Dynamical Behavior of Nonautonomous Stochastic Reaction-Diffusion Neural Network Models

This brief investigates nonautonomous stochastic reaction-diffusion neural-network models with S-type distributed delays. First, the existence and uniqueness of mild solution are studied under the Lipschitz condition without the linear growth condition. Due to the existence of a nonautonomous reaction-diffusion term and the infinite dimensional Wiener process, the criteria for the well-posedness of the models are established based on the evolution system theory. Then, the S-type distributed delay, which is an infinite delay, is handled by the truncation method, and sufficient conditions for the global exponential stability are obtained by constructing a simple Lyapunov-Krasovskii functional candidate. Finally, neural-network examples and an illustrative example are given to show the applications of the obtained results.</p

One-carbon metabolites, B vitamins and associations with systemic inflammation and angiogenesis biomarkers among colorectal cancer patients:results from the ColoCare Study

B-vitamins involved in one-carbon metabolism have been implicated in the development of inflammation- A nd angiogenesis-related chronic diseases, such as colorectal cancer. Yet, the role of one-carbon metabolism in inflammation and angiogenesis among colorectal cancer patients remains unclear.The objective of this study was to investigate associations of components of one-carbon metabolism with inflammation and angiogenesis biomarkers among newly diagnosed colorectal cancer patients (n=238) in the prospective ColoCare Study, Heidelberg.We cross-sectionally analyzed associations between 12 B-vitamins and one-carbon metabolites and 10 inflammation and angiogenesis biomarkers from pre-surgery serum samples using multivariable linear regression models. We further explored associations among novel biomarkers in these pathways with Spearman partial correlation analyses. We hypothesized that pyridoxal-5'-phosphate (PLP) is inversely associated with inflammatory biomarkers.We observed that PLP was inversely associated with CRP (r=-0.33, plinearlinear=0.003), IL-6 (r=-0.39, plinear linear=0.02) and TNFα (r=-0.12, plinear=0.045). Similar findings were observed for 5-methyl-tetrahydrofolate and CRP (r=-0.14), SAA (r=-0.14) and TNFα (r=-0.15) among colorectal cancer patients. Folate catabolite apABG was positively correlated with IL-6 (r= 0.27, plinearlinear<0.0001), indicating higher folate utilization during inflammation.Our data support the hypothesis of inverse associations between PLP and inflammatory biomarkers among colorectal cancer patients. A better understanding of the role and inter-relation of PLP and other one-carbon metabolites with inflammatory processes among colorectal carcinogenesis and prognosis could identify targets for future dietary guidance for colorectal cancer patients.</p

Metabolomics Analytics Workflow for Epidemiological Research: Perspectives from the Consortium of Metabolomics Studies (COMETS)

The application of metabolomics technology to epidemiological studies is emerging as a new approach to elucidate disease etiology and for biomarker discovery. However, analysis of metabolomics data is complex and there is an urgent need for the standardization of analysis workflow and reporting of study findings. To inform the development of such guidelines, we conducted a survey of 47 cohort representatives from the Consortium of Metabolomics Studies (COMETS) to gain insights into the current strategies and procedures used for analyzing metabolomics data in epidemiological studies worldwide. The results indicated a variety of applied analytical strategies, from biospecimen and data pre-processing and quality control to statistical analysis and reporting of study findings. These strategies included methods commonly used within the metabolomics community and applied in epidemiological research, as well as novel approaches to pre-processing pipelines and data analysis. To help with these discrepancies, we propose use of open-source initiatives such as the online web-based tool COMETS Analytics, which includes helpful tools to guide analytical workflow and the standardized reporting of findings from metabolomics analyses within epidemiological studies. Ultimately, this will improve the quality of statistical analyses, research findings, and study reproducibility

SiO2 / GaN MOS コウゾウ ノ シンライセイ ニ カンスル ケンキュウ

博第1699号甲第1699号博士(工学)奈良先端科学技術大学院大

Real Time Cardan Shaft State Estimation of High-Speed Train Based on Ensemble Empirical Mode Decomposition

Due to the special location and structure of transmission system on high-speed train named CRH5, dynamic unbalance state of the cardan shaft will pose a threat to the train servicing safety, so effective methods that test the cardan shaft operating information and estimate the performance state in real time are needed. In this study a useful estimation method based on ensemble empirical mode decomposition (EEMD) is presented. By using this method, time-frequency characteristic of cardan shaft can be extracted effectively by separating the gearbox vibration acceleration data. Preliminary analysis suggests that the pinions rotating vibration separated from gearbox vibration by EEMD can be used as important assessment basis to estimate cardan shaft state. With two sets gearbox vibration signals collected from the in-service train at different running speed, the comparative analysis verifies that the proposed method has high effectiveness for cardan-shaft state estimate. Of course, it needs further research to quantify the performance state of cardan shaft based on this method