AIM:To construct and evaluate a new non-invasive fibrosis index for assessment of the stage of liver f ibrosis. METHODS:A new f ibrosis index (Fibro-Stiffness index) was developed in 165 of 285 patients with chronic h...AIM:To construct and evaluate a new non-invasive fibrosis index for assessment of the stage of liver f ibrosis. METHODS:A new f ibrosis index (Fibro-Stiffness index) was developed in 165 of 285 patients with chronic hepatitis C, and was validated in the other 120 patients where liver biopsy was performed. Its usefulness was compared with liver stiffness (LS) measured by FibroScan, the aminotransferase-to-platelet ratio index, the Forns index and the FibroIndex. RESULTS: The Fibro-Stiffness index consists of LS,platelet count and prothrombin time. The values of the Fibro-Stiffness index differed signif icantly between neighboring f ibrosis stages except F0-F1. The area under the receiver operating characteristics curves of the Fibro-Stiffness index for prediction of F≥2 (0.90), F≥ 3 (0.90) and F= 4(0.92) in the estimation group and those for F≥ 3 (0.93) and F =4 (0.97) in the validation group were the highest among the 5 methods examined. The accuracy of the Fibro-Stiffness index had highest values for F≥2, F≥3 and F=4 in both the estimation and validation groups. The diagnostic performance for F= 4 was improved by a combination of the Fibro-Stiffness index with serum hyaluronic acid level. CONCLUSION: The Fibro-Stiffness index was constructed and validated. It showed superior diagnostic performance to other indices for F ≥ 2,3 and 4.展开更多
近年来,以Wi-Fi为代表的无线局域网(Wireless Local Area Network,WLAN)技术不断发展和成熟,被广泛应用到各个领域。其中,将无线网络与传统控制系统融合起来,形成具备高移动性、可扩展性和灵活性等优势的无线网络控制系统(Wireless Netw...近年来,以Wi-Fi为代表的无线局域网(Wireless Local Area Network,WLAN)技术不断发展和成熟,被广泛应用到各个领域。其中,将无线网络与传统控制系统融合起来,形成具备高移动性、可扩展性和灵活性等优势的无线网络控制系统(Wireless Networked Control Systems,WNCS),成为控制界的研究趋势之一。针对基于Wi-Fi技术的无线网络控制系统进行了研究,利用TrueTime仿真工具箱以及MATLAB/Simulink仿真环境,构建了一个WNCS的仿真系统模型,设计了相应的PID控制器,并研究了网络传输速率、采样周期等网络性能指标对系统控制性能的影响。展开更多
To gain a more comprehensive understanding and evaluate foam aluminum's performance,researchers have introduced various characterization indicators.However,the current understanding of the significance of these in...To gain a more comprehensive understanding and evaluate foam aluminum's performance,researchers have introduced various characterization indicators.However,the current understanding of the significance of these indicators in analyzing foam aluminum's performance is limited.This study employs the Generalized Regression Neural Network(GRNN)method to establish a model that links foam aluminum's microstructure characterization data with its mechanical properties.Through the GRNN model,researchers extracted four of the most crucial features and their corresponding weight values from the 13 pore characteristics of foam aluminum.Subsequently,a new characterization formula,called“Wang equivalent porosity”(WEP),was developed by using residual weights assigned to the feature weights,and four parameter coefficients were obtained.This formula aims to represent the relationship between foam aluminum's microstructural features and its mechanical performance.Furthermore,the researchers conducted model verification using compression data from 11 sets of foam aluminum.The validation results showed that among these 11 foam aluminum datasets,the Gibson-Ashby formula yielded anomalous results in two cases,whereas WEP exhibited exceptional stability without any anomalies.In comparison to the Gibson-Ashby formula,WEP demonstrated an 18.18%improvement in evaluation accuracy.展开更多
文摘AIM:To construct and evaluate a new non-invasive fibrosis index for assessment of the stage of liver f ibrosis. METHODS:A new f ibrosis index (Fibro-Stiffness index) was developed in 165 of 285 patients with chronic hepatitis C, and was validated in the other 120 patients where liver biopsy was performed. Its usefulness was compared with liver stiffness (LS) measured by FibroScan, the aminotransferase-to-platelet ratio index, the Forns index and the FibroIndex. RESULTS: The Fibro-Stiffness index consists of LS,platelet count and prothrombin time. The values of the Fibro-Stiffness index differed signif icantly between neighboring f ibrosis stages except F0-F1. The area under the receiver operating characteristics curves of the Fibro-Stiffness index for prediction of F≥2 (0.90), F≥ 3 (0.90) and F= 4(0.92) in the estimation group and those for F≥ 3 (0.93) and F =4 (0.97) in the validation group were the highest among the 5 methods examined. The accuracy of the Fibro-Stiffness index had highest values for F≥2, F≥3 and F=4 in both the estimation and validation groups. The diagnostic performance for F= 4 was improved by a combination of the Fibro-Stiffness index with serum hyaluronic acid level. CONCLUSION: The Fibro-Stiffness index was constructed and validated. It showed superior diagnostic performance to other indices for F ≥ 2,3 and 4.
文摘近年来,以Wi-Fi为代表的无线局域网(Wireless Local Area Network,WLAN)技术不断发展和成熟,被广泛应用到各个领域。其中,将无线网络与传统控制系统融合起来,形成具备高移动性、可扩展性和灵活性等优势的无线网络控制系统(Wireless Networked Control Systems,WNCS),成为控制界的研究趋势之一。针对基于Wi-Fi技术的无线网络控制系统进行了研究,利用TrueTime仿真工具箱以及MATLAB/Simulink仿真环境,构建了一个WNCS的仿真系统模型,设计了相应的PID控制器,并研究了网络传输速率、采样周期等网络性能指标对系统控制性能的影响。
基金Sponsored by the Shanxi Provincial College Teaching Reform Innovation Funding Project(Grant No.201901d111270)the Natural Science Foundation of Shanxi Province(Grant No.201701d11127)。
文摘To gain a more comprehensive understanding and evaluate foam aluminum's performance,researchers have introduced various characterization indicators.However,the current understanding of the significance of these indicators in analyzing foam aluminum's performance is limited.This study employs the Generalized Regression Neural Network(GRNN)method to establish a model that links foam aluminum's microstructure characterization data with its mechanical properties.Through the GRNN model,researchers extracted four of the most crucial features and their corresponding weight values from the 13 pore characteristics of foam aluminum.Subsequently,a new characterization formula,called“Wang equivalent porosity”(WEP),was developed by using residual weights assigned to the feature weights,and four parameter coefficients were obtained.This formula aims to represent the relationship between foam aluminum's microstructural features and its mechanical performance.Furthermore,the researchers conducted model verification using compression data from 11 sets of foam aluminum.The validation results showed that among these 11 foam aluminum datasets,the Gibson-Ashby formula yielded anomalous results in two cases,whereas WEP exhibited exceptional stability without any anomalies.In comparison to the Gibson-Ashby formula,WEP demonstrated an 18.18%improvement in evaluation accuracy.
