of anxiety and depression in college students through attention to negative information, and perceived social support plays a moderating role in this mediating model. The findings suggest that when a risk event occurs, colleges and universities should pay attention to guiding students to adjust their attentional bias to external information, and give students enough care and support to improve their mental health.Copyright © 2023 Xi'an Medical University. All rights reserved.
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The IEEE Power Electronics Society (PELS) Atlanta Chapter recently partnered with the NCAB Group to deliver a workshop on printed circuit board (PCB) design and manufacturing on 4 October 2022. The event was held at Georgia Institute of Technology (Georgia Tech) and was significant for the PELS Atlanta Chapter because it was its first in-person event since the Covid-19 pandemic and one of the IEEE Day events.
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Background: The outbreak of coronavirus disease 2019 (COVID-19) has created significant challenges in the management of oncology patients, including patients with colorectal cancer (CRC). We suspect that the COVID-19 pandemic had a major impact on the number of CRC inpatients and outpatients, which might leave many CRC patients unable to get timely medical treatment. At the time, the most important task was to satisfy the imperious demand for rapid optimization of processes and the development of efficient and effective triage and treatment strategies, as well as emergency distant clinical reasoning. Methods: The number of outpatients and inpatients, as well as surgeries performed in Shanghai East Hospital from December 2019 to February 2020 were collected. Using December 2019 data as the baseline status before the pandemic, the changes during this period were analyzed which can reflect the impact of COVID-19 on the treatment of CRC patients. In addition, a triage system and management strategy for patients with CRC during COVID-19 were designed and implemented. To evaluate their effectiveness, we assessed COVID-19 infection rates among CRC patients in relation to total patients and healthcare staff. Result: Compared with the pre-COVID-19 period (December 2019), a drastic decline in the number of outpatient visits (2,789 to 120) and inpatient hospitalizations (207 to 50) for all the CRC patients, as well as in non-emergency colorectal surgeries (133 to 23), was observed in February 2020 at our hospital. Conclusion: A multidisciplinary triage strategy aligned with regional guidance and digital, artificial intelligence (AI)-technology solutions can help increase the efficacy in patient management, allow efficient access to care and reduce the incidence of COVID-19 among CRC patients. © 2022 The HealthBook Company Ltd. All Rights Reserved.
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The 2022 Beijing Winter Olympics took place when American public opinion about China was already predominantly negative as media reports had a lot of highlights of human rights violations happening in China. Besides, earlier, the global image of China was undermined by the COVID-19 pandemic. In this study, we explored whether American public opinion about the Olympics and China can be influenced by images of the Olympics shared in the media. Findings from the 2 × 2 between-subject experimental design suggest that the opinions about the Olympics can be predicted by people's beliefs about China's role in the global pandemic. In addition to that, our findings suggest that pre-existing opinions and feelings held by most of the population can mitigate the effects of visual primes. © The Author(s) 2023.
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Objective: To study the clinical characteristics of diabetes mellitus with Coronavirus disease 2019 (COVID-19) and explore the possible mechanism of diabetes predisposition. Method(s): A single center, retrospective and observational study was used to collect 48 inpatients diagnosed with COVID-19 who were admitted to the first ward of the third department of infection, Raytheon hospital, Wuhan from February 23, 2020 to March 30, 2020. Demographic data, symptoms, laboratory tests, comorbidities, treatments and clinical outcomes have been collected. The patients were divided into non-diabetic group and diabetic group according to the combination of diabetes. The clinical data and laboratory test results of the two groups were observed, and the t test, non-parametric test and Chi square test were used for comparison. Result(s): All the 5 patients with COVID-19 diabetes mellitus had fever and respiratory symptoms, chest CT was consistent with typical COVID-19 imaging features, and novel coronavirus nucleic acid test results were positive. There were no statistically significant differences in age, gender composition, co-existing diseases, clinical symptoms, clinical typing, disease course and treatment plan between the diabetic group and the non-diabetic group (P>0.05).There was a statistically significant difference in fasting blood glucose between the non-diabetic group and the diabetic group (P<0.05).The difference of fasting blood glucose at discharge from the diabetes group compared with that at admission was also statistically significant (P<0.05).There was no statistically significant difference between the two groups in other laboratory examination indexes (P>0.05). Conclusion(s): COVID-19 patients with diabetes are mainly manifested by fever and respiratory symptoms.Chest CT shows typical COVID-19 imaging features.Copyright © 2020 by the Chinese Medical Association.