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Search Results: 1 - 10 of 23580 matches for " Yingjie Shi "
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Removal Hg0 from Flue Gas with Modified VTSS by KBr and KI  [PDF]
Yingjie Shi, Yakui Li
Journal of Materials Science and Chemical Engineering (MSCE) , 2015, DOI: 10.4236/msce.2015.312010
Abstract:

Vanadium titanium steel slag (VTSS) containing transition metal can promote the adsorption of Hg0. The method of KBr and KI impregnation was applied to modify VTSS and the properties of the adsorbents were tested. The Hg0 removal tests were carried out with a fixed bed under different conditions. The results showed that the Hg0 adsorption capacity increase with the increasing temperature. The efficiency was highest with KI(3)/VTSS at 20C and adsorption capacity was 163.4 ug/g after 3 h. The highest Hg0 removal efficiency were 90.6% for KI(3)/VTSS, 73.5% for KBr(10)/VTSS/ VTSS at 120C, respectively.

An ACOA-AFSA Fusion Routing Algorithm for Underwater Wireless Sensor Network
Huafeng Wu,Xinqiang Chen,Chaojian Shi,Yingjie Xiao,Ming Xu
International Journal of Distributed Sensor Networks , 2012, DOI: 10.1155/2012/920505
Abstract: Due to intrinsic properties of aqueous environments, routing protocols for underwater wireless sensor network (UWSN) have to cope with many challenges such as long propagation delay, bad robustness, and high energy consumption. Basic ant colony optimization algorithm (ACOA) is an intelligent heuristic algorithm which has good robustness, distributed computing and combines with other algorithms easily. But its disadvantage is that it may converge at local solution, not global solution. Artificial fish swarm algorithm (AFSA) is one kind of intelligent algorithm that can converge at global solution set quickly but has lower precision in finding global solution. Therefore we can make use of AFSA and ACOA based on idea of complementary advantages. So ACOA-AFSA fusion routing algorithm is proposed which possesses advantages of AFSA and ACOA. As fusion algorithm has aforementioned virtues, it can reduce existing routing protocols’ transmission delay, energy consumption and improve routing protocols’ robustness theoretically. Finally we verify the feasibility and effectiveness of fusion algorithm through a series of simulations.
Resonance characteristics of two-span continuous beam under moving high speed trains
Wang, Yingjie;Wei, QingChao;Shi, Jin;Long, Xuyou;
Latin American Journal of Solids and Structures , 2010, DOI: 10.1590/S1679-78252010000200005
Abstract: the resonance characteristics of a two-span continuous beam traversed by moving high speed trains at a constant velocity is investigated, in which the continuous beam has uniform span length. each span of the continuous beam is modeled as a bernoulli-euler beam and the moving trains are represented as a series of two degrees-of-freedom mass-springdamper systems at the axle locations. a method of modal analysis is proposed in this paper to investigate the vibration of two-span continuous beam. the effects of different influencing parameters, such as the velocities of moving trains, the damping ratios and the span lengths of the beam, on the dynamic response of the continuous beam are examined. the two-span continuous beam has two critical velocities causing two resonance responses, which is different from simple supported beam. the resonance condition of the two-span continuous beam is put forward which depends on the first and second natural frequency of the beam and the moving velocity.
CpGAVAS, an integrated web server for the annotation, visualization, analysis, and GenBank submission of completely sequenced chloroplast genome sequences
Liu Chang,Shi Linchun,Zhu Yingjie,Chen Haimei
BMC Genomics , 2012, DOI: 10.1186/1471-2164-13-715
Abstract: Background The complete sequences of chloroplast genomes provide wealthy information regarding the evolutionary history of species. With the advance of next-generation sequencing technology, the number of completely sequenced chloroplast genomes is expected to increase exponentially, powerful computational tools annotating the genome sequences are in urgent need. Results We have developed a web server CPGAVAS. The server accepts a complete chloroplast genome sequence as input. First, it predicts protein-coding and rRNA genes based on the identification and mapping of the most similar, full-length protein, cDNA and rRNA sequences by integrating results from Blastx, Blastn, protein2genome and est2genome programs. Second, tRNA genes and inverted repeats (IR) are identified using tRNAscan, ARAGORN and vmatch respectively. Third, it calculates the summary statistics for the annotated genome. Fourth, it generates a circular map ready for publication. Fifth, it can create a Sequin file for GenBank submission. Last, it allows the extractions of protein and mRNA sequences for given list of genes and species. The annotation results in GFF3 format can be edited using any compatible annotation editing tools. The edited annotations can then be uploaded to CPGAVAS for update and re-analyses repeatedly. Using known chloroplast genome sequences as test set, we show that CPGAVAS performs comparably to another application DOGMA, while having several superior functionalities. Conclusions CPGAVAS allows the semi-automatic and complete annotation of a chloroplast genome sequence, and the visualization, editing and analysis of the annotation results. It will become an indispensible tool for researchers studying chloroplast genomes. The software is freely accessible from http://www.herbalgenomics.org/cpgavas.
Molecular cloning of a novel bioH gene from an environmental metagenome encoding a carboxylesterase with exceptional tolerance to organic solvents
Shi Yuping,Pan Yingjie,Li Bailin,He Wei
BMC Biotechnology , 2013, DOI: 10.1186/1472-6750-13-13
Abstract: Background BioH is one of the key enzymes to produce the precursor pimeloyl-ACP to initiate biotin biosynthesis de novo in bacteria. To date, very few bioH genes have been characterized. In this study, we cloned and identified a novel bioH gene, bioHx, from an environmental metagenome by a functional metagenomic approach. The bioHx gene, encoding an enzyme that is capable of hydrolysis of p-nitrophenyl esters of fatty acids, was expressed in Escherichia coli BL21 using the pET expression system. The biochemical property of the purified BioHx protein was also investigated. Results Screening of an unamplified metagenomic library with a tributyrin-containing medium led to the isolation of a clone exhibiting lipolytic activity. This clone carried a 4,570-bp DNA fragment encoding for six genes, designated bioF, bioHx, fabG, bioC, orf5 and sdh, four of which were implicated in the de novo biotin biosynthesis. The bioHx gene encodes a protein of 259 aa with a calculated molecular mass of 28.60 kDa, displaying 24-39% amino acid sequence identity to a few characterized bacterial BioH enzymes. It contains a pentapeptide motif (Gly76-Trp77-Ser78-Met79-Gly80) and a catalytic triad (Ser78-His230-Asp202), both of which are characteristic for lipolytic enzymes. BioHx was expressed as a recombinant protein and characterized. The purified BioHx protein displayed carboxylesterase activity, and it was most active on p-nitrophenyl esters of fatty acids substrate with a short acyl chain (C4). Comparing BioHx with other known BioH proteins revealed interesting diversity in their sensitivity to ionic and nonionic detergents and organic solvents, and BioHx exhibited exceptional resistance to organic solvents, being the most tolerant one amongst all known BioH enzymes. This ascribed BioHx as a novel carboxylesterase with a strong potential in industrial applications. Conclusions This study constituted the first investigation of a novel bioHx gene in a biotin biosynthetic gene cluster cloned from an environmental metagenome. The bioHx gene was successfully cloned, expressed and characterized. The results demonstrated that BioHx is a novel carboxylesterase, displaying distinct biochemical properties with strong application potential in industry. Our results also provided the evidence for the effectiveness of functional metagenomic approach for identifying novel bioH genes from complex ecosystem.
A Randomized Phase I/II Trial to Compare Weekly Usage with Triple Weekly Usage of Paclitaxel in Concurrent Radiochemotherapy for Patients with Locally Advanced Non-small Cell Lung Cancer
Anhui SHI,Guangying ZHU,Rong YU,Yingjie WANG
Chinese Journal of Lung Cancer , 2011,
Abstract: Background and objective Although the guidelines of the National Comprehensive Cancer Network of USA recommend that the standard therapy for locally advanced non-small cell lung cancer (LANSCLC) is concurrent chemoradiotherapy. There is ongoing controversy about the treatment regimen which combines chemotherapy concurrently with radiotherapy. The aim of this study is to compare weekly usage with triple weekly usage of paclitaxel in concurrent radiochemotherapy for patients with LANSCLC, and to obtain the best paclitaxel regimen in the concurrent radiochemotherapy. Methods From April 2006 to April 2009, some LANSCLC patients in multicenter were randomly divided into weekly usage (45 mg/m2, 1 times/week, a total of 270 mg/m2 in six weeks) and triple weekly usage (15 mg/m2, 3 times/week, a total of 270 mg/m2 in six weeks) group of paclitaxel by a random number table. All patients were treated with 3D radiotherapy, and 95% planning target volume (PTV) received a prescription dose of (60-70) Gy/(30-35)times/(6-7)weeks, (1.8-2.0) Gy/fraction. Then the side effects, response and overall survival rate were compared between two groups of patients. Results Thirty-eight LANSCLC patients were enrolled. Weekly usage and triple weekly usage group were 20 and 18 patients, respectively. In the triple weekly usage group, the side effects were 12 patients had radiation esophagitis of I-II degree, 1 patient had radiation esophagitis of III degree, 2 patients had radiation pneumonitis of I degree, 1 patient had radiation pneumonitis of II degree, 1 patient had radiation pneumonitis of III degree and died of respiratory failure, 2 patients developed weight loss of I degree. In the weekly usage group, the side effects were 11 patients had radiation esophagitis of I-III degree, 6 patients had radiation pneumonitis of II-III degree, 2 patients developed weight loss of I degree, 6 patients developed leucopenia of III-IV degree. The response rate of two groups was 88.8% and 50.0%, respectively (P=0.026). 1-year survival rate of two groups was 79% and 67%, respectively (P=0.607). Conclusion Although the preliminary results did not show the merits of survival in triple weekly usage, but preliminary results show that triple weekly usage was more safe and effective than weekly usage of paclitaxel in concurrent radiochemotherapy for patients with LANSCLC.
AxPUE: Application Level Metrics for Power Usage Effectiveness in Data Centers
Runlin Zhou,Yingjie Shi,Chunge Zhu,Fan Liu
Computer Science , 2013,
Abstract: The rapid growth of data volume brings big challenges to the data center computing, and energy efficiency is one of the most concerned problems. Researchers from various fields are now proposing solutions to green the data center operations. Power usage effectiveness metric plays an important role in the energy saving research. However, the exising usage effectiveness metrics focus on measuring the relationship between the total facility energy consumed and the IT equipment energy consumed, without reflecting the energy efficiency of applications. In this paper, we analyze the requirements of application-level metrics for power usage efficiency of the data centers, and propose two novel energy efficiency metrics to provide strong guidance and useful insight to data center design and optimization. We conduct comprehensive experiments in the practical data centers using BigDataBench, a big data benchmark suite, and the results demonstrate the rationality and efficiency of AxPUE in measuring the actual computation energy consumption in data centers.
The Implications from Benchmarking Three Big Data Systems
Jing Quan,Yingjie Shi,Ming Zhao,Wei Yang
Computer Science , 2013,
Abstract: Along with today's data explosion and application diversification, a variety of hardware platforms for big data are emerging, attracting interests from both industry and academia. The existing hardware platforms represent a wide range of implementation approaches, and different hardware platforms have different strengths. In this paper, we conduct comprehensive evaluations on three representative big data systems: Intel Xeon, Atom (low power processors), and many-core Tilera using BigDataBench - a big data benchmark suite. Then we explore the relative performance of the three implementation approaches by running BigDataBench, and provide strong guidance for the big data systems construction. Through our experiments, we have inferred that a big data system based on specific hardware has different performance in the context of different applications and data volumes. When we construct a system, we should take into account not only the performance or energy consumption of the pure hardware, but also the characteristics of applications running on them. Data scale, application type and complexity should be considered comprehensively when researchers or architects plan to choose fundamental components for their big data systems.
In Vitro Effects of Pirfenidone on Cardiac Fibroblasts: Proliferation, Myofibroblast Differentiation, Migration and Cytokine Secretion
Qiang Shi, Xiaoyan Liu, Yuanyuan Bai, Chuanjue Cui, Jun Li, Yishi Li, Shengshou Hu, Yingjie Wei
PLOS ONE , 2011, DOI: 10.1371/journal.pone.0028134
Abstract: Cardiac fibroblasts (CFs) are the primary cell type responsible for cardiac fibrosis during pathological myocardial remodeling. Several studies have illustrated that pirfenidone (5-methyl-1-phenyl-2-[1H]-pyridone) attenuates cardiac fibrosis in different animal models. However, the effects of pirfenidone on cardiac fibroblast behavior have not been examined. In this study, we investigated whether pirfenidone directly modulates cardiac fibroblast behavior that is important in myocardial remodeling such as proliferation, myofibroblast differentiation, migration and cytokine secretion. Fibroblasts were isolated from neonatal rat hearts and bioassays were performed to determine the effects of pirfenidone on fibroblast function. We demonstrated that treatment of CFs with pirfenidone resulted in decreased proliferation, and attenuated fibroblast α-smooth muscle actin expression and collagen contractility. Boyden chamber assay illustrated that pirfenidone inhibited fibroblast migration ability, probably by decreasing the ratio of matrix metalloproteinase-9 to tissue inhibitor of metalloproteinase-1. Furthermore, pirfenidone attenuated the synthesis and secretion of transforming growth factor-β1 but elevated that of interleukin-10. These direct and pleiotropic effects of pirfenidone on cardiac fibroblasts point to its potential use in the treatment of adverse myocardial remodeling.
Rigorous assessment and integration of the sequence and structure based features to predict hot spots
Ruoying Chen, Wenjing Chen, Sixiao Yang, Di Wu, Yong Wang, Yingjie Tian, Yong Shi
BMC Bioinformatics , 2011, DOI: 10.1186/1471-2105-12-311
Abstract: In this study, we first comprehensively collect the features to discriminate hot spots and non-hot spots and analyze their distributions. We find that hot spots have lower relASA and larger relative change in ASA, suggesting hot spots tend to be protected from bulk solvent. In addition, hot spots have more contacts including hydrogen bonds, salt bridges, and atomic contacts, which favor complexes formation. Interestingly, we find that conservation score and sequence entropy are not significantly different between hot spots and non-hot spots in Ab+ dataset (all complexes). While in Ab- dataset (antigen-antibody complexes are excluded), there are significant differences in two features between hot pots and non-hot spots. Secondly, we explore the predictive ability for each feature and the combinations of features by support vector machines (SVMs). The results indicate that sequence-based feature outperforms other combinations of features with reasonable accuracy, with a precision of 0.69, a recall of 0.68, an F1 score of 0.68, and an AUC of 0.68 on independent test set. Compared with other machine learning methods and two energy-based approaches, our approach achieves the best performance. Moreover, we demonstrate the applicability of our method to predict hot spots of two protein complexes.Experimental results show that support vector machine classifiers are quite effective in predicting hot spots based on sequence features. Hot spots cannot be fully predicted through simple analysis based on physicochemical characteristics, but there is reason to believe that integration of features and machine learning methods can remarkably improve the predictive performance for hot spots.A lot of biological processes are regulated or performed by protein-protein interactions [1-5]. Elucidating the molecular mechanism of proteins interactions is a key topic in protein function study. Hence, to fully understand or control biological processes, we need to probe the principles of pro
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