Tracing the Origin of Genotype II African Swine Fever Virus in China by Genomic Epidemiology Analysis

The pandemic spread of African swine fever (ASF) has caused serious effects on the global pig industry. Virus genome sequencing and genomic epidemiology analysis play an important role in tracking the outbreaks of the disease and tracing the transmission of the virus. Here we obtained the full-length genome sequence of African swine fever virus (ASFV) in the first outbreak of ASF in China on August 3rd, 2018 and compared it with other published genotype II ASFV genomes including 9 genomes collected in China from September 2018 to October 2020. Phylogenetic analysis on genomic sequences revealed that genotype II ASFV has evolved into different genetic clusters with temporal and spatial correlation since being introduced into Europe and then Asia. There was a strong support for the monophyletic grouping of all the ASFV genome sequences from China and other Asian countries, which shared a common ancestor with those from the Central or Eastern Europe. An evolutionary rate of 1.312 × 10−5 nucleotide substitutions per site per year was estimated for genotype II ASFV genomes. Eight single nucleotide variations which located in MGF110-1L, MGF110-7L, MGF360-10L, MGF505-5R, MGF505-9R, K145R, NP419L, and I267L were identified as anchor mutations that defined genetic clusters of genotype II ASFV in Europe and Asia. This study expanded our knowledge of the molecular epidemiology of ASFV and provided valuable information for effective control of the disease.

The macro-economic and CO2 emissions impacts of COVID-19 and recovery policies in China.

The outbreak and ongoing evolution of the COVID-19 pandemic have dramatically impacted economic development and CO2 emissions. China is under simultaneous pressure to recover from the outbreak and meet its carbon reduction targets, and the government is endeavouring to stimulate economic recovery through fiscal and monetary policies. This paper uses a computable general equilibrium model to measure the impact on China's economic recovery and carbon emissions by incorporating the pandemic shock and related economic recovery policies of loan prime rate (LPR) and value-added tax (VAT) reduction. The study found that COVID-19 led to a simultaneous shock on China's supply and demand sides in which GDP dropped by 2.62% and carbon emissions fell by 2.53%, compared to the period prior to COVID-19. Although the LPR and VAT reduction effectively mitigated economic loss, the combined LPR and VAT reduction had a more substantial effect on boosting GDP than the single policies. The VAT cut expands production and was used to overcome supply-side shocks, while lowering LPR mitigates the damage of demand-side shocks. Compared to the VAT reduction policy, reduced LPR has smaller carbon emissions per unit of GDP output. Consequently, we recommend that the government concentrate on a combination of policies to navigate pandemic shocks, as the two economic stimulus policies are confirmed to complement one another in terms of strengths and shortcomings.

The macro-economic and CO2 emissions impacts of COVID-19 and recovery policies in China

The outbreak and ongoing evolution of the COVID-19 pandemic have dramatically impacted economic development and CO2 emissions. China is under simultaneous pressure to recover from the outbreak and meet its carbon reduction targets, and the government is endeavouring to stimulate economic recovery through fiscal and monetary policies. This paper uses a computable general equilibrium model to measure the impact on China’s economic recovery and carbon emissions by incorporating the pandemic shock and related economic recovery policies of loan prime rate (LPR) and value-added tax (VAT) reduction. The study found that COVID-19 led to a simultaneous shock on China’s supply and demand sides in which GDP dropped by 2.62% and carbon emissions fell by 2.53%, compared to the period prior to COVID-19. Although the LPR and VAT reduction effectively mitigated economic loss, the combined LPR and VAT reduction had a more substantial effect on boosting GDP than the single policies. The VAT cut expands production and was used to overcome supply-side shocks, while lowering LPR mitigates the damage of demand-side shocks. Compared to the VAT reduction policy, reduced LPR has smaller carbon emissions per unit of GDP output. Consequently, we recommend that the government concentrate on a combination of policies to navigate pandemic shocks, as the two economic stimulus policies are confirmed to complement one another in terms of strengths and shortcomings.

Dynamic Gesture Recognition Model Based on Millimeter-Wave Radar With ResNet-18 and LSTM.

In this article, a multi-layer convolutional neural network (ResNet-18) and Long Short-Term Memory Networks (LSTM) model is proposed for dynamic gesture recognition. The Soli dataset is based on the dynamic gesture signals collected by millimeter-wave radar. As a gesture sensor radar, Soli radar has high positional accuracy and can recognize small movements, to achieve the ultimate goal of Human-Computer Interaction (HCI). A set of velocity-range Doppler images transformed from the original signal is used as the input of the model. Especially, ResNet-18 is used to extract deeper spatial features and solve the problem of gradient extinction or gradient explosion. LSTM is used to extract temporal features and solve the problem of long-time dependence. The model was implemented on the Soli dataset for the dynamic gesture recognition experiment, where the accuracy of gesture recognition obtained 92.55%. Finally, compare the model with the traditional methods. The result shows that the model proposed in this paper achieves higher accuracy in dynamic gesture recognition. The validity of the model is verified by experiments.