Pattern changes of ecological product trade in countries along the Belt and Road.

The Belt and Road Initiative (BRI) was designed to promote economic and trade cooperation between countries along the Belt and Road (B&R), specifically by building an international trade network. Ecological resources are the basis for human survival. Countries along the B&R transform ecological resources into ecological products by production activities. These products can then be used for trade, thereby driving the countries' economic development. This study uses net primary productivity (NPP) as a unified measure of ecological products, and explores the pattern changes of ecological product trade in countries along the B&R, from 2013 to 2019 (from the BRI proposal to the outbreak of COVID-19). The purpose of the study is to reveal the impact of the BRI on the trade of ecological products. The results show that (1) the trade scale of ecological products in the B&R region has changed significantly. The total volume of traded ecological products increased from 2071.74 to 2631.00 TgC. This represented an increase of about 26.99%, or 7.41% higher than the global average. (2) The spatial distribution pattern of ecological product trade did not change significantly in countries along the B&R. However, the gravity centers of the total and net trade volume of ecological products moved 120.74 km to the northeast and 392.98 km to the southeast, respectively. (3) The trade structure of ecological products in the B&R region, six sub-regions, and most countries remained relatively stable. Only the proportion of the livestock products trade in Mongolia and the proportion of the forest products trade in Bhutan have increased significantly. This finding suggests that the strength and breadth of the construction of unimpeded trade in countries along the B&R still need to further strengthened, in order to accelerate the realization of the vision of the Green Silk Road.

Spatio-Temporal Patterns of the Land Carrying Capacity of Tibet Based on Grain Demand and Calorie Requirement

Tibet constitutes a major part of the Qinghai–Tibet Plateau (QTP) and is a typical ethnic minority (e.g., Tibetan) and ecologically fragile area in the world. Land resources are one of the most important foundations of food production, and Tibet’s increasingly multi-type food demands are putting new pressure on land resources. However, there is still debate on how many people can be supported with the food production in Tibet. Investigating the land carrying capacity (LCC) in Tibet is very important for maintaining food security and formulating sustainable land management and utilization. Based on an analysis of the unique characteristics of the local farming, pastoral production, and dietary consumption, the spatio-temporal patterns of theLCC in Tibet in 2000–2019 were quantitatively assessed against the grain demands and calorie requirements at three different standards of living (i.e., basic prosperity, comprehensive moderate prosperity, and affluence). The dietary consumption was characterized by the high consumption of grains and meat products, and the low consumption of fruits and vegetables. The LCC in Tibet has continued to increase. The LCC in approximately 60% of the counties increased, with the high-LCC counties concentrated mainly in the Yarlung Zangbo River—Nyangqu River—Lhasa River area, and municipal districts and pastoral counties generally experiencing a low LCC. The load on land resources (LoL) in Tibet exhibited the characteristic of overall balance with local overloads and increasing tensions. More than 50% of the counties experienced population overload, mainly in municipal districts and pastoral counties. Food surplus was mainly found in farming counties, while the food production in pastoral counties was generally unable to meet the calorie demand. Considering the important role of land use in maintaining regional food security and ecological security, the conversion of grassland to cultivated land, the occupation of cultivated land, and the phenomenon of cultivated land was used to non grain should be avoided. Trans-regional transport of food should be strengthened to meet the calorie needs in population overload areas in the future. Our study provides a perspective for evaluating the pressure of land resources. The result can provide a reference for realizing the balance of grain and calorie supply–demand and lay a foundation for formulating sustainable land use policies in the QPT.

Cold Chain Food and COVID-19 Transmission Risk: From the Perspective of Consumption and Trade

Since the outbreak of the coronavirus disease 2019 (COVID-19), political and academic circles have focused significant attention on stopping the chain of COVID-19 transmission. In particular outbreaks related to cold chain food (CCF) have been reported, and there remains a possibility that CCF can be a carrier. Based on CCF consumption and trade matrix data, here, the 'source';of COVID-19 transmission through CCF was analyzed using a complex network analysis method, informing the construction of a risk assessment model reflecting internal and external transmission dynamics. The model included the COVID-19 risk index, CCF consumption level, urbanization level, CCF trade quantity, and others. The risk level of COVID-19 transmission by CCF and the dominant risk types were analyzed at national and global scales as well as at the community level. The results were as follows. (1) The global CCF trade network is typically dominated by six core countries in six main communities, such as Indonesia, Argentina, Ukraine, Netherlands, and the USA. These locations are one of the highest sources of risk for COVID-19 transmission. (2) The risk of COVID-19 transmission by CCF in specific trade communities is higher than the global average, with the Netherlands–Germany community being at the highest level. There are eight European countries (i.e., Netherlands, Germany, Belgium, France, Spain, Britain, Italy, and Poland) and three American countries (namely the USA, Mexico, and Brazil) facing a very high level of COVID-19 transmission risk by CCF. (3) Of the countries, 62% are dominated by internal diffusion and 23% by external input risk. The countries with high comprehensive transmission risk mainly experience risks from external inputs. This study provides methods for tracing the source of virus transmission and provides a policy reference for preventing the chain of COVID-19 transmission by CCF and maintaining the security of the global food supply chain.

Risk of Global External Cereals Supply under the Background of the COVID-19 Pandemic: Based on the Perspective of Trade Network.

International food trade is an integral part of the food system, and the COVID-19 pandemic has exposed the fragility of external food supplies. Based on the perspective of cereals trade networks (CTN), the pandemic risk is combined with the trade intensity between countries, and an assessment model of cereals external supply risk is constructed that includes external dependence index (EDI), import concentration, and risk of COVID-19 from import countries index (RICI). The results show that: (1) the global main CTN have typical scale-free characteristics, and seven communities are detected under the influence of the core countries; (2) about 60%, 50%, and 70% of countries face risks of medium and above (high and very high) external dependence, concentration of imports, and COVID-19 in the country of origin, respectively. Under the influence of the pandemic, the risk of global external cereal supply index (RECSI) has increased by 65%, and the USA-CAN communities show the highest risk index; (3) the countries with a very high risk are mainly the Pacific island countries and the Latin American and African countries. In addition, Japan, Mexico, South Korea, and 80% of the net food-importing developing countries are at high or very high RECSI levels. Approximately 50% of countries belong to the compound risk type, and many export countries belong to the RICI risk type; (4) global external food supply is subjected to multiple potential threats such as trade interruption, "price crisis", and "payment dilemma". The geographical proximity of community members and the geographical proximity of the pandemic risk is superimposed, increasing the regional risk of external food supply; and (5) this study confirms that the food-exporting countries should avoid the adoption of food export restriction measures and can prevent potential external supply risks from the dimensions of maintaining global food liquidity and promoting diversification of import sources. We believe that our assessment model of cereals external supply risk comprises a useful method for investigations regarding the international CTN or global food crisis under the background of the pandemic.

A predictive model and scoring system combining clinical and CT characteristics for the diagnosis of COVID-19.

OBJECTIVES: To develop a predictive model and scoring system to enhance the diagnostic efficiency for coronavirus disease 2019 (COVID-19). METHODS: From January 19 to February 6, 2020, 88 confirmed COVID-19 patients presenting with pneumonia and 80 non-COVID-19 patients suffering from pneumonia of other origins were retrospectively enrolled. Clinical data and laboratory results were collected. CT features and scores were evaluated at the segmental level according to the lesions' position, attenuation, and form. Scores were calculated based on the size of the pneumonia lesion, which graded at the range of 1 to 4. Air bronchogram, tree-in-bud sign, crazy-paving pattern, subpleural curvilinear line, bronchiectasis, air space, pleural effusion, and mediastinal and/or hilar lymphadenopathy were also evaluated. RESULTS: Multivariate logistic regression analysis showed that history of exposure (ß = 3.095, odds ratio (OR) = 22.088), leukocyte count (ß = - 1.495, OR = 0.224), number of segments with peripheral lesions (ß = 1.604, OR = 1.604), and crazy-paving pattern (ß = 2.836, OR = 2.836) were used for establishing the predictive model to identify COVID-19-positive patients (p < 0.05). In this model, values of area under curve (AUC) in the training and testing groups were 0.910 and 0.914, respectively (p < 0.001). A predicted score for COVID-19 (PSC-19) was calculated based on the predictive model by the following formula: PSC-19 = 2 × history of exposure (0-1 point) - 1 × leukocyte count (0-2 points) + 1 × peripheral lesions (0-1 point) + 2 × crazy-paving pattern (0-1 point), with an optimal cutoff point of 1 (sensitivity, 88.5%; specificity, 91.7%). CONCLUSIONS: Our predictive model and PSC-19 can be applied for identification of COVID-19-positive cases, assisting physicians and radiologists until receiving the results of reverse transcription-polymerase chain reaction (RT-PCR) tests. KEY POINTS: • Prediction of RT-PCR positivity is crucial for fast diagnosis of patients suspected of having coronavirus disease 2019 (COVID-19). • Typical CT manifestations are advantageous for diagnosing COVID-19 and differentiation of COVID-19 from other types of pneumonia. • A predictive model and scoring system combining both clinical and CT features were herein developed to enable high diagnostic efficiency for COVID-19.

Infection Control for CT Equipment and Radiographers' Personal Protection During the Coronavirus Disease (COVID-19) Outbreak in China.

OBJECTIVE. Because CT plays an important role in diagnosis, isolation, treatment, and effective evaluation of coronavirus disease (COVID-19), infection prevention and control management of CT examination rooms is important. CONCLUSION. We describe modifications to the CT examination process, strict disinfection of examination rooms, arrangement of waiting areas, and efforts to increase radiographers' awareness of personal protection made at our institution during the COVID-19 outbreak. In addition, we discuss the potential of using artificial intelligence in imaging patients with contagious diseases.