|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Risk assessment on the epidemics of human infection with a novel avian influenza A (H7N9) virus in Jiangsu Province, China显示文摘A novel avian influenza A (H7N9) virus was discovered in February 2013 in China and has resulted in more than 100 comfirmed human infections including 26 fatal cases as of May 2, 2013. The situation raises many urgent questions and global public health concerns. In this study, epidemiologic characteristics of infected human cases in Jiangsu province were analyzed and risk assessment was undertaken based on the information available. Briefly, it is highly unlikely that a pandemic of human infection with avian influenza A (H7N9) virus will happen in Jiangsu Province in the near future. In the end, some measures are recommended to prevent the situation from becoming worse. | Wendong Liu Yefei Zhu Xian Qi Ke Xu Aihua Ge Hong Ji Jing Ai Changjun Bao Fenyang Tang Minghao Zhou | 2013 | The Journal of Biomedical Research2013，27，3： | 9 |
| 2 | Green access point selection for wireless local area networks enhanced by cognitive radio显示文摘 | Ge Wendong Chen Shanzhi Ji Hong | 2013 | Mobile Networks and Applications2013，18，4： | 1 |
| 3 | Toward carbon neutrality:Uncovering constraints on critical minerals in the Chinese power system显示文摘China has set up its ambitious carbon neutrality target,which mainly relies on significant energy-related carbon emissions reduction.As the largest important contributing sector,power sector must achieve energy transition,in which critical minerals will play an essential role.However,the potential supply and demand for these minerals are uncertain.This study aims to predict the cumulative demand for critical minerals in the power sector under different scenarios via dynamic material flow analysis(DMFA),including total demands,supplies and production capacities of different minerals.Then,these critical minerals are categorized into superior and scarce resources for further analysis so that more detailed results can be obtained.Results present that the total minerals supply will not meet the total minerals demand(74260 kt)in 2060.Serious resource shortages will occur for several key minerals,such as Cr,Cu,Mn,Ag,Te,Ga,and Co.In addition,the demand for renewable energy will be nearly fifty times higher than that of fossil fuels energy,implying more diversified demands for various minerals.Finally,several policy recommendations are proposed to help improve the overall resource efficiency,such as strategic reserves,material substitutions,and circular economy. | Wendong Wei Zewen Ge Yong Geng Mingkun Jiang Zhujun Chen Wei Wu | 2022 | Fundamental Research2022，2，3： | 1 |
| 4 | Optimal energy-efficient power control for cognitive radio based on static and dynamic features of primary users显示文摘 | Ge Wendong Ji Hong Si Pengbo | 2011 | High Technology Letters2011，17，4： | 0 |
| 5 | Effects of incident energy and angle on carbon cluster ions implantation on silicon substrate:a molecular dynamics study显示文摘Carbon cluster ion implantation is an important technique in fabricating functional devices at micro/nanoscale. In this work, a numerical model is constructed for implantation and implemented with a cuttingedge molecular dynamics method. A series of simulations with varying incident energies and incident angles is performed for incidence on silicon substrate and correlated effects are compared in detail. Meanwhile, the behavior of the cluster during implantation is also examined under elevated temperatures. By mapping the nanoscopic morphology with variable parameters, numerical formalism is proposed to explain the different impacts on phrase transition and surface pattern formation. Particularly, implantation efficiency(IE) is computed and further used to evaluate the performance of the overall process. The calculated results could be properly adopted as the theoretical basis for designing nano-structures and adjusting devices' properties. | Ye Wei Shengbo Sang Bing Zhou Xiao Deng Jing Chai Jianlong Ji Yang Ge Yuanliang Huo Wendong Zhang | 2017 | Journal of Semiconductors2017，38，9： | 0 |
| 6 | Predicting Risk of Mortality in Pediatric ICU Based on Ensemble Step-Wise Feature Selection显示文摘Background.Prediction of mortality risk in intensive care units(ICU)is an important task.Data-driven methods such as scoring systems,machine learning methods,and deep learning methods have been investigated for a long time.However,few datadriven methods are specially developed for pediatric ICU.In this paper,we aim to amend this gap—build a simple yet effective linear machine learning model from a number of hand-crafted features for mortality prediction in pediatric ICU.Methods.We use a recently released publicly available pediatric ICU dataset named pediatric intensive care(PIC)from Children’s Hospital of Zhejiang University School of Medicine in China.Unlike previous sophisticated machine learning methods,we want our method to keep simple that can be easily understood by clinical staffs.Thus,an ensemble step-wise feature ranking and selection method is proposed to select a small subset of effective features from the entire feature set.A logistic regression classifier is built upon selected features for mortality prediction.Results.The final predictive linear model with 11 features achieves a 0.7531 ROC-AUC score on the hold-out test set,which is comparable with a logistic regression classifier using all 397 features(0.7610 ROC-AUC score)and is higher than the existing well known pediatric mortality risk scorer PRISM III(0.6895 ROC-AUC score).Conclusions.Our method improves feature ranking and selection by utilizing an ensemble method while keeping a simple linear form of the predictive model and therefore achieves better generalizability and performance on mortality prediction in pediatric ICU. | Shenda Hong Xinlin Hou Jin Jing Wendong Ge Luxia Zhang | 2021 | Health Data Science2021，，1： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员