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Research on Safety Monitoring and Warning System Based on Information Fusion for Coking Production
Nailu Zhang,Libo Li,Xin Liu,Yuzhe Zhang,Fuchao Li 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.8
Coking production process is very complex, and full of risk factors, toxic and harmful substance, it’s a typical high risk industry. In view of the prominent safety hazards and strong interference to safety monitoring in coking production, put forward a kind of safety monitoring and warning system based on information fusion for coking production. To achieve the target that safety condition was monitored accurately and hazardous situation warned reliably, safety information of the monitoring and warning areas was collected by sensor network which include combustible gas sensor, dust sensor, temperature sensor, pressure sensor, flowmeter and IP camera ,and the information fusion model of safety monitoring and warning was established, and then, through the BP neural network and the D-S evidence theory algorithm, various safety information was fused. Actual tests show that it has achieved the goal that monitoring accurately and warning reliably. It is of great significance to ensure the security of coking production.
Wang, Shuang,Zhang, Yuchen,Dai, Wenrui,Lauter, Kristin,Kim, Miran,Tang, Yuzhe,Xiong, Hongkai,Jiang, Xiaoqian Oxford University Press 2016 Bioinformatics Vol.32 No.2
<P>Motivation: Genome-wide association studies (GWAS) have been widely used in discovering the association between genotypes and phenotypes. Human genome data contain valuable but highly sensitive information. Unprotected disclosure of such information might put individual's privacy at risk. It is important to protect human genome data. Exact logistic regression is a bias-reduction method based on a penalized likelihood to discover rare variants that are associated with disease susceptibility. We propose the HEALER framework to facilitate secure rare variants analysis with a small sample size. Results: We target at the algorithm design aiming at reducing the computational and storage costs to learn a homomorphic exact logistic regression model (i.e. evaluate P-values of coefficients), where the circuit depth is proportional to the logarithmic scale of data size. We evaluate the algorithm performance using rare Kawasaki Disease datasets.</P>
Haomiao Ding,Yuzhe Zhang,Yue Zha,Sijia Zhou,Chaoqing Cao,Huajian Zhu,Feng Xu,Xiuqiang Zhang,Caisheng Wang 한국식품과학회 2022 Food Science and Biotechnology Vol.31 No.13
The cytoprotective and potential molecular mechanisms of Hylocereus polyrhizus protein (RFPP) were investigated on the hydrogen peroxide (H2O2)-triggered damage in normal human embryonic lung (MRC-5) cells. An MTT assay was conducted to assess the MRC-5 cell viability after exposure to H2O2 or RFPP. Cell cycle distribution and apoptosis were explored via flow cytometry. The contents of related proteins were assessed via western blot. MRC-5 cells exhibited markedly decreased cellular viability after treatment with H2O2; however, treatment with RFPP suppressed this decrease. Additionally, RFPP interference dampened H2O2-triggered intracellular apoptosis levels and increased H2O2-triggered intracellular S phase. In these processes, the contents of phosphorylated (p)-AKT along with p-mTOR proteins were downregulated in 120 µM H2O2-treated cells compared with vehicle-treated cells. Nevertheless, in MRC-5 cells inoculated with RFPP, the levels expression of these proteins were reversed. To conclude, RFPP protected MRC-5 cells from H2O2-triggered damage via activation of the PI3K/AKT/mTOR cascade.