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The goal of this article is to answer two questions: Has world agricultural convergence occurred? If not, how can this goal be fulfilled? This article introduces a model averaging method to consider both a parametric and a semi-parametric SFA model to better estimate technical efficiency. Then, three types of convergence tests are employed to check if world agricultural catch-up occurs and to determine the degree of convergence across different groups of countries. The empirical results on a balanced panel of 126 countries from 1970-2014 show that world agricultural convergence has not occurred. This article then investigates the situations in different groups of countries and discusses how to use international trade, irrigation system, and structural transformation to improve agricultural efficiency and to diminish the efficiency gap among different countries in the future.

PurposeThis article investigates the mechanism of the direct and indirect effects of epidemics on agricultural production and projects the impact of COVID-19 on agricultural output in China.Design/methodology/approachThis article first adopts a dynamic panel model and spatial Durbin model to estimate the direct and indirect effects, followed by a growth accounting method to identify the channels by which epidemics affect agriculture; finally, it projects the overall impact of COVID-19 on agriculture.FindingsThe incidence rate of epidemics in a province has a negative impact on that province's own agricultural productivity, but the increase in the input factors (land, fertilizer and machinery) can make up for the loss and thus lead to insignificant direct effects. However, this “input-offset-productivity” mechanism fails to radiate to the surrounding provinces and therefore leads to significant indirect/spillover effects. It is projected that COVID-19 will lower China's agricultural growth rate by 0.4%–2.0% in 2020 under different scenarios.Research limitations/implicationsIt is crucial to establish a timely disclosure and sharing system of epidemic information across provinces, improve the support and resilience of agricultural production in the short run and accelerate the process of agricultural modernization in the long run.Originality/valueConsidering the infectivity of epidemics, this article evaluates the mechanism of the direct and indirect effects by introducing a spatial dynamic model into the growth accounting framework. Moreover, besides the impact on input portfolio and productivity, this article also investigates whether epidemics reshape agricultural production processes due to panic effects and control measures.

According to the National Internet Information Office's "Domestic Blockchain Information Service Filing", there had been 72 enterprises registered for providing blockchain-based financial services by the end of 2019, accounting for 17% of the total number, and 120 financial services had been filed. This data reflects the booming blockchain financial application, and the growing interest in blockchain finance. This paper uses qualitative analysis and scale method to analyze the blockchain financial derivatives cluster, based on the collection of 122 operating blockchain financial enterprises’ main businesses. The study finds that blockchain financial derivatives have advantages of mitigating information asymmetry and reducing transaction costs; compared with traditional finance, it also changes the form of transactions rather than the nature of finance (i.e. credit), and innovates related financial businesses focusing on credit and technology. The results of this paper provide an important reference for the business innovation transformation of traditional financial enterprises and investors' investment choices, and also suggests that the government should introduce relevant policies as soon as possible to regulate legal loopholes.

The outbreak of Novel Coronavirus Pneumonia (NCP) has significantly affected China and beyond. How to effectively control such epidemic has gradually become a global issue. This paper reviews the e...

In opportunistic networks such as social networks, the mobile nodes usually encounter others irregularly and frequently, so the data dissemination can be assisted by evaluating the nodal activities in the historical contacts with other nodes. Specially, in this paper the nodal activity is calculated according to the number of encountered nodes during a period. Generally, the higher activity will be obtained when the node has encountered more other nodes. Thus, we propose a Data Dissemination Algorithm based on Nodal Activities (DDANA), where the correlations between nodes and the destination is exploited for the data dissemination as well. Experimental results show that DDANA can improve the delivery ratio and shorten the delivery time.

The outbreak and wide spread of COVID-19 poses a new threat to global food security. This paper aims to address two important policy related issues, that is which agricultural subsector suffers more under zoonotic diseases and how do zoonotic diseases affect these subsectors. Using provincial panel data of 24 main farm commodities in China from 2002 to 2017, this paper identifies the impacts of zoonotic diseases and projects the potential disruption of COVID-19 to agricultural output in China under three scenarios. The main findings are as follows. First, zoonotic diseases have adverse impacts on almost all the farm commodities, while livestock on average suffers more than crops. Second, zoonotic diseases affect these subsectors mainly through the channel of adverse shocks on total factor productivity (TFP). Third, while a few subsectors can find a way to offset part of the TFP loss by applying more input, most subsectors suffer from both input reduction and TFP loss. Fourth, the spread of COVID-19 is projected to lower the growth rates of China's crop and livestock sector by 1.1%-2.3% and 1.3%-2.6%, with TFP loss by 1.1%-2.0% and 1.4%-2.7%, respectively, in 2020. This paper then discusses several policy implications for mitigating the negative impacts of COVID-19 on agricultural production in China and elsewhere.

In recent years, the cascade multi-level technology has become hot spot in the electric power electron area. The technology can solve the contradiction between the switching frequency and the switching capacity of the large-power switching devices. But along with the number of cascade unit increases, unbalance usage becomes a problem. This paper proposes balanced control method based on Chaos Theory. It can be concluded from the distribute procedure based on random function that the active probability of each DC power source and switching devices is same. And the results of simulation prove the control strategies accuracy.

Drilling process has a nature of surprise and uncertainty. It is urgent for us to decrease the drilling problems and to increase drilling speed. The scale of drilling data is becoming larger and larger. However there are plentiful and valuable knowledge hidden behind them. It is of great benefit to grasp the potential information. It will be beyond people's capacities when artificially analyzing and understanding these data stored in such a great database, so the techniques of knowledge discovery and data mining are arising at the historic moment. Knowledge discovery in drilling analysis, process monitoring and control is a new and important technology. Though still in its infant stage, it shows great application prospects. Its development, present application state and general process are briefly described in this paper. Then the authors analyze the approaches, the application and the theory of data mining and knowledge discovery for drilling analysis, process monitoring and control. Through analyses of characteristics of operational data, the authors also point out the challenges for data mining and knowledge discovery for process monitoring and control and contents to be studied. At last, the application of knowledge discovery in drilling optimization in Daqing Oilfield is analyzed.