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The coronavirus disease (COVID-19) which emerged in Wuhan, China, in December 2019, is widely controlled now in China. However, the global epidemic is still severe. To study and comment on Hubei's approaches for responding to the disease, the paper considered some factors such as suspected cases (part of them are influenza patients or common pneumonia patients, etc.), quarantine, patient classification (three types), clinically diagnosed cases, and lockdown of Wuhan and Hubei. After that, the paper established an S E L I H R model based on the surveillance data of Hubei published by the Hubei Health Commission from 10 January 2020 to 30 April 2020 and used the fminsearch optimization method to estimate the optimal parameters of the model. We obtained the basic reproduction number R 0 = 3.1571 from 10 to 22 January. R 0 was calculated as 2.0471 from 23 to 27 January. From 28 January to 30 April, R 0 = 1.5014. Through analysis, it is not hard to find that the patients without classification during the period of confirmed cases will result in the cumulative number of cases in Hubei to increase. In addition, regarding the lockdown measures implemented by Hubei during the epidemic, our simulations also show that if the lockdown time of either Hubei or Wuhan is advanced, it will effectively curb the spread of the epidemic. If the lockdown measures are not taken, the total cumulative number of cases will increase substantially. From the results of the study, it can be concluded that the lockdown, patient classification, and the large-scale case screening are essential to slow the spread of COVID-19, which can provide references for other countries or regions. [ABSTRACT FROM AUTHOR]

With the rapid development of economy and the increasing improvement of agricultural production level, people's demand for fruits is also increasing year by year. China is the largest fruit production and consumption country in the world. According to relevant statistics reported for China, by the end of 2019, the total amount of various fruits sold had reached about 270 million tons, with apples accounting for 48% of the global output and pears accounting for 69% of the national total output. However, China's fruit picking is still dominated by manual picking process, which takes a lot of manpower and time to complete, therefore resulting in low fruit picking efficiency. Some farmers are unable to complete fruit picking in a short time, resulting in a large number of fruits unable to be listed, resulting in huge losses. To solve this problem, this paper focuses on the visual recognition and path planning for intelligent fruit-picking robot. Using robot to complete fruit picking is the best way at present. This paper establishes a picking robot recognition and positioning system based on stereo vision, which is used to identify and locate the fruits planted in the orchard area. The coordinate error of the target point of the intelligent fruit-picking robot coordinate system is less than 10 mm, which has high accuracy. Then, the path of intelligent fruit-picking robot is planned based on visual feedback algorithm and biological stimulation neural network. Our empirical evaluations suggest that the proposed robot walks in the planting park in the shape of "zigzag" and realizes full-coverage path planning after 6 turns. The results show the efficiency of the intelligent method. [ABSTRACT FROM AUTHOR]

The new development concept is the theoretical guidance and important foundation for high-quality foreign trade development in the new era. This paper develops an evaluation index system to measure the high-quality development level of foreign trade based on the meaning of high-quality development of foreign trade under the new concept of development. The dynamic changing trend of high-quality development of China's provincial foreign trade from 2013 to 2019 and the ranking change of the development index are examined in this paper using a time series factor model. Finally, China's provinces are categorized based on the quality of their foreign trade development. The findings show that, from 2013 to 2019, China's high-quality foreign trade development has been on the rise; the level of high-quality foreign trade development has been raised to varying degrees in the eastern, central, and western regions of China, but each region plays a different role. Compared to 2013, the truly "high-quality" areas of China's provincial foreign trade development were always concentrated in the eastern region, which ranked high on the comprehensive evaluation index, while the "low-quality" areas were mainly concentrated in the central and western regions, which ranked low on the comprehensive evaluation index. [ABSTRACT FROM AUTHOR]

Since the infectious coronavirus disease (COVID-19) was first reported in Wuhan, it has become a public health problem in China and even around the world. This pandemic is having devastating effects on societies and economies around the world. The increase in the number of COVID-19 tests gives more information about the epidemic spread, which may lead to the possibility of surrounding it to prevent further infections. However, wearing a face mask that prevents the transmission of droplets in the air and maintaining an appropriate physical distance between people, and reducing close contact with each other can still be beneficial in combating this pandemic. Therefore, this research paper focuses on implementing a Face Mask and Social Distancing Detection model as an embedded vision system. The pretrained models such as the MobileNet, ResNet Classifier, and VGG are used in our context. People violating social distancing or not wearing masks were detected. After implementing and deploying the models, the selected one achieved a confidence score of 100%. This paper also provides a comparative study of different face detection and face mask classification models. The system performance is evaluated in terms of precision, recall, F1-score, support, sensitivity, specificity, and accuracy that demonstrate the practical applicability. The system performs with F1-score of 99%, sensitivity of 99%, specificity of 99%, and an accuracy of 100%. Hence, this solution tracks the people with or without masks in a real-time scenario and ensures social distancing by generating an alarm if there is a violation in the scene or in public places. This can be used with the existing embedded camera infrastructure to enable these analytics which can be applied to various verticals, as well as in an office building or at airport terminals/gates. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic and antipandemic policies have significantly impacted highway transportation. Many studies have been conducted to quantify these impacts. However, quantitative analysis of the impacts on province-wide traffic in developing countries, such as China, is still inadequate. This paper tried to fill this gap by proposing equations to quantify the traffic variations of overall province-wide traffic and to analyze the intercity bus traffic variation and intercity bus usage, applying the K-means cluster method to conduct the analysis of traffic reductions in regions with different levels of economic development, and using the hypothesis testing for traffic recovery analysis. It is found that passenger vehicle traffic and truck traffic dropped by 59.67% and 68.19% during the outbreak, respectively. The intercity bus traffic on highways declined by 59.8% to 98.6%, and the intercity bus usage dropped by 55.6% on average. For traffic reductions in different regions, the higher the GDP per capita was, the more the traffic was affected by the pandemic. In regions with lower GDP per capita, traffic variations were minor. It is also found that the passenger vehicle traffic went through four stages in 99 days: the Decline Stage, Rapid Recovery Stage, Slow Recovery Stage, and Normal Stage, while truck traffic only experienced the Decline Stage, Rapid Recovery Stage, and Normal Stage and took 51 days to recover to the Normal Stage. In the Rapid Recovery Stage, the recovery rates were 15.6% and 12.9% per week for passenger vehicle traffic and truck traffic, respectively, and the recovery rate was only 2.1% for passenger vehicle traffic in the Slow Recovery Stage. Despite the recovery of traffic volumes, neither passenger-kilometers nor tonne-kilometers of freight in 2020 reached the same level as in 2019. These findings help the understanding of the pandemic's impacts on highway traffic for researchers and can provide valuable references for decision-makers to develop antipandemic policies. [ABSTRACT FROM AUTHOR]

Narrow and closed spaces like high-speed train cabins are at great risk for airborne infectious disease transmission. With the threat of COVID-19 as well as other potential contagious diseases, it is necessary to protect passengers from infection. Except for the traditional preventions such as increasing ventilation or wearing masks, this paper proposes a novel measurement that optimizes passenger-to-car assignment schemes to reduce the infection risk for high-speed railway passengers. First, we estimated the probability of an infected person boarding the train at any station. Once infectors occur, the non-steady-state Wells–Riley equation is used to model the airborne transmission intercar cabin. The expected number of susceptible passengers infected on the train can be calculated, which is the so-called overall infection risk. The model to minimize overall infection risk, as a pure integer quadratic programming problem, is solved by LINGO software and tested on several scenarios compared with the classical sequential and discrete assignment strategies used in China. The results show that the proposed model can reduce 67.6% and 56.8% of the infection risk in the base case compared to the sequential and discrete assignment, respectively. In other scenarios, the reduction lies mostly between 10% and 90%. The optimized assignment scheme suggests that the cotravel itinerary among passengers from high-risk and low-risk areas should be reduced, as well as passengers with long- and short-distance trips. Sensitivity analysis shows that our model works better when the incidence is higher at downstream or low-flow stations. Increasing the number of cars and car service capacity can also improve the optimization effect. Moreover, the model is applicable to other epidemics since it is insensitive to the Wells–Riley equation parameters. The results can provide a guideline for railway operators during the post-COVID-19 and other epidemic periods. [ABSTRACT FROM AUTHOR]

Since the end of 2019, the outbreak of COVID-19 has severely affected port production and operation. There is little research on the systematic impact assessment. This study took Shanghai Port as an example and evaluated the impact under different scenarios through establishing a System Dynamics model. It is found that the epidemic mainly has a greater impact on passenger transport, but less on cargo transport. The ports with the function of transportation in highway, railway, and waterway were the key nodes in the international logistics network. More attention should be paid to the impact assessment of COVID-19 on ports' production and operation. It is necessary to strengthen the port's collection and distribution capabilities, improve port production efficiency, and further strengthen port modernization. This research method proposed in this paper can provide a reference for the impact assessment of similar events, and the empirical results can provide a reference for handling the epidemic shock for the port and shipping departments. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic caused by SARS-CoV-2 dominated the year 2020 and has an unprecedented impact on global air transport. This paper tries to make an overall review on the interaction of air transport and the COVID-19 pandemic. Although the confirmed cases were first reported in China, the origin of the pandemic remains uncertain. China was the first country to control the COVID-19 pandemic, and domestic air traffic recovers at a fast pace. Compared to 2019 level, world scheduled capacity, passengers carried, and revenues for 2020 were reduced by 50%, 60%, and $371 billion, respectively. Compared with domestic passenger traffic, international passenger traffic reduces more seats, passengers, and revenues. Because air transport contributes to economic growth, many countries or regions provide aviation bailout. The US provides most direct aid, while China mostly provides policy measures. In the post-COVID-19 period, IATA suggests that accepting vaccinated passengers is the best practice to reopen borders. Air cargo will play an important role in the distribution of COVID-19 vaccines. Meanwhile, air transport should be more digitalized, sustainable, and responsible in the future. [ABSTRACT FROM AUTHOR]

Since the end of 2019, the outbreak of COVID-19 has severely affected port production and operation. There is little research on the systematic impact assessment. This study took Shanghai Port as an example and evaluated the impact under different scenarios through establishing a System Dynamics model. It is found that the epidemic mainly has a greater impact on passenger transport, but less on cargo transport. The ports with the function of transportation in highway, railway, and waterway were the key nodes in the international logistics network. More attention should be paid to the impact assessment of COVID-19 on ports' production and operation. It is necessary to strengthen the port's collection and distribution capabilities, improve port production efficiency, and further strengthen port modernization. This research method proposed in this paper can provide a reference for the impact assessment of similar events, and the empirical results can provide a reference for handling the epidemic shock for the port and shipping departments. [ABSTRACT FROM AUTHOR]

SARS-CoV-2 is a specific type of Coronavirus that was firstly reported in China in December 2019 and is the causative agent of coronavirus disease 2019 (COVID-19). In March 2020, this disease spread to different parts of the world causing a global pandemic. Although this disease is still increasing exponentially day by day, early diagnosis of this disease is very important to reduce the death rate and to reduce the prevalence of this pandemic. Since there are sometimes human errors by physicians in the diagnosis of this disease, using computer-aided diagnostic systems can be helpful to get more accurate results. In this paper, chest X-ray images have been examined using a new pipeline machine vision-based system to provide more accurate results. In the proposed method, after preprocessing the input X-ray images, the region of interest has been segmented. Then, a combined gray-level cooccurrence matrix (GLCM) and Discrete Wavelet Transform (DWT) features have been extracted from the processed images. Finally, an improved version of Convolutional Neural Network (CNN) based on the Red Fox Optimization algorithm is employed for the classification of the images based on the features. The proposed method is validated by performing to three datasets and its results are compared with some state-of-the-art methods. The final results show that the suggested method has proper efficiency toward the others for the diagnosis of COVID-19. [ABSTRACT FROM AUTHOR]

By calculating the mutual information of stock indexes of 10 primary industry sectors in China, this paper analyzes the dependence relationship among Chinese stock sectors during the COVID-19 and the dynamic evolution of the relationship by using the sliding window method. According to the actual situation of the development of COVID-19 in China, the samples were divided into three stages, namely, calm period, pandemic period, and post-pandemic period. The results show that the dependence relationship among Chinese stock sectors is significantly enhanced in the pandemic period, but it decreases in the post-pandemic period and the dependence structure is similar to that in the calm period. The industrials sector is most closely connected with other sectors in the pandemic period. The information technology sector and telecommunication services sector maintain strong dependence in the three periods and share little contact with other sectors. In the pandemic period, the dependence between the consumer staples sector and other sectors is significantly enhanced, and consumer staples sector and health care sector maintain a strong dependence. From the results of the sliding window, the Chinese stock market is sensitive to the impact of COVID-19, but the duration of the impact on the dependence among the stock sectors is not long. [ABSTRACT FROM AUTHOR]

A novel coronavirus which has appeared from China, has been circulating hastily around the world. We summarized the publications including oral manifestation of coronavirus disease 2019 (COVID‐19) cases based on PubMed and Google Scholar data bases, and also present a case that highlights oral lesions 2 days prior to the first COVID‐19 general symptoms. Two authors independently reviewed the papers, 17 studies of more than 170 confirmed cases between ages of 9 and 90 were included. The most common oral manifestation was dry mouth followed by dysgeusia and pseudomembranous fungal structure. Change in tongue sensation and ulceration, muscle pain during mastication, swelling in oral cavity, and herpetic lesions were other common symptoms. Associated symptoms, latency time, treatment, and prognosis have also been meticulously reviewed. We hope that careful clinical intraoral examination on all COVID‐19 positive patients and equally on any patients who need dental care will pave the way for further studies. [ABSTRACT FROM AUTHOR]

COVID‐19 diseases have been a nationwide pandemic condition. However, cutaneous, skin histopathological manifestations of COVID‐19 infection are not well described. Our study aims are to present heterogeneous cutaneous, histopathological manifestations in COVID‐19 patients, to investigate the possible relationship between cutaneous manifestations and histopathological features in COVID‐19 infection. We performed a systemic review in PubMed database and Chinese medical journal search engines which were wangfang.data (http://www.wanfangdata.com.cn/), Science China (http://www.cnki.net/) until June 17th, 2020. Search terms "COVID‐19," "SARS‐Coronavirus‐2" and "Coronavirus" were used in combination with "cutaneous," "rash," "skin," "dermatology." Seventy‐five papers were included with confirmed COVID‐19 infection. The most frequent cutaneous manifestation of COVID‐19 present was erythema, nearly 38.4%. Trunk was the most affected location, presenting in 51.4% patients. Rash occurred before onset of other symptoms was in 5.3% patients. Seventy‐seven patients were received treatments. Rash was dismissed in 49% patients, improved in 21.2% patients ranged from 0 to 17 days. The histopathological examination present in 39 patients. Skin is one of target organs affected by COVID‐19 infection. Cutaneous manifestations should be paid more attention. It can help doctors diagnose COVID‐19 infection in prodromal stage, understand progression, and determine prognosis of COVID‐19 infection. [ABSTRACT FROM AUTHOR]