2009 3rd International Conference on Bioinformatics and Biomedical Engineering最新文献_第3页

Feasibility Study on the Pyrolysis Production for Hydrogen-Riched Fuel Gas from the Wet Sewage Sludge 湿污泥热解生产富氢燃料气的可行性研究

2009 3rd International Conference on Bioinformatics and Biomedical Engineering Pub Date : 2009-06-11 DOI: 10.1109/ICBBE.2009.5162853

Sijiang Xiong, Bei-ping Zhang, Xiaoyuan Jia, B. Xiao, Maoyun He

{"title":"Feasibility Study on the Pyrolysis Production for Hydrogen-Riched Fuel Gas from the Wet Sewage Sludge","authors":"Sijiang Xiong, Bei-ping Zhang, Xiaoyuan Jia, B. Xiao, Maoyun He","doi":"10.1109/ICBBE.2009.5162853","DOIUrl":"https://doi.org/10.1109/ICBBE.2009.5162853","url":null,"abstract":"The feasibility of producing hydrogen-riched fuel gas from wet sewage sludge was assessed in this paper, which consist in carrying out the pyrolysis of dewatered residual activated sludge as it is produced in the wastewater treatment plant with a moisture content of above 70%, without subjecting it to any previous thermal drying process. In order to establish the most favorable conditions for the production of hydrogen-riched fuel gas, the effects of moisture content, heating rate and temperature were analyzed. It was found that the natural moisture of the sludge was converted into steam at high temperature, which can take part in the partial gasification of the sludge, leading to an increase in the gas production and the yield of hydrogen. In addition, pyrolyzing wet sludge at high temperature with high heating rates could maximize the gas yield productivity and raise its quality as a fuel and as a source of hydrogen or syngas as well. In this process, the drying, pyrolysis and gasification of wet sewage sludge were completed in a single thermal process, and resulting in a considerable amount of gases with potential value as fuels due to the relatively high calorific values they contain.","PeriodicalId":6430,"journal":{"name":"2009 3rd International Conference on Bioinformatics and Biomedical Engineering","volume":"37 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2009-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74051428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Blending Sulfonated Polyethersulfone to Improve the Blood Compatibility of Polyethersulfone Membrane 共混磺化聚醚砜提高聚醚砜膜的血液相容性

2009 3rd International Conference on Bioinformatics and Biomedical Engineering Pub Date : 2009-06-11 DOI: 10.1109/ICBBE.2009.5162459

Haitao Wang

引用次数: 1

HRV and DBP in Monitoring the Short-Term Effect of Wood-Based Materials on Human Physiologic System HRV和DBP监测木基材料对人体生理系统的短期影响

2009 3rd International Conference on Bioinformatics and Biomedical Engineering Pub Date : 2009-06-11 DOI: 10.1109/ICBBE.2009.5162909

Haipeng Yu, Yixing Liu, Jun Wu

引用次数: 0

A Full-Scale Study On Phosphorus Removal From Biological A/O Process Enhanced by Zeolite 沸石强化生物A/O工艺除磷的全面研究

2009 3rd International Conference on Bioinformatics and Biomedical Engineering Pub Date : 2009-06-11 DOI: 10.1109/ICBBE.2009.5162171

G. Cheng, Shan Xu, Ruifang Wang, Z. Wu, Fei-juan Zhang, Xiang-feng Huang

引用次数: 2

Temperature Dependent Predictive Models for Vapor Pressures of Oxygen-Containing Polycyclic Aromatic Hydrocarbons 含氧多环芳烃蒸气压的温度依赖预测模型

2009 3rd International Conference on Bioinformatics and Biomedical Engineering Pub Date : 2009-06-11 DOI: 10.1109/ICBBE.2009.5163562

Guanghui Ding, Mihua Shao, Jing Zhang

引用次数: 0

A Design Proposal of a Reconfigurable Filter for an Optical Blood Oxygen Analyzer 光学血氧分析仪可重构滤波器的设计方案

2009 3rd International Conference on Bioinformatics and Biomedical Engineering Pub Date : 2009-06-11 DOI: 10.1109/ICBBE.2009.5162167

N. Joglekar, R. Veljanovski, A. Zayegh, Jatin Mitra

引用次数: 1

Using Logistic Regression Method to Predict Protein Function from Protein-Protein Interaction Data 用逻辑回归方法预测蛋白质-蛋白质相互作用数据中的蛋白质功能

2009 3rd International Conference on Bioinformatics and Biomedical Engineering Pub Date : 2009-06-11 DOI: 10.1109/ICBBE.2009.5163737

Qingshan Ni, Zheng-Zhi Wang, Qingjuan Han, Gangguo Li, Xiaomin Wang, Guangyun Wang

引用次数: 7

Abiotic Degradation of Nitroaromatic Compounds by Steel Converter Slag with Fe(II) 铁(II)对转炉炉渣非生物降解硝基芳香族化合物的研究

2009 3rd International Conference on Bioinformatics and Biomedical Engineering Pub Date : 2009-06-11 DOI: 10.1109/ICBBE.2009.5162262

Jun Yu Li, Li Xie, Fubo Luan, J. Sheng, Qi Zhou

引用次数: 0

Comparison of Different Approaches to ICP Dominated Pulse Extraction ICP主导脉冲提取不同方法的比较

2009 3rd International Conference on Bioinformatics and Biomedical Engineering Pub Date : 2009-06-11 DOI: 10.1109/ICBBE.2009.5162539

Peng Xu, Shaozhi Wu, S. Asgari, M. Kasprowicz, M. Bergsneider, Xiao Hu

引用次数: 1

Enzyme Function Classification Using Protein Sequence Features and Random Forest 基于蛋白质序列特征和随机森林的酶功能分类

2009 3rd International Conference on Bioinformatics and Biomedical Engineering Pub Date : 2009-06-11 DOI: 10.1109/ICBBE.2009.5162790

Chetan Kumar, Gang Li, A. Choudhary

{"title":"Enzyme Function Classification Using Protein Sequence Features and Random Forest","authors":"Chetan Kumar, Gang Li, A. Choudhary","doi":"10.1109/ICBBE.2009.5162790","DOIUrl":"https://doi.org/10.1109/ICBBE.2009.5162790","url":null,"abstract":"Enzymes are proteins that catalyze bio-chemical reactions in different ways and play important roles in metabolic pathways. The exponential rise in sequences of new enzymes has necessitated developing methods that accurately predict their function. To address this problem, approaches that cluster enzymes based on their sequence and structural similarity have been applied, but are known to fail for dissimilar proteins that perform the same function. In this paper, we present a machine learning approach to accurately predict the main function class of enzymes based on a unique set of 73 sequence-derived features. Our features can be extracted using freely available online tools. We used different multi-class classifiers to categorize enzyme protein sequences into one of the NC-IUBMB defined six main function classes. Amongst the classifiers, Random Forest reported the best results with an overall accuracy of 88% and precision and recall in the range of 84% to 93% and 82% to 93% respectively. Our results compare favorably with existing methods, and in some cases report better performance. Random Forest has been proven to be a very efficient data mining algorithm. This paper is first in exploring their application to enzyme function prediction. The datasets can be accessed online at the location: http://cholera.ece.northwestern.edu/EnzyPredict.","PeriodicalId":6430,"journal":{"name":"2009 3rd International Conference on Bioinformatics and Biomedical Engineering","volume":"2015 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2009-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78716028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6