Microorganisms
November 2023
African swine fever, which is induced by the African swine fever virus (ASFV), poses a significant threat to the global pig industry due to its high lethality in domestic pigs and wild boars. Despite the severity of the disease, there is a lack of effective vaccines and drugs against the ASFV. The p72 protein, constituting 31 to 33% of the total virus particle mass, serves as the primary capsid protein of ASFV.
View Article and Find Full Text PDFACS Appl Mater Interfaces
July 2023
CsSnI powder is, for the first time, solution-prepared via the formula CsI + SnI + I → CsSnI. The product is highly pure and air/thermal stable. It is found that -dimethylformamide (DMF) and methanol induce severe CsSnI deterioration with the appearance of a CsI phase in film preparation from CsSnI powder, while solvents of γ-butyrolactone (GBL) and ethylene glycol methyl ether (EGME) (Film-EGME) give better results.
View Article and Find Full Text PDFSensors (Basel)
December 2022
As a single feature parameter cannot comprehensively evaluate the health status of a battery, a multi-source information fusion method based on the Gaussian mixture model and Bayesian inference distance is proposed for the health assessment of vehicle batteries. The missing and abnormal data from real-life vehicle operations are preprocessed to extract the sensitive characteristic parameters which determine the battery performance. The normal state Gaussian mixture model is established using the fault-free state data, whereas the Bayesian inference distance is constructed as an index to quantitatively evaluate the battery performance state.
View Article and Find Full Text PDFSemi-transparent TiO/graphene photoanodes are prepared at room temperature via an electrophoretic deposition method followed by compression and applied in dye-sensitized solar cells (DSSCs). Compression enhances the power conversion efficiency (PCE) of a DSSC, which constitutes up 18.4 times improvement compared to the uncompressed device.
View Article and Find Full Text PDFThis paper presents a new method to assess the performance degradation of roller bearings based on the fusion of multiple features, with the aim of improving the early degradation detection ability of the electrostatic monitoring system. At first, a set of feature parameters of the electrostatic monitoring system indicating the normal state of the bearings are extracted from the perspective of the time domain, frequency domain and complexity. Then, the parameter set is processed to reduce the dimensions and eliminate the redundancy using spectral regression.
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