Design and Implementation of Intelligent Truck Based on Azure Kinect

In recent years, due to the impact of COVID-19, the market prospect of non-contact handling has improved and the development potential is huge. This paper designs an intelligent truck based on Azure Kinect, which can save manpower and improve efficiency, and greatly reduce the infection risk of medical staff and community workers. The target object is visually recognized by Azure Kinect to obtain the center of mass of the target, and the GPS and Kalman filter are used to achieve accurate positioning. The 4-DOF robot arm is selected to grasp and transport the target object, so as to complete the non-contact handling work. In this paper, different shapes of objects are tested. The experiment shows that the system can accurately complete the positioning function, and the accuracy rate is 95.56%. The target object recognition is combined with the depth information to determine the distance, and the spatial coordinates of the object centroid are obtained in real time. The accuracy rate can reach 94.48%, and the target objects of different shapes can be recognized. When the target object is grasped by the robot arm, it can be grasped accurately according to the depth information, and the grasping rate reaches 92.67%. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

INFLUENCE OF AGE, PERIOD, AND BIRTH COHORT EFFECTS ON SECULAR TREND IN GOUT INCIDENCE IN THE UNITED KINGDOM

BackgroundThe risk of incident gout in the United Kingdom (UK) appears to have declined since 2013.[1] However, whether this is temporary or likely to continue is unclear.ObjectivesTo examine the influence of age, calendar year, and year of birth on recent gout incidence in the UK.MethodsUsing data from IQVIA Medical Research Database in the UK, we identified incident gout by READ codes from 1999 to 2019. We grouped age, calendar year, and year of birth into 3-year categories. We assessed the effect of age, calendar year, and birth cohort categories on the incidence rate of gout using the age-period-cohort model among all participants and in men and women separately.ResultsOver the 21 years, there were 164,588 incident gout cases. The incidence rate of gout increased with age until age 80, then leveled off (P for trend <0.001) (Figure 1A). The gout incidence increased from 1999 to 2013, then declined (Figure 1B). The incidence rate of gout was higher in the late birth cohorts than in the early birth cohorts from the Year 1999 to the Year 2013 (Figure 1C);however, such a trend was reversed after the Year 2013, with the incidence rate of gout being higher in the early birth cohorts than that in the late birth cohorts (Figure 1D). Similar patterns were observed in men and women.ConclusionUsing the age-period-cohort model, we found that the risk of gout in the UK increased from 1999 to 2013 and then declined afterward. These findings suggest that some environmental factors occurring after 2013 may play role. Such a downward trend of the risk of gout may continue if these environmental factors are still present.Reference[1]Abhishek A, Tata LJ, Mamas M, et al. Has the gout epidemic peaked in the UK? A nationwide cohort study using data from the Clinical Practice Research Datalink, from 1997 to across the COVID-19 pandemic in 2021. Ann Rheum Dis 2022 Jan 27.Figure 1.(A) Age rate ratios and the corresponding 95% confidence intervals of gout incidence. The relative risk of each age category compared with the reference age category (57-59) was adjusted for the calendar year and birth cohort. (B) Calendar year rate ratios and 95% confidence intervals of gout incidence. The relative risk of each calendar year compared with the reference calendar year (2008-2010) was adjusted for age and birth cohort. (C) Cohort rate ratios and the corresponding 95% confidence intervals of gout incidence. The relative risk of each birth cohort (1911-1982) compared with the reference birth cohort (1950-1952) was adjusted for age and calendar year. (D) Cohort rate ratios and the corresponding 95% confidence intervals of gout incidence. The relative risk of each birth cohort (1923-1988) compared with the reference birth cohort (1950-1952) was adjusted for age and calendar year.[Figure omitted. See PDF]AcknowledgementsThis work was supported by the National Natural Science Foundation of China (81930071, 82072502, U21A20352), Project Program of National Clinical Research Center for Geriatric Disorders (2021LNJJ06, 2022LNJJ07), the Natural Science Foundation of Hunan Province (2022JJ20100), and the Science and Technology Innovation Program of Hunan Province (2022RC3075, 2022RC1009).Disclosure of InterestsNone Declared.

Comparison of the Performances for CAPM and Fama-French models During COVID-19

Since the outbreak of COVID-19, it has caused a startling stun to both society and economy in numerous nations, where different industries suffered unequally. This paper reviews the various performance of the Capital Asset Pricing Model (CAPM), and the Fama-French three-factor model and the five-factor model in different regions and industries. To metric the performance, various statistics models and scaling are applied including Pearson correlation, linear regression, R2 scores, t-test, etc. Specifically, this paper demonstrates the different performances of the CAPM model on the US and Egyptian stock markets, whereas using generalized method of moments in a panel data analysis to evaluate the performance in the U.S. market and the paired sample t-test and Wilcoxon signed-rank to evaluate the performance in the Egyptian market. The Fama-French three-factor model and five-factor model are both based on the U.S. market and analyze the model's performance (measured by significant level) in the U.S. market in general and in individual sectors, respectively. Whereas, in terms of three-factors model, the OLS estimation and relapse expected excess return are used onto the variables and multiple linear regression method was used to study the significance of factors in three sub-industries. Regarding to five-factors model, a multivariate regression with covariates and OLS estimation are the method for evaluation. These results shed light for deeply understanding the model and recognizing the impact on the security market of the COVID-19. © 2023 SPIE.

Consensus of Chinese experts on the work and demonstration of online Balint groups working committee on doctor-patient relationship, Chinese psychiatrist association, Chinese medical doctor association.

Balint group helps health professionals to get emotional support and different perspectives of feedback, inspire reflection, and alleviate job burnout. During the outbreak of COVID-19, it was difficult for medical staff to carry out the traditional form of in person Balint group. Referring to the work of international pilot online Balint group, leaders of Balint group all over China have accumulated some experience and encountered new problems by using the internet to carry out discussion. In order to assist and standardize the work of online Balint group and enrich the ways of expanding Balint work, the Working Committee on Doctor-patient Relationship, Chinese Psychiatrist Association, Chinese Medical Doctor Association organized experts to have two rounds of discussion, and developed the consensus on: Principles and forms of online Balint group, the way of using web platforms for demonstration and learning, matters needing attention, the future development, and so on.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.

Basic needs of the first batch of medical staff in the fever clinic of Peking union medical college hospital during Coronavirus disease 2019 outbreak: A qualitative study.

Objective The objective of this study was to investigate the basic needs of medical staff during the coronavirus disease 2019 pandemic in a fever clinic, so as to provide a reference for the global epidemic medical teams. Methods A semi-structured qualitative interview outline was designed, including: (1) work level: Working hours, working intensity, and safety guarantee in a fever clinic;(2)life level: Diet, sleep, and physical comfort;(3)psychological level: Emotion, pressure, coping style, and interpersonal resources. The basic needs of the first batch of the fever clinic in Peking Union Medical College Hospital was studied by open telephone interviews. Results A total of 37 medical staff were interviewed, including 8 males (21.6%) and 29 females (78.4%). Among them, there were 16 doctors (43.2%), 19 nurses (51.4%), and 2 medical technicians (5.4%). In terms of work settings, the ideal continuous working time was 4-6 hours per shift. There should be pro re nata positions during extremely high workload, and sufficient personal protective equipment was the key to safety. In terms of living conditions, providing meals according to different shifts was important for dietary needs, and sleeping pills were temporarily needed for sleep. In terms of psychological reactions, nervousness and worrying were relatively common. Family and colleagues were important resources of support. Sport could help relieve physical and psychological stress, and psychological support from psychologists was helpful in reducing their negative emotions. Conclusions The basic needs of medical staff should be respected so as to keep the efficacy of their work. We suggest that medical staff can rest after each 4-6 h working shift. Personal protective equipment should be sufficient. Psychological support should be noted in all of them and provided when necessary.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.

Effective Responses to Public Emergencies at the Urban Community Level: A Perspective of COVID-19 Prevention and Control

Community is directly responsible for implementing the policy measures against public emergencies such as extreme weather, earthquake, flash flood and pandemic diseases. Summarizing the experience at the urban community level can help promote the global emergency management. This paper, from the perspective of COVID-19 prevention and control, selects three communities with different features to explore an effective response system for public emergency management at the urban community level. It demonstrates that based on a centralized leadership, the multi-level governance (MLG) network combined with information technology has mobilized their participation in combating COVID-19 and ensured the effective and timely response to the public emergencies, which blocked the spread of epidemic to the greatest extent, proving worthy of being promoted as one of the Chinese approaches and Chinese wisdom.

An Intelligent Classification Diagnosis Based on Blood Oxygen Saturation Signals for Medical Data Security Including COVID-19 in Industry 5.0

Obstructive sleep apnea-hypopnea syndrome (OSAHS) is gradually valued due to its high prevalence, high risk, and high mortality. Alternative to the polysomnography (PSG) diagnosis, the proposed method assesses the subject's degree of illness considering the supply chain and Industry 5.0 requirement efficiently and accurately. This article uses the blood oxygen saturation (SpO(2)) signal count of the number of apnea or hypoventilation events during the sleep of the subject, calculating the apnea-hypopnea index (AHI) and the subject's disease level. SpO(2) signals are used to extract 35-D features based on the time domain, including approximate entropy, central tendency measure, and Lempel-Ziv complexity to accelerate the diagnosis process in supply chains. The feature selection process is reduced from 35 to 7 dimensions that benefits to the implementation in the practical supply chains in Industry 5.0 by extracting the extracted features. This article applies Pearson correlation coefficient selection, based on minimum redundancy-maximum correlation algorithm selection, and a wrapper based on the backward search algorithm. The accuracy rate is 86.92%, and the specificity is 90.7% under the selected random forest classifier. A random forest classifier was used to calculate the AHI index, and a linear regression analysis was performed with the AHI index obtained from the PSG. The result reaches a 92% accuracy rate in assessing the prevalence of OSAHS, satisfying the industrial deployment.

Analysis of influencing factors of blood glucose levels in diabetic patients during epidemic of COVID-19.

Objective: To investigate the blood glucose control of diabetic patients during the Coronavirus disease 2019 (COVID-19) epidemic, and to explore the factors affecting blood glucose. Method(s): Three hundred and fifty patients with diabetes mellitus hospitalized in the Endocrinology Department of the Second Affiliated Hospital of Air Force Military Medical University from 2017 to 2019 were selected, and we send questionnaires (a self-made questionnaire containing 39 questions, Zung anxiety self-assessment scale, Zung depression self-assessment scale) to the patients through WeChat group. After the effective questionnaires were collected, the patients were divided into good blood glucose control group (fasting blood glucose <=7 mmol/L and 2 h postprandial blood glucose <=10 mmol/L) and poor blood glucose control group (fasting blood glucose>7 mmol/L and/or 2 hours postprandial blood glucose>10 mmol/L). Chi square test or Fisher exact probability method and t test were used to compare the differences between the two groups. In Multi-factor logistic regression, the backward regression method was performed. Result(s): A total of 310 questionnaires were collected, 4 of which did not meet the requirements were eliminated, and a total of 306 valid questionnaires were analyzed. There were 108 cases (35.3%) in the well-controlled group and 198 cases (64.7%) in the poorly controlled group. Compared with well-controlled group, there was a higher percentage of patients with aged >=45 years, diabetes course >=5 years, combined with chronic complications of diabetes, weekly exercise time during the epidemic period<150 min,weekly monitoring of blood glucose frequency <=1 to 2 times and sleep disorders during the epidemic, anxiety, and depression in poorly controlled group, and there were statistically significant differences (P<0.05).The above 8 factors with P<0.05 were included in the logistic regression model. Diabetes course >=5 years, weekly exercise time during the epidemic<150 min, sleep disturbance during the epidemic, weekly monitoring of blood glucose frequency <= 1 to 2 times, depression were risk factors for poor blood glucose control (P<0.05). Conclusion(s): During the epidemic period, the blood glucose level of diabetes patients was generally high. The factors that affected blood glucose control included a long course of diabetes, short exercise time, low monitoring frequency of blood glucose, sleep disorders, and depression.Copyright © 2020 by the Chinese Medical Association.

Plant-derived nanovesicles: further exploration of biomedical function and application potential

Extracellular vesicles (EVs) are phospholipid bilayer vesicles actively secreted by cells, that contain a variety of functional nucleic acids, proteins, and lipids, and are important mediums of intercellular communication. Based on their natural properties, EVs can not only retain the pharmacological effects of their source cells but also serve as natural delivery carriers. Among them, plant-derived nanovesicles (PNVs) are characterized as natural disease therapeutics with many advantages such as simplicity, safety, eco-friendliness, low cost, and low toxicity due to their abundant resources, large yield, and low risk of immunogenicity in vivo. This review systematically introduces the biogenesis, isolation methods, physical characterization, and components of PNVs, and describes their administration and cellular uptake as therapeutic agents. We highlight the therapeutic potential of PNVs as therapeutic agents and drug delivery carriers, including anti-inflammatory, anticancer, wound healing, regeneration, and antiaging properties as well as their potential use in the treatment of liver disease and COVID-19. Finally, the toxicity and immunogenicity, the current clinical application, and the possible challenges in the future development of PNVs were analyzed. We expect the functions of PNVs to be further explored to promote clinical translation, thereby facilitating the development of a new framework for the treatment of human diseases.Copyright © 2023 Chinese Pharmaceutical Association and Institute of Materia Medica, Chinese Academy of Medical Sciences

Study on pathogen spectrum of 1,046 hospitalized children with respiratory tract infections during COVID-19

Objectives: This study aimed to describe the pathogen spectrum of bacteria and viruses of RTIs in hospitalized children during the Coronavirus disease 2019 (COVID-19) epidemic in Shenzhen. Method(s): From October 2020 to October 2021, the results of pathogenic tests causing RTIs were retrospectively analyzed in hospitalized children in Shenzhen Luohu Hospital Group. Result(s): 829 sputum samples for bacterial isolation and 1,037 nasopharyngeal swabs for virus detection in total. The positive detection rate (PDR) of bacteria was 42.1%. Staphylococcus aureus (18.8%) was the predominant bacteria detected in positive cases, with Moraxella catarrhalis (10.9%), Streptococcus pneumoniae (9.5%) following. The PDR of the virus was 65.6%. The viruses ranking first to third were Human Rhinovirus (HRV), Respiratory syncytial virus (RSV), and Human Parainfluenza (HPIV), with rates of 28.0, 18.1, and 13.5%, respectively. Children under 3 years were the most susceptible population to RTIs. The pathogens of S. aureus, M. catarrhalis, S. pneumoniae, HRV, and HPIV were more prevalent in autumn. Meanwhile, RSV had a high rate of infection in summer and autumn. S. aureus and HRV had higher co-infection rates. Conclusion(s): Our findings demonstrate the pathogen spectrum of 1,046 hospitalized children with RTIs in Shenzhen, China, during the COVID-19 outbreak.Copyright © 2022 the author(s), published by De Gruyter, Berlin/Boston.

Changes in Ecotourism Flow in Hunan Province of China in the Context of COVID-19

This study analyzed the changes in ecotourism flow in Hunan Province before and after the COVID-19 epidemic by obtaining the ecotourism route data for 2019 and 2020 from online tourism platforms such as wasp nest, poor travel, Ctrip, tuniu and qunar, and determining geographical distribution characteristics, node characteristics and network characteristics with the help of software such as UCINET, Netdraw and ArcGIS. The results re-vealed major changes in spatial distribution, the roles of nodes, and the structure and composition of the flow net-work. (1) COVID-19 has changed the spatial distribution pattern of ecotourism flows in Hunan Province. Under the influence of the epidemic, the spatial geographical concentration trend in Hunan Province decreased from 30.42 in 2019 to 28.94 in 2020, the flow in the North weakened, and the hot spots shifted to the south. In order to promote the development of global tourism in Hunan Province, we should focus on how to correctly handle the differences in tourism resources and the imbalance in tourism development between the Xiangxi region and other tourism regions. (2) The COVID-19 epidemic triggered changes of the roles of some nodes in the ecotourism flow network in Hunan Province. The comprehensive efficiency value of the node decreased from 266 to 222, indicating that crisis events such as the epidemic have caused damage to the ecotourism flow in Hunan Province, and the surrounding low-density ecotourism sites with good natural scenery have become more favored by tourists after the COVID-19 epidemic. (3) The COVID-19 situation has affected the structure and composition of the ecotourism flow network in Hunan Province. The overall network density of ecotourism flow in Hunan Province increased from 0.18 to 0.14, the degree of separation between ecotourism destinations increased, and tourists' demand for health and safety has driven the development of ecotourism flow in Hunan Province towards multinode and multiregional characteristics. © 2023, Editorial office of Journal of Resources and Ecology. All rights reserved.

Analysis of influencing factors of blood glucose levels in diabetic patients during epidemic of COVID-19.

Objective: To investigate the blood glucose control of diabetic patients during the Coronavirus disease 2019 (COVID-19) epidemic, and to explore the factors affecting blood glucose. Method(s): Three hundred and fifty patients with diabetes mellitus hospitalized in the Endocrinology Department of the Second Affiliated Hospital of Air Force Military Medical University from 2017 to 2019 were selected, and we send questionnaires (a self-made questionnaire containing 39 questions, Zung anxiety self-assessment scale, Zung depression self-assessment scale) to the patients through WeChat group. After the effective questionnaires were collected, the patients were divided into good blood glucose control group (fasting blood glucose <=7 mmol/L and 2 h postprandial blood glucose <=10 mmol/L) and poor blood glucose control group (fasting blood glucose>7 mmol/L and/or 2 hours postprandial blood glucose>10 mmol/L). Chi square test or Fisher exact probability method and t test were used to compare the differences between the two groups. In Multi-factor logistic regression, the backward regression method was performed. Result(s): A total of 310 questionnaires were collected, 4 of which did not meet the requirements were eliminated, and a total of 306 valid questionnaires were analyzed. There were 108 cases (35.3%) in the well-controlled group and 198 cases (64.7%) in the poorly controlled group. Compared with well-controlled group, there was a higher percentage of patients with aged >=45 years, diabetes course >=5 years, combined with chronic complications of diabetes, weekly exercise time during the epidemic period<150 min,weekly monitoring of blood glucose frequency <=1 to 2 times and sleep disorders during the epidemic, anxiety, and depression in poorly controlled group, and there were statistically significant differences (P<0.05).The above 8 factors with P<0.05 were included in the logistic regression model. Diabetes course >=5 years, weekly exercise time during the epidemic<150 min, sleep disturbance during the epidemic, weekly monitoring of blood glucose frequency <= 1 to 2 times, depression were risk factors for poor blood glucose control (P<0.05). Conclusion(s): During the epidemic period, the blood glucose level of diabetes patients was generally high. The factors that affected blood glucose control included a long course of diabetes, short exercise time, low monitoring frequency of blood glucose, sleep disorders, and depression.Copyright © 2020 by the Chinese Medical Association.

Estimating the Reciprocal of a Binomial Proportion

The binomial proportion is a classic parameter with many applications and has also been extensively studied in the literature. By contrast, the reciprocal of the binomial proportion, or the inverse proportion, is often overlooked, even though it also plays an important role in various fields. To estimate the inverse proportion, the maximum likelihood method fails to yield a valid estimate when there is no successful event in the Bernoulli trials. To overcome this zero-event problem, several methods have been introduced in the previous literature. Yet to the best of our knowledge, there is little work on a theoretical comparison of the existing estimators. In this paper, we first review some commonly used estimators for the inverse proportion, study their asymptotic properties, and then develop a new estimator that aims to eliminate the estimation bias. We further conduct Monte Carlo simulations to compare the finite sample performance of the existing and new estimators, and also apply them to handle the zero-event problem in a meta-analysis of COVID-19 data for assessing the relative risks of physical distancing on the infection of coronavirus. © 2023 The Authors. International Statistical Review published by John Wiley & Sons Ltd on behalf of International Statistical Institute.

What are people asking about COVID-19? A question classification dataset

We present COVID-Q, a set of 1,690 questions about COVID-19 from 13 sources, which we annotate into 15 question categories and 207 question clusters. The most common questions in our dataset asked about transmission, prevention, and societal effects of COVID, and we found that many questions that appeared in multiple sources were not answered by any FAQ websites of reputable organizations such as the CDC and FDA. We post our dataset publicly at https://github.com/JerryWei03/COVID-Q. For classifying questions into 15 categories, a BERT baseline scored 58.1% accuracy when trained on 20 examples per category, and for a question clustering task, a BERT + triplet loss baseline achieved 49.5% accuracy. We hope COVID-Q can help either for direct use in developing applied systems or as a domain-specific resource for model evaluation. © ACL 2020.All right reserved.

Emergence and Persistent Dominance of SARS-CoV-2 Omicron BA.2.3.7 Variant, Taiwan.

Since April 2022, waves of SARS-CoV-2 Omicron variant cases have surfaced in Taiwan and spread throughout the island. Using high-throughput sequencing of the SARS-CoV-2 genome, we analyzed 2,405 PCR-positive swab samples from 2,339 persons and identified the Omicron BA.2.3.7 variant as a major lineage within recent community outbreaks in Taiwan.

Effects of occupant behavior and ventilation on exposure to respiratory droplets in the indoor environment

To quantify the risk of the transmission of respiratory infections in indoor environments, we systematically assessed exposure to talking- and breathing-generated respiratory droplets in a generic indoor environment using computational fluid dynamic (CFD) simulations. The flow field in the indoor environment was obtained with SST k-ω model and Lagrangian method was used to predict droplet trajectories, where droplet evaporation was considered. Droplets can be categorized into small droplets (initial size ≤30 μm or ≤10 μm as droplet nuclei), medium droplets (30–80 μm) and large droplets (>100 μm) according to the exposure characteristics. Droplets up to 100 μm, particular the small ones, can contribute to both short-range and long-range airborne routes. For the face-to-face talking scenario, the intake fraction and deposition fractions of droplets on the face and facial mucosa of the susceptible were up to 4.96%, 2.14%, and 0.12%, respectively, indicating inhalation is the dominant route. The exposure risk from a talking infector decreases monotonically with the interpersonal distance, while that of nasal-breathing generated droplets maintains a relatively stable level within 1.0 m. Keeping an angle of 15° or above with the expiratory flow is efficient to reduce intake fractions to <0.37% for small droplets. Adjusting the orientation from face-to-face to face-to-back can reduce exposure to small droplets by approximately 88.0% during talking and 66.2% during breathing. A higher ventilation rate can reduce the risk of exposure to small droplets but may increase the risk of transmission via medium droplets by enhancing their evaporation rate. This study would serve as a fundamental research for epidemiologist, healthcare workers and the public in the purpose of infection control. © 2023 Elsevier Ltd

Association between ambient sulfur dioxide pollution and asthma mortality: Evidence from a nationwide analysis in China

There is a lack of research on the effects of acute exposure to ambient sulfur dioxide (SO2) on mortality caused by asthma, especially nationwide research in China. To explore the acute effect of exposure to ambient SO2 on asthma mortality using nationwide dataset in China from 2015 to 2020 and further evaluate the associations in subgroups with different geographical and demographic characteristics. We used data from China's Disease Surveillance Points system with 29,553 asthma deaths in China during 2015–2020. The exposure variable was the daily mean concentrations of SO2 from the ChinaHighSO2 10 km × 10 km daily grid dataset. Bilinear interpolation was used to estimate each individual's exposure to air pollutants and meteorological variables. We used a time-stratified case crossover design at the individual level to analyze the exposure response relationship between short-term exposure to SO2 and asthma mortality. Stratified analyses were carried out by sex, age group, marital status, warm season and cold season, urbanicity and region. Significant associations between short-term exposure to ambient SO2 and increased asthma mortality were found in this nationwide study. The excess risk (ER) for each 10 μg/m3 increase in SO2 concentrations at lag07 was 7.78 % (95 % CI, 4.16–11.52 %). Season appeared to significantly modify the association. The associations were stronger in cold season (ER 9.78 %, 95 % CI:5.82 −13.89 %). The association remained consistent using different lag periods, adjusting for other pollutants, and in the analysis during pre-Corona Virus Disease 2019 (COVID-19) period. Our study indicates increased risk of asthma mortality with acute exposures to SO2 in Chinese population. The current study lends support for greater awareness of the harmful effect of SO2 in China and other countries with high SO2 pollution. © 2022 The Authors