Objective This study aimed to investigate the application of an artificial neural network (ANN) in optimizing the Osteoporosis Self-Assessment Tool for Asians (OSTA) score. Methods OSTA score was calculated for each female participant that underwent dual-energy X-ray absorptiometry examination in two hospitals (one in each of two Chinese cities, Harbin and Ningbo). An ANN model was built using age and weight as input and femoral neck T-score as output. Osteoporosis risk screening by joint application of ANN and OSTA score was evaluated by receiver operating characteristic curve analysis. Results Nearly 90% of women with dual-energy X-ray absorptiometry-determined femoral neck osteoporosis were ≥60 years old. The ANN with age and weight as input and OSTA score both identified osteoporosis, with respective accuracy rates of 78.8% and 78.3%. However, both methods failed to identify osteoporosis in women < 60 years old. Compared with OSTA score alone, combined use of the two tools increased the rate of osteoporosis recognition among women > 80 years old. Conclusions OSTA score-mediated osteoporosis risk screening should be restricted to women ≥60 years old. Joint application of ANN and OSTA improved osteoporosis risk screening among Chinese women > 80 years old.

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Geraniin is a polyphenolic compound first isolated from Geranium thunbergii. The major protease (M pro ), namely 3C-like protease (3CL pro ), of coronaviruses is considered an attractive drug target as it is essential for the processing and maturation of viral polyproteins. Thus, our primary goal is to explore the efficiency of geraniin on 3CL pro of SARS-CoV-2 using the computational biology strategy. In this work, we studied the anti-coronavirus effect of geraniin in vitro and its potential inhibitory mode against the 3CL pro of SARS-CoV-2. We found that geraniin inhibited HCoV-OC43 coronavirus-infected cells during the attachment and penetration phases.Molecular docking and dynamics simulations exhibited that geraniin had a strong binding affinity and high stable binding to 3CL pro of SARS-CoV-2. Geraniin exhibited a strong inhibitory activity on SARS-CoV-2 and may be a potential inhibitor of SARS-CoV-2 3CL pro .

Abstract. The accuracy of fault detection is helpful to improve the stability of power quality. With the development of new energy, the technology of flexible HVDC transmission has been gradually mature, but there are still some problems. In this paper, the Mallat algorithm is used to detect the DC line fault and three-phase grounding fault in the flexible HVDC system. The high frequency wavelet coefficient amplitude obtained by Mallat decomposition is used to distinguish the fault type. The simulation results show that after wavelet decomposition of fault voltage has the modulus maxima. We can judge the fault type by the value of the modulus maximum, its maximum value is the starting and ending time of the fault, and the fault detection accuracy error is within 1%.

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