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The COVID-19 outbreak is a global pandemic declared by the World Health Organization, with rapidly increasing cases in most countries. A wide range of research is urgently needed for understanding the COVID-19 pandemic, such as transmissibility, geographic spreading, risk factors for infections, and economic impacts. Reliable data archive and sharing are essential to jump-start innovative research to combat COVID-19. This research is a collaborative and innovative effort in building such an archive, including the collection of various data resources relevant to COVID-19 research, such as daily cases, social media, population mobility, health facilities, climate, socioeconomic data, research articles, policy and regulation, and global news. Due to the heterogeneity between data sources, our effort also includes processing and integrating different datasets based on GIS (Geographic Information System) base maps to make them relatable and comparable. To keep the data files permanent, we published all open data to the Harvard Dataverse (https://dataverse.harvard.edu/dataverse/2019ncov), an online data management and sharing platform with a permanent Digital Object Identifier number for each dataset. Finally, preliminary studies are conducted based on the shared COVID-19 datasets and revealed different spatial transmission patterns among mainland China, Italy, and the United States. [ABSTRACT FROM AUTHOR]

A visible-light-promoted photoredox/nickel protocol for Synthesis of thiophosphates with trimethylsilyl thioether and P(O)H compounds is described. In this transformation, S–P(O) bond formation are particularly attractive since they provide a straightforward, nontoxic, and high efficiency protocol for thiophosphates formation under pleasant smell during the experimental process. This strategy shows a new approach to conduct and can be scaled-up, and various sulfur-containing organophosphorus are readily obtained in moderate to excellent yields with excellent chemoselectivity and good functional-group tolerance. To create your abstract, type over the instructions in the template box below.Fonts or abstract dimensions should not be changed or altered. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract: The dehydrogenation reaction of [Pd(H)(OH)]+ toward methane has been investigated theoretically. Both high- and low-spin states potential-energy surfaces for the reaction were built up by using density functional theory (DFT). As compared with the [PdH]+ system, there is having many features in common. Our calculations indicate that the ground-states species have low electron spin and low s population in the metal-center for the transition states. After extensive sampling of the potential-energy surfaces (PESs), the finding shows that the σ-complex assisted metathesis (σ-CAM) process favor energetically low-spin singlet state in a spin-conserving manner. [ABSTRACT FROM AUTHOR]

Frictional heat of the ball screw pairs is an important heat source for machine tools. Aiming at the shortcomings in current research, the frictional heating effect was studied in depth. The sliding and rolling frictional mechanisms were analyzed with the thermo-force coupling effect. The calculation method of sliding strokes based on relative motion principle of planetary transmission were proposed. A new frictional heating effect model was established and the nut temperature was calculated. The calculation value of the nut temperature was compared with its measurement value. The calculated residual was only − 0.64 ℃ ∼ 0.53 ℃. The traditional empirical model and the new model was compared in the same test, and the new model accuracy has been improved by 91.35%. [Display omitted] • The calculation method of sliding strokes based on the relative motion principle of planetary transmission were proposed, which reduced the complexity of motion analysis for ball screw pairs. • A new frictional heat calculation model was established, which can characterize the frictional heating effect of ball screw pairs. • The sliding and rolling frictional mechanism of the ball screw pairs was analyzed, and the thermo-force coupling effect due to thermal deformation was considered. [ABSTRACT FROM AUTHOR]

Abstract Because of the low detection probability and recognition efficiency of the single-band signal of an infrared point target, the multi-band composite detection probability is analyzed and a multi-band recognition method is proposed. By using the binary hypothesis method, we can conveniently deduce the multi-band theoretical detection threshold and obtain the composite detection probability and false alarm probability. The numerical simulation results show that multi-band composite detection ability is superior to that of single-band. For the difficult classification between background and target spectral signals with serious interference noise in reality, this paper proposes a highly effective spectral signal recognition method based on the optimized AdaBoost algorithm. By virtue of the high classification accuracy of the AdaBoost algorithm, with the Pruning classifier as a basic classifier to be learnt, the proposed method abandons any abnormal data that seriously deviate from the mean value center of the correction classification data, the end result of which reduces the number of iterations and enhances the classification effect of the AdaBoost algorithm. Compared with other algorithms from test results, the optimized AdaBoost algorithm has higher recognition accuracy and quicker computation, and it reduces the sensitivity to noise to prevent the phenomenon of over-fitting. [ABSTRACT FROM AUTHOR]

Multispectral detection signals are relatively stable and complementary to single spectral detection signals with deficiencies of severe scintillation and poor anti-interference. To take advantage of multispectral radiation characteristics in the application of infrared target detection, the concept of a multispectral radiation envelope is proposed. To build the multispectral radiation envelope model, the temperature distribution of an aerial infrared target is calculated first. By considering the coupling heat transfer process, the heat balance equation is built by using the node network, and the convective heat transfer laws as a function of target speed are uncovered. Then, the tail flame temperature distribution model is built and the temperature distributions at different horizontal distances are calculated. Second, to obtain the optimal detection angles, envelope models of reflected background multispectral radiation and target multispectral radiation are built. Finally, the envelope characteristics of the aerial target multispectral radiation are analyzed in different wavebands in detail. The results we obtained reflect Wien’s displacement law and prove the effectiveness and reasonableness of the envelope model, and also indicate that the major difference between multispectral wavebands is greatly influenced by the target speed. Moreover, optimal detection angles are obtained by numerical simulation, and these are very important for accurate and fast target detection, attack decision-making and developing multispectral detection platforms. [ABSTRACT FROM AUTHOR]

A timely understanding of the spatiotemporal pattern and development trend of COVID-19 is critical for timely prevention and control. However, the under-reporting of casesis widespread in fields associated with public health. It is also possible to draw biased inferences and formulate inappropriate prevention and control policies if the phenomenon of under-reporting is not taken into account. Therefore, in this paper, a novel framework was proposed to explore the impact of under-reporting on COVID-19 spatiotemporal distributions, and empirical analysis was carried out using infection data of healthcare workers in Wuhan and Hubei (excluding Wuhan). The results show that (1) the lognormal distribution was the most suitable to describe the evolution of epidemic with time; (2) the estimated peak infection time of the reported cases lagged the peak infection time of the healthcare worker cases, and the estimated infection time interval of the reported cases was smaller than that of the healthcare worker cases. (3) The impact of under-reporting cases on the early stages of the pandemic was greater than that on its later stages, and the impact on the early onset area was greater than that on the late onset area. (4) Although the number of reported cases was lower than the actual number of cases, a high spatial correlation existed between the cumulatively reported cases and healthcare worker cases. The proposed framework of this study is highly extensible, and relevant researchers can use data sources from other counties to carry out similar research. • A novel framework was proposed to explore the impact of under-reporting on COVID-19 spatiotemporal distributions. • An empirical analysis was carried out based proposed framework using infection data of healthcare workers in Wuhan and Hubei (excluding Wuhan). • An open-source dataset of HCW diagnoses is provided, which both ensures the reproducibility of the study and provides the data needed to support related research on data under-reporting. [ABSTRACT FROM AUTHOR]

Abstract: A novel Fe(II)/diaryl prolinol catalyzed asymmetric 1,3-dipolar cycloaddition of azomethine ylides with alkenes has been developed. In the presence of FeCl2 (10 mol %) and α,α-bis(3,5-bistrifluoromethylphenyl)prolinol L1 (10 mol %), [3+2] cycloaddition of azomethine ylides with electronic-deficient olefins underwent smoothly in CH3CN at room temperature to generate the desired endo-adducts in moderate to good yields and enantioselectivities. This is the first example of Fe(II)/N,O-ligand (L1) catalyzed 1,3-dipolar enantioselective cycloaddition reaction of azomethine ylides. [ABSTRACT FROM AUTHOR]