Model-based state of charge (SOC) estimation method depends on the accuracy of the online identified battery model. However, when battery model parameters are identified by conventional recursive least squares (RLS), voltage and current noise will lead to the deviation of parameters and further affect the accuracy of SOC estimation. To analyze the difference influence of voltage and current noise, a simulation is carried out under the same noise variance of both voltage and current. Results indicate that voltage noise is the main cause of parameter deviation. Based on these results, a novel method, the auxiliary model recursive least square (AM-RLS) which enjoys low computational complexity is proposed to compensate the parameter deviation caused by voltage noise. The AM-RLS method is further combined with an extendedKalman filter (EKF) to estimate SOC in real time. Both simulation and experimental results show that AM-RLS can effectively attenuate the parameter deviation and SOC estimation error under noise interference. Compared with RLS, the maximum SOC errors of the proposed method are reduced by 2.6% and 5.86% respectively under two current profiles.

Background: Nowadays, medical grade 316L stainless steel (316L SS) is being widely used for intravascular stents, and the drug-eluting stent (DES) system is able to significantly reduce the occurrences of in-stent restenosis. But the drugs and the polymer coating used in DES potentially induce the forming of late stent thrombosis. In order to reduce the occurrence of ISR after stent implantation, the development of novel drugs for DESs is urgently needed. Methods: This study aimed to investigate the potential mechanisms of epigallocatechin-3-gallate (EGCG) on human umbilical vein endothelial cells (HUVEC) grown on 316L stainless steel (316L SS) using flow cytometry and Q-PCR methods. Results: Our results showed that EGCG (12.5, 25, 50, 100 μmol/L) significantly inhibited HUVEC proliferation. Flow cytometry analysis indicated that EGCG (25, 50, 100 μmol/L) induced apoptosis. Moreover, qRT-PCRrevealed that genes associated with cell apoptosis (caspase-3, 8, 9, Fas) and autophagy (Atg 5, Atg 7, Atg 12) were up-regulated after EGCG treatment. Conclusion: These findings indicate that EGCG possesses chemo preventive potential in stent coating which may serve as a novel new drug for stent implantation.

Brucellosis is a highly contagious zoonosis chronic infectious disease with a strong latent capability to endanger human health and economic development via direct or indirect ways. However, the existing methods for brucellosis diagnosis are time-consuming and expensive as they require a tedious experimental procedure and a sophisticated experimental device and performance. To overcome these defects, it is truly necessary to establish a real-time, on-site, and rapid detection method for human brucellosis. Here, a lateral flow immunoassay (LFIA) with a rapid, sensitive, and alternative diagnostic procedure for human brucellosis with a high degree of accuracy was developed based on blue silica nanoparticles (SiNPs), Staphylococcal protein A (SPA), and surface Lipopolysaccharide of Brucella spp. (LPS), which can be applied for rapid and feasible detection of human brucellosis. To our knowledge, this is the first report that uses blue SiNPs as a signal probe of LFIA for the rapid diagnosis of human brucellosis. The precursor of blue SiNPs@SPA such as colorless SiNPs and blue SiNPs was synthesized at first and then coupled with SPA onto the surface of blue SiNPs by covalent bond to prepare blue SiNPs@SPA as a capture signal to catch the antibody in the brucellosis-positive serum. When SPA was combined with the antibodies in the brucellosis-positive serum, it was captured by LPS on the test line, forming an antigen–antibody sandwich structure, resulting in the T line turning blue. Finally, the results showed that it is acceptable to use blue SiNPs as visible labels of LFIA, and standard brucellosis serum (containing Brucella spp. antibody at 1,000 IU/ml) could be detected at a dilution of 10−5 and the detection limit of this method was 0.01 IU/ml. Moreover, it also demonstrated good specificity and accuracy for the detection of real human serum samples. Above all, the blue SiNPs-based LFIA that we developed provides a rapid, highly accurate, and inexpensive on-site diagnosis of human brucellosis, and shows great promise in clinical diagnostics for other diseases.

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