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Search Results: 1 - 10 of 15084 matches for " REN Zhengwu "
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Modifying the Traditional Analyzing Method of Cylindrical Workpieces’ Deep Drawing Process by Using a Novel Loop Material Theory Method  [PDF]
Rongxin Yang, Zhengwu Lin
Engineering (ENG) , 2017, DOI: 10.4236/eng.2017.94019
Abstract: In this paper, the traditional empirical coefficient method and a novel loop material analytical method presented by the authors have been compared and discussed by analyzing several practical cylindrical workpieces’ deep drawing projects. Also, some conclusions about how to modify the traditional analyzing method of cylindrical workpieces’ deep drawing process could be concluded and the necessity of this modification could be proved.
Information technology in pharmacovigilance: Benefits, challenges, and future directions from industry perspectives
Zhengwu Lu
Drug, Healthcare and Patient Safety , 2009, DOI: http://dx.doi.org/10.2147/DHPS.S7180
Abstract: formation technology in pharmacovigilance: Benefits, challenges, and future directions from industry perspectives Perspectives (8573) Total Article Views Authors: Zhengwu Lu Published Date October 2009 Volume 2009:1 Pages 35 - 45 DOI: http://dx.doi.org/10.2147/DHPS.S7180 Zhengwu Lu Clinical Research Department, Abbott Vascular, Santa Clara, CA, USA Abstract: Risk assessment during clinical product development needs to be conducted in a thorough and rigorous manner. However, it is impossible to identify all safety concerns during controlled clinical trials. Once a product is marketed, there is generally a large increase in the number of patients exposed, including those with comorbid conditions and those being treated with concomitant medications. Therefore, postmarketing safety data collection and clinical risk assessment based on observational data are critical for evaluating and characterizing a product’s risk profile and for making informed decisions on risk minimization. Information science promises to deliver effective e-clinical or e-health solutions to realize several core benefits: time savings, high quality, cost reductions, and increased efficiencies with safer and more efficacious medicines. The development and use of standard-based pharmacovigilance system with integration connection to electronic medical records, electronic health records, and clinical data management system holds promise as a tool for enabling early drug safety detections, data mining, results interpretation, assisting in safety decision making, and clinical collaborations among clinical partners or different functional groups. The availability of a publicly accessible global safety database updated on a frequent basis would further enhance detection and communication about safety issues. Due to recent high-profile drug safety problems, the pharmaceutical industry is faced with greater regulatory enforcement and increased accountability demands for the protection and welfare of patients. This changing climate requires biopharmaceutical companies to take a more proactive approach in dealing with drug safety and pharmacovigilance.
Information technology in pharmacovigilance: Benefits, challenges, and future directions from industry perspectives
Zhengwu Lu
Drug, Healthcare and Patient Safety , 2009,
Abstract: Zhengwu LuClinical Research Department, Abbott Vascular, Santa Clara, CA, USAAbstract: Risk assessment during clinical product development needs to be conducted in a thorough and rigorous manner. However, it is impossible to identify all safety concerns during controlled clinical trials. Once a product is marketed, there is generally a large increase in the number of patients exposed, including those with comorbid conditions and those being treated with concomitant medications. Therefore, postmarketing safety data collection and clinical risk assessment based on observational data are critical for evaluating and characterizing a product’s risk profile and for making informed decisions on risk minimization. Information science promises to deliver effective e-clinical or e-health solutions to realize several core benefits: time savings, high quality, cost reductions, and increased efficiencies with safer and more efficacious medicines. The development and use of standard-based pharmacovigilance system with integration connection to electronic medical records, electronic health records, and clinical data management system holds promise as a tool for enabling early drug safety detections, data mining, results interpretation, assisting in safety decision making, and clinical collaborations among clinical partners or different functional groups. The availability of a publicly accessible global safety database updated on a frequent basis would further enhance detection and communication about safety issues. Due to recent high-profile drug safety problems, the pharmaceutical industry is faced with greater regulatory enforcement and increased accountability demands for the protection and welfare of patients. This changing climate requires biopharmaceutical companies to take a more proactive approach in dealing with drug safety and pharmacovigilance.Keywords: information technology, pharmacovigilance, safety, standard, risk management, adverse event, adverse drug reaction
Clinical data management: Current status, challenges, and future directions from industry perspectives
Zhengwu Lu, Jing Su
Open Access Journal of Clinical Trials , 2010, DOI: http://dx.doi.org/10.2147/OAJCT.S8172
Abstract: ical data management: Current status, challenges, and future directions from industry perspectives Other (18549) Total Article Views Authors: Zhengwu Lu, Jing Su Published Date June 2010 Volume 2010:2 Pages 93 - 105 DOI: http://dx.doi.org/10.2147/OAJCT.S8172 Zhengwu Lu1, Jing Su2 1Smith Hanley Consulting, Houston, Texas; 2Department of Chemical Engineering, University of Massachusetts, Amherst, MA, USA Abstract: To maintain a competitive position, the biopharmaceutical industry has been facing the challenge of increasing productivity both internally and externally. As the product of the clinical development process, clinical data are recognized to be the key corporate asset and provide critical evidence of a medicine’s efficacy and safety and of its potential economic value to the market. It is also well recognized that using effective technology-enabled methods to manage clinical data can enhance the speed with which the drug is developed and commercialized, hence enhancing the competitive advantage. The effective use of data-capture tools may ensure that high-quality data are available for early review and rapid decision-making. A well-designed, protocol-driven, standardized, site workflow-oriented and documented database, populated via efficient data feed mechanisms, will ensure regulatory and commercial questions receive rapid responses. When information from a sponsor’s clinical database or data warehouse develops into corporate knowledge, the value of the medicine can be realized. Moreover, regulators, payer groups, patients, activist groups, patient advocacy groups, and employers are becoming more educated consumers of medicine, requiring monetary value and quality, and seeking out up-todate medical information supplied by biopharmaceutical companies. All these developments in the current biopharmaceutical arena demand that clinical data management (CDM) is at the forefront, leading change, influencing direction, and providing objective evidence. Sustaining an integrated database or data repository for initial product registration and subsequent postmarketing uses is a long-term process to maximize return on investment for organizations. CDM should be the owner of driving clinical data-cleaning process in consultation with other stakeholders, such as clinical operations, safety, quality assurance, and sites, and responsible for building a knowledge base to add potential value in assisting further study designs or clinical programs. CDM needs to draw on a broad range of skills such as technical, scientific, project management, information technology (IT), systems engineering, and interpersonal skills to tackle, drive, and provide valued service in managing data within the anticipated e-clinical age. Commitment to regulatory compliance is required in this regulated industry; however, a can-do attitude with strong willingness to change and to seek ways to improve CDM functions and processes proactively are essential to continued success and t
Clinical data management: Current status, challenges, and future directions from industry perspectives
Zhengwu Lu,Jing Su
Open Access Journal of Clinical Trials , 2010,
Abstract: Zhengwu Lu1, Jing Su21Smith Hanley Consulting, Houston, Texas; 2Department of Chemical Engineering, University of Massachusetts, Amherst, MA, USAAbstract: To maintain a competitive position, the biopharmaceutical industry has been facing the challenge of increasing productivity both internally and externally. As the product of the clinical development process, clinical data are recognized to be the key corporate asset and provide critical evidence of a medicine’s efficacy and safety and of its potential economic value to the market. It is also well recognized that using effective technology-enabled methods to manage clinical data can enhance the speed with which the drug is developed and commercialized, hence enhancing the competitive advantage. The effective use of data-capture tools may ensure that high-quality data are available for early review and rapid decision-making. A well-designed, protocol-driven, standardized, site workflow-oriented and documented database, populated via efficient data feed mechanisms, will ensure regulatory and commercial questions receive rapid responses. When information from a sponsor’s clinical database or data warehouse develops into corporate knowledge, the value of the medicine can be realized. Moreover, regulators, payer groups, patients, activist groups, patient advocacy groups, and employers are becoming more educated consumers of medicine, requiring monetary value and quality, and seeking out up-todate medical information supplied by biopharmaceutical companies. All these developments in the current biopharmaceutical arena demand that clinical data management (CDM) is at the forefront, leading change, influencing direction, and providing objective evidence. Sustaining an integrated database or data repository for initial product registration and subsequent postmarketing uses is a long-term process to maximize return on investment for organizations. CDM should be the owner of driving clinical data-cleaning process in consultation with other stakeholders, such as clinical operations, safety, quality assurance, and sites, and responsible for building a knowledge base to add potential value in assisting further study designs or clinical programs. CDM needs to draw on a broad range of skills such as technical, scientific, project management, information technology (IT), systems engineering, and interpersonal skills to tackle, drive, and provide valued service in managing data within the anticipated e-clinical age. Commitment to regulatory compliance is required in this regulated industry; however, a can-do attitude wi
A Review on Progress in QSPR Studies for Surfactants
Jiwei Hu,Xiaoyi Zhang,Zhengwu Wang
International Journal of Molecular Sciences , 2010, DOI: 10.3390/ijms11031020
Abstract: This paper presents a review on recent progress in quantitative structure-property relationship (QSPR) studies of surfactants and applications of various molecular descriptors. QSPR studies on critical micelle concentration (cmc) and surface tension (γ) of surfactants are introduced. Studies on charge distribution in ionic surfactants by quantum chemical calculations and its effects on the structures and properties of the colloids of surfactants are also reviewed. The trends of QSPR studies on cloud point (for nonionic surfactants), biodegradation potential and some other properties of surfactants are evaluated .
Calculating Node Importance Considering Cascading Failure in Traffic Networks
Zhengwu Wang,Aiwu Kuang,Hejie Wang
Research Journal of Applied Sciences, Engineering and Technology , 2013,
Abstract: The traffic network is a scale-free network. In selective attack, invalidation of few key nodes may lead to network failure so it is important to find these key nodes. In this study, the key nodes are determined by establishing calculating methods of node importance based on cascading failure behaviors. First, a cascading failure model of traffic network is posed. Its differences from current models are as follows: 1) The upper travel network and lower road network are influenced each other, 2) Capacity of nodes and links are given at first but not in direct proportion to initial flow that is related to initial capacity, 3) Travel time is used to describe status of links, 4) Capacity of links may change. The evaluation method of node importance of traffic network considering cascading failure is proposed then based on node deletion. It uses congestion status of cascading failure network to describe the node importance and algorithm procedures are designed to estimate importance of all nodes. At the end, the experiment analysis shows that network structure and traveler behaviors have in significant influence on node importance.
Bayesian Clustering of Shapes of Curves
Zhengwu Zhang,Debdeep Pati,Anuj Srivastava
Computer Science , 2015,
Abstract: Unsupervised clustering of curves according to their shapes is an important problem with broad scientific applications. The existing model-based clustering techniques either rely on simple probability models (e.g., Gaussian) that are not generally valid for shape analysis or assume the number of clusters. We develop an efficient Bayesian method to cluster curve data using an elastic shape metric that is based on joint registration and comparison of shapes of curves. The elastic-inner product matrix obtained from the data is modeled using a Wishart distribution whose parameters are assigned carefully chosen prior distributions to allow for automatic inference on the number of clusters. Posterior is sampled through an efficient Markov chain Monte Carlo procedure based on the Chinese restaurant process to infer (1) the posterior distribution on the number of clusters, and (2) clustering configuration of shapes. This method is demonstrated on a variety of synthetic data and real data examples on protein structure analysis, cell shape analysis in microscopy images, and clustering of shaped from MPEG7 database.
Based on the FHWA for the establishment of road traffic noise prediction model in Lanzhou city
基于FHWA的兰州市道路交通噪声预测模型的建立

SHI Yao,JU Tianzhen,WEN Fei,CHANG Chenghu,WANG Qinhu,CAO Chun,WU Yonghong,JIA Li,REN Zhengwu,YANG Hong,CHEN Yuan,
石垚
,巨天珍,温飞,常成虎,王勤花,曹春,吴永红,贾丽,任正武,杨泓,陈源

环境科学学报 , 2006,
Abstract: This paper combined the forecast model of the noise pollution in the road traffic by USA (FHWA)and the massive research achievement by domestic scholar's in this filed, totally chosen sample date on the established model from the 52 roads and lanes, 142 inspecting sites in Lanzhou city, and analyzed the relevance between the factors influencing the noise in the road traffic and the noise in the road traffic itself based on the principal of statistics, and finally set up the statistical forecasting model of noise pollution in conformity to the road characteristics of Lanzhou city. Then, the forecasting by 15 inspecting sites and the real test are found consistent with each other to a high degree , and this model can be used in the appraisals for noise pollution forecasting in road traffic of Lanzhou city.
Investigation of adsorption of surfactant at the air-water interface with quantum chemistry method
MeiLing Chen,ZhengWu Wang,HaiJun Wang,GeXin Zhang,FuMing Tao
Chinese Science Bulletin , 2007, DOI: 10.1007/s11434-007-0201-5
Abstract: Density functional theory (DFT) of quantum chemistry was used to optimize the configuration of the anionic surfactant complexes CH3(CH2)7OSO 3 (H2O)n (n=0–6) and calculate their molecular frequencies at the B3LYP/6-311+G* level. The interaction of CH3(CH2)7OSO 3 with 1 to 6 water molecules was investigated at the air-water interface with DFT. The results revealed that the hydration shell was formed in the form of H-bond between the hydrophilic group of CH3(CH2)7OSO 3 and 6 waters. The strength of H-bonds belongs to medium. Binding free energy revealed that the hydration shell was stable. The increase of the number of water molecules will cause increases of the total charge of hydrophilic group and S10-O9-C8 bond angle, but decreases of the alkyl chain length and the bond lengths of S10-O11, S10-O12 as well as S10-O13, respectively.
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