Unexplained pneumonia (UP) caused by a novel coronavirus SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) emerged in China in late December 2019 and has infected more than 9000 cases by 31 January 2020. Shanghai reported the first imported case of COVID-19 (Coronavirus Disease 2019) in 20 January 2020. A combinative approach of real-time RT-PCR, CRISPR-based assay and metagenomic next-generation sequencing (mNGS) were used to diagnose this unexplained pneumonia patient. Real-time RT-PCR and CRISPR-based assay both reported positive. This sample belonged to Betacoronavirus and shared a more than 99% nucleotide (nt) identity with the Wuhan SARS-CoV-2 isolates. We further compared pros and cons of common molecular diagnostics in UP. In this study, we illustrated the importance of combining molecular diagnostics to rule out common pathogens and performed mNGS to obtain unbiased potential pathogen result for the diagnosis of UP. ARTICLE HISTORY

Public health interventions have been implemented to contain the outbreak of COVID-19 in New York City. However, the assessment of those interventions, e.g. social distancing, cloth face covering based on the real-world data from filed study is lacking. The SEIR compartmental model was used to evaluate the social distancing and cloth face covering effect on the daily culminative laboratory confirmed cases in NYC, and COVID-19 transmissibility. The latter was measured by Rt reproduction numbers in three phases which were based on two interventions in implemented in the timeline. The transmissibility decreased from phase 1 to phase 3. The Initial, R0 was 4.60 in Phase 1 without any intervention. After social distancing, the Rt value was reduced by 68%, while after the mask recommendation, it was further reduced by ~60%. Interventions resulted in significant reduction of confirmed case numbers, relative to predicted values based on SEIR model without intervention. Our findings highlight the effectiveness of social distancing and cloth face coverings in slowing down the spread of SARS-CoV-2 in NYC.

The photovoltaic power generation system needed to be work at the maximum power point (MPP) to get the maximum efficiency. As the MPP can be influenced by environment condition, such as temperature and irradiation, it is necessary to optimize and control the PV system operation process. In this paper, a rough Fuzzy-PID control strategy is proposed to adjusting the PV operation to make the system working efficiency. Rough Fuzzy-PID control strategy is best in dealing with time-varying and non-linear system, it is much suitable for solving the MPPT of photovoltaic system through switching pulse generation to DC/DC buck converter. These control systems are modeled and simulated in Matlab/Simulink environment.