WorldWideScience

Sample records for genome-scale identification method

  1. Genome-scale identification of Legionella pneumophila effectors using a machine learning approach.

    Directory of Open Access Journals (Sweden)

    David Burstein

    2009-07-01

    Full Text Available A large number of highly pathogenic bacteria utilize secretion systems to translocate effector proteins into host cells. Using these effectors, the bacteria subvert host cell processes during infection. Legionella pneumophila translocates effectors via the Icm/Dot type-IV secretion system and to date, approximately 100 effectors have been identified by various experimental and computational techniques. Effector identification is a critical first step towards the understanding of the pathogenesis system in L. pneumophila as well as in other bacterial pathogens. Here, we formulate the task of effector identification as a classification problem: each L. pneumophila open reading frame (ORF was classified as either effector or not. We computationally defined a set of features that best distinguish effectors from non-effectors. These features cover a wide range of characteristics including taxonomical dispersion, regulatory data, genomic organization, similarity to eukaryotic proteomes and more. Machine learning algorithms utilizing these features were then applied to classify all the ORFs within the L. pneumophila genome. Using this approach we were able to predict and experimentally validate 40 new effectors, reaching a success rate of above 90%. Increasing the number of validated effectors to around 140, we were able to gain novel insights into their characteristics. Effectors were found to have low G+C content, supporting the hypothesis that a large number of effectors originate via horizontal gene transfer, probably from their protozoan host. In addition, effectors were found to cluster in specific genomic regions. Finally, we were able to provide a novel description of the C-terminal translocation signal required for effector translocation by the Icm/Dot secretion system. To conclude, we have discovered 40 novel L. pneumophila effectors, predicted over a hundred additional highly probable effectors, and shown the applicability of machine

  2. In silico method for modelling metabolism and gene product expression at genome scale

    Energy Technology Data Exchange (ETDEWEB)

    Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem; Portnoy, Vasiliy A.; Lewis, Nathan E.; Orth, Jeffrey D.; Rutledge, Alexandra C.; Smith, Richard D.; Adkins, Joshua N.; Zengler, Karsten; Palsson, Bernard O.

    2012-07-03

    Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome and transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism.

  3. SECOM: A novel hash seed and community detection based-approach for genome-scale protein domain identification

    KAUST Repository

    Fan, Ming

    2012-06-28

    With rapid advances in the development of DNA sequencing technologies, a plethora of high-throughput genome and proteome data from a diverse spectrum of organisms have been generated. The functional annotation and evolutionary history of proteins are usually inferred from domains predicted from the genome sequences. Traditional database-based domain prediction methods cannot identify novel domains, however, and alignment-based methods, which look for recurring segments in the proteome, are computationally demanding. Here, we propose a novel genome-wide domain prediction method, SECOM. Instead of conducting all-against-all sequence alignment, SECOM first indexes all the proteins in the genome by using a hash seed function. Local similarity can thus be detected and encoded into a graph structure, in which each node represents a protein sequence and each edge weight represents the shared hash seeds between the two nodes. SECOM then formulates the domain prediction problem as an overlapping community-finding problem in this graph. A backward graph percolation algorithm that efficiently identifies the domains is proposed. We tested SECOM on five recently sequenced genomes of aquatic animals. Our tests demonstrated that SECOM was able to identify most of the known domains identified by InterProScan. When compared with the alignment-based method, SECOM showed higher sensitivity in detecting putative novel domains, while it was also three orders of magnitude faster. For example, SECOM was able to predict a novel sponge-specific domain in nucleoside-triphosphatase (NTPases). Furthermore, SECOM discovered two novel domains, likely of bacterial origin, that are taxonomically restricted to sea anemone and hydra. SECOM is an open-source program and available at http://sfb.kaust.edu.sa/Pages/Software.aspx. © 2012 Fan et al.

  4. SECOM: A novel hash seed and community detection based-approach for genome-scale protein domain identification

    KAUST Repository

    Fan, Ming; Wong, Ka-Chun; Ryu, Tae Woo; Ravasi, Timothy; Gao, Xin

    2012-01-01

    With rapid advances in the development of DNA sequencing technologies, a plethora of high-throughput genome and proteome data from a diverse spectrum of organisms have been generated. The functional annotation and evolutionary history of proteins are usually inferred from domains predicted from the genome sequences. Traditional database-based domain prediction methods cannot identify novel domains, however, and alignment-based methods, which look for recurring segments in the proteome, are computationally demanding. Here, we propose a novel genome-wide domain prediction method, SECOM. Instead of conducting all-against-all sequence alignment, SECOM first indexes all the proteins in the genome by using a hash seed function. Local similarity can thus be detected and encoded into a graph structure, in which each node represents a protein sequence and each edge weight represents the shared hash seeds between the two nodes. SECOM then formulates the domain prediction problem as an overlapping community-finding problem in this graph. A backward graph percolation algorithm that efficiently identifies the domains is proposed. We tested SECOM on five recently sequenced genomes of aquatic animals. Our tests demonstrated that SECOM was able to identify most of the known domains identified by InterProScan. When compared with the alignment-based method, SECOM showed higher sensitivity in detecting putative novel domains, while it was also three orders of magnitude faster. For example, SECOM was able to predict a novel sponge-specific domain in nucleoside-triphosphatase (NTPases). Furthermore, SECOM discovered two novel domains, likely of bacterial origin, that are taxonomically restricted to sea anemone and hydra. SECOM is an open-source program and available at http://sfb.kaust.edu.sa/Pages/Software.aspx. © 2012 Fan et al.

  5. Meta-Analysis of Heterogeneous Data Sources for Genome-Scale Identification of Risk Genes in Complex Phenotypes

    DEFF Research Database (Denmark)

    Pers, Tune Hannes; Hansen, Niclas Tue; Hansen, Kasper Lage

    2011-01-01

    Meta‐analyses of large‐scale association studies typically proceed solely within one data type and do not exploit the potential complementarities in other sources of molecular evidence. Here, we present an approach to combine heterogeneous data from genome‐wide association (GWA) studies, protein......) with an odds ratio of 1.28 [1.12–1.48], which replicates a previous case‐control study. In addition, we demonstrate our approach's general applicability by use of type 2 diabetes data sets. The method presented augments moderately powered GWA data, and represents a validated, flexible, and publicly available...

  6. Hob Identification Methods

    Directory of Open Access Journals (Sweden)

    Andrzej Piotrowski

    2018-03-01

    Full Text Available In industrial practice, hobs are manufactured and used. The problem boils down to the identification of a hob with defining its profile, which depends on many design and technological parameters (such as the grinding wheel size, profile, type and positioning during machining. This makes the basis for the correct execution and sharpening of the tool. The accuracy of the hob determines the quality of gear wheel teeth being shaped. The article presents the hob identification methods that are possible to be used in industrial and laboratory practice.

  7. Using Genome-scale Models to Predict Biological Capabilities

    DEFF Research Database (Denmark)

    O’Brien, Edward J.; Monk, Jonathan M.; Palsson, Bernhard O.

    2015-01-01

    Constraint-based reconstruction and analysis (COBRA) methods at the genome scale have been under development since the first whole-genome sequences appeared in the mid-1990s. A few years ago, this approach began to demonstrate the ability to predict a range of cellular functions, including cellul...

  8. Next-generation genome-scale models for metabolic engineering

    DEFF Research Database (Denmark)

    King, Zachary A.; Lloyd, Colton J.; Feist, Adam M.

    2015-01-01

    Constraint-based reconstruction and analysis (COBRA) methods have become widely used tools for metabolic engineering in both academic and industrial laboratories. By employing a genome-scale in silico representation of the metabolic network of a host organism, COBRA methods can be used to predict...... examples of applying COBRA methods to strain optimization are presented and discussed. Then, an outlook is provided on the next generation of COBRA models and the new types of predictions they will enable for systems metabolic engineering....

  9. Fixing Formalin: A Method to Recover Genomic-Scale DNA Sequence Data from Formalin-Fixed Museum Specimens Using High-Throughput Sequencing.

    Directory of Open Access Journals (Sweden)

    Sarah M Hykin

    Full Text Available For 150 years or more, specimens were routinely collected and deposited in natural history collections without preserving fresh tissue samples for genetic analysis. In the case of most herpetological specimens (i.e. amphibians and reptiles, attempts to extract and sequence DNA from formalin-fixed, ethanol-preserved specimens-particularly for use in phylogenetic analyses-has been laborious and largely ineffective due to the highly fragmented nature of the DNA. As a result, tens of thousands of specimens in herpetological collections have not been available for sequence-based phylogenetic studies. Massively parallel High-Throughput Sequencing methods and the associated bioinformatics, however, are particularly suited to recovering meaningful genetic markers from severely degraded/fragmented DNA sequences such as DNA damaged by formalin-fixation. In this study, we compared previously published DNA extraction methods on three tissue types subsampled from formalin-fixed specimens of Anolis carolinensis, followed by sequencing. Sufficient quality DNA was recovered from liver tissue, making this technique minimally destructive to museum specimens. Sequencing was only successful for the more recently collected specimen (collected ~30 ybp. We suspect this could be due either to the conditions of preservation and/or the amount of tissue used for extraction purposes. For the successfully sequenced sample, we found a high rate of base misincorporation. After rigorous trimming, we successfully mapped 27.93% of the cleaned reads to the reference genome, were able to reconstruct the complete mitochondrial genome, and recovered an accurate phylogenetic placement for our specimen. We conclude that the amount of DNA available, which can vary depending on specimen age and preservation conditions, will determine if sequencing will be successful. The technique described here will greatly improve the value of museum collections by making many formalin-fixed specimens

  10. Fixing Formalin: A Method to Recover Genomic-Scale DNA Sequence Data from Formalin-Fixed Museum Specimens Using High-Throughput Sequencing.

    Science.gov (United States)

    Hykin, Sarah M; Bi, Ke; McGuire, Jimmy A

    2015-01-01

    For 150 years or more, specimens were routinely collected and deposited in natural history collections without preserving fresh tissue samples for genetic analysis. In the case of most herpetological specimens (i.e. amphibians and reptiles), attempts to extract and sequence DNA from formalin-fixed, ethanol-preserved specimens-particularly for use in phylogenetic analyses-has been laborious and largely ineffective due to the highly fragmented nature of the DNA. As a result, tens of thousands of specimens in herpetological collections have not been available for sequence-based phylogenetic studies. Massively parallel High-Throughput Sequencing methods and the associated bioinformatics, however, are particularly suited to recovering meaningful genetic markers from severely degraded/fragmented DNA sequences such as DNA damaged by formalin-fixation. In this study, we compared previously published DNA extraction methods on three tissue types subsampled from formalin-fixed specimens of Anolis carolinensis, followed by sequencing. Sufficient quality DNA was recovered from liver tissue, making this technique minimally destructive to museum specimens. Sequencing was only successful for the more recently collected specimen (collected ~30 ybp). We suspect this could be due either to the conditions of preservation and/or the amount of tissue used for extraction purposes. For the successfully sequenced sample, we found a high rate of base misincorporation. After rigorous trimming, we successfully mapped 27.93% of the cleaned reads to the reference genome, were able to reconstruct the complete mitochondrial genome, and recovered an accurate phylogenetic placement for our specimen. We conclude that the amount of DNA available, which can vary depending on specimen age and preservation conditions, will determine if sequencing will be successful. The technique described here will greatly improve the value of museum collections by making many formalin-fixed specimens available for

  11. Genome scale engineering techniques for metabolic engineering.

    Science.gov (United States)

    Liu, Rongming; Bassalo, Marcelo C; Zeitoun, Ramsey I; Gill, Ryan T

    2015-11-01

    Metabolic engineering has expanded from a focus on designs requiring a small number of genetic modifications to increasingly complex designs driven by advances in genome-scale engineering technologies. Metabolic engineering has been generally defined by the use of iterative cycles of rational genome modifications, strain analysis and characterization, and a synthesis step that fuels additional hypothesis generation. This cycle mirrors the Design-Build-Test-Learn cycle followed throughout various engineering fields that has recently become a defining aspect of synthetic biology. This review will attempt to summarize recent genome-scale design, build, test, and learn technologies and relate their use to a range of metabolic engineering applications. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  12. Genome-scale neurogenetics: methodology and meaning.

    Science.gov (United States)

    McCarroll, Steven A; Feng, Guoping; Hyman, Steven E

    2014-06-01

    Genetic analysis is currently offering glimpses into molecular mechanisms underlying such neuropsychiatric disorders as schizophrenia, bipolar disorder and autism. After years of frustration, success in identifying disease-associated DNA sequence variation has followed from new genomic technologies, new genome data resources, and global collaborations that could achieve the scale necessary to find the genes underlying highly polygenic disorders. Here we describe early results from genome-scale studies of large numbers of subjects and the emerging significance of these results for neurobiology.

  13. Genome scale metabolic modeling of cancer

    DEFF Research Database (Denmark)

    Nilsson, Avlant; Nielsen, Jens

    2017-01-01

    of metabolism which allows simulation and hypotheses testing of metabolic strategies. It has successfully been applied to many microorganisms and is now used to study cancer metabolism. Generic models of human metabolism have been reconstructed based on the existence of metabolic genes in the human genome......Cancer cells reprogram metabolism to support rapid proliferation and survival. Energy metabolism is particularly important for growth and genes encoding enzymes involved in energy metabolism are frequently altered in cancer cells. A genome scale metabolic model (GEM) is a mathematical formalization...

  14. Identification methods of irradiated food

    International Nuclear Information System (INIS)

    Raffi, J.J.

    1991-01-01

    After a general review of the different possible methods, the stress is put upon the ones close to application: electron spin resonance, thermoluminescence and method of lipids. The problem of the specificity of each method is discussed (proof or presumption): they are then placed in the context of the programme of identification of irradiated foods just co-organized by the author with the Community Bureau of Reference (CEC) [fr

  15. Multivariate methods for particle identification

    CERN Document Server

    Visan, Cosmin

    2013-01-01

    The purpose of this project was to evaluate several MultiVariate methods in order to determine which one, if any, offers better results in Particle Identification (PID) than a simple n$\\sigma$ cut on the response of the ALICE PID detectors. The particles considered in the analysis were Pions, Kaons and Protons and the detectors used were TPC and TOF. When used with the same input n$\\sigma$ variables, the results show similar perfoance between the Rectangular Cuts Optimization method and the simple n$\\sigma$ cuts. The method MLP and BDT show poor results for certain ranges of momentum. The KNN method is the best performing, showing similar results for Pions and Protons as the Cuts method, and better results for Kaons. The extension of the methods to include additional input variables leads to poor results, related to instabilities still to be investigated.

  16. TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks

    Directory of Open Access Journals (Sweden)

    Jensen Paul A

    2011-09-01

    Full Text Available Abstract Background Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict relationships between metabolic flux and the genes that encode and regulate enzyme activity. Recently, mixed integer programming has been used to encode these gene-protein-reaction (GPR relationships into a single optimization problem, but these techniques are often of limited generality and lack a tool for automating the conversion of rules to a coupled regulatory/metabolic model. Results We present TIGER, a Toolbox for Integrating Genome-scale Metabolism, Expression, and Regulation. TIGER converts a series of generalized, Boolean or multilevel rules into a set of mixed integer inequalities. The package also includes implementations of existing algorithms to integrate high-throughput expression data with genome-scale models of metabolism and transcriptional regulation. We demonstrate how TIGER automates the coupling of a genome-scale metabolic model with GPR logic and models of transcriptional regulation, thereby serving as a platform for algorithm development and large-scale metabolic analysis. Additionally, we demonstrate how TIGER's algorithms can be used to identify inconsistencies and improve existing models of transcriptional regulation with examples from the reconstructed transcriptional regulatory network of Saccharomyces cerevisiae. Conclusion The TIGER package provides a consistent platform for algorithm development and extending existing genome-scale metabolic models with regulatory networks and high-throughput data.

  17. Reframed Genome-Scale Metabolic Model to Facilitate Genetic Design and Integration with Expression Data.

    Science.gov (United States)

    Gu, Deqing; Jian, Xingxing; Zhang, Cheng; Hua, Qiang

    2017-01-01

    Genome-scale metabolic network models (GEMs) have played important roles in the design of genetically engineered strains and helped biologists to decipher metabolism. However, due to the complex gene-reaction relationships that exist in model systems, most algorithms have limited capabilities with respect to directly predicting accurate genetic design for metabolic engineering. In particular, methods that predict reaction knockout strategies leading to overproduction are often impractical in terms of gene manipulations. Recently, we proposed a method named logical transformation of model (LTM) to simplify the gene-reaction associations by introducing intermediate pseudo reactions, which makes it possible to generate genetic design. Here, we propose an alternative method to relieve researchers from deciphering complex gene-reactions by adding pseudo gene controlling reactions. In comparison to LTM, this new method introduces fewer pseudo reactions and generates a much smaller model system named as gModel. We showed that gModel allows two seldom reported applications: identification of minimal genomes and design of minimal cell factories within a modified OptKnock framework. In addition, gModel could be used to integrate expression data directly and improve the performance of the E-Fmin method for predicting fluxes. In conclusion, the model transformation procedure will facilitate genetic research based on GEMs, extending their applications.

  18. Identification methods for irradiated wheat

    International Nuclear Information System (INIS)

    Zhu Shengtao; Kume, Tamikazu; Ishigaki, Isao.

    1992-02-01

    The effect of irradiation on wheat seeds was examined using various kinds of analytical methods for the identification of irradiated seeds. In germination test, the growth of sprouts was markedly inhibited at 500Gy, which was not affected by storage. The decrease in germination percentage was detected at 3300Gy. The results of enzymatic activity change in the germ measured by Vita-Scope germinator showed that the seeds irradiated at 10kGy could be identified. The content of amino acids in ungerminated and germinated seeds were analyzed. Irradiation at 10kGy caused the decrease of lysine content but the change was small which need very careful operation to detect it. The chemiluminescence intensity increased with radiation dose and decreased during storage. The wheat irradiated at 10kGy could be identified even after 3 months storage. In the electron spin resonance (ESR) spectrum analysis, the signal intensity with the g value f 2.0055 of skinned wheat seeds increased with radiation dose. Among these methods, germination test was the most sensitive and effective for identification of irradiated wheat. (author)

  19. Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming

    Energy Technology Data Exchange (ETDEWEB)

    Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh; Ramkrishna, Doraiswami

    2017-03-27

    Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs.

  20. Genome-scale biological models for industrial microbial systems.

    Science.gov (United States)

    Xu, Nan; Ye, Chao; Liu, Liming

    2018-04-01

    The primary aims and challenges associated with microbial fermentation include achieving faster cell growth, higher productivity, and more robust production processes. Genome-scale biological models, predicting the formation of an interaction among genetic materials, enzymes, and metabolites, constitute a systematic and comprehensive platform to analyze and optimize the microbial growth and production of biological products. Genome-scale biological models can help optimize microbial growth-associated traits by simulating biomass formation, predicting growth rates, and identifying the requirements for cell growth. With regard to microbial product biosynthesis, genome-scale biological models can be used to design product biosynthetic pathways, accelerate production efficiency, and reduce metabolic side effects, leading to improved production performance. The present review discusses the development of microbial genome-scale biological models since their emergence and emphasizes their pertinent application in improving industrial microbial fermentation of biological products.

  1. Metingear: a development environment for annotating genome-scale metabolic models.

    Science.gov (United States)

    May, John W; James, A Gordon; Steinbeck, Christoph

    2013-09-01

    Genome-scale metabolic models often lack annotations that would allow them to be used for further analysis. Previous efforts have focused on associating metabolites in the model with a cross reference, but this can be problematic if the reference is not freely available, multiple resources are used or the metabolite is added from a literature review. Associating each metabolite with chemical structure provides unambiguous identification of the components and a more detailed view of the metabolism. We have developed an open-source desktop application that simplifies the process of adding database cross references and chemical structures to genome-scale metabolic models. Annotated models can be exported to the Systems Biology Markup Language open interchange format. Source code, binaries, documentation and tutorials are freely available at http://johnmay.github.com/metingear. The application is implemented in Java with bundles available for MS Windows and Macintosh OS X.

  2. Identification and authentication. Common biometric methods review

    OpenAIRE

    Lysak, A.

    2012-01-01

    Major biometric methods used for identification and authentication purposes in modern computing systems are considered in the article. Basic classification, application areas and key differences are given.

  3. Analysis of Piscirickettsia salmonis Metabolism Using Genome-Scale Reconstruction, Modeling, and Testing

    Directory of Open Access Journals (Sweden)

    María P. Cortés

    2017-12-01

    Full Text Available Piscirickettsia salmonis is an intracellular bacterial fish pathogen that causes piscirickettsiosis, a disease with highly adverse impact in the Chilean salmon farming industry. The development of effective treatment and control methods for piscireckttsiosis is still a challenge. To meet it the number of studies on P. salmonis has grown in the last couple of years but many aspects of the pathogen’s biology are still poorly understood. Studies on its metabolism are scarce and only recently a metabolic model for reference strain LF-89 was developed. We present a new genome-scale model for P. salmonis LF-89 with more than twice as many genes as in the previous model and incorporating specific elements of the fish pathogen metabolism. Comparative analysis with models of different bacterial pathogens revealed a lower flexibility in P. salmonis metabolic network. Through constraint-based analysis, we determined essential metabolites required for its growth and showed that it can benefit from different carbon sources tested experimentally in new defined media. We also built an additional model for strain A1-15972, and together with an analysis of P. salmonis pangenome, we identified metabolic features that differentiate two main species clades. Both models constitute a knowledge-base for P. salmonis metabolism and can be used to guide the efficient culture of the pathogen and the identification of specific drug targets.

  4. Star identification methods, techniques and algorithms

    CERN Document Server

    Zhang, Guangjun

    2017-01-01

    This book summarizes the research advances in star identification that the author’s team has made over the past 10 years, systematically introducing the principles of star identification, general methods, key techniques and practicable algorithms. It also offers examples of hardware implementation and performance evaluation for the star identification algorithms. Star identification is the key step for celestial navigation and greatly improves the performance of star sensors, and as such the book include the fundamentals of star sensors and celestial navigation, the processing of the star catalog and star images, star identification using modified triangle algorithms, star identification using star patterns and using neural networks, rapid star tracking using star matching between adjacent frames, as well as implementation hardware and using performance tests for star identification. It is not only valuable as a reference book for star sensor designers and researchers working in pattern recognition and othe...

  5. The OME Framework for genome-scale systems biology

    Energy Technology Data Exchange (ETDEWEB)

    Palsson, Bernhard O. [Univ. of California, San Diego, CA (United States); Ebrahim, Ali [Univ. of California, San Diego, CA (United States); Federowicz, Steve [Univ. of California, San Diego, CA (United States)

    2014-12-19

    The life sciences are undergoing continuous and accelerating integration with computational and engineering sciences. The biology that many in the field have been trained on may be hardly recognizable in ten to twenty years. One of the major drivers for this transformation is the blistering pace of advancements in DNA sequencing and synthesis. These advances have resulted in unprecedented amounts of new data, information, and knowledge. Many software tools have been developed to deal with aspects of this transformation and each is sorely needed [1-3]. However, few of these tools have been forced to deal with the full complexity of genome-scale models along with high throughput genome- scale data. This particular situation represents a unique challenge, as it is simultaneously necessary to deal with the vast breadth of genome-scale models and the dizzying depth of high-throughput datasets. It has been observed time and again that as the pace of data generation continues to accelerate, the pace of analysis significantly lags behind [4]. It is also evident that, given the plethora of databases and software efforts [5-12], it is still a significant challenge to work with genome-scale metabolic models, let alone next-generation whole cell models [13-15]. We work at the forefront of model creation and systems scale data generation [16-18]. The OME Framework was borne out of a practical need to enable genome-scale modeling and data analysis under a unified framework to drive the next generation of genome-scale biological models. Here we present the OME Framework. It exists as a set of Python classes. However, we want to emphasize the importance of the underlying design as an addition to the discussions on specifications of a digital cell. A great deal of work and valuable progress has been made by a number of communities [13, 19-24] towards interchange formats and implementations designed to achieve similar goals. While many software tools exist for handling genome-scale

  6. Multiple independent identification decisions: a method of calibrating eyewitness identifications.

    Science.gov (United States)

    Pryke, Sean; Lindsay, R C L; Dysart, Jennifer E; Dupuis, Paul

    2004-02-01

    Two experiments (N = 147 and N = 90) explored the use of multiple independent lineups to identify a target seen live. In Experiment 1, simultaneous face, body, and sequential voice lineups were used. In Experiment 2, sequential face, body, voice, and clothing lineups were used. Both studies demonstrated that multiple identifications (by the same witness) from independent lineups of different features are highly diagnostic of suspect guilt (G. L. Wells & R. C. L. Lindsay, 1980). The number of suspect and foil selections from multiple independent lineups provides a powerful method of calibrating the accuracy of eyewitness identification. Implications for use of current methods are discussed. ((c) 2004 APA, all rights reserved)

  7. Use of genome-scale microbial models for metabolic engineering

    DEFF Research Database (Denmark)

    Patil, Kiran Raosaheb; Åkesson, M.; Nielsen, Jens

    2004-01-01

    Metabolic engineering serves as an integrated approach to design new cell factories by providing rational design procedures and valuable mathematical and experimental tools. Mathematical models have an important role for phenotypic analysis, but can also be used for the design of optimal metaboli...... network structures. The major challenge for metabolic engineering in the post-genomic era is to broaden its design methodologies to incorporate genome-scale biological data. Genome-scale stoichiometric models of microorganisms represent a first step in this direction....

  8. Integration of expression data in genome-scale metabolic network reconstructions

    Directory of Open Access Journals (Sweden)

    Anna S. Blazier

    2012-08-01

    Full Text Available With the advent of high-throughput technologies, the field of systems biology has amassed an abundance of omics data, quantifying thousands of cellular components across a variety of scales, ranging from mRNA transcript levels to metabolite quantities. Methods are needed to not only integrate this omics data but to also use this data to heighten the predictive capabilities of computational models. Several recent studies have successfully demonstrated how flux balance analysis (FBA, a constraint-based modeling approach, can be used to integrate transcriptomic data into genome-scale metabolic network reconstructions to generate predictive computational models. In this review, we summarize such FBA-based methods for integrating expression data into genome-scale metabolic network reconstructions, highlighting their advantages as well as their limitations.

  9. Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming.

    Science.gov (United States)

    Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh; Ramkrishna, Doraiswami

    2017-08-01

    Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs. The software is implemented in Matlab, and is provided as supplementary information . hyunseob.song@pnnl.gov. Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2017. This work is written by US Government employees and are in the public domain in the US.

  10. The Genome-Scale Integrated Networks in Microorganisms

    Directory of Open Access Journals (Sweden)

    Tong Hao

    2018-02-01

    Full Text Available The genome-scale cellular network has become a necessary tool in the systematic analysis of microbes. In a cell, there are several layers (i.e., types of the molecular networks, for example, genome-scale metabolic network (GMN, transcriptional regulatory network (TRN, and signal transduction network (STN. It has been realized that the limitation and inaccuracy of the prediction exist just using only a single-layer network. Therefore, the integrated network constructed based on the networks of the three types attracts more interests. The function of a biological process in living cells is usually performed by the interaction of biological components. Therefore, it is necessary to integrate and analyze all the related components at the systems level for the comprehensively and correctly realizing the physiological function in living organisms. In this review, we discussed three representative genome-scale cellular networks: GMN, TRN, and STN, representing different levels (i.e., metabolism, gene regulation, and cellular signaling of a cell’s activities. Furthermore, we discussed the integration of the networks of the three types. With more understanding on the complexity of microbial cells, the development of integrated network has become an inevitable trend in analyzing genome-scale cellular networks of microorganisms.

  11. Genome-scale modeling for metabolic engineering.

    Science.gov (United States)

    Simeonidis, Evangelos; Price, Nathan D

    2015-03-01

    We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information-an area which we expect will become increasingly important for metabolic engineering-and present recent developments in the field of metabolic and regulatory integration.

  12. Enumeration of smallest intervention strategies in genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Axel von Kamp

    2014-01-01

    Full Text Available One ultimate goal of metabolic network modeling is the rational redesign of biochemical networks to optimize the production of certain compounds by cellular systems. Although several constraint-based optimization techniques have been developed for this purpose, methods for systematic enumeration of intervention strategies in genome-scale metabolic networks are still lacking. In principle, Minimal Cut Sets (MCSs; inclusion-minimal combinations of reaction or gene deletions that lead to the fulfilment of a given intervention goal provide an exhaustive enumeration approach. However, their disadvantage is the combinatorial explosion in larger networks and the requirement to compute first the elementary modes (EMs which itself is impractical in genome-scale networks. We present MCSEnumerator, a new method for effective enumeration of the smallest MCSs (with fewest interventions in genome-scale metabolic network models. For this we combine two approaches, namely (i the mapping of MCSs to EMs in a dual network, and (ii a modified algorithm by which shortest EMs can be effectively determined in large networks. In this way, we can identify the smallest MCSs by calculating the shortest EMs in the dual network. Realistic application examples demonstrate that our algorithm is able to list thousands of the most efficient intervention strategies in genome-scale networks for various intervention problems. For instance, for the first time we could enumerate all synthetic lethals in E.coli with combinations of up to 5 reactions. We also applied the new algorithm exemplarily to compute strain designs for growth-coupled synthesis of different products (ethanol, fumarate, serine by E.coli. We found numerous new engineering strategies partially requiring less knockouts and guaranteeing higher product yields (even without the assumption of optimal growth than reported previously. The strength of the presented approach is that smallest intervention strategies can be

  13. Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.

    Science.gov (United States)

    Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen

    2017-02-01

    Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too. Our solution (PSOMCS) is to use particle swarm optimization (PSO) along with the direct calculation of cMCSs from the stoichiometric matrix to obtain optimal designs satisfying multiple objectives. To illustrate the working of PSOMCS, we apply it to a toy network. Next we show its superiority by comparing its performance against other comparable methods on a medium sized E. coli core metabolic network. PSOMCS not only finds solutions comparable to previously published results but also it is orders of magnitude faster. Finally, we use PSOMCS to predict knockouts satisfying multiple objectives in a genome-scale metabolic model of E. coli and compare it with OptKnock and RobustKnock. PSOMCS finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. It can be used in identifying knockouts which will force optimal desired behaviors in large and genome scale metabolic networks. It will be even more useful as larger metabolic models of industrially relevant organisms become available.

  14. Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

    Science.gov (United States)

    Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

    2016-09-19

    Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

  15. Identification methods for structural health monitoring

    CERN Document Server

    Papadimitriou, Costas

    2016-01-01

    The papers in this volume provide an introduction to well known and established system identification methods for structural health monitoring and to more advanced, state-of-the-art tools, able to tackle the challenges associated with actual implementation. Starting with an overview on fundamental methods, introductory concepts are provided on the general framework of time and frequency domain, parametric and non-parametric methods, input-output or output only techniques. Cutting edge tools are introduced including, nonlinear system identification methods; Bayesian tools; and advanced modal identification techniques (such as the Kalman and particle filters, the fast Bayesian FFT method). Advanced computational tools for uncertainty quantification are discussed to provide a link between monitoring and structural integrity assessment. In addition, full scale applications and field deployments that illustrate the workings and effectiveness of the introduced monitoring schemes are demonstrated.

  16. Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network

    OpenAIRE

    Mart?n-Jim?nez, Cynthia A.; Salazar-Barreto, Diego; Barreto, George E.; Gonz?lez, Janneth

    2017-01-01

    Astrocytes are the most abundant cells of the central nervous system; they have a predominant role in maintaining brain metabolism. In this sense, abnormal metabolic states have been found in different neuropathological diseases. Determination of metabolic states of astrocytes is difficult to model using current experimental approaches given the high number of reactions and metabolites present. Thus, genome-scale metabolic networks derived from transcriptomic data can be used as a framework t...

  17. Fuel number identification method and device

    International Nuclear Information System (INIS)

    Doi, Takami; Seno, Makoto; Kikuchi, Takashi; Sakamoto, Hiromi; Takahashi, Masaki; Tanaka, Keiji.

    1997-01-01

    The present invention provides a method of and a device for automatically identifying fuel numbers impressed on fuel assemblies disposed in a fuel reprocessing facility, power plant and a reactor core at a high speed and at a high identification rate. Namely, three or more character images are photographed for one fuel assembly as an object of the identification under different illumination conditions. As a result, different character images by the number of the illumination directions can be obtained for identical impressed characters. Learning on a neural network system is applied to the images of all of the characters impressed on the fuel assembly obtained under illumination of predetermined directions. Then, result of the identification by the number of the illumination directions can be obtained for each of the characters as an object of the identification. As a result, since the result of the identification is determined based on a theory of decision of majority, highly automatic identification can be realized. (I.S.)

  18. Radionuclide identification using subtractive clustering method

    International Nuclear Information System (INIS)

    Farias, Marcos Santana; Mourelle, Luiza de Macedo

    2011-01-01

    Radionuclide identification is crucial to planning protective measures in emergency situations. This paper presents the application of a method for a classification system of radioactive elements with a fast and efficient response. To achieve this goal is proposed the application of subtractive clustering algorithm. The proposed application can be implemented in reconfigurable hardware, a flexible medium to implement digital hardware circuits. (author)

  19. Genome-scale metabolic modeling of Mucor circinelloides and comparative analysis with other oleaginous species.

    Science.gov (United States)

    Vongsangnak, Wanwipa; Klanchui, Amornpan; Tawornsamretkit, Iyarest; Tatiyaborwornchai, Witthawin; Laoteng, Kobkul; Meechai, Asawin

    2016-06-01

    We present a novel genome-scale metabolic model iWV1213 of Mucor circinelloides, which is an oleaginous fungus for industrial applications. The model contains 1213 genes, 1413 metabolites and 1326 metabolic reactions across different compartments. We demonstrate that iWV1213 is able to accurately predict the growth rates of M. circinelloides on various nutrient sources and culture conditions using Flux Balance Analysis and Phenotypic Phase Plane analysis. Comparative analysis of three oleaginous genome-scale models, including M. circinelloides (iWV1213), Mortierella alpina (iCY1106) and Yarrowia lipolytica (iYL619_PCP) revealed that iWV1213 possesses a higher number of genes involved in carbohydrate, amino acid, and lipid metabolisms that might contribute to its versatility in nutrient utilization. Moreover, the identification of unique and common active reactions among the Zygomycetes oleaginous models using Flux Variability Analysis unveiled a set of gene/enzyme candidates as metabolic engineering targets for cellular improvement. Thus, iWV1213 offers a powerful metabolic engineering tool for multi-level omics analysis, enabling strain optimization as a cell factory platform of lipid-based production. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Particle identification methods in High Energy Physics

    Energy Technology Data Exchange (ETDEWEB)

    Va' Vra, J.

    2000-01-27

    This paper deals with two major particle identification methods: dE/dx and Cherenkov detection. In the first method, the authors systematically compare existing dE/dx data with various predictions available in the literature, such as the Particle Data group recommendation, and judge the overall consistency. To my knowledge, such comparison was not done yet in a published form for the gaseous detectors used in High-Energy physics. As far as the second method, there are two major Cherenkov light detection techniques: the threshold and the Ring imaging methods. The authors discuss the recent trend in these techniques.

  1. New Waste Beverage Cans Identification Method

    Directory of Open Access Journals (Sweden)

    Firmansyah Burlian

    2016-05-01

    Full Text Available The primary emphasis of this work is on the development of a new waste beverage cans identification method for automated beverage cans sorting systems known as the SVS system. The method described involved window-based subdivision of the image into X-cells, construction of X-candidate template for N-cells, calculation of matching scores of reference templates for the N-cells image, and application of matching score to identify the grade of the object. The SVS system performance for correct beverage cans grade identification is 95.17% with estimated throughput of 21,600 objects per hour with a conveyor belt width of 18˝. The weight of the throughput depends on the size and type of the objects.

  2. Computational botany methods for automated species identification

    CERN Document Server

    Remagnino, Paolo; Wilkin, Paul; Cope, James; Kirkup, Don

    2017-01-01

    This book discusses innovative methods for mining information from images of plants, especially leaves, and highlights the diagnostic features that can be implemented in fully automatic systems for identifying plant species. Adopting a multidisciplinary approach, it explores the problem of plant species identification, covering both the concepts of taxonomy and morphology. It then provides an overview of morphometrics, including the historical background and the main steps in the morphometric analysis of leaves together with a number of applications. The core of the book focuses on novel diagnostic methods for plant species identification developed from a computer scientist’s perspective. It then concludes with a chapter on the characterization of botanists' visions, which highlights important cognitive aspects that can be implemented in a computer system to more accurately replicate the human expert’s fixation process. The book not only represents an authoritative guide to advanced computational tools fo...

  3. A mixed-integer linear programming approach to the reduction of genome-scale metabolic networks.

    Science.gov (United States)

    Röhl, Annika; Bockmayr, Alexander

    2017-01-03

    Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.

  4. Quantitative Assessment of Thermodynamic Constraints on the Solution Space of Genome-Scale Metabolic Models

    Science.gov (United States)

    Hamilton, Joshua J.; Dwivedi, Vivek; Reed, Jennifer L.

    2013-01-01

    Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. PMID:23870272

  5. Quantitative assessment of thermodynamic constraints on the solution space of genome-scale metabolic models.

    Science.gov (United States)

    Hamilton, Joshua J; Dwivedi, Vivek; Reed, Jennifer L

    2013-07-16

    Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  6. System Identification Methods for Aircraft Flight Control Development and Validation

    Science.gov (United States)

    1995-10-01

    System-identification methods compose a mathematical model, or series of models, : from measurements of inputs and outputs of dynamic systems. This paper : discusses the use of frequency-domain system-identification methods for the : development and ...

  7. IONS: Identification of Orthologs by Neighborhood and Similarity-an Automated Method to Identify Orthologs in Chromosomal Regions of Common Evolutionary Ancestry and its Application to Hemiascomycetous Yeasts.

    Science.gov (United States)

    Seret, Marie-Line; Baret, Philippe V

    2011-01-01

    Comparative sequence analysis is widely used to infer gene function and study genome evolution and requires proper ortholog identification across different genomes. We have developed a program for the Identification of Orthologs in one-to-one relationship by Neighborhood and Similarity (IONS) between closely related species. The algorithm combines two levels of evidence to determine co-ancestrality at the genome scale: sequence similarity and shared neighborhood. The method was initially designed to provide anchor points for syntenic blocks within the Génolevures project concerning nine hemiascomycetous yeasts (about 50,000 genes) and is applicable to different input databases. Comparison based on use of a Rand index shows that the results are highly consistent with the pillars of the Yeast Gene Order Browser, a manually curated database. Compared with SYNERGY, another algorithm reporting homology relationships, our method's main advantages are its automation and the absence of dataset-dependent parameters, facilitating consistent integration of newly released genomes.

  8. [Personal identification with biometric and genetic methods].

    Science.gov (United States)

    Cabanis, Emmanuel-Alain; Le Gall, Jean-Yves; Ardaillou, Raymond

    2007-11-01

    The need for personal identification is growing in many avenues of society. To "identify" a person is to establish a link between his or her observed characteristics and those previously stored in a database. To "authenticate" is to decide whether or not someone is the person he or she claims to be. These two objectives can now be achieved by analysing biometric data and genetic prints. All biometric techniques proceed in several stages: acquisition of an image or physical parameters, encoding them with a mathematical model, comparing the results of this model with those contained in the database, and calculating the error risk. These techniques must be usable worldwide and must examine specific and permanent personal data. The most widely used are facial recognition, digital prints (flexion folds and dermatoglyphs, that offer the advantage of leaving marks), and the surface and texture of the iris. Other biometric techniques analyse behaviours such as walking, signing, typing, or speaking. Implanted radio-transmitters are another means of identification. All these systems are evaluated on the basis of the same parameters, namely the false rejection rate, the false acceptance rate, and the failure-to-enrol rate. The uses of biometrics are increasing and diversifying, and now include national and international identification systems, control of access to protected sites, criminal and victim identification, and transaction security. Genetic methods can identify individuals almost infallibly, based on short tandem repeats of 2-5 nucleotides, or microsatellites. The most recent kits analyze 11-16 independent autosomal markers. Mitochondrial DNA and Y chromosome DNA can also be analyzed. These genetic tests are currently used to identify suspected criminals or their victims from biological samples, and to establish paternity. Personal identification raises many ethical questions, however, such as when to create and how to use a database while preserving personal freedom

  9. Fuel number identification method and device therefor

    International Nuclear Information System (INIS)

    Doi, Takami; Seno, Makoto; Tanaka, Keiji

    1998-01-01

    The present invention provides a method of and a device for automatically identifying the number on the upper surface of a fuel of a fuel assembly in a PWR type reactor. Namely, the number on the upper surface of the fuel assembly of the PWR is not arranged in a row, but indent letters are dispersed to predetermined positions of the surface to be indented. Accordingly, the identification of letters is difficult. In the present invention, the letters are identified by the following procedures. Procedure (1): the letters are detected while having a corner portion of the upper surface of a fuel assembly where the number is indented as characteristic points. A procedure (2): a letter region is determined to a relative position based on the characteristic points while determining indent letters having the same direction as one group. A procedure (3): a letter identification treatment is applied to the letter images in the above-mentioned letter region to identify them. A neural network is used for the letter identification treatment. (N.H.)

  10. Investigating host-pathogen behavior and their interaction using genome-scale metabolic network models.

    Science.gov (United States)

    Sadhukhan, Priyanka P; Raghunathan, Anu

    2014-01-01

    Genome Scale Metabolic Modeling methods represent one way to compute whole cell function starting from the genome sequence of an organism and contribute towards understanding and predicting the genotype-phenotype relationship. About 80 models spanning all the kingdoms of life from archaea to eukaryotes have been built till date and used to interrogate cell phenotype under varying conditions. These models have been used to not only understand the flux distribution in evolutionary conserved pathways like glycolysis and the Krebs cycle but also in applications ranging from value added product formation in Escherichia coli to predicting inborn errors of Homo sapiens metabolism. This chapter describes a protocol that delineates the process of genome scale metabolic modeling for analysing host-pathogen behavior and interaction using flux balance analysis (FBA). The steps discussed in the process include (1) reconstruction of a metabolic network from the genome sequence, (2) its representation in a precise mathematical framework, (3) its translation to a model, and (4) the analysis using linear algebra and optimization. The methods for biological interpretations of computed cell phenotypes in the context of individual host and pathogen models and their integration are also discussed.

  11. Modeling Lactococcus lactis using a genome-scale flux model

    Directory of Open Access Journals (Sweden)

    Nielsen Jens

    2005-06-01

    Full Text Available Abstract Background Genome-scale flux models are useful tools to represent and analyze microbial metabolism. In this work we reconstructed the metabolic network of the lactic acid bacteria Lactococcus lactis and developed a genome-scale flux model able to simulate and analyze network capabilities and whole-cell function under aerobic and anaerobic continuous cultures. Flux balance analysis (FBA and minimization of metabolic adjustment (MOMA were used as modeling frameworks. Results The metabolic network was reconstructed using the annotated genome sequence from L. lactis ssp. lactis IL1403 together with physiological and biochemical information. The established network comprised a total of 621 reactions and 509 metabolites, representing the overall metabolism of L. lactis. Experimental data reported in the literature was used to fit the model to phenotypic observations. Regulatory constraints had to be included to simulate certain metabolic features, such as the shift from homo to heterolactic fermentation. A minimal medium for in silico growth was identified, indicating the requirement of four amino acids in addition to a sugar. Remarkably, de novo biosynthesis of four other amino acids was observed even when all amino acids were supplied, which is in good agreement with experimental observations. Additionally, enhanced metabolic engineering strategies for improved diacetyl producing strains were designed. Conclusion The L. lactis metabolic network can now be used for a better understanding of lactococcal metabolic capabilities and potential, for the design of enhanced metabolic engineering strategies and for integration with other types of 'omic' data, to assist in finding new information on cellular organization and function.

  12. Predicting growth of the healthy infant using a genome scale metabolic model.

    Science.gov (United States)

    Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens

    2017-01-01

    An estimated 165 million children globally have stunted growth, and extensive growth data are available. Genome scale metabolic models allow the simulation of molecular flux over each metabolic enzyme, and are well adapted to analyze biological systems. We used a human genome scale metabolic model to simulate the mechanisms of growth and integrate data about breast-milk intake and composition with the infant's biomass and energy expenditure of major organs. The model predicted daily metabolic fluxes from birth to age 6 months, and accurately reproduced standard growth curves and changes in body composition. The model corroborates the finding that essential amino and fatty acids do not limit growth, but that energy is the main growth limiting factor. Disruptions to the supply and demand of energy markedly affected the predicted growth, indicating that elevated energy expenditure may be detrimental. The model was used to simulate the metabolic effect of mineral deficiencies, and showed the greatest growth reduction for deficiencies in copper, iron, and magnesium ions which affect energy production through oxidative phosphorylation. The model and simulation method were integrated to a platform and shared with the research community. The growth model constitutes another step towards the complete representation of human metabolism, and may further help improve the understanding of the mechanisms underlying stunting.

  13. Incorporating Protein Biosynthesis into the Saccharomyces cerevisiae Genome-scale Metabolic Model

    DEFF Research Database (Denmark)

    Olivares Hernandez, Roberto

    Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been construc......Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been...

  14. Toward the automated generation of genome-scale metabolic networks in the SEED.

    Science.gov (United States)

    DeJongh, Matthew; Formsma, Kevin; Boillot, Paul; Gould, John; Rycenga, Matthew; Best, Aaron

    2007-04-26

    Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis). We have implemented our tools and database within the SEED, an open-source software environment for comparative genome annotation and analysis. Our method sets the

  15. Toward the automated generation of genome-scale metabolic networks in the SEED

    Directory of Open Access Journals (Sweden)

    Gould John

    2007-04-01

    Full Text Available Abstract Background Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. Results We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis. We have implemented our tools and database within the SEED, an open-source software environment for comparative

  16. [A accurate identification method for Chinese materia medica--systematic identification of Chinese materia medica].

    Science.gov (United States)

    Wang, Xue-Yong; Liao, Cai-Li; Liu, Si-Qi; Liu, Chun-Sheng; Shao, Ai-Juan; Huang, Lu-Qi

    2013-05-01

    This paper put forward a more accurate identification method for identification of Chinese materia medica (CMM), the systematic identification of Chinese materia medica (SICMM) , which might solve difficulties in CMM identification used the ordinary traditional ways. Concepts, mechanisms and methods of SICMM were systematically introduced and possibility was proved by experiments. The establishment of SICMM will solve problems in identification of Chinese materia medica not only in phenotypic characters like the mnorphous, microstructure, chemical constituents, but also further discovery evolution and classification of species, subspecies and population in medical plants. The establishment of SICMM will improve the development of identification of CMM and create a more extensive study space.

  17. Constraining Genome-Scale Models to Represent the Bow Tie Structure of Metabolism for 13C Metabolic Flux Analysis

    Directory of Open Access Journals (Sweden)

    Tyler W. H. Backman

    2018-01-01

    Full Text Available Determination of internal metabolic fluxes is crucial for fundamental and applied biology because they map how carbon and electrons flow through metabolism to enable cell function. 13 C Metabolic Flux Analysis ( 13 C MFA and Two-Scale 13 C Metabolic Flux Analysis (2S- 13 C MFA are two techniques used to determine such fluxes. Both operate on the simplifying approximation that metabolic flux from peripheral metabolism into central “core” carbon metabolism is minimal, and can be omitted when modeling isotopic labeling in core metabolism. The validity of this “two-scale” or “bow tie” approximation is supported both by the ability to accurately model experimental isotopic labeling data, and by experimentally verified metabolic engineering predictions using these methods. However, the boundaries of core metabolism that satisfy this approximation can vary across species, and across cell culture conditions. Here, we present a set of algorithms that (1 systematically calculate flux bounds for any specified “core” of a genome-scale model so as to satisfy the bow tie approximation and (2 automatically identify an updated set of core reactions that can satisfy this approximation more efficiently. First, we leverage linear programming to simultaneously identify the lowest fluxes from peripheral metabolism into core metabolism compatible with the observed growth rate and extracellular metabolite exchange fluxes. Second, we use Simulated Annealing to identify an updated set of core reactions that allow for a minimum of fluxes into core metabolism to satisfy these experimental constraints. Together, these methods accelerate and automate the identification of a biologically reasonable set of core reactions for use with 13 C MFA or 2S- 13 C MFA, as well as provide for a substantially lower set of flux bounds for fluxes into the core as compared with previous methods. We provide an open source Python implementation of these algorithms at https://github.com/JBEI/limitfluxtocore.

  18. Genome-scale modeling using flux ratio constraints to enable metabolic engineering of clostridial metabolism in silico.

    Science.gov (United States)

    McAnulty, Michael J; Yen, Jiun Y; Freedman, Benjamin G; Senger, Ryan S

    2012-05-14

    Genome-scale metabolic networks and flux models are an effective platform for linking an organism genotype to its phenotype. However, few modeling approaches offer predictive capabilities to evaluate potential metabolic engineering strategies in silico. A new method called "flux balance analysis with flux ratios (FBrAtio)" was developed in this research and applied to a new genome-scale model of Clostridium acetobutylicum ATCC 824 (iCAC490) that contains 707 metabolites and 794 reactions. FBrAtio was used to model wild-type metabolism and metabolically engineered strains of C. acetobutylicum where only flux ratio constraints and thermodynamic reversibility of reactions were required. The FBrAtio approach allowed solutions to be found through standard linear programming. Five flux ratio constraints were required to achieve a qualitative picture of wild-type metabolism for C. acetobutylicum for the production of: (i) acetate, (ii) lactate, (iii) butyrate, (iv) acetone, (v) butanol, (vi) ethanol, (vii) CO2 and (viii) H2. Results of this simulation study coincide with published experimental results and show the knockdown of the acetoacetyl-CoA transferase increases butanol to acetone selectivity, while the simultaneous over-expression of the aldehyde/alcohol dehydrogenase greatly increases ethanol production. FBrAtio is a promising new method for constraining genome-scale models using internal flux ratios. The method was effective for modeling wild-type and engineered strains of C. acetobutylicum.

  19. An Efficient Vital Area Identification Method

    International Nuclear Information System (INIS)

    Jung, Woo Sik

    2017-01-01

    A new Vital Area Identification (VAI) method was developed in this study for minimizing the burden of VAI procedure. It was accomplished by performing simplification of sabotage event trees or Probabilistic Safety Assessment (PSA) event trees at the very first stage of VAI procedure. Target sets and prevention sets are calculated from the sabotage fault tree. The rooms in the shortest (most economical) prevention set are selected and protected as vital areas. All physical protection is emphasized to protect these vital areas. All rooms in the protected area, the sabotage of which could lead to core damage, should be incorporated into sabotage fault tree. So, sabotage fault tree development is a very difficult task that requires high engineering costs. IAEA published INFCIRC/225/Rev.5 in 2011 which includes principal international guidelines for the physical protection of nuclear material and nuclear installations. A new efficient VAI method was developed and demonstrated in this study. Since this method drastically reduces VAI problem size, it provides very quick and economical VAI procedure. A consistent and integrated VAI procedure had been developed by taking advantage of PSA results, and more efficient VAI method was further developed in this study by inserting PSA event tree simplification at the initial stage of VAI procedure.

  20. [Bacterial identification methods in the microbiology laboratory].

    Science.gov (United States)

    Bou, Germán; Fernández-Olmos, Ana; García, Celia; Sáez-Nieto, Juan Antonio; Valdezate, Sylvia

    2011-10-01

    In order to identify the agent responsible of the infectious process and understanding the pathogenic/pathological implications, clinical course, and to implement an effective antimicrobial therapy, a mainstay in the practice of clinical microbiology is the allocation of species to a microbial isolation. In daily routine practice microbiology laboratory phenotypic techniques are applied to achieve this goal. However, they have some limitations that are seen more clearly for some kinds of microorganism. Molecular methods can circumvent some of these limitations, although its implementation is not universal. This is due to higher costs and the level of expertise required for thei implementation, so molecular methods are often centralized in reference laboratories and centers. Recently, proteomics-based methods made an important breakthrough in the field of diagnostic microbiology and will undoubtedly have a major impact on the future organization of the microbiology services. This paper is a short review of the most noteworthy aspects of the three bacterial identification methods described above used in microbiology laboratories. Copyright © 2011 Elsevier España, S.L. All rights reserved.

  1. Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

    Energy Technology Data Exchange (ETDEWEB)

    Seaver, Samuel M. D.; Bradbury, Louis M. T.; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

    2015-03-10

    There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.

  2. Targeted and genome-scale methylomics reveals gene body signatures in human cell lines

    Science.gov (United States)

    Ball, Madeleine Price; Li, Jin Billy; Gao, Yuan; Lee, Je-Hyuk; LeProust, Emily; Park, In-Hyun; Xie, Bin; Daley, George Q.; Church, George M.

    2012-01-01

    Cytosine methylation, an epigenetic modification of DNA, is a target of growing interest for developing high throughput profiling technologies. Here we introduce two new, complementary techniques for cytosine methylation profiling utilizing next generation sequencing technology: bisulfite padlock probes (BSPPs) and methyl sensitive cut counting (MSCC). In the first method, we designed a set of ~10,000 BSPPs distributed over the ENCODE pilot project regions to take advantage of existing expression and chromatin immunoprecipitation data. We observed a pattern of low promoter methylation coupled with high gene body methylation in highly expressed genes. Using the second method, MSCC, we gathered genome-scale data for 1.4 million HpaII sites and confirmed that gene body methylation in highly expressed genes is a consistent phenomenon over the entire genome. Our observations highlight the usefulness of techniques which are not inherently or intentionally biased in favor of only profiling particular subsets like CpG islands or promoter regions. PMID:19329998

  3. In Silico Genome-Scale Reconstruction and Validation of the Corynebacterium glutamicum Metabolic Network

    DEFF Research Database (Denmark)

    Kjeldsen, Kjeld Raunkjær; Nielsen, J.

    2009-01-01

    A genome-scale metabolic model of the Gram-positive bacteria Corynebacterium glutamicum ATCC 13032 was constructed comprising 446 reactions and 411 metabolite, based on the annotated genome and available biochemical information. The network was analyzed using constraint based methods. The model...... was extensively validated against published flux data, and flux distribution values were found to correlate well between simulations and experiments. The split pathway of the lysine synthesis pathway of C. glutamicum was investigated, and it was found that the direct dehydrogenase variant gave a higher lysine...... yield than the alternative succinyl pathway at high lysine production rates. The NADPH demand of the network was not found to be critical for lysine production until lysine yields exceeded 55% (mmol lysine (mmol glucose)(-1)). The model was validated during growth on the organic acids acetate...

  4. Reconstruction of genome-scale human metabolic models using omics data

    DEFF Research Database (Denmark)

    Ryu, Jae Yong; Kim, Hyun Uk; Lee, Sang Yup

    2015-01-01

    used to describe metabolic phenotypes of healthy and diseased human tissues and cells, and to predict therapeutic targets. Here we review recent trends in genome-scale human metabolic modeling, including various generic and tissue/cell type-specific human metabolic models developed to date, and methods......, databases and platforms used to construct them. For generic human metabolic models, we pay attention to Recon 2 and HMR 2.0 with emphasis on data sources used to construct them. Draft and high-quality tissue/cell type-specific human metabolic models have been generated using these generic human metabolic...... refined through gap filling, reaction directionality assignment and the subcellular localization of metabolic reactions. We review relevant tools for this model refinement procedure as well. Finally, we suggest the direction of further studies on reconstructing an improved human metabolic model....

  5. Portraits of Benvenuto Cellini and Anthropological Methods of Their Identification

    Science.gov (United States)

    Nasobin, Oleg

    2016-01-01

    Modern methods of biometric identification are increasingly applied in order to attribute works of art. They are based on developments in the 19th century anthropological methods. So, this article describes how the successional anthropological methods were applied for the identification of Benvenuto Cellini's portraits. Objective comparison of…

  6. Genome scale metabolic network reconstruction of Spirochaeta cellobiosiphila

    Directory of Open Access Journals (Sweden)

    Bharat Manna

    2017-10-01

    Full Text Available Substantial rise in the global energy demand is one of the biggest challenges in this century. Environmental pollution due to rapid depletion of the fossil fuel resources and its alarming impact on the climate change and Global Warming have motivated researchers to look for non-petroleum-based sustainable, eco-friendly, renewable, low-cost energy alternatives, such as biofuel. Lignocellulosic biomass is one of the most promising bio-resources with huge potential to contribute to this worldwide energy demand. However, the complex organization of the Cellulose, Hemicellulose and Lignin in the Lignocellulosic biomass requires extensive pre-treatment and enzymatic hydrolysis followed by fermentation, raising overall production cost of biofuel. This encourages researchers to design cost-effective approaches for the production of second generation biofuels. The products from enzymatic hydrolysis of cellulose are mostly glucose monomer or cellobiose unit that are subjected to fermentation. Spirochaeta genus is a well-known group of obligate or facultative anaerobes, living primarily on carbohydrate metabolism. Spirochaeta cellobiosiphila sp. is a facultative anaerobe under this genus, which uses a variety of monosaccharides and disaccharides as energy sources. However, most rapid growth occurs on cellobiose and fermentation yields significant amount of ethanol, acetate, CO2, H2 and small amounts of formate. It is predicted to be promising microbial machinery for industrial fermentation processes for biofuel production. The metabolic pathways that govern cellobiose metabolism in Spirochaeta cellobiosiphila are yet to be explored. The function annotation of the genome sequence of Spirochaeta cellobiosiphila is in progress. In this work we aim to map all the metabolic activities for reconstruction of genome-scale metabolic model of Spirochaeta cellobiosiphila.

  7. Communications device identification methods, communications methods, wireless communications readers, wireless communications systems, and articles of manufacture

    Science.gov (United States)

    Steele, Kerry D [Kennewick, WA; Anderson, Gordon A [Benton City, WA; Gilbert, Ronald W [Morgan Hill, CA

    2011-02-01

    Communications device identification methods, communications methods, wireless communications readers, wireless communications systems, and articles of manufacture are described. In one aspect, a communications device identification method includes providing identification information regarding a group of wireless identification devices within a wireless communications range of a reader, using the provided identification information, selecting one of a plurality of different search procedures for identifying unidentified ones of the wireless identification devices within the wireless communications range, and identifying at least some of the unidentified ones of the wireless identification devices using the selected one of the search procedures.

  8. Environmental versatility promotes modularity in genome-scale metabolic networks.

    Science.gov (United States)

    Samal, Areejit; Wagner, Andreas; Martin, Olivier C

    2011-08-24

    The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chemical environments. For such networks, we define a network module as a maximal set of reactions that are fully coupled, i.e., whose fluxes can only vary in fixed proportions. This definition overcomes limitations of purely graph based analyses of metabolism by exploiting the functional links between reactions. We call a metabolic network viable in a given chemical environment if it can synthesize all of an organism's biomass compounds from nutrients in this environment. An organism's metabolism is highly versatile if it can sustain life in many different chemical environments. We here ask whether versatility affects the modularity of metabolic networks. Using recently developed techniques to randomly sample large numbers of viable metabolic networks from a vast space of metabolic networks, we use flux balance analysis to study in silico metabolic networks that differ in their versatility. We find that highly versatile networks are also highly modular. They contain more modules and more reactions that are organized into modules. Most or all reactions in a module are associated with the same biochemical pathways. Modules that arise in highly versatile networks generally involve reactions that process nutrients or closely related chemicals. We also observe that the metabolism of E. coli is significantly more modular than even our most versatile networks. Our work shows that modularity in metabolic networks can be a by-product of functional constraints, e.g., the need to sustain life in multiple

  9. Environmental versatility promotes modularity in genome-scale metabolic networks

    Directory of Open Access Journals (Sweden)

    Wagner Andreas

    2011-08-01

    Full Text Available Abstract Background The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chemical environments. For such networks, we define a network module as a maximal set of reactions that are fully coupled, i.e., whose fluxes can only vary in fixed proportions. This definition overcomes limitations of purely graph based analyses of metabolism by exploiting the functional links between reactions. We call a metabolic network viable in a given chemical environment if it can synthesize all of an organism's biomass compounds from nutrients in this environment. An organism's metabolism is highly versatile if it can sustain life in many different chemical environments. We here ask whether versatility affects the modularity of metabolic networks. Results Using recently developed techniques to randomly sample large numbers of viable metabolic networks from a vast space of metabolic networks, we use flux balance analysis to study in silico metabolic networks that differ in their versatility. We find that highly versatile networks are also highly modular. They contain more modules and more reactions that are organized into modules. Most or all reactions in a module are associated with the same biochemical pathways. Modules that arise in highly versatile networks generally involve reactions that process nutrients or closely related chemicals. We also observe that the metabolism of E. coli is significantly more modular than even our most versatile networks. Conclusions Our work shows that modularity in metabolic networks can be a by-product of functional

  10. Metabolite coupling in genome-scale metabolic networks

    Directory of Open Access Journals (Sweden)

    Palsson Bernhard Ø

    2006-03-01

    metabolites. Conclusion The coupling of metabolites is an important topological property of metabolic networks. By computing coupling quantitatively for the first time in genome-scale metabolic networks, we provide insight into the basic structure of these networks.

  11. Signal trend identification with fuzzy methods

    International Nuclear Information System (INIS)

    Reifman, J.; Tsoukalas, L. H.; Wang, X.; Wei, T. Y. C.

    1999-01-01

    A fuzzy-logic-based methodology for on-line signal trend identification is introduced. Although signal trend identification is complicated by the presence of noise, fuzzy logic can help capture important features of on-line signals and classify incoming power plant signals into increasing, decreasing and steady-state trend categories. In order to verify the methodology, a code named PROTREN is developed and tested using plant data. The results indicate that the code is capable of detecting transients accurately, identifying trends reliably, and not misinterpreting a steady-state signal as a transient one

  12. Comparison of identification methods for oral asaccharolytic Eubacterium species.

    Science.gov (United States)

    Wade, W G; Slayne, M A; Aldred, M J

    1990-12-01

    Thirty one strains of oral, asaccharolytic Eubacterium spp. and the type strains of E. brachy, E. nodatum and E. timidum were subjected to three identification techniques--protein-profile analysis, determination of metabolic end-products, and the API ATB32A identification kit. Five clusters were obtained from numerical analysis of protein profiles and excellent correlations were seen with the other two methods. Protein profiles alone allowed unequivocal identification.

  13. Comparison of System Identification Methods using Ambient Bridge Test Data

    DEFF Research Database (Denmark)

    Andersen, P.; Brincker, Rune; Peeters, B.

    1999-01-01

    In this paper the performance of four different system identification methods is compared using operational data obtained from an ambient vibration test of the Swiss Z24 highway bridge. The four methods are the frequency domain based peak-picking methods, the polyreference LSCE method, the stocha......In this paper the performance of four different system identification methods is compared using operational data obtained from an ambient vibration test of the Swiss Z24 highway bridge. The four methods are the frequency domain based peak-picking methods, the polyreference LSCE method...

  14. A virtual closed loop method for closed loop identification

    NARCIS (Netherlands)

    Agüero, J.C.; Goodwin, G.C.; Hof, Van den P.M.J.

    2011-01-01

    Indirect methods for the identification of linear plant models on the basis of closed loop data are based on the use of (reconstructed) input signals that are uncorrelated with the noise. This generally requires exact (linear) controller knowledge. On the other hand, direct identification requires

  15. A Bayesian statistical method for particle identification in shower counters

    International Nuclear Information System (INIS)

    Takashimizu, N.; Kimura, A.; Shibata, A.; Sasaki, T.

    2004-01-01

    We report an attempt on identifying particles using a Bayesian statistical method. We have developed the mathematical model and software for this purpose. We tried to identify electrons and charged pions in shower counters using this method. We designed an ideal shower counter and studied the efficiency of identification using Monte Carlo simulation based on Geant4. Without having any other information, e.g. charges of particles which are given by tracking detectors, we have achieved 95% identifications of both particles

  16. Genome-scale reconstruction of the metabolic network in Yersinia pestis, strain 91001

    Energy Technology Data Exchange (ETDEWEB)

    Navid, A; Almaas, E

    2009-01-13

    The gram-negative bacterium Yersinia pestis, the aetiological agent of bubonic plague, is one the deadliest pathogens known to man. Despite its historical reputation, plague is a modern disease which annually afflicts thousands of people. Public safety considerations greatly limit clinical experimentation on this organism and thus development of theoretical tools to analyze the capabilities of this pathogen is of utmost importance. Here, we report the first genome-scale metabolic model of Yersinia pestis biovar Mediaevalis based both on its recently annotated genome, and physiological and biochemical data from literature. Our model demonstrates excellent agreement with Y. pestis known metabolic needs and capabilities. Since Y. pestis is a meiotrophic organism, we have developed CryptFind, a systematic approach to identify all candidate cryptic genes responsible for known and theoretical meiotrophic phenomena. In addition to uncovering every known cryptic gene for Y. pestis, our analysis of the rhamnose fermentation pathway suggests that betB is the responsible cryptic gene. Despite all of our medical advances, we still do not have a vaccine for bubonic plague. Recent discoveries of antibiotic resistant strains of Yersinia pestis coupled with the threat of plague being used as a bioterrorism weapon compel us to develop new tools for studying the physiology of this deadly pathogen. Using our theoretical model, we can study the cell's phenotypic behavior under different circumstances and identify metabolic weaknesses which may be harnessed for the development of therapeutics. Additionally, the automatic identification of cryptic genes expands the usage of genomic data for pharmaceutical purposes.

  17. Genome-scale metabolic analysis of Clostridium thermocellum for bioethanol production

    Directory of Open Access Journals (Sweden)

    Brooks J Paul

    2010-03-01

    Full Text Available Abstract Background Microorganisms possess diverse metabolic capabilities that can potentially be leveraged for efficient production of biofuels. Clostridium thermocellum (ATCC 27405 is a thermophilic anaerobe that is both cellulolytic and ethanologenic, meaning that it can directly use the plant sugar, cellulose, and biochemically convert it to ethanol. A major challenge in using microorganisms for chemical production is the need to modify the organism to increase production efficiency. The process of properly engineering an organism is typically arduous. Results Here we present a genome-scale model of C. thermocellum metabolism, iSR432, for the purpose of establishing a computational tool to study the metabolic network of C. thermocellum and facilitate efforts to engineer C. thermocellum for biofuel production. The model consists of 577 reactions involving 525 intracellular metabolites, 432 genes, and a proteomic-based representation of a cellulosome. The process of constructing this metabolic model led to suggested annotation refinements for 27 genes and identification of areas of metabolism requiring further study. The accuracy of the iSR432 model was tested using experimental growth and by-product secretion data for growth on cellobiose and fructose. Analysis using this model captures the relationship between the reduction-oxidation state of the cell and ethanol secretion and allowed for prediction of gene deletions and environmental conditions that would increase ethanol production. Conclusions By incorporating genomic sequence data, network topology, and experimental measurements of enzyme activities and metabolite fluxes, we have generated a model that is reasonably accurate at predicting the cellular phenotype of C. thermocellum and establish a strong foundation for rational strain design. In addition, we are able to draw some important conclusions regarding the underlying metabolic mechanisms for observed behaviors of C. thermocellum

  18. IRiS: construction of ARG networks at genomic scales.

    Science.gov (United States)

    Javed, Asif; Pybus, Marc; Melé, Marta; Utro, Filippo; Bertranpetit, Jaume; Calafell, Francesc; Parida, Laxmi

    2011-09-01

    Given a set of extant haplotypes IRiS first detects high confidence recombination events in their shared genealogy. Next using the local sequence topology defined by each detected event, it integrates these recombinations into an ancestral recombination graph. While the current system has been calibrated for human population data, it is easily extendible to other species as well. IRiS (Identification of Recombinations in Sequences) binary files are available for non-commercial use in both Linux and Microsoft Windows, 32 and 64 bit environments from https://researcher.ibm.com/researcher/view_project.php?id = 2303 parida@us.ibm.com.

  19. Genome-scale modelling of microbial metabolism with temporal and spatial resolution.

    Science.gov (United States)

    Henson, Michael A

    2015-12-01

    Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated. © 2015 Authors; published by Portland Press Limited.

  20. A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

    Science.gov (United States)

    Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien

    2017-01-01

    Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.

  1. Identifying all moiety conservation laws in genome-scale metabolic networks.

    Science.gov (United States)

    De Martino, Andrea; De Martino, Daniele; Mulet, Roberto; Pagnani, Andrea

    2014-01-01

    The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell's metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative integer solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation.

  2. Identifying all moiety conservation laws in genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Andrea De Martino

    Full Text Available The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell's metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative integer solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation.

  3. Computational solution to automatically map metabolite libraries in the context of genome scale metabolic networks

    Directory of Open Access Journals (Sweden)

    Benjamin eMerlet

    2016-02-01

    Full Text Available This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc and flat file formats (SBML and Matlab files. We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics and Glasgow Polyomics on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks.In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks.In order to achieve this goal we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities.

  4. Deriving metabolic engineering strategies from genome-scale modeling with flux ratio constraints.

    Science.gov (United States)

    Yen, Jiun Y; Nazem-Bokaee, Hadi; Freedman, Benjamin G; Athamneh, Ahmad I M; Senger, Ryan S

    2013-05-01

    Optimized production of bio-based fuels and chemicals from microbial cell factories is a central goal of systems metabolic engineering. To achieve this goal, a new computational method of using flux balance analysis with flux ratios (FBrAtio) was further developed in this research and applied to five case studies to evaluate and design metabolic engineering strategies. The approach was implemented using publicly available genome-scale metabolic flux models. Synthetic pathways were added to these models along with flux ratio constraints by FBrAtio to achieve increased (i) cellulose production from Arabidopsis thaliana; (ii) isobutanol production from Saccharomyces cerevisiae; (iii) acetone production from Synechocystis sp. PCC6803; (iv) H2 production from Escherichia coli MG1655; and (v) isopropanol, butanol, and ethanol (IBE) production from engineered Clostridium acetobutylicum. The FBrAtio approach was applied to each case to simulate a metabolic engineering strategy already implemented experimentally, and flux ratios were continually adjusted to find (i) the end-limit of increased production using the existing strategy, (ii) new potential strategies to increase production, and (iii) the impact of these metabolic engineering strategies on product yield and culture growth. The FBrAtio approach has the potential to design "fine-tuned" metabolic engineering strategies in silico that can be implemented directly with available genomic tools. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

    Directory of Open Access Journals (Sweden)

    Marko Budinich

    Full Text Available Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA and multi-objective flux variability analysis (MO-FVA. Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity that take place at the ecosystem scale.

  6. A Computational Solution to Automatically Map Metabolite Libraries in the Context of Genome Scale Metabolic Networks.

    Science.gov (United States)

    Merlet, Benjamin; Paulhe, Nils; Vinson, Florence; Frainay, Clément; Chazalviel, Maxime; Poupin, Nathalie; Gloaguen, Yoann; Giacomoni, Franck; Jourdan, Fabien

    2016-01-01

    This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc) and flat file formats (SBML and Matlab files). We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics) and Glasgow Polyomics (GP) on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks. In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks. In order to achieve this goal, we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities.

  7. Genome-scale metabolic models applied to human health and disease.

    Science.gov (United States)

    Cook, Daniel J; Nielsen, Jens

    2017-11-01

    Advances in genome sequencing, high throughput measurement of gene and protein expression levels, data accessibility, and computational power have allowed genome-scale metabolic models (GEMs) to become a useful tool for understanding metabolic alterations associated with many different diseases. Despite the proven utility of GEMs, researchers confront multiple challenges in the use of GEMs, their application to human health and disease, and their construction and simulation in an organ-specific and disease-specific manner. Several approaches that researchers are taking to address these challenges include using proteomic and transcriptomic-informed methods to build GEMs for individual organs, diseases, and patients and using constraints on model behavior during simulation to match observed metabolic fluxes. We review the challenges facing researchers in the use of GEMs, review the approaches used to address these challenges, and describe advances that are on the horizon and could lead to a better understanding of human metabolism. WIREs Syst Biol Med 2017, 9:e1393. doi: 10.1002/wsbm.1393 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

  8. Survey of protein–DNA interactions in Aspergillus oryzae on a genomic scale

    Science.gov (United States)

    Wang, Chao; Lv, Yangyong; Wang, Bin; Yin, Chao; Lin, Ying; Pan, Li

    2015-01-01

    The genome-scale delineation of in vivo protein–DNA interactions is key to understanding genome function. Only ∼5% of transcription factors (TFs) in the Aspergillus genus have been identified using traditional methods. Although the Aspergillus oryzae genome contains >600 TFs, knowledge of the in vivo genome-wide TF-binding sites (TFBSs) in aspergilli remains limited because of the lack of high-quality antibodies. We investigated the landscape of in vivo protein–DNA interactions across the A. oryzae genome through coupling the DNase I digestion of intact nuclei with massively parallel sequencing and the analysis of cleavage patterns in protein–DNA interactions at single-nucleotide resolution. The resulting map identified overrepresented de novo TF-binding motifs from genomic footprints, and provided the detailed chromatin remodeling patterns and the distribution of digital footprints near transcription start sites. The TFBSs of 19 known Aspergillus TFs were also identified based on DNase I digestion data surrounding potential binding sites in conjunction with TF binding specificity information. We observed that the cleavage patterns of TFBSs were dependent on the orientation of TF motifs and independent of strand orientation, consistent with the DNA shape features of binding motifs with flanking sequences. PMID:25883143

  9. The RAVEN Toolbox and Its Use for Generating a Genome-scale Metabolic Model for Penicillium chrysogenum

    Science.gov (United States)

    Agren, Rasmus; Liu, Liming; Shoaie, Saeed; Vongsangnak, Wanwipa; Nookaew, Intawat; Nielsen, Jens

    2013-01-01

    We present the RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox: a software suite that allows for semi-automated reconstruction of genome-scale models. It makes use of published models and/or the KEGG database, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology. The RAVEN Toolbox workflow was applied in order to reconstruct a genome-scale metabolic model for the important microbial cell factory Penicillium chrysogenum Wisconsin54-1255. The model was validated in a bibliomic study of in total 440 references, and it comprises 1471 unique biochemical reactions and 1006 ORFs. It was then used to study the roles of ATP and NADPH in the biosynthesis of penicillin, and to identify potential metabolic engineering targets for maximization of penicillin production. PMID:23555215

  10. Genome-scale metabolic model of the fission yeast Schizosaccharomyces pombe and the reconciliation of in silico/in vivo mutant growth

    Science.gov (United States)

    2012-01-01

    Background Over the last decade, the genome-scale metabolic models have been playing increasingly important roles in elucidating metabolic characteristics of biological systems for a wide range of applications including, but not limited to, system-wide identification of drug targets and production of high value biochemical compounds. However, these genome-scale metabolic models must be able to first predict known in vivo phenotypes before it is applied towards these applications with high confidence. One benchmark for measuring the in silico capability in predicting in vivo phenotypes is the use of single-gene mutant libraries to measure the accuracy of knockout simulations in predicting mutant growth phenotypes. Results Here we employed a systematic and iterative process, designated as Reconciling In silico/in vivo mutaNt Growth (RING), to settle discrepancies between in silico prediction and in vivo observations to a newly reconstructed genome-scale metabolic model of the fission yeast, Schizosaccharomyces pombe, SpoMBEL1693. The predictive capabilities of the genome-scale metabolic model in predicting single-gene mutant growth phenotypes were measured against the single-gene mutant library of S. pombe. The use of RING resulted in improving the overall predictive capability of SpoMBEL1693 by 21.5%, from 61.2% to 82.7% (92.5% of the negative predictions matched the observed growth phenotype and 79.7% the positive predictions matched the observed growth phenotype). Conclusion This study presents validation and refinement of a newly reconstructed metabolic model of the yeast S. pombe, through improving the metabolic model’s predictive capabilities by reconciling the in silico predicted growth phenotypes of single-gene knockout mutants, with experimental in vivo growth data. PMID:22631437

  11. Large deviations and queueing networks: Methods for rate function identification

    OpenAIRE

    Atar, Rami; Dupuis, Paul

    1999-01-01

    This paper considers the problem of rate function identification for multidimensional queueing models with feedback. A set of techniques are introduced which allow this identification when the model possesses certain structural properties. The main tools used are representation formulas for exponential integrals, weak convergence methods, and the regularity properties of associated Skorokhod Problems. Two examples are treated as special cases of the general theory: the classical Jackson netwo...

  12. Genome-scale metabolic models as platforms for strain design and biological discovery.

    Science.gov (United States)

    Mienda, Bashir Sajo

    2017-07-01

    Genome-scale metabolic models (GEMs) have been developed and used in guiding systems' metabolic engineering strategies for strain design and development. This strategy has been used in fermentative production of bio-based industrial chemicals and fuels from alternative carbon sources. However, computer-aided hypotheses building using established algorithms and software platforms for biological discovery can be integrated into the pipeline for strain design strategy to create superior strains of microorganisms for targeted biosynthetic goals. Here, I described an integrated workflow strategy using GEMs for strain design and biological discovery. Specific case studies of strain design and biological discovery using Escherichia coli genome-scale model are presented and discussed. The integrated workflow presented herein, when applied carefully would help guide future design strategies for high-performance microbial strains that have existing and forthcoming genome-scale metabolic models.

  13. Investigating methods of stream planform identification

    Science.gov (United States)

    Lohberg, M. M.; Lusk, K.; Miller, D.; Stonedahl, F.; Stonedahl, S. H.

    2013-12-01

    Stream planforms are used to map scientific measurements, estimate volumetric discharge, and model stream flow. Changes in these planforms can be used to quantify erosion and water level fluctuations. This research investigated five cost-effective methods of identifying stream planforms: (1) consumer-grade digital camera GPS (2) multi-view stereo 3D scene reconstruction (using Microsoft Photosynth (TM)) (3) a cross-sectional measurement approach (4) a triangulation-based measurement approach and (5) the 'square method' - a novel photogrammetric procedure which involved floating a large wooden square in the stream, photographing the square and banks from numerous angles and then using the square to correct for perspective and extract the outline (using custom post-processing software). Data for each of the five methods was collected at Blackhawk Creek in Davenport, Iowa. Additionally we placed 30 control points near the banks of the stream and measured 88 lengths between these control points. We measured or calculated the locations of these control points with each of our five methods and calculated the average percent error associated with each method using the predicted control point locations. The effectiveness of each method was evaluated in terms of accuracy, affordability, environmental intrusiveness, and ease of use. The camera equipped with GPS proved to be a very ineffective method due to an extremely high level of error, 289%. The 3D point cloud extracted from Photosynth was missing markers for many of the control points, so the error calculation (which yielded 11.7%) could only be based on five of the 88 lengths and is thus highly uncertain. The two non-camera methods (cross-sectional and triangulation measurements) resulted in low percent error (2.04% and 1.31% respectively) relative to the control point lengths, but these methods were very time consuming, exhausting, and only provided low resolution outlines. High resolution data collection would

  14. Construction of a Genome-Scale Metabolic Model of Arthrospira platensis NIES-39 and Metabolic Design for Cyanobacterial Bioproduction.

    Directory of Open Access Journals (Sweden)

    Katsunori Yoshikawa

    Full Text Available Arthrospira (Spirulina platensis is a promising feedstock and host strain for bioproduction because of its high accumulation of glycogen and superior characteristics for industrial production. Metabolic simulation using a genome-scale metabolic model and flux balance analysis is a powerful method that can be used to design metabolic engineering strategies for the improvement of target molecule production. In this study, we constructed a genome-scale metabolic model of A. platensis NIES-39 including 746 metabolic reactions and 673 metabolites, and developed novel strategies to improve the production of valuable metabolites, such as glycogen and ethanol. The simulation results obtained using the metabolic model showed high consistency with experimental results for growth rates under several trophic conditions and growth capabilities on various organic substrates. The metabolic model was further applied to design a metabolic network to improve the autotrophic production of glycogen and ethanol. Decreased flux of reactions related to the TCA cycle and phosphoenolpyruvate reaction were found to improve glycogen production. Furthermore, in silico knockout simulation indicated that deletion of genes related to the respiratory chain, such as NAD(PH dehydrogenase and cytochrome-c oxidase, could enhance ethanol production by using ammonium as a nitrogen source.

  15. SLD Identification: A Survey of Methods Used by School Psychologists

    Science.gov (United States)

    Watson, Michael D., Jr.; Simon, Joan B.; Nunnley, Lenora

    2016-01-01

    IDEA 2004 opened the door for states, and in some cases districts, to choose among three different methods for identifying children with Specific Learning Disabilities (SLDs). This study provides an in-depth look at SLD identification practices in a state that allows school psychologists to use any of the three methods. Eighty-four school…

  16. A identification system for chemical warfare agents with PGNAA method

    International Nuclear Information System (INIS)

    Wang Bairong; Yin Guanghua; Yang Zhongping

    2006-01-01

    The principle and the experimental commanding of Chemical warfare Agents Identification with PGNAA method are discussed in this paper. The choosing of Detector, neutron source and the data processing method are detailed. Finally, a set of experimental instruments composed of Cf-232 and BGO detector is developed based on the theory discussed above. (authors)

  17. Identification system for chemical warfare agents with PGNAA method

    International Nuclear Information System (INIS)

    Wang Bairong; Yin Guanghua; Yang Zhongpin

    2007-01-01

    The principle and the experimental commanding of Chemical warfare Agents Identification with PGNAA method are discussed in this paper. The choosing of detector, neutron source and the data processing method are detailed. Finally, a set of experimental instruments composed of Cf-232 and BGO detector is developed based on this theory discussed above. (authors)

  18. Methodes for identification of specific language impairment

    Directory of Open Access Journals (Sweden)

    Toktam Maleki Shahmahmood

    2014-06-01

    Full Text Available Background and Aim: Specific language impiarment (SLI is one of the most prevalent developmental language disorders its diagnosis is a problematic issue among researchers and clinicians because of the heterogeneity of language profiles in the affected population and overlapping with other developmental language disorders. The aim of this study was to review the suggested diagnostic criteria for this disorder, controversies about these criteria and identify the most accurate diagnostic methods.Methods: Published article from 1980 to 2012 in bibliographic and publisher databases including Pubmed, Google scholar, Cochran library, Web of Science, ProQuest, Springer, Oxford, Science direct, Ovid, Iran Medex and Magiran about the diagnostic methods for discriminating preschoool children with specific language impiarment from normal developing children were reviewd in this article. These keywords were used for research: “specific language impairment”, “SLI”, “diagnosis or identification”, “standardized tests”, and “tests for language development”.Conclusion: The results of this study show inspite of agreement of researchers and clinicians about exclusionary criteria as one basic part of the diagnosis of specific language impiarment , there is no consensus about the other part, inclusionary criteria. Different studies used different inclusionary criteria which can be divided to categories of clincal judgment, discrepancy-based criteria, standardized testing, clinical markers and markers from spontaneous speech samples. Advantages, disadvantages, and clinical applicability of each diagnostic method are discussed in this article.

  19. Estimating phylogenetic trees from genome-scale data.

    Science.gov (United States)

    Liu, Liang; Xi, Zhenxiang; Wu, Shaoyuan; Davis, Charles C; Edwards, Scott V

    2015-12-01

    The heterogeneity of signals in the genomes of diverse organisms poses challenges for traditional phylogenetic analysis. Phylogenetic methods known as "species tree" methods have been proposed to directly address one important source of gene tree heterogeneity, namely the incomplete lineage sorting that occurs when evolving lineages radiate rapidly, resulting in a diversity of gene trees from a single underlying species tree. Here we review theory and empirical examples that help clarify conflicts between species tree and concatenation methods, and misconceptions in the literature about the performance of species tree methods. Considering concatenation as a special case of the multispecies coalescent model helps explain differences in the behavior of the two methods on phylogenomic data sets. Recent work suggests that species tree methods are more robust than concatenation approaches to some of the classic challenges of phylogenetic analysis, including rapidly evolving sites in DNA sequences and long-branch attraction. We show that approaches, such as binning, designed to augment the signal in species tree analyses can distort the distribution of gene trees and are inconsistent. Computationally efficient species tree methods incorporating biological realism are a key to phylogenetic analysis of whole-genome data. © 2015 New York Academy of Sciences.

  20. Computational methods for protein identification from mass spectrometry data.

    Directory of Open Access Journals (Sweden)

    Leo McHugh

    2008-02-01

    Full Text Available Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology.

  1. Generating Genome-Scale Candidate Gene Lists for Pharmacogenomics

    DEFF Research Database (Denmark)

    Hansen, Niclas Tue; Brunak, Søren; Altman, R. B.

    2009-01-01

    A critical task in pharmacogenomics is identifying genes that may be important modulators of drug response. High-throughput experimental methods are often plagued by false positives and do not take advantage of existing knowledge. Candidate gene lists can usefully summarize existing knowledge...

  2. BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

    DEFF Research Database (Denmark)

    King, Zachary A.; Lu, Justin; Dräger, Andreas

    2016-01-01

    Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repo...

  3. In Silico Genome-Scale Reconstruction and Validation of the Staphylococcus aureus Metabolic Network

    NARCIS (Netherlands)

    Heinemann, Matthias; Kümmel, Anne; Ruinatscha, Reto; Panke, Sven

    2005-01-01

    A genome-scale metabolic model of the Gram-positive, facultative anaerobic opportunistic pathogen Staphylococcus aureus N315 was constructed based on current genomic data, literature, and physiological information. The model comprises 774 metabolic processes representing approximately 23% of all

  4. An Integrative Bioinformatics Framework for Genome-scale Multiple Level Network Reconstruction of Rice

    Directory of Open Access Journals (Sweden)

    Liu Lili

    2013-06-01

    Full Text Available Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs, protein-protein interactions (PPIs and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However, the lack of curated metabolic model of rice is blocking the exploration of genome-scale multi-level network reconstruction. Here, we have merged GRNs, PPIs and genome-scale metabolic networks (GSMNs approaches into a single framework for rice via omics’ regulatory information reconstruction and integration. Firstly, we reconstructed a genome-scale metabolic model, containing 4,462 function genes, 2,986 metabolites involved in 3,316 reactions, and compartmentalized into ten subcellular locations. Furthermore, 90,358 pairs of protein-protein interactions, 662,936 pairs of gene regulations and 1,763 microRNA-target interactions were integrated into the metabolic model. Eventually, a database was developped for systematically storing and retrieving the genome-scale multi-level network of rice. This provides a reference for understanding genotype-phenotype relationship of rice, and for analysis of its molecular regulatory network.

  5. Methods of Identification and Evaluation of Brownfield Sites

    Directory of Open Access Journals (Sweden)

    Safet Kurtović

    2014-04-01

    Full Text Available The basic objective of this paper was to determine the importance and potential restoration of brownfield sites in terms of economic prosperity of a particular region or country. In addition, in a theoretical sense, this paper presents the methods used in the identification of brownfield sites such as Smart Growth Network model and Thomas GIS model, and methods for evaluation of brownfield sites or the indexing method, cost-benefit and multivariate analysis.

  6. Impact of identity theft on methods of identification.

    Science.gov (United States)

    McLemore, Jerri; Hodges, Walker; Wyman, Amy

    2011-06-01

    Responsibility for confirming a decedent's identity commonly falls on the shoulders of the coroner or medical examiner. Misidentification of bodies results in emotional turmoil for the next-of-kin and can negatively impact the coroner's or medical examiner's career. To avoid such mishaps, the use of scientific methods to establish a positive identification is advocated. The use of scientific methods of identification may not be reliable in cases where the decedent had assumed the identity of another person. Case studies of erroneously identified bodies due to identity theft from the state medical examiner offices in Iowa and New Mexico are presented. This article discusses the scope and major concepts of identity theft and how identity theft prevents the guarantee of a positive identification.

  7. An Identification Key for Selecting Methods for Sustainability Assessments

    Directory of Open Access Journals (Sweden)

    Michiel C. Zijp

    2015-03-01

    Full Text Available Sustainability assessments can play an important role in decision making. This role starts with selecting appropriate methods for a given situation. We observed that scientists, consultants, and decision-makers often do not systematically perform a problem analyses that guides the choice of the method, partly related to a lack of systematic, though sufficiently versatile approaches to do so. Therefore, we developed and propose a new step towards method selection on the basis of question articulation: the Sustainability Assessment Identification Key. The identification key was designed to lead its user through all important choices needed for comprehensive question articulation. Subsequently, methods that fit the resulting specific questions are suggested by the key. The key consists of five domains, of which three determine method selection and two the design or use of the method. Each domain consists of four or more criteria that need specification. For example in the domain “system boundaries”, amongst others, the spatial and temporal scales are specified. The key was tested (retrospectively on a set of thirty case studies. Using the key appeared to contribute to improved: (i transparency in the link between the question and method selection; (ii consistency between questions asked and answers provided; and (iii internal consistency in methodological design. There is latitude to develop the current initial key further, not only for selecting methods pertinent to a problem definition, but also as a principle for associated opportunities such as stakeholder identification.

  8. LocateP: Genome-scale subcellular-location predictor for bacterial proteins

    Directory of Open Access Journals (Sweden)

    Zhou Miaomiao

    2008-03-01

    Full Text Available Abstract Background In the past decades, various protein subcellular-location (SCL predictors have been developed. Most of these predictors, like TMHMM 2.0, SignalP 3.0, PrediSi and Phobius, aim at the identification of one or a few SCLs, whereas others such as CELLO and Psortb.v.2.0 aim at a broader classification. Although these tools and pipelines can achieve a high precision in the accurate prediction of signal peptides and transmembrane helices, they have a much lower accuracy when other sequence characteristics are concerned. For instance, it proved notoriously difficult to identify the fate of proteins carrying a putative type I signal peptidase (SPIase cleavage site, as many of those proteins are retained in the cell membrane as N-terminally anchored membrane proteins. Moreover, most of the SCL classifiers are based on the classification of the Swiss-Prot database and consequently inherited the inconsistency of that SCL classification. As accurate and detailed SCL prediction on a genome scale is highly desired by experimental researchers, we decided to construct a new SCL prediction pipeline: LocateP. Results LocateP combines many of the existing high-precision SCL identifiers with our own newly developed identifiers for specific SCLs. The LocateP pipeline was designed such that it mimics protein targeting and secretion processes. It distinguishes 7 different SCLs within Gram-positive bacteria: intracellular, multi-transmembrane, N-terminally membrane anchored, C-terminally membrane anchored, lipid-anchored, LPxTG-type cell-wall anchored, and secreted/released proteins. Moreover, it distinguishes pathways for Sec- or Tat-dependent secretion and alternative secretion of bacteriocin-like proteins. The pipeline was tested on data sets extracted from literature, including experimental proteomics studies. The tests showed that LocateP performs as well as, or even slightly better than other SCL predictors for some locations and outperforms

  9. Biometric and Emotion Identification: An ECG Compression Based Method

    Directory of Open Access Journals (Sweden)

    Susana Brás

    2018-04-01

    Full Text Available We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG. The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1 conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2 conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3 identification of the ECG record class, using a 1-NN (nearest neighbor classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model.

  10. General Anisotropy Identification of Paperboard with Virtual Fields Method

    Science.gov (United States)

    J.M. Considine; F. Pierron; K.T. Turner; D.W. Vahey

    2014-01-01

    This work extends previous efforts in plate bending of Virtual Fields Method (VFM) parameter identification to include a general 2-D anisotropicmaterial. Such an extension was needed for instances in which material principal directions are unknown or when specimen orientation is not aligned with material principal directions. A new fixture with a multiaxial force...

  11. Biometric and Emotion Identification: An ECG Compression Based Method.

    Science.gov (United States)

    Brás, Susana; Ferreira, Jacqueline H T; Soares, Sandra C; Pinho, Armando J

    2018-01-01

    We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG). The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1) conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2) conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3) identification of the ECG record class, using a 1-NN (nearest neighbor) classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model.

  12. Biometric and Emotion Identification: An ECG Compression Based Method

    Science.gov (United States)

    Brás, Susana; Ferreira, Jacqueline H. T.; Soares, Sandra C.; Pinho, Armando J.

    2018-01-01

    We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG). The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1) conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2) conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3) identification of the ECG record class, using a 1-NN (nearest neighbor) classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model. PMID:29670564

  13. Probability of identification (POI): a statistical model for the validation of qualitative botanical identification methods

    Science.gov (United States)

    A qualitative botanical identification method (BIM) is an analytical procedure which returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) mate...

  14. Characterizing steady states of genome-scale metabolic networks in continuous cell cultures.

    Directory of Open Access Journals (Sweden)

    Jorge Fernandez-de-Cossio-Diaz

    2017-11-01

    Full Text Available In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced.

  15. Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica.

    Science.gov (United States)

    Mishra, Pranjul; Lee, Na-Rae; Lakshmanan, Meiyappan; Kim, Minsuk; Kim, Byung-Gee; Lee, Dong-Yup

    2018-03-19

    Recently, there have been several attempts to produce long-chain dicarboxylic acids (DCAs) in various microbial hosts. Of these, Yarrowia lipolytica has great potential due to its oleaginous characteristics and unique ability to utilize hydrophobic substrates. However, Y. lipolytica should be further engineered to make it more competitive: the current approaches are mostly intuitive and cumbersome, thus limiting its industrial application. In this study, we proposed model-guided metabolic engineering strategies for enhanced production of DCAs in Y. lipolytica. At the outset, we reconstructed genome-scale metabolic model (GSMM) of Y. lipolytica (iYLI647) by substantially expanding the previous models. Subsequently, the model was validated using three sets of published culture experiment data. It was finally exploited to identify genetic engineering targets for overexpression, knockout, and cofactor modification by applying several in silico strain design methods, which potentially give rise to high yield production of the industrially relevant long-chain DCAs, e.g., dodecanedioic acid (DDDA). The resultant targets include (1) malate dehydrogenase and malic enzyme genes and (2) glutamate dehydrogenase gene, in silico overexpression of which generated additional NADPH required for fatty acid synthesis, leading to the increased DDDA fluxes by 48% and 22% higher, respectively, compared to wild-type. We further investigated the effect of supplying branched-chain amino acids on the acetyl-CoA turn-over rate which is key metabolite for fatty acid synthesis, suggesting their significance for production of DDDA in Y. lipolytica. In silico model-based strain design strategies allowed us to identify several metabolic engineering targets for overproducing DCAs in lipid accumulating yeast, Y. lipolytica. Thus, the current study can provide a methodological framework that is applicable to other oleaginous yeasts for value-added biochemical production.

  16. A system boundary identification method for life cycle assessment

    DEFF Research Database (Denmark)

    Li, Tao; Zhang, Hongchao; Liu, Zhichao

    2014-01-01

    , technical, geographical and temporal dimensions are presented to limit the boundaries of LCA. An algorithm is developed to identify an appropriate boundary by searching the process tree and evaluating the environmental impact contribution of each process while it is added into the studied system...... as processes are added. The two threshold rules and identification methods presented can be used to identify system boundary of LCA. The case study demonstrated that the methodology presented in this paper is an effective tool for the boundary identification....

  17. A topological method for vortex identification in turbulent flows

    Energy Technology Data Exchange (ETDEWEB)

    Zhong, Qiang; Chen, Huai; Li, Danxun [State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084 (China); Chen, Qigang, E-mail: lidx@mail.tsinghua.edu.cn [School of Civil Engineering, Beijing Jiaotong University, Beijing 100044 (China)

    2017-02-15

    We present a novel vortex identification method based on structured vorticity ( ω {sub s}) of the direction field of flow (velocity vectors set to unit magnitude). As a direct measure of streamline curvature is insensitive to vortex strength, ω {sub s} is effective in detecting vortices of various strengths. The effectiveness has been tested against both analytical flows (pure shear flow, Oseen vortex flow, strong outward spiraling motion, straining flow, Taylor–Green flow) and experimental flows (closed cavity flow, closed and open channel flow). Comparison of the new method with the swirling-strength method indicates that the new method shows promise as being a simple and effective criterion for vortex identification. (paper)

  18. Image portion identification methods, image parsing methods, image parsing systems, and articles of manufacture

    Science.gov (United States)

    Lassahn, Gordon D.; Lancaster, Gregory D.; Apel, William A.; Thompson, Vicki S.

    2013-01-08

    Image portion identification methods, image parsing methods, image parsing systems, and articles of manufacture are described. According to one embodiment, an image portion identification method includes accessing data regarding an image depicting a plurality of biological substrates corresponding to at least one biological sample and indicating presence of at least one biological indicator within the biological sample and, using processing circuitry, automatically identifying a portion of the image depicting one of the biological substrates but not others of the biological substrates.

  19. IONS: Identification of Orthologs by Neighborhood and Similarity—an Automated Method to Identify Orthologs in Chromosomal Regions of Common Evolutionary Ancestry and its Application to Hemiascomycetous Yeasts

    Science.gov (United States)

    Seret, Marie-Line; Baret, Philippe V.

    2011-01-01

    Comparative sequence analysis is widely used to infer gene function and study genome evolution and requires proper ortholog identification across different genomes. We have developed a program for the Identification of Orthologs in one-to-one relationship by Neighborhood and Similarity (IONS) between closely related species. The algorithm combines two levels of evidence to determine co-ancestrality at the genome scale: sequence similarity and shared neighborhood. The method was initially designed to provide anchor points for syntenic blocks within the Génolevures project concerning nine hemiascomycetous yeasts (about 50,000 genes) and is applicable to different input databases. Comparison based on use of a Rand index shows that the results are highly consistent with the pillars of the Yeast Gene Order Browser, a manually curated database. Compared with SYNERGY, another algorithm reporting homology relationships, our method’s main advantages are its automation and the absence of dataset-dependent parameters, facilitating consistent integration of newly released genomes. PMID:21918595

  20. A Systematic Identification Method for Thermodynamic Property Modelling

    DEFF Research Database (Denmark)

    Ana Perederic, Olivia; Cunico, Larissa; Sarup, Bent

    2017-01-01

    In this work, a systematic identification method for thermodynamic property modelling is proposed. The aim of the method is to improve the quality of phase equilibria prediction by group contribution based property prediction models. The method is applied to lipid systems where the Original UNIFAC...... model is used. Using the proposed method for estimating the interaction parameters using only VLE data, a better phase equilibria prediction for both VLE and SLE was obtained. The results were validated and compared with the original model performance...

  1. A steam generating unit identification using subspace methods

    International Nuclear Information System (INIS)

    Poshtan, J.; Mojallali, H.

    2002-01-01

    A Valid boiler model is a tool for the improvement of the steam generation control system and hence results boiler efficiency enhancement. However, methods of obtaining such a model are not readily found in the open literature and are often specific to a particular plant. This paper presents boiler model using a new method in system identification called S ubspace methods . This method is shown to provide an accurate state space model for boiler in a few numbers of operations, directly from input-output data without any prior knowledge of the system equations and any requirement to several stages of testing

  2. [Identification of Dens Draconis and Os Draconis by XRD method].

    Science.gov (United States)

    Chen, Guang-Yun; Wu, Qi-Nan; Shen, Bei; Chen, Rong

    2012-04-01

    To establish an XRD method for evaluating the quality of Os Draconis and Dens Draconis and applying in judgement of the counterfeit. Dens Draconis, Os Draconis and the counterfeit of Os Draconis were analyzed by XRD. Their diffraction patterns were clustered analysis and evaluated their similarity degree. Established the analytical method of Dens Draconis and Os Draconis basing the features fingerprint information of the 10 common peaks by XRD pattern. Obtained the XRD pattern of the counterfeit of Os Draconis. The similarity degree of separate sources of Dens Draconis was high,while the similarity degree of separate sources of Os Draconis was significant different from each other. This method can be used for identification and evaluation of Os Draconis and Dens Draconis. It also can be used for identification the counterfeit of Os Draconis effectively.

  3. Comparison of three methods for identification of pathogenic Neisseria species

    Energy Technology Data Exchange (ETDEWEB)

    Appelbaum, P.C.; Lawrence, R.B.

    1979-05-01

    A radiometric procedure was compared with the Minitek and Cystine Trypticase Agar sugar degradation methods for identification of 113 Neisseria species (58 Neisseria meningitidis, 51 Neisseria gonorrhoeae, 2 Neisseria lactamica, 2 Neisseria sicca). Identification of meningococci and gonoccoi was confirmed by agglutination and fluorescent antibody techniques, respectively. The Minitek method identified 97% of meningococci, 92% of gonococci, and 100% of other Neisseria after 4 h of incubation. The radiometric (Bactec) procedure identified 100% of gonococci and 100% of miscellaneous Neisseria after 3 h, but problems were encountered with meningococci: 45% of the later strains yielded index values for fructose between 20 and 28 (recommended negative cut-off point, less than 20), with strongly positive (greater than 100) glucose and maltose and negative o-nitrophenyl-beta-0-galactopyranoside reactions in all 58 strains. The Cystine Trypticase Agar method identified 91% of meningococci, ases.

  4. Optimum Identification Method of Sorting Green Household Waste

    Directory of Open Access Journals (Sweden)

    Daud Mohd Hisam

    2016-01-01

    Full Text Available This project is related to design of sorting facility for reducing, reusing, recycling green waste material, and in particular to invent an automatic system to distinguish household waste in order to separate them from the main waste stream. The project focuses on thorough analysis of the properties of green household waste. The method of identification is using capacitive sensor where the characteristic data taken on three different sensor drive frequency. Three types of material have been chosen as a medium of this research, to be separated using the selected method. Based on capacitance characteristics and its ability to penetrate green object, optimum identification method is expected to be recognized in this project. The output capacitance sensor is in analogue value. The results demonstrate that the information from the sensor is enough to recognize the materials that have been selected.

  5. Moving force identification based on modified preconditioned conjugate gradient method

    Science.gov (United States)

    Chen, Zhen; Chan, Tommy H. T.; Nguyen, Andy

    2018-06-01

    This paper develops a modified preconditioned conjugate gradient (M-PCG) method for moving force identification (MFI) by improving the conjugate gradient (CG) and preconditioned conjugate gradient (PCG) methods with a modified Gram-Schmidt algorithm. The method aims to obtain more accurate and more efficient identification results from the responses of bridge deck caused by vehicles passing by, which are known to be sensitive to ill-posed problems that exist in the inverse problem. A simply supported beam model with biaxial time-varying forces is used to generate numerical simulations with various analysis scenarios to assess the effectiveness of the method. Evaluation results show that regularization matrix L and number of iterations j are very important influence factors to identification accuracy and noise immunity of M-PCG. Compared with the conventional counterpart SVD embedded in the time domain method (TDM) and the standard form of CG, the M-PCG with proper regularization matrix has many advantages such as better adaptability and more robust to ill-posed problems. More importantly, it is shown that the average optimal numbers of iterations of M-PCG can be reduced by more than 70% compared with PCG and this apparently makes M-PCG a preferred choice for field MFI applications.

  6. Development of evaluation method for software hazard identification techniques

    International Nuclear Information System (INIS)

    Huang, H. W.; Chen, M. H.; Shih, C.; Yih, S.; Kuo, C. T.; Wang, L. H.; Yu, Y. C.; Chen, C. W.

    2006-01-01

    This research evaluated the applicable software hazard identification techniques nowadays, such as, Preliminary Hazard Analysis (PHA), Failure Modes and Effects Analysis (FMEA), Fault Tree Analysis (FTA), Markov chain modeling, Dynamic Flow-graph Methodology (DFM), and simulation-based model analysis; and then determined indexes in view of their characteristics, which include dynamic capability, completeness, achievability, detail, signal/noise ratio, complexity, and implementation cost. By this proposed method, the analysts can evaluate various software hazard identification combinations for specific purpose. According to the case study results, the traditional PHA + FMEA + FTA (with failure rate) + Markov chain modeling (with transfer rate) combination is not competitive due to the dilemma for obtaining acceptable software failure rates. However, the systematic architecture of FTA and Markov chain modeling is still valuable for realizing the software fault structure. The system centric techniques, such as DFM and simulation-based model-analysis, show the advantage on dynamic capability, achievability, detail, signal/noise ratio. However, their disadvantages are the completeness complexity and implementation cost. This evaluation method can be a platform to reach common consensus for the stakeholders. Following the evolution of software hazard identification techniques, the evaluation results could be changed. However, the insight of software hazard identification techniques is much more important than the numbers obtained by the evaluation. (authors)

  7. Probability of identification: a statistical model for the validation of qualitative botanical identification methods.

    Science.gov (United States)

    LaBudde, Robert A; Harnly, James M

    2012-01-01

    A qualitative botanical identification method (BIM) is an analytical procedure that returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) material, or whether it contains excessive nontarget (undesirable) material. The report describes the development and validation of studies for a BIM based on the proportion of replicates identified, or probability of identification (POI), as the basic observed statistic. The statistical procedures proposed for data analysis follow closely those of the probability of detection, and harmonize the statistical concepts and parameters between quantitative and qualitative method validation. Use of POI statistics also harmonizes statistical concepts for botanical, microbiological, toxin, and other analyte identification methods that produce binary results. The POI statistical model provides a tool for graphical representation of response curves for qualitative methods, reporting of descriptive statistics, and application of performance requirements. Single collaborator and multicollaborative study examples are given.

  8. Genome-scale cold stress response regulatory networks in ten Arabidopsis thaliana ecotypes

    DEFF Research Database (Denmark)

    Barah, Pankaj; Jayavelu, Naresh Doni; Rasmussen, Simon

    2013-01-01

    available from Arabidopsis thaliana 1001 genome project, we further investigated sequence polymorphisms in the core cold stress regulon genes. Significant numbers of non-synonymous amino acid changes were observed in the coding region of the CBF regulon genes. Considering the limited knowledge about......BACKGROUND: Low temperature leads to major crop losses every year. Although several studies have been conducted focusing on diversity of cold tolerance level in multiple phenotypically divergent Arabidopsis thaliana (A. thaliana) ecotypes, genome-scale molecular understanding is still lacking....... RESULTS: In this study, we report genome-scale transcript response diversity of 10 A. thaliana ecotypes originating from different geographical locations to non-freezing cold stress (10°C). To analyze the transcriptional response diversity, we initially compared transcriptome changes in all 10 ecotypes...

  9. A protocol for generating a high-quality genome-scale metabolic reconstruction.

    Science.gov (United States)

    Thiele, Ines; Palsson, Bernhard Ø

    2010-01-01

    Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have been developed over the last 10 years. These reconstructions represent structured knowledge bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates a myriad of computational biological studies, including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge bases. Here we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction, as well as the common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process.

  10. Genome scale models of yeast: towards standardized evaluation and consistent omic integration

    DEFF Research Database (Denmark)

    Sanchez, Benjamin J.; Nielsen, Jens

    2015-01-01

    Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published and are curre......Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published...... in which all levels of omics data (from gene expression to flux) have been integrated in yeast GEMs. Relevant conclusions and current challenges for both GEM evaluation and omic integration are highlighted....

  11. Genome-scale modeling of yeast: chronology, applications and critical perspectives.

    Science.gov (United States)

    Lopes, Helder; Rocha, Isabel

    2017-08-01

    Over the last 15 years, several genome-scale metabolic models (GSMMs) were developed for different yeast species, aiding both the elucidation of new biological processes and the shift toward a bio-based economy, through the design of in silico inspired cell factories. Here, an historical perspective of the GSMMs built over time for several yeast species is presented and the main inheritance patterns among the metabolic reconstructions are highlighted. We additionally provide a critical perspective on the overall genome-scale modeling procedure, underlining incomplete model validation and evaluation approaches and the quest for the integration of regulatory and kinetic information into yeast GSMMs. A summary of experimentally validated model-based metabolic engineering applications of yeast species is further emphasized, while the main challenges and future perspectives for the field are finally addressed. © FEMS 2017.

  12. Identification Method of Mud Shale Fractures Base on Wavelet Transform

    Science.gov (United States)

    Xia, Weixu; Lai, Fuqiang; Luo, Han

    2018-01-01

    In recent years, inspired by seismic analysis technology, a new method for analysing mud shale fractures oil and gas reservoirs by logging properties has emerged. By extracting the high frequency attribute of the wavelet transform in the logging attribute, the formation information hidden in the logging signal is extracted, identified the fractures that are not recognized by conventional logging and in the identified fracture segment to show the “cycle jump”, “high value”, “spike” and other response effect is more obvious. Finally formed a complete wavelet denoising method and wavelet high frequency identification fracture method.

  13. [Combine fats products: methodic opportunities of it identification].

    Science.gov (United States)

    Viktorova, E V; Kulakova, S N; Mikhaĭlov, N A

    2006-01-01

    At present time very topical problem is falsification of milk fat. The number of methods was considered to detection of milk fat authention and possibilities his difference from combined fat products. The analysis of modern approaches to valuation of milk fat authention has showed that the main method for detection of fat nature is gas chromatography analysis. The computer method of express identification of fat products is proposed for quick getting of information about accessory of examine fat to nature milk or combined fat product.

  14. Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism

    Science.gov (United States)

    2016-03-15

    RESEARCH ARTICLE Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism Francisco G...jaques.reifman.civ@mail.mil Abstract A hallmark of Pseudomonas aeruginosa is its ability to establish biofilm -based infections that are difficult to...eradicate. Biofilms are less susceptible to host inflammatory and immune responses and have higher antibiotic tolerance than free-living planktonic

  15. In silico analysis of human metabolism: Reconstruction, contextualization and application of genome-scale models

    DEFF Research Database (Denmark)

    Geng, Jun; Nielsen, Jens

    2017-01-01

    The arising prevalence of metabolic diseases calls for a holistic approach for analysis of the underlying nature of abnormalities in cellular functions. Through mathematic representation and topological analysis of cellular metabolism, GEnome scale metabolic Models (GEMs) provide a promising fram...... that correctly describe interactions between cells or tissues, and we therefore discuss how GEMs can be integrated with blood circulation models. Finally, we end the review with proposing some possible future research directions....

  16. Lyoluminescence technique as an identification method for irradiated food stuffs

    International Nuclear Information System (INIS)

    Chazhoor, J.S.

    1988-01-01

    The paper presents the studies made on the suitability of lyoluminescence technique as an analytical method for the identification of irradiated food stuffs. Powder milk, cinnamon, cardamom, clove, red chilly, cocoa, pepper, tea, coffee, turmeric and coriander showed lyoluminescence response when irradiated by a 10 kGy 60 Co and dissolved in luminol solution. Various dosimetric parameters such as effect of storage time, proportionality of the lyoluminescence response to dose etc were studied. (author). 1 tab., 3 figs

  17. MOST-visualization: software for producing automated textbook-style maps of genome-scale metabolic networks.

    Science.gov (United States)

    Kelley, James J; Maor, Shay; Kim, Min Kyung; Lane, Anatoliy; Lun, Desmond S

    2017-08-15

    Visualization of metabolites, reactions and pathways in genome-scale metabolic networks (GEMs) can assist in understanding cellular metabolism. Three attributes are desirable in software used for visualizing GEMs: (i) automation, since GEMs can be quite large; (ii) production of understandable maps that provide ease in identification of pathways, reactions and metabolites; and (iii) visualization of the entire network to show how pathways are interconnected. No software currently exists for visualizing GEMs that satisfies all three characteristics, but MOST-Visualization, an extension of the software package MOST (Metabolic Optimization and Simulation Tool), satisfies (i), and by using a pre-drawn overview map of metabolism based on the Roche map satisfies (ii) and comes close to satisfying (iii). MOST is distributed for free on the GNU General Public License. The software and full documentation are available at http://most.ccib.rutgers.edu/. dslun@rutgers.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  18. Vortex Tube Modeling Using the System Identification Method

    Energy Technology Data Exchange (ETDEWEB)

    Han, Jaeyoung; Jeong, Jiwoong; Yu, Sangseok [Chungnam Nat’l Univ., Daejeon (Korea, Republic of); Im, Seokyeon [Tongmyong Univ., Busan (Korea, Republic of)

    2017-05-15

    In this study, vortex tube system model is developed to predict the temperature of the hot and the cold sides. The vortex tube model is developed based on the system identification method, and the model utilized in this work to design the vortex tube is ARX type (Auto-Regressive with eXtra inputs). The derived polynomial model is validated against experimental data to verify the overall model accuracy. It is also shown that the derived model passes the stability test. It is confirmed that the derived model closely mimics the physical behavior of the vortex tube from both the static and dynamic numerical experiments by changing the angles of the low-temperature side throttle valve, clearly showing temperature separation. These results imply that the system identification based modeling can be a promising approach for the prediction of complex physical systems, including the vortex tube.

  19. An identification method for damping ratio in rotor systems

    Science.gov (United States)

    Wang, Weimin; Li, Qihang; Gao, Jinji; Yao, Jianfei; Allaire, Paul

    2016-02-01

    Centrifugal compressor testing with magnetic bearing excitations is the last step to assure the compressor rotordynamic stability in the designed operating conditions. To meet the challenges of stability evaluation, a new method combining the rational polynomials method (RPM) with the weighted instrumental variables (WIV) estimator to fit the directional frequency response function (dFRF) is presented. Numerical simulation results show that the method suggested in this paper can identify the damping ratio of the first forward and backward modes with high accuracy, even in a severe noise environment. Experimental tests were conducted to study the effect of different bearing configurations on the stability of rotor. Furthermore, two example centrifugal compressors (a nine-stage straight-through and a six-stage back-to-back) were employed to verify the feasibility of identification method in industrial configurations as well.

  20. Identification of fractional order systems using modulating functions method

    KAUST Repository

    Liu, Dayan

    2013-06-01

    The modulating functions method has been used for the identification of linear and nonlinear systems. In this paper, we generalize this method to the on-line identification of fractional order systems based on the Riemann-Liouville fractional derivatives. First, a new fractional integration by parts formula involving the fractional derivative of a modulating function is given. Then, we apply this formula to a fractional order system, for which the fractional derivatives of the input and the output can be transferred into the ones of the modulating functions. By choosing a set of modulating functions, a linear system of algebraic equations is obtained. Hence, the unknown parameters of a fractional order system can be estimated by solving a linear system. Using this method, we do not need any initial values which are usually unknown and not equal to zero. Also we do not need to estimate the fractional derivatives of noisy output. Moreover, it is shown that the proposed estimators are robust against high frequency sinusoidal noises and the ones due to a class of stochastic processes. Finally, the efficiency and the stability of the proposed method is confirmed by some numerical simulations.

  1. Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets

    NARCIS (Netherlands)

    Levering, J.; Fiedler, T.; Sieg, A.; van Grinsven, K.W.A.; Hering, S.; Veith, N.; Olivier, B.G.; Klett, L.; Hugenholtz, J.; Teusink, B.; Kreikemeyer, B.; Kummer, U.

    2016-01-01

    Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes

  2. Process identification method based on the Z transformation; Methode d'identification de processus par la transformation en Z

    Energy Technology Data Exchange (ETDEWEB)

    Zwingelstein, G [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

    1968-07-01

    A simple method is described for identifying the transfer function of a linear retard-less system, based on the inversion of the Z transformation of the transmittance using a computer. It is assumed in this study that the signals at the entrance and at the exit of the circuit considered are of the deterministic type. The study includes: the theoretical principle of the inversion of the Z transformation, details about programming simulation, and identification of filters whose degrees vary from the first to the fifth order. (authors) [French] On decrit une methode simple d'identification de fonction de transfert d'un systeme lineaire sans retard, qui repose sur l'inversion de la transformee en Z de la transmittance a l'aide d'un calculateur. On suppose dans cette etude, que les signaux a l'entree et a la sortie du circuit considere sont de type deterministe. L'etude comporte: le principe theorique de l'inversion de la transformation en Z, les details de la programmation, la simulation et l'identification de filtres dont le degre varie du premier au cinquieme ordre. (auteurs)

  3. Methods, Systems and Apparatuses for Radio Frequency Identification

    Science.gov (United States)

    Fink, Patrick W. (Inventor); Chu, Andrew W. (Inventor); Lin, Gregory Y. (Inventor); Kennedy, Timothy F. (Inventor); Ngo, Phong H. (Inventor); Brown, Dewey T. (Inventor); Byerly, Diane (Inventor)

    2017-01-01

    A system for radio frequency identification (RFID) includes an enclosure defining an interior region interior to the enclosure, and a feed for generating an electromagnetic field in the interior region in response to a signal received from an RFID reader via a radio frequency (RF) transmission line and, in response to the electromagnetic field, receiving a signal from an RFID sensor attached to an item in the interior region. The structure of the enclosure may be conductive and may include a metamaterial portion, an electromagnetically absorbing portion, or a wall extending in the interior region. Related apparatuses and methods for performing RFID are provided.

  4. DNA Checkerboard Method for Bacterial Pathogen Identification in Oral Diseases

    OpenAIRE

    Nascimento, Cássio do; Issa, João Paulo Mardegan; Watanabe, Evandro; Ito, Izabel Yoko

    2006-01-01

    This work aim to show by literature review the principal characteristics of the DNA checkerboard method for bacterial pathogens identification in oral diseases, showing the most varieties uses and applications of this technique Este trabajo tiene como objetivo, presentar en una revisión de la literatura, las principales características del método de chequeo del DNA para la identificación de bacterias patógenas en la cavidad oral, mostrando las diferentes utilizaciones y aplicaciones de est...

  5. Process identification method based on the Z transformation

    International Nuclear Information System (INIS)

    Zwingelstein, G.

    1968-01-01

    A simple method is described for identifying the transfer function of a linear retard-less system, based on the inversion of the Z transformation of the transmittance using a computer. It is assumed in this study that the signals at the entrance and at the exit of the circuit considered are of the deterministic type. The study includes: the theoretical principle of the inversion of the Z transformation, details about programming simulation, and identification of filters whose degrees vary from the first to the fifth order. (authors) [fr

  6. The PLR-DTW method for ECG based biometric identification.

    Science.gov (United States)

    Shen, Jun; Bao, Shu-Di; Yang, Li-Cai; Li, Ye

    2011-01-01

    There has been a surge of research on electrocardiogram (ECG) signal based biometric for person identification. Though most of the existing studies claimed that ECG signal is unique to an individual and can be a viable biometric, one of the main difficulties for real-world applications of ECG biometric is the accuracy performance. To address this problem, this study proposes a PLR-DTW method for ECG biometric, where the Piecewise Linear Representation (PLR) is used to keep important information of an ECG signal segment while reduce the data dimension at the same time if necessary, and the Dynamic Time Warping (DTW) is used for similarity measures between two signal segments. The performance evaluation was carried out on three ECG databases, and the existing method using wavelet coefficients, which was proved to have good accuracy performance, was selected for comparison. The analysis results show that the PLR-DTW method achieves an accuracy rate of 100% for identification, while the one using wavelet coefficients achieved only around 93%.

  7. Comparison Study of Subspace Identification Methods Applied to Flexible Structures

    Science.gov (United States)

    Abdelghani, M.; Verhaegen, M.; Van Overschee, P.; De Moor, B.

    1998-09-01

    In the past few years, various time domain methods for identifying dynamic models of mechanical structures from modal experimental data have appeared. Much attention has been given recently to so-called subspace methods for identifying state space models. This paper presents a detailed comparison study of these subspace identification methods: the eigensystem realisation algorithm with observer/Kalman filter Markov parameters computed from input/output data (ERA/OM), the robust version of the numerical algorithm for subspace system identification (N4SID), and a refined version of the past outputs scheme of the multiple-output error state space (MOESP) family of algorithms. The comparison is performed by simulating experimental data using the five mode reduced model of the NASA Mini-Mast structure. The general conclusion is that for the case of white noise excitations as well as coloured noise excitations, the N4SID/MOESP algorithms perform equally well but give better results (improved transfer function estimates, improved estimates of the output) compared to the ERA/OM algorithm. The key computational step in the three algorithms is the approximation of the extended observability matrix of the system to be identified, for N4SID/MOESP, or of the observer for the system to be identified, for the ERA/OM. Furthermore, the three algorithms only require the specification of one dimensioning parameter.

  8. The identification method of the nuclear fragments in emulsions

    International Nuclear Information System (INIS)

    Jipa, Alexandru; Ocheseanu, Silvia; Caramarcu, Costin; Calin, Marius; Constantin, Florin; Stan, Emil

    2003-01-01

    The visualization detectors have been successfully used from the beginning of the study of the relativistic nuclear collisions. One of these detectors used in such experiments is the nuclear emulsion. To increase the speed of the passage from pictures to experimental data different methods and tools have been proposed during the time. For identifying the nuclear fragments obtained in the relativistic radioactive beams multiple layers of nuclear emulsions have been exposed in experiments performed at the Synchrophasotron from the JINR Dubna (BECQUEREL Collaboration). The nuclear fragments have been identified using PAVICOM scanning and measuring system. In the present work an identification method based on a real time image processing machine and a reconstruction algorithm based on special conformal transforms is proposed. The results obtained by this method are compared with those obtained using PAVICOM device. Because in this study only pictures have been used, not initial nuclear emulsions, some difficulties in the identification of the nuclear fragments with higher polar angles can appear. Generally, comparable results have been obtained. The authors thank Dr. Pavel Zarubin from JINR Dubna, Laboratory of High Energy Physics, and Dr. Maria Haiduc, Institute of Space Sciences Bucharest-Magurele, for the pictures of the nuclear emulsions exposed in these experiments. (authors)

  9. Improved genome-scale multi-target virtual screening via a novel collaborative filtering approach to cold-start problem.

    Science.gov (United States)

    Lim, Hansaim; Gray, Paul; Xie, Lei; Poleksic, Aleksandar

    2016-12-13

    Conventional one-drug-one-gene approach has been of limited success in modern drug discovery. Polypharmacology, which focuses on searching for multi-targeted drugs to perturb disease-causing networks instead of designing selective ligands to target individual proteins, has emerged as a new drug discovery paradigm. Although many methods for single-target virtual screening have been developed to improve the efficiency of drug discovery, few of these algorithms are designed for polypharmacology. Here, we present a novel theoretical framework and a corresponding algorithm for genome-scale multi-target virtual screening based on the one-class collaborative filtering technique. Our method overcomes the sparseness of the protein-chemical interaction data by means of interaction matrix weighting and dual regularization from both chemicals and proteins. While the statistical foundation behind our method is general enough to encompass genome-wide drug off-target prediction, the program is specifically tailored to find protein targets for new chemicals with little to no available interaction data. We extensively evaluate our method using a number of the most widely accepted gene-specific and cross-gene family benchmarks and demonstrate that our method outperforms other state-of-the-art algorithms for predicting the interaction of new chemicals with multiple proteins. Thus, the proposed algorithm may provide a powerful tool for multi-target drug design.

  10. Genome-scale model guided design of Propionibacterium for enhanced propionic acid production

    Directory of Open Access Journals (Sweden)

    Laura Navone

    2018-06-01

    Full Text Available Production of propionic acid by fermentation of propionibacteria has gained increasing attention in the past few years. However, biomanufacturing of propionic acid cannot compete with the current oxo-petrochemical synthesis process due to its well-established infrastructure, low oil prices and the high downstream purification costs of microbial production. Strain improvement to increase propionic acid yield is the best alternative to reduce downstream purification costs. The recent generation of genome-scale models for a number of Propionibacterium species facilitates the rational design of metabolic engineering strategies and provides a new opportunity to explore the metabolic potential of the Wood-Werkman cycle. Previous strategies for strain improvement have individually targeted acid tolerance, rate of propionate production or minimisation of by-products. Here we used the P. freudenreichii subsp. shermanii and the pan-Propionibacterium genome-scale metabolic models (GEMs to simultaneously target these combined issues. This was achieved by focussing on strategies which yield higher energies and directly suppress acetate formation. Using P. freudenreichii subsp. shermanii, two strategies were assessed. The first tested the ability to manipulate the redox balance to favour propionate production by over-expressing the first two enzymes of the pentose-phosphate pathway (PPP, Zwf (glucose-6-phosphate 1-dehydrogenase and Pgl (6-phosphogluconolactonase. Results showed a 4-fold increase in propionate to acetate ratio during the exponential growth phase. Secondly, the ability to enhance the energy yield from propionate production by over-expressing an ATP-dependent phosphoenolpyruvate carboxykinase (PEPCK and sodium-pumping methylmalonyl-CoA decarboxylase (MMD was tested, which extended the exponential growth phase. Together, these strategies demonstrate that in silico design strategies are predictive and can be used to reduce by-product formation in

  11. Rapid prototyping of microbial cell factories via genome-scale engineering.

    Science.gov (United States)

    Si, Tong; Xiao, Han; Zhao, Huimin

    2015-11-15

    Advances in reading, writing and editing genetic materials have greatly expanded our ability to reprogram biological systems at the resolution of a single nucleotide and on the scale of a whole genome. Such capacity has greatly accelerated the cycles of design, build and test to engineer microbes for efficient synthesis of fuels, chemicals and drugs. In this review, we summarize the emerging technologies that have been applied, or are potentially useful for genome-scale engineering in microbial systems. We will focus on the development of high-throughput methodologies, which may accelerate the prototyping of microbial cell factories. Copyright © 2014 Elsevier Inc. All rights reserved.

  12. Integration of Genome Scale Metabolic Networks and Gene Regulation of Metabolic Enzymes With Physiologically Based Pharmacokinetics.

    Science.gov (United States)

    Maldonado, Elaina M; Leoncikas, Vytautas; Fisher, Ciarán P; Moore, J Bernadette; Plant, Nick J; Kierzek, Andrzej M

    2017-11-01

    The scope of physiologically based pharmacokinetic (PBPK) modeling can be expanded by assimilation of the mechanistic models of intracellular processes from systems biology field. The genome scale metabolic networks (GSMNs) represent a whole set of metabolic enzymes expressed in human tissues. Dynamic models of the gene regulation of key drug metabolism enzymes are available. Here, we introduce GSMNs and review ongoing work on integration of PBPK, GSMNs, and metabolic gene regulation. We demonstrate example models. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

  13. Rapid Prototyping of Microbial Cell Factories via Genome-scale Engineering

    Science.gov (United States)

    Si, Tong; Xiao, Han; Zhao, Huimin

    2014-01-01

    Advances in reading, writing and editing genetic materials have greatly expanded our ability to reprogram biological systems at the resolution of a single nucleotide and on the scale of a whole genome. Such capacity has greatly accelerated the cycles of design, build and test to engineer microbes for efficient synthesis of fuels, chemicals and drugs. In this review, we summarize the emerging technologies that have been applied, or are potentially useful for genome-scale engineering in microbial systems. We will focus on the development of high-throughput methodologies, which may accelerate the prototyping of microbial cell factories. PMID:25450192

  14. Genome-scale modeling of the protein secretory machinery in yeast

    DEFF Research Database (Denmark)

    Feizi, Amir; Österlund, Tobias; Petranovic, Dina

    2013-01-01

    The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking....... Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm...

  15. Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling

    DEFF Research Database (Denmark)

    Ghaffari, Pouyan; Mardinoglu, Adil; Asplund, Anna

    2015-01-01

    Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines...... based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted...... for inhibition of cell growth may provide leads for the development of efficient cancer treatment strategies....

  16. On the orthogonalised reverse path method for nonlinear system identification

    Science.gov (United States)

    Muhamad, P.; Sims, N. D.; Worden, K.

    2012-09-01

    The problem of obtaining the underlying linear dynamic compliance matrix in the presence of nonlinearities in a general multi-degree-of-freedom (MDOF) system can be solved using the conditioned reverse path (CRP) method introduced by Richards and Singh (1998 Journal of Sound and Vibration, 213(4): pp. 673-708). The CRP method also provides a means of identifying the coefficients of any nonlinear terms which can be specified a priori in the candidate equations of motion. Although the CRP has proved extremely useful in the context of nonlinear system identification, it has a number of small issues associated with it. One of these issues is the fact that the nonlinear coefficients are actually returned in the form of spectra which need to be averaged over frequency in order to generate parameter estimates. The parameter spectra are typically polluted by artefacts from the identification of the underlying linear system which manifest themselves at the resonance and anti-resonance frequencies. A further problem is associated with the fact that the parameter estimates are extracted in a recursive fashion which leads to an accumulation of errors. The first minor objective of this paper is to suggest ways to alleviate these problems without major modification to the algorithm. The results are demonstrated on numerically-simulated responses from MDOF systems. In the second part of the paper, a more radical suggestion is made, to replace the conditioned spectral analysis (which is the basis of the CRP method) with an alternative time domain decorrelation method. The suggested approach - the orthogonalised reverse path (ORP) method - is illustrated here using data from simulated single-degree-of-freedom (SDOF) and MDOF systems.

  17. Variable identification in group method of data handling methodology

    Energy Technology Data Exchange (ETDEWEB)

    Pereira, Iraci Martinez, E-mail: martinez@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Bueno, Elaine Inacio [Instituto Federal de Educacao, Ciencia e Tecnologia, Guarulhos, SP (Brazil)

    2011-07-01

    The Group Method of Data Handling - GMDH is a combinatorial multi-layer algorithm in which a network of layers and nodes is generated using a number of inputs from the data stream being evaluated. The GMDH network topology has been traditionally determined using a layer by layer pruning process based on a preselected criterion of what constitutes the best nodes at each level. The traditional GMDH method is based on an underlying assumption that the data can be modeled by using an approximation of the Volterra Series or Kolmorgorov-Gabor polynomial. A Monitoring and Diagnosis System was developed based on GMDH and Artificial Neural Network - ANN methodologies, and applied to the IPEN research Reactor IEA-R1. The GMDH was used to study the best set of variables to be used to train an ANN, resulting in a best monitoring variable estimative. The system performs the monitoring by comparing these estimative calculated values with measured ones. The IPEN Reactor Data Acquisition System is composed of 58 variables (process and nuclear variables). As the GMDH is a self-organizing methodology, the input variables choice is made automatically, and the real input variables used in the Monitoring and Diagnosis System were not showed in the final result. This work presents a study of variable identification of GMDH methodology by means of an algorithm that works in parallel with the GMDH algorithm and traces the initial variables paths, resulting in an identification of the variables that composes the best Monitoring and Diagnosis Model. (author)

  18. Variable identification in group method of data handling methodology

    International Nuclear Information System (INIS)

    Pereira, Iraci Martinez; Bueno, Elaine Inacio

    2011-01-01

    The Group Method of Data Handling - GMDH is a combinatorial multi-layer algorithm in which a network of layers and nodes is generated using a number of inputs from the data stream being evaluated. The GMDH network topology has been traditionally determined using a layer by layer pruning process based on a preselected criterion of what constitutes the best nodes at each level. The traditional GMDH method is based on an underlying assumption that the data can be modeled by using an approximation of the Volterra Series or Kolmorgorov-Gabor polynomial. A Monitoring and Diagnosis System was developed based on GMDH and Artificial Neural Network - ANN methodologies, and applied to the IPEN research Reactor IEA-R1. The GMDH was used to study the best set of variables to be used to train an ANN, resulting in a best monitoring variable estimative. The system performs the monitoring by comparing these estimative calculated values with measured ones. The IPEN Reactor Data Acquisition System is composed of 58 variables (process and nuclear variables). As the GMDH is a self-organizing methodology, the input variables choice is made automatically, and the real input variables used in the Monitoring and Diagnosis System were not showed in the final result. This work presents a study of variable identification of GMDH methodology by means of an algorithm that works in parallel with the GMDH algorithm and traces the initial variables paths, resulting in an identification of the variables that composes the best Monitoring and Diagnosis Model. (author)

  19. An overview of modal-based damage identification methods

    Energy Technology Data Exchange (ETDEWEB)

    Farrar, C.R.; Doebling, S.W. [Los Alamos National Lab., NM (United States). Engineering Analysis Group

    1997-09-01

    This paper provides an overview of methods that examine changes in measured vibration response to detect, locate, and characterize damage in structural and mechanical systems. The basic idea behind this technology is that modal parameters (notably frequencies, mode shapes, and modal damping) are functions of the physical properties of the structure (mass, damping, and stiffness). Therefore, changes in the physical properties will cause detectable changes in the modal properties. The motivation for the development of this technology is first provided. The methods are then categorized according to various criteria such as the level of damage detection provided, model-based vs. non-model-based methods and linear vs. nonlinear methods. This overview is limited to methods that can be adapted to a wide range of structures (i.e., are not dependent on a particular assumed model form for the system such as beam-bending behavior and methods and that are not based on updating finite element models). Next, the methods are described in general terms including difficulties associated with their implementation and their fidelity. Past, current and future-planned applications of this technology to actual engineering systems are summarized. The paper concludes with a discussion of critical issues for future research in the area of modal-based damage identification.

  20. An online substructure identification method for local structural health monitoring

    International Nuclear Information System (INIS)

    Hou, Jilin; Ou, Jinping; Jankowski, Łukasz

    2013-01-01

    This paper proposes a substructure isolation method, which uses time series of measured local response for online monitoring of substructures. The proposed monitoring process consists of two key steps: construction of the isolated substructure, and its identification. The isolated substructure is an independent virtual structure, which is numerically isolated from the global structure by placing virtual supports on the interface. First, the isolated substructure is constructed by a specific linear combination of time series of its measured local responses. Then, the isolated substructure is identified using its local natural frequencies extracted from the combined responses. The substructure is assumed to be linear; the outside part of the global structure can have any characteristics. The method has no requirements on the initial state of the structure, and so the process can be carried out repetitively for online monitoring. Online isolation and monitoring is illustrated in a numerical example with a frame model, and then verified in a cantilever beam experiment. (paper)

  1. Comprehensive Mapping of Pluripotent Stem Cell Metabolism Using Dynamic Genome-Scale Network Modeling

    Directory of Open Access Journals (Sweden)

    Sriram Chandrasekaran

    2017-12-01

    Full Text Available Summary: Metabolism is an emerging stem cell hallmark tied to cell fate, pluripotency, and self-renewal, yet systems-level understanding of stem cell metabolism has been limited by the lack of genome-scale network models. Here, we develop a systems approach to integrate time-course metabolomics data with a computational model of metabolism to analyze the metabolic state of naive and primed murine pluripotent stem cells. Using this approach, we find that one-carbon metabolism involving phosphoglycerate dehydrogenase, folate synthesis, and nucleotide synthesis is a key pathway that differs between the two states, resulting in differential sensitivity to anti-folates. The model also predicts that the pluripotency factor Lin28 regulates this one-carbon metabolic pathway, which we validate using metabolomics data from Lin28-deficient cells. Moreover, we identify and validate metabolic reactions related to S-adenosyl-methionine production that can differentially impact histone methylation in naive and primed cells. Our network-based approach provides a framework for characterizing metabolic changes influencing pluripotency and cell fate. : Chandrasekaran et al. use computational modeling, metabolomics, and metabolic inhibitors to discover metabolic differences between various pluripotent stem cell states and infer their impact on stem cell fate decisions. Keywords: systems biology, stem cell biology, metabolism, genome-scale modeling, pluripotency, histone methylation, naive (ground state, primed state, cell fate, metabolic network

  2. Network Thermodynamic Curation of Human and Yeast Genome-Scale Metabolic Models

    Science.gov (United States)

    Martínez, Verónica S.; Quek, Lake-Ee; Nielsen, Lars K.

    2014-01-01

    Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. PMID:25028891

  3. Genome-scale metabolic model of Pichia pastoris with native and humanized glycosylation of recombinant proteins.

    Science.gov (United States)

    Irani, Zahra Azimzadeh; Kerkhoven, Eduard J; Shojaosadati, Seyed Abbas; Nielsen, Jens

    2016-05-01

    Pichia pastoris is used for commercial production of human therapeutic proteins, and genome-scale models of P. pastoris metabolism have been generated in the past to study the metabolism and associated protein production by this yeast. A major challenge with clinical usage of recombinant proteins produced by P. pastoris is the difference in N-glycosylation of proteins produced by humans and this yeast. However, through metabolic engineering, a P. pastoris strain capable of producing humanized N-glycosylated proteins was constructed. The current genome-scale models of P. pastoris do not address native nor humanized N-glycosylation, and we therefore developed ihGlycopastoris, an extension to the iLC915 model with both native and humanized N-glycosylation for recombinant protein production, but also an estimation of N-glycosylation of P. pastoris native proteins. This new model gives a better prediction of protein yield, demonstrates the effect of the different types of N-glycosylation of protein yield, and can be used to predict potential targets for strain improvement. The model represents a step towards a more complete description of protein production in P. pastoris, which is required for using these models to understand and optimize protein production processes. © 2015 Wiley Periodicals, Inc.

  4. Genome-scale reconstruction of metabolic networks of Lactobacillus casei ATCC 334 and 12A.

    Directory of Open Access Journals (Sweden)

    Elena Vinay-Lara

    Full Text Available Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications.

  5. Hermitian Mindlin Plate Wavelet Finite Element Method for Load Identification

    Directory of Open Access Journals (Sweden)

    Xiaofeng Xue

    2016-01-01

    Full Text Available A new Hermitian Mindlin plate wavelet element is proposed. The two-dimensional Hermitian cubic spline interpolation wavelet is substituted into finite element functions to construct frequency response function (FRF. It uses a system’s FRF and response spectrums to calculate load spectrums and then derives loads in the time domain via the inverse fast Fourier transform. By simulating different excitation cases, Hermitian cubic spline wavelets on the interval (HCSWI finite elements are used to reverse load identification in the Mindlin plate. The singular value decomposition (SVD method is adopted to solve the ill-posed inverse problem. Compared with ANSYS results, HCSWI Mindlin plate element can accurately identify the applied load. Numerical results show that the algorithm of HCSWI Mindlin plate element is effective. The accuracy of HCSWI can be verified by comparing the FRF of HCSWI and ANSYS elements with the experiment data. The experiment proves that the load identification of HCSWI Mindlin plate is effective and precise by using the FRF and response spectrums to calculate the loads.

  6. Toxicity identification evaluation methods for identification of toxicants in refinery effluents

    International Nuclear Information System (INIS)

    Barten, K.A.; Mount, D.R.; Hackett, J.R.

    1993-01-01

    During the last five years, the authors have used Toxicity Identification Evaluation (TIE) methods to characterize and identify the source(s) of toxicity in effluents from dozens of municipal and industrial facilities. In most cases, specific chemicals responsible for toxicity have been identified. Although generally successful, the initial experience was that for several refinery effluents, they were able only to qualitatively characterize the presence of organic toxicants; standard toxicant identification procedures were not able to isolate specific organic chemicals. They believe that organic toxicity in these refinery effluents is caused by multiple organic compounds rather than by just a few; evidence for this includes an inability to isolate toxicity in a small number of fractions using liquid chromatography and the presence of very large numbers of compounds in isolated fractions. There is also evidence that the toxicant(s) may be ionic, in that the toxicity of whole effluent and isolated fractions often show increasing toxicity with decreasing pH. Finally, positive-pressure filtration has also reduced toxicity in some samples. In this presentation the authors summarize their experiences with refinery effluents, focusing on typical patterns they have observed and alternative procedures they have used to better understand the nature of these toxicants

  7. ReacKnock: identifying reaction deletion strategies for microbial strain optimization based on genome-scale metabolic network.

    Directory of Open Access Journals (Sweden)

    Zixiang Xu

    Full Text Available Gene knockout has been used as a common strategy to improve microbial strains for producing chemicals. Several algorithms are available to predict the target reactions to be deleted. Most of them apply mixed integer bi-level linear programming (MIBLP based on metabolic networks, and use duality theory to transform bi-level optimization problem of large-scale MIBLP to single-level programming. However, the validity of the transformation was not proved. Solution of MIBLP depends on the structure of inner problem. If the inner problem is continuous, Karush-Kuhn-Tucker (KKT method can be used to reformulate the MIBLP to a single-level one. We adopt KKT technique in our algorithm ReacKnock to attack the intractable problem of the solution of MIBLP, demonstrated with the genome-scale metabolic network model of E. coli for producing various chemicals such as succinate, ethanol, threonine and etc. Compared to the previous methods, our algorithm is fast, stable and reliable to find the optimal solutions for all the chemical products tested, and able to provide all the alternative deletion strategies which lead to the same industrial objective.

  8. Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model

    International Nuclear Information System (INIS)

    Fang, Yilin; Scheibe, Timothy D.; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E.; Lovley, Derek R.

    2011-01-01

    The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species, multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The

  9. Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model.

    Science.gov (United States)

    Fang, Yilin; Scheibe, Timothy D; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E; Lovley, Derek R

    2011-03-25

    The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The

  10. Metabolic network reconstruction and genome-scale model of butanol-producing strain Clostridium beijerinckii NCIMB 8052

    Directory of Open Access Journals (Sweden)

    Kim Pan-Jun

    2011-08-01

    Full Text Available Abstract Background Solventogenic clostridia offer a sustainable alternative to petroleum-based production of butanol--an important chemical feedstock and potential fuel additive or replacement. C. beijerinckii is an attractive microorganism for strain design to improve butanol production because it (i naturally produces the highest recorded butanol concentrations as a byproduct of fermentation; and (ii can co-ferment pentose and hexose sugars (the primary products from lignocellulosic hydrolysis. Interrogating C. beijerinckii metabolism from a systems viewpoint using constraint-based modeling allows for simulation of the global effect of genetic modifications. Results We present the first genome-scale metabolic model (iCM925 for C. beijerinckii, containing 925 genes, 938 reactions, and 881 metabolites. To build the model we employed a semi-automated procedure that integrated genome annotation information from KEGG, BioCyc, and The SEED, and utilized computational algorithms with manual curation to improve model completeness. Interestingly, we found only a 34% overlap in reactions collected from the three databases--highlighting the importance of evaluating the predictive accuracy of the resulting genome-scale model. To validate iCM925, we conducted fermentation experiments using the NCIMB 8052 strain, and evaluated the ability of the model to simulate measured substrate uptake and product production rates. Experimentally observed fermentation profiles were found to lie within the solution space of the model; however, under an optimal growth objective, additional constraints were needed to reproduce the observed profiles--suggesting the existence of selective pressures other than optimal growth. Notably, a significantly enriched fraction of actively utilized reactions in simulations--constrained to reflect experimental rates--originated from the set of reactions that overlapped between all three databases (P = 3.52 × 10-9, Fisher's exact test

  11. Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model

    Science.gov (United States)

    Fang, Yilin; Scheibe, Timothy D.; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E.; Lovley, Derek R.

    2011-03-01

    The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The

  12. Currently used methods for identification and characterization of hemichannels.

    Science.gov (United States)

    Schalper, Kurt A; Palacios-Prado, Nicolás; Orellana, Juan A; Sáez, Juan C

    2008-05-01

    Connexins and pannexins are vertebrate transmembrane proteins that form hexameric conduits termed hemichannels. Functional hemichannels allow the diffusional transport of ions and small molecules across the plasma membrane and serve as paracrine and autocrine communication pathways. During the last decade, interest in the hemichannel field increased substantially. Today, there is evidence for the existence of connexin hemichannels in vertebrate cells and bulk of information supports their function in diverse physiological and pathological responses. Controversy regarding the molecular identity of the hemichannel type mediating many responses arose recently with the identification of pannexin-based hemichannels. Here, the authors describe the most frequently used methods for studying hemichannels in living mammalian cells and focus on those with which they have more experience. Although the available in vitro evidence is substantial, further studies and possibly new experimental approaches are required to understand the role and properties of connexin and pannexin hemichannels in vivo.

  13. [Use of THP-1 for allergens identification method validation].

    Science.gov (United States)

    Zhao, Xuezheng; Jia, Qiang; Zhang, Jun; Li, Xue; Zhang, Yanshu; Dai, Yufei

    2014-05-01

    Look for an in vitro test method to evaluate sensitization using THP-1 cells by the changes of the expression of cytokines to provide more reliable markers of the identification of sensitization. The monocyte-like THP-1 cells were induced and differentiated into THP-1-macrophages with PMA (0.1 microg/ml). The changes of expression of cytokines at different time points after the cells being treated with five known allergens, 2,4-dinitrochlorobenzene (DNCB), nickel sulfate (NiSO4), phenylene diamine (PPDA) potassium dichromate (K2Cr2O7) and toluene diisocyanate (TDI) and two non-allergens sodium dodecyl sulfate (SDS) and isopropanol (IPA) at various concentrations were evaluated. The IL-6 and TNF-alpha production was measured by ELISA. The secretion of IL-1beta and IL-8 was analyzed by Cytometric Bead Array (CBA). The section of the IL-6, TNF-alpha, IL-1beta and IL-8 were the highest when THP-1 cells were exposed to NiSO4, DNCB and K2Cr2O7 for 6h, PPDA and TDI for 12h. The production of IL-6 were approximately 40, 25, 20, 50 and 50 times for five kinds chemical allergens NiSO4, DNCB, K2Cr2O7, PPDA and TDI respectively at the optimum time points and the optimal concentration compared to the control group. The expression of TNF-alpha were 20, 12, 20, 8 and 5 times more than the control group respectively. IL-1beta secretion were 30, 60, 25, 30 and 45 times respectively compared to the control group. The production of IL-8 were approximately 15, 12, 15, 12 and 7 times respectively compared to the control group. Both non-allergens SDS and IPA significantly induced IL-6 secretion in a dose-dependent manner however SDS cause a higher production levels, approximately 20 times of the control. Therefore IL-6 may not be a reliable marker for identification of allergens. TNF-alpha, IL-1beta and IL-8 expressions did not change significantly after exposed to the two non-allergens. The test method using THP-1 cells by detecting the productions of cytokines (TNF-alpha, IL-1beta and

  14. Study of Biometric Identification Method Based on Naked Footprint

    Directory of Open Access Journals (Sweden)

    Raji Rafiu King

    2013-10-01

    Full Text Available The scale of deployment of biometric identity-verification systems has recently seen an enormous increase owing to the need for more secure and reliable way of identifying people. Footprint identification which can be defined as the measurement of footprint features for recognizing the identity of a user has surfaced recently. This study is based on a biometric personal identification method using static footprint features viz. friction ridge / texture and foot shape / silhouette. To begin with, naked footprints of users are captured; images then undergo pre processing followed by the extraction of two features; shape using Gradient Vector Flow (GVF) snake model and minutiae extraction respectively. Matching is then effected based on these two features followed by a fusion of these two results for either a reject or accept decision. Our shape matching feature is based on cosine similarity while the texture one is based on miniature score matching. The results from our research establish that the naked footprint is a credible biometric feature as two barefoot impressions of an individual match perfectly while that of two different persons shows a great deal of dissimilarity. Normal 0 false false false IN X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Doi: 10.12777/ijse.5.2.29-35 How to cite this article: King

  15. Reconstruction and analysis of a genome-scale metabolic model for Scheffersomyces stipitis

    Directory of Open Access Journals (Sweden)

    Balagurunathan Balaji

    2012-02-01

    Full Text Available Abstract Background Fermentation of xylose, the major component in hemicellulose, is essential for economic conversion of lignocellulosic biomass to fuels and chemicals. The yeast Scheffersomyces stipitis (formerly known as Pichia stipitis has the highest known native capacity for xylose fermentation and possesses several genes for lignocellulose bioconversion in its genome. Understanding the metabolism of this yeast at a global scale, by reconstructing the genome scale metabolic model, is essential for manipulating its metabolic capabilities and for successful transfer of its capabilities to other industrial microbes. Results We present a genome-scale metabolic model for Scheffersomyces stipitis, a native xylose utilizing yeast. The model was reconstructed based on genome sequence annotation, detailed experimental investigation and known yeast physiology. Macromolecular composition of Scheffersomyces stipitis biomass was estimated experimentally and its ability to grow on different carbon, nitrogen, sulphur and phosphorus sources was determined by phenotype microarrays. The compartmentalized model, developed based on an iterative procedure, accounted for 814 genes, 1371 reactions, and 971 metabolites. In silico computed growth rates were compared with high-throughput phenotyping data and the model could predict the qualitative outcomes in 74% of substrates investigated. Model simulations were used to identify the biosynthetic requirements for anaerobic growth of Scheffersomyces stipitis on glucose and the results were validated with published literature. The bottlenecks in Scheffersomyces stipitis metabolic network for xylose uptake and nucleotide cofactor recycling were identified by in silico flux variability analysis. The scope of the model in enhancing the mechanistic understanding of microbial metabolism is demonstrated by identifying a mechanism for mitochondrial respiration and oxidative phosphorylation. Conclusion The genome-scale

  16. Probing the genome-scale metabolic landscape of Bordetella pertussis, the causative agent of whooping cough.

    Science.gov (United States)

    Branco Dos Santos, Filipe; Olivier, Brett G; Boele, Joost; Smessaert, Vincent; De Rop, Philippe; Krumpochova, Petra; Klau, Gunnar W; Giera, Martin; Dehottay, Philippe; Teusink, Bas; Goffin, Philippe

    2017-08-25

    Whooping cough is a highly-contagious respiratory disease caused by Bordetella pertussi s. Despite vaccination, its incidence has been rising alarmingly, and yet, the physiology of B. pertussis remains poorly understood. We combined genome-scale metabolic reconstruction, a novel optimization algorithm and experimental data to probe the full metabolic potential of this pathogen, using strain Tohama I as a reference. Experimental validation showed that B. pertussis secretes a significant proportion of nitrogen as arginine and purine nucleosides, which may contribute to modulation of the host response. We also found that B. pertussis can be unexpectedly versatile, being able to metabolize many compounds while displaying minimal nutrient requirements. It can grow without cysteine - using inorganic sulfur sources such as thiosulfate - and it can grow on organic acids such as citrate or lactate as sole carbon sources, providing in vivo demonstration that its TCA cycle is functional. Although the metabolic reconstruction of eight additional strains indicates that the structural genes underlying this metabolic flexibility are widespread, experimental validation suggests a role of strain-specific regulatory mechanisms in shaping metabolic capabilities. Among five alternative strains tested, three were shown to grow on substrate combinations requiring a functional TCA cycle, but only one could use thiosulfate. Finally, the metabolic model was used to rationally design growth media with over two-fold improvements in pertussis toxin production. This study thus provides novel insights into B. pertussis physiology, and highlights the potential, but also limitations of models solely based on metabolic gene content. IMPORTANCE The metabolic capabilities of Bordetella pertussis - the causative agent of whooping cough - were investigated from a systems-level perspective. We constructed a comprehensive genome-scale metabolic model for B. pertussis , and challenged its predictions

  17. Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis

    Science.gov (United States)

    Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.; Du, Niu; Mih, Nathan; Diamond, Spencer; Lee, Jenny J.; Golden, Susan S.; Palsson, Bernhard O.

    2016-01-01

    The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. Here, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting in the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology. PMID:27911809

  18. Identification of sewage leaks by active remote-sensing methods

    Science.gov (United States)

    Goldshleger, Naftaly; Basson, Uri

    2016-04-01

    The increasing length of sewage pipelines, and concomitant risk of leaks due to urban and industrial growth and development is exposing the surrounding land to contamination risk and environmental harm. It is therefore important to locate such leaks in a timely manner, to minimize the damage. Advances in active remote sensing Ground Penetrating Radar (GPR) and Frequency Domain Electromagnetic (FDEM) technologies was used to identify leaking potentially responsible for pollution and to identify minor spills before they cause widespread damage. This study focused on the development of these electromagnetic methods to replace conventional acoustic methods for the identification of leaks along sewage pipes. Electromagnetic methods provide an additional advantage in that they allow mapping of the fluid-transport system in the subsurface. Leak-detection systems using GPR and FDEM are not limited to large amounts of water, but enable detecting leaks of tens of liters per hour, because they can locate increases in environmental moisture content of only a few percentage along the pipes. The importance and uniqueness of this research lies in the development of practical tools to provide a snapshot and monitoring of the spatial changes in soil moisture content up to depths of about 3-4 m, in open and paved areas, at relatively low cost, in real time or close to real time. Spatial measurements performed using GPR and FDEM systems allow monitoring many tens of thousands of measurement points per hectare, thus providing a picture of the spatial situation along pipelines and the surrounding. The main purpose of this study was to develop a method for detecting sewage leaks using the above-proposed geophysical methods, since their contaminants can severely affect public health. We focused on identifying, locating and characterizing such leaks in sewage pipes in residential and industrial areas.

  19. Moving image analysis to the cloud: A case study with a genome-scale tomographic study

    Energy Technology Data Exchange (ETDEWEB)

    Mader, Kevin [4Quant Ltd., Switzerland & Institute for Biomedical Engineering at University and ETH Zurich (Switzerland); Stampanoni, Marco [Institute for Biomedical Engineering at University and ETH Zurich, Switzerland & Swiss Light Source at Paul Scherrer Institut, Villigen (Switzerland)

    2016-01-28

    Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures.

  20. Moving image analysis to the cloud: A case study with a genome-scale tomographic study

    International Nuclear Information System (INIS)

    Mader, Kevin; Stampanoni, Marco

    2016-01-01

    Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures

  1. Principles of proteome allocation are revealed using proteomic data and genome-scale models

    DEFF Research Database (Denmark)

    Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.

    2016-01-01

    to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the "generalist" (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions......Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked...... of these sectors for the general stress response sigma factor sigma(S). Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally...

  2. Bio-succinic acid production: Escherichia coli strains design from genome-scale perspectives

    Directory of Open Access Journals (Sweden)

    Bashir Sajo Mienda

    2017-10-01

    Full Text Available Escherichia coli (E. coli has been established to be a native producer of succinic acid (a platform chemical with different applications via mixed acid fermentation reactions. Genome-scale metabolic models (GEMs of E. coli have been published with capabilities of predicting strain design strategies for the production of bio-based succinic acid. Proof-of-principle strains are fundamentally constructed as a starting point for systems strategies for industrial strains development. Here, we review for the first time, the use of E. coli GEMs for construction of proof-of-principles strains for increasing succinic acid production. Specific case studies, where E. coli proof-of-principle strains were constructed for increasing bio-based succinic acid production from glucose and glycerol carbon sources have been highlighted. In addition, a propose systems strategies for industrial strain development that could be applicable for future microbial succinic acid production guided by GEMs have been presented.

  3. Improved annotation through genome-scale metabolic modeling of Aspergillus oryzae

    DEFF Research Database (Denmark)

    Vongsangnak, Wanwipa; Olsen, Peter; Hansen, Kim

    2008-01-01

    Background: Since ancient times the filamentous fungus Aspergillus oryzae has been used in the fermentation industry for the production of fermented sauces and the production of industrial enzymes. Recently, the genome sequence of A. oryzae with 12,074 annotated genes was released but the number...... to a genome scale metabolic model of A. oryzae. Results: Our assembled EST sequences we identified 1,046 newly predicted genes in the A. oryzae genome. Furthermore, it was possible to assign putative protein functions to 398 of the newly predicted genes. Noteworthy, our annotation strategy resulted...... model was validated and shown to correctly describe the phenotypic behavior of A. oryzae grown on different carbon sources. Conclusion: A much enhanced annotation of the A. oryzae genome was performed and a genomescale metabolic model of A. oryzae was reconstructed. The model accurately predicted...

  4. A systems approach to predict oncometabolites via context-specific genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Hojung Nam

    2014-09-01

    Full Text Available Altered metabolism in cancer cells has been viewed as a passive response required for a malignant transformation. However, this view has changed through the recently described metabolic oncogenic factors: mutated isocitrate dehydrogenases (IDH, succinate dehydrogenase (SDH, and fumarate hydratase (FH that produce oncometabolites that competitively inhibit epigenetic regulation. In this study, we demonstrate in silico predictions of oncometabolites that have the potential to dysregulate epigenetic controls in nine types of cancer by incorporating massive scale genetic mutation information (collected from more than 1,700 cancer genomes, expression profiling data, and deploying Recon 2 to reconstruct context-specific genome-scale metabolic models. Our analysis predicted 15 compounds and 24 substructures of potential oncometabolites that could result from the loss-of-function and gain-of-function mutations of metabolic enzymes, respectively. These results suggest a substantial potential for discovering unidentified oncometabolites in various forms of cancers.

  5. Genome-scale analysis of positional clustering of mouse testis-specific genes

    Directory of Open Access Journals (Sweden)

    Lee Bernett TK

    2005-01-01

    Full Text Available Abstract Background Genes are not randomly distributed on a chromosome as they were thought even after removal of tandem repeats. The positional clustering of co-expressed genes is known in prokaryotes and recently reported in several eukaryotic organisms such as Caenorhabditis elegans, Drosophila melanogaster, and Homo sapiens. In order to further investigate the mode of tissue-specific gene clustering in higher eukaryotes, we have performed a genome-scale analysis of positional clustering of the mouse testis-specific genes. Results Our computational analysis shows that a large proportion of testis-specific genes are clustered in groups of 2 to 5 genes in the mouse genome. The number of clusters is much higher than expected by chance even after removal of tandem repeats. Conclusion Our result suggests that testis-specific genes tend to cluster on the mouse chromosomes. This provides another piece of evidence for the hypothesis that clusters of tissue-specific genes do exist.

  6. Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression

    DEFF Research Database (Denmark)

    Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.

    2017-01-01

    orders of magnitude. Data values also have greatly varying magnitudes. Standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers based on rational arithmetic require a near-optimal warm start to be practical on large problems (current ME......Constraint-Based Reconstruction and Analysis (COBRA) is currently the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many...... models have 70,000 constraints and variables and will grow larger). We have developed a quadrupleprecision version of our linear and nonlinear optimizer MINOS, and a solution procedure (DQQ) involving Double and Quad MINOS that achieves reliability and efficiency for ME models and other challenging...

  7. A Parameter Identification Method for Helicopter Noise Source Identification and Physics-Based Semi-Empirical Modeling

    Science.gov (United States)

    Greenwood, Eric, II; Schmitz, Fredric H.

    2010-01-01

    A new physics-based parameter identification method for rotor harmonic noise sources is developed using an acoustic inverse simulation technique. This new method allows for the identification of individual rotor harmonic noise sources and allows them to be characterized in terms of their individual non-dimensional governing parameters. This new method is applied to both wind tunnel measurements and ground noise measurements of two-bladed rotors. The method is shown to match the parametric trends of main rotor Blade-Vortex Interaction (BVI) noise, allowing accurate estimates of BVI noise to be made for operating conditions based on a small number of measurements taken at different operating conditions.

  8. Zea mays iRS1563: A Comprehensive Genome-Scale Metabolic Reconstruction of Maize Metabolism

    Science.gov (United States)

    Saha, Rajib; Suthers, Patrick F.; Maranas, Costas D.

    2011-01-01

    The scope and breadth of genome-scale metabolic reconstructions have continued to expand over the last decade. Herein, we introduce a genome-scale model for a plant with direct applications to food and bioenergy production (i.e., maize). Maize annotation is still underway, which introduces significant challenges in the association of metabolic functions to genes. The developed model is designed to meet rigorous standards on gene-protein-reaction (GPR) associations, elementally and charged balanced reactions and a biomass reaction abstracting the relative contribution of all biomass constituents. The metabolic network contains 1,563 genes and 1,825 metabolites involved in 1,985 reactions from primary and secondary maize metabolism. For approximately 42% of the reactions direct literature evidence for the participation of the reaction in maize was found. As many as 445 reactions and 369 metabolites are unique to the maize model compared to the AraGEM model for A. thaliana. 674 metabolites and 893 reactions are present in Zea mays iRS1563 that are not accounted for in maize C4GEM. All reactions are elementally and charged balanced and localized into six different compartments (i.e., cytoplasm, mitochondrion, plastid, peroxisome, vacuole and extracellular). GPR associations are also established based on the functional annotation information and homology prediction accounting for monofunctional, multifunctional and multimeric proteins, isozymes and protein complexes. We describe results from performing flux balance analysis under different physiological conditions, (i.e., photosynthesis, photorespiration and respiration) of a C4 plant and also explore model predictions against experimental observations for two naturally occurring mutants (i.e., bm1 and bm3). The developed model corresponds to the largest and more complete to-date effort at cataloguing metabolism for a plant species. PMID:21755001

  9. Network thermodynamic curation of human and yeast genome-scale metabolic models.

    Science.gov (United States)

    Martínez, Verónica S; Quek, Lake-Ee; Nielsen, Lars K

    2014-07-15

    Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  10. Genome-scale model guided design of Propionibacterium for enhanced propionic acid production.

    Science.gov (United States)

    Navone, Laura; McCubbin, Tim; Gonzalez-Garcia, Ricardo A; Nielsen, Lars K; Marcellin, Esteban

    2018-06-01

    Production of propionic acid by fermentation of propionibacteria has gained increasing attention in the past few years. However, biomanufacturing of propionic acid cannot compete with the current oxo-petrochemical synthesis process due to its well-established infrastructure, low oil prices and the high downstream purification costs of microbial production. Strain improvement to increase propionic acid yield is the best alternative to reduce downstream purification costs. The recent generation of genome-scale models for a number of Propionibacterium species facilitates the rational design of metabolic engineering strategies and provides a new opportunity to explore the metabolic potential of the Wood-Werkman cycle. Previous strategies for strain improvement have individually targeted acid tolerance, rate of propionate production or minimisation of by-products. Here we used the P. freudenreichii subsp . shermanii and the pan- Propionibacterium genome-scale metabolic models (GEMs) to simultaneously target these combined issues. This was achieved by focussing on strategies which yield higher energies and directly suppress acetate formation. Using P. freudenreichii subsp . shermanii , two strategies were assessed. The first tested the ability to manipulate the redox balance to favour propionate production by over-expressing the first two enzymes of the pentose-phosphate pathway (PPP), Zwf (glucose-6-phosphate 1-dehydrogenase) and Pgl (6-phosphogluconolactonase). Results showed a 4-fold increase in propionate to acetate ratio during the exponential growth phase. Secondly, the ability to enhance the energy yield from propionate production by over-expressing an ATP-dependent phosphoenolpyruvate carboxykinase (PEPCK) and sodium-pumping methylmalonyl-CoA decarboxylase (MMD) was tested, which extended the exponential growth phase. Together, these strategies demonstrate that in silico design strategies are predictive and can be used to reduce by-product formation in

  11. Genome-scale consequences of cofactor balancing in engineered pentose utilization pathways in Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    Amit Ghosh

    Full Text Available Biofuels derived from lignocellulosic biomass offer promising alternative renewable energy sources for transportation fuels. Significant effort has been made to engineer Saccharomyces cerevisiae to efficiently ferment pentose sugars such as D-xylose and L-arabinose into biofuels such as ethanol through heterologous expression of the fungal D-xylose and L-arabinose pathways. However, one of the major bottlenecks in these fungal pathways is that the cofactors are not balanced, which contributes to inefficient utilization of pentose sugars. We utilized a genome-scale model of S. cerevisiae to predict the maximal achievable growth rate for cofactor balanced and imbalanced D-xylose and L-arabinose utilization pathways. Dynamic flux balance analysis (DFBA was used to simulate batch fermentation of glucose, D-xylose, and L-arabinose. The dynamic models and experimental results are in good agreement for the wild type and for the engineered D-xylose utilization pathway. Cofactor balancing the engineered D-xylose and L-arabinose utilization pathways simulated an increase in ethanol batch production of 24.7% while simultaneously reducing the predicted substrate utilization time by 70%. Furthermore, the effects of cofactor balancing the engineered pentose utilization pathways were evaluated throughout the genome-scale metabolic network. This work not only provides new insights to the global network effects of cofactor balancing but also provides useful guidelines for engineering a recombinant yeast strain with cofactor balanced engineered pathways that efficiently co-utilizes pentose and hexose sugars for biofuels production. Experimental switching of cofactor usage in enzymes has been demonstrated, but is a time-consuming effort. Therefore, systems biology models that can predict the likely outcome of such strain engineering efforts are highly useful for motivating which efforts are likely to be worth the significant time investment.

  12. Comparison of PCR method with the culture method for identification of gonococci from endocervical swabs

    Directory of Open Access Journals (Sweden)

    Alam A

    2002-01-01

    Full Text Available Gonococcal infection remains still a major cause of morbidity among sexually active individuals. Diagnosis of the infection in a female case is more difficult than that in a male. This was a prospective study among 269 female commercial sex workers (CSWs to screen them for gonococcal infection, comparing the rapid method of identification of gonococci by polymerase chain reaction (PCR with the selective culture method. A total of 92 (34.2% CSWs were identified positive for Neisseria gonorrhoeae by combination of the two methods. The PCR method identified 87 of the specimens to harbour cppB gene of N. gonorrhoeae, whereas culture method identified 83 specimens showing colonies of gonococci. Taking into consideration of the total positive cases (92, the PCR method showed a sensitivity of 94.57%, whereas sensitivity of culture method was 90.22%. The selective culture method appears to be the most applicable in the identification of gonococci from clinical specimens, particularly in the less resourceful countries like Bangladesh.

  13. Modeling Method for Increased Precision and Scope of Directly Measurable Fluxes at a Genome-Scale

    DEFF Research Database (Denmark)

    McCloskey, Douglas; Young, Jamey D.; Xu, Sibei

    2016-01-01

    pathways of traditional MFA models and also covers the additional pathways of purine, pyrimidine, isoprenoid, methionine, riboflavin, coenzyme A, and folate, as well as other biosynthetic pathways. When evaluating the iDM2014 using a set of measured intracellular intermediate and cofactor mass isotopomer...

  14. Primary Identification Methods and their Effectiveness in Mass Disaster Situations: A Literature Review

    Directory of Open Access Journals (Sweden)

    Naiara M. Gaglietti

    2017-06-01

    Full Text Available Mass disasters generally result in an elevated number of casualties that need identification. The primary identification methods listed by INTERPOL (DNA, fingerprint and forensic dentistry have a very important role in helping and speeding up the victim identification process. The present study sought to report mass destruction cases found in the literature published from 2005 to 2015 that have used the primary human identification methods. This study has been done as a literature review using the keywords: disasters, natural disasters, disaster victims, and human identification in a total of 16 selected papers and 13 listed disasters. It has been concluded that the primary identification methods are capable and efficient to perform a safe and satisfactory identification of mass disasters victims, used both separately or in combination.

  15. Rapid Methods for the Laboratory Identification of Pathogenic Microorganisms.

    Science.gov (United States)

    1982-09-01

    coli Hemophilus influenzae Bacillus anthracis Bacillus circulans Bacillus coagulans Bacillus cereus T Candida albicans Cryptococcus neoformans Legionel...reveree aide If neceeeary and Identify by block number) Lectins: Rapid Identification, Bacillus anthracisjCryptococcus " neoformans. Neisseria...field-type kit for the rapid identification of Bacillus anthracis. We have shown that certain lectins will selectively interact with B. anthracis

  16. The Detection of Subsynchronous Oscillation in HVDC Based on the Stochastic Subspace Identification Method

    Directory of Open Access Journals (Sweden)

    Chen Shi

    2014-01-01

    Full Text Available Subsynchronous oscillation (SSO usually caused by series compensation, power system stabilizer (PSS, high voltage direct current transmission (HVDC and other power electronic equipment, which will affect the safe operation of generator shafting even the system. It is very important to identify the modal parameters of SSO to take effective control strategies as well. Since the identification accuracy of traditional methods are not high enough, the stochastic subspace identification (SSI method is proposed to improve the identification accuracy of subsynchronous oscillation modal. The stochastic subspace identification method was compared with the other two methods on subsynchronous oscillation IEEE benchmark model and Xiang-Shang HVDC system model, the simulation results show that the stochastic subspace identification method has the advantages of high identification precision, high operation efficiency and strong ability of anti-noise.

  17. Enhanced detection method for corneal protein identification using shotgun proteomics

    Directory of Open Access Journals (Sweden)

    Schlager John J

    2009-06-01

    Full Text Available Abstract Background The cornea is a specialized transparent connective tissue responsible for the majority of light refraction and image focus for the retina. There are three main layers of the cornea: the epithelium that is exposed and acts as a protective barrier for the eye, the center stroma consisting of parallel collagen fibrils that refract light, and the endothelium that is responsible for hydration of the cornea from the aqueous humor. Normal cornea is an immunologically privileged tissue devoid of blood vessels, but injury can produce a loss of these conditions causing invasion of other processes that degrade the homeostatic properties resulting in a decrease in the amount of light refracted onto the retina. Determining a measure and drift of phenotypic cornea state from normal to an injured or diseased state requires knowledge of the existing protein signature within the tissue. In the study of corneal proteins, proteomics procedures have typically involved the pulverization of the entire cornea prior to analysis. Separation of the epithelium and endothelium from the core stroma and performing separate shotgun proteomics using liquid chromatography/mass spectrometry results in identification of many more proteins than previously employed methods using complete pulverized cornea. Results Rabbit corneas were purchased, the epithelium and endothelium regions were removed, proteins processed and separately analyzed using liquid chromatography/mass spectrometry. Proteins identified from separate layers were compared against results from complete corneal samples. Protein digests were separated using a six hour liquid chromatographic gradient and ion-trap mass spectrometry used for detection of eluted peptide fractions. The SEQUEST database search results were filtered to allow only proteins with match probabilities of equal or better than 10-3 and peptides with a probability of 10-2 or less with at least two unique peptides isolated within

  18. Genome-scale characterization of RNA tertiary structures and their functional impact by RNA solvent accessibility prediction.

    Science.gov (United States)

    Yang, Yuedong; Li, Xiaomei; Zhao, Huiying; Zhan, Jian; Wang, Jihua; Zhou, Yaoqi

    2017-01-01

    As most RNA structures are elusive to structure determination, obtaining solvent accessible surface areas (ASAs) of nucleotides in an RNA structure is an important first step to characterize potential functional sites and core structural regions. Here, we developed RNAsnap, the first machine-learning method trained on protein-bound RNA structures for solvent accessibility prediction. Built on sequence profiles from multiple sequence alignment (RNAsnap-prof), the method provided robust prediction in fivefold cross-validation and an independent test (Pearson correlation coefficients, r, between predicted and actual ASA values are 0.66 and 0.63, respectively). Application of the method to 6178 mRNAs revealed its positive correlation to mRNA accessibility by dimethyl sulphate (DMS) experimentally measured in vivo (r = 0.37) but not in vitro (r = 0.07), despite the lack of training on mRNAs and the fact that DMS accessibility is only an approximation to solvent accessibility. We further found strong association across coding and noncoding regions between predicted solvent accessibility of the mutation site of a single nucleotide variant (SNV) and the frequency of that variant in the population for 2.2 million SNVs obtained in the 1000 Genomes Project. Moreover, mapping solvent accessibility of RNAs to the human genome indicated that introns, 5' cap of 5' and 3' cap of 3' untranslated regions, are more solvent accessible, consistent with their respective functional roles. These results support conformational selections as the mechanism for the formation of RNA-protein complexes and highlight the utility of genome-scale characterization of RNA tertiary structures by RNAsnap. The server and its stand-alone downloadable version are available at http://sparks-lab.org. © 2016 Yang et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  19. A method for model identification and parameter estimation

    International Nuclear Information System (INIS)

    Bambach, M; Heinkenschloss, M; Herty, M

    2013-01-01

    We propose and analyze a new method for the identification of a parameter-dependent model that best describes a given system. This problem arises, for example, in the mathematical modeling of material behavior where several competing constitutive equations are available to describe a given material. In this case, the models are differential equations that arise from the different constitutive equations, and the unknown parameters are coefficients in the constitutive equations. One has to determine the best-suited constitutive equations for a given material and application from experiments. We assume that the true model is one of the N possible parameter-dependent models. To identify the correct model and the corresponding parameters, we can perform experiments, where for each experiment we prescribe an input to the system and observe a part of the system state. Our approach consists of two stages. In the first stage, for each pair of models we determine the experiment, i.e. system input and observation, that best differentiates between the two models, and measure the distance between the two models. Then we conduct N(N − 1) or, depending on the approach taken, N(N − 1)/2 experiments and use the result of the experiments as well as the previously computed model distances to determine the true model. We provide sufficient conditions on the model distances and measurement errors which guarantee that our approach identifies the correct model. Given the model, we identify the corresponding model parameters in the second stage. The problem in the second stage is a standard parameter estimation problem and we use a method suitable for the given application. We illustrate our approach on three examples, including one where the models are elliptic partial differential equations with different parameterized right-hand sides and an example where we identify the constitutive equation in a problem from computational viscoplasticity. (paper)

  20. Nuclear material enrichment identification method based on cross-correlation and high order spectra

    International Nuclear Information System (INIS)

    Yang Fan; Wei Biao; Feng Peng; Mi Deling; Ren Yong

    2013-01-01

    In order to enhance the sensitivity of nuclear material identification system (NMIS) against the change of nuclear material enrichment, the principle of high order statistic feature is introduced and applied to traditional NMIS. We present a new enrichment identification method based on cross-correlation and high order spectrum algorithm. By applying the identification method to NMIS, the 3D graphs with nuclear material character are presented and can be used as new signatures to identify the enrichment of nuclear materials. The simulation result shows that the identification method could suppress the background noises, electronic system noises, and improve the sensitivity against enrichment change to exponential order with no system structure modification. (authors)

  1. Rapid method for identification of transgenic fish zygosity

    Directory of Open Access Journals (Sweden)

    . Alimuddin

    2007-07-01

    Full Text Available Identification of zygosity in transgenik fish is normally achieved by PCR analysis with genomic DNA template extracted from the tissue of progenies which are derived by mating the transgenic fish and wild-type counterpart.  This method needs relatively large amounts of fish material and is time- and labor-intensive. New approaches addressing this problem could be of great help for fish biotechnologists.  In this experiment, we applied a quantitative real-time PCR (qr-PCR method to analyze zygosity in a stable line of transgenic zebrafish (Danio rerio carrying masu salmon, Oncorhynchus masou D6-desaturase-like gene. The qr-PCR was performed using iQ SYBR Green Supermix in the iCycler iQ Real-time PCR Detection System (Bio-Rad Laboratories, USA.  Data were analyzed using the comparative cycle threshold method.  The results demonstrated a clear-cut identification of all transgenic fish (n=20 classified as a homozygous or heterozygous.  Mating of those fish with wild-type had revealed transgene transmission to the offspring following expected Mendelian laws. Thus, we found that the qTR-PCR to be effective for a rapid and precise determination of zygosity in transgenic fish. This technique could be useful in the establishment of breeding programs for mass transgenic fish production and in experiments in which zygosity effect could have a functional impact. Keywords: quantitative real-time PCR; zygosity; transgenic fish; mass production   ABSTRAK Identifikasi sigositas ikan transgenik biasanya dilakukan menggunakan analisa PCR dengan cetakan DNA genomik yang diekstraksi dari jaringan ikan hasil persilangan antara ikan transgenik dan ikan normal.   Metode ini memerlukan ikan dalam jumlah yang banyak, dan juga waktu serta tenaga.  Pendekatan baru untuk mengatasi masalah tersebut akan memberikan manfaat besar kepada peneliti bioteknologi perikanan.  Pada penelitian ini, kami menggunakan metode PCR real-time kuantitatif (krt-PCR untuk

  2. The architecture of ArgR-DNA complexes at the genome-scale in Escherichia coli

    DEFF Research Database (Denmark)

    Cho, Suhyung; Cho, Yoo-Bok; Kang, Taek Jin

    2015-01-01

    DNA-binding motifs that are recognized by transcription factors (TFs) have been well studied; however, challenges remain in determining the in vivo architecture of TF-DNA complexes on a genome-scale. Here, we determined the in vivo architecture of Escherichia coli arginine repressor (ArgR)-DNA co...

  3. Analysis of growth of Lactobacillus plantarum WCFS1 on a complex medium using a genome-scale metabolic model

    NARCIS (Netherlands)

    Teusink, B.; Wiersma, A.; Molenaar, D.; Francke, C.; Vos, de W.M.; Siezen, R.J.; Smid, E.J.

    2006-01-01

    A genome-scale metabolic model of the lactic acid bacterium Lactobacillus plantarum WCFS1 was constructed based on genomic content and experimental data. The complete model includes 721 genes, 643 reactions, and 531 metabolites. Different stoichiometric modeling techniques were used for

  4. Using a genome-scale metabolic network model to elucidate the mechanism of chloroquine action in Plasmodium falciparum

    Directory of Open Access Journals (Sweden)

    Shivendra G. Tewari

    2017-08-01

    Full Text Available Chloroquine, long the default first-line treatment against malaria, is now abandoned in large parts of the world because of widespread drug-resistance in Plasmodium falciparum. In spite of its importance as a cost-effective and efficient drug, a coherent understanding of the cellular mechanisms affected by chloroquine and how they influence the fitness and survival of the parasite remains elusive. Here, we used a systems biology approach to integrate genome-scale transcriptomics to map out the effects of chloroquine, identify targeted metabolic pathways, and translate these findings into mechanistic insights. Specifically, we first developed a method that integrates transcriptomic and metabolomic data, which we independently validated against a recently published set of such data for Krebs-cycle mutants of P. falciparum. We then used the method to calculate the effect of chloroquine treatment on the metabolic flux profiles of P. falciparum during the intraerythrocytic developmental cycle. The model predicted dose-dependent inhibition of DNA replication, in agreement with earlier experimental results for both drug-sensitive and drug-resistant P. falciparum strains. Our simulations also corroborated experimental findings that suggest differences in chloroquine sensitivity between ring- and schizont-stage P. falciparum. Our analysis also suggests that metabolic fluxes that govern reduced thioredoxin and phosphoenolpyruvate synthesis are significantly decreased and are pivotal to chloroquine-based inhibition of P. falciparum DNA replication. The consequences of impaired phosphoenolpyruvate synthesis and redox metabolism are reduced carbon fixation and increased oxidative stress, respectively, both of which eventually facilitate killing of the parasite. Our analysis suggests that a combination of chloroquine (or an analogue and another drug, which inhibits carbon fixation and/or increases oxidative stress, should increase the clearance of P

  5. The impact of parameter identification methods on drug therapy control in an intensive care unit

    NARCIS (Netherlands)

    Hann, C.E.; Chase, J.G.; Ypma, M.F.; Elfring, J.; Nor, N.H.M.; Lawrence, P.; Shaw, G.M.

    2008-01-01

    This paper investigates the impact of fast parameter identification methods, which do not require any forward simulations, on model-based glucose control, using retrospective data in the Christchurch Hospital Intensive Care Unit. The integral-based identification method has been previously

  6. Accurate Lithium-ion battery parameter estimation with continuous-time system identification methods

    International Nuclear Information System (INIS)

    Xia, Bing; Zhao, Xin; Callafon, Raymond de; Garnier, Hugues; Nguyen, Truong; Mi, Chris

    2016-01-01

    Highlights: • Continuous-time system identification is applied in Lithium-ion battery modeling. • Continuous-time and discrete-time identification methods are compared in detail. • The instrumental variable method is employed to further improve the estimation. • Simulations and experiments validate the advantages of continuous-time methods. - Abstract: The modeling of Lithium-ion batteries usually utilizes discrete-time system identification methods to estimate parameters of discrete models. However, in real applications, there is a fundamental limitation of the discrete-time methods in dealing with sensitivity when the system is stiff and the storage resolutions are limited. To overcome this problem, this paper adopts direct continuous-time system identification methods to estimate the parameters of equivalent circuit models for Lithium-ion batteries. Compared with discrete-time system identification methods, the continuous-time system identification methods provide more accurate estimates to both fast and slow dynamics in battery systems and are less sensitive to disturbances. A case of a 2"n"d-order equivalent circuit model is studied which shows that the continuous-time estimates are more robust to high sampling rates, measurement noises and rounding errors. In addition, the estimation by the conventional continuous-time least squares method is further improved in the case of noisy output measurement by introducing the instrumental variable method. Simulation and experiment results validate the analysis and demonstrate the advantages of the continuous-time system identification methods in battery applications.

  7. Expanding a dynamic flux balance model of yeast fermentation to genome-scale

    Science.gov (United States)

    2011-01-01

    Background Yeast is considered to be a workhorse of the biotechnology industry for the production of many value-added chemicals, alcoholic beverages and biofuels. Optimization of the fermentation is a challenging task that greatly benefits from dynamic models able to accurately describe and predict the fermentation profile and resulting products under different genetic and environmental conditions. In this article, we developed and validated a genome-scale dynamic flux balance model, using experimentally determined kinetic constraints. Results Appropriate equations for maintenance, biomass composition, anaerobic metabolism and nutrient uptake are key to improve model performance, especially for predicting glycerol and ethanol synthesis. Prediction profiles of synthesis and consumption of the main metabolites involved in alcoholic fermentation closely agreed with experimental data obtained from numerous lab and industrial fermentations under different environmental conditions. Finally, fermentation simulations of genetically engineered yeasts closely reproduced previously reported experimental results regarding final concentrations of the main fermentation products such as ethanol and glycerol. Conclusion A useful tool to describe, understand and predict metabolite production in batch yeast cultures was developed. The resulting model, if used wisely, could help to search for new metabolic engineering strategies to manage ethanol content in batch fermentations. PMID:21595919

  8. Data partitioning enables the use of standard SOAP Web Services in genome-scale workflows.

    Science.gov (United States)

    Sztromwasser, Pawel; Puntervoll, Pål; Petersen, Kjell

    2011-07-26

    Biological databases and computational biology tools are provided by research groups around the world, and made accessible on the Web. Combining these resources is a common practice in bioinformatics, but integration of heterogeneous and often distributed tools and datasets can be challenging. To date, this challenge has been commonly addressed in a pragmatic way, by tedious and error-prone scripting. Recently however a more reliable technique has been identified and proposed as the platform that would tie together bioinformatics resources, namely Web Services. In the last decade the Web Services have spread wide in bioinformatics, and earned the title of recommended technology. However, in the era of high-throughput experimentation, a major concern regarding Web Services is their ability to handle large-scale data traffic. We propose a stream-like communication pattern for standard SOAP Web Services, that enables efficient flow of large data traffic between a workflow orchestrator and Web Services. We evaluated the data-partitioning strategy by comparing it with typical communication patterns on an example pipeline for genomic sequence annotation. The results show that data-partitioning lowers resource demands of services and increases their throughput, which in consequence allows to execute in-silico experiments on genome-scale, using standard SOAP Web Services and workflows. As a proof-of-principle we annotated an RNA-seq dataset using a plain BPEL workflow engine.

  9. Ensembl Genomes: an integrative resource for genome-scale data from non-vertebrate species.

    Science.gov (United States)

    Kersey, Paul J; Staines, Daniel M; Lawson, Daniel; Kulesha, Eugene; Derwent, Paul; Humphrey, Jay C; Hughes, Daniel S T; Keenan, Stephan; Kerhornou, Arnaud; Koscielny, Gautier; Langridge, Nicholas; McDowall, Mark D; Megy, Karine; Maheswari, Uma; Nuhn, Michael; Paulini, Michael; Pedro, Helder; Toneva, Iliana; Wilson, Derek; Yates, Andrew; Birney, Ewan

    2012-01-01

    Ensembl Genomes (http://www.ensemblgenomes.org) is an integrative resource for genome-scale data from non-vertebrate species. The project exploits and extends technology (for genome annotation, analysis and dissemination) developed in the context of the (vertebrate-focused) Ensembl project and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. Since its launch in 2009, Ensembl Genomes has undergone rapid expansion, with the goal of providing coverage of all major experimental organisms, and additionally including taxonomic reference points to provide the evolutionary context in which genes can be understood. Against the backdrop of a continuing increase in genome sequencing activities in all parts of the tree of life, we seek to work, wherever possible, with the communities actively generating and using data, and are participants in a growing range of collaborations involved in the annotation and analysis of genomes.

  10. Revisiting the chlorophyll biosynthesis pathway using genome scale metabolic model of Oryza sativa japonica

    Science.gov (United States)

    Chatterjee, Ankita; Kundu, Sudip

    2015-01-01

    Chlorophyll is one of the most important pigments present in green plants and rice is one of the major food crops consumed worldwide. We curated the existing genome scale metabolic model (GSM) of rice leaf by incorporating new compartment, reactions and transporters. We used this modified GSM to elucidate how the chlorophyll is synthesized in a leaf through a series of bio-chemical reactions spanned over different organelles using inorganic macronutrients and light energy. We predicted the essential reactions and the associated genes of chlorophyll synthesis and validated against the existing experimental evidences. Further, ammonia is known to be the preferred source of nitrogen in rice paddy fields. The ammonia entering into the plant is assimilated in the root and leaf. The focus of the present work is centered on rice leaf metabolism. We studied the relative importance of ammonia transporters through the chloroplast and the cytosol and their interlink with other intracellular transporters. Ammonia assimilation in the leaves takes place by the enzyme glutamine synthetase (GS) which is present in the cytosol (GS1) and chloroplast (GS2). Our results provided possible explanation why GS2 mutants show normal growth under minimum photorespiration and appear chlorotic when exposed to air. PMID:26443104

  11. Construction and analysis of a genome-scale metabolic network for Bacillus licheniformis WX-02.

    Science.gov (United States)

    Guo, Jing; Zhang, Hong; Wang, Cheng; Chang, Ji-Wei; Chen, Ling-Ling

    2016-05-01

    We constructed the genome-scale metabolic network of Bacillus licheniformis (B. licheniformis) WX-02 by combining genomic annotation, high-throughput phenotype microarray (PM) experiments and literature-based metabolic information. The accuracy of the metabolic network was assessed by an OmniLog PM experiment. The final metabolic model iWX1009 contains 1009 genes, 1141 metabolites and 1762 reactions, and the predicted metabolic phenotypes showed an agreement rate of 76.8% with experimental PM data. In addition, key metabolic features such as growth yield, utilization of different substrates and essential genes were identified by flux balance analysis. A total of 195 essential genes were predicted from LB medium, among which 149 were verified with the experimental essential gene set of B. subtilis 168. With the removal of 5 reactions from the network, pathways for poly-γ-glutamic acid (γ-PGA) synthesis were optimized and the γ-PGA yield reached 83.8 mmol/h. Furthermore, the important metabolites and pathways related to γ-PGA synthesis and bacterium growth were comprehensively analyzed. The present study provides valuable clues for exploring the metabolisms and metabolic regulation of γ-PGA synthesis in B. licheniformis WX-02. Copyright © 2016 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

  12. Novel insights into obesity and diabetes through genome-scale metabolic modeling

    Directory of Open Access Journals (Sweden)

    Leif eVäremo

    2013-04-01

    Full Text Available The growing prevalence of metabolic diseases, such as obesity and diabetes, are putting a high strain on global healthcare systems as well as increasing the demand for efficient treatment strategies. More than 360 million people worldwide are suffering from type 2 diabetes and, with the current trends, the projection is that 10% of the global adult population will be affected by 2030. In light of the systemic properties of metabolic diseases as well as the interconnected nature of metabolism, it is necessary to begin taking a holistic approach to study these diseases. Human genome-scale metabolic models (GEMs are topological and mathematical representations of cell metabolism and have proven to be valuable tools in the area of systems biology. Successful applications of GEMs include the process of gaining further biological and mechanistic understanding of diseases, finding potential biomarkers and identifying new drug targets. This review will focus on the modeling of human metabolism in the field of obesity and diabetes, showing its vast range of applications of clinical importance as well as point out future challenges.

  13. Genome-scale modeling enables metabolic engineering of Saccharomyces cerevisiae for succinic acid production.

    Science.gov (United States)

    Agren, Rasmus; Otero, José Manuel; Nielsen, Jens

    2013-07-01

    In this work, we describe the application of a genome-scale metabolic model and flux balance analysis for the prediction of succinic acid overproduction strategies in Saccharomyces cerevisiae. The top three single gene deletion strategies, Δmdh1, Δoac1, and Δdic1, were tested using knock-out strains cultivated anaerobically on glucose, coupled with physiological and DNA microarray characterization. While Δmdh1 and Δoac1 strains failed to produce succinate, Δdic1 produced 0.02 C-mol/C-mol glucose, in close agreement with model predictions (0.03 C-mol/C-mol glucose). Transcriptional profiling suggests that succinate formation is coupled to mitochondrial redox balancing, and more specifically, reductive TCA cycle activity. While far from industrial titers, this proof-of-concept suggests that in silico predictions coupled with experimental validation can be used to identify novel and non-intuitive metabolic engineering strategies.

  14. Data partitioning enables the use of standard SOAP Web Services in genome-scale workflows

    Directory of Open Access Journals (Sweden)

    Sztromwasser Paweł

    2011-06-01

    Full Text Available Biological databases and computational biology tools are provided by research groups around the world, and made accessible on the Web. Combining these resources is a common practice in bioinformatics, but integration of heterogeneous and often distributed tools and datasets can be challenging. To date, this challenge has been commonly addressed in a pragmatic way, by tedious and error-prone scripting. Recently however a more reliable technique has been identified and proposed as the platform that would tie together bioinformatics resources, namely Web Services. In the last decade the Web Services have spread wide in bioinformatics, and earned the title of recommended technology. However, in the era of high-throughput experimentation, a major concern regarding Web Services is their ability to handle large-scale data traffic. We propose a stream-like communication pattern for standard SOAP Web Services, that enables efficient flow of large data traffic between a workflow orchestrator and Web Services. We evaluated the data-partitioning strategy by comparing it with typical communication patterns on an example pipeline for genomic sequence annotation. The results show that data-partitioning lowers resource demands of services and increases their throughput, which in consequence allows to execute in-silico experiments on genome-scale, using standard SOAP Web Services and workflows. As a proof-of-principle we annotated an RNA-seq dataset using a plain BPEL workflow engine.

  15. A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism

    KAUST Repository

    Hefzi, Hooman

    2016-11-23

    Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess optimization, we reconstructed the metabolic pathways in CHO and associated them with >1,700 genes in the Cricetulus griseus genome. The genome-scale metabolic model based on this reconstruction, iCHO1766, and cell-line-specific models for CHO-K1, CHO-S, and CHO-DG44 cells provide the biochemical basis of growth and recombinant protein production. The models accurately predict growth phenotypes and known auxotrophies in CHO cells. With the models, we quantify the protein synthesis capacity of CHO cells and demonstrate that common bioprocess treatments, such as histone deacetylase inhibitors, inefficiently increase product yield. However, our simulations show that the metabolic resources in CHO are more than three times more efficiently utilized for growth or recombinant protein synthesis following targeted efforts to engineer the CHO secretory pathway. This model will further accelerate CHO cell engineering and help optimize bioprocesses.

  16. Genome-scale metabolic network validation of Shewanella oneidensis using transposon insertion frequency analysis.

    Directory of Open Access Journals (Sweden)

    Hong Yang

    2014-09-01

    Full Text Available Transposon mutagenesis, in combination with parallel sequencing, is becoming a powerful tool for en-masse mutant analysis. A probability generating function was used to explain observed miniHimar transposon insertion patterns, and gene essentiality calls were made by transposon insertion frequency analysis (TIFA. TIFA incorporated the observed genome and sequence motif bias of the miniHimar transposon. The gene essentiality calls were compared to: 1 previous genome-wide direct gene-essentiality assignments; and, 2 flux balance analysis (FBA predictions from an existing genome-scale metabolic model of Shewanella oneidensis MR-1. A three-way comparison between FBA, TIFA, and the direct essentiality calls was made to validate the TIFA approach. The refinement in the interpretation of observed transposon insertions demonstrated that genes without insertions are not necessarily essential, and that genes that contain insertions are not always nonessential. The TIFA calls were in reasonable agreement with direct essentiality calls for S. oneidensis, but agreed more closely with E. coli essentiality calls for orthologs. The TIFA gene essentiality calls were in good agreement with the MR-1 FBA essentiality predictions, and the agreement between TIFA and FBA predictions was substantially better than between the FBA and the direct gene essentiality predictions.

  17. GMATA: An Integrated Software Package for Genome-Scale SSR Mining, Marker Development and Viewing.

    Science.gov (United States)

    Wang, Xuewen; Wang, Le

    2016-01-01

    Simple sequence repeats (SSRs), also referred to as microsatellites, are highly variable tandem DNAs that are widely used as genetic markers. The increasing availability of whole-genome and transcript sequences provides information resources for SSR marker development. However, efficient software is required to efficiently identify and display SSR information along with other gene features at a genome scale. We developed novel software package Genome-wide Microsatellite Analyzing Tool Package (GMATA) integrating SSR mining, statistical analysis and plotting, marker design, polymorphism screening and marker transferability, and enabled simultaneously display SSR markers with other genome features. GMATA applies novel strategies for SSR analysis and primer design in large genomes, which allows GMATA to perform faster calculation and provides more accurate results than existing tools. Our package is also capable of processing DNA sequences of any size on a standard computer. GMATA is user friendly, only requires mouse clicks or types inputs on the command line, and is executable in multiple computing platforms. We demonstrated the application of GMATA in plants genomes and reveal a novel distribution pattern of SSRs in 15 grass genomes. The most abundant motifs are dimer GA/TC, the A/T monomer and the GCG/CGC trimer, rather than the rich G/C content in DNA sequence. We also revealed that SSR count is a linear to the chromosome length in fully assembled grass genomes. GMATA represents a powerful application tool that facilitates genomic sequence analyses. GAMTA is freely available at http://sourceforge.net/projects/gmata/?source=navbar.

  18. Substructure identification for shear structures: cross-power spectral density method

    International Nuclear Information System (INIS)

    Zhang, Dongyu; Johnson, Erik A

    2012-01-01

    In this paper, a substructure identification method for shear structures is proposed. A shear structure is divided into many small substructures; utilizing the dynamic equilibrium of a one-floor substructure, an inductive identification problem is formulated, using the cross-power spectral densities between structural floor accelerations and a reference response, to estimate the parameters of that one story. Repeating this procedure, all story parameters of the shear structure are identified from top to bottom recursively. An identification error analysis is performed for the proposed substructure method, revealing how uncertain factors (e.g. measurement noise) in the identification process affect the identification accuracy. According to the error analysis, a smart reference selection rule is designed to choose the optimal reference response that further enhances the identification accuracy. Moreover, based on the identification error analysis, explicit formulae are developed to calculate the variances of the parameter identification errors. A ten-story shear structure is used to illustrate the effectiveness of the proposed substructure method. The simulation results show that the method, combined with the reference selection rule, can very accurately identify structural parameters despite large measurement noise. Furthermore, the proposed formulae provide good predictions for the variances of the parameter identification errors, which are vital for providing accurate warnings of structural damage. (paper)

  19. A comparison of Heuristic method and Llewellyn’s rules for identification of redundant constraints

    Science.gov (United States)

    Estiningsih, Y.; Farikhin; Tjahjana, R. H.

    2018-03-01

    Important techniques in linear programming is modelling and solving practical optimization. Redundant constraints are consider for their effects on general linear programming problems. Identification and reduce redundant constraints are for avoidance of all the calculations associated when solving an associated linear programming problems. Many researchers have been proposed for identification redundant constraints. This paper a compararison of Heuristic method and Llewellyn’s rules for identification of redundant constraints.

  20. Searching methods for biometric identification systems: Fundamental limits

    NARCIS (Netherlands)

    Willems, F.M.J.

    2009-01-01

    We study two-stage search procedures for biometric identification systems in an information-theoretical setting. Our main conclusion is that clustering based on vector-quantization achieves the optimum trade-off between the number of clusters (cluster rate) and the number of individuals within a

  1. A method for crack profiles identification in eddy current testing by the multi-directional scan

    International Nuclear Information System (INIS)

    Kojima, Fumio; Ikeda, Takuya; Nguyen, Doung

    2006-01-01

    This paper is concerned with a method for identification of crack shape in conducting materials. Multi-directional scanning strategies using Eddy Current Testing is performed for sizing complex natural crackings. Two dimensional measurements by means of multi-directional scan are used in a output least square identifications. (author)

  2. Mathematical correlation of modal-parameter-identification methods via system-realization theory

    Science.gov (United States)

    Juang, Jer-Nan

    1987-01-01

    A unified approach is introduced using system-realization theory to derive and correlate modal-parameter-identification methods for flexible structures. Several different time-domain methods are analyzed and treated. A basic mathematical foundation is presented which provides insight into the field of modal-parameter identification for comparison and evaluation. The relation among various existing methods is established and discussed. This report serves as a starting point to stimulate additional research toward the unification of the many possible approaches for modal-parameter identification.

  3. Mathematical correlation of modal parameter identification methods via system realization theory

    Science.gov (United States)

    Juang, J. N.

    1986-01-01

    A unified approach is introduced using system realization theory to derive and correlate modal parameter identification methods for flexible structures. Several different time-domain and frequency-domain methods are analyzed and treated. A basic mathematical foundation is presented which provides insight into the field of modal parameter identification for comparison and evaluation. The relation among various existing methods is established and discussed. This report serves as a starting point to stimulate additional research towards the unification of the many possible approaches for modal parameter identification.

  4. Determining the control circuitry of redox metabolism at the genome-scale.

    Directory of Open Access Journals (Sweden)

    Stephen Federowicz

    2014-04-01

    Full Text Available Determining how facultative anaerobic organisms sense and direct cellular responses to electron acceptor availability has been a subject of intense study. However, even in the model organism Escherichia coli, established mechanisms only explain a small fraction of the hundreds of genes that are regulated during electron acceptor shifts. Here we propose a qualitative model that accounts for the full breadth of regulated genes by detailing how two global transcription factors (TFs, ArcA and Fnr of E. coli, sense key metabolic redox ratios and act on a genome-wide basis to regulate anabolic, catabolic, and energy generation pathways. We first fill gaps in our knowledge of this transcriptional regulatory network by carrying out ChIP-chip and gene expression experiments to identify 463 regulatory events. We then interfaced this reconstructed regulatory network with a highly curated genome-scale metabolic model to show that ArcA and Fnr regulate >80% of total metabolic flux and 96% of differential gene expression across fermentative and nitrate respiratory conditions. Based on the data, we propose a feedforward with feedback trim regulatory scheme, given the extensive repression of catabolic genes by ArcA and extensive activation of chemiosmotic genes by Fnr. We further corroborated this regulatory scheme by showing a 0.71 r(2 (p<1e-6 correlation between changes in metabolic flux and changes in regulatory activity across fermentative and nitrate respiratory conditions. Finally, we are able to relate the proposed model to a wealth of previously generated data by contextualizing the existing transcriptional regulatory network.

  5. Noise analysis of genome-scale protein synthesis using a discrete computational model of translation

    Energy Technology Data Exchange (ETDEWEB)

    Racle, Julien; Hatzimanikatis, Vassily, E-mail: vassily.hatzimanikatis@epfl.ch [Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne (Switzerland); Swiss Institute of Bioinformatics (SIB), CH-1015 Lausanne (Switzerland); Stefaniuk, Adam Jan [Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne (Switzerland)

    2015-07-28

    Noise in genetic networks has been the subject of extensive experimental and computational studies. However, very few of these studies have considered noise properties using mechanistic models that account for the discrete movement of ribosomes and RNA polymerases along their corresponding templates (messenger RNA (mRNA) and DNA). The large size of these systems, which scales with the number of genes, mRNA copies, codons per mRNA, and ribosomes, is responsible for some of the challenges. Additionally, one should be able to describe the dynamics of ribosome exchange between the free ribosome pool and those bound to mRNAs, as well as how mRNA species compete for ribosomes. We developed an efficient algorithm for stochastic simulations that addresses these issues and used it to study the contribution and trade-offs of noise to translation properties (rates, time delays, and rate-limiting steps). The algorithm scales linearly with the number of mRNA copies, which allowed us to study the importance of genome-scale competition between mRNAs for the same ribosomes. We determined that noise is minimized under conditions maximizing the specific synthesis rate. Moreover, sensitivity analysis of the stochastic system revealed the importance of the elongation rate in the resultant noise, whereas the translation initiation rate constant was more closely related to the average protein synthesis rate. We observed significant differences between our results and the noise properties of the most commonly used translation models. Overall, our studies demonstrate that the use of full mechanistic models is essential for the study of noise in translation and transcription.

  6. Genome-scale analysis of aberrant DNA methylation in colorectal cancer

    Science.gov (United States)

    Hinoue, Toshinori; Weisenberger, Daniel J.; Lange, Christopher P.E.; Shen, Hui; Byun, Hyang-Min; Van Den Berg, David; Malik, Simeen; Pan, Fei; Noushmehr, Houtan; van Dijk, Cornelis M.; Tollenaar, Rob A.E.M.; Laird, Peter W.

    2012-01-01

    Colorectal cancer (CRC) is a heterogeneous disease in which unique subtypes are characterized by distinct genetic and epigenetic alterations. Here we performed comprehensive genome-scale DNA methylation profiling of 125 colorectal tumors and 29 adjacent normal tissues. We identified four DNA methylation–based subgroups of CRC using model-based cluster analyses. Each subtype shows characteristic genetic and clinical features, indicating that they represent biologically distinct subgroups. A CIMP-high (CIMP-H) subgroup, which exhibits an exceptionally high frequency of cancer-specific DNA hypermethylation, is strongly associated with MLH1 DNA hypermethylation and the BRAFV600E mutation. A CIMP-low (CIMP-L) subgroup is enriched for KRAS mutations and characterized by DNA hypermethylation of a subset of CIMP-H-associated markers rather than a unique group of CpG islands. Non-CIMP tumors are separated into two distinct clusters. One non-CIMP subgroup is distinguished by a significantly higher frequency of TP53 mutations and frequent occurrence in the distal colon, while the tumors that belong to the fourth group exhibit a low frequency of both cancer-specific DNA hypermethylation and gene mutations and are significantly enriched for rectal tumors. Furthermore, we identified 112 genes that were down-regulated more than twofold in CIMP-H tumors together with promoter DNA hypermethylation. These represent ∼7% of genes that acquired promoter DNA methylation in CIMP-H tumors. Intriguingly, 48/112 genes were also transcriptionally down-regulated in non-CIMP subgroups, but this was not attributable to promoter DNA hypermethylation. Together, we identified four distinct DNA methylation subgroups of CRC and provided novel insight regarding the role of CIMP-specific DNA hypermethylation in gene silencing. PMID:21659424

  7. Identification Male Fertility Through Abnormalities Sperm Based Morphology (Teratospermia) using Invariant Moment Method

    Science.gov (United States)

    Syahputra, M. F.; Chairani, R.; Seniman; Rahmat, R. F.; Abdullah, D.; Napitupulu, D.; Setiawan, M. I.; Albra, W.; Erliana, C. I.; Andayani, U.

    2018-03-01

    Sperm morphology is still a standard laboratory analysis in diagnosing infertility in men. Manually identification of sperm form is still not accurate, the difficulty in seeing the form of the invisible sperm from the digital microscope image is often a weakness in the process of identification and takes a long time. Therefore, male fertility identification application system is needed Through sperm abnormalities based on sperm morphology (teratospermia). The method used is invariant moment method. This study uses 15 data testing and 20 data training sperm image. That the process of male fertility identification through sperm abnormalities based on sperm morphology (teratospermia) has an accuracy rate of 80.77%. Use of time to process Identification of male fertility through sperm abnormalities Based on sperm morphology (teratospermia) during 0.4369 seconds.

  8. iCN718, an Updated and Improved Genome-Scale Metabolic Network Reconstruction of Acinetobacter baumannii AYE.

    Science.gov (United States)

    Norsigian, Charles J; Kavvas, Erol; Seif, Yara; Palsson, Bernhard O; Monk, Jonathan M

    2018-01-01

    Acinetobacter baumannii has become an urgent clinical threat due to the recent emergence of multi-drug resistant strains. There is thus a significant need to discover new therapeutic targets in this organism. One means for doing so is through the use of high-quality genome-scale reconstructions. Well-curated and accurate genome-scale models (GEMs) of A. baumannii would be useful for improving treatment options. We present an updated and improved genome-scale reconstruction of A. baumannii AYE, named iCN718, that improves and standardizes previous A. baumannii AYE reconstructions. iCN718 has 80% accuracy for predicting gene essentiality data and additionally can predict large-scale phenotypic data with as much as 89% accuracy, a new capability for an A. baumannii reconstruction. We further demonstrate that iCN718 can be used to analyze conserved metabolic functions in the A. baumannii core genome and to build strain-specific GEMs of 74 other A. baumannii strains from genome sequence alone. iCN718 will serve as a resource to integrate and synthesize new experimental data being generated for this urgent threat pathogen.

  9. A new identification method for energetic ion ΔE-E telescopes

    International Nuclear Information System (INIS)

    Martin, Cesar; Bronchalo, Enrique; Medina, Jose

    2007-01-01

    A new ion identification method for ΔE-E telescopes is presented. The method works by counting data points under ΔE(E) curves on ΔE-E diagrams. These curves are obtained by simulating the telescope response to a flux of energetic ions. The method is checked against three published methods applied to several experimental data sets

  10. A new identification method for energetic ion {delta}E-E telescopes

    Energy Technology Data Exchange (ETDEWEB)

    Martin, Cesar [Departamento de Fisica, Universidad de Alcala, 28871 Alcala de Henares, Madrid (Spain); Institut fuer Experimentelle und Angewandte Physik, Christian-Albrechts, Universitaet zu Kiel, 24118 Kiel (Germany); Bronchalo, Enrique [Departamento de Fisica, Universidad de Alcala, 28871 Alcala de Henares, Madrid (Spain); Departamento de Fisica y Arquitectura de Computadores, Universidad Miguel Hernandez, Avda. Universidad s/n, 03202 Elche, Alicante (Spain)], E-mail: ebronchalo@umh.es; Medina, Jose [Departamento de Fisica, Universidad de Alcala, 28871 Alcala de Henares, Madrid (Spain)

    2007-11-21

    A new ion identification method for {delta}E-E telescopes is presented. The method works by counting data points under {delta}E(E) curves on {delta}E-E diagrams. These curves are obtained by simulating the telescope response to a flux of energetic ions. The method is checked against three published methods applied to several experimental data sets.

  11. RRW: repeated random walks on genome-scale protein networks for local cluster discovery

    Directory of Open Access Journals (Sweden)

    Can Tolga

    2009-09-01

    Full Text Available Abstract Background We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins. Results We apply the proposed technique on a functional network of yeast genes and accurately identify statistically significant clusters of proteins. We validate the biological significance of the results using known complexes in the MIPS complex catalogue database and well-characterized biological processes. We find that 90% of the created clusters have the majority of their catalogued proteins belonging to the same MIPS complex, and about 80% have the majority of their proteins involved in the same biological process. We compare our method to various other clustering techniques, such as the Markov Clustering Algorithm (MCL, and find a significant improvement in the RRW clusters' precision and accuracy values. Conclusion RRW, which is a technique that exploits the topology of the network, is more precise and robust in finding local clusters. In addition, it has the added flexibility of being able to find multi-functional proteins by allowing overlapping clusters.

  12. Microindentation as a complementary method for phase identification

    Science.gov (United States)

    Zupanič, Franc

    2011-12-01

    This work investigates the possibility of using microindentation as a complementary tool for phase identification, especially in heterogeneous microstructures. Five phases present in alloys Al64Cu23Fe13 and Al94Mn2Be2Cu2 were indented in the microindentation region. A load of 20 mN was found to be convenient for testing because it was too low to produce cracks around indents, yet high enough to avoid too large scattering of the results, occurring at smaller loads. It allowed testing of particles as small as 10 μm in the lateral direction and 3 μm in thickness. Some phases can be distinguished from others by specific characteristics of indentation curves. Otherwise, a single quantitative parameter or combinations of several indentation parameters (defined in EN ISO 14577-1) sufficed. The microindentation can considerably help by phase identification; however, a wider application will require a database, providing indentation properties for a particular phase at different loads and taking into account the indentation size effect.

  13. Fingerprint: A Unique and Reliable Method for Identification

    Directory of Open Access Journals (Sweden)

    Palash Kumar Bose

    2017-01-01

    Full Text Available Fingerprints have been the gold standard for personal identification within the forensic community for more than one hundred years. It is still universal in spite of discovery of DNA fingerprint. The science of fingerprint identification has evolved over time from the early use of finger prints to mark business transactions in ancient Babylonia to their use today as core technology in biometric security devices and as scientific evidence in courts of law throughout the world. The science of fingerprints, dactylography or dermatoglyphics, had long been widely accepted, and well acclaimed and reputed as panacea for individualization, particularly in forensic investigations. Human fingerprints are detailed, unique, difficult to alter, and durable over the life of an individual, making them suitable as lifelong markers of human identity. Fingerprints can be readily used by police or other authorities to identify individuals who wish to conceal their identity, or to identify people who are incapacitated or deceased, as in the aftermath of a natural disaster

  14. Direct Linear System Identification Method for Multistory Three-dimensional Building Structure with General Eccentricity

    OpenAIRE

    Shintani, Kenichirou; Yoshitomi, Shinta; Takewaki, Izuru

    2017-01-01

    A method of physical parameter system identification (SI) is proposed here for three-dimensional (3D) building structures with in-plane rigid floors in which the stiffness and damping coefficients of each structural frame in the 3D building structure are identified from the measured floor horizontal accelerations. A batch processing least-squares estimation method for many discrete time domain measured data is proposed for the direct identification of the stiffness and damping coefficients of...

  15. Expression induction of P450 genes by imidacloprid in Nilaparvata lugens: A genome-scale analysis.

    Science.gov (United States)

    Zhang, Jianhua; Zhang, Yixi; Wang, Yunchao; Yang, Yuanxue; Cang, Xinzhu; Liu, Zewen

    2016-09-01

    The overexpression of P450 monooxygenase genes is a main mechanism for the resistance to imidacloprid, a representative neonicotinoid insecticide, in Nilaparvata lugens (brown planthopper, BPH). However, only two P450 genes (CYP6AY1 and CYP6ER1), among fifty-four P450 genes identified from BPH genome database, have been reported to play important roles in imidacloprid resistance until now. In this study, after the confirmation of important roles of P450s in imidacloprid resistance by the synergism analysis, the expression induction by imidacloprid was determined for all P450 genes. In the susceptible (Sus) strain, eight P450 genes in Clade4, eight in Clade3 and two in Clade2 were up-regulated by imidacloprid, among which three genes (CYP6CS1, CYP6CW1 and CYP6ER1, all in Clade3) were increased to above 4.0-fold and eight genes to above 2.0-fold. In contrast, no P450 genes were induced in Mito clade. Eight genes induced to above 2.0-fold were selected to determine their expression and induced levels in Huzhou population, in which piperonyl butoxide showed the biggest effects on imidacloprid toxicity among eight field populations. The expression levels of seven P450 genes were higher in Huzhou population than that in Sus strain, with the biggest differences for CYP6CS1 (9.8-fold), CYP6ER1 (7.7-fold) and CYP6AY1 (5.1-fold). The induction levels for all tested genes were bigger in Sus strain than that in Huzhou population except CYP425B1. Screening the induction of P450 genes by imidacloprid in the genome-scale will provide an overall view on the possible metabolic factors in the resistance to neonicotinoid insecticides. The further work, such as the functional study of recombinant proteins, will be performed to validate the roles of these P450s in imidacloprid resistance. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. A Method of Fire Scenarios Identification in a Consolidated Fire Risk Analysis

    International Nuclear Information System (INIS)

    Lim, Ho Gon; Han, Sang Hoon; Yang, Joon Eon

    2010-01-01

    Conventional fire PSA consider only two cases of fire scenarios, that is one for fire without propagation and the other for single propagation to neighboring compartment. Recently, a consolidated fire risk analysis using single fault tree (FT) was developed. However, the fire scenario identification in the new method is similar to conventional fire analysis method. The present study develops a new method of fire scenario identification in a consolidated fire risk analysis method. An equation for fire propagation is developed to identify fire scenario and a mapping method of fire scenarios into internal event risk model is discussed. Finally, an algorithm for automatic program is suggested

  17. Molecular Methods To Improve Diagnosis and Identification of Mucormycosis▿

    Science.gov (United States)

    Hammond, Sarah P.; Bialek, Ralf; Milner, Danny A.; Petschnigg, Eva M.; Baden, Lindsey R.; Marty, Francisco M.

    2011-01-01

    Mucormycosis is difficult to diagnose. Samples from suspected cases often fail to grow Mucorales in microbiologic cultures. We identified all hematologic malignancy and stem cell transplant patients diagnosed with proven mucormycosis between 2001 and 2009 at Brigham and Women's Hospital/Dana-Farber Cancer Institute. Seminested PCR targeting Mucorales 18S ribosomal DNA and sequencing were performed on formalin-fixed paraffin-embedded tissue samples. Of 29 cases of mucormycosis, 27 had tissue samples available for PCR and sequencing. Mucorales PCR was positive in 22. Among 12 culture-positive cases, 10 were PCR positive and sequencing was concordant with culture results to the genus level in 9. Among 15 culture-negative cases, PCR was positive and sequencing allowed genus identification in 12. Mucorales PCR is useful for confirmation of the diagnosis of mucormycosis and for further characterization of the infection in cases where cultures are negative. PMID:21508149

  18. Molecular methods to improve diagnosis and identification of mucormycosis.

    Science.gov (United States)

    Hammond, Sarah P; Bialek, Ralf; Milner, Danny A; Petschnigg, Eva M; Baden, Lindsey R; Marty, Francisco M

    2011-06-01

    Mucormycosis is difficult to diagnose. Samples from suspected cases often fail to grow Mucorales in microbiologic cultures. We identified all hematologic malignancy and stem cell transplant patients diagnosed with proven mucormycosis between 2001 and 2009 at Brigham and Women's Hospital/Dana-Farber Cancer Institute. Seminested PCR targeting Mucorales 18S ribosomal DNA and sequencing were performed on formalin-fixed paraffin-embedded tissue samples. Of 29 cases of mucormycosis, 27 had tissue samples available for PCR and sequencing. Mucorales PCR was positive in 22. Among 12 culture-positive cases, 10 were PCR positive and sequencing was concordant with culture results to the genus level in 9. Among 15 culture-negative cases, PCR was positive and sequencing allowed genus identification in 12. Mucorales PCR is useful for confirmation of the diagnosis of mucormycosis and for further characterization of the infection in cases where cultures are negative.

  19. Hankel Matrix Correlation Function-Based Subspace Identification Method for UAV Servo System

    Directory of Open Access Journals (Sweden)

    Minghong She

    2018-01-01

    Full Text Available For the identification problem of closed-loop subspace model, we propose a zero space projection method based on the estimation of correlation function to fill the block Hankel matrix of identification model by combining the linear algebra with geometry. By using the same projection of related data in time offset set and LQ decomposition, the multiplication operation of projection is achieved and dynamics estimation of the unknown equipment system model is obtained. Consequently, we have solved the problem of biased estimation caused when the open-loop subspace identification algorithm is applied to the closed-loop identification. A simulation example is given to show the effectiveness of the proposed approach. In final, the practicability of the identification algorithm is verified by hardware test of UAV servo system in real environment.

  20. Modal identification of composite structures using Eigen realization method

    International Nuclear Information System (INIS)

    Hamidzadeh, H.R.; Afolabi, D.

    1996-01-01

    Experimental modal analysis has proved to be a useful tool to determine the vibration response of complex composite structures. An accurate method for extracting modal parameters of these type of structures are presented. The method used experimental impulse response of the system as input and provides natural frequencies and damping ratios of a dynamic system. The employed theories are Eigen Realization and Impulse Response methods. The adopted method is superior to other available methods in time and frequency domains. The presented method is proven to provide robustness with respect to measured noise

  1. Microarray analysis of serum mRNA in patients with head and neck squamous cell carcinoma at whole-genome scale

    Czech Academy of Sciences Publication Activity Database

    Čapková, M.; Šáchová, Jana; Strnad, Hynek; Kolář, Michal; Hroudová, Miluše; Chovanec, M.; Čada, Z.; Štefl, M.; Valach, J.; Kastner, J.; Smetana, K. Jr.; Plzák, J.

    -, April 23 (2014) ISSN 2314-6141 R&D Projects: GA MZd(CZ) NT13488 Institutional support: RVO:68378050 Keywords : Microarray Analysis * Head and Neck Squamous Cell Carcinoma * whole-genome scale Subject RIV: EB - Genetics ; Molecular Biology

  2. Identification of the parameters of an elastic material model using the constitutive equation gap method

    KAUST Repository

    Florentin, Éric

    2010-04-23

    Today, the identification ofmaterialmodel parameters is based more and more on full-field measurements. This article explains how an appropriate use of the constitutive equation gap method (CEGM) can help in this context. The CEGM is a well-known concept which, until now, has been used mainly for the verification of finite element simulations. This has led to many developments, especially concerning the techniques for constructing statically admissible stress fields. The originality of the present study resides in the application of these recent developments to the identification problem. The proposed CEGM is described in detail, then evaluated through the identification of heterogeneous isotropic elastic properties. The results obtained are systematically compared with those of the equilibrium gap method, which is a well-known technique for the resolution of such identification problems. We prove that the use of the enhanced CEGM significantly improves the quality of the results. © Springer-Verlag 2010.

  3. A feature point identification method for positron emission particle tracking with multiple tracers

    Energy Technology Data Exchange (ETDEWEB)

    Wiggins, Cody, E-mail: cwiggin2@vols.utk.edu [University of Tennessee-Knoxville, Department of Physics and Astronomy, 1408 Circle Drive, Knoxville, TN 37996 (United States); Santos, Roque [University of Tennessee-Knoxville, Department of Nuclear Engineering (United States); Escuela Politécnica Nacional, Departamento de Ciencias Nucleares (Ecuador); Ruggles, Arthur [University of Tennessee-Knoxville, Department of Nuclear Engineering (United States)

    2017-01-21

    A novel detection algorithm for Positron Emission Particle Tracking (PEPT) with multiple tracers based on optical feature point identification (FPI) methods is presented. This new method, the FPI method, is compared to a previous multiple PEPT method via analyses of experimental and simulated data. The FPI method outperforms the older method in cases of large particle numbers and fine time resolution. Simulated data show the FPI method to be capable of identifying 100 particles at 0.5 mm average spatial error. Detection error is seen to vary with the inverse square root of the number of lines of response (LORs) used for detection and increases as particle separation decreases. - Highlights: • A new approach to positron emission particle tracking is presented. • Using optical feature point identification analogs, multiple particle tracking is achieved. • Method is compared to previous multiple particle method. • Accuracy and applicability of method is explored.

  4. A simple and rapid molecular method for Leptospira species identification

    NARCIS (Netherlands)

    Ahmed, Ahmed; Anthony, Richard M.; Hartskeerl, Rudy A.

    2010-01-01

    Serological and DNA-based classification systems only have little correlation. Currently serological and molecular methods for characterizing Leptospira are complex and costly restricting their world-wide distribution and use. Ligation mediated amplification combined with microarray analysis

  5. Libraries for spectrum identification: Method of normalized coordinates versus linear correlation

    International Nuclear Information System (INIS)

    Ferrero, A.; Lucena, P.; Herrera, R.G.; Dona, A.; Fernandez-Reyes, R.; Laserna, J.J.

    2008-01-01

    In this work it is proposed that an easy solution based directly on linear algebra in order to obtain the relation between a spectrum and a spectrum base. This solution is based on the algebraic determination of an unknown spectrum coordinates with respect to a spectral library base. The identification capacity comparison between this algebraic method and the linear correlation method has been shown using experimental spectra of polymers. Unlike the linear correlation (where the presence of impurities may decrease the discrimination capacity), this method allows to detect quantitatively the existence of a mixture of several substances in a sample and, consequently, to beer in mind impurities for improving the identification

  6. The power grid AGC frequency bias coefficient online identification method based on wide area information

    Science.gov (United States)

    Wang, Zian; Li, Shiguang; Yu, Ting

    2015-12-01

    This paper propose online identification method of regional frequency deviation coefficient based on the analysis of interconnected grid AGC adjustment response mechanism of regional frequency deviation coefficient and the generator online real-time operation state by measured data through PMU, analyze the optimization method of regional frequency deviation coefficient in case of the actual operation state of the power system and achieve a more accurate and efficient automatic generation control in power system. Verify the validity of the online identification method of regional frequency deviation coefficient by establishing the long-term frequency control simulation model of two-regional interconnected power system.

  7. Systems and methods for remote long standoff biometric identification using microwave cardiac signals

    Science.gov (United States)

    McGrath, William R. (Inventor); Talukder, Ashit (Inventor)

    2012-01-01

    Systems and methods for remote, long standoff biometric identification using microwave cardiac signals are provided. In one embodiment, the invention relates to a method for remote biometric identification using microwave cardiac signals, the method including generating and directing first microwave energy in a direction of a person, receiving microwave energy reflected from the person, the reflected microwave energy indicative of cardiac characteristics of the person, segmenting a signal indicative of the reflected microwave energy into a waveform including a plurality of heart beats, identifying patterns in the microwave heart beats waveform, and identifying the person based on the identified patterns and a stored microwave heart beats waveform.

  8. Rapid screening of guar gum using portable Raman spectral identification methods.

    Science.gov (United States)

    Srivastava, Hirsch K; Wolfgang, Steven; Rodriguez, Jason D

    2016-01-25

    Guar gum is a well-known inactive ingredient (excipient) used in a variety of oral pharmaceutical dosage forms as a thickener and stabilizer of suspensions and as a binder of powders. It is also widely used as a food ingredient in which case alternatives with similar properties, including chemically similar gums, are readily available. Recent supply shortages and price fluctuations have caused guar gum to come under increasing scrutiny for possible adulteration by substitution of cheaper alternatives. One way that the U.S. FDA is attempting to screen pharmaceutical ingredients at risk for adulteration or substitution is through field-deployable spectroscopic screening. Here we report a comprehensive approach to evaluate two field-deployable Raman methods--spectral correlation and principal component analysis--to differentiate guar gum from other gums. We report a comparison of the sensitivity of the spectroscopic screening methods with current compendial identification tests. The ability of the spectroscopic methods to perform unambiguous identification of guar gum compared to other gums makes them an enhanced surveillance alternative to the current compendial identification tests, which are largely subjective in nature. Our findings indicate that Raman spectral identification methods perform better than compendial identification methods and are able to distinguish guar gum from other gums with 100% accuracy for samples tested by spectral correlation and principal component analysis. Published by Elsevier B.V.

  9. Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model

    International Nuclear Information System (INIS)

    Dash, Satyakam; Mueller, Thomas J.; Venkataramanan, Keerthi P.; Papoutsakis, Eleftherios T.; Maranas, Costas D.

    2014-01-01

    Clostridia are anaerobic Gram-positive Firmicutes containing broad and flexible systems for substrate utilization, which have been used successfully to produce a range of industrial compounds. Clostridium acetobutylicum has been used to produce butanol on an industrial scale through acetone-butanol-ethanol (ABE) fermentation. A genome-scale metabolic (GSM) model is a powerful tool for understanding the metabolic capacities of an organism and developing metabolic engineering strategies for strain development. The integration of stress related specific transcriptomics information with the GSM model provides opportunities for elucidating the focal points of regulation

  10. Modal method for crack identification applied to reactor recirculation pump

    International Nuclear Information System (INIS)

    Miller, W.H.; Brook, R.

    1991-01-01

    Nuclear reactors have been operating and producing useful electricity for many years. Within the last few years, several plants have found cracks in the reactor coolant pump shaft near the thermal barrier. The modal method and results described herein show the analytical results of using a Modal Analysis test method to determine the presence, size, and location of a shaft crack. The authors have previously demonstrated that the test method can analytically and experimentally identify shaft cracks as small as five percent (5%) of the shaft diameter. Due to small differences in material property distribution, the attempt to identify cracks smaller than 3% of the shaft diameter has been shown to be impractical. The rotor dynamics model includes a detailed motor rotor, external weights and inertias, and realistic total support stiffness. Results of the rotor dynamics model have been verified through a comparison with on-site vibration test data

  11. Geochemical methods for identification of formations being prospective for uranium

    International Nuclear Information System (INIS)

    Zhukova, A.M.; Komarova, N.I.; Spiridonov, A.A.; Shor, G.M.

    1985-01-01

    Geochemical methods of uranium content evaluation in metamorphic, ultrametamorphic and sedimentary formations are considered. At that, the following four factors are of the highest importance: 1) average uranium content-geochemical background; 2) character of uranium distribution; 3) forms of uranium presence; 4) the value of thorium-uranium ratio. A complex of radiogeochemical criteria, favourable for uranium presence is formulated: high average background content of total and '' mobile''uranium and high value of variation coefficient (80-100% and above); low (approximately one or lower) thorium-uranium ratio; sharp increase in uranium concentration in accessory minerals. Radiogeochemical peculiarities of metamorphic and ultrametamorphic formations prospective for uranium are enumerated. The peculiarities condition specificity of geochemical prospecting methods. Prospecting methods first of all must be directed at the evaluation of radioelement distribution parameters and specification of the forms of their presence

  12. High throughput screening method for identification of new lipofection reagents.

    Science.gov (United States)

    Regelin, A E; Fernholz, E; Krug, H F; Massing, U

    2001-08-01

    Lipofection, the transfer of genetic material into cells by means of cationic lipids, is of growing interest for in vitro and in vivo approaches. In order to identify ideal lipofection reagents in a HTS, we have developed an automated lipofection method for the transfer of reporter genes into cells and for determination of the lipofection results. The method has specifically been designed and optimized for 96-well microtiter plates and can successfully be carried out by a pipetting robot with accessory equipment. It consists of two separate parts: (1) pretransfection (preparation of liposomes, formation of lipoplexes, and lipoplex transfer to the cells) and (2) posttransfection (determination of the reporter enzyme activity and the protein content of the transfected cells). Individual steps of the lipofection method were specifically optimized - for example, lipoplex formation and incubation time as well as cell lysis, cell cultivating, and the reporter gene assay. The HTS method facilitates characterization of the transfection properties (efficiency and cytotoxicity) of large numbers of (cationic) lipids in various adherent cell types.

  13. Sponge cell culture? A molecular identification method for sponge cells

    NARCIS (Netherlands)

    Sipkema, D.; Heilig, G.H.J.; Akkermans, A.D.L.; Osinga, R.; Tramper, J.; Wijffels, R.H.

    2003-01-01

    Dissociated sponge cells are easily confused with unicellular organisms. This has been an obstacle in the development of sponge-cell lines. We developed a molecular detection method to identify cells of the sponge Dysidea avara in dissociated cell cultures. The 18S ribosomal RNA gene from a Dysidea

  14. Identification of alternative method of teaching and learning the ...

    African Journals Online (AJOL)

    This study examines alternative method of teaching and learning of the concept of diffusion. An improvised U-shape glass tube called ionic mobility tube was used to observed and measure the rate of movement of divalent metal ions in an aqueous medium in the absence of an electric current. The study revealed that the ...

  15. Identification of buried victims in natural disaster with GPR method

    Science.gov (United States)

    Dewi, Rianty Kusuma; Kurniawan, Adityo; Taqwantara, Reyhan Fariz; Iskandar, Farras M.; Naufal, Taufiq Ziyan; Widodo

    2017-07-01

    Indonesian is one of the most seismically active regions in the world and has very complicated plate convergence because there is meeting point of several tectonic plates. The complexity of tectonic features causes a lot of natural disasters such as landslides, tsunamis, earth quakes, volcanoes eruption, etc. Sometimes, the disasters occurs in high populated area and causing thousands to millions of victim been buried under the rumble. Unfortunately, the evacuation still uses the conventional method such using rescue dogs whereas the sensitivity of smell is decrease when the victims buried under the level of the ground. The purpose of this study is to detect buried bodies using GPR method, so it can enhance the effectiveness and the efficiency in looking for the disaster victims. GPR method is used because it can investigate things under the ground. A detailed GPR research has been done in Cikutra Graveyard, Bandung, with corpse buried two week until two years before the research. The radar profiles from this research showed amplitude contras anomaly between the new corpse and the old ones. We obtained the amplitude contras at 1.2-1.4 meters under the surface. This method proved to be effective but still need more attention on undulated surface and non-soil areas.

  16. A Novel Degradation Identification Method for Wind Turbine Pitch System

    Science.gov (United States)

    Guo, Hui-Dong

    2018-04-01

    It’s difficult for traditional threshold value method to identify degradation of operating equipment accurately. An novel degradation evaluation method suitable for wind turbine condition maintenance strategy implementation was proposed in this paper. Based on the analysis of typical variable-speed pitch-to-feather control principle and monitoring parameters for pitch system, a multi input multi output (MIMO) regression model was applied to pitch system, where wind speed, power generation regarding as input parameters, wheel rotation speed, pitch angle and motor driving currency for three blades as output parameters. Then, the difference between the on-line measurement and the calculated value from the MIMO regression model applying least square support vector machines (LSSVM) method was defined as the Observed Vector of the system. The Gaussian mixture model (GMM) was applied to fitting the distribution of the multi dimension Observed Vectors. Applying the model established, the Degradation Index was calculated using the SCADA data of a wind turbine damaged its pitch bearing retainer and rolling body, which illustrated the feasibility of the provided method.

  17. Kalman and particle filtering methods for full vehicle and tyre identification

    Science.gov (United States)

    Bogdanski, Karol; Best, Matthew C.

    2018-05-01

    This paper considers identification of all significant vehicle handling dynamics of a test vehicle, including identification of a combined-slip tyre model, using only those sensors currently available on most vehicle controller area network buses. Using an appropriately simple but efficient model structure, all of the independent parameters are found from test vehicle data, with the resulting model accuracy demonstrated on independent validation data. The paper extends previous work on augmented Kalman Filter state estimators to concentrate wholly on parameter identification. It also serves as a review of three alternative filtering methods; identifying forms of the unscented Kalman filter, extended Kalman filter and particle filter are proposed and compared for effectiveness, complexity and computational efficiency. All three filters are suited to applications of system identification and the Kalman Filters can also operate in real-time in on-line model predictive controllers or estimators.

  18. Microbiological method for radiation sterilization (I). General knowledge and handling technique for bacterial identification

    International Nuclear Information System (INIS)

    Koshikawa, Tomihiko

    2004-01-01

    The part I in this title series describes the basic knowledge and technique for identification of bacteria in the radiation sterilization of medical devices, where the radiation dose can be decided from the number and radio-resistance of the bioburden (bacteria on the device). Four essential, actual technologies for identification are described: isolation and storage of bacteria; decision of bacterial natures, involving 3 Gram staining methods, morphology by microscopy and/or phase-contrast microscopy, spore-forming bacteria, and size measurement by micrometry; Other test items for identification of genus, involving motility, oxygen demand, catalase, oxidase, acid production from glucose, and OF (oxidation or fermentation for glucose degradation) test; and colony observation. Media, identification kits and record forms for these are presented. (N.I.)

  19. Spectral analysis methods for vehicle interior vibro-acoustics identification

    Science.gov (United States)

    Hosseini Fouladi, Mohammad; Nor, Mohd. Jailani Mohd.; Ariffin, Ahmad Kamal

    2009-02-01

    Noise has various effects on comfort, performance and health of human. Sound are analysed by human brain based on the frequencies and amplitudes. In a dynamic system, transmission of sound and vibrations depend on frequency and direction of the input motion and characteristics of the output. It is imperative that automotive manufacturers invest a lot of effort and money to improve and enhance the vibro-acoustics performance of their products. The enhancement effort may be very difficult and time-consuming if one relies only on 'trial and error' method without prior knowledge about the sources itself. Complex noise inside a vehicle cabin originated from various sources and travel through many pathways. First stage of sound quality refinement is to find the source. It is vital for automotive engineers to identify the dominant noise sources such as engine noise, exhaust noise and noise due to vibration transmission inside of vehicle. The purpose of this paper is to find the vibro-acoustical sources of noise in a passenger vehicle compartment. The implementation of spectral analysis method is much faster than the 'trial and error' methods in which, parts should be separated to measure the transfer functions. Also by using spectral analysis method, signals can be recorded in real operational conditions which conduce to more consistent results. A multi-channel analyser is utilised to measure and record the vibro-acoustical signals. Computational algorithms are also employed to identify contribution of various sources towards the measured interior signal. These achievements can be utilised to detect, control and optimise interior noise performance of road transport vehicles.

  20. ITPI: Initial Transcription Process-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula

    Directory of Open Access Journals (Sweden)

    Baixia Zhang

    2016-01-01

    Full Text Available Identification of bioactive components is an important area of research in traditional Chinese medicine (TCM formula. The reported identification methods only consider the interaction between the components and the target proteins, which is not sufficient to explain the influence of TCM on the gene expression. Here, we propose the Initial Transcription Process-based Identification (ITPI method for the discovery of bioactive components that influence transcription factors (TFs. In this method, genome-wide chip detection technology was used to identify differentially expressed genes (DEGs. The TFs of DEGs were derived from GeneCards. The components influencing the TFs were derived from STITCH. The bioactive components in the formula were identified by evaluating the molecular similarity between the components in formula and the components that influence the TF of DEGs. Using the formula of Tian-Zhu-San (TZS as an example, the reliability and limitation of ITPI were examined and 16 bioactive components that influence TFs were identified.

  1. Application of Story-wise Shear Building Identification Method to Actual Ambient Vibration

    Directory of Open Access Journals (Sweden)

    Kohei eFujita

    2015-02-01

    Full Text Available A sophisticated and smart story stiffness System Identification (SI method for a shear building model is applied to a full-scale building frame subjected to micro-tremors. The advantageous and novel feature is that not only the modal parameters, such as natural frequencies and damping ratios, but also the physical model parameters, such as story stiffnesses and damping coefficients, can be identified using micro-tremors. While the building responses to earthquake ground motions are necessary in the previous SI method, it is shown in this paper that the micro-tremor measurements in a full-scale 5 story building frame can be used for identification within the same framework. The SI using micro-tremor measurements leads to the enhanced usability of the previously proposed story-wise shear building identification method. The degree of ARX models and cut-off frequencies of band-pass filter are determined to derive reliable results.

  2. Identification of metabolic system parameters using global optimization methods

    Directory of Open Access Journals (Sweden)

    Gatzke Edward P

    2006-01-01

    Full Text Available Abstract Background The problem of estimating the parameters of dynamic models of complex biological systems from time series data is becoming increasingly important. Methods and results Particular consideration is given to metabolic systems that are formulated as Generalized Mass Action (GMA models. The estimation problem is posed as a global optimization task, for which novel techniques can be applied to determine the best set of parameter values given the measured responses of the biological system. The challenge is that this task is nonconvex. Nonetheless, deterministic optimization techniques can be used to find a global solution that best reconciles the model parameters and measurements. Specifically, the paper employs branch-and-bound principles to identify the best set of model parameters from observed time course data and illustrates this method with an existing model of the fermentation pathway in Saccharomyces cerevisiae. This is a relatively simple yet representative system with five dependent states and a total of 19 unknown parameters of which the values are to be determined. Conclusion The efficacy of the branch-and-reduce algorithm is illustrated by the S. cerevisiae example. The method described in this paper is likely to be widely applicable in the dynamic modeling of metabolic networks.

  3. Introduction to DNA methods for identification of irradiated foods

    International Nuclear Information System (INIS)

    Delincee, H.

    1996-01-01

    This brief introduction sets the scene with respect to the presentations in this ADMIT meeting dealing with DNA changes as a tool to detect the radiation processing of food. The choice to examine DNA seems obvious, since DNA is a sensitive cellular target to irradiation and the changes in DNA are responsible for many effects observed in irradiated foods, such as the inactivation of microorganisms, elimination of insects, inhibition of sprouting in bulbs and tubers and delay of ripening in several fruits. Therefore, these changes in DNA should be discernible in microbial or insect DNA or in the nucleic acids in the food itself. If DNA changes were specific to irradiation, a detection method could be designed which would have wide applicability, since most foods are derived from living organisms which all contain DNA. Such a method could almost be the universal method for detecting the radiation treatment of foods. Radiation-induced changes in DNA can be analysed by a variety of analytical techniques, which have mostly been employed on pure DNA or on DNA in living cells in radiation biology research. Whether or not some of these techniques can be utilised to detect irradiated food has recently been very briefly discussed. (author)

  4. Identification of Cracked Zone in Sutami dam Using Geoelectrical Method

    Directory of Open Access Journals (Sweden)

    Fina Fitriah

    2015-12-01

    Full Text Available We identified the craked zones based on geoelectrical resistivity method in Sutami Dam. There are four lines measurement of geoelectrical resistivity method with a length of 380-400 meters. The direction of each line is from the northeast to the southwest. All of the tracks are located at the top of Sutami Dam i.e. two tracks in the upstream and the others in the downstream. From the analysis we found that the lithology is detected by geoelectrical resistivty method showed two layers of design of Sutami Dam. The two layers that are detected are transition zone and filter zone. Transition zone consists of sandstone rock containing water (0.922 Ωm-9.57 Ωm and dry sandstone (>9.57 Ωm-320 Ωm. Filter zone consists of sand (>320 Ωm-4410 Ωm. Cracked zones spread in the upstream, downstream, and roadway at the top of Sutami Dam which are indicated by the presence of low resistivity (0.922 Ωm-9.57 Ωm based on 3D processing of data of geoelectrical resistivity. The distribution of cracked zone indicates that Sutami Dam is susceptible to ground movement.

  5. Particle identification method in the CsI(Tl) scintillator used for the CHIMERA 4 pi detector

    CERN Document Server

    Alderighi, M; Basssini, R; Berceanu, I; Blicharska, J; Boiano, C; Borderie, B; Bougault, R; Bruno, M; Cali, C; Cardella, G; Cavallaro, S; D'Agostino, M; D'andrea, M; Dayras, R; De Filippo, E; Fichera, F; Geraci, E; Giustolisi, F; Grzeszczuk, A; Guardone, N; Guazzoni, P; Guinet, D; Iacono-Manno, M; Kowalski, S; La Guidara, E; Lanchais, A L; Lanzalone, G; Lanzanò, G; Le Neindre, N; Li, S; Maiolino, C; Majka, Z; Manfredi, G; Nicotra, D; Paduszynski, T; Pagano, A; Papa, M; Petrovici, C M; Piasecki, E; Pirrone, S; Politi, G; Pop, A; Porto, F; Rivet, M F; Rosato, E; Sacca, G; Sechi, G; Simion, V; Sperduto, M L; Steckmeyer, J C; Trifiró, A; Trimarchi, M; Urso, S; Vannini, G; Vigilante, M; Wilczynski, J; Wu, H; Xiao, Z; Zetta, L; Zipper, W

    2002-01-01

    The charged particle identification obtained by the analysis of signals coming from the CsI(Tl) detectors of the CHIMERA 4 pi heavy-ion detector is presented. A simple double-gate integration method, with the use of the cyclotron radiofrequency as reference time, results in low thresholds for isotopic particle identification. The dependence of the identification quality on the gate generation timing is discussed. Isotopic identification of light ions up to Beryllium is clearly seen. For the first time also the identification of Z=5 particles is observed. The identification of neutrons interacting with CsI(Tl) by (n,alpha) and (n,gamma) reactions is also discussed.

  6. Identification and classification of spine vertebrae by automated methods

    Science.gov (United States)

    Long, L. Rodney; Thoma, George R.

    2001-07-01

    We are currently working toward developing computer-assisted methods for the indexing of a collection of 17,000 digitized x-ray images by biomedical content. These images were collected as part of a nationwide health survey and form a research resource for osteoarthitis and bone morphometry. This task requires the development of algorithms to robustly analyze the x-ray contents for key landmarks, to segment the vertebral bodies, to accurately measure geometric features of the individual vertebrae and inter-vertebral areas, and to classify the spine anatomy into normal or abnormal classes for conditions of interest, including anterior osteophytes and disc space narrowing. Subtasks of this work have been created and divided among collaborators. In this paper, we provide a technical description of the overall task, report on progress made by collaborators, and provide the most recent results of our own research into obtaining first-order location of the spine region of interest by automated methods. We are currently concentrating on images of the cervical spine, but will expand the work to include the lumbar spine as well. Development of successful image processing techniques for computer-assisted indexing of medical image collections is expected to have a significant impact within the medical research and patient care systems.

  7. A multiplex PCR method for rapid identification of Brachionus rotifers.

    Science.gov (United States)

    Vasileiadou, Kalliopi; Papakostas, Spiros; Triantafyllidis, Alexander; Kappas, Ilias; Abatzopoulos, Theodore J

    2009-01-01

    Cryptic species are increasingly being recognized in many organisms. In Brachionus rotifers, many morphologically similar yet genetically distinct species/biotypes have been described. A number of Brachionus cryptic species have been recognized among hatchery strains. In this study, we present a simple, one-step genetic method to detect the presence of those Brachionus sp. rotifers that have been found in hatcheries. With the proposed technique, each of the B. plicatilis sensu stricto, B. ibericus, Brachionus sp. Nevada, Brachionus sp. Austria, Brachionus sp. Manjavacas, and Brachionus sp. Cayman species and/or biotypes can be identified with polymerase chain reaction (PCR) analysis. Based on 233 cytochrome c oxidase subunit I sequences, we reviewed all the available cryptic Brachionus sp. genetic polymorphisms, and we designed six nested primers. With these primers, a specific amplicon of distinct size is produced for every one of the involved species/biotypes. Two highly sensitive protocols were developed for using the primers. Many of the primers can be combined in the same PCR. The proposed method has been found to be an effective and practical tool to investigate the presence of the above six cryptic species/biotypes in both individual and communal (bulk) rotifer deoxyribonucleic acid extractions from hatcheries. With this technique, hatchery managers could easily determine their rotifer composition at the level of cryptic species and monitor their cultures more efficiently.

  8. Individual feature identification method for nuclear accident emergency decision-making

    International Nuclear Information System (INIS)

    Chen Yingfeng; Wang Jianlong; Lin Xiaoling; Yang Yongxin; Lu Xincheng

    2014-01-01

    According to the individual feature identification method and combining with the characteristics of nuclear accident emergency decision-making, the evaluation index system of the nuclear accident emergency decision-making was determined on the basis of investigation and analysis. The effectiveness of the nuclear accident emergency decision-making was evaluated based on the individual standards by solving the individual features of the individual standard identification decisions. The case study shows that the optimization result is reasonable, objective and reliable, and it can provide an effective analysis method and decision-making support for optimization of nuclear accident emergency protective measures. (authors)

  9. Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets.

    Science.gov (United States)

    Levering, Jennifer; Fiedler, Tomas; Sieg, Antje; van Grinsven, Koen W A; Hering, Silvio; Veith, Nadine; Olivier, Brett G; Klett, Lara; Hugenholtz, Jeroen; Teusink, Bas; Kreikemeyer, Bernd; Kummer, Ursula

    2016-08-20

    Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49. Initially, we based the reconstruction on genome annotations and already existing and curated metabolic networks of Bacillus subtilis, Escherichia coli, Lactobacillus plantarum and Lactococcus lactis. This initial draft was manually curated with the final reconstruction accounting for 480 genes associated with 576 reactions and 558 metabolites. In order to constrain the model further, we performed growth experiments of wild type and arcA deletion strains of S. pyogenes M49 in a chemically defined medium and calculated nutrient uptake and production fluxes. We additionally performed amino acid auxotrophy experiments to test the consistency of the model. The established genome-scale model can be used to understand the growth requirements of the human pathogen S. pyogenes and define optimal and suboptimal conditions, but also to describe differences and similarities between S. pyogenes and related lactic acid bacteria such as L. lactis in order to find strategies to reduce the growth of the pathogen and propose drug targets. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Genome-scale portrait and evolutionary significance of human-specific core promoter tri- and tetranucleotide short tandem repeats.

    Science.gov (United States)

    Nazaripanah, N; Adelirad, F; Delbari, A; Sahaf, R; Abbasi-Asl, T; Ohadi, M

    2018-04-05

    While there is an ongoing trend to identify single nucleotide substitutions (SNSs) that are linked to inter/intra-species differences and disease phenotypes, short tandem repeats (STRs)/microsatellites may be of equal (if not more) importance in the above processes. Genes that contain STRs in their promoters have higher expression divergence compared to genes with fixed or no STRs in the gene promoters. In line with the above, recent reports indicate a role of repetitive sequences in the rise of young transcription start sites (TSSs) in human evolution. Following a comparative genomics study of all human protein-coding genes annotated in the GeneCards database, here we provide a genome-scale portrait of human-specific short- and medium-size (≥ 3-repeats) tri- and tetranucleotide STRs and STR motifs in the critical core promoter region between - 120 and + 1 to the TSS and evidence of skewing of this compartment in reference to the STRs that are not human-specific (Levene's test p human-specific transcripts was detected in the tri and tetra human-specific compartments (mid-p genome-scale skewing of STRs at a specific region of the human genome and a link between a number of these STRs and TSS selection/transcript specificity. The STRs and genes listed here may have a role in the evolution and development of characteristics and phenotypes that are unique to the human species.

  11. Gender Identification of the Speaker Using VQ Method

    Directory of Open Access Journals (Sweden)

    Vasif V. Nabiyev

    2009-11-01

    Full Text Available Speaking is the easiest and natural form of communication between people. Intensive studies are made in order to provide this communication via computers between people. The systems using voice biometric technology are attracting attention especially in the angle of cost and usage. When compared with the other biometic systems the application is much more practical. For example by using a microphone placed in the environment voice record can be obtained even without notifying the user and the system can be applied. Moreover the remote access facility is one of the other advantages of voice biometry. In this study, it is aimed to automatically determine the gender of the speaker through the speech waves which include personal information. If the speaker gender can be determined while composing models according to the gender information, the success of voice recognition systems can be increased in an important degree. Generally all the speaker recognition systems are composed of two parts which are feature extraction and matching. Feature extraction is the procedure in which the least information presenting the speech and the speaker is determined through voice signal. There are different features used in voice applications such as LPC, MFCC and PLP. In this study as a feature vector MFCC is used. Feature mathcing is the procedure in which the features derived from unknown speakers and known speaker group are compared. According to the text used in comparison the system is devided to two parts that are text dependent and text independent. While the same text is used in text dependent systems, different texts are used in indepentent text systems. Nowadays, DTW and HMM are text dependent, VQ and GMM are text indepentent matching methods. In this study due to the high success ratio and simple application features VQ approach is used.In this study a system which determines the speaker gender automatically and text independent is proposed. The proposed

  12. Metamodel-based inverse method for parameter identification: elastic-plastic damage model

    Science.gov (United States)

    Huang, Changwu; El Hami, Abdelkhalak; Radi, Bouchaïb

    2017-04-01

    This article proposed a metamodel-based inverse method for material parameter identification and applies it to elastic-plastic damage model parameter identification. An elastic-plastic damage model is presented and implemented in numerical simulation. The metamodel-based inverse method is proposed in order to overcome the disadvantage in computational cost of the inverse method. In the metamodel-based inverse method, a Kriging metamodel is constructed based on the experimental design in order to model the relationship between material parameters and the objective function values in the inverse problem, and then the optimization procedure is executed by the use of a metamodel. The applications of the presented material model and proposed parameter identification method in the standard A 2017-T4 tensile test prove that the presented elastic-plastic damage model is adequate to describe the material's mechanical behaviour and that the proposed metamodel-based inverse method not only enhances the efficiency of parameter identification but also gives reliable results.

  13. System identification by methods from the statistical signal theory, history and state of the art

    International Nuclear Information System (INIS)

    Christensen, Palle; Gundersen, Vidar B.

    1999-01-01

    Condition monitoring is an important area in which the OECD Halden Reactor Project has developed several tools. This paper presents a general overview of methods utilised in diagnosis systems, signal validation systems and process optimisation systems such as EFD, Mocom, Aladdin and PEANO. An overview of lessons learned on diagnosis of technical systems with special reference to system identification is reported. The analysis of input-output behaviour by special, suitable methods may be used as a tool for diagnosis. An overview of methods for empirical modelling and data analysis and their major differences is presented. It is explained how system identification methods and transforms may be used to build models based on observed data from a system. According to the Webster dictionary diagnosis is 'Investigation or analysis of the cause or nature of a condition, situation or a problem.' By examining data collected from a process the aim is to detect abnormal conditions and if possible understand what has been the cause of the observed problem. Section 1 gives a retrospective view at the development in the field of system identification. Section 2 presents a classification of the methods, while section 3 provides some practical advice on how diagnosis can be carried out by means of system identification methods (author) (ml)

  14. Analysis of blind identification methods for estimation of kinetic parameters in dynamic medical imaging

    Science.gov (United States)

    Riabkov, Dmitri

    Compartment modeling of dynamic medical image data implies that the concentration of the tracer over time in a particular region of the organ of interest is well-modeled as a convolution of the tissue response with the tracer concentration in the blood stream. The tissue response is different for different tissues while the blood input is assumed to be the same for different tissues. The kinetic parameters characterizing the tissue responses can be estimated by blind identification methods. These algorithms use the simultaneous measurements of concentration in separate regions of the organ; if the regions have different responses, the measurement of the blood input function may not be required. In this work it is shown that the blind identification problem has a unique solution for two-compartment model tissue response. For two-compartment model tissue responses in dynamic cardiac MRI imaging conditions with gadolinium-DTPA contrast agent, three blind identification algorithms are analyzed here to assess their utility: Eigenvector-based Algorithm for Multichannel Blind Deconvolution (EVAM), Cross Relations (CR), and Iterative Quadratic Maximum Likelihood (IQML). Comparisons of accuracy with conventional (not blind) identification techniques where the blood input is known are made as well. The statistical accuracies of estimation for the three methods are evaluated and compared for multiple parameter sets. The results show that the IQML method gives more accurate estimates than the other two blind identification methods. A proof is presented here that three-compartment model blind identification is not unique in the case of only two regions. It is shown that it is likely unique for the case of more than two regions, but this has not been proved analytically. For the three-compartment model the tissue responses in dynamic FDG PET imaging conditions are analyzed with the blind identification algorithms EVAM and Separable variables Least Squares (SLS). A method of

  15. New methods of microbiological identification using MALDI-TOF

    Directory of Open Access Journals (Sweden)

    Jacyr Pasternak

    2012-03-01

    Full Text Available Rapid diagnosis of pathogens is decisive to guarantee adequatetherapy in infections: culture methods are precise and sensitive, butrather slow. New resources are available to enable faster diagnosis,and the most promising is MALDI-TOF technology: mass spectrometryapplied to microbiological diagnosis. Times as fast as 10 to 15 minutes to etiological diagnosis are possible after a positive blood culture result. We hope to have this technology in our laboratory, ANVISA permitting and improving their very slow rate of doing things… MALDI-TOF is basically putting a sample of culture or an enriched suspension of the probable pathogen over a small spot with a matrix and vaporizing it with a laser pulse: the products are aspired into a chamber, ionized and reach detectors at variable times: the detectors show time of arrival and quantity of the product, and each pathogen has its characteristic spectrum analyzed by a software.

  16. Identification of mine waters by statistical multivariate methods

    Energy Technology Data Exchange (ETDEWEB)

    Mali, N [IGGG, Ljubljana (Slovenia)

    1992-01-01

    Three water-bearing aquifers are present in the Velenje lignite mine. The aquifer waters have differing chemical composition; a geochemical water analysis can therefore determine the source of mine water influx. Mine water samples from different locations in the mine were analyzed, the results of chemical content and of electric conductivity of mine water were statistically processed by means of MICROGAS, SPSS-X and IN STATPAC computer programs, which apply three multivariate statistical methods (discriminate, cluster and factor analysis). Reliability of calculated values was determined with the Kolmogorov and Smirnov tests. It is concluded that laboratory analysis of single water samples can produce measurement errors, but statistical processing of water sample data can identify origin and movement of mine water. 15 refs.

  17. Research on Palmprint Identification Method Based on Quantum Algorithms

    Directory of Open Access Journals (Sweden)

    Hui Li

    2014-01-01

    Full Text Available Quantum image recognition is a technology by using quantum algorithm to process the image information. It can obtain better effect than classical algorithm. In this paper, four different quantum algorithms are used in the three stages of palmprint recognition. First, quantum adaptive median filtering algorithm is presented in palmprint filtering processing. Quantum filtering algorithm can get a better filtering result than classical algorithm through the comparison. Next, quantum Fourier transform (QFT is used to extract pattern features by only one operation due to quantum parallelism. The proposed algorithm exhibits an exponential speed-up compared with discrete Fourier transform in the feature extraction. Finally, quantum set operations and Grover algorithm are used in palmprint matching. According to the experimental results, quantum algorithm only needs to apply square of N operations to find out the target palmprint, but the traditional method needs N times of calculation. At the same time, the matching accuracy of quantum algorithm is almost 100%.

  18. Study on identification method of auto refurbishment test

    Science.gov (United States)

    Jiang, Zhenfei; Feng, Qingfu; Wang, Zhengyu; Jiang, Suqin; Chen, Xing; Zheng, Shaoyuan; Li, Bokui

    2018-04-01

    In recent years, a large number of refurbished cars inflow into the market as new cars. The traditional methods to identify refurbished cars are mostly based on experience, the subjectivity is too high and the credibility is low. In the production of automobile, the state and the automobile industry set clear standards for the thickness of the automobile paint. There is a big difference between the thickness of machine spraying and manual spraying. By studying this difference and combining with the standard, it can be identified accurately whether the car has been renovated; during the second assembly process, the surface of some parts (such as bolts) will have obvious signs of wear and tear due to the regular assembly and disassembly, it can also be identified accurately through the study of these assembly traces.

  19. Benchmarking of methods for identification of antimicrobial resistance genes in bacterial whole genome data

    DEFF Research Database (Denmark)

    Clausen, Philip T. L. C.; Zankari, Ea; Aarestrup, Frank Møller

    2016-01-01

    to two different methods in current use for identification of antibiotic resistance genes in bacterial WGS data. A novel method, KmerResistance, which examines the co-occurrence of k-mers between the WGS data and a database of resistance genes, was developed. The performance of this method was compared...... with two previously described methods; ResFinder and SRST2, which use an assembly/BLAST method and BWA, respectively, using two datasets with a total of 339 isolates, covering five species, originating from the Oxford University Hospitals NHS Trust and Danish pig farms. The predicted resistance...... was compared with the observed phenotypes for all isolates. To challenge further the sensitivity of the in silico methods, the datasets were also down-sampled to 1% of the reads and reanalysed. The best results were obtained by identification of resistance genes by mapping directly against the raw reads...

  20. A simple method for identification of irradiated spices

    International Nuclear Information System (INIS)

    Behere, A.; Desai, S.R.P.; Nair, P.M.; Rao, S.M.D.

    1992-01-01

    Thermoluminescence (TL) properties of curry powder, a salt containing spice mixture, and three different ground spices, viz, chilli, turmeric and pepper, were compared with TL of table salt. The spices other than curry powder, did not exhibit characteristic TL in the absence of salt. Therefore studies were initiated to develop a simple and reliable method using common salt for distinguishing irradiated spices (10 kGy) from unirradiated ones under normal conditions of storage. Common salt exhibited a characteristic TL glow at 170 o C. However, when present in curry powder, the TL glow of salt showed a shift to 208 o C. It was further observed that upon storage up to 6 months, the TL of irradiated curry powder retained about 10% of the original intensity and still could be distinguished from the untreated samples. From our results it is evident that common salt could be used as an indicator either internally or externally in small sachets for incorporating into prepacked spices. (author)

  1. A simple method for identification of irradiated spices

    Energy Technology Data Exchange (ETDEWEB)

    Behere, A; Desai, S R.P.; Nair, P M [Bhabha Atomic Research Centre, Bombay (India). Food Technology and Enzyme Engineering Div.; Rao, S M.D. [Bhabha Atomic Research Centre, Bombay (India). Technical Physics and Prototype Engineering Div.

    1992-07-01

    Thermoluminescence (TL) properties of curry powder, a salt containing spice mixture, and three different ground spices, viz, chilli, turmeric and pepper, were compared with TL of table salt. The spices other than curry powder, did not exhibit characteristic TL in the absence of salt. Therefore studies were initiated to develop a simple and reliable method using common salt for distinguishing irradiated spices (10 kGy) from unirradiated ones under normal conditions of storage. Common salt exhibited a characteristic TL glow at 170{sup o}C. However, when present in curry powder, the TL glow of salt showed a shift to 208{sup o}C. It was further observed that upon storage up to 6 months, the TL of irradiated curry powder retained about 10% of the original intensity and still could be distinguished from the untreated samples. From our results it is evident that common salt could be used as an indicator either internally or externally in small sachets for incorporating into prepacked spices. (author).

  2. Identification of rural landscape classes through a GIS clustering method

    Directory of Open Access Journals (Sweden)

    Irene Diti

    2013-09-01

    Full Text Available The paper presents a methodology aimed at supporting the rural planning process. The analysis of the state of the art of local and regional policies focused on rural and suburban areas, and the study of the scientific literature in the field of spatial analysis methodologies, have allowed the definition of the basic concept of the research. The proposed method, developed in a GIS, is based on spatial metrics selected and defined to cover various agricultural, environmental, and socio-economic components. The specific goal of the proposed methodology is to identify homogeneous extra-urban areas through their objective characterization at different scales. Once areas with intermediate urban-rural characters have been identified, the analysis is then focused on the more detailed definition of periurban agricultural areas. The synthesis of the results of the analysis of the various landscape components is achieved through an original interpretative key which aims to quantify the potential impacts of rural areas on the urban system. This paper presents the general framework of the methodology and some of the main results of its first implementation through an Italian case study.

  3. Subspace methods for identification of human ankle joint stiffness.

    Science.gov (United States)

    Zhao, Y; Westwick, D T; Kearney, R E

    2011-11-01

    Joint stiffness, the dynamic relationship between the angular position of a joint and the torque acting about it, describes the dynamic, mechanical behavior of a joint during posture and movement. Joint stiffness arises from both intrinsic and reflex mechanisms, but the torques due to these mechanisms cannot be measured separately experimentally, since they appear and change together. Therefore, the direct estimation of the intrinsic and reflex stiffnesses is difficult. In this paper, we present a new, two-step procedure to estimate the intrinsic and reflex components of ankle stiffness. In the first step, a discrete-time, subspace-based method is used to estimate a state-space model for overall stiffness from the measured overall torque and then predict the intrinsic and reflex torques. In the second step, continuous-time models for the intrinsic and reflex stiffnesses are estimated from the predicted intrinsic and reflex torques. Simulations and experimental results demonstrate that the algorithm estimates the intrinsic and reflex stiffnesses accurately. The new subspace-based algorithm has three advantages over previous algorithms: 1) It does not require iteration, and therefore, will always converge to an optimal solution; 2) it provides better estimates for data with high noise or short sample lengths; and 3) it provides much more accurate results for data acquired under the closed-loop conditions, that prevail when subjects interact with compliant loads.

  4. Best methods for identification and treatment of PCOS.

    Science.gov (United States)

    Artini, P G; Di Berardino, O M; Simi, G; Papini, F; Ruggiero, M; Monteleone, P; Cela, V

    2010-02-01

    The polycystic ovarian syndrome (PCOS) includes a wide spectrum of clinical symptoms and signs. Three different diagnostic classifications have been proposed to define this disease. The first one, published in 1990, known as the "NIH criteria" requires the simultaneous presence of hyperandrogenism and menstrual dysfunction in order to diagnose PCOS. Later on, in 2003, an expert panel met in Rotterdam and added to the previous criteria the presence of polycystic ovarian morphology detected by transvaginal ultrasonography. The later classification broadened the spectrum of PCOS and also included women with oligomenorrhea and PCO without hyperandrogenism or hyperandrogenism and PCO without menstrual dysfunction. Finally, the Androgen Excess Society, published in 2006 new diagnostic criteria which required the presence of clinical or biochemical hyperandrogenism, with either PCO or menstrual dysfunction to diagnose PCOS. This review focuses on the diagnostic techniques and methods of treatment for PCOS patients. Special attention is given to the role of insulin resistance and the potential utility of insulin sensitizers in management of the syndrome. The benefit and utmost importance of lifestyle modification for the long-term health of these women is stressed as well. It is hoped that some clarity in this regard will allow more women to not only be diagnosed and managed properly for their presenting symptoms (hirsutism, irregular menses, etc.), but also to be educated and managed for the continuing health risk of insulin resistance throughout their lives.

  5. Comparison among four proposed direct blood culture microbial identification methods using MALDI-TOF MS

    Directory of Open Access Journals (Sweden)

    Ali M. Bazzi

    2017-05-01

    Full Text Available Summary: Matrix-assisted laser desorption-ionization time-of-flight (MALDI-TOF mass spectrometry facilitates rapid and accurate identification of pathogens, which is critical for sepsis patients.In this study, we assessed the accuracy in identification of both Gram-negative and Gram-positive bacteria, except for Streptococcus viridans, using four rapid blood culture methods with Vitek MALDI-TOF-MS. We compared our proposed lysis centrifugation followed by washing and 30% acetic acid treatment method (method 2 with two other lysis centrifugation methods (washing and 30% formic acid treatment (method 1; 100% ethanol treatment (method 3, and picking colonies from 90 to 180 min subculture plates (method 4. Methods 1 and 2 identified all organisms down to species level with 100% accuracy, except for Streptococcus viridans, Streptococcus pyogenes, Enterobacter cloacae and Proteus vulgaris. The latter two were identified to genus level with 100% accuracy. Each method exhibited excellent accuracy and precision in terms of identification to genus level with certain limitations. Keywords: MALDI-TOF, Gram-negative, Gram-positive, Sepsis, Blood culture

  6. Comparison among four proposed direct blood culture microbial identification methods using MALDI-TOF MS.

    Science.gov (United States)

    Bazzi, Ali M; Rabaan, Ali A; El Edaily, Zeyad; John, Susan; Fawarah, Mahmoud M; Al-Tawfiq, Jaffar A

    Matrix-assisted laser desorption-ionization time-of-flight (MALDI-TOF) mass spectrometry facilitates rapid and accurate identification of pathogens, which is critical for sepsis patients. In this study, we assessed the accuracy in identification of both Gram-negative and Gram-positive bacteria, except for Streptococcus viridans, using four rapid blood culture methods with Vitek MALDI-TOF-MS. We compared our proposed lysis centrifugation followed by washing and 30% acetic acid treatment method (method 2) with two other lysis centrifugation methods (washing and 30% formic acid treatment (method 1); 100% ethanol treatment (method 3)), and picking colonies from 90 to 180min subculture plates (method 4). Methods 1 and 2 identified all organisms down to species level with 100% accuracy, except for Streptococcus viridans, Streptococcus pyogenes, Enterobacter cloacae and Proteus vulgaris. The latter two were identified to genus level with 100% accuracy. Each method exhibited excellent accuracy and precision in terms of identification to genus level with certain limitations. Copyright © 2016 King Saud Bin Abdulaziz University for Health Sciences. Published by Elsevier Ltd. All rights reserved.

  7. Parameter Identification of Ship Maneuvering Models Using Recursive Least Square Method Based on Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Man Zhu

    2017-03-01

    Full Text Available Determination of ship maneuvering models is a tough task of ship maneuverability prediction. Among several prime approaches of estimating ship maneuvering models, system identification combined with the full-scale or free- running model test is preferred. In this contribution, real-time system identification programs using recursive identification method, such as the recursive least square method (RLS, are exerted for on-line identification of ship maneuvering models. However, this method seriously depends on the objects of study and initial values of identified parameters. To overcome this, an intelligent technology, i.e., support vector machines (SVM, is firstly used to estimate initial values of the identified parameters with finite samples. As real measured motion data of the Mariner class ship always involve noise from sensors and external disturbances, the zigzag simulation test data include a substantial quantity of Gaussian white noise. Wavelet method and empirical mode decomposition (EMD are used to filter the data corrupted by noise, respectively. The choice of the sample number for SVM to decide initial values of identified parameters is extensively discussed and analyzed. With de-noised motion data as input-output training samples, parameters of ship maneuvering models are estimated using RLS and SVM-RLS, respectively. The comparison between identification results and true values of parameters demonstrates that both the identified ship maneuvering models from RLS and SVM-RLS have reasonable agreements with simulated motions of the ship, and the increment of the sample for SVM positively affects the identification results. Furthermore, SVM-RLS using data de-noised by EMD shows the highest accuracy and best convergence.

  8. Identification of Dynamic Flow Stress Curves Using the Virtual Fields Methods: Theoretical Feasibility Analysis

    Science.gov (United States)

    Leem, Dohyun; Kim, Jin-Hwan; Barlat, Frédéric; Song, Jung Han; Lee, Myoung-Gyu

    2018-03-01

    An inverse approach based on the virtual fields method (VFM) is presented to identify the material hardening parameters under dynamic deformation. This dynamic-VFM (D-VFM) method does not require load information for the parameter identification. Instead, it utilizes acceleration fields in a specimen's gage region. To investigate the feasibility of the proposed inverse approach for dynamic deformation, the virtual experiments using dynamic finite element simulations were conducted. The simulation could provide all the necessary data for the identification such as displacement, strain, and acceleration fields. The accuracy of the identification results was evaluated by changing several parameters such as specimen geometry, velocity, and traction boundary conditions. The analysis clearly shows that the D-VFM which utilizes acceleration fields can be a good alternative to the conventional identification procedure that uses load information. Also, it was found that proper deformation conditions are required for generating sufficient acceleration fields during dynamic deformation to enhance the identification accuracy with the D-VFM.

  9. Comparative study using phenotypic, genotypic and proteomics methods for identification of coagulase-negative staphylococci

    NARCIS (Netherlands)

    Dr. P.F.G. Wolffs; Ing M. Valkenburg; Dr. A.J.C. van den Brule, van den; M.Sc. A. Jansz; Drs A.J.M. Loonen; Ing J.N.B. Bergland

    2012-01-01

    Five methods were compared to determine the best technique for accurate identification of coagulase-negative staphylococci (CoNS) (n=142 strains). MALDI-TOF MS showed the best results for rapid and accurate CoNS differentiation (correct identity in 99.3%). An alternative to this approach could be

  10. Animal DNA identification in food products and animal feed by real time polymerase chain reaction method

    Directory of Open Access Journals (Sweden)

    Людмила Мар’янівна Іщенко

    2016-11-01

    Full Text Available Approbation of diagnostic tests for species identification of beef, pork and chicken by real time polymerase chain reaction method was done. Meat food, including heat treated and animal feed, was used for research. The fact of inconsistencies was revealed for product composition of some meat products that is marked by manufacturer 

  11. Measurement methods for high energy particle identification in gaseous mixture detectors

    International Nuclear Information System (INIS)

    Marchand, Patrick.

    1981-01-01

    In this work, we discuss some methods for high energy particle identification. We study and design a MWPC equipped with a preamplifier gap for increased resolution. In addition, we propose a new mehod of counting primary collisions. The electronic system used for multiplexing analog wire signals is also described [fr

  12. Numerical method of identification of an unknown source term in a heat equation

    Directory of Open Access Journals (Sweden)

    Fatullayev Afet Golayo?lu

    2002-01-01

    Full Text Available A numerical procedure for an inverse problem of identification of an unknown source in a heat equation is presented. Approach of proposed method is to approximate unknown function by polygons linear pieces which are determined consecutively from the solution of minimization problem based on the overspecified data. Numerical examples are presented.

  13. Systems identification: a theoretical method applied to tracer kinetics in aquatic microcosms

    International Nuclear Information System (INIS)

    Halfon, E.; Georgia Univ., Athens

    1974-01-01

    A mathematical model of radionuclide kinetics in a laboratory microcosm was built and the transfer parameters estimated by multiple regression and system identification techniques. Insight into the functioning of the system was obtained from analysis of the model. Methods employed have allowed movements of radioisotopes not directly observable in the experimental systems to be distinguished. Results are generalized to whole ecosystems

  14. New logarithmic technique of diffusivity identification using the flash method; Nouvelle technique logarithmique d`identification de la diffusivite par la methode flash

    Energy Technology Data Exchange (ETDEWEB)

    Thermitus, M.A.; Laurent, M. [Institut National des Sciences Appliquees (INSA), 69 - Villeurbanne (France)

    1997-12-31

    Using a logarithmic transformation, the thermogram of a flash experiment can be interpreted as the sum of the adiabatic model solution with a term representative of the losses. Two methods based on this transformation are proposed in this study. They are based on the identification of a parameter that depends on the thickness of the sample and on its diffusivity and not on the experimental conditions. They allow to identify the diffusivity with a high precision even for materials with a low conductivity at high temperatures. (J.S.) 12 refs.

  15. Nonlinear system identification NARMAX methods in the time, frequency, and spatio-temporal domains

    CERN Document Server

    Billings, Stephen A

    2013-01-01

    Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains describes a comprehensive framework for the identification and analysis of nonlinear dynamic systems in the time, frequency, and spatio-temporal domains. This book is written with an emphasis on making the algorithms accessible so that they can be applied and used in practice. Includes coverage of: The NARMAX (nonlinear autoregressive moving average with exogenous inputs) modelThe orthogonal least squares algorithm that allows models to be built term by

  16. Identification techniques for phenomenological models of hysteresis based on the conjugate gradient method

    International Nuclear Information System (INIS)

    Andrei, Petru; Oniciuc, Liviu; Stancu, Alexandru; Stoleriu, Laurentiu

    2007-01-01

    An identification technique for the parameters of phenomenological models of hysteresis is presented. The basic idea of our technique is to set up a system of equations for the parameters of the model as a function of known quantities on the major or minor hysteresis loops (e.g. coercive force, susceptibilities at various points, remanence), or other magnetization curves. This system of equations can be either over or underspecified and is solved by using the conjugate gradient method. Numerical results related to the identification of parameters in the Energetic, Jiles-Atherton, and Preisach models are presented

  17. Identification of the corporate values of an enterprise: theory, approaches, methodic

    Directory of Open Access Journals (Sweden)

    Kozlov Vladimir Aleksandrovich

    2015-07-01

    Full Text Available This article focuses on research and composition of the instrument to identify the corporate values of the enterprise and practical activities to support them. The first part based on theoretical evidence of essence and correlation between notions of ‘Corporate culture’ and ‘Corporate values’. The method of corporate values identification, based on indirect approach, is proposed and the examples are provided. The results of implemented project for corporate values identification at industrial enterprise are presented. For further support the tasks and activities for corporate values management are proposed.

  18. Simple Sample Preparation Method for Direct Microbial Identification and Susceptibility Testing From Positive Blood Cultures.

    Science.gov (United States)

    Pan, Hong-Wei; Li, Wei; Li, Rong-Guo; Li, Yong; Zhang, Yi; Sun, En-Hua

    2018-01-01

    Rapid identification and determination of the antibiotic susceptibility profiles of the infectious agents in patients with bloodstream infections are critical steps in choosing an effective targeted antibiotic for treatment. However, there has been minimal effort focused on developing combined methods for the simultaneous direct identification and antibiotic susceptibility determination of bacteria in positive blood cultures. In this study, we constructed a lysis-centrifugation-wash procedure to prepare a bacterial pellet from positive blood cultures, which can be used directly for identification by matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) and antibiotic susceptibility testing by the Vitek 2 system. The method was evaluated using a total of 129 clinical bacteria-positive blood cultures. The whole sample preparation process could be completed in identification was 96.49% for gram-negative bacteria and 97.22% for gram-positive bacteria. Vitek 2 antimicrobial susceptibility testing of gram-negative bacteria showed an agreement rate of antimicrobial categories of 96.89% with a minor error, major error, and very major error rate of 2.63, 0.24, and 0.24%, respectively. Category agreement of antimicrobials against gram-positive bacteria was 92.81%, with a minor error, major error, and very major error rate of 4.51, 1.22, and 1.46%, respectively. These results indicated that our direct antibiotic susceptibility analysis method worked well compared to the conventional culture-dependent laboratory method. Overall, this fast, easy, and accurate method can facilitate the direct identification and antibiotic susceptibility testing of bacteria in positive blood cultures.

  19. Simple Sample Preparation Method for Direct Microbial Identification and Susceptibility Testing From Positive Blood Cultures

    Directory of Open Access Journals (Sweden)

    Hong-wei Pan

    2018-03-01

    Full Text Available Rapid identification and determination of the antibiotic susceptibility profiles of the infectious agents in patients with bloodstream infections are critical steps in choosing an effective targeted antibiotic for treatment. However, there has been minimal effort focused on developing combined methods for the simultaneous direct identification and antibiotic susceptibility determination of bacteria in positive blood cultures. In this study, we constructed a lysis-centrifugation-wash procedure to prepare a bacterial pellet from positive blood cultures, which can be used directly for identification by matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS and antibiotic susceptibility testing by the Vitek 2 system. The method was evaluated using a total of 129 clinical bacteria-positive blood cultures. The whole sample preparation process could be completed in <15 min. The correct rate of direct MALDI-TOF MS identification was 96.49% for gram-negative bacteria and 97.22% for gram-positive bacteria. Vitek 2 antimicrobial susceptibility testing of gram-negative bacteria showed an agreement rate of antimicrobial categories of 96.89% with a minor error, major error, and very major error rate of 2.63, 0.24, and 0.24%, respectively. Category agreement of antimicrobials against gram-positive bacteria was 92.81%, with a minor error, major error, and very major error rate of 4.51, 1.22, and 1.46%, respectively. These results indicated that our direct antibiotic susceptibility analysis method worked well compared to the conventional culture-dependent laboratory method. Overall, this fast, easy, and accurate method can facilitate the direct identification and antibiotic susceptibility testing of bacteria in positive blood cultures.

  20. An Automatic Parameter Identification Method for a PMSM Drive with LC-Filter

    DEFF Research Database (Denmark)

    Bech, Michael Møller; Christensen, Jeppe Haals; Weber, Magnus L.

    2016-01-01

    of the PMSM fed through an LC-filter. Based on the measured current response, model parameters for both the filter (L, R, C) and the PMSM (L and R) are estimated: First, the frequency response of the system is estimated using Welch Modified Periodogram method and then an optimization algorithm is used to find...... the parameters in an analytical reference model that minimize the model error. To demonstrate the practical feasibility of the method, a fully functional drive including an embedded real-time controller has been built. In addition to modulation, data acquisition and control the whole parameter identification...... method is also implemented on the real-time controller. Based on laboratory experiments on a 22 kW drive, it is concluded that the embedded identification method can estimate the five parameters in less than ten seconds....

  1. Review on applied foods and analyzed methods in identification testing of irradiated foods

    International Nuclear Information System (INIS)

    Kim, Kwang Hoon; Lee, Hoo Chul; Park, Sung Hyun; Kim, Soo Jin; Kim, Kwan Soo; Jeong, Il Yun; Lee, Ju Woon; Yook, Hong Sun

    2010-01-01

    Identification methods of irradiated foods have been adopted as official test by EU and Codex. PSL, TL, ESR and GC/MS methods were registered in Korea food code on 2009 and put in force as control system of verification for labelling of food irradiation. But most generally applicable PSL and TL methods are specified applicable foods according to domestic approved items. Unlike these specifications, foods unpermitted in Korea are included in applicable items of ESR and GC/MS methods. According to recent research data, numerous food groups are possible to effective legal control by identification and these items are demanded to permit regulations for irradiation additionally. Especially, the prohibition of irradiation for meats or seafoods is not harmonized with international standards and interacts as trade friction or industrial restrictions due to unprepared domestic regulation. Hence, extension of domestic legal permission for food irradiation can contrive to related industrial development and also can reduce trade friction and enhance international competitiveness

  2. A review of output-only structural mode identification literature employing blind source separation methods

    Science.gov (United States)

    Sadhu, A.; Narasimhan, S.; Antoni, J.

    2017-09-01

    Output-only modal identification has seen significant activity in recent years, especially in large-scale structures where controlled input force generation is often difficult to achieve. This has led to the development of new system identification methods which do not require controlled input. They often work satisfactorily if they satisfy some general assumptions - not overly restrictive - regarding the stochasticity of the input. Hundreds of papers covering a wide range of applications appear every year related to the extraction of modal properties from output measurement data in more than two dozen mechanical, aerospace and civil engineering journals. In little more than a decade, concepts of blind source separation (BSS) from the field of acoustic signal processing have been adopted by several researchers and shown that they can be attractive tools to undertake output-only modal identification. Originally intended to separate distinct audio sources from a mixture of recordings, mathematical equivalence to problems in linear structural dynamics have since been firmly established. This has enabled many of the developments in the field of BSS to be modified and applied to output-only modal identification problems. This paper reviews over hundred articles related to the application of BSS and their variants to output-only modal identification. The main contribution of the paper is to present a literature review of the papers which have appeared on the subject. While a brief treatment of the basic ideas are presented where relevant, a comprehensive and critical explanation of their contents is not attempted. Specific issues related to output-only modal identification and the relative advantages and limitations of BSS methods both from theoretical and application standpoints are discussed. Gap areas requiring additional work are also summarized and the paper concludes with possible future trends in this area.

  3. IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models.

    Science.gov (United States)

    Ye, Chao; Xu, Nan; Dong, Chuan; Ye, Yuannong; Zou, Xuan; Chen, Xiulai; Guo, Fengbiao; Liu, Liming

    2017-04-07

    Genome-scale metabolic models (GSMMs) constitute a platform that combines genome sequences and detailed biochemical information to quantify microbial physiology at the system level. To improve the unity, integrity, correctness, and format of data in published GSMMs, a consensus IMGMD database was built in the LAMP (Linux + Apache + MySQL + PHP) system by integrating and standardizing 328 GSMMs constructed for 139 microorganisms. The IMGMD database can help microbial researchers download manually curated GSMMs, rapidly reconstruct standard GSMMs, design pathways, and identify metabolic targets for strategies on strain improvement. Moreover, the IMGMD database facilitates the integration of wet-lab and in silico data to gain an additional insight into microbial physiology. The IMGMD database is freely available, without any registration requirements, at http://imgmd.jiangnan.edu.cn/database.

  4. Evaluating current automatic de-identification methods with Veteran’s health administration clinical documents

    Directory of Open Access Journals (Sweden)

    Ferrández Oscar

    2012-07-01

    Full Text Available Abstract Background The increased use and adoption of Electronic Health Records (EHR causes a tremendous growth in digital information useful for clinicians, researchers and many other operational purposes. However, this information is rich in Protected Health Information (PHI, which severely restricts its access and possible uses. A number of investigators have developed methods for automatically de-identifying EHR documents by removing PHI, as specified in the Health Insurance Portability and Accountability Act “Safe Harbor” method. This study focuses on the evaluation of existing automated text de-identification methods and tools, as applied to Veterans Health Administration (VHA clinical documents, to assess which methods perform better with each category of PHI found in our clinical notes; and when new methods are needed to improve performance. Methods We installed and evaluated five text de-identification systems “out-of-the-box” using a corpus of VHA clinical documents. The systems based on machine learning methods were trained with the 2006 i2b2 de-identification corpora and evaluated with our VHA corpus, and also evaluated with a ten-fold cross-validation experiment using our VHA corpus. We counted exact, partial, and fully contained matches with reference annotations, considering each PHI type separately, or only one unique ‘PHI’ category. Performance of the systems was assessed using recall (equivalent to sensitivity and precision (equivalent to positive predictive value metrics, as well as the F2-measure. Results Overall, systems based on rules and pattern matching achieved better recall, and precision was always better with systems based on machine learning approaches. The highest “out-of-the-box” F2-measure was 67% for partial matches; the best precision and recall were 95% and 78%, respectively. Finally, the ten-fold cross validation experiment allowed for an increase of the F2-measure to 79% with partial matches

  5. Comprehensive reconstruction and in silico analysis of Aspergillus niger genome-scale metabolic network model that accounts for 1210 ORFs.

    Science.gov (United States)

    Lu, Hongzhong; Cao, Weiqiang; Ouyang, Liming; Xia, Jianye; Huang, Mingzhi; Chu, Ju; Zhuang, Yingping; Zhang, Siliang; Noorman, Henk

    2017-03-01

    Aspergillus niger is one of the most important cell factories for industrial enzymes and organic acids production. A comprehensive genome-scale metabolic network model (GSMM) with high quality is crucial for efficient strain improvement and process optimization. The lack of accurate reaction equations and gene-protein-reaction associations (GPRs) in the current best model of A. niger named GSMM iMA871, however, limits its application scope. To overcome these limitations, we updated the A. niger GSMM by combining the latest genome annotation and literature mining technology. Compared with iMA871, the number of reactions in iHL1210 was increased from 1,380 to 1,764, and the number of unique ORFs from 871 to 1,210. With the aid of our transcriptomics analysis, the existence of 63% ORFs and 68% reactions in iHL1210 can be verified when glucose was used as the only carbon source. Physiological data from chemostat cultivations, 13 C-labeled and molecular experiments from the published literature were further used to check the performance of iHL1210. The average correlation coefficients between the predicted fluxes and estimated fluxes from 13 C-labeling data were sufficiently high (above 0.89) and the prediction of cell growth on most of the reported carbon and nitrogen sources was consistent. Using the updated genome-scale model, we evaluated gene essentiality on synthetic and yeast extract medium, as well as the effects of NADPH supply on glucoamylase production in A. niger. In summary, the new A. niger GSMM iHL1210 contains significant improvements with respect to the metabolic coverage and prediction performance, which paves the way for systematic metabolic engineering of A. niger. Biotechnol. Bioeng. 2017;114: 685-695. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  6. Genome-Scale, Constraint-Based Modeling of Nitrogen Oxide Fluxes during Coculture of Nitrosomonas europaea and Nitrobacter winogradskyi

    Science.gov (United States)

    Giguere, Andrew T.; Murthy, Ganti S.; Bottomley, Peter J.; Sayavedra-Soto, Luis A.

    2018-01-01

    ABSTRACT Nitrification, the aerobic oxidation of ammonia to nitrate via nitrite, emits nitrogen (N) oxide gases (NO, NO2, and N2O), which are potentially hazardous compounds that contribute to global warming. To better understand the dynamics of nitrification-derived N oxide production, we conducted culturing experiments and used an integrative genome-scale, constraint-based approach to model N oxide gas sources and sinks during complete nitrification in an aerobic coculture of two model nitrifying bacteria, the ammonia-oxidizing bacterium Nitrosomonas europaea and the nitrite-oxidizing bacterium Nitrobacter winogradskyi. The model includes biotic genome-scale metabolic models (iFC578 and iFC579) for each nitrifier and abiotic N oxide reactions. Modeling suggested both biotic and abiotic reactions are important sources and sinks of N oxides, particularly under microaerobic conditions predicted to occur in coculture. In particular, integrative modeling suggested that previous models might have underestimated gross NO production during nitrification due to not taking into account its rapid oxidation in both aqueous and gas phases. The integrative model may be found at https://github.com/chaplenf/microBiome-v2.1. IMPORTANCE Modern agriculture is sustained by application of inorganic nitrogen (N) fertilizer in the form of ammonium (NH4+). Up to 60% of NH4+-based fertilizer can be lost through leaching of nitrifier-derived nitrate (NO3−), and through the emission of N oxide gases (i.e., nitric oxide [NO], N dioxide [NO2], and nitrous oxide [N2O] gases), the latter being a potent greenhouse gas. Our approach to modeling of nitrification suggests that both biotic and abiotic mechanisms function as important sources and sinks of N oxides during microaerobic conditions and that previous models might have underestimated gross NO production during nitrification. PMID:29577088

  7. Genome-Scale, Constraint-Based Modeling of Nitrogen Oxide Fluxes during Coculture of Nitrosomonas europaea and Nitrobacter winogradskyi.

    Science.gov (United States)

    Mellbye, Brett L; Giguere, Andrew T; Murthy, Ganti S; Bottomley, Peter J; Sayavedra-Soto, Luis A; Chaplen, Frank W R

    2018-01-01

    Nitrification, the aerobic oxidation of ammonia to nitrate via nitrite, emits nitrogen (N) oxide gases (NO, NO 2 , and N 2 O), which are potentially hazardous compounds that contribute to global warming. To better understand the dynamics of nitrification-derived N oxide production, we conducted culturing experiments and used an integrative genome-scale, constraint-based approach to model N oxide gas sources and sinks during complete nitrification in an aerobic coculture of two model nitrifying bacteria, the ammonia-oxidizing bacterium Nitrosomonas europaea and the nitrite-oxidizing bacterium Nitrobacter winogradskyi . The model includes biotic genome-scale metabolic models (iFC578 and iFC579) for each nitrifier and abiotic N oxide reactions. Modeling suggested both biotic and abiotic reactions are important sources and sinks of N oxides, particularly under microaerobic conditions predicted to occur in coculture. In particular, integrative modeling suggested that previous models might have underestimated gross NO production during nitrification due to not taking into account its rapid oxidation in both aqueous and gas phases. The integrative model may be found at https://github.com/chaplenf/microBiome-v2.1. IMPORTANCE Modern agriculture is sustained by application of inorganic nitrogen (N) fertilizer in the form of ammonium (NH 4 + ). Up to 60% of NH 4 + -based fertilizer can be lost through leaching of nitrifier-derived nitrate (NO 3 - ), and through the emission of N oxide gases (i.e., nitric oxide [NO], N dioxide [NO 2 ], and nitrous oxide [N 2 O] gases), the latter being a potent greenhouse gas. Our approach to modeling of nitrification suggests that both biotic and abiotic mechanisms function as important sources and sinks of N oxides during microaerobic conditions and that previous models might have underestimated gross NO production during nitrification.

  8. Genome-scale comparison and constraint-based metabolic reconstruction of the facultative anaerobic Fe(III-reducer Rhodoferax ferrireducens

    Directory of Open Access Journals (Sweden)

    Daugherty Sean

    2009-09-01

    Full Text Available Abstract Background Rhodoferax ferrireducens is a metabolically versatile, Fe(III-reducing, subsurface microorganism that is likely to play an important role in the carbon and metal cycles in the subsurface. It also has the unique ability to convert sugars to electricity, oxidizing the sugars to carbon dioxide with quantitative electron transfer to graphite electrodes in microbial fuel cells. In order to expand our limited knowledge about R. ferrireducens, the complete genome sequence of this organism was further annotated and then the physiology of R. ferrireducens was investigated with a constraint-based, genome-scale in silico metabolic model and laboratory studies. Results The iterative modeling and experimental approach unveiled exciting, previously unknown physiological features, including an expanded range of substrates that support growth, such as cellobiose and citrate, and provided additional insights into important features such as the stoichiometry of the electron transport chain and the ability to grow via fumarate dismutation. Further analysis explained why R. ferrireducens is unable to grow via photosynthesis or fermentation of sugars like other members of this genus and uncovered novel genes for benzoate metabolism. The genome also revealed that R. ferrireducens is well-adapted for growth in the subsurface because it appears to be capable of dealing with a number of environmental insults, including heavy metals, aromatic compounds, nutrient limitation and oxidative stress. Conclusion This study demonstrates that combining genome-scale modeling with the annotation of a new genome sequence can guide experimental studies and accelerate the understanding of the physiology of under-studied yet environmentally relevant microorganisms.

  9. [Identification of special quality eggs with NIR spectroscopy technology based on symbol entropy feature extraction method].

    Science.gov (United States)

    Zhao, Yong; Hong, Wen-Xue

    2011-11-01

    Fast, nondestructive and accurate identification of special quality eggs is an urgent problem. The present paper proposed a new feature extraction method based on symbol entropy to identify near infrared spectroscopy of special quality eggs. The authors selected normal eggs, free range eggs, selenium-enriched eggs and zinc-enriched eggs as research objects and measured the near-infrared diffuse reflectance spectra in the range of 12 000-4 000 cm(-1). Raw spectra were symbolically represented with aggregation approximation algorithm and symbolic entropy was extracted as feature vector. An error-correcting output codes multiclass support vector machine classifier was designed to identify the spectrum. Symbolic entropy feature is robust when parameter changed and the highest recognition rate reaches up to 100%. The results show that the identification method of special quality eggs using near-infrared is feasible and the symbol entropy can be used as a new feature extraction method of near-infrared spectra.

  10. Analyses of Dynamics in Dairy Products and Identification of Lactic Acid Bacteria Population by Molecular Methods

    Directory of Open Access Journals (Sweden)

    Aytül Sofu

    2017-01-01

    Full Text Available Lactic acid bacteria (LAB with different ecological niches are widely seen in fermented meat, vegetables, dairy products and cereals as well as in fermented beverages. Lactic acid bacteria are the most important group of bacteria in dairy industry due to their probiotic characteristics and fermentation agents as starter culture. In the taxonomy of the lactic acid bacteria; by means of rep-PCR, which is the analysis of repetitive sequences that are based on 16S ribosomal RNA (rRNA gene sequence, it is possible to conduct structural microbial community analyses such as Restriction Fragment Length Polymorphism (RFLP analysis of DNA fragments of different sizes cut with enzymes, Random Amplified Polymorphic DNA (RAPD polymorphic DNA amplified randomly at low temperatures and Amplified Fragment-Length Polymorphism (AFLP-PCR of cut genomic DNA. Besides, in the recent years, non-culture-based molecular methods such as Pulse Field Gel Electrophoresis (PFGE, Denaturing Gradient Gel Electrophoresis (DGGE, Thermal Gradient Gel Electrophoresis (TGGE, and Fluorescence In-situ Hybridization (FISH have replaced classical methods once used for the identification of LAB. Identification of lactic acid bacteria culture independent regardless of the method will be one of the most important methods used in the future pyrosequencing as a Next Generation Sequencing (NGS techniques. This paper reviews molecular-method based studies conducted on the identification of LAB species in dairy products.

  11. Recon2Neo4j: applying graph database technologies for managing comprehensive genome-scale networks.

    Science.gov (United States)

    Balaur, Irina; Mazein, Alexander; Saqi, Mansoor; Lysenko, Artem; Rawlings, Christopher J; Auffray, Charles

    2017-04-01

    The goal of this work is to offer a computational framework for exploring data from the Recon2 human metabolic reconstruction model. Advanced user access features have been developed using the Neo4j graph database technology and this paper describes key features such as efficient management of the network data, examples of the network querying for addressing particular tasks, and how query results are converted back to the Systems Biology Markup Language (SBML) standard format. The Neo4j-based metabolic framework facilitates exploration of highly connected and comprehensive human metabolic data and identification of metabolic subnetworks of interest. A Java-based parser component has been developed to convert query results (available in the JSON format) into SBML and SIF formats in order to facilitate further results exploration, enhancement or network sharing. The Neo4j-based metabolic framework is freely available from: https://diseaseknowledgebase.etriks.org/metabolic/browser/ . The java code files developed for this work are available from the following url: https://github.com/ibalaur/MetabolicFramework . ibalaur@eisbm.org. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  12. Construction and Analysis of Two Genome-Scale Deletion Libraries for Bacillus subtilis.

    Science.gov (United States)

    Koo, Byoung-Mo; Kritikos, George; Farelli, Jeremiah D; Todor, Horia; Tong, Kenneth; Kimsey, Harvey; Wapinski, Ilan; Galardini, Marco; Cabal, Angelo; Peters, Jason M; Hachmann, Anna-Barbara; Rudner, David Z; Allen, Karen N; Typas, Athanasios; Gross, Carol A

    2017-03-22

    A systems-level understanding of Gram-positive bacteria is important from both an environmental and health perspective and is most easily obtained when high-quality, validated genomic resources are available. To this end, we constructed two ordered, barcoded, erythromycin-resistance- and kanamycin-resistance-marked single-gene deletion libraries of the Gram-positive model organism, Bacillus subtilis. The libraries comprise 3,968 and 3,970 genes, respectively, and overlap in all but four genes. Using these libraries, we update the set of essential genes known for this organism, provide a comprehensive compendium of B. subtilis auxotrophic genes, and identify genes required for utilizing specific carbon and nitrogen sources, as well as those required for growth at low temperature. We report the identification of enzymes catalyzing several missing steps in amino acid biosynthesis. Finally, we describe a suite of high-throughput phenotyping methodologies and apply them to provide a genome-wide analysis of competence and sporulation. Altogether, we provide versatile resources for studying gene function and pathway and network architecture in Gram-positive bacteria. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  13. Comparing SVM and ANN based Machine Learning Methods for Species Identification of Food Contaminating Beetles.

    Science.gov (United States)

    Bisgin, Halil; Bera, Tanmay; Ding, Hongjian; Semey, Howard G; Wu, Leihong; Liu, Zhichao; Barnes, Amy E; Langley, Darryl A; Pava-Ripoll, Monica; Vyas, Himansu J; Tong, Weida; Xu, Joshua

    2018-04-25

    Insect pests, such as pantry beetles, are often associated with food contaminations and public health risks. Machine learning has the potential to provide a more accurate and efficient solution in detecting their presence in food products, which is currently done manually. In our previous research, we demonstrated such feasibility where Artificial Neural Network (ANN) based pattern recognition techniques could be implemented for species identification in the context of food safety. In this study, we present a Support Vector Machine (SVM) model which improved the average accuracy up to 85%. Contrary to this, the ANN method yielded ~80% accuracy after extensive parameter optimization. Both methods showed excellent genus level identification, but SVM showed slightly better accuracy  for most species. Highly accurate species level identification remains a challenge, especially in distinguishing between species from the same genus which may require improvements in both imaging and machine learning techniques. In summary, our work does illustrate a new SVM based technique and provides a good comparison with the ANN model in our context. We believe such insights will pave better way forward for the application of machine learning towards species identification and food safety.

  14. COMPARATIVE ANALYSIS OF METHODS FOR IDENTIFICATION OF NONTUBERCULOUS MYCOBACTERIA ISOLATED FROM CLINICAL MATERIAL

    Directory of Open Access Journals (Sweden)

    A. V. Lyamin

    2017-01-01

    Full Text Available Recently there has been a significant increase in the incidence of mycobacteriosis, which is due to an increase in the proportion of immunosuppressed patients, the presence of these various comorbid conditions, as well as the improvement of diagnostic methods. Selecting the most accurate method of identification is extremely important in determining treatment strategy of patients. The aim of the study was to conduct a comparative analysis of modern methods of identification NTMB isolated from clinical specimens in 2015 in the Samara region. The work was carried out identification of 78 strains of microorganisms. Laboratory diagnosis was carried out using the DNA hybridization method and MALDI-ToF mass spectrometry. When microbial identification using MALDI-ToF mass spectrometry was isolated 16 strains (20.5% M. kansasii; 11 strains (14.1% M. avium and M. fortuitum; 9 strains (11.5% M. gordonae; strain 3 (3.8% M. peregrinum, M. szulgai, M. chimera intracellulare group, strain 2 (2.6% M. abscessus, M. septicum, M. paragordonae, M. senegalence, 1 strain (1.3% M. chelonae, M. frederiksbergense, M. monacense, M. lentiflavum. By using mass spectrometry, it was identified 15 types NTMB compared with 9 types — by DNA hybridization. Full match identification results was observed only in 45 (57.7% strains of divergent strains were found in 16 (20.5%. Most often when using the DNA hybridization method, discrepancy was detected in slow-growing cultures (9 strains with a predominance of microorganisms identified as M. gordonae. Among the representatives of fast-growing NTMB, seven investigations were identified in the identification, more often among representatives of the M. fortuitum and M. peregrinum groups. Particular attention should be paid to the identification of the M. kansasii strain by a molecular genetic method, which mass spectrometry was defined as M. bovis. Both cultures of M. tuberculosis complex, which were identified by MALDI

  15. Identification of Burkholderia spp. in the Clinical Microbiology Laboratory: Comparison of Conventional and Molecular Methods

    Science.gov (United States)

    van Pelt, Cindy; Verduin, Cees M.; Goessens, Wil H. F.; Vos, Margreet C.; Tümmler, Burkhard; Segonds, Christine; Reubsaet, Frans; Verbrugh, Henri; van Belkum, Alex

    1999-01-01

    Cystic fibrosis (CF) predisposes patients to bacterial colonization and infection of the lower airways. Several species belonging to the genus Burkholderia are potential CF-related pathogens, but microbiological identification may be complicated. This situation is not in the least due to the poorly defined taxonomic status of these bacteria, and further validation of the available diagnostic assays is required. A total of 114 geographically diverse bacterial isolates, previously identified in reference laboratories as Burkholderia cepacia (n = 51), B. gladioli (n = 14), Ralstonia pickettii (n = 6), B. multivorans (n = 2), Stenotrophomonas maltophilia (n = 3), and Pseudomonas aeruginosa (n = 11), were collected from environmental, clinical, and reference sources. In addition, 27 clinical isolates putatively identified as Burkholderia spp. were recovered from the sputum of Dutch CF patients. All isolates were used to evaluate the accuracy of two selective growth media, four systems for biochemical identification (API 20NE, Vitek GNI, Vitek NFC, and MicroScan), and three different PCR-based assays. The PCR assays amplify different parts of the ribosomal DNA operon, either alone or in combination with cleavage by various restriction enzymes (PCR-restriction fragment length polymorphism [RFLP] analysis). The best system for the biochemical identification of B. cepacia appeared to be the API 20NE test. None of the biochemical assays successfully grouped the B. gladioli strains. The PCR-RFLP method appeared to be the optimal method for accurate nucleic acid-mediated identification of the different Burkholderia spp. With this method, B. gladioli was also reliably classified in a separate group. For the laboratory diagnosis of B. cepacia, we recommend parallel cultures on blood agar medium and selective agar plates. Further identification of colonies with a Burkholderia phenotype should be performed with the API 20NE test. For final confirmation of species identities, PCR

  16. Constraining genome-scale models to represent the bow tie structure of metabolism for 13C metabolic flux analysis

    DEFF Research Database (Denmark)

    Backman, Tyler W.H.; Ando, David; Singh, Jahnavi

    2018-01-01

    for a minimum of fluxes into core metabolism to satisfy these experimental constraints. Together, these methods accelerate and automate the identification of a biologically reasonable set of core reactions for use with 13C MFA or 2S- 13C MFA, as well as provide for a substantially lower set of flux bounds......Determination of internal metabolic fluxes is crucial for fundamental and applied biology because they map how carbon and electrons flow through metabolism to enable cell function. 13C Metabolic Flux Analysis (13C MFA) and Two-Scale 13C Metabolic Flux Analysis (2S-13C MFA) are two techniques used...

  17. Comparison of biochemical and molecular methods for the identification of bacterial isolates associated with failed loggerhead sea turtle eggs.

    Science.gov (United States)

    Awong-Taylor, J; Craven, K S; Griffiths, L; Bass, C; Muscarella, M

    2008-05-01

    Comparison of biochemical vs molecular methods for identification of microbial populations associated with failed loggerhead turtle eggs. Two biochemical (API and Microgen) and one molecular methods (16s rRNA analysis) were compared in the areas of cost, identification, corroboration of data with other methods, ease of use, resources and software. The molecular method was costly and identified only 66% of the isolates tested compared with 74% for API. A 74% discrepancy in identifications occurred between API and 16s rRNA analysis. The two biochemical methods were comparable in cost, but Microgen was easier to use and yielded the lowest discrepancy among identifications (29%) when compared with both API 20 enteric (API 20E) and API 20 nonenteric (API 20NE) combined. A comparison of API 20E and API 20NE indicated an 83% discrepancy between the two methods. The Microgen identification system appears to be better suited than API or 16s rRNA analysis for identification of environmental isolates associated with failed loggerhead eggs. Most identification methods are not intended for use with environmental isolates. A comparison of identification systems would provide better options for identifying environmental bacteria for ecological studies.

  18. A genome scale RNAi screen identifies GLI1 as a novel gene regulating vorinostat sensitivity.

    Science.gov (United States)

    Falkenberg, K J; Newbold, A; Gould, C M; Luu, J; Trapani, J A; Matthews, G M; Simpson, K J; Johnstone, R W

    2016-07-01

    Vorinostat is an FDA-approved histone deacetylase inhibitor (HDACi) that has proven clinical success in some patients; however, it remains unclear why certain patients remain unresponsive to this agent and other HDACis. Constitutive STAT (signal transducer and activator of transcription) activation, overexpression of prosurvival Bcl-2 proteins and loss of HR23B have been identified as potential biomarkers of HDACi resistance; however, none have yet been used to aid the clinical utility of HDACi. Herein, we aimed to further elucidate vorinostat-resistance mechanisms through a functional genomics screen to identify novel genes that when knocked down by RNA interference (RNAi) sensitized cells to vorinostat-induced apoptosis. A synthetic lethal functional screen using a whole-genome protein-coding RNAi library was used to identify genes that when knocked down cooperated with vorinostat to induce tumor cell apoptosis in otherwise resistant cells. Through iterative screening, we identified 10 vorinostat-resistance candidate genes that sensitized specifically to vorinostat. One of these vorinostat-resistance genes was GLI1, an oncogene not previously known to regulate the activity of HDACi. Treatment of vorinostat-resistant cells with the GLI1 small-molecule inhibitor, GANT61, phenocopied the effect of GLI1 knockdown. The mechanism by which GLI1 loss of function sensitized tumor cells to vorinostat-induced apoptosis is at least in part through interactions with vorinostat to alter gene expression in a manner that favored apoptosis. Upon GLI1 knockdown and vorinostat treatment, BCL2L1 expression was repressed and overexpression of BCL2L1 inhibited GLI1-knockdown-mediated vorinostat sensitization. Taken together, we present the identification and characterization of GLI1 as a new HDACi resistance gene, providing a strong rationale for development of GLI1 inhibitors for clinical use in combination with HDACi therapy.

  19. [Comparison of methods for the identification of the most common yeasts in the clinical microbiology laboratory].

    Science.gov (United States)

    Guelfand, L; Grisolía, P; Bozzano, C; Kaufman, S

    2003-01-01

    We evaluated different methods for the routine identification of medically important yeasts. A total of 150 clinical isolates: 25 C. albicans, 25 C. tropicalis, 25 C. glabrata, 25 C. parapsilosis, 8 C. guilliermondii, 11 C. krusei and 31 Cryptococcus neoformans were tested by Yeast Biochemical Card bioMerieux Vitek (YBC), CHROMagar Candida (CHR). The addition of yeast morphology in Corn Meal agar-Tween 80 (AM) to YBC and CHR was also evaluated. The reference methods used were: API 20C, germ tube formation, AM, Christensen urea and Birdseed agar. YBC identified 135 yeasts with an overall accuracy of 90%. Sensitivity (S) and specificity (E) were: 92-98% for C. albicans and C. tropicalis; 84-99% for C. papapsilosis; 100-99% for C. glabrata; 91-100% for C. krusei; 63-98% for C. guilliermondii and 90-99% for Cryptococcus neoformans, respectively. CHR identified correctly 100% for C. albicans, 92% for C. tropicalis and 91% for C. krusei. Both methods combined with AM provided 100% S and E. We found that YBC system was appropriate for identification of yeasts isolated from human sources. CHR was effective and easy to use for identification of C. albicans, C. tropicalis and C. krusei. The routine use of AM with both methods is recommended.

  20. Identification of Hidden Failures in Process Control Systems Based on the HMG Method

    DEFF Research Database (Denmark)

    Jalashgar, Atoosa

    1998-01-01

    cause the systems to become overloaded and even unstable, if they remain hidden. The method uses a particular terminology to contribute to the identification of system properties, including goals, functions, and the capabilities. All identified knowledge about the system is then represented by using...... a tailored combination of two function-oriented methods, Multilevel Flow Modelling (MFM) and Goal Tree-Success Tree (GTST). The features of the method, called Hybrid MFM-GTST, are described and demonstrated by using an example of a process control system. (C) 1998 John Wiley & Sons, Inc....

  1. An application of multilevel flow modelling method for nuclear plant state identification

    International Nuclear Information System (INIS)

    Businaro, T.; Di Lorenzo, A.; Meo, G.B.; Rabbani, M.I.; Rubino, E.

    1986-01-01

    With the advent of advanced digital techniques it has been rendered possible, necessity of which has long since been recognised, to develop a computer based man-machine interface and hance an expert system based on knowledge based decision making for operator support in the control rooms of nuclear plants. The Multilevel Flow Modelling method developed at RISO Laboratories, Denmark, has been applied in the present experiment to model Italian PEC reactor and to verify applicability of this method in plant state identification. In MFM method functional structure of a process plant is described in terms of a set of interrelated mass and energy flow structures on different levels of physical aggregation

  2. In-core sipping method for the identification of failed fuel assemblies

    International Nuclear Information System (INIS)

    Wu Zhongwang; Zhang Yajun

    2000-01-01

    The failed fuel assembly identification system is an important safety system which ensures safe operations of reactor and immediate treatment of failed fuel rod cladding. The system uses an internationally recognized method to identify failed fuel assemblies in a reactor with fuel element cases. The in-core sipping method is customary used to identify failed fuel assemblies during refueling or after fuel rod cladding failure accidents. The test is usually performed after reactor shutdown by taking samples from each fuel element case while the cases are still in their original core positions. The sample activity is then measured to identify failed fuel assemblies. A failed fuel assembly identification system was designed for the NHR-200 based on the properties of the NHR-200 and national requirements. the design provides an internationally recognized level of safety to ensure the safety of NHR-200

  3. The review of identification and assay methods of β-blockers

    Directory of Open Access Journals (Sweden)

    Ольга Олександрівна Віслоус

    2015-10-01

    Full Text Available Every year the number of β-blockers on the pharmaceutical market is increasing, requiring systematization of their standardization methods.Aim of research. The aim of our research is to study literature data about identification and assay methods of β-blockers with different direction of action – selective (praktolol, metoprolol, atenolol, acebutolol, betaxolol, bevantolol, bisoprolol, celiprolol, esmolol, epanolol, esatenolol, nebivolol, Talinolol, non-selective (alprenolol, Oxprenololum, pindolol, propranolol, timolol, sotalol, nadolol, mepindolol, karteol, tertatolol, bopindolol, bupranolol, penbutolol, kloranolol and combined (labetalol, carvedilol.Methods. The analytical review of literature sources about β-blockers analysis by physical, chemical, and physicochemical methods.Results. After literature sources’ analyzing it was found that physical and physicochemical constants are basically used for β-blockers pharmacopoeial analysis; both physicochemical values and chemical reactions are used in forensic analysis, resulting in the article.It was founded that titration methods, mostly acid-base titration method, are used for β-blockers assay in the analysis of substances. For β-blockers detection in biological fluids and dosage forms, active pharmaceutical ingredients and metabolites mixture separation one should prefer physicochemical methods, such as gas chromatography and liquid chromatography, absorption UV-Visible spectroscopy, fluorometry, etc.Conclusion. The results have shown can be used for the further search of the identification and assay optimal methods of β-blockers both pure and mixed with other active substances and excipients

  4. Method of identification of unbranched chain reaction with cross termination of chain

    International Nuclear Information System (INIS)

    Poluehktov, V.A.; Begishev, I.R.

    1977-01-01

    Gas-phase chlorination of unsymmetrical difluoroethane initiated by gamma quanta of Co 60 has been studied. At decreased temperatures the only hydrogen is replaced by a chlorine atom. Over a wide range of ratios of the initial reagents, the reaction occurs with a chain rupture. An analysis of the kinetics of such a reaction provides a method for identification of an unbranched chain reaction with a cross-rupture of the chain

  5. Identification of Histamine H3 Receptor Ligands Using a New Crystal Structure Fragment-based Method

    DEFF Research Database (Denmark)

    Frandsen, Ida Osborn; Boesgaard, Michael W; Fidom, Kimberley

    2017-01-01

    Virtual screening offers an efficient alternative to high-throughput screening in the identification of pharmacological tools and lead compounds. Virtual screening is typically based on the matching of target structures or ligand pharmacophores to commercial or in-house compound catalogues....... The complete pharmacophore fragment library is freely available through the GPCR database, GPCRdb, allowing the successful application herein to be repeated for most of the 285 class A GPCR targets. The method could also easily be adapted to other protein families....

  6. Identification of a type of defects in CdTe crystals by the piezo spectroscopic method

    International Nuclear Information System (INIS)

    Tarbajev, M.Yi.

    1999-01-01

    The dependence of line shifts and the photoluminescence line intensity of bound exciton complexes on the direction of elastic deformation are studied for CdTe crystals at 4.2 K. On the basis of the found differences in piezo optic behavior of excitons bound to neutral donors and acceptors, the method of identification of a type of defects in CdTe crystals is proposed

  7. Application of PCR-DGGE method for identification of nematode communities in pepper growing soil

    OpenAIRE

    Nguyen, Thi Phuong; Ha, Duy Ngo; Nguyen, Huu Hung; Duong, Duc Hieu

    2017-01-01

    Soil nematodes play an important role in indication for assessing soil environments and ecosystems. Previous studies of nematode community analyses based on molecular identification have shown to be useful for assessing soil environments. Here we applied PCR-DGGE method for molecular analysis of five soil nematode communities (designed as S1 to S5) collected from four provinces in Southeastern Vietnam (Binh Duong, Ba Ria Vung Tau, Binh Phuoc and Dong Nai) based on SSU gene. By sequencing DNA ...

  8. Noncontact blood species identification method based on spatially resolved near-infrared transmission spectroscopy

    Science.gov (United States)

    Zhang, Linna; Sun, Meixiu; Wang, Zhennan; Li, Hongxiao; Li, Yingxin; Li, Gang; Lin, Ling

    2017-09-01

    The inspection and identification of whole blood are crucially significant for import-export ports and inspection and quarantine departments. In our previous research, we proved Near-Infrared diffuse transmitted spectroscopy method was potential for noninvasively identifying three blood species, including macaque, human and mouse, with samples measured in the cuvettes. However, in open sampling cases, inspectors may be endangered by virulence factors in blood samples. In this paper, we explored the noncontact measurement for classification, with blood samples measured in the vacuum blood vessels. Spatially resolved near-infrared spectroscopy was used to improve the prediction accuracy. Results showed that the prediction accuracy of the model built with nine detection points was more than 90% in identification between all five species, including chicken, goat, macaque, pig and rat, far better than the performance of the model built with single-point spectra. The results fully supported the idea that spatially resolved near-infrared spectroscopy method can improve the prediction ability, and demonstrated the feasibility of this method for noncontact blood species identification in practical applications.

  9. Mining Genome-Scale Growth Phenotype Data through Constant-Column Biclustering

    KAUST Repository

    Alzahrani, Majed A.

    2017-01-01

    for mining in growth phenotype data. Here, we propose Gracob, a novel, efficient graph-based method that casts and solves the constant-column biclustering problem as a maximal clique finding problem in a multipartite graph. We compared Gracob with a large

  10. Flux balance analysis of genome-scale metabolic model of rice ...

    Indian Academy of Sciences (India)

    2015-09-28

    Sep 28, 2015 ... biologists are also trying to understand the plant's systems level biochemistry ... metabolism to observe the effect of intracellular transporters' transport ..... [The information about this pathway and associated genes in .... 2013 A method for accounting for mainte- ... Biological control of rice diseases pp 1–11.

  11. Updated and standardized genome-scale reconstruction of Mycobacterium tuberculosis H37Rv, iEK1011, simulates flux states indicative of physiological conditions

    DEFF Research Database (Denmark)

    Kavvas, Erol S.; Seif, Yara; Yurkovich, James T.

    2018-01-01

    previous M. tuberculosis H37Rv genome-scale reconstructions. We functionally assess iEK1011 against previous models and show that the model increases correct gene essentiality predictions on two different experimental datasets by 6% (53% to 60%) and 18% (60% to 71%), respectively. We compared simulations...

  12. A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification

    Directory of Open Access Journals (Sweden)

    Wei Gao

    2016-01-01

    Full Text Available According to the regularization method in the inverse problem of load identification, a new method for determining the optimal regularization parameter is proposed. Firstly, quotient function (QF is defined by utilizing the regularization parameter as a variable based on the least squares solution of the minimization problem. Secondly, the quotient function method (QFM is proposed to select the optimal regularization parameter based on the quadratic programming theory. For employing the QFM, the characteristics of the values of QF with respect to the different regularization parameters are taken into consideration. Finally, numerical and experimental examples are utilized to validate the performance of the QFM. Furthermore, the Generalized Cross-Validation (GCV method and the L-curve method are taken as the comparison methods. The results indicate that the proposed QFM is adaptive to different measuring points, noise levels, and types of dynamic load.

  13. Improved Discovery of Molecular Interactions in Genome-Scale Data with Adaptive Model-Based Normalization

    Science.gov (United States)

    Brown, Patrick O.

    2013-01-01

    Background High throughput molecular-interaction studies using immunoprecipitations (IP) or affinity purifications are powerful and widely used in biology research. One of many important applications of this method is to identify the set of RNAs that interact with a particular RNA-binding protein (RBP). Here, the unique statistical challenge presented is to delineate a specific set of RNAs that are enriched in one sample relative to another, typically a specific IP compared to a non-specific control to model background. The choice of normalization procedure critically impacts the number of RNAs that will be identified as interacting with an RBP at a given significance threshold – yet existing normalization methods make assumptions that are often fundamentally inaccurate when applied to IP enrichment data. Methods In this paper, we present a new normalization methodology that is specifically designed for identifying enriched RNA or DNA sequences in an IP. The normalization (called adaptive or AD normalization) uses a basic model of the IP experiment and is not a variant of mean, quantile, or other methodology previously proposed. The approach is evaluated statistically and tested with simulated and empirical data. Results and Conclusions The adaptive (AD) normalization method results in a greatly increased range in the number of enriched RNAs identified, fewer false positives, and overall better concordance with independent biological evidence, for the RBPs we analyzed, compared to median normalization. The approach is also applicable to the study of pairwise RNA, DNA and protein interactions such as the analysis of transcription factors via chromatin immunoprecipitation (ChIP) or any other experiments where samples from two conditions, one of which contains an enriched subset of the other, are studied. PMID:23349766

  14. Mining Genome-Scale Growth Phenotype Data through Constant-Column Biclustering

    KAUST Repository

    Alzahrani, Majed A.

    2017-07-10

    Growth phenotype profiling of genome-wide gene-deletion strains over stress conditions can offer a clear picture that the essentiality of genes depends on environmental conditions. Systematically identifying groups of genes from such recently emerging high-throughput data that share similar patterns of conditional essentiality and dispensability under various environmental conditions can elucidate how genetic interactions of the growth phenotype are regulated in response to the environment. In this dissertation, we first demonstrate that detecting such “co-fit” gene groups can be cast as a less well-studied problem in biclustering, i.e., constant-column biclustering. Despite significant advances in biclustering techniques, very few were designed for mining in growth phenotype data. Here, we propose Gracob, a novel, efficient graph-based method that casts and solves the constant-column biclustering problem as a maximal clique finding problem in a multipartite graph. We compared Gracob with a large collection of widely used biclustering methods that cover different types of algorithms designed to detect different types of biclusters. Gracob showed superior performance on finding co-fit genes over all the existing methods on both a variety of synthetic data sets with a wide range of settings, and three real growth phenotype data sets for E. coli, proteobacteria, and yeast.

  15. High Resolution Ultrasonic Method for 3D Fingerprint Recognizable Characteristics in Biometrics Identification

    Science.gov (United States)

    Maev, R. Gr.; Bakulin, E. Yu.; Maeva, A.; Severin, F.

    Biometrics is a rapidly evolving scientific and applied discipline that studies possible ways of personal identification by means of unique biological characteristics. Such identification is important in various situations requiring restricted access to certain areas, information and personal data and for cases of medical emergencies. A number of automated biometric techniques have been developed, including fingerprint, hand shape, eye and facial recognition, thermographic imaging, etc. All these techniques differ in the recognizable parameters, usability, accuracy and cost. Among these, fingerprint recognition stands alone since a very large database of fingerprints has already been acquired. Also, fingerprints are key evidence left at a crime scene and can be used to indentify suspects. Therefore, of all automated biometric techniques, especially in the field of law enforcement, fingerprint identification seems to be the most promising. We introduce a newer development of the ultrasonic fingerprint imaging. The proposed method obtains a scan only once and then varies the C-scan gate position and width to visualize acoustic reflections from any appropriate depth inside the skin. Also, B-scans and A-scans can be recreated from any position using such data array, which gives the control over the visualization options. By setting the C-scan gate deeper inside the skin, distribution of the sweat pores (which are located along the ridges) can be easily visualized. This distribution should be unique for each individual so this provides a means of personal identification, which is not affected by any changes (accidental or intentional) of the fingers' surface conditions. This paper discusses different setups, acoustic parameters of the system, signal and image processing options and possible ways of 3-dimentional visualization that could be used as a recognizable characteristic in biometric identification.

  16. A measurement fusion method for nonlinear system identification using a cooperative learning algorithm.

    Science.gov (United States)

    Xia, Youshen; Kamel, Mohamed S

    2007-06-01

    Identification of a general nonlinear noisy system viewed as an estimation of a predictor function is studied in this article. A measurement fusion method for the predictor function estimate is proposed. In the proposed scheme, observed data are first fused by using an optimal fusion technique, and then the optimal fused data are incorporated in a nonlinear function estimator based on a robust least squares support vector machine (LS-SVM). A cooperative learning algorithm is proposed to implement the proposed measurement fusion method. Compared with related identification methods, the proposed method can minimize both the approximation error and the noise error. The performance analysis shows that the proposed optimal measurement fusion function estimate has a smaller mean square error than the LS-SVM function estimate. Moreover, the proposed cooperative learning algorithm can converge globally to the optimal measurement fusion function estimate. Finally, the proposed measurement fusion method is applied to ARMA signal and spatial temporal signal modeling. Experimental results show that the proposed measurement fusion method can provide a more accurate model.

  17. Comprehensive evaluation of SNP identification with the Restriction Enzyme-based Reduced Representation Library (RRL method

    Directory of Open Access Journals (Sweden)

    Du Ye

    2012-02-01

    Full Text Available Abstract Background Restriction Enzyme-based Reduced Representation Library (RRL method represents a relatively feasible and flexible strategy used for Single Nucleotide Polymorphism (SNP identification in different species. It has remarkable advantage of reducing the complexity of the genome by orders of magnitude. However, comprehensive evaluation for actual efficacy of SNP identification by this method is still unavailable. Results In order to evaluate the efficacy of Restriction Enzyme-based RRL method, we selected Tsp 45I enzyme which covers 266 Mb flanking region of the enzyme recognition site according to in silico simulation on human reference genome, then we sequenced YH RRL after Tsp 45I treatment and obtained reads of which 80.8% were mapped to target region with an 20-fold average coverage, about 96.8% of target region was covered by at least one read and 257 K SNPs were identified in the region using SOAPsnp software. Compared with whole genome resequencing data, we observed false discovery rate (FDR of 13.95% and false negative rate (FNR of 25.90%. The concordance rate of homozygote loci was over 99.8%, but that of heterozygote were only 92.56%. Repeat sequences and bases quality were proved to have a great effect on the accuracy of SNP calling, SNPs in recognition sites contributed evidently to the high FNR and the low concordance rate of heterozygote. Our results indicated that repeat masking and high stringent filter criteria could significantly decrease both FDR and FNR. Conclusions This study demonstrates that Restriction Enzyme-based RRL method was effective for SNP identification. The results highlight the important role of bias and the method-derived defects represented in this method and emphasize the special attentions noteworthy.

  18. Technical efficiency and economic viability of different cattle identification methods allowed by the Brazilian traceability system

    Directory of Open Access Journals (Sweden)

    Marcos Aurelio Lopes

    2017-03-01

    Full Text Available We aimed to evaluate the technical efficiency and economic viability of the implementation and use of four cattle identification methods allowed by the Brazilian traceability system. The study was conducted in a beef cattle production system located in the State of Mato Grosso, from January to June 2012. Four identification methods (treatments were compared: T1: ear tag in one ear and ear button in the other ear (eabu; T2: ear tag and iron brand on the right leg (eaib; T3: ear tag in one ear and tattoo on the other ear (eata; and T4: ear tag in one ear and electronic ear tag (eael on the other. Each treatment was applied to 60 Nelore animals, totaling 240 animals, divided equally into three life stages (calves, young cattle, adult cattle. The study had two phases: implementation (phase 1 and reading and transfer of identification numbers to an electronic database (phase 2. All operating expenses related to the two phases of the study were determined. The database was constructed, and the statistical analyses were performed using SPSS® 17.0 software. Regarding the time spent on implementation (phase 1, conventional ear tags and electronic ear tags produced similar results, which were lower than those of hot iron and tattoo methods, which differed from each other. Regarding the time required for reading the numbers on animals and their transcription into a database (phase 2, electronic ear-tagging was the fastest method, followed by conventional ear tag, hot iron and tattoo. Among the methods analyzed, the electronic ear tag had the highest technical efficiency because it required less time to implement identifiers and to complete the process of reading and transcription to an electronic database and because it did not exhibit any errors. However, the cost of using the electronic ear-tagging method was higher primarily due to the cost of the device.

  19. Method of transient identification based on a possibilistic approach, optimized by genetic algorithm

    International Nuclear Information System (INIS)

    Almeida, Jose Carlos Soares de

    2001-02-01

    This work develops a method for transient identification based on a possible approach, optimized by Genetic Algorithm to optimize the number of the centroids of the classes that represent the transients. The basic idea of the proposed method is to optimize the partition of the search space, generating subsets in the classes within a partition, defined as subclasses, whose centroids are able to distinguish the classes with the maximum correct classifications. The interpretation of the subclasses as fuzzy sets and the possible approach provided a heuristic to establish influence zones of the centroids, allowing to achieve the 'don't know' answer for unknown transients, that is, outside the training set. (author)

  20. Identification of atypical Aeromonas salmonicida : Inter-laboratory evaluation and harmonization of methods

    DEFF Research Database (Denmark)

    Dalsgaard, Inger; Gudmundsdottir, B.K.; Helgason, S.

    1998-01-01

    the biochemical identification of atypical Aer. salmonicida before and after standardization of media and methods. Five laboratories examined 25 isolates of Aer. salmonicida from diverse fish species and geographical locations including the reference strains of Aer. salmonicida subsp, salmonicida (NCMB 1102......) and Aer. salmonicida subsp. achromogenes (NCMB 1110), Without standardization of the methods, 100% agreement was obtained only for two tests: motility and ornithine decarboxylase. The main reason for the discrepancies found was the variation of the incubation time prior to reading the biochemical...

  1. Attributes identification of nuclear material by non-destructive radiation measurement methods

    International Nuclear Information System (INIS)

    Gan Lin

    2002-01-01

    Full text: The nuclear materials should be controlled under the regulation of National Safeguard System. The non-destructive analysis method, which is simple and quick, provide a effective process in determining the nuclear materials, nuclear scraps and wastes. The method play a very important role in the fields of nuclear material control and physical protection against the illegal removal and smuggling of nuclear material. The application of non-destructive analysis in attributes identification of nuclear material is briefly described in this paper. The attributes determined by radioactive detection technique are useful tolls to identify the characterization of special nuclear material (isotopic composition, enrichment etc.). (author)

  2. A New Identification Method of Both Magnetization Characteristic and Parameters of an Unloaded Transformer

    Directory of Open Access Journals (Sweden)

    Petr Orsag

    2008-01-01

    Full Text Available In this paper a new method of identification of both the magnetization characteristic and the instantaneous parameters G(t and K(t of a single-phase transformer under a sinusoidal supply voltage is proposed. The instantaneous conductance G(t and inverse inductance K(t of the transformer cross section are determined by the scalar product of time functions. The magnetization characteristic is derived by means of the inverse inductance K(t. The method is practically applied to an isolating transformer.

  3. A Comfort-Aware Energy Efficient HVAC System Based on the Subspace Identification Method

    Directory of Open Access Journals (Sweden)

    O. Tsakiridis

    2016-01-01

    Full Text Available A proactive heating method is presented aiming at reducing the energy consumption in a HVAC system while maintaining the thermal comfort of the occupants. The proposed technique fuses time predictions for the zones’ temperatures, based on a deterministic subspace identification method, and zones’ occupancy predictions, based on a mobility model, in a decision scheme that is capable of regulating the balance between the total energy consumed and the total discomfort cost. Simulation results for various occupation-mobility models demonstrate the efficiency of the proposed technique.

  4. Microbiological method for radiation sterilization (II). Identification procedure of gram positive bacteria by using BBL CRYSTAL GP identification kit

    International Nuclear Information System (INIS)

    Koshikawa, Tomihiko

    2004-01-01

    The part II in this title series describes details of the commercially available BBL CRYSTAL GP Identification Kit with the software (Becton, Dickinson and Co., Ltd.), by which identification of Gram positive bacteria as well as their number becoming easier in the radiation sterilization of medical devices. Isolation of a bacterium has to be confirmed by microscopy and its Gram positive property, by the Gram staining. The exponentially growing bacteria are to be inoculated in the Kit and cultured for 18-24 hr at 37 deg C with the lid attached by substrates for identification. Reactions to substrates are to be judged by CRYSTAL auto-reader, which is further to be searched by the computer software (code-book) for final identification. For possible misidentification, re-isolation of the bacterium, prolonged culture, concentrated inoculation and re-consideration for ranking of identification the software provides are necessary as well as other identification approaches. Representative bacteria as the bioburden are spp. of Bacilli, Corynebacteria, Staphylococci and Micrococci. (N.I.)

  5. Comparison among three methods for mycobacteria identification Comparación entre tres métodos para identificar micobacterias

    OpenAIRE

    Misael Mondragón-Barreto; Carlos A. Vázquez-Chacón; Candelaria Barrón-Rivero; Patricia Acosta-Blanco; Kenneth C. Jost Jr; Susana Balandrano; Hiram Olivera-Díaz

    2000-01-01

    OBJECTIVE: To compare three methods: Biochemical tests, high-performance liquid chromatography (HPLC) and polymerase chain reaction-restriction fragments length polymorphism (PCR-RFLP), for the identification of mycobacteria, and to perform a cost-benefit analysis to define an optimum identification algorithm. MATERIAL AND METHODS: One-hundred-and-seven mycobacteria isolates were identified by the three methods at Instituto de Diagnóstico y Referencia Epidemiológicos, between February of 1999...

  6. Using constitutive equation gap method for identification of elastic material parameters: Technical insights and illustrations

    KAUST Repository

    Florentin, Éric

    2011-08-09

    The constitutive equation gap method (CEGM) is a well-known concept which, until now, has been used mainly for the verification of finite element simulations. Recently, CEGM-based functional has been proposed to identify local elastic parameters based on experimental full-field measurement. From a technical point of view, this approach requires to quickly describe a space of statically admissible stress fields. We present here the technical insights, inspired from previous works in verification, that leads to the construction of such a space. Then, the identification strategy is implemented and the obtained results are compared with the actual material parameters for numerically generated benchmarks. The quality of the identification technique is demonstrated that makes it a valuable tool for interactive design as a way to validate local material properties. © 2011 Springer-Verlag.

  7. Identification of new biomarker of radiation exposure for establishing rapid, simplified biodosimetric method

    International Nuclear Information System (INIS)

    Iizuka, Daisuke; Kawai, Hidehiko; Kamiya, Kenji; Suzuki, Fumio; Izumi, Shunsuke

    2014-01-01

    Until now, counting chromosome aberration is the most accurate method for evaluating radiation doses. However, this method is time consuming and requires skills for evaluating chromosome aberrations. It could be difficult to apply this method to majority of people who are expected to be exposed to ionizing radiation. In this viewpoint, establishment of rapid, simplified biodosimetric methods for triage will be anticipated. Due to the development of mass spectrometry method and the identification of new molecules such as microRNA (miRNA), it is conceivable that new molecular biomarker of radiation exposure using some newly developed mass spectrometry. In this review article, the part of our results including the changes of protein (including the changes of glycosylation), peptide, metabolite, miRNA after radiation exposure will be shown. (author)

  8. Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints

    DEFF Research Database (Denmark)

    Sanchez, Benjamin J.; Zhang, Xi-Cheng; Nilsson, Avlant

    2017-01-01

    , which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance...... and turnover number. We applied GECKO to a Saccharomyces cerevisiae GEM and demonstrated that the new model could correctly describe phenotypes that the previous model could not, particularly under high enzymatic pressure conditions, such as yeast growing on different carbon sources in excess, coping...... with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between...

  9. Analysis of genetic variation and potential applications in genome-scale metabolic modeling

    DEFF Research Database (Denmark)

    Cardoso, Joao; Andersen, Mikael Rørdam; Herrgard, Markus

    2015-01-01

    scale and resolution by re-sequencing thousands of strains systematically. In this article, we review challenges in the integration and analysis of large-scale re-sequencing data, present an extensive overview of bioinformatics methods for predicting the effects of genetic variants on protein function......Genetic variation is the motor of evolution and allows organisms to overcome the environmental challenges they encounter. It can be both beneficial and harmful in the process of engineering cell factories for the production of proteins and chemicals. Throughout the history of biotechnology......, there have been efforts to exploit genetic variation in our favor to create strains with favorable phenotypes. Genetic variation can either be present in natural populations or it can be artificially created by mutagenesis and selection or adaptive laboratory evolution. On the other hand, unintended genetic...

  10. Reconstructing the Backbone of the Saccharomycotina Yeast Phylogeny Using Genome-Scale Data

    Directory of Open Access Journals (Sweden)

    Xing-Xing Shen

    2016-12-01

    Full Text Available Understanding the phylogenetic relationships among the yeasts of the subphylum Saccharomycotina is a prerequisite for understanding the evolution of their metabolisms and ecological lifestyles. In the last two decades, the use of rDNA and multilocus data sets has greatly advanced our understanding of the yeast phylogeny, but many deep relationships remain unsupported. In contrast, phylogenomic analyses have involved relatively few taxa and lineages that were often selected with limited considerations for covering the breadth of yeast biodiversity. Here we used genome sequence data from 86 publicly available yeast genomes representing nine of the 11 known major lineages and 10 nonyeast fungal outgroups to generate a 1233-gene, 96-taxon data matrix. Species phylogenies reconstructed using two different methods (concatenation and coalescence and two data matrices (amino acids or the first two codon positions yielded identical and highly supported relationships between the nine major lineages. Aside from the lineage comprised by the family Pichiaceae, all other lineages were monophyletic. Most interrelationships among yeast species were robust across the two methods and data matrices. However, eight of the 93 internodes conflicted between analyses or data sets, including the placements of: the clade defined by species that have reassigned the CUG codon to encode serine, instead of leucine; the clade defined by a whole genome duplication; and the species Ascoidea rubescens. These phylogenomic analyses provide a robust roadmap for future comparative work across the yeast subphylum in the disciplines of taxonomy, molecular genetics, evolutionary biology, ecology, and biotechnology. To further this end, we have also provided a BLAST server to query the 86 Saccharomycotina genomes, which can be found at http://y1000plus.org/blast.

  11. Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

    Science.gov (United States)

    Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

    2008-06-18

    Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson

  12. Reconstructing the Backbone of the Saccharomycotina Yeast Phylogeny Using Genome-Scale Data

    Science.gov (United States)

    Shen, Xing-Xing; Zhou, Xiaofan; Kominek, Jacek; Kurtzman, Cletus P.; Hittinger, Chris Todd; Rokas, Antonis

    2016-01-01

    Understanding the phylogenetic relationships among the yeasts of the subphylum Saccharomycotina is a prerequisite for understanding the evolution of their metabolisms and ecological lifestyles. In the last two decades, the use of rDNA and multilocus data sets has greatly advanced our understanding of the yeast phylogeny, but many deep relationships remain unsupported. In contrast, phylogenomic analyses have involved relatively few taxa and lineages that were often selected with limited considerations for covering the breadth of yeast biodiversity. Here we used genome sequence data from 86 publicly available yeast genomes representing nine of the 11 known major lineages and 10 nonyeast fungal outgroups to generate a 1233-gene, 96-taxon data matrix. Species phylogenies reconstructed using two different methods (concatenation and coalescence) and two data matrices (amino acids or the first two codon positions) yielded identical and highly supported relationships between the nine major lineages. Aside from the lineage comprised by the family Pichiaceae, all other lineages were monophyletic. Most interrelationships among yeast species were robust across the two methods and data matrices. However, eight of the 93 internodes conflicted between analyses or data sets, including the placements of: the clade defined by species that have reassigned the CUG codon to encode serine, instead of leucine; the clade defined by a whole genome duplication; and the species Ascoidea rubescens. These phylogenomic analyses provide a robust roadmap for future comparative work across the yeast subphylum in the disciplines of taxonomy, molecular genetics, evolutionary biology, ecology, and biotechnology. To further this end, we have also provided a BLAST server to query the 86 Saccharomycotina genomes, which can be found at http://y1000plus.org/blast. PMID:27672114

  13. State of charge estimation of lithium-ion batteries based on an improved parameter identification method

    International Nuclear Information System (INIS)

    Xia, Bizhong; Chen, Chaoren; Tian, Yong; Wang, Mingwang; Sun, Wei; Xu, Zhihui

    2015-01-01

    The SOC (state of charge) is the most important index of the battery management systems. However, it cannot be measured directly with sensors and must be estimated with mathematical techniques. An accurate battery model is crucial to exactly estimate the SOC. In order to improve the model accuracy, this paper presents an improved parameter identification method. Firstly, the concept of polarization depth is proposed based on the analysis of polarization characteristics of the lithium-ion batteries. Then, the nonlinear least square technique is applied to determine the model parameters according to data collected from pulsed discharge experiments. The results show that the proposed method can reduce the model error as compared with the conventional approach. Furthermore, a nonlinear observer presented in the previous work is utilized to verify the validity of the proposed parameter identification method in SOC estimation. Finally, experiments with different levels of discharge current are carried out to investigate the influence of polarization depth on SOC estimation. Experimental results show that the proposed method can improve the SOC estimation accuracy as compared with the conventional approach, especially under the conditions of large discharge current. - Highlights: • The polarization characteristics of lithium-ion batteries are analyzed. • The concept of polarization depth is proposed to improve model accuracy. • A nonlinear least square technique is applied to determine the model parameters. • A nonlinear observer is used as the SOC estimation algorithm. • The validity of the proposed method is verified by experimental results.

  14. Radioisotope identification method for poorly resolved gamma-ray spectrum of nuclear security concern

    International Nuclear Information System (INIS)

    Ninh, Giang Nguyen; Phongphaeth, Pengvanich; Nares, Chankow; Hao, Quang Nguyen

    2016-01-01

    Gamma-ray signal can be used as a fingerprint for radioisotope identification. In the context of radioactive and nuclear materials security at the border control point, the detection task can present a significant challenge due to various constraints such as the limited measurement time, the shielding conditions, and the noise interference. This study proposes a novel method to identify the signal of one or several radioisotopes from a poorly resolved gamma-ray spectrum. In this method, the noise component in the raw spectrum is reduced by the wavelet decomposition approach, and the removal of the continuum background is performed using the baseline determination algorithm. Finally, the identification of radioisotope is completed using the matrix linear regression method. The proposed method has been verified by experiments using the poorly resolved gamma-ray signals from various scenarios including single source, mixing of natural uranium with five of the most common industrial radioactive sources (57Co, 60Co, 133Ba, 137Cs, and 241Am). The preliminary results show that the proposed algorithm is comparable with the commercial method

  15. Radioisotope identification method for poorly resolved gamma-ray spectrum of nuclear security concern

    Energy Technology Data Exchange (ETDEWEB)

    Ninh, Giang Nguyen; Phongphaeth, Pengvanich, E-mail: phongphaeth.p@chula.ac.th; Nares, Chankow [Nuclear Engineering Department, Faculty of Engineering, Chulalongkorn University, 254 Phayathai Road, Pathumwan, Bangkok 10330 (Thailand); Hao, Quang Nguyen [Vietnam Atomic Energy Institute, Ministry of Science and Technology, Hanoi (Viet Nam)

    2016-01-22

    Gamma-ray signal can be used as a fingerprint for radioisotope identification. In the context of radioactive and nuclear materials security at the border control point, the detection task can present a significant challenge due to various constraints such as the limited measurement time, the shielding conditions, and the noise interference. This study proposes a novel method to identify the signal of one or several radioisotopes from a poorly resolved gamma-ray spectrum. In this method, the noise component in the raw spectrum is reduced by the wavelet decomposition approach, and the removal of the continuum background is performed using the baseline determination algorithm. Finally, the identification of radioisotope is completed using the matrix linear regression method. The proposed method has been verified by experiments using the poorly resolved gamma-ray signals from various scenarios including single source, mixing of natural uranium with five of the most common industrial radioactive sources (57Co, 60Co, 133Ba, 137Cs, and 241Am). The preliminary results show that the proposed algorithm is comparable with the commercial method.

  16. A Simple and Effective Isocratic HPLC Method for Fast Identification and Quantification of Surfactin

    International Nuclear Information System (INIS)

    Muhammad Qadri Effendy Mubarak; Abdul Rahman Hassan; Aidil Abdul Hamid; Sahaid Khalil; Mohd Hafez Mohd Isa

    2015-01-01

    The aim of this study was to establish a simple, accurate and reproducible method for the identification and quantification of surfactin using high-performance liquid chromatography (HPLC). Previously reported method of identification and quantification of surfactin were time consuming and requires a large quantity of mobile phase. The new method was achieved by application of Chromolith® high performance RP-18 (100 x 4.6 mm, 5 μm) as the stationary phase and optimization of mobile phase ratio and flow rate. Mobile phase consisted of acetonitrile (ACN) and 3.8 mM trifluroacetic acid (TFA) solution of 80:20 ratio at flow rate of 2.2 mL/ min was obtained as the optimal conditions. Total elution time of the obtained surfactin peaks was four times quicker than various methods previously reported in the literature. The method described here allowed for fine separation of surfactin in standard sample (98 % purity) and surfactin in fermentation broth. (author)

  17. Impulse response identification with deterministic inputs using non-parametric methods

    International Nuclear Information System (INIS)

    Bhargava, U.K.; Kashyap, R.L.; Goodman, D.M.

    1985-01-01

    This paper addresses the problem of impulse response identification using non-parametric methods. Although the techniques developed herein apply to the truncated, untruncated, and the circulant models, we focus on the truncated model which is useful in certain applications. Two methods of impulse response identification will be presented. The first is based on the minimization of the C/sub L/ Statistic, which is an estimate of the mean-square prediction error; the second is a Bayesian approach. For both of these methods, we consider the effects of using both the identity matrix and the Laplacian matrix as weights on the energy in the impulse response. In addition, we present a method for estimating the effective length of the impulse response. Estimating the length is particularly important in the truncated case. Finally, we develop a method for estimating the noise variance at the output. Often, prior information on the noise variance is not available, and a good estimate is crucial to the success of estimating the impulse response with a nonparametric technique

  18. Health condition identification of multi-stage planetary gearboxes using a mRVM-based method

    Science.gov (United States)

    Lei, Yaguo; Liu, Zongyao; Wu, Xionghui; Li, Naipeng; Chen, Wu; Lin, Jing

    2015-08-01

    Multi-stage planetary gearboxes are widely applied in aerospace, automotive and heavy industries. Their key components, such as gears and bearings, can easily suffer from damage due to tough working environment. Health condition identification of planetary gearboxes aims to prevent accidents and save costs. This paper proposes a method based on multiclass relevance vector machine (mRVM) to identify health condition of multi-stage planetary gearboxes. In this method, a mRVM algorithm is adopted as a classifier, and two features, i.e. accumulative amplitudes of carrier orders (AACO) and energy ratio based on difference spectra (ERDS), are used as the input of the classifier to classify different health conditions of multi-stage planetary gearboxes. To test the proposed method, seven health conditions of a two-stage planetary gearbox are considered and vibration data is acquired from the planetary gearbox under different motor speeds and loading conditions. The results of three tests based on different data show that the proposed method obtains an improved identification performance and robustness compared with the existing method.

  19. The place of molecular methods in the identification of dermatophytes and the determination of their feasibility

    Directory of Open Access Journals (Sweden)

    Fatma Bıyık

    2013-03-01

    Full Text Available Background and Design: Unlike opportunistic fungi, dermatophytes cannot be isolated on the conventional culture media in a few days. Their growing periods cover approximately two weeks in a suitable media and identification are made with conventional methods as typical macroscopic and microscopic appearance. However, successful results are not always obtained with the phenotypic features, and thus, diagnostic problems and delay in diagnosis and treatment may arise. For this reason, the methods based on nucleic acid amplification have been necessary. In this study, we aimed to identify 56 dermatophytes strains, which were identified by conventional methods, by molecular methods and to investigate the correlation between the two methods and to determine the usability of molecular methods in routine laboratories. Materials and Methods: Several clinical samples of 270 patients with suspected dermatophytoses (hair+scalp, skin and nail scrapings were examined by conventional methods; Sabouraud dextrose agar, corn meal agar and potato dextrose agar were used for isolation. In case of necessity to hydrolyze urea, to be used different vitamins in Trichophyton agar media were investigated. Polymerase chain reaction (PCR and sequence analyses were done for the molecular diagnosis. Results: Using conventional methods, 37 strains (66,1% were identified as Trichophyton(T rubrum, four (7.1% - T.mentagrophytes, four (7.1% - T.tonsurans, one (1.8% - T.violaceum, eight (14.3% - Trichophyton spp., one (1.8% - Microsporum(M canis, and one (1.8% - Microsporum spp. According to the molecular and sequence analyses results (T1PCR, 25GAPCR, ITSPCR-RFLP and sequence analyses, 41 (73.8% strains were identified as T.rubrum, 10 (17.8% - T.interdigitale, one (1.8% - T. violaceum, two (3.6% - M. canis, one (1.8% - Peacilomyces lilacinus, and one (1,8% - Aspergillus fumigatus. Discussion: This study suggests that, molecular methods offer fast and reliable results in

  20. HyDe: a Python Package for Genome-Scale Hybridization Detection.

    Science.gov (United States)

    Blischak, Paul D; Chifman, Julia; Wolfe, Andrea D; Kubatko, Laura S

    2018-03-19

    The analysis of hybridization and gene flow among closely related taxa is a common goal for researchers studying speciation and phylogeography. Many methods for hybridization detection use simple site pattern frequencies from observed genomic data and compare them to null models that predict an absence of gene flow. The theory underlying the detection of hybridization using these site pattern probabilities exploits the relationship between the coalescent process for gene trees within population trees and the process of mutation along the branches of the gene trees. For certain models, site patterns are predicted to occur in equal frequency (i.e., their difference is 0), producing a set of functions called phylogenetic invariants. In this paper we introduce HyDe, a software package for detecting hybridization using phylogenetic invariants arising under the coalescent model with hybridization. HyDe is written in Python, and can be used interactively or through the command line using pre-packaged scripts. We demonstrate the use of HyDe on simulated data, as well as on two empirical data sets from the literature. We focus in particular on identifying individual hybrids within population samples and on distinguishing between hybrid speciation and gene flow. HyDe is freely available as an open source Python package under the GNU GPL v3 on both GitHub (https://github.com/pblischak/HyDe) and the Python Package Index (PyPI: https://pypi.python.org/pypi/phyde).

  1. Linear time algorithms to construct populations fitting multiple constraint distributions at genomic scales.

    Science.gov (United States)

    Siragusa, Enrico; Haiminen, Niina; Utro, Filippo; Parida, Laxmi

    2017-10-09

    Computer simulations can be used to study population genetic methods, models and parameters, as well as to predict potential outcomes. For example, in plant populations, predicting the outcome of breeding operations can be studied using simulations. In-silico construction of populations with pre-specified characteristics is an important task in breeding optimization and other population genetic studies. We present two linear time Simulation using Best-fit Algorithms (SimBA) for two classes of problems where each co-fits two distributions: SimBA-LD fits linkage disequilibrium and minimum allele frequency distributions, while SimBA-hap fits founder-haplotype and polyploid allele dosage distributions. An incremental gap-filling version of previously introduced SimBA-LD is here demonstrated to accurately fit the target distributions, allowing efficient large scale simulations. SimBA-hap accuracy and efficiency is demonstrated by simulating tetraploid populations with varying numbers of founder haplotypes, we evaluate both a linear time greedy algoritm and an optimal solution based on mixed-integer programming. SimBA is available on http://researcher.watson.ibm.com/project/5669.

  2. A genome-scale RNA-interference screen identifies RRAS signaling as a pathologic feature of Huntington's disease.

    Directory of Open Access Journals (Sweden)

    John P Miller

    Full Text Available A genome-scale RNAi screen was performed in a mammalian cell-based assay to identify modifiers of mutant huntingtin toxicity. Ontology analysis of suppressor data identified processes previously implicated in Huntington's disease, including proteolysis, glutamate excitotoxicity, and mitochondrial dysfunction. In addition to established mechanisms, the screen identified multiple components of the RRAS signaling pathway as loss-of-function suppressors of mutant huntingtin toxicity in human and mouse cell models. Loss-of-function in orthologous RRAS pathway members also suppressed motor dysfunction in a Drosophila model of Huntington's disease. Abnormal activation of RRAS and a down-stream effector, RAF1, was observed in cellular models and a mouse model of Huntington's disease. We also observe co-localization of RRAS and mutant huntingtin in cells and in mouse striatum, suggesting that activation of R-Ras may occur through protein interaction. These data indicate that mutant huntingtin exerts a pathogenic effect on this pathway that can be corrected at multiple intervention points including RRAS, FNTA/B, PIN1, and PLK1. Consistent with these results, chemical inhibition of farnesyltransferase can also suppress mutant huntingtin toxicity. These data suggest that pharmacological inhibition of RRAS signaling may confer therapeutic benefit in Huntington's disease.

  3. An improved EMD method for modal identification and a combined static-dynamic method for damage detection

    Science.gov (United States)

    Yang, Jinping; Li, Peizhen; Yang, Youfa; Xu, Dian

    2018-04-01

    Empirical mode decomposition (EMD) is a highly adaptable signal processing method. However, the EMD approach has certain drawbacks, including distortions from end effects and mode mixing. In the present study, these two problems are addressed using an end extension method based on the support vector regression machine (SVRM) and a modal decomposition method based on the characteristics of the Hilbert transform. The algorithm includes two steps: using the SVRM, the time series data are extended at both endpoints to reduce the end effects, and then, a modified EMD method using the characteristics of the Hilbert transform is performed on the resulting signal to reduce mode mixing. A new combined static-dynamic method for identifying structural damage is presented. This method combines the static and dynamic information in an equilibrium equation that can be solved using the Moore-Penrose generalized matrix inverse. The combination method uses the differences in displacements of the structure with and without damage and variations in the modal force vector. Tests on a four-story, steel-frame structure were conducted to obtain static and dynamic responses of the structure. The modal parameters are identified using data from the dynamic tests and improved EMD method. The new method is shown to be more accurate and effective than the traditional EMD method. Through tests with a shear-type test frame, the higher performance of the proposed static-dynamic damage detection approach, which can detect both single and multiple damage locations and the degree of the damage, is demonstrated. For structures with multiple damage, the combined approach is more effective than either the static or dynamic method. The proposed EMD method and static-dynamic damage detection method offer improved modal identification and damage detection, respectively, in structures.

  4. Genome-scale prediction of proteins with long intrinsically disordered regions.

    Science.gov (United States)

    Peng, Zhenling; Mizianty, Marcin J; Kurgan, Lukasz

    2014-01-01

    Proteins with long disordered regions (LDRs), defined as having 30 or more consecutive disordered residues, are abundant in eukaryotes, and these regions are recognized as a distinct class of biologically functional domains. LDRs facilitate various cellular functions and are important for target selection in structural genomics. Motivated by the lack of methods that directly predict proteins with LDRs, we designed Super-fast predictor of proteins with Long Intrinsically DisordERed regions (SLIDER). SLIDER utilizes logistic regression that takes an empirically chosen set of numerical features, which consider selected physicochemical properties of amino acids, sequence complexity, and amino acid composition, as its inputs. Empirical tests show that SLIDER offers competitive predictive performance combined with low computational cost. It outperforms, by at least a modest margin, a comprehensive set of modern disorder predictors (that can indirectly predict LDRs) and is 16 times faster compared to the best currently available disorder predictor. Utilizing our time-efficient predictor, we characterized abundance and functional roles of proteins with LDRs over 110 eukaryotic proteomes. Similar to related studies, we found that eukaryotes have many (on average 30.3%) proteins with LDRs with majority of proteomes having between 25 and 40%, where higher abundance is characteristic to proteomes that have larger proteins. Our first-of-its-kind large-scale functional analysis shows that these proteins are enriched in a number of cellular functions and processes including certain binding events, regulation of catalytic activities, cellular component organization, biogenesis, biological regulation, and some metabolic and developmental processes. A webserver that implements SLIDER is available at http://biomine.ece.ualberta.ca/SLIDER/. Copyright © 2013 Wiley Periodicals, Inc.

  5. Identification of Yeast Species In the Oral Cavity of Iranian Soldiers By Disk Diffusion Method

    Directory of Open Access Journals (Sweden)

    M. Imami

    2008-02-01

    Full Text Available Background:The disk diffusion method for identification of yeasts species was performed based on different but distinct susceptibilities of yeasts spp.to chemicals:janus green, ethidium bromide,2,3,5-triphenyltetrazolium chloride, brilliant green, cycloheximide and rhodamine 6G. Methods: Atotal of 568 Iranian soldiers went under study for isolation and identification of Yeast species from their oral cavity. Asterile swab was used for each individual and specimens were collected from the nasopharynx region, then inoculated to petri dishes containing Sabouraud Dextrose Agar and incubated for 48 hrs at 37 °C. All colonies were counted and stocked in distilled water and stored in a refrigerator for further analysis. The yeasts were identified by the “disk diffusion test” [6,8]. This is a simple, rapid, accurate, and inexpensive technique presented by Sobczak [8]. By this method we identified yeast species within 24-48 hrs. Results: 51.4% of petri dishes were positive for yeast species and 318 strains were identified. Candida albicans, Candida kefyr, Candida tropicalis and Candida guilliermondii were the most common yeast species isolated from the oral cavity of soldiers. Conclusion: We used this method because of its simplicity and other beneficial characteristics for rapid identification of large and numerous isolates and the results were compared with other morphological characters such as chlamydospore and germ tube production. In addition,we used some type strains (Candida parapsilosis: PTCC 5089,Candida tropicalis: PTCC 5028,Saccharomyces cerevisiae:PTCC 5052,Candida lipolytica: PTCC 5063,Candida lipolytica:PTCC 5064,and the results were acceptable.

  6. A Maximum Power Transfer Tracking Method for WPT Systems with Coupling Coefficient Identification Considering Two-Value Problem

    Directory of Open Access Journals (Sweden)

    Xin Dai

    2017-10-01

    Full Text Available Maximum power transfer tracking (MPTT is meant to track the maximum power point during the system operation of wireless power transfer (WPT systems. Traditionally, MPTT is achieved by impedance matching at the secondary side when the load resistance is varied. However, due to a loosely coupling characteristic, the variation of coupling coefficient will certainly affect the performance of impedance matching, therefore MPTT will fail accordingly. This paper presents an identification method of coupling coefficient for MPTT in WPT systems. Especially, the two-value issue during the identification is considered. The identification approach is easy to implement because it does not require additional circuit. Furthermore, MPTT is easy to realize because only two easily measured DC parameters are needed. The detailed identification procedure corresponding to the two-value issue and the maximum power transfer tracking process are presented, and both the simulation analysis and experimental results verified the identification method and MPTT.

  7. Comparing culture and molecular methods for the identification of microorganisms involved in necrotizing soft tissue infections

    DEFF Research Database (Denmark)

    Rudkjøbing, Vibeke Børsholt; Thomsen, Trine Rolighed; Xu, Yijuan

    2016-01-01

    BACKGROUND: Necrotizing soft tissue infections (NSTIs) are a group of infections affecting all soft tissues. NSTI involves necrosis of the afflicted tissue and is potentially life threatening due to major and rapid destruction of tissue, which often leads to septic shock and organ failure. The gold...... to culture. Although the molecular methods generally gave concordant results, our results indicate that Microseq may misidentify or overlook microorganisms that can be detected by other molecular methods. Half of the patients were found to be infected with S. pyogenes, but several atypical findings were also...... that clinicians should be prepared to diagnose and treat any combination of microbial pathogens. Some of the tested molecular methods offer a faster turnaround time combined with a high specificity, which makes supplemental use of such methods attractive for identification of microorganisms, especially...

  8. Extraction and identification of cyclobutanones from irradiated cheese employing a rapid direct solvent extraction method.

    Science.gov (United States)

    Tewfik, Ihab

    2008-01-01

    2-Alkylcyclobutanones (cyclobutanones) are accepted as chemical markers for irradiated foods containing lipid. However, current extraction procedures (Soxhlet-florisil chromatography) for the isolation of these markers involve a long and tedious clean-up regime prior to gas chromatography-mass spectrophotometry identification. This paper outlines an alternative isolation and clean-up method for the extraction of cyclobutanones in irradiated Camembert cheese. The newly developed direct solvent extraction method enables the efficient screening of large numbers of food samples and is not as resource intensive as the BS EN 1785:1997 method. Direct solvent extraction appears to be a simple, robust method and has the added advantage of a considerably shorter extraction time for the analysis of foods containing lipid.

  9. A Novel Coupled State/Input/Parameter Identification Method for Linear Structural Systems

    Directory of Open Access Journals (Sweden)

    Zhimin Wan

    2018-01-01

    Full Text Available In many engineering applications, unknown states, inputs, and parameters exist in the structures. However, most methods require one or two of these variables to be known in order to identify the other(s. Recently, the authors have proposed a method called EGDF for coupled state/input/parameter identification for nonlinear system in state space. However, the EGDF method based solely on acceleration measurements is found to be unstable, which can cause the drift of the identified inputs and displacements. Although some regularization methods can be adopted for solving the problem, they are not suitable for joint input-state identification in real time. In this paper, a strategy of data fusion of displacement and acceleration measurements is used to avoid the low-frequency drift in the identified inputs and structural displacements for linear structural systems. Two numerical examples about a plane truss and a single-stage isolation system are conducted to verify the effectiveness of the proposed modified EGDF algorithm.

  10. Strategy for identification & characterization of Bartonella henselae with conventional & molecular methods

    Directory of Open Access Journals (Sweden)

    Kavita Diddi

    2013-01-01

    Full Text Available Background & objectives: Bartonella henselae is a fastidious gram-negative bacterium usually causing self limiting infections in immunocompetent individuals but often causes potentially life threatening infection, such as bacillary angiomatosis in immunocompromised patients. Both diagnosis of infections and research into molecular mechanisms of pathogenesis have been hindered by lack of appropriate and reliable diagnostic techniques. We undertook this study to standardize methods to characterize B. henselae in clinical samples to diagnose Bartonella infection correctly. Methods: B. henselae ATCC 49882 strain was procured from American type culture collection, USA. This strain was revived and maintained in the laboratory, and identification and characterization of this strain was done by conventional and molecular techniques, which included culture on various media, staining by different methods including electron microscopy, biochemical analysis by conventional methods and API, polymerase chain reaction (PCR for amplification of citrate synthase gene followed by restriction fragment length polymorphism (RFLP. Results: This organism was biochemically inert due to slow growth and generated unique identification code with API. The amplification of the citrate-synthase gene with primers yielded a 381 bp product followed by specific RFLP profile for B. henselae. Interpretation & conclusions: Bartonella is fastidious and fragile organism and should be handled carefully. Extra effort and careful observation are required to isolate and characterize this organism.

  11. Methods of the Detection and Identification of Structural Defects in Saturated Metallic Composite Castings

    Directory of Open Access Journals (Sweden)

    Gawdzińska K.

    2017-09-01

    Full Text Available Diagnostics of composite castings, due to their complex structure, requires that their characteristics are tested by an appropriate description method. Any deviation from the specific characteristic will be regarded as a material defect. The detection of defects in composite castings sometimes is not sufficient and the defects have to be identified. This study classifies defects found in the structures of saturated metallic composite castings and indicates those stages of the process where such defects are likely to be formed. Not only does the author determine the causes of structural defects, describe methods of their detection and identification, but also proposes a schematic procedure to be followed during detection and identification of structural defects of castings made from saturated reinforcement metallic composites. Alloys examination was conducted after technological process, while using destructive (macroscopic tests, light and scanning electron microscopy and non-destructive (ultrasonic and X-ray defectoscopy, tomography, gravimetric method methods. Research presented in this article are part of author’s work on castings quality.

  12. On the efficiency of high-energy particle identification statistical methods

    International Nuclear Information System (INIS)

    Chilingaryan, A.A.

    1982-01-01

    An attempt is made to analyze the statistical methods of making decisions on the high-energy particle identification. The Bayesian approach is shown to provide the most complete account of the primary discriminative information between the particles of various tupes. It does not impose rigid requirements on the density form of the probability function and ensures the account of the a priori information as compared with the Neyman-Pearson approach, the mimimax technique and the heristic rules of the decision limits construction in the variant region of the specially chosen parameter. The methods based on the concept of the nearest neighbourhood are shown to be the most effective one among the local methods of the probability function density estimation. The probability distances between the training sample classes are suggested to make a decision on selecting the high-energy particle detector optimal parameters. The method proposed and the software constructed are tested on the problem of the cosmic radiation hadron identification by means of transition radiation detectors (the ''PION'' experiment)

  13. A Development of Common Cause Failure Propagation Paths Identification Method Using Coloured Petri Nets

    International Nuclear Information System (INIS)

    Yim, Ho Bin; Park, Jae Min; Lee, Chang Gyun; Huh, Jae Young; Lee, Gyu Cheon

    2017-01-01

    The concept of Common-Cause Failure (CCF) first appeared in the aerospace industry several decades ago, and nuclear power industry actively adopted the concept to the nuclear power plant (NPP) system analysis after the TMI accident. Since digital Instrumentation and Control (I and C) systems were applied to the NPP design, the CCF issues once again drew attention from the nuclear power industry in 90's. Identification of CCF has not been considered as a challenging issue because of its simplicity. However, as the systems become more complex and interconnected, demands are increasing to analyze CCF in more detail, for example, CCF with multiple initiating events or supporting situation awareness of the operation crew. The newly suggested CCF propagation paths identification method, CCF-SIREn, is expected to resolve path identification issue more practically and efficiently. CCF-SIREn uses general diagrams so that the compatibility and usability can be hugely increased. It also offers up-to-date CCF information with a least analysis effort whenever the ordinary NPP design change processes are made. A back-propagation technique is still under development to find out root-causes from the suspiciously responding signals, alarms and components. The probabilistic approach is also under consideration to prioritize defined CCF.

  14. [Identification of Candida dubliniensis strains using heat tolerance tests, morphological characteristics and molecular methods].

    Science.gov (United States)

    Arikan, Sevtap; Darka, Ozge; Hasçelik, Gülşen; Günalp, Ayfer

    2003-01-01

    Described in 1995, Candida dubliniensis is a novel Candida species closely related to Candida albicans due primarily to its ability to produce germ tube and chlamydospores. Given these phenotypic similarities between the two species, C. dubliniensis cannot be readily distinguished from Candida albicans by routine laboratory work-up. We explored the frequency of isolation of C. dubliniensis among 213 strains previously defined as C. albicans based on their ability to produce germ tube. The test isolates were initially examined for their morphological features on cornmeal tween 80 agar, inability to grow at 45 degrees C, and the biochemical assimilation profile (ID 32C system, bioMerieux, France). Among all, 2 (0.9%) of the isolates were identified as C. dubliniensis based on the production of numerous chlamydospores in chains on cornmeal tween 80 agar and the lack of growth at 45 degrees C. The assimilation profile of these isolates was found to be in accordance with this identification. In an effort to confirm the identification, polymerase chain reaction (PCR) studies were carried out by using the C. dubliniensis specific primer set, DUBF and DUBR. Both of the isolates yielded C. dubliniensis-specific 288 base pair amplification products, confirming the previous identification obtained with the initial screening tests. The isolates were found to be susceptible to fluconazole and itraconazole, and generated amphotericin B minimal inhibitory concentrations of 0.5-1 microgram/ml by NCCLS M27-A2 microdilution method. These data suggest that the isolation rate of C. dubliniensis among our clinical isolates is low. The morphological features on cornmeal tween 80 agar and the lack of ability to grow at 45 degrees C appear as reliable, cheap, and practical screening tests in initial identification of C. dubliniensis among germ tube-producing Candida strains.

  15. Power System Oscillation Modes Identifications: Guidelines for Applying TLS-ESPRIT Method

    Science.gov (United States)

    Gajjar, Gopal R.; Soman, Shreevardhan

    2013-05-01

    Fast measurements of power system quantities available through wide-area measurement systems enables direct observations for power system electromechanical oscillations. But the raw observations data need to be processed to obtain the quantitative measures required to make any inference regarding the power system state. A detailed discussion is presented for the theory behind the general problem of oscillatory mode indentification. This paper presents some results on oscillation mode identification applied to a wide-area frequency measurements system. Guidelines for selection of parametes for obtaining most reliable results from the applied method are provided. Finally, some results on real measurements are presented with our inference on them.

  16. Investigation of the stochastic subspace identification method for on-line wind turbine tower monitoring

    Science.gov (United States)

    Dai, Kaoshan; Wang, Ying; Lu, Wensheng; Ren, Xiaosong; Huang, Zhenhua

    2017-04-01

    Structural health monitoring (SHM) of wind turbines has been applied in the wind energy industry to obtain their real-time vibration parameters and to ensure their optimum performance. For SHM, the accuracy of its results and the efficiency of its measurement methodology and data processing algorithm are the two major concerns. Selection of proper measurement parameters could improve such accuracy and efficiency. The Stochastic Subspace Identification (SSI) is a widely used data processing algorithm for SHM. This research discussed the accuracy and efficiency of SHM using SSI method to identify vibration parameters of on-line wind turbine towers. Proper measurement parameters, such as optimum measurement duration, are recommended.

  17. A touch probe method of operating an implantable RFID tag for orthopedic implant identification.

    Science.gov (United States)

    Liu, Xiaoyu; Berger, J Lee; Ogirala, Ajay; Mickle, Marlin H

    2013-06-01

    The major problem in operating an implantable radio-frequency identification (RFID) tag embedded on an orthopedic implant is low efficiency because of metallic interference. To improve the efficiency, this paper proposes a method of operating an implantable passive RFID tag using a touch probe at 13.56 MHz. This technology relies on the electric field interaction between two pairs of electrodes, one being a part of the touch probe placed on the surface of tissue and the other being a part of the tag installed under the tissue. Compared with using a conventional RFID antenna such as a loop antenna, this method has a better performance in the near field operation range to reduce interference with the orthopedic implant. Properly matching the touch probe and the tag to the tissue and the implant reduces signal attenuation and increases the overall system efficiency. The experiments have shown that this method has a great performance in the near field transcutaneous operation and can be used for orthopedic implant identification.

  18. Comparison of two inductive learning methods: A case study in failed fuel identification

    International Nuclear Information System (INIS)

    Reifman, J.; Lee, J.C.

    1992-01-01

    Two inductive learning methods, the ID3 and Rg algorithms, are studied as a means for systematically and automatically constructing the knowledge base of expert systems. Both inductive learning methods are general-purpose and use information entropy as a discriminatory measure in order to group objects of a common class. ID3 constructs a knowledge base by building decision trees that discriminate objects of a data set as a function of their class. Rg constructs a knowledge base by grouping objects of the same class into patterns or clusters. The two inductive methods are applied to the construction of a knowledge base for failed fuel identification in the Experimental Breeder Reactor II. Through analysis of the knowledge bases generated, the ID3 and Rg algorithms are compared for their knowledge representation, data overfitting, feature space partition, feature selection, and search procedure

  19. Blind system identification of two-thermocouple sensor based on cross-relation method

    Science.gov (United States)

    Li, Yanfeng; Zhang, Zhijie; Hao, Xiaojian

    2018-03-01

    In dynamic temperature measurement, the dynamic characteristics of the sensor affect the accuracy of the measurement results. Thermocouples are widely used for temperature measurement in harsh conditions due to their low cost, robustness, and reliability, but because of the presence of the thermal inertia, there is a dynamic error in the dynamic temperature measurement. In order to eliminate the dynamic error, two-thermocouple sensor was used to measure dynamic gas temperature in constant velocity flow environments in this paper. Blind system identification of two-thermocouple sensor based on a cross-relation method was carried out. Particle swarm optimization algorithm was used to estimate time constants of two thermocouples and compared with the grid based search method. The method was validated on the experimental equipment built by using high temperature furnace, and the input dynamic temperature was reconstructed by using the output data of the thermocouple with small time constant.

  20. Comparison of two inductive learning methods: A case study in failed fuel identification

    Energy Technology Data Exchange (ETDEWEB)

    Reifman, J. [Argonne National Lab., IL (United States); Lee, J.C. [Michigan Univ., Ann Arbor, MI (United States). Dept. of Nuclear Engineering

    1992-05-01

    Two inductive learning methods, the ID3 and Rg algorithms, are studied as a means for systematically and automatically constructing the knowledge base of expert systems. Both inductive learning methods are general-purpose and use information entropy as a discriminatory measure in order to group objects of a common class. ID3 constructs a knowledge base by building decision trees that discriminate objects of a data set as a function of their class. Rg constructs a knowledge base by grouping objects of the same class into patterns or clusters. The two inductive methods are applied to the construction of a knowledge base for failed fuel identification in the Experimental Breeder Reactor II. Through analysis of the knowledge bases generated, the ID3 and Rg algorithms are compared for their knowledge representation, data overfitting, feature space partition, feature selection, and search procedure.

  1. Comparison of two inductive learning methods: A case study in failed fuel identification

    Energy Technology Data Exchange (ETDEWEB)

    Reifman, J. (Argonne National Lab., IL (United States)); Lee, J.C. (Michigan Univ., Ann Arbor, MI (United States). Dept. of Nuclear Engineering)

    1992-01-01

    Two inductive learning methods, the ID3 and Rg algorithms, are studied as a means for systematically and automatically constructing the knowledge base of expert systems. Both inductive learning methods are general-purpose and use information entropy as a discriminatory measure in order to group objects of a common class. ID3 constructs a knowledge base by building decision trees that discriminate objects of a data set as a function of their class. Rg constructs a knowledge base by grouping objects of the same class into patterns or clusters. The two inductive methods are applied to the construction of a knowledge base for failed fuel identification in the Experimental Breeder Reactor II. Through analysis of the knowledge bases generated, the ID3 and Rg algorithms are compared for their knowledge representation, data overfitting, feature space partition, feature selection, and search procedure.

  2. The methodics of the identification of π-p elastic interactions in bubble chamber

    International Nuclear Information System (INIS)

    Balea, E.; Berceanu, S.; Coca, C.; Sararu, A.; Mihul, A.L.M.; Balea, O.; Karnauhov, V.M.; Moroz, V.I.

    1979-01-01

    A method for elastic events separation from the two prong-events in a hydrogen bubble chamber exposed to π - meson-beams is presented. It is argued that for elastic events the simultaneous cuts in the angle of coplanarity and the angular kinematical correlation are less sensitive to the experimental errors than in other kinematical correlations. The proposed methodics is compared with other current technics for elastic events identification. Our method for elastic events separation has been tested on a sample of two prong-events from the CERN 2m H 2 bubble chamber exposed to a beam of 16 GeV/c π - mesons. The processing of elastic events candidates is presented too. (author)

  3. Identification of some Fusarium species from selected crop seeds using traditional method and BIO-PCR

    Directory of Open Access Journals (Sweden)

    Tomasz Kulik

    2012-12-01

    Full Text Available We identified a species level of the fungal cultures isolated from selected crop seeds using traditional method and BIO-PCR. The use of BIO-PCR did not correspond completely to the morphological analyses. Both methods showed increased infection with F. poae in winter wheat seed sample originated from north Poland. Fungal culture No 40 (isolated from faba bean and identified with traditional method as mixed culture with F. culmorum and F. graminearum did not produce expected product after PCR reaction with species specific primers OPT18F470, OPT18R470. However, the use of additional primers Fc01F, Fc01R allowed for reliable identification of F. culmorum in the culture.

  4. Identification method of non-reflective faults based on index distribution of optical fibers.

    Science.gov (United States)

    Lee, Wonkyoung; Myong, Seung Il; Lee, Jyung Chan; Lee, Sangsoo

    2014-01-13

    This paper investigates an identification method of non-reflective faults based on index distribution of optical fibers. The method identifies not only reflective faults but also non-reflective faults caused by tilted fiber-cut, lateral connector-misalignment, fiber-bend, and temperature variation. We analyze the reason why wavelength dependence of the fiber-bend is opposite to that of the lateral connector-misalignment, and the effect of loss due to temperature variation on OTDR waveforms through simulation and experimental results. This method can be realized by only upgrade of fault-analysis software without the hardware change, it is, therefore, competitive and cost-effective in passive optical networks.

  5. Developing a Clustering-Based Empirical Bayes Analysis Method for Hotspot Identification

    Directory of Open Access Journals (Sweden)

    Yajie Zou

    2017-01-01

    Full Text Available Hotspot identification (HSID is a critical part of network-wide safety evaluations. Typical methods for ranking sites are often rooted in using the Empirical Bayes (EB method to estimate safety from both observed crash records and predicted crash frequency based on similar sites. The performance of the EB method is highly related to the selection of a reference group of sites (i.e., roadway segments or intersections similar to the target site from which safety performance functions (SPF used to predict crash frequency will be developed. As crash data often contain underlying heterogeneity that, in essence, can make them appear to be generated from distinct subpopulations, methods are needed to select similar sites in a principled manner. To overcome this possible heterogeneity problem, EB-based HSID methods that use common clustering methodologies (e.g., mixture models, K-means, and hierarchical clustering to select “similar” sites for building SPFs are developed. Performance of the clustering-based EB methods is then compared using real crash data. Here, HSID results, when computed on Texas undivided rural highway cash data, suggest that all three clustering-based EB analysis methods are preferred over the conventional statistical methods. Thus, properly classifying the road segments for heterogeneous crash data can further improve HSID accuracy.

  6. Comparative analyses reveal discrepancies among results of commonly used methods for Anopheles gambiaemolecular form identification

    Directory of Open Access Journals (Sweden)

    Pinto João

    2011-08-01

    Full Text Available Abstract Background Anopheles gambiae M and S molecular forms, the major malaria vectors in the Afro-tropical region, are ongoing a process of ecological diversification and adaptive lineage splitting, which is affecting malaria transmission and vector control strategies in West Africa. These two incipient species are defined on the basis of single nucleotide differences in the IGS and ITS regions of multicopy rDNA located on the X-chromosome. A number of PCR and PCR-RFLP approaches based on form-specific SNPs in the IGS region are used for M and S identification. Moreover, a PCR-method to detect the M-specific insertion of a short interspersed transposable element (SINE200 has recently been introduced as an alternative identification approach. However, a large-scale comparative analysis of four widely used PCR or PCR-RFLP genotyping methods for M and S identification was never carried out to evaluate whether they could be used interchangeably, as commonly assumed. Results The genotyping of more than 400 A. gambiae specimens from nine African countries, and the sequencing of the IGS-amplicon of 115 of them, highlighted discrepancies among results obtained by the different approaches due to different kinds of biases, which may result in an overestimation of MS putative hybrids, as follows: i incorrect match of M and S specific primers used in the allele specific-PCR approach; ii presence of polymorphisms in the recognition sequence of restriction enzymes used in the PCR-RFLP approaches; iii incomplete cleavage during the restriction reactions; iv presence of different copy numbers of M and S-specific IGS-arrays in single individuals in areas of secondary contact between the two forms. Conclusions The results reveal that the PCR and PCR-RFLP approaches most commonly utilized to identify A. gambiae M and S forms are not fully interchangeable as usually assumed, and highlight limits of the actual definition of the two molecular forms, which might

  7. A lithology identification method for continental shale oil reservoir based on BP neural network

    Science.gov (United States)

    Han, Luo; Fuqiang, Lai; Zheng, Dong; Weixu, Xia

    2018-06-01

    The Dongying Depression and Jiyang Depression of the Bohai Bay Basin consist of continental sedimentary facies with a variable sedimentary environment and the shale layer system has a variety of lithologies and strong heterogeneity. It is difficult to accurately identify the lithologies with traditional lithology identification methods. The back propagation (BP) neural network was used to predict the lithology of continental shale oil reservoirs. Based on the rock slice identification, x-ray diffraction bulk rock mineral analysis, scanning electron microscope analysis, and the data of well logging and logging, the lithology was divided with carbonate, clay and felsic as end-member minerals. According to the core-electrical relationship, the frequency histogram was then used to calculate the logging response range of each lithology. The lithology-sensitive curves selected from 23 logging curves (GR, AC, CNL, DEN, etc) were chosen as the input variables. Finally, the BP neural network training model was established to predict the lithology. The lithology in the study area can be divided into four types: mudstone, lime mudstone, lime oil-mudstone, and lime argillaceous oil-shale. The logging responses of lithology were complicated and characterized by the low values of four indicators and medium values of two indicators. By comparing the number of hidden nodes and the number of training times, we found that the number of 15 hidden nodes and 1000 times of training yielded the best training results. The optimal neural network training model was established based on the above results. The lithology prediction results of BP neural network of well XX-1 showed that the accuracy rate was over 80%, indicating that the method was suitable for lithology identification of continental shale stratigraphy. The study provided the basis for the reservoir quality and oily evaluation of continental shale reservoirs and was of great significance to shale oil and gas exploration.

  8. Method of Increasing Identification Accuracy under Experimental Tests of Dynamic Objects

    Directory of Open Access Journals (Sweden)

    Y. N. Pavlov

    2015-01-01

    Full Text Available The work concerns a problem of increasing identification accuracy of linear dynamic systems on the basis of experimental data obtained by applying test signals to the system.The work is aimed at considering a possibility to use the experimentally obtained hodograph counting to determine parameters of this system in a specific context of the linear dynamic system of the second order.An offer was to use a method of harmonious linearization and a described cut method.The type of frequency transfer function of the identified system was assumed as known.It was supposed that when obtaining the frequency characteristics of a real system there are disturbances interfering with experiment as a result of which points of experimentally received hodograph are random displaced.An identification problem solution was searched in a class of the hodograph set by the system model, which had the same type of frequency transfer function, as the type of frequency transfer function of the identified system.The unknown coefficients of frequency transfer function of the system model were searched through minimizing a proximity criterion (measure of the experimentally received hodograph of the system and of the system model hodograph over the entire aggregate of points. One of the authors described this criterion in the earlier publication.The solution to a problem of nonlinear dynamic system identification by the frequency hodograph was reduced to the solution of the system of equations of the rather unknown linear parameters of frequency transfer function of the system model.The program to simulate a process of the pseudo-experimental data, containing random errors, and determine parameters of this system is developed for a dynamic system of the second order.A conducted computing experiment is conducted to estimate an error at which the offered algorithm defines the values of parameters of this system.

  9. From the patient to the clinical mycology laboratory: how can we optimise microscopy and culture methods for mould identification?

    Science.gov (United States)

    Vyzantiadis, Timoleon-Achilleas A; Johnson, Elizabeth M; Kibbler, Christopher C

    2012-06-01

    The identification of fungi relies mainly on morphological criteria. However, there is a need for robust and definitive phenotypic identification procedures in order to evaluate continuously evolving molecular methods. For the future, there is an emerging consensus that a combined (phenotypic and molecular) approach is more powerful for fungal identification, especially for moulds. Most of the procedures used for phenotypic identification are based on experience rather than comparative studies of effectiveness or performance and there is a need for standardisation among mycology laboratories. This review summarises and evaluates the evidence for the major existing phenotypic identification procedures for the predominant causes of opportunistic mould infection. We have concentrated mainly on Aspergillus, Fusarium and mucoraceous mould species, as these are the most important clinically and the ones for which there are the most molecular taxonomic data.

  10. Rapid identification of ascomycetous yeasts from clinical specimens by a molecular method based on flow cytometry and comparison with identifications from phenotypic assays.

    Science.gov (United States)

    Page, Brent T; Shields, Christine E; Merz, William G; Kurtzman, Cletus P

    2006-09-01

    This study was designed to compare the identification of ascomycetous yeasts recovered from clinical specimens by using phenotypic assays (PA) and a molecular flow cytometric (FC) method. Large-subunit rRNA domains 1 and 2 (D1/D2) gene sequence analysis was also performed and served as the reference for correct strain identification. A panel of 88 clinical isolates was tested that included representatives of nine commonly encountered species and six infrequently encountered species. The PA included germ tube production, fermentation of seven carbohydrates, morphology on corn meal agar, urease and phenoloxidase activities, and carbohydrate assimilation tests when needed. The FC method (Luminex) employed species-specific oligonucleotides attached to polystyrene beads, which were hybridized with D1/D2 amplicons from the unidentified isolates. The PA identified 81 of 88 strains correctly but misidentified 4 of Candida dubliniensis, 1 of C. bovina, 1 of C. palmioleophila, and 1 of C. bracarensis. The FC method correctly identified 79 of 88 strains and did not misidentify any isolate but did not identify nine isolates because oligonucleotide probes were not available in the current library. The FC assay takes approximately 5 h, whereas the PA takes from 2 h to 5 days for identification. In conclusion, PA did well with the commonly encountered species, was not accurate for uncommon species, and takes significantly longer than the FC method. These data strongly support the potential of FC technology for rapid and accurate identification of medically important yeasts. With the introduction of new antifungals, rapid, accurate identification of pathogenic yeasts is more important than ever for guiding antifungal chemotherapy.

  11. Identification of a Multicriteria Decision-Making Model Using the Characteristic Objects Method

    Directory of Open Access Journals (Sweden)

    Andrzej Piegat

    2014-01-01

    Full Text Available This paper presents a new, nonlinear, multicriteria, decision-making method: the characteristic objects (COMET. This approach, which can be characterized as a fuzzy reference model, determines a measurement standard for decision-making problems. This model is distinguished by a constant set of specially chosen characteristic objects that are independent of the alternatives. After identifying a multicriteria model, this method can be used to compare any number of decisional objects (alternatives and select the best one. In the COMET, in contrast to other methods, the rank-reversal phenomenon is not observed. Rank-reversal is a paradoxical feature in the decision-making methods, which is caused by determining the absolute evaluations of considered alternatives on the basis of the alternatives themselves. In the Analytic Hierarchy Process (AHP method and similar methods, when a new alternative is added to the original alternative set, the evaluation base and the resulting evaluations of all objects change. A great advantage of the COMET is its ability to identify not only linear but also nonlinear multicriteria models of decision makers. This identification is based not on a ranking of component criteria of the multicriterion but on a ranking of a larger set of characteristic objects (characteristic alternatives that are independent of the small set of alternatives analyzed in a given problem. As a result, the COMET is free of the faults of other methods.

  12. A Rapid Identification Method for Calamine Using Near-Infrared Spectroscopy Based on Multi-Reference Correlation Coefficient Method and Back Propagation Artificial Neural Network.

    Science.gov (United States)

    Sun, Yangbo; Chen, Long; Huang, Bisheng; Chen, Keli

    2017-07-01

    As a mineral, the traditional Chinese medicine calamine has a similar shape to many other minerals. Investigations of commercially available calamine samples have shown that there are many fake and inferior calamine goods sold on the market. The conventional identification method for calamine is complicated, therefore as a result of the large scale of calamine samples, a rapid identification method is needed. To establish a qualitative model using near-infrared (NIR) spectroscopy for rapid identification of various calamine samples, large quantities of calamine samples including crude products, counterfeits and processed products were collected and correctly identified using the physicochemical and powder X-ray diffraction method. The NIR spectroscopy method was used to analyze these samples by combining the multi-reference correlation coefficient (MRCC) method and the error back propagation artificial neural network algorithm (BP-ANN), so as to realize the qualitative identification of calamine samples. The accuracy rate of the model based on NIR and MRCC methods was 85%; in addition, the model, which took comprehensive multiple factors into consideration, can be used to identify crude calamine products, its counterfeits and processed products. Furthermore, by in-putting the correlation coefficients of multiple references as the spectral feature data of samples into BP-ANN, a BP-ANN model of qualitative identification was established, of which the accuracy rate was increased to 95%. The MRCC method can be used as a NIR-based method in the process of BP-ANN modeling.

  13. Automated method for identification and artery-venous classification of vessel trees in retinal vessel networks.

    Science.gov (United States)

    Joshi, Vinayak S; Reinhardt, Joseph M; Garvin, Mona K; Abramoff, Michael D

    2014-01-01

    The separation of the retinal vessel network into distinct arterial and venous vessel trees is of high interest. We propose an automated method for identification and separation of retinal vessel trees in a retinal color image by converting a vessel segmentation image into a vessel segment map and identifying the individual vessel trees by graph search. Orientation, width, and intensity of each vessel segment are utilized to find the optimal graph of vessel segments. The separated vessel trees are labeled as primary vessel or branches. We utilize the separated vessel trees for arterial-venous (AV) classification, based on the color properties of the vessels in each tree graph. We applied our approach to a dataset of 50 fundus images from 50 subjects. The proposed method resulted in an accuracy of 91.44% correctly classified vessel pixels as either artery or vein. The accuracy of correctly classified major vessel segments was 96.42%.

  14. A New Method of Reliability Evaluation Based on Wavelet Information Entropy for Equipment Condition Identification

    International Nuclear Information System (INIS)

    He, Z J; Zhang, X L; Chen, X F

    2012-01-01

    Aiming at reliability evaluation of condition identification of mechanical equipment, it is necessary to analyze condition monitoring information. A new method of reliability evaluation based on wavelet information entropy extracted from vibration signals of mechanical equipment is proposed. The method is quite different from traditional reliability evaluation models that are dependent on probability statistics analysis of large number sample data. The vibration signals of mechanical equipment were analyzed by means of second generation wavelet package (SGWP). We take relative energy in each frequency band of decomposed signal that equals a percentage of the whole signal energy as probability. Normalized information entropy (IE) is obtained based on the relative energy to describe uncertainty of a system instead of probability. The reliability degree is transformed by the normalized wavelet information entropy. A successful application has been achieved to evaluate the assembled quality reliability for a kind of dismountable disk-drum aero-engine. The reliability degree indicates the assembled quality satisfactorily.

  15. A simple identification method for spore-forming bacteria showing high resistance against γ-rays

    International Nuclear Information System (INIS)

    Koshikawa, Tomihiko; Sone, Koji; Kobayashi, Toshikazu

    1993-01-01

    A simple identification method was developed for spore-forming bacteria which are highly resistant against γ-rays. Among 23 species of Bacillus studied, the spores of Bacillus megaterium, B. cereus, B. thuringiensis, B. pumilus and B. aneurinolyticus showed high resistance against γ-rays as compared with other spores of Bacillus species. Combination of the seven kinds of biochemical tests, namely, the citrate utilization test, nitrate reduction test, starch hydrolysis test, Voges-Proskauer reaction test, gelatine hydrolysis test, mannitol utilization test and xylose utilization test showed a characteristic pattern for each species of Bacillus. The combination pattern of each the above tests with a few supplementary test, if necessary, was useful to identify Bacillus species showing high radiation resistance against γ-rays. The method is specific for B. megaterium, B. thuringiensis and B. pumilus, and highly selective for B. aneurinolyticus and B. cereus. (author)

  16. A Semismooth Newton Method for Nonlinear Parameter Identification Problems with Impulsive Noise

    KAUST Repository

    Clason, Christian

    2012-01-01

    This work is concerned with nonlinear parameter identification in partial differential equations subject to impulsive noise. To cope with the non-Gaussian nature of the noise, we consider a model with L 1 fitting. However, the nonsmoothness of the problem makes its efficient numerical solution challenging. By approximating this problem using a family of smoothed functionals, a semismooth Newton method becomes applicable. In particular, its superlinear convergence is proved under a second-order condition. The convergence of the solution to the approximating problem as the smoothing parameter goes to zero is shown. A strategy for adaptively selecting the regularization parameter based on a balancing principle is suggested. The efficiency of the method is illustrated on several benchmark inverse problems of recovering coefficients in elliptic differential equations, for which one- and two-dimensional numerical examples are presented. © by SIAM.

  17. Use of an uncertainty analysis for genome-scale models as a prediction tool for microbial growth processes in subsurface environments.

    Science.gov (United States)

    Klier, Christine

    2012-03-06

    The integration of genome-scale, constraint-based models of microbial cell function into simulations of contaminant transport and fate in complex groundwater systems is a promising approach to help characterize the metabolic activities of microorganisms in natural environments. In constraint-based modeling, the specific uptake flux rates of external metabolites are usually determined by Michaelis-Menten kinetic theory. However, extensive data sets based on experimentally measured values are not always available. In this study, a genome-scale model of Pseudomonas putida was used to study the key issue of uncertainty arising from the parametrization of the influx of two growth-limiting substrates: oxygen and toluene. The results showed that simulated growth rates are highly sensitive to substrate affinity constants and that uncertainties in specific substrate uptake rates have a significant influence on the variability of simulated microbial growth. Michaelis-Menten kinetic theory does not, therefore, seem to be appropriate for descriptions of substrate uptake processes in the genome-scale model of P. putida. Microbial growth rates of P. putida in subsurface environments can only be accurately predicted if the processes of complex substrate transport and microbial uptake regulation are sufficiently understood in natural environments and if data-driven uptake flux constraints can be applied.

  18. Identification of Village Building via Google Earth Images and Supervised Machine Learning Methods

    Directory of Open Access Journals (Sweden)

    Zhiling Guo

    2016-03-01

    Full Text Available In this study, a method based on supervised machine learning is proposed to identify village buildings from open high-resolution remote sensing images. We select Google Earth (GE RGB images to perform the classification in order to examine its suitability for village mapping, and investigate the feasibility of using machine learning methods to provide automatic classification in such fields. By analyzing the characteristics of GE images, we design different features on the basis of two kinds of supervised machine learning methods for classification: adaptive boosting (AdaBoost and convolutional neural networks (CNN. To recognize village buildings via their color and texture information, the RGB color features and a large number of Haar-like features in a local window are utilized in the AdaBoost method; with multilayer trained networks based on gradient descent algorithms and back propagation, CNN perform the identification by mining deeper information from buildings and their neighborhood. Experimental results from the testing area at Savannakhet province in Laos show that our proposed AdaBoost method achieves an overall accuracy of 96.22% and the CNN method is also competitive with an overall accuracy of 96.30%.

  19. Development of objective flow regime identification method using self-organizing neural network

    International Nuclear Information System (INIS)

    Lee, Jae Young; Kim, Nam Seok; Kwak, Nam Yee

    2004-01-01

    Two-phase flow shows various flow patterns according to the amount of the void and its relative velocity to the liquid flow. This variation directly affect the interfacial transfer which is the key factor for the design or analysis of the phase change systems. Especially the safety analysis of the nuclear power plant has been performed based on the numerical code furnished with the proper constitutive relations depending highly upon the flow regimes. Heavy efforts have been focused to identify the flow regime and at this moment we stand on relative very stable engineering background compare to the other research field. However, the issues related to objectiveness and transient flow regime are still open to study. Lee et al. and Ishii developed the method for the objective and instantaneous flow regime identification based on the neural network and new index of probability distribution of the flow regime which allows just one second observation for the flow regime identification. In the present paper, we developed the self-organized neural network for more objective approach to this problem. Kohonen's Self-Organizing Map (SOM) has been used for clustering, visualization, and abstraction. The SOM is trained through unsupervised competitive learning using a 'winner takes it all' policy. Therefore, its unsupervised training character delete the possible interference of the regime developer to the neural network training. After developing the computer code, we evaluate the performance of the code with the vertically upward two-phase flow in the pipes of 25.4 and 50.4 cmm I.D. Also, the sensitivity of the number of the clusters to the flow regime identification was made

  20. A NOVEL WRAPPING CURVELET TRANSFORMATION BASED ANGULAR TEXTURE PATTERN (WCTATP EXTRACTION METHOD FOR WEED IDENTIFICATION

    Directory of Open Access Journals (Sweden)

    D. Ashok Kumar

    2016-02-01

    Full Text Available Apparently weed is a major menace in crop production as it competes with crop for nutrients, moisture, space and light which resulting in poor growth and development of the crop and finally yield. Yield loss accounts for even more than 70% when crops are frown under unweeded condition with severe weed infestation. Weed management is the most significant process in the agricultural applications to improve the crop productivity rate and reduce the herbicide application cost. Existing weed detection techniques does not yield better performance due to the complex background, illumination variation and crop and weed overlapping in the agricultural field image. Hence, there arises a need for the development of effective weed identification technique. To overcome this drawback, this paper proposes a novel Wrapping Curvelet Transformation Based Angular Texture Pattern Extraction Method (WCTATP for weed identification. In our proposed work, Global Histogram Equalization (GHE is used improve the quality of the image and Adaptive Median Filter (AMF is used for filtering the impulse noise from the image. Plant image identification is performed using green pixel extraction and k-means clustering. Wrapping Curvelet transform is applied to the plant image. Feature extraction is performed to extract the angular texture pattern of the plant image. Particle Swarm Optimization (PSO based Differential Evolution Feature Selection (DEFS approach is applied to select the optimal features. Then, the selected features are learned and passed through an RVM based classifier to find out the weed. Edge detection and contouring is performed to identify the weed in the plant image. The Fuzzy rule-based approach is applied to detect the low, medium and high levels of the weed patchiness. From the experimental results, it is clearly observed that the accuracy of the proposed approach is higher than the existing Support Vector Machine (SVM based approaches. The proposed approach

  1. An improved wavelet-Galerkin method for dynamic response reconstruction and parameter identification of shear-type frames

    Science.gov (United States)

    Bu, Haifeng; Wang, Dansheng; Zhou, Pin; Zhu, Hongping

    2018-04-01

    An improved wavelet-Galerkin (IWG) method based on the Daubechies wavelet is proposed for reconstructing the dynamic responses of shear structures. The proposed method flexibly manages wavelet resolution level according to excitation, thereby avoiding the weakness of the wavelet-Galerkin multiresolution analysis (WGMA) method in terms of resolution and the requirement of external excitation. IWG is implemented by this work in certain case studies, involving single- and n-degree-of-freedom frame structures subjected to a determined discrete excitation. Results demonstrate that IWG performs better than WGMA in terms of accuracy and computation efficiency. Furthermore, a new method for parameter identification based on IWG and an optimization algorithm are also developed for shear frame structures, and a simultaneous identification of structural parameters and excitation is implemented. Numerical results demonstrate that the proposed identification method is effective for shear frame structures.

  2. Dynamic Friction Parameter Identification Method with LuGre Model for Direct-Drive Rotary Torque Motor

    Directory of Open Access Journals (Sweden)

    Xingjian Wang

    2016-01-01

    Full Text Available Attainment of high-performance motion/velocity control objectives for the Direct-Drive Rotary (DDR torque motor should fully consider practical nonlinearities in controller design, such as dynamic friction. The LuGre model has been widely utilized to describe nonlinear friction behavior; however, parameter identification for the LuGre model remains a challenge. A new dynamic friction parameter identification method for LuGre model is proposed in this study. Static parameters are identified through a series of constant velocity experiments, while dynamic parameters are obtained through a presliding process. Novel evolutionary algorithm (NEA is utilized to increase identification accuracy. Experimental results gathered from the identification experiments conducted in the study for a practical DDR torque motor control system validate the effectiveness of the proposed method.

  3. Identification of the parameters of an elastic material model using the constitutive equation gap method

    KAUST Repository

    Florentin, É ric; Lubineau, Gilles

    2010-01-01

    study resides in the application of these recent developments to the identification problem. The proposed CEGM is described in detail, then evaluated through the identification of heterogeneous isotropic elastic properties. The results obtained

  4. A Molecular Method for the Identification of Honey Bee Subspecies Used by Beekeepers in Russia

    Science.gov (United States)

    Syromyatnikov, Mikhail Y.; Borodachev, Anatoly V.; Kokina, Anastasia V.; Popov, Vasily N.

    2018-01-01

    Apis mellifera L. includes several recognized subspecies that differ in their biological properties and agricultural characteristics. Distinguishing between honey bee subspecies is complicated. We analyzed the Folmer region of the COX1 gene in honey bee subspecies cultivated at bee farms in Russia and identified subspecies-specific SNPs. DNA analysis revealed two clearly distinct haplogroups in A. mellifera mellifera. The first one was characterized by multiple cytosine-thymine (thymine–cytosine) transitions, one adenine-guanine substitution, and one thymine–adenine substitution. The nucleotide sequence of the second haplogroup coincided with sequences from other subspecies, except the unique C/A SNP at position 421 of the 658-bp Folmer region. A. mellifera carnica and A. mellifera carpatica could be distinguished from A. mellifera mellifera and A. mellifera caucasica by the presence of the A/G SNP at position 99 of the 658-bp Folmer region. The G/A SNP at position 448 was typical for A. mellifera carnica. A. mellifera caucasica COX1 sequence lacked all the above-mentioned sites. We developed a procedure for rapid identification of honey bee subspecies by PCR with restriction fragment length polymorphism (RFLP) using mutagenic primers. The developed molecular method for honey bee subspecies identification is fast and inexpensive. PMID:29382048

  5. Model Optimization Identification Method Based on Closed-loop Operation Data and Process Characteristics Parameters

    Directory of Open Access Journals (Sweden)

    Zhiqiang GENG

    2014-01-01

    Full Text Available Output noise is strongly related to input in closed-loop control system, which makes model identification of closed-loop difficult, even unidentified in practice. The forward channel model is chosen to isolate disturbance from the output noise to input, and identified by optimization the dynamic characteristics of the process based on closed-loop operation data. The characteristics parameters of the process, such as dead time and time constant, are calculated and estimated based on the PI/PID controller parameters and closed-loop process input/output data. And those characteristics parameters are adopted to define the search space of the optimization identification algorithm. PSO-SQP optimization algorithm is applied to integrate the global search ability of PSO with the local search ability of SQP to identify the model parameters of forward channel. The validity of proposed method has been verified by the simulation. The practicability is checked with the PI/PID controller parameter turning based on identified forward channel model.

  6. Development of Database Assisted Structure Identification (DASI Methods for Nontargeted Metabolomics

    Directory of Open Access Journals (Sweden)

    Lochana C. Menikarachchi

    2016-05-01

    Full Text Available Metabolite structure identification remains a significant challenge in nontargeted metabolomics research. One commonly used strategy relies on searching biochemical databases using exact mass. However, this approach fails when the database does not contain the unknown metabolite (i.e., for unknown-unknowns. For these cases, constrained structure generation with combinatorial structure generators provides a potential option. Here we evaluated structure generation constraints based on the specification of: (1 substructures required (i.e., seed structures; (2 substructures not allowed; and (3 filters to remove incorrect structures. Our approach (database assisted structure identification, DASI used predictive models in MolFind to find candidate structures with chemical and physical properties similar to the unknown. These candidates were then used for seed structure generation using eight different structure generation algorithms. One algorithm was able to generate correct seed structures for 21/39 test compounds. Eleven of these seed structures were large enough to constrain the combinatorial structure generator to fewer than 100,000 structures. In 35/39 cases, at least one algorithm was able to generate a correct seed structure. The DASI method has several limitations and will require further experimental validation and optimization. At present, it seems most useful for identifying the structure of unknown-unknowns with molecular weights <200 Da.

  7. A novel method for identification and quantification of consistently differentially methylated regions.

    Directory of Open Access Journals (Sweden)

    Ching-Lin Hsiao

    Full Text Available Advances in biotechnology have resulted in large-scale studies of DNA methylation. A differentially methylated region (DMR is a genomic region with multiple adjacent CpG sites that exhibit different methylation statuses among multiple samples. Many so-called "supervised" methods have been established to identify DMRs between two or more comparison groups. Methods for the identification of DMRs without reference to phenotypic information are, however, less well studied. An alternative "unsupervised" approach was proposed, in which DMRs in studied samples were identified with consideration of nature dependence structure of methylation measurements between neighboring probes from tiling arrays. Through simulation study, we investigated effects of dependencies between neighboring probes on determining DMRs where a lot of spurious signals would be produced if the methylation data were analyzed independently of the probe. In contrast, our newly proposed method could successfully correct for this effect with a well-controlled false positive rate and a comparable sensitivity. By applying to two real datasets, we demonstrated that our method could provide a global picture of methylation variation in studied samples. R source codes to implement the proposed method were freely available at http://www.csjfann.ibms.sinica.edu.tw/eag/programlist/ICDMR/ICDMR.html.

  8. Identification of influential spreaders in online social networks using interaction weighted K-core decomposition method

    Science.gov (United States)

    Al-garadi, Mohammed Ali; Varathan, Kasturi Dewi; Ravana, Sri Devi

    2017-02-01

    Online social networks (OSNs) have become a vital part of everyday living. OSNs provide researchers and scientists with unique prospects to comprehend individuals on a scale and to analyze human behavioral patterns. Influential spreaders identification is an important subject in understanding the dynamics of information diffusion in OSNs. Targeting these influential spreaders is significant in planning the techniques for accelerating the propagation of information that is useful for various applications, such as viral marketing applications or blocking the diffusion of annoying information (spreading of viruses, rumors, online negative behaviors, and cyberbullying). Existing K-core decomposition methods consider links equally when calculating the influential spreaders for unweighted networks. Alternatively, the proposed link weights are based only on the degree of nodes. Thus, if a node is linked to high-degree nodes, then this node will receive high weight and is treated as an important node. Conversely, the degree of nodes in OSN context does not always provide accurate influence of users. In the present study, we improve the K-core method for OSNs by proposing a novel link-weighting method based on the interaction among users. The proposed method is based on the observation that the interaction of users is a significant factor in quantifying the spreading capability of user in OSNs. The tracking of diffusion links in the real spreading dynamics of information verifies the effectiveness of our proposed method for identifying influential spreaders in OSNs as compared with degree centrality, PageRank, and original K-core.

  9. PINP: a new method of tagging neuronal populations for identification during in vivo electrophysiological recording.

    Directory of Open Access Journals (Sweden)

    Susana Q Lima

    Full Text Available Neural circuits are exquisitely organized, consisting of many different neuronal subpopulations. However, it is difficult to assess the functional roles of these subpopulations using conventional extracellular recording techniques because these techniques do not easily distinguish spikes from different neuronal populations. To overcome this limitation, we have developed PINP (Photostimulation-assisted Identification of Neuronal Populations, a method of tagging neuronal populations for identification during in vivo electrophysiological recording. The method is based on expressing the light-activated channel channelrhodopsin-2 (ChR2 to restricted neuronal subpopulations. ChR2-tagged neurons can be detected electrophysiologically in vivo since illumination of these neurons with a brief flash of blue light triggers a short latency reliable action potential. We demonstrate the feasibility of this technique by expressing ChR2 in distinct populations of cortical neurons using two different strategies. First, we labeled a subpopulation of cortical neurons-mainly fast-spiking interneurons-by using adeno-associated virus (AAV to deliver ChR2 in a transgenic mouse line in which the expression of Cre recombinase was driven by the parvalbumin promoter. Second, we labeled subpopulations of excitatory neurons in the rat auditory cortex with ChR2 based on projection target by using herpes simplex virus 1 (HSV1, which is efficiently taken up by axons and transported retrogradely; we find that this latter population responds to acoustic stimulation differently from unlabeled neurons. Tagging neurons is a novel application of ChR2, used in this case to monitor activity instead of manipulating it. PINP can be readily extended to other populations of genetically identifiable neurons, and will provide a useful method for probing the functional role of different neuronal populations in vivo.

  10. Genome-scale reconstruction and in silico analysis of the Ralstonia eutropha H16 for polyhydroxyalkanoate synthesis, lithoautotrophic growth, and 2-methyl citric acid production

    Directory of Open Access Journals (Sweden)

    Kim Tae

    2011-06-01

    Full Text Available Abstract Background Ralstonia eutropha H16, found in both soil and water, is a Gram-negative lithoautotrophic bacterium that can utillize CO2 and H2 as its sources of carbon and energy in the absence of organic substrates. R. eutropha H16 can reach high cell densities either under lithoautotrophic or heterotrophic conditions, which makes it suitable for a number of biotechnological applications. It is the best known and most promising producer of polyhydroxyalkanoates (PHAs from various carbon substrates and is an environmentally important bacterium that can degrade aromatic compounds. In order to make R. eutropha H16 a more efficient and robust biofactory, system-wide metabolic engineering to improve its metabolic performance is essential. Thus, it is necessary to analyze its metabolic characteristics systematically and optimize the entire metabolic network at systems level. Results We present the lithoautotrophic genome-scale metabolic model of R. eutropha H16 based on the annotated genome with biochemical and physiological information. The stoichiometic model, RehMBEL1391, is composed of 1391 reactions including 229 transport reactions and 1171 metabolites. Constraints-based flux analyses were performed to refine and validate the genome-scale metabolic model under environmental and genetic perturbations. First, the lithoautotrophic growth characteristics of R. eutropha H16 were investigated under varying feeding ratios of gas mixture. Second, the genome-scale metabolic model was used to design the strategies for the production of poly[R-(--3hydroxybutyrate] (PHB under different pH values and carbon/nitrogen source uptake ratios. It was also used to analyze the metabolic characteristics of R. eutropha when the phosphofructokinase gene was expressed. Finally, in silico gene knockout simulations were performed to identify targets for metabolic engineering essential for the production of 2-methylcitric acid in R. eutropha H16. Conclusion The

  11. Understanding the Representative Gut Microbiota Dysbiosis in Metformin-Treated Type 2 Diabetes Patients Using Genome-Scale Metabolic Modeling

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    Dorines Rosario

    2018-06-01

    Full Text Available Dysbiosis in the gut microbiome composition may be promoted by therapeutic drugs such as metformin, the world’s most prescribed antidiabetic drug. Under metformin treatment, disturbances of the intestinal microbes lead to increased abundance of Escherichia spp., Akkermansia muciniphila, Subdoligranulum variabile and decreased abundance of Intestinibacter bartlettii. This alteration may potentially lead to adverse effects on the host metabolism, with the depletion of butyrate producer genus. However, an increased production of butyrate and propionate was verified in metformin-treated Type 2 diabetes (T2D patients. The mechanisms underlying these nutritional alterations and their relation with gut microbiota dysbiosis remain unclear. Here, we used Genome-scale Metabolic Models of the representative gut bacteria Escherichia spp., I. bartlettii, A. muciniphila, and S. variabile to elucidate their bacterial metabolism and its effect on intestinal nutrient pool, including macronutrients (e.g., amino acids and short chain fatty acids, minerals and chemical elements (e.g., iron and oxygen. We applied flux balance analysis (FBA coupled with synthetic lethality analysis interactions to identify combinations of reactions and extracellular nutrients whose absence prevents growth. Our analyses suggest that Escherichia sp. is the bacteria least vulnerable to nutrient availability. We have also examined bacterial contribution to extracellular nutrients including short chain fatty acids, amino acids, and gasses. For instance, Escherichia sp. and S. variabile may contribute to the production of important short chain fatty acids (e.g., acetate and butyrate, respectively involved in the host physiology under aerobic and anaerobic conditions. We have also identified pathway susceptibility to nutrient availability and reaction changes among the four bacteria using both FBA and flux variability analysis. For instance, lipopolysaccharide synthesis, nucleotide sugar

  12. RegPrecise 3.0--a resource for genome-scale exploration of transcriptional regulation in bacteria.

    Science.gov (United States)

    Novichkov, Pavel S; Kazakov, Alexey E; Ravcheev, Dmitry A; Leyn, Semen A; Kovaleva, Galina Y; Sutormin, Roman A; Kazanov, Marat D; Riehl, William; Arkin, Adam P; Dubchak, Inna; Rodionov, Dmitry A

    2013-11-01

    Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in prokaryotes is one of the critical tasks of modern genomics. Bacteria from different taxonomic groups, whose lifestyles and natural environments are substantially different, possess highly diverged transcriptional regulatory networks. The comparative genomics approaches are useful for in silico reconstruction of bacterial regulons and networks operated by both transcription factors (TFs) and RNA regulatory elements (riboswitches). RegPrecise (http://regprecise.lbl.gov) is a web resource for collection, visualization and analysis of transcriptional regulons reconstructed by comparative genomics. We significantly expanded a reference collection of manually curated regulons we introduced earlier. RegPrecise 3.0 provides access to inferred regulatory interactions organized by phylogenetic, structural and functional properties. Taxonomy-specific collections include 781 TF regulogs inferred in more than 160 genomes representing 14 taxonomic groups of Bacteria. TF-specific collections include regulogs for a selected subset of 40 TFs reconstructed across more than 30 taxonomic lineages. Novel collections of regulons operated by RNA regulatory elements (riboswitches) include near 400 regulogs inferred in 24 bacterial lineages. RegPrecise 3.0 provides four classifications of the reference regulons implemented as controlled vocabularies: 55 TF protein families; 43 RNA motif families; ~150 biological processes or metabolic pathways; and ~200 effectors or environmental signals. Genome-wide visualization of regulatory networks and metabolic pathways covered by the reference regulons are available for all studied genomes. A separate section of RegPrecise 3.0 contains draft regulatory networks in 640 genomes obtained by an conservative propagation of the reference regulons to closely related genomes. RegPrecise 3.0 gives access to the transcriptional regulons reconstructed in

  13. Study of on-machine error identification and compensation methods for micro machine tools

    International Nuclear Information System (INIS)

    Wang, Shih-Ming; Yu, Han-Jen; Lee, Chun-Yi; Chiu, Hung-Sheng

    2016-01-01

    Micro machining plays an important role in the manufacturing of miniature products which are made of various materials with complex 3D shapes and tight machining tolerance. To further improve the accuracy of a micro machining process without increasing the manufacturing cost of a micro machine tool, an effective machining error measurement method and a software-based compensation method are essential. To avoid introducing additional errors caused by the re-installment of the workpiece, the measurement and compensation method should be on-machine conducted. In addition, because the contour of a miniature workpiece machined with a micro machining process is very tiny, the measurement method should be non-contact. By integrating the image re-constructive method, camera pixel correction, coordinate transformation, the error identification algorithm, and trajectory auto-correction method, a vision-based error measurement and compensation method that can on-machine inspect the micro machining errors and automatically generate an error-corrected numerical control (NC) program for error compensation was developed in this study. With the use of the Canny edge detection algorithm and camera pixel calibration, the edges of the contour of a machined workpiece were identified and used to re-construct the actual contour of the work piece. The actual contour was then mapped to the theoretical contour to identify the actual cutting points and compute the machining errors. With the use of a moving matching window and calculation of the similarity between the actual and theoretical contour, the errors between the actual cutting points and theoretical cutting points were calculated and used to correct the NC program. With the use of the error-corrected NC program, the accuracy of a micro machining process can be effectively improved. To prove the feasibility and effectiveness of the proposed methods, micro-milling experiments on a micro machine tool were conducted, and the results

  14. A Time-Space Domain Information Fusion Method for Specific Emitter Identification Based on Dempster-Shafer Evidence Theory.

    Science.gov (United States)

    Jiang, Wen; Cao, Ying; Yang, Lin; He, Zichang

    2017-08-28

    Specific emitter identification plays an important role in contemporary military affairs. However, most of the existing specific emitter identification methods haven't taken into account the processing of uncertain information. Therefore, this paper proposes a time-space domain information fusion method based on Dempster-Shafer evidence theory, which has the ability to deal with uncertain information in the process of specific emitter identification. In this paper, radars will generate a group of evidence respectively based on the information they obtained, and our main task is to fuse the multiple groups of evidence to get a reasonable result. Within the framework of recursive centralized fusion model, the proposed method incorporates a correlation coefficient, which measures the relevance between evidence and a quantum mechanical approach, which is based on the parameters of radar itself. The simulation results of an illustrative example demonstrate that the proposed method can effectively deal with uncertain information and get a reasonable recognition result.

  15. Application of enzymatic alkalimetric method for identification of cream and palm oils

    Directory of Open Access Journals (Sweden)

    A. V. Nikulina

    2018-01-01

    Full Text Available Nowadays the "butter" product category is widely falsified by non-dairy fats, mainly by palm oil. The methods recommended for the detection of palm oil in the fat- and oil industry products require a long-term sample preparation or the use of expensive complex equipment, which makes it urgent to search for new, more rapid analytical methods that can be used in small laboratories. An enzymatic- and alkalimetric method distinguishing between palm oil and butter is suggested in the work. The method consists in enzymatic hydrolysis of fat followed by titrimetric determination of the amount of excreted fatty acids with visual fixation of the equivalence point; titrant is the aqueous sodium hydroxide solution (0.1 mol / dm3 and indicator is phenolphthalein. Pancreatic lipase was used as the enzyme. The effect of enzyme activity, the medium pH, temperature and time on the hydrolysis of palm oil and butter was studied. The developed method peculiarity is the use of non-optimal conditions for lipid splitting. This makes it possible to reduce the rate of reaction to establish fine differences in the hydrolysis of different compositions fats. Conditions for the identification of fats - at pH = 7.9 (aqueous solution of sodium tetraborate 1% by weight were justified. In the presence of pancreatic lipase 20000, the splitting of palm oil begins in 25 minutes after the experiment start, and butter splitting begins after 10 minutes. Optimum hydrolysis time allowing to distinguish between palm oil and butter is 20 min. Identification of fats is carried out by comparing the results of alkalimetric titration of the splitting products after 5 minutes (V5’ and 20 minutes (V20’ after the beginning of hydrolysis of the fat under study with the pancreatic lipase 20000. If the sample analyzed contains only butter, then V20’ / V5’ ? 2. Numerically equal values of V5’ and V20’ are obtained when analyzing a palm oil. The value V20’ / V5’, which is in

  16. Isolation and Identification of Volatile Components in Tempe by Simultaneous Distillation-Extraction Method by Modified Extraction Method

    Directory of Open Access Journals (Sweden)

    Syahrial Syahrial

    2010-06-01

    Full Text Available An isolation and identification of volatile components in temps for 2, 5 and 8 days fermentation by simultaneous distillation-extraction method was carried out. Simultaneous distillation-extraction apparatus was modified by Muchalal from the basic Likens-Nickerson's design. Steam distillation and benzena as an extraction solvent was used in this system. The isolation was continuously carried out for 3 hours which maximum water temperature In the Liebig condenser was 8 °C. The extract was concentrated by freeze concentration method, and the volatile components were analyzed and identified by combined gas chromatography-mass spectrophotometry (GC-MS. The Muchalal's simultaneous distillation extraction apparatus have some disadvantage in cold finger condenser, and it's extractor did not have condenser. At least 47, 13 and 5 volatile components were found in 2, 5 and 8 days fermentation, respectively. The volatile components in the 2 days fermentation were nonalal, ɑ-pinene, 2,4-decadienal, 5-phenyldecane, 5-phenylundecane, 4-phenylundecane, 5-phenyldodecane, 4-phenyldodecane, 3-phenyldodecane, 2-phenyldodecane, 5-phenyltridecane, and caryophyllene; in the 5 days fermentation were nonalal, caryophyllene, 4-phenylundecane, 5-phenyldodecane, 4-phenyldodecane, 3-phenyldodecane, 2-phenyldodecane; and in the 8 days fermentation were ethenyl butanoic, 2-methy1-3-(methylethenylciclohexyl etanoic and 3,7-dimethyl-5-octenyl etanoic.

  17. A PCR detection method for rapid identification of Melissococcus pluton in honeybee larvae.

    Science.gov (United States)

    Govan, V A; Brözel, V; Allsopp, M H; Davison, S

    1998-05-01

    Melissococcus pluton is the causative agent of European foulbrood, a disease of honeybee larvae. This bacterium is particularly difficult to isolate because of its stringent growth requirements and competition from other bacteria. PCR was used selectively to amplify specific rRNA gene sequences of M. pluton from pure culture, from crude cell lysates, and directly from infected bee larvae. The PCR primers were designed from M. pluton 16S rRNA sequence data. The PCR products were visualized by agarose gel electrophoresis and confirmed as originating from M. pluton by sequencing in both directions. Detection was highly specific, and the probes did not hybridize with DNA from other bacterial species tested. This method enabled the rapid and specific detection and identification of M. pluton from pure cultures and infected bee larvae.

  18. A Genetic Programming Method for the Identification of Signal Peptides and Prediction of Their Cleavage Sites

    Directory of Open Access Journals (Sweden)

    David Lennartsson

    2004-01-01

    Full Text Available A novel approach to signal peptide identification is presented. We use an evolutionary algorithm for automatic evolution of classification programs, so-called programmatic motifs. The variant of evolutionary algorithm used is called genetic programming where a population of solution candidates in the form of full computer programs is evolved, based on training examples consisting of signal peptide sequences. The method is compared with a previous work using artificial neural network (ANN approaches. Some advantages compared to ANNs are noted. The programmatic motif can perform computational tasks beyond that of feed-forward neural networks and has also other advantages such as readability. The best motif evolved was analyzed and shown to detect the h-region of the signal peptide. A powerful parallel computer cluster was used for the experiment.

  19. Rapid detection and identification of pathogenic mycobacteria by combining radiometric and nucleic acid probe methods

    International Nuclear Information System (INIS)

    Ellner, P.D.; Kiehn, T.E.; Cammarata, R.; Hosmer, M.

    1988-01-01

    The combination of radiometric methodology (BACTEC 12B) and probe technology for recovery and identification of mycobacteria was studied in two large hospital laboratories. The sediment from vials with positive growth indices was tested with DNA probes specific for Mycobacterium tuberculosis, Mycobacterium avium, and Mycobacterium intracellulare. The sensitivity of the radiometric method and the specificity of the probes resulted in a marked reduction in the time to the final report. Biochemical testing could be eliminated on isolates giving a positive reaction with one of the probes. Some 176 isolates of M. tuberculosis, 110 of M. avium, and 5 of M. intracellulare were recovered. Two-thirds of these isolates were detected and identified within 2 weeks of inoculation and the remainder was detected by 4 weeks, a reduction of 5 to 7 weeks to the final report

  20. A Monte Carlo methods for identification and sensitivity analysis of coagulation processes

    International Nuclear Information System (INIS)

    Vikhansky, Alexander; Kraft, Markus

    2004-01-01

    A stochastic simulation algorithm is presented to calculate parametric derivatives of solutions of a population balance equation. The dispersed system is approximated by an N-particle stochastic weighted ensemble. The derivatives are accounted for through infinitesimal deviation of the statistical weights that are recalculated at each coagulation. Thus, all the parametric derivatives can be calculated along one trajectory of the process, given N sufficiently large. We use an operator-splitting technique to account for surface growth of the particles. The obtained solution is in good agreement with the available analytical solutions. As soon as the parametric derivatives are known the gradient-based methods can be applied to the control and identification of the coagulation process. The extension of the proposed technique to a multi-dimensional case is straightforward

  1. Identification and Evaluation of Strategic Decisions in Gas Industry Using DEMATEL Method

    Directory of Open Access Journals (Sweden)

    Mohammad Reza Mehregan

    2012-07-01

    Full Text Available Given the fluctuations of oil price in international markets and its effect on global economy, it is expected that gas industry and use of gas as an alternative energy, have become more important. Therefore, identification of strategic decisions in this industry has attracted increasing attention of managers and researchers. This study aims to identify and evaluate strategic decisions in the National Iranian Gas Company, using DEMATEL method for the first time. For data collection, paired comparison questionnaire have been used. The results of the research show that expanding operations to enter a new market, opening and starting up a new plant or facility, expansion of capacity and restructuring are respectively the most important strategic decisions in the industry.

  2. Molecular Methods Used for the Identification of Potentially Probiotic Lactobacillus reuteri Strains

    Directory of Open Access Journals (Sweden)

    Agnes Weiss

    2005-01-01

    Full Text Available Forty potentially probiotic Lactobacillus strains as well as reference strains of different genera were grown under standardised conditions. Cell masses were harvested and DNA was isolated. For identification, all strains were subjected to genus-specific polymerase chain reaction (PCR, and the affiliation with the genus Lactobacillus was confirmed for all isolates. Using two species-specific primer-pairs for Lactobacillus reuteri, specific amplicons were observed for eight of the forty investigated strains. For differentiation, these eight strains as well as the reference strains of the species L. reuteri and closely related species were subjected to randomly amplified polymorphic DNA (RAPD-PCR using fourteen arbitrary primers. Two selected strains as well as probiotic and common reference strains were further investigated applying pulsed field gel electrophoresis (PFGE. With the latter two methods, individual profiles were found for most strains, but no difference between probiotic and common strains could be made out.

  3. Method of and system for identification or estimation of a refractive index of a liquid

    DEFF Research Database (Denmark)

    2015-01-01

    This invention relates to a method of and a system (100) for identification or estimation of a refractive index of a liquid (120) comprising a light receiving part (111) adapted to receive polarised or non-polarised light (125; 135), a light emitting part (112) adapted, during use, to transmit...... light (130), an optical structure (110) being adapted to receive, during use, polarised light (125) via or from the light receiving part (111), and being adapted to receive, during use, a liquid (120) having a predetermined refractive index to be identified or estimated, and a first polariser (115......); is adapted, during use, to pass the received light (135) through the optical path so that a narrow wavelength range of the transmitted light (130) is influenced by the predetermined refractive index of the received liquid (120) and that the influenced narrow wavelength range, when observed by a user and...

  4. pMD-Membrane: A Method for Ligand Binding Site Identification in Membrane-Bound Proteins.

    Directory of Open Access Journals (Sweden)

    Priyanka Prakash

    2015-10-01

    Full Text Available Probe-based or mixed solvent molecular dynamics simulation is a useful approach for the identification and characterization of druggable sites in drug targets. However, thus far the method has been applied only to soluble proteins. A major reason for this is the potential effect of the probe molecules on membrane structure. We have developed a technique to overcome this limitation that entails modification of force field parameters to reduce a few pairwise non-bonded interactions between selected atoms of the probe molecules and bilayer lipids. We used the resulting technique, termed pMD-membrane, to identify allosteric ligand binding sites on the G12D and G13D oncogenic mutants of the K-Ras protein bound to a negatively charged lipid bilayer. In addition, we show that differences in probe occupancy can be used to quantify changes in the accessibility of druggable sites due to conformational changes induced by membrane binding or mutation.

  5. A computerized method for automated identification of erect posteroanterior and supine anteroposterior chest radiographs

    International Nuclear Information System (INIS)

    Kao, E-Fong; Chou, Ming-Chung; Lin, Wei-Chen; Hsu, Jui-Sheng; Jaw, Twei-Shiun; Liu, Gin-Chung

    2011-01-01

    A computerized scheme was developed for automated identification of erect posteroanterior (PA) and supine anteroposterior (AP) chest radiographs. The method was based on three features, the tilt angle of the scapula superior border, the tilt angle of the clavicle and the extent of radiolucence in lung fields, to identify the view of a chest radiograph. The three indices A scapula , A clavicle and C lung were determined from a chest image for the three features. Linear discriminant analysis was used to classify PA and AP chest images based on the three indices. The performance of the method was evaluated by receiver operating characteristic analysis. The proposed method was evaluated using a database of 600 PA and 600 AP chest radiographs. The discriminant performances Az of A scapula , A clavicle and C lung were 0.878 ± 0.010, 0.683 ± 0.015 and 0.962 ± 0.006, respectively. The combination of the three indices obtained an Az value of 0.979 ± 0.004. The results indicate that the combination of the three indices could yield high discriminant performance. The proposed method could provide radiologists with information about the view of chest radiographs for interpretation or could be used as a preprocessing step for analyzing chest images.

  6. Identification of Non-Stationary Magnetic Field Sources Using the Matching Pursuit Method

    Directory of Open Access Journals (Sweden)

    Beata Palczynska

    2017-05-01

    Full Text Available The measurements of electromagnetic field emissions, performed on board a vessel have showed that, in this specific environment, a high level of non-stationary magnetic fields (MFs is observed. The adaptive time-frequency method can be used successfully to analyze this type of measured signal. It allows one to specify the time interval in which the individual frequency components of the signal occur. In this paper, the method of identification of non-stationary MF sources based on the matching pursuit (MP algorithm is presented. It consists of the decomposition of an examined time-waveform into the linear expansion of chirplet atoms and the analysis of the matrix of their parameters. The main feature of the proposed method is the modification of the chirplet’s matrix in a way that atoms, whose normalized energies are lower than a certain threshold, will be rejected. On the time-frequency planes of the spectrograms, obtained separately for each remaining chirlpet, it can clearly identify the time-frequency structures appearing in the examined signal. The choice of a threshold defines the computing speed and precision of the performed analysis. The method was implemented in the virtual application and used for processing real data, obtained from measurements of time-vary MF emissions onboard a ship.

  7. Transferability of Object-Oriented Image Analysis Methods for Slum Identification

    Directory of Open Access Journals (Sweden)

    Alfred Stein

    2013-08-01

    Full Text Available Updated spatial information on the dynamics of slums can be helpful to measure and evaluate progress of policies. Earlier studies have shown that semi-automatic detection of slums using remote sensing can be challenging considering the large variability in definition and appearance. In this study, we explored the potential of an object-oriented image analysis (OOA method to detect slums, using very high resolution (VHR imagery. This method integrated expert knowledge in the form of a local slum ontology. A set of image-based parameters was identified that was used for differentiating slums from non-slum areas in an OOA environment. The method was implemented on three subsets of the city of Ahmedabad, India. Results show that textural features such as entropy and contrast derived from a grey level co-occurrence matrix (GLCM and the size of image segments are stable parameters for classification of built-up areas and the identification of slums. Relation with classified slum objects, in terms of enclosed by slums and relative border with slums was used to refine classification. The analysis on three different subsets showed final accuracies ranging from 47% to 68%. We conclude that our method produces useful results as it allows including location specific adaptation, whereas generically applicable rulesets for slums are still to be developed.

  8. Sparse feature learning for instrument identification: Effects of sampling and pooling methods.

    Science.gov (United States)

    Han, Yoonchang; Lee, Subin; Nam, Juhan; Lee, Kyogu

    2016-05-01

    Feature learning for music applications has recently received considerable attention from many researchers. This paper reports on the sparse feature learning algorithm for musical instrument identification, and in particular, focuses on the effects of the frame sampling techniques for dictionary learning and the pooling methods for feature aggregation. To this end, two frame sampling techniques are examined that are fixed and proportional random sampling. Furthermore, the effect of using onset frame was analyzed for both of proposed sampling methods. Regarding summarization of the feature activation, a standard deviation pooling method is used and compared with the commonly used max- and average-pooling techniques. Using more than 47 000 recordings of 24 instruments from various performers, playing styles, and dynamics, a number of tuning parameters are experimented including the analysis frame size, the dictionary size, and the type of frequency scaling as well as the different sampling and pooling methods. The results show that the combination of proportional sampling and standard deviation pooling achieve the best overall performance of 95.62% while the optimal parameter set varies among the instrument classes.

  9. Raman fiber-optical method for colon cancer detection: Cross-validation and outlier identification approach

    Science.gov (United States)

    Petersen, D.; Naveed, P.; Ragheb, A.; Niedieker, D.; El-Mashtoly, S. F.; Brechmann, T.; Kötting, C.; Schmiegel, W. H.; Freier, E.; Pox, C.; Gerwert, K.

    2017-06-01

    Endoscopy plays a major role in early recognition of cancer which is not externally accessible and therewith in increasing the survival rate. Raman spectroscopic fiber-optical approaches can help to decrease the impact on the patient, increase objectivity in tissue characterization, reduce expenses and provide a significant time advantage in endoscopy. In gastroenterology an early recognition of malign and precursor lesions is relevant. Instantaneous and precise differentiation between adenomas as precursor lesions for cancer and hyperplastic polyps on the one hand and between high and low-risk alterations on the other hand is important. Raman fiber-optical measurements of colon biopsy samples taken during colonoscopy were carried out during a clinical study, and samples of adenocarcinoma (22), tubular adenomas (141), hyperplastic polyps (79) and normal tissue (101) from 151 patients were analyzed. This allows us to focus on the bioinformatic analysis and to set stage for Raman endoscopic measurements. Since spectral differences between normal and cancerous biopsy samples are small, special care has to be taken in data analysis. Using a leave-one-patient-out cross-validation scheme, three different outlier identification methods were investigated to decrease the influence of systematic errors, like a residual risk in misplacement of the sample and spectral dilution of marker bands (esp. cancerous tissue) and therewith optimize the experimental design. Furthermore other validations methods like leave-one-sample-out and leave-one-spectrum-out cross-validation schemes were compared with leave-one-patient-out cross-validation. High-risk lesions were differentiated from low-risk lesions with a sensitivity of 79%, specificity of 74% and an accuracy of 77%, cancer and normal tissue with a sensitivity of 79%, specificity of 83% and an accuracy of 81%. Additionally applied outlier identification enabled us to improve the recognition of neoplastic biopsy samples.

  10. Raman fiber-optical method for colon cancer detection: Cross-validation and outlier identification approach.

    Science.gov (United States)

    Petersen, D; Naveed, P; Ragheb, A; Niedieker, D; El-Mashtoly, S F; Brechmann, T; Kötting, C; Schmiegel, W H; Freier, E; Pox, C; Gerwert, K

    2017-06-15

    Endoscopy plays a major role in early recognition of cancer which is not externally accessible and therewith in increasing the survival rate. Raman spectroscopic fiber-optical approaches can help to decrease the impact on the patient, increase objectivity in tissue characterization, reduce expenses and provide a significant time advantage in endoscopy. In gastroenterology an early recognition of malign and precursor lesions is relevant. Instantaneous and precise differentiation between adenomas as precursor lesions for cancer and hyperplastic polyps on the one hand and between high and low-risk alterations on the other hand is important. Raman fiber-optical measurements of colon biopsy samples taken during colonoscopy were carried out during a clinical study, and samples of adenocarcinoma (22), tubular adenomas (141), hyperplastic polyps (79) and normal tissue (101) from 151 patients were analyzed. This allows us to focus on the bioinformatic analysis and to set stage for Raman endoscopic measurements. Since spectral differences between normal and cancerous biopsy samples are small, special care has to be taken in data analysis. Using a leave-one-patient-out cross-validation scheme, three different outlier identification methods were investigated to decrease the influence of systematic errors, like a residual risk in misplacement of the sample and spectral dilution of marker bands (esp. cancerous tissue) and therewith optimize the experimental design. Furthermore other validations methods like leave-one-sample-out and leave-one-spectrum-out cross-validation schemes were compared with leave-one-patient-out cross-validation. High-risk lesions were differentiated from low-risk lesions with a sensitivity of 79%, specificity of 74% and an accuracy of 77%, cancer and normal tissue with a sensitivity of 79%, specificity of 83% and an accuracy of 81%. Additionally applied outlier identification enabled us to improve the recognition of neoplastic biopsy samples. Copyright

  11. Nonparametric identification of nonlinear dynamic systems using a synchronisation-based method

    Science.gov (United States)

    Kenderi, Gábor; Fidlin, Alexander

    2014-12-01

    The present study proposes an identification method for highly nonlinear mechanical systems that does not require a priori knowledge of the underlying nonlinearities to reconstruct arbitrary restoring force surfaces between degrees of freedom. This approach is based on the master-slave synchronisation between a dynamic model of the system as the slave and the real system as the master using measurements of the latter. As the model synchronises to the measurements, it becomes an observer of the real system. The optimal observer algorithm in a least-squares sense is given by the Kalman filter. Using the well-known state augmentation technique, the Kalman filter can be turned into a dual state and parameter estimator to identify parameters of a priori characterised nonlinearities. The paper proposes an extension of this technique towards nonparametric identification. A general system model is introduced by describing the restoring forces as bilateral spring-dampers with time-variant coefficients, which are estimated as augmented states. The estimation procedure is followed by an a posteriori statistical analysis to reconstruct noise-free restoring force characteristics using the estimated states and their estimated variances. Observability is provided using only one measured mechanical quantity per degree of freedom, which makes this approach less demanding in the number of necessary measurement signals compared with truly nonparametric solutions, which typically require displacement, velocity and acceleration signals. Additionally, due to the statistical rigour of the procedure, it successfully addresses signals corrupted by significant measurement noise. In the present paper, the method is described in detail, which is followed by numerical examples of one degree of freedom (1DoF) and 2DoF mechanical systems with strong nonlinearities of vibro-impact type to demonstrate the effectiveness of the proposed technique.

  12. [Research on the identification method of LTE condition in the laser-induced plasma].

    Science.gov (United States)

    Fan, Juan-juan; Huang, Dan; Wang, Xin; Zhang, Lei; Ma, Wei-guang; Dong, Lei; Yin, Wang-bao; Jia, Suo-tang

    2014-12-01

    Because of the poor accuracy of the commonly used Boltzmann plot method and double-line method, the Boltzmann-Maxwell distribution combined with the Saha-Eggert formula is proposed to improve the measurement accuracy of the plasma temperature; the simple algorithm for determining the linewidth of the emission line was established according to the relationship between the area and the peak value of the Gaussian formula, and the plasma electron density was calculated through the Stark broadening of the spectral lines; the method for identifying the plasma local thermal equilibrium (LTE) condition was established based on the McWhirter criterion. The experimental results show that with the increase in laser energy, the plasma temperature and electron density increase linearly; when the laser energy changes within 127~510 mJ, the plasma electron density changes in the range of 1.30532X10(17)~1.87322X10(17) cm(-3), the plasma temperature changes in the range of 12586~12957 K, and all the plasma generated in this experiment meets the LTE condition threshold according to the McWhirter criterion. For element Al, there exist relatively few observable lines at the same ionization state in the spectral region of the spectrometer, thus it is unable to use the Boltzmann plane method to calculate temperature. One hundred sets of Al plasma spectra were used for temperature measurement by employing the Saha-Boltzmann method and the relative standard deviation (RSD) value is 0.4%, and compared with 1.3% of the double line method, the accuracy has been substantially increased. The methods proposed can be used for rapid plasma temperature and electron density calculation, the LTE condition identification, and are valuable in studies such as free calibration, spectral effectiveness analysis, spectral temperature correction, the best collection location determination, LTE condition distribution in plasma, and so on.

  13. Evaluation of Different Methods for Identification of Structural Alerts Using Chemical Ames Mutagenicity Data Set as a Benchmark.

    Science.gov (United States)

    Yang, Hongbin; Li, Jie; Wu, Zengrui; Li, Weihua; Liu, Guixia; Tang, Yun

    2017-06-19

    Identification of structural alerts for toxicity is useful in drug discovery and other fields such as environmental protection. With structural alerts, researchers can quickly identify potential toxic compounds and learn how to modify them. Hence, it is important to determine structural alerts from a large number of compounds quickly and accurately. There are already many methods reported for identification of structural alerts. However, how to evaluate those methods is a problem. In this paper, we tried to evaluate four of the methods for monosubstructure identification with three indices including accuracy rate, coverage rate, and information gain to compare their advantages and disadvantages. The Kazius' Ames mutagenicity data set was used as the benchmark, and the four methods were MoSS (graph-based), SARpy (fragment-based), and two fingerprint-based methods including Bioalerts and the fingerprint (FP) method we previously used. The results showed that Bioalerts and FP could detect key substructures with high accuracy and coverage rates because they allowed unclosed rings and wildcard atom or bond types. However, they also resulted in redundancy so that their predictive performance was not as good as that of SARpy. SARpy was competitive in predictive performance in both training set and external validation set. These results might be helpful for users to select appropriate methods and further development of methods for identification of structural alerts.

  14. Feasibility Study on Tension Estimation Technique for Hanger Cables Using the FE Model-Based System Identification Method

    Directory of Open Access Journals (Sweden)

    Kyu-Sik Park

    2015-01-01

    Full Text Available Hanger cables in suspension bridges are partly constrained by horizontal clamps. So, existing tension estimation methods based on a single cable model are prone to higher errors as the cable gets shorter, making it more sensitive to flexural rigidity. Therefore, inverse analysis and system identification methods based on finite element models are suggested recently. In this paper, the applicability of system identification methods is investigated using the hanger cables of Gwang-An bridge. The test results show that the inverse analysis and systemic identification methods based on finite element models are more reliable than the existing string theory and linear regression method for calculating the tension in terms of natural frequency errors. However, the estimation error of tension can be varied according to the accuracy of finite element model in model based methods. In particular, the boundary conditions affect the results more profoundly when the cable gets shorter. Therefore, it is important to identify the boundary conditions through experiment if it is possible. The FE model-based tension estimation method using system identification method can take various boundary conditions into account. Also, since it is not sensitive to the number of natural frequency inputs, the availability of this system is high.

  15. Identification of Error of Commissions in the LOCA Using the CESA Method

    Energy Technology Data Exchange (ETDEWEB)

    Tukhbyet-olla, Myeruyert; Kang, Sunkoo; Kim, Jonghyun [KEPCO international nuclear graduate school, Ulsan (Korea, Republic of)

    2015-10-15

    An Errors of commission (EOCs) can be defined as the performance of any inappropriate action that aggravates the situation. The primary focus in current PSA is placed on those sequences of hardware failures and/or EOOs that lead to unsafe system states. Although EOCs can be treated when identified, a systematic and comprehensive treatment of EOC opportunities remains outside the scope of PSAs. However, some past experiences in the nuclear industry show that EOCs have contributed to severe accidents. Some recent and emerging human reliability analysis (HRA) methods suggest approaches to identify and quantify EOCs, such as ATHEANA, MERMOS, GRS, MDTA, and CESA. The CESA method, developed by the Risk and Human Reliability Group at the Paul Scherrer Institute, is to identify potentially risk-significant EOCs, given an existing PSA. The main idea underlying the method is to catalog the key actions that are required in the procedural response to plant events and to identify specific scenarios in which these candidate actions could erroneously appear to be required. This paper aims at identifying EOCs in the LOCA by using the CESA method. This study is focused on the identification of EOCs, while the quantification of EOCs is out of scope. Then, this paper applies the CESA method to the emergency operating procedure (EOP) of LOCA for APR1400. Finally, this study presents potential EOCs that may lead to the aggravation in the mitigation of LOCA. This study has identified the EOC events for APR1400 in the LOCA using CESA method. The result identified three candidate EOCs event using operator action catalog and RAW cutset of LOCA. These candidate EOC events are inappropriate terminations of safety injection system, safety injection tank and containment spray system. Then after reviewing top 100 accident sequences of PSA, this study finally identified one EOC scenario and EOC path, that is, inappropriate termination of safety injection system.

  16. Evaluation of identification methods of irradiated spices and dehydrated vegetables in Brazil

    International Nuclear Information System (INIS)

    Bernardes, D.M.L.; Del Mastro, N.L.

    1998-01-01

    Complete text of publication follows. This paper deals with the use of analytical methods to determine whether imported or for export Brazilian spices and dehydrated vegetables were irradiated. Viscosimetry, thermoluminescence (TL) and electron spin resonance (ESR) were used for the identification of some irradiated products: black pepper, white pepper, cinnamon, nutmeg, garlic, cumin, oregano, celery, paprika and coriander. Viscosimetry was performed in suspensions of irradiated spices and dehydrated vegetables which had been gellified by heat. Thermoluminescence (TL) is based on the transference of electrons to an excited state by radiation with emission of light when the electrons are thermally stimulated. The thermoluminescent signal of spices can be explained by the presence of mineral grains adhering on the surface of the samples. Free radicals produced by irradiation of spices were analyzed by electron spin resonance (EPR) signals. The results of this study lead to the conclusion that viscosimetry, thermoluminescence and electron spin resonance are analytical methods that can be use to detect whether spices and dehydrated vegetables were irradiated, specially when a combination of different methods was used

  17. Radiologic identification of disaster victims: A simple and reliable method using CT of the paranasal sinuses

    International Nuclear Information System (INIS)

    Ruder, Thomas D.; Kraehenbuehl, Markus; Gotsmy, Walther F.; Mathier, Sandra; Ebert, Lars C.; Thali, Michael J.; Hatch, Gary M.

    2012-01-01

    Objective: To assess the reliability of radiologic identification using visual comparison of ante and post mortem paranasal sinus computed tomography (CT). Subjects and methods: The study was approved by the responsible justice department and university ethics committee. Four blinded readers with varying radiological experience separately compared 100 post mortem to 25 ante mortem head CTs with the goal to identify as many matching pairs as possible (out of 23 possible matches). Sensitivity, specificity, positive and negative predictive values were calculated for all readers. The chi-square test was applied to establish if there was significant difference in sensitivity between radiologists and non-radiologists. Results: For all readers, sensitivity was 83.7%, specificity was 100.0%, negative predictive value (NPV) was 95.4%, positive predictive value (PPV) was 100.0%, and accuracy was 96.3%. For radiologists, sensitivity was 97.8%, NPV was 99.4%, and accuracy was 99.5%. For non-radiologists, average sensitivity was 69.6%, negative predictive value (NPV) was 91.7%, and accuracy was 93.0%. Radiologists achieved a significantly higher sensitivity (p < 0.01) than non-radiologists. Conclusions: Visual comparison of ante mortem and post mortem CT of the head is a robust and reliable method for identifying unknown decedents, particularly in regard to positive matches. The sensitivity and NPV of the method depend on the reader's experience.

  18. Impact source identification in finite isotropic plates using a time-reversal method: theoretical study

    International Nuclear Information System (INIS)

    Chen, Chunlin; Yuan, Fuh-Gwo

    2010-01-01

    This paper aims to identify impact sources on plate-like structures based on the synthetic time-reversal (T-R) concept using an array of sensors. The impact source characteristics, namely, impact location and impact loading time history, are reconstructed using the invariance of time-reversal concept, reciprocal theory, and signal processing algorithms. Numerical verification for two finite isotropic plates under low and high velocity impacts is performed to demonstrate the versatility of the synthetic T-R method for impact source identification. The results show that the impact location and time history of the impact force with various shapes and frequency bands can be readily obtained with only four sensors distributed around the impact location. The effects of time duration and the inaccuracy in the estimated impact location on the accuracy of the time history of the impact force using the T-R method are investigated. Since the T-R technique retraces all the multi-paths of reflected waves from the geometrical boundaries back to the impact location, it is well suited for quantifying the impact characteristics for complex structures. In addition, this method is robust against noise and it is suggested that a small number of sensors is sufficient to quantify the impact source characteristics through simple computation; thus it holds promise for the development of passive structural health monitoring (SHM) systems for impact monitoring in near real-time

  19. A Dissipation Gap Method for full-field measurement-based identification of elasto-plastic material parameters

    KAUST Repository

    Blaysat, Benoît

    2012-05-18

    Using enriched data such as displacement fields obtained from digital image correlation is a pathway to the local identification of material parameters. Up to now, most of the identification techniques for nonlinear models are based on Finite Element Updating Methods. This article explains how an appropriate use of the Dissipation Gap Method can help in this context and be an interesting alternative to these classical techniques. The Dissipation Gap Methods rely on the concept of error in dissipation that has been used mainly for the verification of finite element simulations. We provide here an original application of these founding developments to the identification of material parameters for nonlinear behaviors. The proposed technique and especially the main technical keypoint of building the admissible fields are described in detail. The approach is then illustrated through the identification of heterogeneous isotropic elasto-plastic properties. The basic numerical features highlighted through these simple examples demonstrate this approach to be a promising tool for nonlinear identification. © 2012 John Wiley & Sons, Ltd.

  20. Post-BEMUSE Reflood Model Input Uncertainty Methods (PREMIUM) Benchmark Phase II: Identification of Influential Parameters

    International Nuclear Information System (INIS)

    Kovtonyuk, A.; Petruzzi, A.; D'Auria, F.

    2015-01-01

    The objective of the Post-BEMUSE Reflood Model Input Uncertainty Methods (PREMIUM) benchmark is to progress on the issue of the quantification of the uncertainty of the physical models in system thermal-hydraulic codes by considering a concrete case: the physical models involved in the prediction of core reflooding. The PREMIUM benchmark consists of five phases. This report presents the results of Phase II dedicated to the identification of the uncertain code parameters associated with physical models used in the simulation of reflooding conditions. This identification is made on the basis of the Test 216 of the FEBA/SEFLEX programme according to the following steps: - identification of influential phenomena; - identification of the associated physical models and parameters, depending on the used code; - quantification of the variation range of identified input parameters through a series of sensitivity calculations. A procedure for the identification of potentially influential code input parameters has been set up in the Specifications of Phase II of PREMIUM benchmark. A set of quantitative criteria has been as well proposed for the identification of influential IP and their respective variation range. Thirteen participating organisations, using 8 different codes (7 system thermal-hydraulic codes and 1 sub-channel module of a system thermal-hydraulic code) submitted Phase II results. The base case calculations show spread in predicted cladding temperatures and quench front propagation that has been characterized. All the participants, except one, predict a too fast quench front progression. Besides, the cladding temperature time trends obtained by almost all the participants show oscillatory behaviour which may have numeric origins. Adopted criteria for identification of influential input parameters differ between the participants: some organisations used the set of criteria proposed in Specifications 'as is', some modified the quantitative thresholds

  1. [Biometric identification method for ECG based on the piecewise linear representation (PLR) and dynamic time warping (DTW)].

    Science.gov (United States)

    Yang, Licai; Shen, Jun; Bao, Shudi; Wei, Shoushui

    2013-10-01

    To treat the problem of identification performance and the complexity of the algorithm, we proposed a piecewise linear representation and dynamic time warping (PLR-DTW) method for ECG biometric identification. Firstly we detected R peaks to get the heartbeats after denoising preprocessing. Then we used the PLR method to keep important information of an ECG signal segment while reducing the data dimension at the same time. The improved DTW method was used for similarity measurements between the test data and the templates. The performance evaluation was carried out on the two ECG databases: PTB and MIT-BIH. The analystic results showed that compared to the discrete wavelet transform method, the proposed PLR-DTW method achieved a higher accuracy rate which is nearly 8% of rising, and saved about 30% operation time, and this demonstrated that the proposed method could provide a better performance.

  2. Beef Quality Identification Using Thresholding Method and Decision Tree Classification Based on Android Smartphone

    Directory of Open Access Journals (Sweden)

    Kusworo Adi

    2017-01-01

    Full Text Available Beef is one of the animal food products that have high nutrition because it contains carbohydrates, proteins, fats, vitamins, and minerals. Therefore, the quality of beef should be maintained so that consumers get good beef quality. Determination of beef quality is commonly conducted visually by comparing the actual beef and reference pictures of each beef class. This process presents weaknesses, as it is subjective in nature and takes a considerable amount of time. Therefore, an automated system based on image processing that is capable of determining beef quality is required. This research aims to develop an image segmentation method by processing digital images. The system designed consists of image acquisition processes with varied distance, resolution, and angle. Image segmentation is done to separate the images of fat and meat using the Otsu thresholding method. Classification was carried out using the decision tree algorithm and the best accuracies were obtained at 90% for training and 84% for testing. Once developed, this system is then embedded into the android programming. Results show that the image processing technique is capable of proper marbling score identification.

  3. A Hilbert transform method for parameter identification of time-varying structures with observer techniques

    International Nuclear Information System (INIS)

    Wang, Zuo-Cai; Ren, Wei-Xin; Chen, Gen-Da

    2012-01-01

    This paper presents a recursive Hilbert transform method for the time-varying property identification of large-scale shear-type buildings with limited sensor deployments. An observer technique is introduced to estimate the building responses from limited available measurements. For an n-story shear-type building with l measurements (l ≤ n), the responses of other stories without measurements can be estimated based on the first r mode shapes (r ≤ l) as-built conditions and l measurements. Both the measured responses and evaluated responses and their Hilbert transforms are then used to track any variation of structural parameters of a multi-story building over time. Given floor masses, both the stiffness and damping coefficients of the building are identified one-by-one from the top to the bottom story. When variations of parameters are detected, a new developed branch-and-bound technique can be used to update the first r mode shapes with the identified parameters. A 60-story shear building with abruptly varying stiffness at different floors is simulated as an example. The numerical results indicate that the proposed method can detect variations of the parameters of large-scale shear-type buildings with limited sensor deployments at appropriate locations. (paper)

  4. Description of an identification method of thermocouple time constant based on application of recursive numerical filtering to temperature fluctuation

    International Nuclear Information System (INIS)

    Bernardin, B.; Le Guillou, G.; Parcy, JP.

    1981-04-01

    Usual spectral methods, based on temperature fluctuation analysis, aiming at thermocouple time constant identification are using an equipment too much sophisticated for on-line application. It is shown that numerical filtering is optimal for this application, the equipment is simpler than for spectral methods and less samples of signals are needed for the same accuracy. The method is described and a parametric study was performed using a temperature noise simulator [fr

  5. The smart cluster method. Adaptive earthquake cluster identification and analysis in strong seismic regions

    Science.gov (United States)

    Schaefer, Andreas M.; Daniell, James E.; Wenzel, Friedemann

    2017-07-01

    Earthquake clustering is an essential part of almost any statistical analysis of spatial and temporal properties of seismic activity. The nature of earthquake clusters and subsequent declustering of earthquake catalogues plays a crucial role in determining the magnitude-dependent earthquake return period and its respective spatial variation for probabilistic seismic hazard assessment. This study introduces the Smart Cluster Method (SCM), a new methodology to identify earthquake clusters, which uses an adaptive point process for spatio-temporal cluster identification. It utilises the magnitude-dependent spatio-temporal earthquake density to adjust the search properties, subsequently analyses the identified clusters to determine directional variation and adjusts its search space with respect to directional properties. In the case of rapid subsequent ruptures like the 1992 Landers sequence or the 2010-2011 Darfield-Christchurch sequence, a reclassification procedure is applied to disassemble subsequent ruptures using near-field searches, nearest neighbour classification and temporal splitting. The method is capable of identifying and classifying earthquake clusters in space and time. It has been tested and validated using earthquake data from California and New Zealand. A total of more than 1500 clusters have been found in both regions since 1980 with M m i n = 2.0. Utilising the knowledge of cluster classification, the method has been adjusted to provide an earthquake declustering algorithm, which has been compared to existing methods. Its performance is comparable to established methodologies. The analysis of earthquake clustering statistics lead to various new and updated correlation functions, e.g. for ratios between mainshock and strongest aftershock and general aftershock activity metrics.

  6. The evidence of the rugoscopy effectiveness as a human identification method in patients submitted to rapid palatal expansion.

    Science.gov (United States)

    Barbieri, Ana A; Scoralick, Raquel A; Naressi, Suely C M; Moraes, Mari E L; Daruge, Eduardo; Daruge, Eduardo

    2013-01-01

    The objective of this study was to demonstrate the effectiveness of rugoscopy as a human identification method, even when the patient is submitted to rapid palatal expansion, which in theory would introduce doubt. With this intent, the Rugoscopic Identity was obtained for each subject using the classification formula proposed by Santos based on the intra-oral casts made before and after treatment from patients who were subjected to palatal expansion. The casts were labeled with the patients' initials and randomly arranged for studying. The palatine rugae kept the same patterns in every case studied. The technical error of the intra-evaluator measurement provided a confidence interval of 95%, making rugoscopy a reliable identification method for patients who were submitted to rapid palatal expansion, because even in the presence of intra-oral changes owing to the use of palatal expanders, the palatine rugae retained the biological and technical requirements for the human identification process. © 2012 American Academy of Forensic Sciences.

  7. An inertial parameter identification method of eliminating system damping effect for a six-degree-of-freedom parallel manipulator

    Directory of Open Access Journals (Sweden)

    Tian Tixian

    2015-04-01

    Full Text Available A new simple and effective inertial parameter identification method based on sinusoidal vibrations of a six-degree-of-freedom parallel manipulator is proposed. Compared with previously known identification algorithms, the advantages of the new approach are there is no need to design the excitation trajectory to consider the condition number of the observation matrix and the inertial matrix can be accurately defined regardless of the effect of viscous friction. In addition, the use of a sinusoidal exciting trajectory allows calculation of the velocities and accelerations from the measured position response. Simulations show that the new approach has acceptable tolerance of dry friction when using a simple coupling parameter modified formula. The experimental application to the hydraulically driven Stewart platform demonstrates the capability and efficiency of the proposed identification method.

  8. Studies of top tagging identification methods and development of a new heavy object tagger

    International Nuclear Information System (INIS)

    Lapsien, Tobias

    2016-05-01

    At the Large Hadron Collider (LHC), precision tests of the standard model of particle physics and searches for new phenomena are performed. To make optimal use of the proton-proton collisions delivered by the LHC and its increasing collision rate, both the detectors and the reconstruction algorithms have to be optimized. The identification of heavy quarks is a key component in many measurements. This thesis describes a hardware and a software project which both aim at improving the identification of heavy quarks. In the first part of this thesis, the Phase 1 upgrade of the CMS pixel detector is introduced. One of the main motivations of the replacement of the Pixel detector is the improved b jet identification at large collision rates. The Phase 1 upgrade involves several production and calibration steps. An X-ray calibration procedure has been developed and the corresponding experimental setup is described. Measurements show that the calibration of the pixel modules is temperature independent and can be performed at room temperature. The stability of the setup is tested in order to fulfill the requirements for mass production of the pixel modules. A method to stabilize the calibration is introduced which is shown to reduce the systematic uncertainty. In the second part, algorithms to identify heavily boosted top quarks (''top tagger'') are described and their performance is compared. The OptimalR HEP top tagger and the shower deconstruction tagger show a better performance than existing tagging algorithms. They can be used in Run II with increased centre-of-mass energies of 13 and 14 TeV. It is also shown that existing top tagging algorithms can be improved by the usage of multivariate analysis methods. New algorithms are commissioned using CMS data with a centre-of-mass energy of 8 TeV, corresponding to an integrated luminosity of 19.7 fb -1 . In order to validate these new algorithms in data, two selections are made to measure the efficiency

  9. Comparison of RNA Extraction Methods for the Identification of Grapevine fan leaf virus

    Directory of Open Access Journals (Sweden)

    Z. Gholampour

    2016-06-01

    Full Text Available Introduction: To now, more than 70 viral diseases have been reported from grapevine. Serological methods are regular diagnostic tools of grapevine viruses, however, their sensitivity has affected by seasonal fluctuations of the virus. Reverse transcription polymerase chain reaction provides significant improvement in detection of grapevine viruses. Extraction of high-quality RNA is essential for the successful application of many molecular techniques, such as RT-PCR. Extraction of high-quality RNA from the leaves of woody plants, such as grapevine, is particularly challenging because of high concentrations of polysaccharides, polyphenols, and other secondary metabolites. Some RNA extraction methods yield pellets that are poorly soluble, indicating the presence of unknown contaminants, whereas others are gelatinous, indicating the presence of polysaccharides. RNA can make complexes with polysaccharides and phenolic compounds render the RNA unusable for applications such as reverse transcription. Grapevine fanleaf virus is a member of the genus Nepovirus in the family Secoviridae. The GFLV genome consists of two positive-sense single stranded RNAs. The genome has a poly (A tail at the 3´ terminus and a covalently linked VPG protein at the 5´ terminus. Several extraction methods had been reported to be used for identification of GFLV in grapevine. Some of them require harmful chemical material; disadvantages of other are high costs. Immunocapture-RT-PCR requires preparation of specific antibody and direct binding RT-PCR (DB-RT-PCR has a high contamination risk. In this study, four RNA extraction protocols were compared with a commercial isolation kit to explore the most efficient RNA isolation method for grapevines. Material and Methods: 40 leaf samples were randomly collected during the growing season of 2011-2012. GFLV was detected in leaf samples by enzyme linked immunosorbent assay (ELISA Using specific antibodies raised against Iranian

  10. Acorn: A grid computing system for constraint based modeling and visualization of the genome scale metabolic reaction networks via a web interface

    Directory of Open Access Journals (Sweden)

    Bushell Michael E

    2011-05-01

    Full Text Available Abstract Background Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the genome. Recently, genome annotations have been used to reconstruct genome scale metabolic reaction networks for numerous species, including Homo sapiens, which allow simulations that provide valuable insights into topics, including predictions of gene essentiality of pathogens, interpretation of genetic polymorphism in metabolic disease syndromes and suggestions for novel approaches to microbial metabolic engineering. These constraint-based simulations are being integrated with the functional genomics portals, an activity that requires efficient implementation of the constraint-based simulations in the web-based environment. Results Here, we present Acorn, an open source (GNU GPL grid computing system for constraint-based simulations of genome scale metabolic reaction networks within an interactive web environment. The grid-based architecture allows efficient execution of computationally intensive, iterative protocols such as Flux Variability Analysis, which can be readily scaled up as the numbers of models (and users increase. The web interface uses AJAX, which facilitates efficient model browsing and other search functions, and intuitive implementation of appropriate simulation conditions. Research groups can install Acorn locally and create user accounts. Users can also import models in the familiar SBML format and link reaction formulas to major functional genomics portals of choice. Selected models and simulation results can be shared between different users and made publically available. Users can construct pathway map layouts and import them into the server using a desktop editor integrated within the system. Pathway maps are then used to visualise numerical results within the web environment. To illustrate these features we have deployed Acorn and created a

  11. 19 CFR 191.14 - Identification of merchandise or articles by accounting method.

    Science.gov (United States)

    2010-04-01

    ... applies to identification of merchandise or articles in inventory or storage, as well as identification of... identified as being received into and withdrawn from the same inventory. Even if merchandise or articles are... or articles under this section, subject to the conditions of this section. If any such inventory...

  12. Advances in methods for identification and characterization of plant transporter function

    DEFF Research Database (Denmark)

    Larsen, Bo; Xu, Deyang; Halkier, Barbara Ann

    2017-01-01

    Transport proteins are crucial for cellular function at all levels. Numerous importers and exporters facilitate transport of a diverse array of metabolites and ions intra- and intercellularly. Identification of transporter function is essential for understanding biological processes at both......-based approaches. In this review, we highlight examples that illustrate how new technology and tools have advanced identification and characterization of plant transporter functions....

  13. Image De-Identification Methods for Clinical Research in the XDS Environment

    NARCIS (Netherlands)

    Aryanto, K. Y. E.; van Kernebeek, G.; Berendsen, B.; Oudkerk, M.; van Ooijen, P. M. A.

    To investigate possible de-identification methodologies within the Cross-Enterprise Document Sharing for imaging (XDS-I) environment in order to provide strengthened support for image data exchange as part of clinical research projects. De-identification, using anonymization or pseudonymization, is

  14. Load power device, system and method of load control and management employing load identification

    Science.gov (United States)

    Yang, Yi; Luebke, Charles John; Schoepf, Thomas J.

    2018-01-09

    A load power device includes a power input, at least one power output for at least one load, a plurality of sensors structured to sense voltage and current at the at least one power output, and a processor. The processor provides: (a) load identification based upon the sensed voltage and current, and (b) load control and management based upon the load identification.

  15. Candida colonization and species identification by two methods in NICU newborn

    Directory of Open Access Journals (Sweden)

    Narges Sadat Taherzadeh

    2016-02-01

    Full Text Available Background: Over the last two decades invasive candidiasis has become an increasing problem in neonatal intensive care units (NICUs. Colonization of skin and mucous membranes with Candida spp. is important factor in the pathogenesis of neonatal infection and several colonized sites are major risk factors evoking higher frequencies of progression to invasive candidiasis. The aim of this study was to detect Candida colonization in NICU patients. Methods: This cross-sectional study was conducted on 93 neonates in NICUs at Imam Khomeini and Children Medical Center Hospitals in Tehran. Cutaneous and mucous membrane samples obtained at first, third, and seventh days of patients’ stay in NICUs during nine months from August 2013 to May 2014. The samples were primarily cultured on CHROMagar Candida medium. The cultured media were incubated at 35°C for 48h and evaluated based on colony color produced on CHROMagar Candida. In addition, isolated colonies were cultured on Corn Meal Agar medium supplemented with tween 80 for identification of Candida spp. based on their morphology. Finally, polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP method was performed for definite identification of isolated species. Results: Colonization by Candida spp. was occurred in 20.43% of neonates. Fifteen and four patients colonized with one and two different Candida spp., respectively. Isolated Candida spp. identified as; C. parapsilosis (n: 10, C. albicans (n: 7, C. tropicalis (n: 3, C. guilliermondii (n: 2, and C. krusei (n: 1. In present study non-albicans Candia species were dominant (69.56% and C. parapsilosis was the most frequent isolate (43.47%. Using Fisher's exact test, the correlation between fungal colonization with low birth weight, low gestational age, and duration of hospital stay was found to be statistically significant (P=0.003. Conclusion: The results of this study imply to the candida species colonization of neonates

  16. Improved method for rapid and accurate isolation and identification of Streptococcus mutans and Streptococcus sobrinus from human plaque samples.

    Science.gov (United States)

    Villhauer, Alissa L; Lynch, David J; Drake, David R

    2017-08-01

    Mutans streptococci (MS), specifically Streptococcus mutans (SM) and Streptococcus sobrinus (SS), are bacterial species frequently targeted for investigation due to their role in the etiology of dental caries. Differentiation of S. mutans and S. sobrinus is an essential part of exploring the role of these organisms in disease progression and the impact of the presence of either/both on a subject's caries experience. Of vital importance to the study of these organisms is an identification protocol that allows us to distinguish between the two species in an easy, accurate, and timely manner. While conducting a 5-year birth cohort study in a Northern Plains American Indian tribe, the need for a more rapid procedure for isolating and identifying high volumes of MS was recognized. We report here on the development of an accurate and rapid method for MS identification. Accuracy, ease of use, and material and time requirements for morphological differentiation on selective agar, biochemical tests, and various combinations of PCR primers were compared. The final protocol included preliminary identification based on colony morphology followed by PCR confirmation of species identification using primers targeting regions of the glucosyltransferase (gtf) genes of SM and SS. This method of isolation and identification was found to be highly accurate, more rapid than the previous methodology used, and easily learned. It resulted in more efficient use of both time and material resources. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. A new time-frequency method for identification and classification of ball bearing faults

    Science.gov (United States)

    Attoui, Issam; Fergani, Nadir; Boutasseta, Nadir; Oudjani, Brahim; Deliou, Adel

    2017-06-01

    In order to fault diagnosis of ball bearing that is one of the most critical components of rotating machinery, this paper presents a time-frequency procedure incorporating a new feature extraction step that combines the classical wavelet packet decomposition energy distribution technique and a new feature extraction technique based on the selection of the most impulsive frequency bands. In the proposed procedure, firstly, as a pre-processing step, the most impulsive frequency bands are selected at different bearing conditions using a combination between Fast-Fourier-Transform FFT and Short-Frequency Energy SFE algorithms. Secondly, once the most impulsive frequency bands are selected, the measured machinery vibration signals are decomposed into different frequency sub-bands by using discrete Wavelet Packet Decomposition WPD technique to maximize the detection of their frequency contents and subsequently the most useful sub-bands are represented in the time-frequency domain by using Short Time Fourier transform STFT algorithm for knowing exactly what the frequency components presented in those frequency sub-bands are. Once the proposed feature vector is obtained, three feature dimensionality reduction techniques are employed using Linear Discriminant Analysis LDA, a feedback wrapper method and Locality Sensitive Discriminant Analysis LSDA. Lastly, the Adaptive Neuro-Fuzzy Inference System ANFIS algorithm is used for instantaneous identification and classification of bearing faults. In order to evaluate the performances of the proposed method, different testing data set to the trained ANFIS model by using different conditions of healthy and faulty bearings under various load levels, fault severities and rotating speed. The conclusion resulting from this paper is highlighted by experimental results which prove that the proposed method can serve as an intelligent bearing fault diagnosis system.

  18. A PCR-based method for identification of bifidobacteria from the human alimentary tract at the species level

    NARCIS (Netherlands)

    Venema, K.; Maathuis, A.J.H.

    2003-01-01

    A polymerase chain reaction (PCR)-based method was developed for the identification of isolates of Bifidobacterium at the species level. Using two Bifidobacterium-specific primers directed against the 16S ribosomal gene (Bif164 and Bif662), a PCR product was obtained from the type strains of 12

  19. Improved method for reliable HMW-GS identification by RP-HPLC and SDS-PAGE in common wheat cultivars

    Science.gov (United States)

    The accurate identification of alleles for high-molecular weight glutenins (HMW-GS) is critical for wheat breeding programs targeting end-use quality. RP-HPLC methods were optimized for separation of HMW-GS, resulting in enhanced resolution of 1By and 1Dx subunits. Statistically significant differe...

  20. Identification of fine-leaved species of genus Festuca by molecular methods

    International Nuclear Information System (INIS)

    Stukonis, V.; Armoniene, R.; Kemesyte, V.

    2015-01-01

    Festuca (L.) is a taxonomically complex genus of family Poaceae. The fine-leaved species of fescue are well adapted to grow in sandy and dry habitats, therefore, they can be used for establishment of lawns of minimal maintenance as well as recultivations of damaged soils. Breeding for the new varieties to meet these purposes requires reliable methods for identification of the species. The discrimination of fine-leaved fescue species based on morphological features is rather difficult, therefore reliable molecular marker would greatly facilitate it and eliminate the need to wait till floral organs are fully formed. Seven fine-leaved species of genus Festuca collected in Lithuania, namely, F. ovina, F. trachyphylla, F. polesica, F. psammophila, F. sabulosa, F. pseudovina and F. wolgensis were investigated at the Institute of Agriculture, Lithuanian Research Centre for Agriculture and Forestry. The ISSR markers, seed storage proteins and isozymes were tested for their ability to distinguish between the fine-leaved species of the genus Festuca. Seed storage protein and ISSR fingerprint profiles could be used to distinguish between fine-leaved species of Festuca, except for closely related F. sabulosa and F. polesica species. Isozyme fingerprints did not contain sufficient number of species specific bands and were not feasible to discriminate between species. (author)

  1. Interfacial damage identification of steel and concrete composite beams based on piezoceramic wave method.

    Science.gov (United States)

    Yan, Shi; Dai, Yong; Zhao, Putian; Liu, Weiling

    2018-01-01

    Steel-concrete composite structures are playing an increasingly important role in economic construction because of a series of advantages of great stiffness, good seismic performance, steel material saving, cost efficiency, convenient construction, etc. However, in service process, due to the long-term effects of environmental impacts and dynamic loading, interfaces of a composite structure might generate debonding cracks, relative slips or separations, and so on, lowering the composite effect of the composite structure. In this paper, the piezoceramics (PZT) are used as transducers to perform experiments on interface debonding slips and separations of composite beams, respectively, aimed at proposing an interface damage identification model and a relevant damage detection innovation method based on PZT wave technology. One part of various PZT patches was embedded in concrete as "smart aggregates," and another part of the PZT patches was pasted on the surface of the steel beam flange, forming a sensor array. A push-out test for four specimens was carried out and experimental results showed that, under the action of the external loading, the received signal amplitudes will increasingly decrease with increase of debonding slips along the interface. The proposed signal energy-based interface damage detection algorithm is highly efficient in surface state evaluations of composite beams.

  2. Identification of irradiated spices by the use of thermoluminescence method (TL)

    Energy Technology Data Exchange (ETDEWEB)

    Sharifzadeh, M.; Sohrabpour, M. (Atomic Energy Organization of Iran, Teheran (Iran, Islamic Republic of))

    In this paper the results of the investigation of identification of irradiated spices by the use of thermoluminescence method is reported. The materials used were black and red peppers, turmeric, cinnamon, and garlic powder. Gamma Cell 220 was used for irradiating samples at dose values of 2.5, 5, 7.5 and 10 kGy respectively. The TL intensity of the unirradiated spices as well as the fading characteristics of the irradiated samples having received a dose of 10 kGy have been measured. Post-irradiation temperature treatment of the irradiated (10 kGy) and unirradiated samples at 60[sup o]C and 100[sup o]C for 24 hours have also been performed. The results show that the TL intensities of unirradiated and irradiated samples from different batches of each spice are fairly distributed. A reasonable TL intensity versus dose has been observed in nearly all cases. Based on the observation made it is possible to distinguish irradiated spices after (4-9) months post-irradiation. (author).

  3. Method for rapid detection and identification of chaetomium and evaluation of resistance to peracetic acid.

    Science.gov (United States)

    Nakayama, Motokazu; Hosoya, Kouichi; Tomiyama, Daisuke; Tsugukuni, Takashi; Matsuzawa, Tetsuhiro; Imanishi, Yumi; Yaguchi, Takashi

    2013-06-01

    In the beverage industry, peracetic acid has been increasingly used as a disinfectant for the filling machinery and environment due to merits of leaving no residue, it is safe for humans, and its antiseptic effect against fungi and endospores of bacteria. Recently, Chaetomium globosum and Chaetomium funicola were reported resistant to peracetic acid; however, little is known concerning the detail of peracetic acid resistance. Therefore, we assessed the peracetic acid resistance of the species of Chaetomium and related genera under identical conditions and made a thorough observation of the microstructure of their ascospores by transmission electron microscopy. The results of analyses revealed that C. globosum and C. funicola showed the high resistance to peracetic acid (a 1-D antiseptic effect after 900 s and 3-D antiseptic effect after 900 s) and had thick cell walls of ascospores that can impede the action mechanism of peracetic acid. We also developed specific primers to detect the C. globosum clade and identify C. funicola by using PCR to amplify the β-tubulin gene. PCR with the primer sets designed for C. globosum (Chae 4F/4R) and C. funicola (Cfu 2F/2R) amplified PCR products specific for the C. globosum clade and C. funicola, respectively. PCR with these two primer sets did not detect other fungi involved in food spoilage and environmental contamination. This detection and identification method is rapid and simple, with extremely high specificity.

  4. Identification of irradiated spices by the use of thermoluminescence method (TL)

    International Nuclear Information System (INIS)

    Sharifzadeh, M.; Sohrabpour, M.

    1993-01-01

    In this paper the results of the investigation of identification of irradiated spices by the use of thermoluminescence method is reported. The materials used were black and red peppers, turmeric, cinnamon, and garlic powder. Gamma Cell 220 was used for irradiating samples at dose values of 2.5, 5, 7.5 and 10 kGy respectively. The TL intensity of the unirradiated spices as well as the fading characteristics of the irradiated samples having received a dose of 10 kGy have been measured. Post-irradiation temperature treatment of the irradiated (10 kGy) and unirradiated samples at 60 o C and 100 o C for 24 hours have also been performed. The results show that the TL intensities of unirradiated and irradiated samples from different batches of each spice are fairly distributed. A reasonable TL intensity versus dose has been observed in nearly all cases. Based on the observation made it is possible to distinguish irradiated spices after (4-9) months post-irradiation. (author)

  5. Methods for automated identification of informative behaviors in natural bioptic driving.

    Science.gov (United States)

    Luo, Gang; Peli, Eli

    2012-06-01

    Visually impaired people may legally drive if wearing bioptic telescopes in some developed countries. To address the controversial safety issue of the practice, we have developed a low-cost in-car recording system that can be installed in study participants' own vehicles to record their daily driving activities. We also developed a set of automated identification techniques of informative behaviors to facilitate efficient manual review of important segments submerged in the vast amount of uncontrolled data. Here, we present the methods and quantitative results of the detection performance for six types of driving maneuvers and behaviors that are important for bioptic driving: bioptic telescope use, turns, curves, intersections, weaving, and rapid stops. The testing data were collected from one normally sighted and two visually impaired subjects across multiple days. The detection rates ranged from 82% up to 100%, and the false discovery rates ranged from 0% to 13%. In addition, two human observers were able to interpret about 80% of targets viewed through the telescope. These results indicate that with appropriate data processing the low-cost system is able to provide reliable data for natural bioptic driving studies.

  6. Identification of aquifer potential in Karanganyar city by using vertical electrical sounding method

    Science.gov (United States)

    Marfuatik, L.; Koesuma, S.; Legowo, B.; Darsono

    2018-03-01

    The identification of aquifer was done by using Vertical Electrical Sounding (VES) method. This research aims to identify potential and depth of the aquifers. The locations of surveys are at ten points,namely TS1 (Alastuwo), TS2 (Wonorejo), TS3 (Kaling), TS4 (Kaling), TS5 (Buran), TS6 (Wonolopo), TS7 (Buran), TS8 (Ngijo), TS9 (Jati), and TS10 (Suruhkalang) where all located in Karanganyar regency. The survey path is about 500-600 meters length which can penetrate current to 100 – 200 meters in depth. The measurement was done by using OYO Mc OHM-EL Model 2119C. Geoelectrical data analysis was processed using Progress version 3.0 Software. The interpretation result shows that the locations of research area are included in Lawu-volcano rock formation which is breccias, lava, and tuff as the constituents. We found that unconfined aquifer in all of locations with different depth and confined aquifer just 7 locations start from 25.04 meters.

  7. Risk assessment of chemicals in food and diet: Hazard identification by methods of animal-based toxicology

    DEFF Research Database (Denmark)

    Barlow, S. M.; Greig, J. B.; Bridges, J. W.

    2002-01-01

    the current state of the science of risk assessment of chemicals in food and diet, by consideration of the four stages of risk assessment, that is. hazard identification. hazard characterisation, exposure assessment and risk characterisation. The contribution of animal-based methods in toxicology to hazard......, on hazard identification for food chemicals, such as new measurement techniques, the use of transgenic animals, assessment of hormone balance and the possibilities for conducting studies in which common human diseases have been modelled. is also considered. (C) 2002 ILSI. Published by Elsevier Science Ltd....... All rights reserved....

  8. Direct identification of microorganisms from positive blood cultures by MALDI-TOF MS using an in-house saponin method.

    Science.gov (United States)

    Yonetani, Shota; Ohnishi, Hiroaki; Ohkusu, Kiyofumi; Matsumoto, Tetsuya; Watanabe, Takashi

    2016-11-01

    Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a fast and reliable method for the identification of bacteria. A MALDI Sepsityper kit is generally used to prepare samples obtained directly from culture bottles. However, the relatively high cost of this kit is a major obstacle to introducing this method into routine clinical use. In this study, the accuracies of three different preparation methods for rapid direct identification of bacteria from positive blood culture bottles by MALDI-TOF MS analysis were compared. In total, 195 positive bottles were included in this study. Overall, 78.5%, 68.7%, and 76.4% of bacteria were correctly identified to the genus level (score ≥1.7) directly from positive blood cultures using the Sepsityper, centrifugation, and saponin methods, respectively. The identification rates using the Sepsityper and saponin methods were significantly higher than that using the centrifugation method (Sepsityper vs. centrifugation, pdirectly from blood culture bottles, and could be a less expensive alternative to the Sepsityper method. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  9. A photometric high-throughput method for identification of electrochemically active bacteria using a WO3 nanocluster probe.

    Science.gov (United States)

    Yuan, Shi-Jie; He, Hui; Sheng, Guo-Ping; Chen, Jie-Jie; Tong, Zhong-Hua; Cheng, Yuan-Yuan; Li, Wen-Wei; Lin, Zhi-Qi; Zhang, Feng; Yu, Han-Qing

    2013-01-01

    Electrochemically active bacteria (EAB) are ubiquitous in environment and have important application in the fields of biogeochemistry, environment, microbiology and bioenergy. However, rapid and sensitive methods for EAB identification and evaluation of their extracellular electron transfer ability are still lacking. Herein we report a novel photometric method for visual detection of EAB by using an electrochromic material, WO(3) nanoclusters, as the probe. This method allowed a rapid identification of EAB within 5 min and a quantitative evaluation of their extracellular electron transfer abilities. In addition, it was also successfully applied for isolation of EAB from environmental samples. Attributed to its rapidness, high reliability, easy operation and low cost, this method has high potential for practical implementation of EAB detection and investigations.

  10. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions.

    Science.gov (United States)

    Zuñiga, Cristal; Li, Chien-Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C; McConnell, Brian O; Long, Christopher P; Knoshaug, Eric P; Guarnieri, Michael T; Antoniewicz, Maciek R; Betenbaugh, Michael J; Zengler, Karsten

    2016-09-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. © 2016 American Society of Plant Biologists. All rights reserved.

  11. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions1

    Science.gov (United States)

    Zuñiga, Cristal; Li, Chien-Ting; Zielinski, Daniel C.; Guarnieri, Michael T.; Antoniewicz, Maciek R.; Zengler, Karsten

    2016-01-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244

  12. GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula.

    Science.gov (United States)

    Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling; Wang, Yun

    2018-01-01

    The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components.

  13. Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method

    Directory of Open Access Journals (Sweden)

    Yang Zhang

    2016-10-01

    Full Text Available Ultra-wideband (UWB radar has been widely used for detecting human physiological signals (respiration, movement, etc. in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc., the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.

  14. Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method.

    Science.gov (United States)

    Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang

    2016-10-27

    Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.

  15. Evaluation of three sample preparation methods for the direct identification of bacteria in positive blood cultures by MALDI-TOF

    OpenAIRE

    Tanner, Hannah; Evans, Jason T.; Gossain, Savita; Hussain, Abid

    2017-01-01

    Background Patient mortality is significantly reduced by rapid identification of bacteria from sterile sites. MALDI-TOF can identify bacteria directly from positive blood cultures and multiple sample preparation methods are available. We evaluated three sample preparation methods and two MALDI-TOF score cut-off values. Positive blood culture bottles with organisms present in Gram stains were prospectively analysed by MALDI-TOF. Three lysis reagents (Saponin, SDS, and SepsiTyper lysis bufer) w...

  16. The constitutive compatibility method for identification of material parameters based on full-field measurements

    KAUST Repository

    Moussawi, Ali

    2013-10-01

    We revisit here the concept of the constitutive relation error for the identification of elastic material parameters based on image correlation. An additional concept, so called constitutive compatibility of stress, is introduced defining a subspace of the classical space of statically admissible stresses. The key idea is to define stresses as compatible with the observed deformation field through the chosen class of constitutive equation. This makes possible the uncoupling of the identification of stress from the identification of the material parameters. As a result, the global cost of the identification is strongly reduced. This uncoupling also leads to parametrized solutions in cases where the solution is non-unique as demonstrated on 2D numerical examples. © 2013 Elsevier B.V.

  17. A Roadmap of Risk Diagnostic Methods: Developing an Integrated View of Risk Identification and Analysis Techniques

    National Research Council Canada - National Science Library

    Williams, Ray; Ambrose, Kate; Bentrem, Laura

    2004-01-01

    ...), which is envisioned to be a comprehensive reference tool for risk identification and analysis (RI AND A) techniques. Program Managers (PMs) responsible for developing or acquiring software-intensive systems typically identify risks in different ways...

  18. The constitutive compatibility method for identification of material parameters based on full-field measurements

    KAUST Repository

    Moussawi, Ali; Lubineau, Gilles; Florentin, É ric; Blaysat, Benoî t

    2013-01-01

    We revisit here the concept of the constitutive relation error for the identification of elastic material parameters based on image correlation. An additional concept, so called constitutive compatibility of stress, is introduced defining a subspace

  19. Screening method for Staphylococcus aureus identification in subclinical bovine mastitis from dairy farms

    Directory of Open Access Journals (Sweden)

    Natapol Pumipuntu

    2017-07-01

    Full Text Available Background: Staphylococcus aureus is one of the most important contagious bacteria causing subclinical bovine mastitis. This bacterial infection is commonly identified by determine the pathogen in bovine milk samples through conventional technique including coagulase test. However, this test has several disadvantages as low sensitivity, risk of biohazard, cost expensive, and limited preparation especially in local area. Aim: Aim of this study was to compare and assess the screening method, Mannitol fermentation test (Mannitol salt agar [MSA], and deoxyribonuclease (DNase test, for S. aureus identification in milk samples. Materials and Methods: A total of 224 subclinical bovine mastitis milk samples were collected from four provinces of Thailand and determined S. aureus using conventional method and also subjected to the screening test, MSA and DNase test. The sensitivity, specificity, positive predictive value (PPV, and negative predictive value (NPV among both tests were analyzed and compared to the tube coagulase test (TCT, as reference method. Immunological test by latex agglutination and molecular assay by determined spa gene were also used to identify and differentiate S. aureus. Results: A total of 130 staphylococci were isolated by selective media, Gram-stain, and catalase test. The number of S. aureus which identified using TCT, MSA and DNase test were 32, 102, and 74 isolates, respectively. All TCT results were correlated to results of latex agglutination and spa gene which were 32 S. aureus. MSA showed 100% sensitivity, 28.57% specificity, 31.37% PPV, and 100% NPV, whereas DNase showed 53.13% sensitivity, 41.84% specificity, 22.97% PPV, and 73.21% NPV. DNase test showed higher specificity value than MSA but the test presented 26.79% false negative results whereas no false-negative result from MSA when comparing to TCT. Conclusion: MSA had a tendency to be a good preference for screening S. aureus because of its high sensitivity and

  20. Methods for using a biometric parameter in the identification of persons

    Science.gov (United States)

    Hively, Lee M [Philadelphia, TN

    2011-11-22

    Brain waves are used as a biometric parameter to provide for authentication and identification of personnel. The brain waves are sampled using EEG equipment and are processed using phase-space distribution functions to compare digital signature data from enrollment of authorized individuals to data taken from a test subject to determine if the data from the test subject matches the signature data to a degree to support positive identification.

  1. Next-generation sequencing library preparation method for identification of RNA viruses on the Ion Torrent Sequencing Platform.

    Science.gov (United States)

    Chen, Guiqian; Qiu, Yuan; Zhuang, Qingye; Wang, Suchun; Wang, Tong; Chen, Jiming; Wang, Kaicheng

    2018-05-09

    Next generation sequencing (NGS) is a powerful tool for the characterization, discovery, and molecular identification of RNA viruses. There were multiple NGS library preparation methods published for strand-specific RNA-seq, but some methods are not suitable for identifying and characterizing RNA viruses. In this study, we report a NGS library preparation method to identify RNA viruses using the Ion Torrent PGM platform. The NGS sequencing adapters were directly inserted into the sequencing library through reverse transcription and polymerase chain reaction, without fragmentation and ligation of nucleic acids. The results show that this method is simple to perform, able to identify multiple species of RNA viruses in clinical samples.

  2. Accuracy-enhanced constitutive parameter identification using virtual fields method and special stereo-digital image correlation

    Science.gov (United States)

    Zhang, Zhongya; Pan, Bing; Grédiac, Michel; Song, Weidong

    2018-04-01

    The virtual fields method (VFM) is generally used with two-dimensional digital image correlation (2D-DIC) or grid method (GM) for identifying constitutive parameters. However, when small out-of-plane translation/rotation occurs to the test specimen, 2D-DIC and GM are prone to yield inaccurate measurements, which further lessen the accuracy of the parameter identification using VFM. In this work, an easy-to-implement but effective "special" stereo-DIC (SS-DIC) method is proposed for accuracy-enhanced VFM identification. The SS-DIC can not only deliver accurate deformation measurement without being affected by unavoidable out-of-plane movement/rotation of a test specimen, but can also ensure evenly distributed calculation data in space, which leads to simple data processing. Based on the accurate kinematics fields with evenly distributed measured points determined by SS-DIC method, constitutive parameters can be identified by VFM with enhanced accuracy. Uniaxial tensile tests of a perforated aluminum plate and pure shear tests of a prismatic aluminum specimen verified the effectiveness and accuracy of the proposed method. Experimental results show that the constitutive parameters identified by VFM using SS-DIC are more accurate and stable than those identified by VFM using 2D-DIC. It is suggested that the proposed SS-DIC can be used as a standard measuring tool for mechanical identification using VFM.

  3. Evaluation of three sample preparation methods for the direct identification of bacteria in positive blood cultures by MALDI-TOF.

    Science.gov (United States)

    Tanner, Hannah; Evans, Jason T; Gossain, Savita; Hussain, Abid

    2017-01-18

    Patient mortality is significantly reduced by rapid identification of bacteria from sterile sites. MALDI-TOF can identify bacteria directly from positive blood cultures and multiple sample preparation methods are available. We evaluated three sample preparation methods and two MALDI-TOF score cut-off values. Positive blood culture bottles with organisms present in Gram stains were prospectively analysed by MALDI-TOF. Three lysis reagents (Saponin, SDS, and SepsiTyper lysis bufer) were applied to each positive culture followed by centrifugation, washing and protein extraction steps. Methods were compared using the McNemar test and 16S rDNA sequencing was used to assess discordant results. In 144 monomicrobial cultures, using ≥2.000 as the cut-off value, species level identifications were obtained from 69/144 (48%) samples using Saponin, 86/144 (60%) using SDS, and 91/144 (63%) using SepsiTyper. The difference between SDS and SepsiTyper was not statistically significant (P = 0.228). Differences between Saponin and the other two reagents were significant (P direct MALDI-TOF identification were observed in monomicrobial cultures. In 32 polymicrobial cultures, MALDI-TOF identified one organism in 34-75% of samples depending on the method. This study demonstrates two inexpensive in-house detergent lysis methods are non-inferior to a commercial kit for analysis of positive blood cultures by direct MALDI-TOF in a clinical diagnostic microbiology laboratory.

  4. Comparison of four methods for rapid identification of Staphylococcus aureus directly from BACTEC 9240 blood culture system

    Directory of Open Access Journals (Sweden)

    N S Ozen

    2011-01-01

    Full Text Available Purpose: Differentiation of Staphylococcus aureus (S. aureus from coagulase-negative staphylococci is very important in blood stream infections. Identification of S. aureus and coagulase-negative staphylococci (CoNS from blood cultures takes generally 18-24 h after positive signaling on continuously monitored automated blood culture system. In this study, we evaluated the performance of tube coagulase test (TCT, slide agglutination test (Dry Spot Staphytect Plus, conventional polymerase chain reaction (PCR and LightCycler Staphylococcus MGrade kit directly from blood culture bottles to achieve rapid identification of S. aureus by using the BACTEC 9240 blood culture system. Materials and Methods: A total of 129 BACTEC 9240 bottles growing gram-positive cocci suggesting Staphylococci were tested directly from blood culture broths (BCBs with TCT, Dry Spot Staphytect Plus, conventional PCR and LightCycler Staphylococcus MGrade kit for rapid identification of S. aureus. Results: The sensitivities of the tests were 99, 68, 99 and 100%, respectively. Conclusion: Our results suggested that 2 h TCT was found to be simple and inexpensive method for the rapid identification of S. aureus directly from positive blood cultures.

  5. Independent review of inappropriate identification, storage and treatment methods of polychlorinated biphenyl waste streams

    International Nuclear Information System (INIS)

    1997-07-01

    The purpose of the review was to evaluate incidents involving the inappropriate identification, storage, and treatment methods associated with polychlorinated biphenyl (PCB) waste streams originating from the V-tank system at the Test Area North (TAN). The team was instructed to perform a comprehensive review of Lockheed Martin Idaho Technologies Company (LMITCO's) compliance programs related to these incidents to assess the adequacy and effectiveness of the management program in all respects including: adequacy of the waste management program in meeting all LMITCO requirements and regulations; adequacy of policies, plans, and procedures in addressing and implementing all federal and state requirements and regulations; and compliance status of LMITCO, LMITCO contract team members, and LMITCO contract/team member subcontractor personnel with established PCB management policies, plans, and procedures. The V-Tanks are part of an intermediate waste disposal system and are located at the Technical Support Facility (TSF) at TAN at the Idaho National Engineering and Environmental Laboratory (INEEL). The IRT evaluated how a waste was characterized, managed, and information was documented; however, they did not take control of wastes or ensure followup was performed on all waste streams that may have been generated from the V-Tanks. The team has also subsequently learned that the Environmental Restoration (ER) program is revising the plans for the decontamination and decommissioning of the intermediate waste disposal system based on new information listed and PCB wastes. The team has not reviewed those in-process changes. The source of PCB in the V-Tank is suspected to be a spill of hydraulic fluid in 1968

  6. Use of the radiochemical method for identification of seized nuclear material - container

    International Nuclear Information System (INIS)

    Rosskopfova, O.; Matel, L.; Rajec, P.; Dobias, M.

    2003-01-01

    Analysis of the nuclear material of the seized illicit trafficking container was performed in the laboratory LARCHA. The container was professionally taken apart in the hot cell of HUMA-LAB APEKO. The compact core of container with mass of 36.00 kg was separated and analysed in the LARCHA laboratory. The results of alpha spectrometry proved that the core of container was made of depleted uranium. A suspicious container was seized, that was believed to be used for transportation of radioactive and nuclear materials. Container, according to Slovak Law, was transported to a Civil defence and police started with expertise analysis. On the basis of previous results, it was assumed that the core of the container was made of a nuclear material. The container was cut inside a hot cell to separate parts at HUMA-Lab Kosice and individual parts were prepared for analyses. From shape and type of the detained container it was assumed that the core of the container was made of depleted uranium and suspected cut pieces were sent to the accredited laboratory LARCHA Bratislava for isotope analysis. Samples from different parts of the container were analysed by using HPGe gamma. The results of gamma spectrometry proved the presence of Co-60, Cs-137 and U-235 with values 11.8 Bq, 5.6 Bq a 3.8 Bq respectively. On the basis of measured results it was calculated mass content (%) of uranium isotopes in samples. It was concluded that: - container is composed of different parts, which are made from steel, lead and uranium; - the wipe tests proved the presence of radionuclides of Cs-137 and Co-60; - the core of the container is made of depleted uranium; - chosen methods, which were used proved that are suitable for analysis and identification of nuclear materials. (authors)

  7. A method for managing re-identification risk from small geographic areas in Canada

    Directory of Open Access Journals (Sweden)

    Neisa Angelica

    2010-04-01

    Full Text Available Abstract Background A common disclosure control practice for health datasets is to identify small geographic areas and either suppress records from these small areas or aggregate them into larger ones. A recent study provided a method for deciding when an area is too small based on the uniqueness criterion. The uniqueness criterion stipulates that an the area is no longer too small when the proportion of unique individuals on the relevant variables (the quasi-identifiers approaches zero. However, using a uniqueness value of zero is quite a stringent threshold, and is only suitable when the risks from data disclosure are quite high. Other uniqueness thresholds that have been proposed for health data are 5% and 20%. Methods We estimated uniqueness for urban Forward Sortation Areas (FSAs by using the 2001 long form Canadian census data representing 20% of the population. We then constructed two logistic regression models to predict when the uniqueness is greater than the 5% and 20% thresholds, and validated their predictive accuracy using 10-fold cross-validation. Predictor variables included the population size of the FSA and the maximum number of possible values on the quasi-identifiers (the number of equivalence classes. Results All model parameters were significant and the models had very high prediction accuracy, with specificity above 0.9, and sensitivity at 0.87 and 0.74 for the 5% and 20% threshold models respectively. The application of the models was illustrated with an analysis of the Ontario newborn registry and an emergency department dataset. At the higher thresholds considerably fewer records compared to the 0% threshold would be considered to be in small areas and therefore undergo disclosure control actions. We have also included concrete guidance for data custodians in deciding which one of the three uniqueness thresholds to use (0%, 5%, 20%, depending on the mitigating controls that the data recipients have in place, the

  8. Testing isotopic labeling with [¹³C₆]glucose as a method of advanced glycation sites identification.

    Science.gov (United States)

    Kielmas, Martyna; Kijewska, Monika; Stefanowicz, Piotr; Szewczuk, Zbigniew

    2012-12-01

    The Maillard reaction occurring between reducing sugars and reactive amino groups of biomolecules leads to the formation of a heterogeneous mixture of compounds: early, intermediate, and advanced glycation end products (AGEs). These compounds could be markers of certain diseases and of the premature aging process. Detection of Amadori products can be performed by various methods, including MS/MS techniques and affinity chromatography on immobilized boronic acid. However, the diversity of the structures of AGEs makes detection of these compounds more difficult. The aim of this study was to test a new method of AGE identification based on isotope (13)C labeling. The model protein (hen egg lysozyme) was modified with an equimolar mixture of [(12)C(6)]glucose and [(13)C(6)]glucose and then subjected to reduction of the disulfide bridges followed by tryptic hydrolysis. The digest obtained was analyzed by LC-MS. The glycation products were identified on the basis of characteristic isotopic patterns resulting from the use of isotopically labeled glucose. This method allowed identification of 38 early Maillard reaction products and five different structures of the end glycation products. This isotopic labeling technique combined with LC-MS is a sensitive method for identification of advanced glycation end products even if their chemical structure is unknown. Copyright © 2012 Elsevier Inc. All rights reserved.

  9. New analytical method for fast nuclide identification in mobile in-situ gamma spectrometers; Neue analytische Methode zur schnellen Nuklididentifikation in mobilen in-situ Gammaspektrometern

    Energy Technology Data Exchange (ETDEWEB)

    Streil, T.; Oeser, V.; Wagner, W. [SARAD GmbH, Dresden (Germany); Doerfel, H.R. [IDEA System GmbH, Karlsruhe (Germany)

    2016-07-01

    Demolition and accidents of nuclear reactors or terroristic attacks may lead to large-area contamination with radionuclides. A suitable mobile measurement equipment should allow a quick overview about the extent of contamination. Recent methods apply for nuclide identification either time-consuming peak-fitting methods inclusive background correction or the so-called trapezoid method determining so-called regions of interest (ROI). Since the nuclide vector is often known, this information can be used as a starting point for the nuclide identification. The presented method uses dynamic smoothing of the registered energy spectrum in accordance with the detector resolution. In this way, noise is effectively suppressed without substantial degradation of the detector resolution. The statistically prepared spectrum is then two-fold differentiated. This provides the peak positions and the two turning points of the found peaks. Nuclide identification is possible using the peak positions, and with the peak and turning point positions and the corresponding values of the spectrum, on may calculate the area of an assumed Gausz distribution without considering the in any case present continuous background. With a 2 x 2'' NaI-detector, as being used in the NucScout device, one can identify a {sup 137}Cs-activity of 200 Bq/kg at distance of 1 m in 10 s. Combined with adapted calibration methods, the algorithm for nuclide identification implemented in the NucScout is also applicable for other geometries, e. g., using a Marinelli cup in the LabScout device.

  10. UNITE: a database providing web-based methods for the molecular identification of ectomycorrhizal fungi

    DEFF Research Database (Denmark)

    Köljalg, U.; Larsson, K.H.; Abarenkov, K.

    2005-01-01

    Identification of ectomycorrhizal (ECM) fungi is often achieved through comparisons of ribosomal DNA internal transcribed spacer (ITS) sequences with accessioned sequences deposited in public databases. A major problem encountered is that annotation of the sequences in these databases is not always....... At present UNITE contains 758 ITS sequences from 455 species and 67 genera of ECM fungi. •  UNITE can be searched by taxon name, via sequence similarity using blastn, and via phylogenetic sequence identification using galaxie. Following implementation, galaxie performs a phylogenetic analysis of the query...... sequence after alignment either to pre-existing generic alignments, or to matches retrieved from a blast search on the UNITE data. It should be noted that the current version of UNITE is dedicated to the reliable identification of ECM fungi. •  The UNITE database is accessible through the URL http://unite.zbi.ee...

  11. Zymography Methods to Simultaneously Analyze Superoxide Dismutase and Catalase Activities: Novel Application for Yeast Species Identification.

    Science.gov (United States)

    Gamero-Sandemetrio, Esther; Gómez-Pastor, Rocío; Matallana, Emilia

    2017-01-01

    We provide an optimized protocol for a double staining technique to analyze superoxide dismutase enzymatic isoforms Cu-Zn SOD (Sod1) and Mn-SOD (Sod2) and catalase in the same polyacrylamide gel. The use of NaCN, which specifically inhibits yeast Sod1 isoform, allows the analysis of Sod2 isoform while the use of H 2 O 2 allows the analysis of catalase. The identification of a different zymography profiling of SOD and catalase isoforms in different yeast species allowed us to propose this technique as a novel yeast identification and classification strategy.

  12. Development of the method of aggregation to determine the current storage area using computer vision and radiofrequency identification

    Science.gov (United States)

    Astafiev, A.; Orlov, A.; Privezencev, D.

    2018-01-01

    The article is devoted to the development of technology and software for the construction of positioning and control systems in industrial plants based on aggregation to determine the current storage area using computer vision and radiofrequency identification. It describes the developed of the project of hardware for industrial products positioning system in the territory of a plant on the basis of radio-frequency grid. It describes the development of the project of hardware for industrial products positioning system in the plant on the basis of computer vision methods. It describes the development of the method of aggregation to determine the current storage area using computer vision and radiofrequency identification. Experimental studies in laboratory and production conditions have been conducted and described in the article.

  13. Species identification in meat products: A new screening method based on high resolution melting analysis of cyt b gene.

    Science.gov (United States)

    Lopez-Oceja, A; Nuñez, C; Baeta, M; Gamarra, D; de Pancorbo, M M

    2017-12-15

    Meat adulteration by substitution with lower value products and/or mislabeling involves economic, health, quality and socio-religious issues. Therefore, identification and traceability of meat species has become an important subject to detect possible fraudulent practices. In the present study the development of a high resolution melt (HRM) screening method for the identification of eight common meat species is reported. Samples from Bos taurus, Ovis aries, Sus scrofa domestica, Equus caballus, Oryctolagus cuniculus, Gallus gallus domesticus, Meleagris gallopavo and Coturnix coturnix were analyzed through the amplification of a 148 bp fragment from the cyt b gene with a universal primer pair in HRM analyses. Melting profiles from each species, as well as from several DNA mixtures of these species and blind samples, allowed a successful species differentiation. The results demonstrated that the HRM method here proposed is a fast, reliable, and low-cost screening technique. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Innovative methods for the identification of predictive biomarker signatures in oncology: Application to bevacizumab

    Directory of Open Access Journals (Sweden)

    Paul Delmar

    2017-03-01

    Full Text Available Current methods for subgroup analyses of data collected from randomized clinical trials (RCTs may lead to false-positives from multiple testing, lack power to detect moderate but clinically meaningful differences, or be too simplistic in characterizing patients who may benefit from treatment. Herein, we present a general procedure based on a set of newly developed statistical methods for the identification and evaluation of complex multivariate predictors of treatment effect. Furthermore, we implemented this procedure to identify a subgroup of patients who may receive the largest benefit from bevacizumab treatment using a panel of 10 biomarkers measured at baseline in patients enrolled on two RCTs investigating bevacizumab in metastatic breast cancer. Data were collected from patients with human epidermal growth factor receptor 2 (HER2-negative (AVADO and HER2-positive (AVEREL metastatic breast cancer. We first developed a classification rule based on an estimated individual scoring system, using data from the AVADO study only. The classification rule takes into consideration a panel of biomarkers, including vascular endothelial growth factor (VEGF-A. We then classified the patients in the independent AVEREL study into patient groups according to “promising” or “not-promising” treatment benefit based on this rule and conducted a statistical analysis within these subgroups to compute point estimates, confidence intervals, and p-values for treatment effect and its interaction. In the group with promising treatment benefit in the AVEREL study, the estimated hazard ratio of bevacizumab versus placebo for progression-free survival was 0.687 (95% confidence interval [CI]: 0.462–1.024, p = 0.065, while in the not-promising group the hazard ratio (HR was 1.152 (95% CI: 0.526–2.524, p = 0.723. Using the median level of VEGF-A from the AVEREL study to divide the study population, then the HR becomes 0.711 (95% CI: 0.435–1.163, p = 0

  15. Container for waste, identification code reading device thereof, method and system for controlling waste by using them

    International Nuclear Information System (INIS)

    Kikuchi, Takashi; Yoshida, Tomiji; Omote, Tatsuyuki.

    1991-01-01

    In the conventional method of controlling waste containers by labels attached thereto, the data relevant to wastes contained in the waste containers are limited. Further, if the label should be peeled off, there is a possibility that the wastes therein can no more be identified. Then, in the present invention, an identification plate is previously attached, to which mechanically readable codes or visually readable letters or numerical figures are written. Then, the identification codes can be read in a remote control manner at high speed and high reliability and the waste containers can be managed only by the identification codes of the containers. Further, the identification codes on the container are made so as to be free from aging degradation, thereby enabling to manage waste containers for long time storage. With such a constitution, since data can be inputted from an input terminal and a great amount of data such as concerning the source of wastes can be managed collectively on a software, the data can be managed easily. (T.M.)

  16. Comparison of four methods for rapid identification of Staphylococcus aureus directly from BACTEC 9240 blood culture system.

    Science.gov (United States)

    Ozen, N S; Ogunc, D; Mutlu, D; Ongut, G; Baysan, B O; Gunseren, F

    2011-01-01

    Differentiation of Staphylococcus aureus (S. aureus) from coagulase-negative staphylococci is very important in blood stream infections. Identification of S. aureus and coagulase-negative staphylococci (CoNS) from blood cultures takes generally 18-24 h after positive signaling on continuously monitored automated blood culture system. In this study, we evaluated the performance of tube coagulase test (TCT), slide agglutination test (Dry Spot Staphytect Plus), conventional polymerase chain reaction (PCR) and LightCycler Staphylococcus MGrade kit directly from blood culture bottles to achieve rapid identification of S. aureus by using the BACTEC 9240 blood culture system. A total of 129 BACTEC 9240 bottles growing gram-positive cocci suggesting Staphylococci were tested directly from blood culture broths (BCBs) with TCT, Dry Spot Staphytect Plus, conventional PCR and LightCycler Staphylococcus MGrade kit for rapid identification of S. aureus. The sensitivities of the tests were 99, 68, 99 and 100%, respectively. Our results suggested that 2 h TCT was found to be simple and inexpensive method for the rapid identification of S. aureus directly from positive blood cultures.

  17. An novel identification method of the environmental risk sources for surface water pollution accidents in chemical industrial parks.

    Science.gov (United States)

    Peng, Jianfeng; Song, Yonghui; Yuan, Peng; Xiao, Shuhu; Han, Lu

    2013-07-01

    The chemical industry is a major source of various pollution accidents. Improving the management level of risk sources for pollution accidents has become an urgent demand for most industrialized countries. In pollution accidents, the released chemicals harm the receptors to some extent depending on their sensitivity or susceptibility. Therefore, identifying the potential risk sources from such a large number of chemical enterprises has become pressingly urgent. Based on the simulation of the whole accident process, a novel and expandable identification method for risk sources causing water pollution accidents is presented. The newly developed approach, by analyzing and stimulating the whole process of a pollution accident between sources and receptors, can be applied to identify risk sources, especially on the nationwide scale. Three major types of losses, such as social, economic and ecological losses, were normalized, analyzed and used for overall consequence modeling. A specific case study area, located in a chemical industry park (CIP) along the Yangtze River in Jiangsu Province, China, was selected to test the potential of the identification method. The results showed that there were four risk sources for pollution accidents in this CIP. Aniline leakage in the HS Chemical Plant would lead to the most serious impact on the surrounding water environment. This potential accident would severely damage the ecosystem up to 3.8 km downstream of Yangtze River, and lead to pollution over a distance stretching to 73.7 km downstream. The proposed method is easily extended to the nationwide identification of potential risk sources.

  18. A single-laboratory validated method for the generation of DNA barcodes for the identification of fish for regulatory compliance.

    Science.gov (United States)

    Handy, Sara M; Deeds, Jonathan R; Ivanova, Natalia V; Hebert, Paul D N; Hanner, Robert H; Ormos, Andrea; Weigt, Lee A; Moore, Michelle M; Yancy, Haile F

    2011-01-01

    The U.S. Food and Drug Administration is responsible for ensuring that the nation's food supply is safe and accurately labeled. This task is particularly challenging in the case of seafood where a large variety of species are marketed, most of this commodity is imported, and processed product is difficult to identify using traditional morphological methods. Reliable species identification is critical for both foodborne illness investigations and for prevention of deceptive practices, such as those where species are intentionally mislabeled to circumvent import restrictions or for resale as species of higher value. New methods that allow accurate and rapid species identifications are needed, but any new methods to be used for regulatory compliance must be both standardized and adequately validated. "DNA barcoding" is a process by which species discriminations are achieved through the use of short, standardized gene fragments. For animals, a fragment (655 base pairs starting near the 5' end) of the cytochrome c oxidase subunit 1 mitochondrial gene has been shown to provide reliable species level discrimination in most cases. We provide here a protocol with single-laboratory validation for the generation of DNA barcodes suitable for the identification of seafood products, specifically fish, in a manner that is suitable for FDA regulatory use.

  19. A Novel Method for Lithium-Ion Battery Online Parameter Identification Based on Variable Forgetting Factor Recursive Least Squares

    Directory of Open Access Journals (Sweden)

    Zizhou Lao

    2018-05-01

    Full Text Available For model-based state of charge (SOC estimation methods, the battery model parameters change with temperature, SOC, and so forth, causing the estimation error to increase. Constantly updating model parameters during battery operation, also known as online parameter identification, can effectively solve this problem. In this paper, a lithium-ion battery is modeled using the Thevenin model. A variable forgetting factor (VFF strategy is introduced to improve forgetting factor recursive least squares (FFRLS to variable forgetting factor recursive least squares (VFF-RLS. A novel method based on VFF-RLS for the online identification of the Thevenin model is proposed. Experiments verified that VFF-RLS gives more stable online parameter identification results than FFRLS. Combined with an unscented Kalman filter (UKF algorithm, a joint algorithm named VFF-RLS-UKF is proposed for SOC estimation. In a variable-temperature environment, a battery SOC estimation experiment was performed using the joint algorithm. The average error of the SOC estimation was as low as 0.595% in some experiments. Experiments showed that VFF-RLS can effectively track the changes in model parameters. The joint algorithm improved the SOC estimation accuracy compared to the method with the fixed forgetting factor.

  20. An identification method of orbit responses rooting in vibration analysis of rotor during touchdowns of active magnetic bearings

    Science.gov (United States)

    Liu, Tao; Lyu, Mindong; Wang, Zixi; Yan, Shaoze

    2018-02-01

    Identification of orbit responses can make the active protection operation more easily realize for active magnetic bearings (AMB) in case of touchdowns. This paper presents an identification method of the orbit responses rooting on signal processing of rotor displacements during touchdowns. The recognition method consists of two major steps. Firstly, the combined rub and bouncing is distinguished from the other orbit responses by the mathematical expectation of axis displacements of the rotor. Because when the combined rub and bouncing occurs, the rotor of AMB will not be always close to the touchdown bearings (TDB). Secondly, we recognize the pendulum vibration and the full rub by the Fourier spectrum of displacement in horizontal direction, as the frequency characteristics of the two responses are different. The principle of the whole identification algorithm is illustrated by two sets of signal generated by a dynamic model of the specific rotor-TDB system. The universality of the method is validated by other four sets of signal. Besides, the adaptability of noise is also tested by adding white noises with different strengths, and the result is promising. As the mathematical expectation and Discrete Fourier transform are major calculations of the algorithm, the calculation quantity of the algorithm is low, so it is fast, easily realized and embedded in the AMB controller, which has an important engineering value for the protection of AMBs during touchdowns.