Spatiotemporal dynamic network for regional maritime vessel flow prediction amid COVID-19

The COVID-19 pandemic has stifled international trade and the global maritime industry. Its impact on the routing of the regional vessel traffic flow provides supportive data to port authorities, ship owners, shippers, and consignees. This study proposes a spatiotemporal dynamic graph neural network (STDGNN) model that includes the usual primary part of the vessel flow and an auxiliary part of newly confirmed COVID-19 cases near the port. The primary part consists of a time-embedding (TE) block, two dynamic graph neural network (DGNN) blocks, and a gated recurrent unit block, to capture the spatiotemporal dependence in the regional vessel traffic flow. The auxiliary part is made of multiple blocks to exploit the dynamic temporal relationships in hours, days, and weeks. Moreover, the performance of the STDGNN model is verified by utilising real vessel traffic flow data (i.e. inflow, outflow, and volume) and the new cases of COVID-19 near the port of New York, USA, provided by the automatic identification system and the Johns Hopkins University Centre for Systems Science and Engineering. The 2-h prediction result shows a 37.7%, 17.23%, and 11.4% improvement in the mean absolute error (MAE) over the gated recurrent unit (GRU), STGCN, and TGCN models, respectively. The delicate and adaptable prediction of vessel traffic flow could help the port relieve congestion, enhance efficiency, and further assist the recovery of regional maritime industries in the post-COVID era.

Case report: Myocarditis following COVID-19 protein subunit vaccination.

We report findings in a 34-year-old female patient who presented with fulminant myocarditis 8 days after receiving the first dose of the ZF2001 RBD-subunit vaccine against coronavirus disease 2019 (COVID-19). Autopsy showed severe interstitial myocarditis, including multiple patchy infiltrations of lymphocytes and monocytes in the myocardium of the left and right ventricular walls associated with myocyte degeneration and necrosis. This report highlights the details of clinical presentations and autopsy findings of myocarditis after ZF2001 (RBD-subunit vaccine) vaccination. The correlation between vaccination and death due to myocarditis is discussed.

Global view on virus infection in non-human primates and implications for public health and wildlife conservation.

Viruses can be transmitted from animals to humans (and vice versa) and across animal species. As such, host-virus interactions and transmission have attracted considerable attention. Non-human primates (NHPs), our closest evolutionary relatives, are susceptible to human viruses and certain pathogens are known to circulate between humans and NHPs. Here, we generated global statistics on VI-NHPs based on a literature search and public data mining. In total, 140 NHP species from 12 families are reported to be infected by 186 DNA and RNA virus species, 68.8% of which are also found in humans, indicating high potential for crossing species boundaries. The top 10 NHP species with high centrality in the NHP-virus network include two great apes (Pan troglodytes, Pongo pygmaeus) and eight Old World monkeys (Macaca mulatta, M. fascicularis, M. leonina, Papio cynocephalus, Cercopithecus ascanius, C. erythrotis, Chlorocebus aethiops, and Allochrocebus lhoesti). Given the wide distribution of Old World monkeys and their frequent contact with humans, there is a high risk of virus circulation between humans and such species. Thus, we suggest recurring epidemiological surveillance of NHPs, specifically Old World monkeys that are in frequent contact with humans, and other effective measures to prevent potential circulation and transmission of viruses. Avoidance of false positives and sampling bias should also be a focus in future work.

An extended state observer based U-model control of the COVID-19.

The coronavirus disease 2019 (COVID-19) is a new, rapidly spreading and evolving pandemic around the world. The COVID-19 has seriously affected people's health or even threaten people's life. In order to contain the spread of the pandemic and minimize its impact on economy, the tried-and-true control theory is utilized. Firstly, the control problem is clarified. Then, by combining advantages of the U-model control and the extended state observer (ESO), an extended state observer-based U-model control (ESOUC) is proposed to generate a population restriction policy. Closed-loop stability of the regulation system is also proved Two examples are considered, and numerical simulation results show that the ESOUC can suppress the COVID-19 faster than the linear active disturbance rejection control, which benefits controlling the infectious disease and the economic recovery. The ESOUC may provide a feasible non-pharmaceutical intervention in the control of the COVID-19.

Comparison of COVID-19 Pandemic Dynamics in Asian Countries with Statistical Modeling.

In the current scenario, the outbreak of a pandemic disease COVID-19 is of great interest. A broad statistical analysis of this event is still to come, but it is immediately needed to evaluate the disease dynamics in order to arrange the appropriate quarantine activities, to estimate the required number of places in hospitals, the level of individual protection, the rate of isolation of infected persons, and among others. In this article, we provide a convenient method of data comparison that can be helpful for both the governmental and private organizations. Up to date, facts and figures of the total the confirmed cases, daily confirmed cases, total deaths, and daily deaths that have been reported in the Asian countries are provided. Furthermore, a statistical model is suggested to provide a best description of the COVID-19 total death data in the Asian countries.