WorldWideScience

Sample records for hybrid computer identification

  1. The study of hybrid model identification,computation analysis and fault location for nonlinear dynamic circuits and systems

    Institute of Scientific and Technical Information of China (English)

    XIE Hong; HE Yi-gang; ZENG Guan-da

    2006-01-01

    This paper presents the hybrid model identification for a class of nonlinear circuits and systems via a combination of the block-pulse function transform with the Volterra series.After discussing the method to establish the hybrid model and introducing the hybrid model identification,a set of relative formulas are derived for calculating the hybrid model and computing the Volterra series solution of nonlinear dynamic circuits and systems.In order to significantly reduce the computation cost for fault location,the paper presents a new fault diagnosis method based on multiple preset models that can be realized online.An example of identification simulation and fault diagnosis are given.Results show that the method has high accuracy and efficiency for fault location of nonlinear dynamic circuits and systems.

  2. Analog and hybrid computing

    CERN Document Server

    Hyndman, D E

    2013-01-01

    Analog and Hybrid Computing focuses on the operations of analog and hybrid computers. The book first outlines the history of computing devices that influenced the creation of analog and digital computers. The types of problems to be solved on computers, computing systems, and digital computers are discussed. The text looks at the theory and operation of electronic analog computers, including linear and non-linear computing units and use of analog computers as operational amplifiers. The monograph examines the preparation of problems to be deciphered on computers. Flow diagrams, methods of ampl

  3. Computer system identification

    OpenAIRE

    Lesjak, Borut

    2008-01-01

    The concept of computer system identity in computer science bears just as much importance as does the identity of an individual in a human society. Nevertheless, the identity of a computer system is incomparably harder to determine, because there is no standard system of identification we could use and, moreover, a computer system during its life-time is quite indefinite, since all of its regular and necessary hardware and software upgrades soon make it almost unrecognizable: after a number o...

  4. Hybrid cluster identification

    Science.gov (United States)

    Martín-Herrero, J.

    2004-10-01

    I present a hybrid method for the labelling of clusters in two-dimensional lattices, which combines the recursive approach with iterative scanning to reduce the stack size required by the pure recursive technique, while keeping its benefits: single pass and straightforward cluster characterization and percolation detection parallel to the labelling. While the capacity to hold the entire lattice in memory is usually regarded as the major constraint for the applicability of the recursive technique, the required stack size is the real limiting factor. Resorting to recursion only for the transverse direction greatly reduces the recursion depth and therefore the required stack. It also enhances the overall performance of the recursive technique, as is shown by results on a set of uniform random binary lattices and on a set of samples of the Ising model. I also show how this technique may replace the recursive technique in Wolff's cluster algorithm, decreasing the risk of stack overflow and increasing its speed, and the Hoshen-Kopelman algorithm in the Swendsen-Wang cluster algorithm, allowing effortless characterization during generation of the samples and increasing its speed.

  5. Hybridity in Embedded Computing Systems

    Institute of Scientific and Technical Information of China (English)

    虞慧群; 孙永强

    1996-01-01

    An embedded system is a system that computer is used as a component in a larger device.In this paper,we study hybridity in embedded systems and present an interval based temporal logic to express and reason about hybrid properties of such kind of systems.

  6. Advanced Hybrid Computer Systems. Software Technology.

    Science.gov (United States)

    This software technology final report evaluates advances made in Advanced Hybrid Computer System software technology . The report describes what...automatic patching software is available as well as which analog/hybrid programming languages would be most feasible for the Advanced Hybrid Computer...compiler software . The problem of how software would interface with the hybrid system is also presented.

  7. Hybrid soft computing approaches research and applications

    CERN Document Server

    Dutta, Paramartha; Chakraborty, Susanta

    2016-01-01

    The book provides a platform for dealing with the flaws and failings of the soft computing paradigm through different manifestations. The different chapters highlight the necessity of the hybrid soft computing methodology in general with emphasis on several application perspectives in particular. Typical examples include (a) Study of Economic Load Dispatch by Various Hybrid Optimization Techniques, (b) An Application of Color Magnetic Resonance Brain Image Segmentation by ParaOptiMUSIG activation Function, (c) Hybrid Rough-PSO Approach in Remote Sensing Imagery Analysis,  (d) A Study and Analysis of Hybrid Intelligent Techniques for Breast Cancer Detection using Breast Thermograms, and (e) Hybridization of 2D-3D Images for Human Face Recognition. The elaborate findings of the chapters enhance the exhibition of the hybrid soft computing paradigm in the field of intelligent computing.

  8. Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology

    Directory of Open Access Journals (Sweden)

    Jieru Zhang

    2016-01-01

    Full Text Available Cancerlectins are cancer-related proteins that function as lectins. They have been identified through computational identification techniques, but these techniques have sometimes failed to identify proteins because of sequence diversity among the cancerlectins. Advanced machine learning identification methods, such as support vector machine and basic sequence features (n-gram, have also been used to identify cancerlectins. In this study, various protein fingerprint features and advanced classifiers, including ensemble learning techniques, were utilized to identify this group of proteins. We improved the prediction accuracy of the original feature extraction methods and classification algorithms by more than 10% on average. Our work provides a basis for the computational identification of cancerlectins and reveals the power of hybrid machine learning techniques in computational proteomics.

  9. Checkpointing for a hybrid computing node

    Energy Technology Data Exchange (ETDEWEB)

    Cher, Chen-Yong

    2016-03-08

    According to an aspect, a method for checkpointing in a hybrid computing node includes executing a task in a processing accelerator of the hybrid computing node. A checkpoint is created in a local memory of the processing accelerator. The checkpoint includes state data to restart execution of the task in the processing accelerator upon a restart operation. Execution of the task is resumed in the processing accelerator after creating the checkpoint. The state data of the checkpoint are transferred from the processing accelerator to a main processor of the hybrid computing node while the processing accelerator is executing the task.

  10. Reachability computation for hybrid systems with Ariadne

    NARCIS (Netherlands)

    L. Benvenuti; D. Bresolin; A. Casagrande; P.J. Collins (Pieter); A. Ferrari; E. Mazzi; T. Villa; A. Sangiovanni-Vincentelli

    2008-01-01

    htmlabstractAriadne is an in-progress open environment to design algorithms for computing with hybrid automata, that relies on a rigorous computable analysis theory to represent geometric objects, in order to achieve provable approximation bounds along the computations. In this paper we discuss the

  11. Computer code for intraply hybrid composite design

    Science.gov (United States)

    Chamis, C. C.; Sinclair, J. H.

    1981-01-01

    A computer program has been developed and is described herein for intraply hybrid composite design (INHYD). The program includes several composite micromechanics theories, intraply hybrid composite theories and a hygrothermomechanical theory. These theories provide INHYD with considerable flexibility and capability which the user can exercise through several available options. Key features and capabilities of INHYD are illustrated through selected samples.

  12. Universal blind quantum computation for hybrid system

    Science.gov (United States)

    Huang, He-Liang; Bao, Wan-Su; Li, Tan; Li, Feng-Guang; Fu, Xiang-Qun; Zhang, Shuo; Zhang, Hai-Long; Wang, Xiang

    2017-08-01

    As progress on the development of building quantum computer continues to advance, first-generation practical quantum computers will be available for ordinary users in the cloud style similar to IBM's Quantum Experience nowadays. Clients can remotely access the quantum servers using some simple devices. In such a situation, it is of prime importance to keep the security of the client's information. Blind quantum computation protocols enable a client with limited quantum technology to delegate her quantum computation to a quantum server without leaking any privacy. To date, blind quantum computation has been considered only for an individual quantum system. However, practical universal quantum computer is likely to be a hybrid system. Here, we take the first step to construct a framework of blind quantum computation for the hybrid system, which provides a more feasible way for scalable blind quantum computation.

  13. MODEL IDENTIFICATION AND COMPUTER ALGEBRA.

    Science.gov (United States)

    Bollen, Kenneth A; Bauldry, Shawn

    2010-10-07

    Multiequation models that contain observed or latent variables are common in the social sciences. To determine whether unique parameter values exist for such models, one needs to assess model identification. In practice analysts rely on empirical checks that evaluate the singularity of the information matrix evaluated at sample estimates of parameters. The discrepancy between estimates and population values, the limitations of numerical assessments of ranks, and the difference between local and global identification make this practice less than perfect. In this paper we outline how to use computer algebra systems (CAS) to determine the local and global identification of multiequation models with or without latent variables. We demonstrate a symbolic CAS approach to local identification and develop a CAS approach to obtain explicit algebraic solutions for each of the model parameters. We illustrate the procedures with several examples, including a new proof of the identification of a model for handling missing data using auxiliary variables. We present an identification procedure for Structural Equation Models that makes use of CAS and that is a useful complement to current methods.

  14. Hybrid Systems: Computation and Control.

    Science.gov (United States)

    2007-11-02

    elbow) and a pinned first joint (shoul- der) (see Figure 2); it is termed an underactuated system since it is a mechanical system with fewer...Montreal, PQ, Canada, 1998. [10] M. W. Spong. Partial feedback linearization of underactuated mechanical systems . In Proceedings, IROS󈨢, pages 314-321...control mechanism and search for optimal combinations of control variables. Besides the nonlinear and hybrid nature of powertrain systems , hardware

  15. Hybrid Workflow Policy Management for Heart Disease Identification

    CERN Document Server

    Kim, Dong-Hyun; Youn, Chan-Hyun

    2010-01-01

    As science technology grows, medical application is becoming more complex to solve the physiological problems within expected time. Workflow management systems (WMS) in Grid computing are promising solution to solve the sophisticated problem such as genomic analysis, drug discovery, disease identification, etc. Although existing WMS can provide basic management functionality in Grid environment, consideration of user requirements such as performance, reliability and interaction with user is missing. In this paper, we propose hybrid workflow management system for heart disease identification and discuss how to guarantee different user requirements according to user SLA. The proposed system is applied to Physio-Grid e-health platform to identify human heart disease with ECG analysis and Virtual Heart Simulation (VHS) workflow applications.

  16. Adaptation and hybridization in computational intelligence

    CERN Document Server

    Jr, Iztok

    2015-01-01

      This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background information and provides some theoretical foundation tackling the CI domain, the second part deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI. This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are confronted with solving the optimization, modeling and simulation problems. It covers the recent advances in CI that encompass Nature-inspired algorithms, like Artificial Neural networks, Evolutionary Algorithms and Swarm Intelligence –based algorithms.  

  17. Lyapunov exponents computation for hybrid neurons.

    Science.gov (United States)

    Bizzarri, Federico; Brambilla, Angelo; Gajani, Giancarlo Storti

    2013-10-01

    Lyapunov exponents are a basic and powerful tool to characterise the long-term behaviour of dynamical systems. The computation of Lyapunov exponents for continuous time dynamical systems is straightforward whenever they are ruled by vector fields that are sufficiently smooth to admit a variational model. Hybrid neurons do not belong to this wide class of systems since they are intrinsically non-smooth owing to the impact and sometimes switching model used to describe the integrate-and-fire (I&F) mechanism. In this paper we show how a variational model can be defined also for this class of neurons by resorting to saltation matrices. This extension allows the computation of Lyapunov exponent spectrum of hybrid neurons and of networks made up of them through a standard numerical approach even in the case of neurons firing synchronously.

  18. Hybrid Parallel Computation of Integration in GRACE

    CERN Document Server

    Yuasa, F; Kawabata, S; Perret-Gallix, D; Itakura, K; Hotta, Y; Okuda, M; Yuasa, Fukuko; Ishikawa, Tadashi; Kawabata, Setsuya; Perret-Gallix, Denis; Itakura, Kazuhiro; Hotta, Yukihiko; Okuda, Motoi

    2000-01-01

    With an integrated software package {\\tt GRACE}, it is possible to generate Feynman diagrams, calculate the total cross section and generate physics events automatically. We outline the hybrid method of parallel computation of the multi-dimensional integration of {\\tt GRACE}. We used {\\tt MPI} (Message Passing Interface) as the parallel library and, to improve the performance we embedded the mechanism of the dynamic load balancing. The reduction rate of the practical execution time was studied.

  19. Hybrid Nanoelectronics: Future of Computer Technology

    Institute of Scientific and Technical Information of China (English)

    Wei Wang; Ming Liu; Andrew Hsu

    2006-01-01

    Nanotechnology may well prove to be the 21st century's new wave of scientific knowledge that transforms people's lives. Nanotechnology research activities are booming around the globe. This article reviews the recent progresses made on nanoelectronic research in US and China, and introduces several novel hybrid solutions specifically useful for future computer technology. These exciting new directions will lead to many future inventions, and have a huge impact to research communities and industries.

  20. Accelerating Climate Simulations Through Hybrid Computing

    Science.gov (United States)

    Zhou, Shujia; Sinno, Scott; Cruz, Carlos; Purcell, Mark

    2009-01-01

    Unconventional multi-core processors (e.g., IBM Cell B/E and NYIDIDA GPU) have emerged as accelerators in climate simulation. However, climate models typically run on parallel computers with conventional processors (e.g., Intel and AMD) using MPI. Connecting accelerators to this architecture efficiently and easily becomes a critical issue. When using MPI for connection, we identified two challenges: (1) identical MPI implementation is required in both systems, and; (2) existing MPI code must be modified to accommodate the accelerators. In response, we have extended and deployed IBM Dynamic Application Virtualization (DAV) in a hybrid computing prototype system (one blade with two Intel quad-core processors, two IBM QS22 Cell blades, connected with Infiniband), allowing for seamlessly offloading compute-intensive functions to remote, heterogeneous accelerators in a scalable, load-balanced manner. Currently, a climate solar radiation model running with multiple MPI processes has been offloaded to multiple Cell blades with approx.10% network overhead.

  1. Spoken Language Identification Using Hybrid Feature Extraction Methods

    CERN Document Server

    Kumar, Pawan; Mishra, A N; Chandra, Mahesh

    2010-01-01

    This paper introduces and motivates the use of hybrid robust feature extraction technique for spoken language identification (LID) system. The speech recognizers use a parametric form of a signal to get the most important distinguishable features of speech signal for recognition task. In this paper Mel-frequency cepstral coefficients (MFCC), Perceptual linear prediction coefficients (PLP) along with two hybrid features are used for language Identification. Two hybrid features, Bark Frequency Cepstral Coefficients (BFCC) and Revised Perceptual Linear Prediction Coefficients (RPLP) were obtained from combination of MFCC and PLP. Two different classifiers, Vector Quantization (VQ) with Dynamic Time Warping (DTW) and Gaussian Mixture Model (GMM) were used for classification. The experiment shows better identification rate using hybrid feature extraction techniques compared to conventional feature extraction methods.BFCC has shown better performance than MFCC with both classifiers. RPLP along with GMM has shown be...

  2. Modelling of data uncertainties on hybrid computers

    Energy Technology Data Exchange (ETDEWEB)

    Schneider, Anke (ed.)

    2016-06-15

    The codes d{sup 3}f and r{sup 3}t are well established for modelling density-driven flow and nuclide transport in the far field of repositories for hazardous material in deep geological formations. They are applicable in porous media as well as in fractured rock or mudstone, for modelling salt- and heat transport as well as a free groundwater surface. Development of the basic framework of d{sup 3}f and r{sup 3}t had begun more than 20 years ago. Since that time significant advancements took place in the requirements for safety assessment as well as for computer hardware development. The period of safety assessment for a repository of high-level radioactive waste was extended to 1 million years, and the complexity of the models is steadily growing. Concurrently, the demands on accuracy increase. Additionally, model and parameter uncertainties become more and more important for an increased understanding of prediction reliability. All this leads to a growing demand for computational power that requires a considerable software speed-up. An effective way to achieve this is the use of modern, hybrid computer architectures which requires basically the set-up of new data structures and a corresponding code revision but offers a potential speed-up by several orders of magnitude. The original codes d{sup 3}f and r{sup 3}t were applications of the software platform UG /BAS 94/ whose development had begun in the early nineteennineties. However, UG had recently been advanced to the C++ based, substantially revised version UG4 /VOG 13/. To benefit also in the future from state-of-the-art numerical algorithms and to use hybrid computer architectures, the codes d{sup 3}f and r{sup 3}t were transferred to this new code platform. Making use of the fact that coupling between different sets of equations is natively supported in UG4, d{sup 3}f and r{sup 3}t were combined to one conjoint code d{sup 3}f++. A direct estimation of uncertainties for complex groundwater flow models with the

  3. 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...

  4. Hybrid Computational Model for High-Altitude Aeroassist Vehicles Project

    Data.gov (United States)

    National Aeronautics and Space Administration — A hybrid continuum/noncontinuum computational model will be developed for analyzing the aerodynamics and heating on aeroassist vehicles. Unique features of this...

  5. Digital Potentiometer for Hybrid Computer EAI 680-PDP-8/I

    DEFF Research Database (Denmark)

    Højberg, Kristian Søe; Olsen, Jens V.

    1974-01-01

    In this article a description is given of a 12 bit digital potentiometer for hybrid computer application. The system is composed of standard building blocks. Emphasis is laid on the development problems met and the problem solutions developed.......In this article a description is given of a 12 bit digital potentiometer for hybrid computer application. The system is composed of standard building blocks. Emphasis is laid on the development problems met and the problem solutions developed....

  6. Hybrid system for computing reachable workspaces for redundant manipulators

    Science.gov (United States)

    Alameldin, Tarek K.; Sobh, Tarek M.

    1991-03-01

    An efficient computation of 3D workspaces for redundant manipulators is based on a " hybrid" a!- gorithm between direct kinematics and screw theory. Direct kinematics enjoys low computational cost but needs edge detection algorithms when workspace boundaries are needed. Screw theory has exponential computational cost per workspace point but does not need edge detection. Screw theory allows computing workspace points in prespecified directions while direct kinematics does not. Applications of the algorithm are discussed.

  7. Microcantilver-based DNA hybridization sensors for Salmonella identification

    Directory of Open Access Journals (Sweden)

    Carlo Ricciardi

    2012-02-01

    Full Text Available The detection of pathogenic microorganisms in foods remains a challenging since the safety of foodstuffs has to be ensured by the food producing companies. Conventional methods for the detection and identification of bacteria mainly rely on specific microbiological and biochemical identification. Biomolecular methods, are commonly used as a support for traditional techniques, thanks to their high sensitivity, specificity and not excessive costs. However, new methods like biosensors for example, can be an exciting alternative to the more traditional tecniques for the detection of pathogens in food. In this study we report Salmonella enterica serotype Enteritidis DNA detection through a novel class of label-free biosensors: microcantilevers (MCs. In general, MCs can operate as a microbalance and is used to detect the mass of the entities anchored to the cantilever surface using the decrease in the resonant frequency. We use DNA hybridization as model reaction system and for this reason, specific single stranded probe DNA of the pathogen and three different DNA targets (single-stranded complementary DNA, PCR product and serial dilutions of DNA extracted from S. Enteritidis strains were applied. Two protocols were reported in order to allow the probe immobilization on cantilever surface: i MC surface was functionalized with 3-aminopropyltriethoxysilane and glutaraldehyde and an amino-modified DNA probe was used; ii gold-coated sensors and thiolated DNA probes were used in order to generate a covalent bonding (Th-Au. For the first one, measures after hybridization with the PCR product showed related frequency shift 10 times higher than hybridization with complementary probe and detectable signals were obtained at the concentrations of 103 and 106 cfu/mL after hybridization with bacterial DNA. There are currently optimizations of the second protocol, where preliminary results have shown to be more uniform and therefore more precise within each of the

  8. Generalised Computability and Applications to Hybrid Systems

    DEFF Research Database (Denmark)

    Korovina, Margarita V.; Kudinov, Oleg V.

    2001-01-01

    We investigate the concept of generalised computability of operators and functionals defined on the set of continuous functions, firstly introduced in [9]. By working in the reals, with equality and without equality, we study properties of generalised computable operators and functionals. Also we...

  9. Wireless Hybrid Identification and Sensing Platform for Equipment Recovery (WHISPER) Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Advanced Systems & Technologies proposed WHISPER (Wireless Hybrid Identification and Sensing Platform for Equipment Recovery) solution to NASA's need for...

  10. Cost Optimization Using Hybrid Evolutionary Algorithm in Cloud Computing

    Directory of Open Access Journals (Sweden)

    B. Kavitha

    2015-07-01

    Full Text Available The main aim of this research is to design the hybrid evolutionary algorithm for minimizing multiple problems of dynamic resource allocation in cloud computing. The resource allocation is one of the big problems in the distributed systems when the client wants to decrease the cost for the resource allocation for their task. In order to assign the resource for the task, the client must consider the monetary cost and computational cost. Allocation of resources by considering those two costs is difficult. To solve this problem in this study, we make the main task of client into many subtasks and we allocate resources for each subtask instead of selecting the single resource for the main task. The allocation of resources for the each subtask is completed through our proposed hybrid optimization algorithm. Here, we hybrid the Binary Particle Swarm Optimization (BPSO and Binary Cuckoo Search algorithm (BCSO by considering monetary cost and computational cost which helps to minimize the cost of the client. Finally, the experimentation is carried out and our proposed hybrid algorithm is compared with BPSO and BCSO algorithms. Also we proved the efficiency of our proposed hybrid optimization algorithm.

  11. Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing.

    Science.gov (United States)

    Kim, Hyunjun; Lee, Junhwa; Ahn, Eunjong; Cho, Soojin; Shin, Myoungsu; Sim, Sung-Han

    2017-09-07

    Crack assessment is an essential process in the maintenance of concrete structures. In general, concrete cracks are inspected by manual visual observation of the surface, which is intrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming, expensive, and often unsafe when inaccessible structural members are to be assessed. Unmanned aerial vehicle (UAV) technologies combined with digital image processing have recently been applied to crack assessment to overcome the drawbacks of manual visual inspection. However, identification of crack information in terms of width and length has not been fully explored in the UAV-based applications, because of the absence of distance measurement and tailored image processing. This paper presents a crack identification strategy that combines hybrid image processing with UAV technology. Equipped with a camera, an ultrasonic displacement sensor, and a WiFi module, the system provides the image of cracks and the associated working distance from a target structure on demand. The obtained information is subsequently processed by hybrid image binarization to estimate the crack width accurately while minimizing the loss of the crack length information. The proposed system has shown to successfully measure cracks thicker than 0.1 mm with the maximum length estimation error of 7.3%.

  12. Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing

    Directory of Open Access Journals (Sweden)

    Hyunjun Kim

    2017-09-01

    Full Text Available Crack assessment is an essential process in the maintenance of concrete structures. In general, concrete cracks are inspected by manual visual observation of the surface, which is intrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming, expensive, and often unsafe when inaccessible structural members are to be assessed. Unmanned aerial vehicle (UAV technologies combined with digital image processing have recently been applied to crack assessment to overcome the drawbacks of manual visual inspection. However, identification of crack information in terms of width and length has not been fully explored in the UAV-based applications, because of the absence of distance measurement and tailored image processing. This paper presents a crack identification strategy that combines hybrid image processing with UAV technology. Equipped with a camera, an ultrasonic displacement sensor, and a WiFi module, the system provides the image of cracks and the associated working distance from a target structure on demand. The obtained information is subsequently processed by hybrid image binarization to estimate the crack width accurately while minimizing the loss of the crack length information. The proposed system has shown to successfully measure cracks thicker than 0.1 mm with the maximum length estimation error of 7.3%.

  13. Load flow computations in hybrid transmission - distributed power systems

    NARCIS (Netherlands)

    Wobbes, E.D.; Lahaye, D.J.P.

    2013-01-01

    We interconnect transmission and distribution power systems and perform load flow computations in the hybrid network. In the largest example we managed to build, fifty copies of a distribution network consisting of fifteen nodes is connected to the UCTE study model, resulting in a system consisting

  14. Mixed model approaches for the identification of QTLs within a maize hybrid breeding program.

    Science.gov (United States)

    van Eeuwijk, Fred A; Boer, Martin; Totir, L Radu; Bink, Marco; Wright, Deanne; Winkler, Christopher R; Podlich, Dean; Boldman, Keith; Baumgarten, Andy; Smalley, Matt; Arbelbide, Martin; ter Braak, Cajo J F; Cooper, Mark

    2010-01-01

    Two outlines for mixed model based approaches to quantitative trait locus (QTL) mapping in existing maize hybrid selection programs are presented: a restricted maximum likelihood (REML) and a Bayesian Markov Chain Monte Carlo (MCMC) approach. The methods use the in-silico-mapping procedure developed by Parisseaux and Bernardo (2004) as a starting point. The original single-point approach is extended to a multi-point approach that facilitates interval mapping procedures. For computational and conceptual reasons, we partition the full set of relationships from founders to parents of hybrids into two types of relations by defining so-called intermediate founders. QTL effects are defined in terms of those intermediate founders. Marker based identity by descent relationships between intermediate founders define structuring matrices for the QTL effects that change along the genome. The dimension of the vector of QTL effects is reduced by the fact that there are fewer intermediate founders than parents. Furthermore, additional reduction in the number of QTL effects follows from the identification of founder groups by various algorithms. As a result, we obtain a powerful mixed model based statistical framework to identify QTLs in genetic backgrounds relevant to the elite germplasm of a commercial breeding program. The identification of such QTLs will provide the foundation for effective marker assisted and genome wide selection strategies. Analyses of an example data set show that QTLs are primarily identified in different heterotic groups and point to complementation of additive QTL effects as an important factor in hybrid performance.

  15. Hybrid Algorithm for Optimal Load Sharing in Grid Computing

    Directory of Open Access Journals (Sweden)

    A. Krishnan

    2012-01-01

    Full Text Available Problem statement: Grid Computing is the fast growing industry, which shares the resources in the organization in an effective manner. Resource sharing requires more optimized algorithmic structure, otherwise the waiting time and response time are increased and the resource utilization is reduced. Approach: In order to avoid such reduction in the performances of the grid system, an optimal resource sharing algorithm is required. In recent days, many load sharing technique are proposed, which provides feasibility but there are many critical issues are still present in these algorithms. Results: In this study a hybrid algorithm for optimization of load sharing is proposed. The hybrid algorithm contains two components which are Hash Table (HT and Distributed Hash Table (DHT. Conclusion: The results of the proposed study show that the hybrid algorithm will optimize the task than existing systems.

  16. Use of a hybrid computer in engineering-seismology research

    Science.gov (United States)

    Park, R.B.; Hays, W.W.

    1977-01-01

    A hybrid computer is an important tool in the seismological research conducted by the U.S. Geological Survey in support of the Energy Research and Development Administration nuclear explosion testing program at the Nevada Test Site and the U.S. Geological Survey Earthquake Hazard Reduction Program. The hybrid computer system, which employs both digital and analog computational techniques, facilitates efficient seismic data processing. Standard data processing operations include: (1) preview of dubbed magnetic tapes of data; (2) correction of data for instrument response; (3) derivation of displacement and acceleration time histories from velocity recordings; (4) extraction of peak-amplitude data; (5) digitization of time histories; (6) rotation of instrumental axes; (7) derivation of response spectra; and (8) derivation of relative transfer functions between recording sites. Catalog of time histories and response spectra of ground motion from nuclear explosions and earthquakes that have been processed by the hybrid computer are used in the Earthquake Hazard Research Program to evaluate the effects of source, propagation path, and site effects on recorded ground motion; to assess seismic risk; to predict system response; and to solve system design problems.

  17. A hybrid computational grid architecture for comparative genomics.

    Science.gov (United States)

    Singh, Aarti; Chen, Chen; Liu, Weiguo; Mitchell, Wayne; Schmidt, Bertil

    2008-03-01

    Comparative genomics provides a powerful tool for studying evolutionary changes among organisms, helping to identify genes that are conserved among species, as well as genes that give each organism its unique characteristics. However, the huge datasets involved makes this approach impractical on traditional computer architectures leading to prohibitively long runtimes. In this paper, we present a new computational grid architecture based on a hybrid computing model to significantly accelerate comparative genomics applications. The hybrid computing model consists of two types of parallelism: coarse grained and fine grained. The coarse-grained parallelism uses a volunteer computing infrastructure for job distribution, while the fine-grained parallelism uses commodity computer graphics hardware for fast sequence alignment. We present the deployment and evaluation of this approach on our grid test bed for the all-against-all comparison of microbial genomes. The results of this comparison are then used by phenotype--genotype explorer (PheGee). PheGee is a new tool that nominates candidate genes responsible for a given phenotype.

  18. A Hybrid Brain-Computer Interface-Based Mail Client

    Directory of Open Access Journals (Sweden)

    Tianyou Yu

    2013-01-01

    Full Text Available Brain-computer interface-based communication plays an important role in brain-computer interface (BCI applications; electronic mail is one of the most common communication tools. In this study, we propose a hybrid BCI-based mail client that implements electronic mail communication by means of real-time classification of multimodal features extracted from scalp electroencephalography (EEG. With this BCI mail client, users can receive, read, write, and attach files to their mail. Using a BCI mouse that utilizes hybrid brain signals, that is, motor imagery and P300 potential, the user can select and activate the function keys and links on the mail client graphical user interface (GUI. An adaptive P300 speller is employed for text input. The system has been tested with 6 subjects, and the experimental results validate the efficacy of the proposed method.

  19. Computational simulation of intermingled-fiber hybrid composite behavior

    Science.gov (United States)

    Mital, Subodh K.; Chamis, Christos C.

    1992-01-01

    Three-dimensional finite-element analysis and a micromechanics based computer code ICAN (Integrated Composite Analyzer) are used to predict the composite properties and microstresses of a unidirectional graphite/epoxy primary composite with varying percentages of S-glass fibers used as hydridizing fibers at a total fiber volume of 0.54. The three-dimensional finite-element model used in the analyses consists of a group of nine fibers, all unidirectional, in a three-by-three unit cell array. There is generally good agreement between the composite properties and microstresses obtained from both methods. The results indicate that the finite-element methods and the micromechanics equations embedded in the ICAN computer code can be used to obtain the properties of intermingled fiber hybrid composites needed for the analysis/design of hybrid composite structures. However, the finite-element model should be big enough to be able to simulate the conditions assumed in the micromechanics equations.

  20. Hybrid Workflow Policy Management for Heart Disease Identification

    Directory of Open Access Journals (Sweden)

    Dong-Hyun Kim

    2009-12-01

    Full Text Available As science technology grows, medical application is becoming more complex to solve the physiological problems within expected time. Workflow management systems (WMS in Grid computing are promisingsolution to solve the sophisticated problem such as genomic analysis, drug discovery, disease identification, etc. Although existing WMS can provide basic management functionality in Grid environment, consideration of user requirements such as performance, reliability and interaction with user is missing. In this paper, we proposehybrid workflow management system for heart disease identification and discuss how to guarantee different user requirements according to user SLA. The proposed system is applied to Physio-Grid e-health platform to identify human heart disease with ECG analysis and Virtual Heart Simulation (VHS workflow applications.

  1. Accelerating Climate and Weather Simulations through Hybrid Computing

    Science.gov (United States)

    Zhou, Shujia; Cruz, Carlos; Duffy, Daniel; Tucker, Robert; Purcell, Mark

    2011-01-01

    Unconventional multi- and many-core processors (e.g. IBM (R) Cell B.E.(TM) and NVIDIA (R) GPU) have emerged as effective accelerators in trial climate and weather simulations. Yet these climate and weather models typically run on parallel computers with conventional processors (e.g. Intel, AMD, and IBM) using Message Passing Interface. To address challenges involved in efficiently and easily connecting accelerators to parallel computers, we investigated using IBM's Dynamic Application Virtualization (TM) (IBM DAV) software in a prototype hybrid computing system with representative climate and weather model components. The hybrid system comprises two Intel blades and two IBM QS22 Cell B.E. blades, connected with both InfiniBand(R) (IB) and 1-Gigabit Ethernet. The system significantly accelerates a solar radiation model component by offloading compute-intensive calculations to the Cell blades. Systematic tests show that IBM DAV can seamlessly offload compute-intensive calculations from Intel blades to Cell B.E. blades in a scalable, load-balanced manner. However, noticeable communication overhead was observed, mainly due to IP over the IB protocol. Full utilization of IB Sockets Direct Protocol and the lower latency production version of IBM DAV will reduce this overhead.

  2. Parametric identification of a servo-hydraulic actuator for real-time hybrid simulation

    Science.gov (United States)

    Qian, Yili; Ou, Ge; Maghareh, Amin; Dyke, Shirley J.

    2014-10-01

    In a typical Real-time Hybrid Simulation (RTHS) setup, servo-hydraulic actuators serve as interfaces between the computational and physical substructures. Time delay introduced by actuator dynamics and complex interaction between the actuators and the specimen has detrimental effects on the stability and accuracy of RTHS. Therefore, a good understanding of servo-hydraulic actuator dynamics is a prerequisite for controller design and computational simulation of RTHS. This paper presents an easy-to-use parametric identification procedure for RTHS users to obtain re-useable actuator parameters for a range of payloads. The critical parameters in a linearized servo-hydraulic actuator model are optimally obtained from genetic algorithms (GA) based on experimental data collected from various specimen mass/stiffness combinations loaded to the target actuator. The actuator parameters demonstrate convincing convergence trend in GA. A key feature of this parametric modeling procedure is its re-usability under different testing scenarios, including different specimen mechanical properties and actuator inner-loop control gains. The models match well with experimental results. The benefit of the proposed parametric identification procedure has been demonstrated by (1) designing an H∞ controller with the identified system parameters that significantly improves RTHS performance; and (2) establishing an analysis and computational simulation of a servo-hydraulic system that help researchers interpret system instability and improve design of experiments.

  3. Evaluation of a Compact Hybrid Brain-Computer Interface System

    Directory of Open Access Journals (Sweden)

    Jaeyoung Shin

    2017-01-01

    Full Text Available We realized a compact hybrid brain-computer interface (BCI system by integrating a portable near-infrared spectroscopy (NIRS device with an economical electroencephalography (EEG system. The NIRS array was located on the subjects’ forehead, covering the prefrontal area. The EEG electrodes were distributed over the frontal, motor/temporal, and parietal areas. The experimental paradigm involved a Stroop word-picture matching test in combination with mental arithmetic (MA and baseline (BL tasks, in which the subjects were asked to perform either MA or BL in response to congruent or incongruent conditions, respectively. We compared the classification accuracies of each of the modalities (NIRS or EEG with that of the hybrid system. We showed that the hybrid system outperforms the unimodal EEG and NIRS systems by 6.2% and 2.5%, respectively. Since the proposed hybrid system is based on portable platforms, it is not confined to a laboratory environment and has the potential to be used in real-life situations, such as in neurorehabilitation.

  4. Energy efficient hybrid computing systems using spin devices

    Science.gov (United States)

    Sharad, Mrigank

    Emerging spin-devices like magnetic tunnel junctions (MTJ's), spin-valves and domain wall magnets (DWM) have opened new avenues for spin-based logic design. This work explored potential computing applications which can exploit such devices for higher energy-efficiency and performance. The proposed applications involve hybrid design schemes, where charge-based devices supplement the spin-devices, to gain large benefits at the system level. As an example, lateral spin valves (LSV) involve switching of nanomagnets using spin-polarized current injection through a metallic channel such as Cu. Such spin-torque based devices possess several interesting properties that can be exploited for ultra-low power computation. Analog characteristic of spin current facilitate non-Boolean computation like majority evaluation that can be used to model a neuron. The magneto-metallic neurons can operate at ultra-low terminal voltage of ˜20mV, thereby resulting in small computation power. Moreover, since nano-magnets inherently act as memory elements, these devices can facilitate integration of logic and memory in interesting ways. The spin based neurons can be integrated with CMOS and other emerging devices leading to different classes of neuromorphic/non-Von-Neumann architectures. The spin-based designs involve `mixed-mode' processing and hence can provide very compact and ultra-low energy solutions for complex computation blocks, both digital as well as analog. Such low-power, hybrid designs can be suitable for various data processing applications like cognitive computing, associative memory, and currentmode on-chip global interconnects. Simulation results for these applications based on device-circuit co-simulation framework predict more than ˜100x improvement in computation energy as compared to state of the art CMOS design, for optimal spin-device parameters.

  5. CSP: A Multifaceted Hybrid Architecture for Space Computing

    Science.gov (United States)

    Rudolph, Dylan; Wilson, Christopher; Stewart, Jacob; Gauvin, Patrick; George, Alan; Lam, Herman; Crum, Gary Alex; Wirthlin, Mike; Wilson, Alex; Stoddard, Aaron

    2014-01-01

    Research on the CHREC Space Processor (CSP) takes a multifaceted hybrid approach to embedded space computing. Working closely with the NASA Goddard SpaceCube team, researchers at the National Science Foundation (NSF) Center for High-Performance Reconfigurable Computing (CHREC) at the University of Florida and Brigham Young University are developing hybrid space computers that feature an innovative combination of three technologies: commercial-off-the-shelf (COTS) devices, radiation-hardened (RadHard) devices, and fault-tolerant computing. Modern COTS processors provide the utmost in performance and energy-efficiency but are susceptible to ionizing radiation in space, whereas RadHard processors are virtually immune to this radiation but are more expensive, larger, less energy-efficient, and generations behind in speed and functionality. By featuring COTS devices to perform the critical data processing, supported by simpler RadHard devices that monitor and manage the COTS devices, and augmented with novel uses of fault-tolerant hardware, software, information, and networking within and between COTS devices, the resulting system can maximize performance and reliability while minimizing energy consumption and cost. NASA Goddard has adopted the CSP concept and technology with plans underway to feature flight-ready CSP boards on two upcoming space missions.

  6. Autonomic Management of Application Workflows on Hybrid Computing Infrastructure

    Directory of Open Access Journals (Sweden)

    Hyunjoo Kim

    2011-01-01

    Full Text Available In this paper, we present a programming and runtime framework that enables the autonomic management of complex application workflows on hybrid computing infrastructures. The framework is designed to address system and application heterogeneity and dynamics to ensure that application objectives and constraints are satisfied. The need for such autonomic system and application management is becoming critical as computing infrastructures become increasingly heterogeneous, integrating different classes of resources from high-end HPC systems to commodity clusters and clouds. For example, the framework presented in this paper can be used to provision the appropriate mix of resources based on application requirements and constraints. The framework also monitors the system/application state and adapts the application and/or resources to respond to changing requirements or environment. To demonstrate the operation of the framework and to evaluate its ability, we employ a workflow used to characterize an oil reservoir executing on a hybrid infrastructure composed of TeraGrid nodes and Amazon EC2 instances of various types. Specifically, we show how different applications objectives such as acceleration, conservation and resilience can be effectively achieved while satisfying deadline and budget constraints, using an appropriate mix of dynamically provisioned resources. Our evaluations also demonstrate that public clouds can be used to complement and reinforce the scheduling and usage of traditional high performance computing infrastructure.

  7. Tensile force identification in cable-stayed structures: Hybrid system identification algorithm and experimental verification

    Energy Technology Data Exchange (ETDEWEB)

    Noh, Myung Hyun [POSCO, Incheon (Korea, Republic of); Hu, Jong Wan [Incheon National University, Incheon (Korea, Republic of)

    2014-11-15

    In this study, we investigate a method to detect tensile forces in cable-stayed structures using the combined sensitivity updating method and the advanced hybrid microgenetic algorithm. The proposed method allows us not only to avoid the trap of minimum at initial searching stage but also to find their final solutions in better numerical efficiency. The validity of the technique is numerically verified using a set of dynamic data obtained from a simulation of the cable model modeled using the finite element method. Then, the hybrid algorithm is applied to vibrating sagged cables in the laboratory scale test. The results obtained are in good agreement with the semi-analytical solutions and experimental results reported by other investigators. The results indicate that the new method is computationally efficient in characterizing the tensile force variation for cable-stayed structures.

  8. Reduced-size kernel models for nonlinear hybrid system identification.

    Science.gov (United States)

    Le, Van Luong; Bloch, Grard; Lauer, Fabien

    2011-12-01

    This brief paper focuses on the identification of nonlinear hybrid dynamical systems, i.e., systems switching between multiple nonlinear dynamical behaviors. Thus the aim is to learn an ensemble of submodels from a single set of input-output data in a regression setting with no prior knowledge on the grouping of the data points into similar behaviors. To be able to approximate arbitrary nonlinearities, kernel submodels are considered. However, in order to maintain efficiency when applying the method to large data sets, a preprocessing step is required in order to fix the submodel sizes and limit the number of optimization variables. This brief paper proposes four approaches, respectively inspired by the fixed-size least-squares support vector machines, the feature vector selection method, the kernel principal component regression and a modification of the latter, in order to deal with this issue and build sparse kernel submodels. These are compared in numerical experiments, which show that the proposed approach achieves the simultaneous classification of data points and approximation of the nonlinear behaviors in an efficient and accurate manner.

  9. Computational hybrid anthropometric paediatric phantom library for internal radiation dosimetry

    Science.gov (United States)

    Xie, Tianwu; Kuster, Niels; Zaidi, Habib

    2017-04-01

    Hybrid computational phantoms combine voxel-based and simplified equation-based modelling approaches to provide unique advantages and more realism for the construction of anthropomorphic models. In this work, a methodology and C++ code are developed to generate hybrid computational phantoms covering statistical distributions of body morphometry in the paediatric population. The paediatric phantoms of the Virtual Population Series (IT’IS Foundation, Switzerland) were modified to match target anthropometric parameters, including body mass, body length, standing height and sitting height/stature ratio, determined from reference databases of the National Centre for Health Statistics and the National Health and Nutrition Examination Survey. The phantoms were selected as representative anchor phantoms for the newborn, 1, 2, 5, 10 and 15 years-old children, and were subsequently remodelled to create 1100 female and male phantoms with 10th, 25th, 50th, 75th and 90th body morphometries. Evaluation was performed qualitatively using 3D visualization and quantitatively by analysing internal organ masses. Overall, the newly generated phantoms appear very reasonable and representative of the main characteristics of the paediatric population at various ages and for different genders, body sizes and sitting stature ratios. The mass of internal organs increases with height and body mass. The comparison of organ masses of the heart, kidney, liver, lung and spleen with published autopsy and ICRP reference data for children demonstrated that they follow the same trend when correlated with age. The constructed hybrid computational phantom library opens up the prospect of comprehensive radiation dosimetry calculations and risk assessment for the paediatric population of different age groups and diverse anthropometric parameters.

  10. A Review of Hybrid Brain-Computer Interface Systems

    Directory of Open Access Journals (Sweden)

    Setare Amiri

    2013-01-01

    Full Text Available Increasing number of research activities and different types of studies in brain-computer interface (BCI systems show potential in this young research area. Research teams have studied features of different data acquisition techniques, brain activity patterns, feature extraction techniques, methods of classifications, and many other aspects of a BCI system. However, conventional BCIs have not become totally applicable, due to the lack of high accuracy, reliability, low information transfer rate, and user acceptability. A new approach to create a more reliable BCI that takes advantage of each system is to combine two or more BCI systems with different brain activity patterns or different input signal sources. This type of BCI, called hybrid BCI, may reduce disadvantages of each conventional BCI system. In addition, hybrid BCIs may create more applications and possibly increase the accuracy and the information transfer rate. However, the type of BCIs and their combinations should be considered carefully. In this paper, after introducing several types of BCIs and their combinations, we review and discuss hybrid BCIs, different possibilities to combine them, and their advantages and disadvantages.

  11. Creating New Germplasm by Distant Hybridization in Stone Fruits:Ⅱ-Embryo Rescue and Hybrid Identification Between Plum and Apricot

    Institute of Scientific and Technical Information of China (English)

    YANG Hong-hua; CHEN Xue-sen; FENG Bao-chun; LIU Huan-fang; ZHENG Zhou

    2004-01-01

    Embryo abortion stage and rescue system of hybrids were studied in the distant hybridization between plum and apricot. Identification of the hybrids was also made. The results showed:(1)Embryo abortion started from three weeks after pollination.(2)The germination and growth of embryos were different at different growth stages,which could germinate and grow with PF value> 0.5,but failed with PF value< 0.5. In embryo rescue system of hybrids,the best germination and differentiation medium was MS + 6-BA 2 mg L-1+ IAA 0.3 mg L-1,the rate of germination and differentiation reached up to 80%,bud induction and multiplication medium was MS + 6-BA 1.5 mg L-1+ IAA 0.3 mg L-1,rooting medium was 1/2 MS + IAA0.8mgL-1. Some hybrids were transplanted into the field successfully.(3)Leaf shape investigation and identification by S allele-specific PCR and RAPDs showed that the hybrids were true ones.

  12. Hybrid cloud and cluster computing paradigms for life science applications.

    Science.gov (United States)

    Qiu, Judy; Ekanayake, Jaliya; Gunarathne, Thilina; Choi, Jong Youl; Bae, Seung-Hee; Li, Hui; Zhang, Bingjing; Wu, Tak-Lon; Ruan, Yang; Ekanayake, Saliya; Hughes, Adam; Fox, Geoffrey

    2010-12-21

    Clouds and MapReduce have shown themselves to be a broadly useful approach to scientific computing especially for parallel data intensive applications. However they have limited applicability to some areas such as data mining because MapReduce has poor performance on problems with an iterative structure present in the linear algebra that underlies much data analysis. Such problems can be run efficiently on clusters using MPI leading to a hybrid cloud and cluster environment. This motivates the design and implementation of an open source Iterative MapReduce system Twister. Comparisons of Amazon, Azure, and traditional Linux and Windows environments on common applications have shown encouraging performance and usability comparisons in several important non iterative cases. These are linked to MPI applications for final stages of the data analysis. Further we have released the open source Twister Iterative MapReduce and benchmarked it against basic MapReduce (Hadoop) and MPI in information retrieval and life sciences applications. The hybrid cloud (MapReduce) and cluster (MPI) approach offers an attractive production environment while Twister promises a uniform programming environment for many Life Sciences applications. We used commercial clouds Amazon and Azure and the NSF resource FutureGrid to perform detailed comparisons and evaluations of different approaches to data intensive computing. Several applications were developed in MPI, MapReduce and Twister in these different environments.

  13. On-line identification of hybrid systems using an adaptive growing and pruning RBF neural network

    DEFF Research Database (Denmark)

    Alizadeh, Tohid

    2008-01-01

    This paper introduces an adaptive growing and pruning radial basis function (GAP-RBF) neural network for on-line identification of hybrid systems. The main idea is to identify a global nonlinear model that can predict the continuous outputs of hybrid systems. In the proposed approach, GAP......-RBF neural network uses a modified unscented kalman filter (UKF) with forgetting factor scheme as the required on-line learning algorithm. The effectiveness of the resulting identification approach is tested and evaluated on a simulated benchmark hybrid system....

  14. Molecular identification of intergenus crosses involving catfish hybrids: risks for aquaculture production

    Directory of Open Access Journals (Sweden)

    Diogo T. Hashimoto

    Full Text Available ABSTRACT Monitoring of the interspecific hybrid production and trade is essential for the appropriate management of these animals in fish farms. The identification of catfish hybrids by morphological analysis is unreliable, particularly of juveniles and post-F1 individuals. Therefore, in the present study, we used five molecular markers (four nuclear genes and one mitochondrial gene to detect hybrids in the trade of pimelodid juvenile fish from different stocks purchased of five seed producers in Brazil. Samples commercialized as pintado (pure species Pseudoplatystoma corruscans from three fish farms were genetically identified as hybrid cachapinta (♀ P. reticulatum x ♂ P. corruscans . In the stocks purchased as cachandiá (hybrid between ♀ P. reticulatum x ♂ Leiarius marmoratus and cachapira (hybrid between ♀ P. reticulatum x ♂ Phractocephalus hemioliopterus , we suggested the occurrence of intergenus crosses involving the hybrid cachapinta, which was used instead of the pure species P. reticulatum . The problems involving the hybrid cachapinta production were discussed in the present study, especially because these animals have caused genetic contamination and threatened the genetic integrity of natural and cultivated populations. In order to improve the surveillance of the production and provide criteria for the correct management of catfish hybrids, genetic markers has become an excellent alternative to the morphological identification, including juveniles or post-F1 generations.

  15. Maze learning by a hybrid brain-computer system

    Science.gov (United States)

    Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

    2016-09-01

    The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

  16. Computational fluid dynamics challenges for hybrid air vehicle applications

    Science.gov (United States)

    Carrin, M.; Biava, M.; Steijl, R.; Barakos, G. N.; Stewart, D.

    2017-06-01

    This paper begins by comparing turbulence models for the prediction of hybrid air vehicle (HAV) flows. A 6 : 1 prolate spheroid is employed for validation of the computational fluid dynamics (CFD) method. An analysis of turbulent quantities is presented and the Shear Stress Transport (SST) k-ω model is compared against a k-ω Explicit Algebraic Stress model (EASM) within the unsteady Reynolds-Averaged Navier-Stokes (RANS) framework. Further comparisons involve Scale Adaptative Simulation models and a local transition transport model. The results show that the flow around the vehicle at low pitch angles is sensitive to transition effects. At high pitch angles, the vortices generated on the suction side provide substantial lift augmentation and are better resolved by EASMs. The validated CFD method is employed for the flow around a shape similar to the Airlander aircraft of Hybrid Air Vehicles Ltd. The sensitivity of the transition location to the Reynolds number is demonstrated and the role of each vehicle£s component is analyzed. It was found that the ¦ns contributed the most to increase the lift and drag.

  17. Universal quantum computation using all-optical hybrid encoding

    Institute of Scientific and Technical Information of China (English)

    郭奇; 程留永; 王洪福; 张寿

    2015-01-01

    By employing displacement operations, single-photon subtractions, and weak cross-Kerr nonlinearity, we propose an alternative way of implementing several universal quantum logical gates for all-optical hybrid qubits encoded in both single-photon polarization state and coherent state. Since these schemes can be straightforwardly implemented only using local operations without teleportation procedure, therefore, less physical resources and simpler operations are required than the existing schemes. With the help of displacement operations, a large phase shift of the coherent state can be obtained via currently available tiny cross-Kerr nonlinearity. Thus, all of these schemes are nearly deterministic and feasible under current technology conditions, which makes them suitable for large-scale quantum computing.

  18. "Hybrids" and the Gendering of Computing Jobs in Australia

    Directory of Open Access Journals (Sweden)

    Gillian Whitehouse

    2005-05-01

    Full Text Available This paper presents recent Australian evidence on the extent to which women are entering “hybrid” computing jobs combining technical and communication or “people management” skills, and the way these skill combinations are valued at organisational level. We draw on a survey of detailed occupational roles in large IT firms to examine the representation of women in a range of jobs consistent with the notion of “hybrid”, and analyse the discourse around these sorts of skills in a set of organisational case studies. Our research shows a traditional picture of labour market segmentation, with limited representation of women in high status jobs, and their relatively greater prevalence in more routine areas of the industry. While our case studies highlight perceptions of the need for hybrid roles and assumptions about the suitability of women for such jobs, the ongoing masculinity of core development functions appears untouched by this discourse.

  19. Genetic identification of F1 and post-F1 serrasalmid juvenile hybrids in Brazilian aquaculture.

    Directory of Open Access Journals (Sweden)

    Diogo Teruo Hashimoto

    Full Text Available Juvenile fish trade monitoring is an important task on Brazilian fish farms. However, the identification of juvenile fish through morphological analysis is not feasible, particularly between interspecific hybrids and pure species individuals, making the monitoring of these individuals difficult. Hybrids can be erroneously identified as pure species in breeding facilities, which might reduce production on farms and negatively affect native populations due to escapes or stocking practices. In the present study, we used a multi-approach analysis (molecular and cytogenetic markers to identify juveniles of three serrasalmid species (Colossoma macropomum, Piaractus mesopotamicus and Piaractus brachypomus and their hybrids in different stocks purchased from three seed producers in Brazil. The main findings of this study were the detection of intergenus backcrossing between the hybrid ♀ patinga (P. mesopotamicus×P. brachypomus×♂ C. macropomum and the occurrence of one hybrid triploid individual. This atypical specimen might result from automixis, a mechanism that produces unreduced gametes in some organisms. Moreover, molecular identification indicated that hybrid individuals are traded as pure species or other types of interspecific hybrids, particularly post-F1 individuals. These results show that serrasalmid fish genomes exhibit high genetic heterogeneity, and multi-approach methods and regulators could improve the surveillance of the production and trade of fish species and their hybrids, thereby facilitating the sustainable development of fish farming.

  20. Computational requirements for on-orbit identification of space systems

    Science.gov (United States)

    Hadaegh, Fred Y.

    1988-01-01

    For the future space systems, on-orbit identification (ID) capability will be required to complement on-orbit control, due to the fact that the dynamics of large space structures, spacecrafts, and antennas will not be known sufficiently from ground modeling and testing. The computational requirements for ID of flexible structures such as the space station (SS) or the large deployable reflectors (LDR) are however, extensive due to the large number of modes, sensors, and actuators. For these systems the ID algorithm operations need not be computed in real-time, only in near real-time, or an appropriate mission time. Consequently the space systems will need advanced processors and efficient parallel processing algorithm design and architectures to implement the identification algorithms in near real-time. The MAX computer currently being developed may handle such computational requirements. The purpose is to specify the on-board computational requirements for dynamic and static identification for large space structures. The computational requirements for six ID algorithms are presented in the context of three examples: the JPL/AFAL ground antenna facility, the space station (SS), and the large deployable reflector (LDR).

  1. A Massive Data Parallel Computational Framework for Petascale/Exascale Hybrid Computer Systems

    CERN Document Server

    Blazewicz, Marek; Diener, Peter; Koppelman, David M; Kurowski, Krzysztof; Löffler, Frank; Schnetter, Erik; Tao, Jian

    2012-01-01

    Heterogeneous systems are becoming more common on High Performance Computing (HPC) systems. Even using tools like CUDA and OpenCL it is a non-trivial task to obtain optimal performance on the GPU. Approaches to simplifying this task include Merge (a library based framework for heterogeneous multi-core systems), Zippy (a framework for parallel execution of codes on multiple GPUs), BSGP (a new programming language for general purpose computation on the GPU) and CUDA-lite (an enhancement to CUDA that transforms code based on annotations). In addition, efforts are underway to improve compiler tools for automatic parallelization and optimization of affine loop nests for GPUs and for automatic translation of OpenMP parallelized codes to CUDA. In this paper we present an alternative approach: a new computational framework for the development of massively data parallel scientific codes applications suitable for use on such petascale/exascale hybrid systems built upon the highly scalable Cactus framework. As the first...

  2. PCR-Reverse Blot Hybridization Assay for Screening and Identification of Pathogens in Sepsis

    OpenAIRE

    Choi, Yeonim; Wang, Hye-young; Lee, Gyusang; Park, Soon-Deok; Jeon, Bo-Young; Uh, Young; Kim, Jong Bae; Lee, Hyeyoung

    2013-01-01

    Rapid and accurate identification of the pathogens involved in bloodstream infections is crucial for the prompt initiation of appropriate therapy, as this can decrease morbidity and mortality rates. A PCR-reverse blot hybridization assay for sepsis, the reverse blot hybridization assay (REBA) Sepsis-ID test, was developed; it uses pan-probes to distinguish Gram-positive and -negative bacteria and fungi. In addition, the assay was designed to identify bacteria and fungi using six genus-specifi...

  3. Identification of hybrid node and link communities in complex networks

    Science.gov (United States)

    He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong

    2015-03-01

    Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.

  4. Secured Authorized Data Using Hybrid Encryption in Cloud Computing

    Directory of Open Access Journals (Sweden)

    Dinesh Shinde

    2017-03-01

    Full Text Available In today’s world to provide a security to a public network like a cloud network is become a toughest task however more likely to reduce the cost at the time of providing security using cryptographic technique to delegate the mask of the decryption task to the cloud servers to reduce the computing cost. As a result, attributebased encryption with delegation emerges. Still, there are caveats and questions remaining in the previous relevant works. For to solution to all problems the cloud servers could tamper or replace the delegated cipher text and respond a forged computing result with malicious intent. They may also cheat the eligible users by responding them that they are ineligible for the purpose of cost saving. Furthermore, during the encryption, the access policies may not be flexible enough as well. Since policy for general circuits enables to achieve the strongest form of access control, a construction for realizing circuit cipher text-policy attribute-based hybrid encryption with verifiable delegation has been considered in our work. In such a system, combined with verifiable computation and encrypt-then-mac mechanism, the data confidentiality, the fine-grained access control and the correctness of the delegated computing results are well guaranteed at the same time. Besides, our scheme achieves security against chosen-plaintext attacks under the k-multilinear Decisional Diffie-Hellman assumption. Moreover, an extensive simulation campaign confirms the feasibility and efficiency of the proposed solution. There are two complementary forms of attribute-based encryption. One is key-policy attribute-based encryption (KP-ABE [8], [9], [10], and the other is cipher text-policy attribute-based encryption. In a KP-ABE system, the decision of access policy is made by the key distributor instead of the enciphered, which limits the practicability and usability for the system in practical applicationsthe access policy for general circuits could be

  5. Model identification in computational stochastic dynamics using experimental modal data

    Science.gov (United States)

    Batou, A.; Soize, C.; Audebert, S.

    2015-01-01

    This paper deals with the identification of a stochastic computational model using experimental eigenfrequencies and mode shapes. In the presence of randomness, it is difficult to construct a one-to-one correspondence between the results provided by the stochastic computational model and the experimental data because of the random modes crossing and veering phenomena that may occur from one realization to another one. In this paper, this correspondence is constructed by introducing an adapted transformation for the computed modal quantities. Then the transformed computed modal quantities can be compared with the experimental data in order to identify the parameters of the stochastic computational model. The methodology is applied to a booster pump of thermal units for which experimental modal data have been measured on several sites.

  6. A Hybrid Segmentation Framework for Computer-Assisted Dental Procedures

    Science.gov (United States)

    Hosntalab, Mohammad; Aghaeizadeh Zoroofi, Reza; Abbaspour Tehrani-Fard, Ali; Shirani, Gholamreza; Reza Asharif, Mohammad

    Teeth segmentation in computed tomography (CT) images is a major and challenging task for various computer assisted procedures. In this paper, we introduced a hybrid method for quantification of teeth in CT volumetric dataset inspired by our previous experiences and anatomical knowledge of teeth and jaws. In this regard, we propose a novel segmentation technique using an adaptive thresholding, morphological operations, panoramic re-sampling and variational level set algorithm. The proposed method consists of several steps as follows: first, we determine the operation region in CT slices. Second, the bony tissues are separated from other tissues by utilizing an adaptive thresholding technique based on the 3D pulses coupled neural networks (PCNN). Third, teeth tissue is classified from other bony tissues by employing panorex lines and anatomical knowledge of teeth in the jaws. In this case, the panorex lines are estimated using Otsu thresholding and mathematical morphology operators. Then, the proposed method is followed by calculating the orthogonal lines corresponding to panorex lines and panoramic re-sampling of the dataset. Separation of upper and lower jaws and initial segmentation of teeth are performed by employing the integral projections of the panoramic dataset. Based the above mentioned procedures an initial mask for each tooth is obtained. Finally, we utilize the initial mask of teeth and apply a variational level set to refine initial teeth boundaries to final contour. In the last step a surface rendering algorithm known as marching cubes (MC) is applied to volumetric visualization. The proposed algorithm was evaluated in the presence of 30 cases. Segmented images were compared with manually outlined contours. We compared the performance of segmentation method using ROC analysis of the thresholding, watershed and our previous works. The proposed method performed best. Also, our algorithm has the advantage of high speed compared to our previous works.

  7. Computational analysis on plug-in hybrid electric motorcycle chassis

    Science.gov (United States)

    Teoh, S. J.; Bakar, R. A.; Gan, L. M.

    2013-12-01

    Plug-in hybrid electric motorcycle (PHEM) is an alternative to promote sustainability lower emissions. However, the PHEM overall system packaging is constrained by limited space in a motorcycle chassis. In this paper, a chassis applying the concept of a Chopper is analysed to apply in PHEM. The chassis 3dimensional (3D) modelling is built with CAD software. The PHEM power-train components and drive-train mechanisms are intergraded into the 3D modelling to ensure the chassis provides sufficient space. Besides that, a human dummy model is built into the 3D modelling to ensure the rider?s ergonomics and comfort. The chassis 3D model then undergoes stress-strain simulation. The simulation predicts the stress distribution, displacement and factor of safety (FOS). The data are used to identify the critical point, thus suggesting the chassis design is applicable or need to redesign/ modify to meet the require strength. Critical points mean highest stress which might cause the chassis to fail. This point occurs at the joints at triple tree and bracket rear absorber for a motorcycle chassis. As a conclusion, computational analysis predicts the stress distribution and guideline to develop a safe prototype chassis.

  8. Computational model predictions of cues for concurrent vowel identification.

    Science.gov (United States)

    Chintanpalli, Ananthakrishna; Ahlstrom, Jayne B; Dubno, Judy R

    2014-10-01

    Although differences in fundamental frequencies (F0s) between vowels are beneficial for their segregation and identification, listeners can still segregate and identify simultaneous vowels that have identical F0s, suggesting that additional cues are contributing, including formant frequency differences. The current perception and computational modeling study was designed to assess the contribution of F0 and formant difference cues for concurrent vowel identification. Younger adults with normal hearing listened to concurrent vowels over a wide range of levels (25-85 dB SPL) for conditions in which F0 was the same or different between vowel pairs. Vowel identification scores were poorer at the lowest and highest levels for each F0 condition, and F0 benefit was reduced at the lowest level as compared to higher levels. To understand the neural correlates underlying level-dependent changes in vowel identification, a computational auditory-nerve model was used to estimate formant and F0 difference cues under the same listening conditions. Template contrast and average localized synchronized rate predicted level-dependent changes in the strength of phase locking to F0s and formants of concurrent vowels, respectively. At lower levels, poorer F0 benefit may be attributed to poorer phase locking to both F0s, which resulted from lower firing rates of auditory-nerve fibers. At higher levels, poorer identification scores may relate to poorer phase locking to the second formant, due to synchrony capture by lower formants. These findings suggest that concurrent vowel identification may be partly influenced by level-dependent changes in phase locking of auditory-nerve fibers to F0s and formants of both vowels.

  9. Whispered speaker identification based on feature and model hybrid compensation

    Institute of Scientific and Technical Information of China (English)

    GU Xiaojiang; ZHAO Heming; Lu Gang

    2012-01-01

    In order to increase short time whispered speaker recognition rate in variable chan- nel conditions, the hybrid compensation in model and feature domains was proposed. This method is based on joint factor analysis in training model stage. It extracts speaker factor and eliminates channel factor by estimating training speech speaker and channel spaces. Then in the test stage, the test speech channel factor is projected into feature space to engage in feature compensation, so it can remove channel information both in model and feature domains in order to improve recognition rate. The experiment result shows that the hybrid compensation can obtain the similar recognition rate in the three different training channel conditions and this method is more effective than joint factor analysis in the test of short whispered speech.

  10. Adaptive Identification of Logging Lithology Based on VPSO-ENN Hybrid Algorithm

    Institute of Scientific and Technical Information of China (English)

    GUO Jian; WANG Yuan-han; LI Yin-ping

    2008-01-01

    Particle swarm optimization (PSO) was modified by variation method of particle velocity, and a variation PSO (VPSO) algorithm was proposed to overcome the shortcomings of PSO, such as premature convergence and local optimization. The VPSO algorithm is combined with Elman neural network (ENN) to form a VPSO-ENN hybrid algorithm. Compared with the hybrid algorithm of genetic algorithm (GA) and BP neural network (GA-BP), VPSO-ENN has less adjustable parameters, faster convergence speed and higher identification precision in the numerical experiment. A system for identifying logging parameters was established based on VPSO-ENN. The results of an engineering case indicate that the intelligent identification system is effective in the lithology identification.

  11. Computer simulation of optimal sensor locations in loading identification

    Science.gov (United States)

    Li, Dong-Sheng; Li, Hong-Nan; Guo, Xing L.

    2003-07-01

    A method is presented for the selection of a set of sensor locations from a larger candidate sent for the purpose of structural loading identification. The method ranks the candidate sensor locations according to their effectiveness for identifying the given known loadings. Measurement locations that yield abnormal jumps in identification results or increase the condition number of the frequency response function are removed. The final sensor configuration tends to minimize the error of the loading identification results and the condition number of the frequency response function. The initial candidate set is selected based on the modal kinetic energy distribution that gives a measure of the dynamic contribution of each physical degree freedom to each of the target mode shapes of interest. In addition, excitation location is considered when selecting appropriate response measurement locations. This method was successfully applied to the optimal sensor location selection and loading identification of a uniform cantilever beam in experiment. It is shown that computer simulation is a good way to select the optimal sensor location for loading identification.

  12. "iSS-Hyb-mRMR": Identification of splicing sites using hybrid space of pseudo trinucleotide and pseudo tetranucleotide composition.

    Science.gov (United States)

    Iqbal, Muhammad; Hayat, Maqsood

    2016-05-01

    Gene splicing is a vital source of protein diversity. Perfectly eradication of introns and joining exons is the prominent task in eukaryotic gene expression, as exons are usually interrupted by introns. Identification of splicing sites through experimental techniques is complicated and time-consuming task. With the avalanche of genome sequences generated in the post genomic age, it remains a complicated and challenging task to develop an automatic, robust and reliable computational method for fast and effective identification of splicing sites. In this study, a hybrid model "iSS-Hyb-mRMR" is proposed for quickly and accurately identification of splicing sites. Two sample representation methods namely; pseudo trinucleotide composition (PseTNC) and pseudo tetranucleotide composition (PseTetraNC) were used to extract numerical descriptors from DNA sequences. Hybrid model was developed by concatenating PseTNC and PseTetraNC. In order to select high discriminative features, minimum redundancy maximum relevance algorithm was applied on the hybrid feature space. The performance of these feature representation methods was tested using various classification algorithms including K-nearest neighbor, probabilistic neural network, general regression neural network, and fitting network. Jackknife test was used for evaluation of its performance on two benchmark datasets S1 and S2, respectively. The predictor, proposed in the current study achieved an accuracy of 93.26%, sensitivity of 88.77%, and specificity of 97.78% for S1, and the accuracy of 94.12%, sensitivity of 87.14%, and specificity of 98.64% for S2, respectively. It is observed, that the performance of proposed model is higher than the existing methods in the literature so for; and will be fruitful in the mechanism of RNA splicing, and other research academia. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  13. ANIBAL - a Hybrid Computer Language for EAI 680-PDP 8/I, FPP 12

    DEFF Research Database (Denmark)

    Højberg, Kristian Søe

    1974-01-01

    A hybrid programming language ANIBAL has been developed for use in an open-shop computing centre with an EAI-680 analog computer, a PDP8/I digital computer, and a FFP-12 floating point processor. An 8K core memory and 812k disk memory is included. The new language consists of standard FORTRAN IV...

  14. Splign: algorithms for computing spliced alignments with identification of paralogs

    Directory of Open Access Journals (Sweden)

    Tatusova Tatiana

    2008-05-01

    Full Text Available Abstract Background The computation of accurate alignments of cDNA sequences against a genome is at the foundation of modern genome annotation pipelines. Several factors such as presence of paralogs, small exons, non-consensus splice signals, sequencing errors and polymorphic sites pose recognized difficulties to existing spliced alignment algorithms. Results We describe a set of algorithms behind a tool called Splign for computing cDNA-to-Genome alignments. The algorithms include a high-performance preliminary alignment, a compartment identification based on a formally defined model of adjacent duplicated regions, and a refined sequence alignment. In a series of tests, Splign has produced more accurate results than other tools commonly used to compute spliced alignments, in a reasonable amount of time. Conclusion Splign's ability to deal with various issues complicating the spliced alignment problem makes it a helpful tool in eukaryotic genome annotation processes and alternative splicing studies. Its performance is enough to align the largest currently available pools of cDNA data such as the human EST set on a moderate-sized computing cluster in a matter of hours. The duplications identification (compartmentization algorithm can be used independently in other areas such as the study of pseudogenes. Reviewers This article was reviewed by: Steven Salzberg, Arcady Mushegian and Andrey Mironov (nominated by Mikhail Gelfand.

  15. A Comparison of Evolutionary Computation Techniques for IIR Model Identification

    Directory of Open Access Journals (Sweden)

    Erik Cuevas

    2014-01-01

    Full Text Available System identification is a complex optimization problem which has recently attracted the attention in the field of science and engineering. In particular, the use of infinite impulse response (IIR models for identification is preferred over their equivalent FIR (finite impulse response models since the former yield more accurate models of physical plants for real world applications. However, IIR structures tend to produce multimodal error surfaces whose cost functions are significantly difficult to minimize. Evolutionary computation techniques (ECT are used to estimate the solution to complex optimization problems. They are often designed to meet the requirements of particular problems because no single optimization algorithm can solve all problems competitively. Therefore, when new algorithms are proposed, their relative efficacies must be appropriately evaluated. Several comparisons among ECT have been reported in the literature. Nevertheless, they suffer from one limitation: their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments. This study presents the comparison of various evolutionary computation optimization techniques applied to IIR model identification. Results over several models are presented and statistically validated.

  16. Optimized Treatment of Fibromyalgia Using System Identification and Hybrid Model Predictive Control.

    Science.gov (United States)

    Deshpande, Sunil; Nandola, Naresh N; Rivera, Daniel E; Younger, Jarred W

    2014-12-01

    The term adaptive intervention is used in behavioral health to describe individually-tailored strategies for preventing and treating chronic, relapsing disorders. This paper describes a system identification approach for developing dynamical models from clinical data, and subsequently, a hybrid model predictive control scheme for assigning dosages of naltrexone as treatment for fibromyalgia, a chronic pain condition. A simulation study that includes conditions of significant plant-model mismatch demonstrates the benefits of hybrid predictive control as a decision framework for optimized adaptive interventions. This work provides insights on the design of novel personalized interventions for chronic pain and related conditions in behavioral health.

  17. Hybrid NN/SVM Computational System for Optimizing Designs

    Science.gov (United States)

    Rai, Man Mohan

    2009-01-01

    A computational method and system based on a hybrid of an artificial neural network (NN) and a support vector machine (SVM) (see figure) has been conceived as a means of maximizing or minimizing an objective function, optionally subject to one or more constraints. Such maximization or minimization could be performed, for example, to optimize solve a data-regression or data-classification problem or to optimize a design associated with a response function. A response function can be considered as a subset of a response surface, which is a surface in a vector space of design and performance parameters. A typical example of a design problem that the method and system can be used to solve is that of an airfoil, for which a response function could be the spatial distribution of pressure over the airfoil. In this example, the response surface would describe the pressure distribution as a function of the operating conditions and the geometric parameters of the airfoil. The use of NNs to analyze physical objects in order to optimize their responses under specified physical conditions is well known. NN analysis is suitable for multidimensional interpolation of data that lack structure and enables the representation and optimization of a succession of numerical solutions of increasing complexity or increasing fidelity to the real world. NN analysis is especially useful in helping to satisfy multiple design objectives. Feedforward NNs can be used to make estimates based on nonlinear mathematical models. One difficulty associated with use of a feedforward NN arises from the need for nonlinear optimization to determine connection weights among input, intermediate, and output variables. It can be very expensive to train an NN in cases in which it is necessary to model large amounts of information. Less widely known (in comparison with NNs) are support vector machines (SVMs), which were originally applied in statistical learning theory. In terms that are necessarily

  18. Model-Invariant Hybrid Computations of Separated Flows for RCA Standard Test Cases

    Science.gov (United States)

    Woodruff, Stephen

    2016-01-01

    NASA's Revolutionary Computational Aerosciences (RCA) subproject has identified several smooth-body separated flows as standard test cases to emphasize the challenge these flows present for computational methods and their importance to the aerospace community. Results of computations of two of these test cases, the NASA hump and the FAITH experiment, are presented. The computations were performed with the model-invariant hybrid LES-RANS formulation, implemented in the NASA code VULCAN-CFD. The model- invariant formulation employs gradual LES-RANS transitions and compensation for model variation to provide more accurate and efficient hybrid computations. Comparisons revealed that the LES-RANS transitions employed in these computations were sufficiently gradual that the compensating terms were unnecessary. Agreement with experiment was achieved only after reducing the turbulent viscosity to mitigate the effect of numerical dissipation. The stream-wise evolution of peak Reynolds shear stress was employed as a measure of turbulence dynamics in separated flows useful for evaluating computations.

  19. Hybrid computing: CPU+GPU co-processing and its application to tomographic reconstruction.

    Science.gov (United States)

    Agulleiro, J I; Vázquez, F; Garzón, E M; Fernández, J J

    2012-04-01

    Modern computers are equipped with powerful computing engines like multicore processors and GPUs. The 3DEM community has rapidly adapted to this scenario and many software packages now make use of high performance computing techniques to exploit these devices. However, the implementations thus far are purely focused on either GPUs or CPUs. This work presents a hybrid approach that collaboratively combines the GPUs and CPUs available in a computer and applies it to the problem of tomographic reconstruction. Proper orchestration of workload in such a heterogeneous system is an issue. Here we use an on-demand strategy whereby the computing devices request a new piece of work to do when idle. Our hybrid approach thus takes advantage of the whole computing power available in modern computers and further reduces the processing time. This CPU+GPU co-processing can be readily extended to other image processing tasks in 3DEM. Copyright © 2012 Elsevier B.V. All rights reserved.

  20. [Maize Hybrid Seed Purity Identification Based on Near Infrared Reflectance (NIR) and Transmittance (NIT) Spectra].

    Science.gov (United States)

    Li, Tian-xin; Jia, Shi-qiang; Liu, Xu; Zhao, Sheng-yi; Ran, Hang; Yan, Yan-lu; An, Dong

    2015-12-01

    This article explore the feasibility of using Near Infrared Reflectance (NIR) and Transmittance (NIT) Spectroscopy (908.1-1677.2 nm wavelength range) to identify maize hybrid purity, and compare the performance of NIR and NIT spectroscopy. Principle Component Analysis (PCA) and Orthogonal Linear Discriminant Analysis (OLDA) were used to reduce the dimension of spectra which have been pretreated by first derivative and vector normalization. The hybrid purity identification model of Nonghua101 and Jingyu16 were built by SVM. Models based on NIR spectra obtained correct identification rate as 100% and 90% for Nonghua101 and Jingyu16 respectively. But NIR spectra were greatly influenced by the placement of seeds, and there existed significant difference between NIR spectra of embryo and non-embryo side. Models based on NIT spectroscopy yielded correct identification rate as 98% both for Nonghua101 and Jingyu16. NIT spectra of embryo and non-embryo side were highly similar. The results indicate that it is feasible to identify maize hybrid purity based on NIR and NIT spectroscopy, and NIT spectroscopy is more suitable to analyze single seed kernel than NIR spectroscopy.

  1. PNA-based fluorescence in situ hybridization for identification of bacteria in clinical samples

    DEFF Research Database (Denmark)

    Fazli, Mustafa; Bjarnsholt, Thomas; Høiby, Niels;

    2014-01-01

    Fluorescence in situ hybridization with PNA probes (PNA-FISH) that target specific bacterial ribosomal RNA sequences is a powerful and rapid tool for identification of bacteria in clinical samples. PNA can diffuse readily through the bacterial cell wall due to its uncharged backbone, and PNA-FISH....... In all these cases, bacteria can be identified in biofilm aggregates, which may explain their recalcitrance to antibiotic treatment.......Fluorescence in situ hybridization with PNA probes (PNA-FISH) that target specific bacterial ribosomal RNA sequences is a powerful and rapid tool for identification of bacteria in clinical samples. PNA can diffuse readily through the bacterial cell wall due to its uncharged backbone, and PNA......-FISH can be performed with high specificity due to the extraordinary thermal stability of RNA-PNA hybrid complexes. We describe a PNA-FISH procedure and provide examples of the application of PNA-FISH for the identification of bacteria in chronic wounds, cystic fibrosis lungs, and soft tissue fillers...

  2. A Hybrid Computational Intelligence Approach Combining Genetic Programming And Heuristic Classification for Pap-Smear Diagnosis

    DEFF Research Database (Denmark)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan

    2001-01-01

    The paper suggests the combined use of different computational intelligence (CI) techniques in a hybrid scheme, as an effective approach to medical diagnosis. Getting to know the advantages and disadvantages of each computational intelligence technique in the recent years, the time has come for p...

  3. Use of hybrid discrete cellular models for identification of macroscopic nutrient loss in reaction-diffusion models of tissues.

    Science.gov (United States)

    Aristotelous, Andreas C; Haider, Mansoor A

    2014-08-01

    Macroscopic models accounting for cellular effects in natural or engineered tissues may involve unknown constitutive terms that are highly dependent on interactions at the scale of individual cells. Hybrid discrete models, which represent cells individually, were used to develop and apply techniques for modeling diffusive nutrient transport and cellular uptake to identify a nonlinear nutrient loss term in a macroscopic reaction-diffusion model of the system. Flexible and robust numerical methods were used, based on discontinuous Galerkin finite elements in space and a Crank-Nicolson temporal discretization. Scales were bridged via averaging operations over a complete set of subdomains yielding data for identification of a macroscopic nutrient loss term that was accurately captured via a fifth-order polynomial. Accuracy of the identified macroscopic model was demonstrated by direct, quantitative comparisons of the tissue and cellular scale models in terms of three error norms computed on a mesoscale mesh. Copyright © 2014 John Wiley & Sons, Ltd.

  4. A hybrid method for identification of structural domains

    Science.gov (United States)

    Hua, Yongpan; Zhu, Min; Wang, Yuelong; Xie, Zhaoyang; Li, Menglong

    2014-12-01

    Structural domains in proteins are the basic units to form various proteins. In the protein's evolution and functioning, domains play important roles. But the definition of domain is not yet precisely given, and the update cycle of structural domain databases is long. The automatic algorithms identify domains slowly, while protein entities with great structural complexity are on the rise. Here, we present a method which recognizes the compact and modular segments of polypeptide chains to identify structural domains, and contrast some data sets to illuminate their effect. The method combines support vector machine (SVM) with K-means algorithm. It is faster and more stable than most current algorithms and performs better. It also indicates that when proteins are presented as some Alpha-carbon atoms in 3D space, it is feasible to identify structural domains by the spatially structural properties. We have developed a web-server, which would be helpful in identification of structural domains (http://vis.sculab.org/~huayongpan/cgi-bin/domainAssignment.cgi).

  5. Identification of cichlid fishes from Lake Malawi using computer vision.

    Directory of Open Access Journals (Sweden)

    Deokjin Joo

    Full Text Available BACKGROUND: The explosively radiating evolution of cichlid fishes of Lake Malawi has yielded an amazing number of haplochromine species estimated as many as 500 to 800 with a surprising degree of diversity not only in color and stripe pattern but also in the shape of jaw and body among them. As these morphological diversities have been a central subject of adaptive speciation and taxonomic classification, such high diversity could serve as a foundation for automation of species identification of cichlids. METHODOLOGY/PRINCIPAL FINDING: Here we demonstrate a method for automatic classification of the Lake Malawi cichlids based on computer vision and geometric morphometrics. For this end we developed a pipeline that integrates multiple image processing tools to automatically extract informative features of color and stripe patterns from a large set of photographic images of wild cichlids. The extracted information was evaluated by statistical classifiers Support Vector Machine and Random Forests. Both classifiers performed better when body shape information was added to the feature of color and stripe. Besides the coloration and stripe pattern, body shape variables boosted the accuracy of classification by about 10%. The programs were able to classify 594 live cichlid individuals belonging to 12 different classes (species and sexes with an average accuracy of 78%, contrasting to a mere 42% success rate by human eyes. The variables that contributed most to the accuracy were body height and the hue of the most frequent color. CONCLUSIONS: Computer vision showed a notable performance in extracting information from the color and stripe patterns of Lake Malawi cichlids although the information was not enough for errorless species identification. Our results indicate that there appears an unavoidable difficulty in automatic species identification of cichlid fishes, which may arise from short divergence times and gene flow between closely related species.

  6. Reducing the Digital Divide among Children Who Received Desktop or Hybrid Computers for the Home

    Directory of Open Access Journals (Sweden)

    Gila Cohen Zilka

    2016-06-01

    Full Text Available Researchers and policy makers have been exploring ways to reduce the digital divide. Parameters commonly used to examine the digital divide worldwide, as well as in this study, are: (a the digital divide in the accessibility and mobility of the ICT infrastructure and of the content infrastructure (e.g., sites used in school; and (b the digital divide in literacy skills. In the present study we examined the degree of effectiveness of receiving a desktop or hybrid computer for the home in reducing the digital divide among children of low socio-economic status aged 8-12 from various localities across Israel. The sample consisted of 1,248 respondents assessed in two measurements. As part of the mixed-method study, 128 children were also interviewed. Findings indicate that after the children received desktop or hybrid computers, changes occurred in their frequency of access, mobility, and computer literacy. Differences were found between the groups: hybrid computers reduce disparities and promote work with the computer and surfing the Internet more than do desktop computers. Narrowing the digital divide for this age group has many implications for the acquisition of skills and study habits, and consequently, for the realization of individual potential. The children spoke about self improvement as a result of exposure to the digital environment, about a sense of empowerment and of improvement in their advantage in the social fabric. Many children expressed a desire to continue their education and expand their knowledge of computer applications, the use of software, of games, and more. Therefore, if there is no computer in the home and it is necessary to decide between a desktop and a hybrid computer, a hybrid computer is preferable.

  7. A Hybrid Model for Individual Identification Based on Keystroke Data in Japanese Free Text Typing

    Science.gov (United States)

    Samura, Toshiharu; Nishimura, Haruhiko

    We have investigated several characteristics of keystroke dynamics in Japanese free text typing. We performed experiments on 189 subjects, representing three groups according to the number of letters they could type in five minutes. In this experiment, we extracted the feature indices from the keystroke timing for each alphabet single letter and for two-letter combinations composed of consonant and vowel pairs in Japanese text. Taking into account two identification methods using weighted Euclidean distance (WED) and Vector Disorder (VD), we proposed their hybrid model for individual identification based on keystroke data in Japanese free text typing. By evaluating the personal identification for the three groups, its high performance was confirmed in proportion to the typing level of the group.

  8. Hybrid Computational Simulation and Study of Terahertz Pulsed Photoconductive Antennas

    Science.gov (United States)

    Emadi, R.; Barani, N.; Safian, R.; Nezhad, A. Zeidaabadi

    2016-08-01

    A photoconductive antenna (PCA) has been numerically investigated in the terahertz (THz) frequency band based on a hybrid simulation method. This hybrid method utilizes an optoelectronic solver, Silvaco TCAD, and a full-wave electromagnetic solver, CST. The optoelectronic solver is used to find the accurate THz photocurrent by considering realistic material parameters. Performance of photoconductive antennas and temporal behavior of the excited photocurrent for various active region geometries such as bare-gap electrode, interdigitated electrodes, and tip-to-tip rectangular electrodes are investigated. Moreover, investigations have been done on the center of the laser illumination on the substrate, substrate carrier lifetime, and diffusion photocurrent associated with the carriers temperature, to achieve efficient and accurate photocurrent. Finally, using the full-wave electromagnetic solver and the calculated photocurrent obtained from the optoelectronic solver, electromagnetic radiation of the antenna and its associated detected THz signal are calculated and compared with a measurement reference for verification.

  9. Performance Comparison of Hybrid Signed Digit Arithmetic in Efficient Computing

    Directory of Open Access Journals (Sweden)

    VISHAL AWASTHI

    2011-10-01

    Full Text Available In redundant representations, addition can be carried out in a constant time independent of the word length of the operands. Adder forms a fundamental building block in almost majority of VLSI designs. A hybrid adder can add an unsigned number to a signed-digit number and hence their efficient performance greatly determinesthe quality of the final output of the concerned circuit. In this paper we designed and compared the speed of adders by reducing the carry propagation time with the help of combined effect of improved architectures of adders and signed digit representation of number systems. The key idea is to draw out a compromise between execution time of fast adding process and area available which is often very limited. In this paper we also tried to verify the various algorithms of signed digit and hybrid signed digit adders.

  10. Hybrid Computational Simulation and Study of Terahertz Pulsed Photoconductive Antennas

    Science.gov (United States)

    Emadi, R.; Barani, N.; Safian, R.; Nezhad, A. Zeidaabadi

    2016-11-01

    A photoconductive antenna (PCA) has been numerically investigated in the terahertz (THz) frequency band based on a hybrid simulation method. This hybrid method utilizes an optoelectronic solver, Silvaco TCAD, and a full-wave electromagnetic solver, CST. The optoelectronic solver is used to find the accurate THz photocurrent by considering realistic material parameters. Performance of photoconductive antennas and temporal behavior of the excited photocurrent for various active region geometries such as bare-gap electrode, interdigitated electrodes, and tip-to-tip rectangular electrodes are investigated. Moreover, investigations have been done on the center of the laser illumination on the substrate, substrate carrier lifetime, and diffusion photocurrent associated with the carriers temperature, to achieve efficient and accurate photocurrent. Finally, using the full-wave electromagnetic solver and the calculated photocurrent obtained from the optoelectronic solver, electromagnetic radiation of the antenna and its associated detected THz signal are calculated and compared with a measurement reference for verification.

  11. Computational and experimental study of air hybrid engine concepts

    OpenAIRE

    Lee, Cho-Yu

    2011-01-01

    This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University The air hybrid engine absorbs the vehicle kinetic energy during braking, stores it in an air tank in the form of compressed air, and reuses it to start the engine and to propel a vehicle during cruising and acceleration. Capturing, storing and reusing this braking energy to achieve stop-start operation and to give additional power can therefore improve fuel economy, particularly in cities and ...

  12. Hybrid computer techniques for solving partial differential equations

    Science.gov (United States)

    Hammond, J. L., Jr.; Odowd, W. M.

    1971-01-01

    Techniques overcome equipment limitations that restrict other computer techniques in solving trivial cases. The use of curve fitting by quadratic interpolation greatly reduces required digital storage space.

  13. A generalized hybrid transfinite element computational approach for nonlinear/linear unified thermal/structural analysis

    Science.gov (United States)

    Tamma, Kumar K.; Railkar, Sudhir B.

    1987-01-01

    The present paper describes the development of a new hybrid computational approach for applicability for nonlinear/linear thermal structural analysis. The proposed transfinite element approach is a hybrid scheme as it combines the modeling versatility of contemporary finite elements in conjunction with transform methods and the classical Bubnov-Galerkin schemes. Applicability of the proposed formulations for nonlinear analysis is also developed. Several test cases are presented to include nonlinear/linear unified thermal-stress and thermal-stress wave propagations. Comparative results validate the fundamental capablities of the proposed hybrid transfinite element methodology.

  14. Hybrid computing: CPU+GPU co-processing and its application to tomographic reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Agulleiro, J.I.; Vazquez, F.; Garzon, E.M. [Supercomputing and Algorithms Group, Associated Unit CSIC-UAL, University of Almeria, 04120 Almeria (Spain); Fernandez, J.J., E-mail: JJ.Fernandez@csic.es [National Centre for Biotechnology, National Research Council (CNB-CSIC), Campus UAM, C/Darwin 3, Cantoblanco, 28049 Madrid (Spain)

    2012-04-15

    Modern computers are equipped with powerful computing engines like multicore processors and GPUs. The 3DEM community has rapidly adapted to this scenario and many software packages now make use of high performance computing techniques to exploit these devices. However, the implementations thus far are purely focused on either GPUs or CPUs. This work presents a hybrid approach that collaboratively combines the GPUs and CPUs available in a computer and applies it to the problem of tomographic reconstruction. Proper orchestration of workload in such a heterogeneous system is an issue. Here we use an on-demand strategy whereby the computing devices request a new piece of work to do when idle. Our hybrid approach thus takes advantage of the whole computing power available in modern computers and further reduces the processing time. This CPU+GPU co-processing can be readily extended to other image processing tasks in 3DEM. -- Highlights: Black-Right-Pointing-Pointer Hybrid computing allows full exploitation of the power (CPU+GPU) in a computer. Black-Right-Pointing-Pointer Proper orchestration of workload is managed by an on-demand strategy. Black-Right-Pointing-Pointer Total number of threads running in the system should be limited to the number of CPUs.

  15. Identification of Enhancers In Human: Advances In Computational Studies

    KAUST Repository

    Kleftogiannis, Dimitrios A.

    2016-03-24

    Roughly ~50% of the human genome, contains noncoding sequences serving as regulatory elements responsible for the diverse gene expression of the cells in the body. One very well studied category of regulatory elements is the category of enhancers. Enhancers increase the transcriptional output in cells through chromatin remodeling or recruitment of complexes of binding proteins. Identification of enhancer using computational techniques is an interesting area of research and up to now several approaches have been proposed. However, the current state-of-the-art methods face limitations since the function of enhancers is clarified, but their mechanism of function is not well understood. This PhD thesis presents a bioinformatics/computer science study that focuses on the problem of identifying enhancers in different human cells using computational techniques. The dissertation is decomposed into four main tasks that we present in different chapters. First, since many of the enhancer’s functions are not well understood, we study the basic biological models by which enhancers trigger transcriptional functions and we survey comprehensively over 30 bioinformatics approaches for identifying enhancers. Next, we elaborate more on the availability of enhancer data as produced by different enhancer identification methods and experimental procedures. In particular, we analyze advantages and disadvantages of existing solutions and we report obstacles that require further consideration. To mitigate these problems we developed the Database of Integrated Human Enhancers (DENdb), a centralized online repository that archives enhancer data from 16 ENCODE cell-lines. The integrated enhancer data are also combined with many other experimental data that can be used to interpret the enhancers content and generate a novel enhancer annotation that complements the existing integrative annotation proposed by the ENCODE consortium. Next, we propose the first deep-learning computational

  16. A Hybrid Circular Queue Method for Iterative Stencil Computations on GPUs

    Institute of Scientific and Technical Information of China (English)

    Yang Yang; Hui-Min Cui; Xiao-Bing Feng; Jing-Ling Xue

    2012-01-01

    In this paper,we present a hybrid circular queue method that can significantly boost the performance of stencil computations on GPU by carefully balancing usage of registers and shared-memory.Unlike earlier methods that rely on circular queues predominantly implemented using indirectly addressable shared memory,our hybrid method exploits a new reuse pattern spanning across the multiple time steps in stencil computations so that circular queues can be implemented by both shared memory and registers effectively in a balanced manner.We describe a framework that automatically finds the best placement of data in registers and shared memory in order to maximize the performance of stencil computations.Validation using four different types of stencils on three different GPU platforms shows that our hybrid method achieves speedups up to 2.93X over methods that use circular queues implemented with shared-memory only.

  17. Effective hybrid evolutionary computational algorithms for global optimization and applied to construct prion AGAAAAGA fibril models

    CERN Document Server

    Zhang, Jiapu

    2010-01-01

    Evolutionary algorithms are parallel computing algorithms and simulated annealing algorithm is a sequential computing algorithm. This paper inserts simulated annealing into evolutionary computations and successful developed a hybrid Self-Adaptive Evolutionary Strategy $\\mu+\\lambda$ method and a hybrid Self-Adaptive Classical Evolutionary Programming method. Numerical results on more than 40 benchmark test problems of global optimization show that the hybrid methods presented in this paper are very effective. Lennard-Jones potential energy minimization is another benchmark for testing new global optimization algorithms. It is studied through the amyloid fibril constructions by this paper. To date, there is little molecular structural data available on the AGAAAAGA palindrome in the hydrophobic region (113-120) of prion proteins.This region belongs to the N-terminal unstructured region (1-123) of prion proteins, the structure of which has proved hard to determine using NMR spectroscopy or X-ray crystallography ...

  18. A new hybrid transfinite element computational methodology for applicability to conduction/convection/radiation heat transfer

    Science.gov (United States)

    Tamma, Kumar K.; Railkar, Sudhir B.

    1988-01-01

    This paper describes new and recent advances in the development of a hybrid transfinite element computational methodology for applicability to conduction/convection/radiation heat transfer problems. The transfinite element methodology, while retaining the modeling versatility of contemporary finite element formulations, is based on application of transform techniques in conjunction with classical Galerkin schemes and is a hybrid approach. The purpose of this paper is to provide a viable hybrid computational methodology for applicability to general transient thermal analysis. Highlights and features of the methodology are described and developed via generalized formulations and applications to several test problems. The proposed transfinite element methodology successfully provides a viable computational approach and numerical test problems validate the proposed developments for conduction/convection/radiation thermal analysis.

  19. A new hybrid transfinite element computational methodology for applicability to conduction/convection/radiation heat transfer

    Science.gov (United States)

    Tamma, Kumar K.; Railkar, Sudhir B.

    1988-01-01

    This paper describes new and recent advances in the development of a hybrid transfinite element computational methodology for applicability to conduction/convection/radiation heat transfer problems. The transfinite element methodology, while retaining the modeling versatility of contemporary finite element formulations, is based on application of transform techniques in conjunction with classical Galerkin schemes and is a hybrid approach. The purpose of this paper is to provide a viable hybrid computational methodology for applicability to general transient thermal analysis. Highlights and features of the methodology are described and developed via generalized formulations and applications to several test problems. The proposed transfinite element methodology successfully provides a viable computational approach and numerical test problems validate the proposed developments for conduction/convection/radiation thermal analysis.

  20. High-fidelity quantum memory using nitrogen-vacancy center ensemble for hybrid quantum computation

    CERN Document Server

    Yang, W L; Hu, Y; Feng, M; Du, J F

    2011-01-01

    We study a hybrid quantum computing system using nitrogen-vacancy center ensemble (NVE) as quantum memory, current-biased Josephson junction (CBJJ) superconducting qubit fabricated in a transmission line resonator (TLR) as quantum computing processor and the microwave photons in TLR as quantum data bus. The storage process is seriously treated by considering all kinds of decoherence mechanisms. Such a hybrid quantum device can also be used to create multi-qubit W states of NVEs through a common CBJJ. The experimental feasibility and challenge are justified using currently available technology.

  1. Computational system identification of continuous-time nonlinear systems using approximate Bayesian computation

    Science.gov (United States)

    Krishnanathan, Kirubhakaran; Anderson, Sean R.; Billings, Stephen A.; Kadirkamanathan, Visakan

    2016-11-01

    In this paper, we derive a system identification framework for continuous-time nonlinear systems, for the first time using a simulation-focused computational Bayesian approach. Simulation approaches to nonlinear system identification have been shown to outperform regression methods under certain conditions, such as non-persistently exciting inputs and fast-sampling. We use the approximate Bayesian computation (ABC) algorithm to perform simulation-based inference of model parameters. The framework has the following main advantages: (1) parameter distributions are intrinsically generated, giving the user a clear description of uncertainty, (2) the simulation approach avoids the difficult problem of estimating signal derivatives as is common with other continuous-time methods, and (3) as noted above, the simulation approach improves identification under conditions of non-persistently exciting inputs and fast-sampling. Term selection is performed by judging parameter significance using parameter distributions that are intrinsically generated as part of the ABC procedure. The results from a numerical example demonstrate that the method performs well in noisy scenarios, especially in comparison to competing techniques that rely on signal derivative estimation.

  2. Hybrid Computational Model for High-Altitude Aeroassist Vehicles Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed effort addresses a need for accurate computational models to support aeroassist and entry vehicle system design over a broad range of flight conditions...

  3. Hybrid PSO-MOBA for Profit Maximization in Cloud Computing

    Directory of Open Access Journals (Sweden)

    Dr. Salu George

    2015-02-01

    Full Text Available Cloud service provider, infrastructure vendor and clients/Cloud user’s are main actors in any cloud enterprise like Amazon web service’s cloud or Google’s cloud. Now these enterprises take care in infrastructure deployment and cloud services management (IaaS/PaaS/SaaS. Cloud user ‘s need to provide correct amount of services needed and characteristic of workload in order to avoid over – provisioning of resources and it’s the important pricing factor. Cloud service provider need to manage the resources and as well as optimize the resources to maximize the profit. To manage the profit we consider the M/M/m queuing model which manages the queue of job and provide average execution time. Resource Scheduling is one of the main concerns in profit maximization for which we take HYBRID PSO-MOBA as it resolves the global convergence problem, faster convergence, less parameter to tune, easier searching in very large problem spaces and locating the right resource. In HYBRID PSO-MOBA we are combining the features of PSO and MOBA to achieve the benefits of both PSO and MOBA and have greater compatibility.

  4. A hybrid system identification methodology for wireless structural health monitoring systems based on dynamic substructuring

    Science.gov (United States)

    Dragos, Kosmas; Smarsly, Kay

    2016-04-01

    System identification has been employed in numerous structural health monitoring (SHM) applications. Traditional system identification methods usually rely on centralized processing of structural response data to extract information on structural parameters. However, in wireless SHM systems the centralized processing of structural response data introduces a significant communication bottleneck. Exploiting the merits of decentralization and on-board processing power of wireless SHM systems, many system identification methods have been successfully implemented in wireless sensor networks. While several system identification approaches for wireless SHM systems have been proposed, little attention has been paid to obtaining information on the physical parameters (e.g. stiffness, damping) of the monitored structure. This paper presents a hybrid system identification methodology suitable for wireless sensor networks based on the principles of component mode synthesis (dynamic substructuring). A numerical model of the monitored structure is embedded into the wireless sensor nodes in a distributed manner, i.e. the entire model is segmented into sub-models, each embedded into one sensor node corresponding to the substructure the sensor node is assigned to. The parameters of each sub-model are estimated by extracting local mode shapes and by applying the equations of the Craig-Bampton method on dynamic substructuring. The proposed methodology is validated in a laboratory test conducted on a four-story frame structure to demonstrate the ability of the methodology to yield accurate estimates of stiffness parameters. Finally, the test results are discussed and an outlook on future research directions is provided.

  5. A HYBRID TECHNIQUE FOR FREQUENCY DOMAIN IDENTIFICATION OF SERVO SYSTEM WITH FRICTION FORCE

    Directory of Open Access Journals (Sweden)

    SHAIK.RAFI KIRAN,

    2011-03-01

    Full Text Available The system identification process in servo system with frictional force seems to be a complex task becauseof its non-linear nature. For such non-linear systems, a good choice is system identification in frequencydomain. However, most of the techniques are manual and are inappropriate for determination of systemparameters. This makes system identification ineffective for servo systems with frictional force. Toovercome this issue, a hybrid technique is proposed in this paper. The proposed technique exploits neuralnetwork and genetic algorithm to determine the system parameters of servo systems with friction. In theproposed technique, the target parameters are determined from the transfer function derived for thesystem. Subsequently, the system parameters are identified by a process formed by blending the neuralnetwork and genetic algorithm techniques. Prior to performing the identification procedure, backpropagation training is given to the neural network using a pre-examined dataset. Then with thecombined operation of neural network and genetic algorithm, the system parameters that are closer tothe target parameters for the servo system with frictional force are determined. The technique isimplemented and compared with the existing frequency domain identification technique. From thecomparative results, it is evident that the proposed technique outperforms the existing technique.

  6. CRES` wind-diesel hybrid system: system identification and performance testing

    Energy Technology Data Exchange (ETDEWEB)

    Vionis, P.S.; Fragoulis, A.N.; Ladakakos, P.D. [Center for Renewable Energy Sources (C.R.E.S.), Pikermi (Greece)

    1996-12-31

    A Wind-Diesel hybrid system has been developed at CRES for investigating the parallel operation of Wind Turbines and Diesel Generators into Autonomous Weak Grids. The system`s architecture is flexible enough so that it can be effectively used for optimising the integration of renewable energy sources in such autonomous power systems, while ensuring the successful implementation of innovative control strategies and testing of new design concepts. In this paper, the design of the wind-diesel simulator and its basic operation modes are described. Results of the components identification procedure are presented. The relevant analysis reveals the components` characteristics under various modes of operation along with the subsystem`s operation limits. The methodology set up for system testing and evaluation has been verified. Results of the first performance tests of the Wind-Diesel hybrid system showing its capabilities are presented and discussed. (Author)

  7. Identification of vibration loads on hydro generator by using hybrid genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    Shouju Li; Yingxi Liu

    2006-01-01

    Vibration dynamic characteristics have been a major issue in the modeling and mechanical analysis of large hydro generators.An algorithm is developed for identifying vibration dynamic characteristics by means of hybrid genetic algorithm.From the measured dynamic responses of a hydro generator,an appropriate estimation algorithm is needed to identify the loading parameters,including the main frequencies and amplitudes of vibrating forces.In order to identify parameters in an efficient and robust manner,an optimization method is proposed that combines genetic algorithm with simulated annealing and elitist strategy.The hybrid genetic algorithm is then used to tackle an ill-posed problem of parameter identification.In which the effectiveness of the proposed optimization method is confirmed by its comparison with actual observation data.

  8. Soft computing applications: the advent of hybrid systems

    Science.gov (United States)

    Bonissone, Piero P.

    1998-10-01

    Soft computing is a new field of computer sciences that deals with the integration of problem- solving technologies such as fuzzy logic, probabilistic reasoning, neural networks, and genetic algorithms. Each of these technologies provide us with complementary reasoning and searching methods to solve complex, real-world problems. We will analyze some of the most synergistic combinations of self computing technologies, with an emphasis on the development of smart algorithm-controllers, such as the use of FL to control GAs and NNs parameters. We will also discuss the application of GAs to evolve NNs or tune FL controllers; and the implementation of FL controllers as NNs tuned by backpropagation-type algorithms. We will conclude with a detailed description of a GA-tuned fuzzy controller to implement a train handling control.

  9. Carbon nanotube reinforced hybrid composites: Computational modeling of environmental fatigue and usability for wind blades

    DEFF Research Database (Denmark)

    Dai, Gaoming; Mishnaevsky, Leon

    2015-01-01

    The potential of advanced carbon/glass hybrid reinforced composites with secondary carbon nanotube reinforcement for wind energy applications is investigated here with the use of computational experiments. Fatigue behavior of hybrid as well as glass and carbon fiber reinforced composites...... with the secondary CNT reinforcements (especially, aligned tubes) present superior fatigue performances than those without reinforcements, also under combined environmental and cyclic mechanical loading. This effect is stronger for carbon composites, than for hybrid and glass composites....... automatically using the Python based code. 3D computational studies of environment and fatigue analyses of multiscale composites with secondary nano-scale reinforcement in different material phases and different CNTs arrangements are carried out systematically in this paper. It was demonstrated that composites...

  10. Hybrid and hierarchical nanoreinforced polymer composites: Computational modelling of structure–properties relationships

    DEFF Research Database (Denmark)

    Mishnaevsky, Leon; Dai, Gaoming

    2014-01-01

    Hybrid and hierarchical polymer composites represent a promising group of materials for engineering applications. In this paper, computational studies of the strength and damage resistance of hybrid and hierarchical composites are reviewed. The reserves of the composite improvement are explored...... by using computational micromechanical models. It is shown that while glass/carbon fibers hybrid composites clearly demonstrate higher stiffness and lower weight with increasing the carbon content, they can have lower strength as compared with usual glass fiber polymer composites. Secondary...... nanoreinforcement can drastically increase the fatigue lifetime of composites. Especially, composites with the nanoplatelets localized in the fiber/matrix interface layer (fiber sizing) ensure much higher fatigue lifetime than those with the nanoplatelets in the matrix....

  11. Hybrid Approach for Language Identification Oriented to Multilingual Speech Recognition in the Basque Context

    Science.gov (United States)

    Barroso, N.; de Ipiña, K. López; Ezeiza, A.; Barroso, O.; Susperregi, U.

    The development of Multilingual Large Vocabulary Continuous Speech Recognition systems involves issues as: Language Identification, Acoustic-Phonetic Decoding, Language Modelling or the development of appropriated Language Resources. The interest on Multilingual Systems arouses because there are three official languages in the Basque Country (Basque, Spanish, and French), and there is much linguistic interaction among them, even if Basque has very different roots than the other two languages. This paper describes the development of a Language Identification (LID) system oriented to robust Multilingual Speech Recognition for the Basque context. The work presents hybrid strategies for LID, based on the selection of system elements by Support Vector Machines and Multilayer Perceptron classifiers and stochastic methods for speech recognition tasks (Hidden Markov Models and n-grams).

  12. Hybrid Computation Model for Intelligent System Design by Synergism of Modified EFC with Neural Network

    OpenAIRE

    2015-01-01

    In recent past, it has been seen in many applications that synergism of computational intelligence techniques outperforms over an individual technique. This paper proposes a new hybrid computation model which is a novel synergism of modified evolutionary fuzzy clustering with associated neural networks. It consists of two modules: fuzzy distribution and neural classifier. In first module, mean patterns are distributed into the number of clusters based on the modified evolutionary fuzzy cluste...

  13. Computer-aided diagnosis system: a Bayesian hybrid classification method.

    Science.gov (United States)

    Calle-Alonso, F; Pérez, C J; Arias-Nicolás, J P; Martín, J

    2013-10-01

    A novel method to classify multi-class biomedical objects is presented. The method is based on a hybrid approach which combines pairwise comparison, Bayesian regression and the k-nearest neighbor technique. It can be applied in a fully automatic way or in a relevance feedback framework. In the latter case, the information obtained from both an expert and the automatic classification is iteratively used to improve the results until a certain accuracy level is achieved, then, the learning process is finished and new classifications can be automatically performed. The method has been applied in two biomedical contexts by following the same cross-validation schemes as in the original studies. The first one refers to cancer diagnosis, leading to an accuracy of 77.35% versus 66.37%, originally obtained. The second one considers the diagnosis of pathologies of the vertebral column. The original method achieves accuracies ranging from 76.5% to 96.7%, and from 82.3% to 97.1% in two different cross-validation schemes. Even with no supervision, the proposed method reaches 96.71% and 97.32% in these two cases. By using a supervised framework the achieved accuracy is 97.74%. Furthermore, all abnormal cases were correctly classified.

  14. Hybrid computing using a neural network with dynamic external memory.

    Science.gov (United States)

    Graves, Alex; Wayne, Greg; Reynolds, Malcolm; Harley, Tim; Danihelka, Ivo; Grabska-Barwińska, Agnieszka; Colmenarejo, Sergio Gómez; Grefenstette, Edward; Ramalho, Tiago; Agapiou, John; Badia, Adrià Puigdomènech; Hermann, Karl Moritz; Zwols, Yori; Ostrovski, Georg; Cain, Adam; King, Helen; Summerfield, Christopher; Blunsom, Phil; Kavukcuoglu, Koray; Hassabis, Demis

    2016-10-27

    Artificial neural networks are remarkably adept at sensory processing, sequence learning and reinforcement learning, but are limited in their ability to represent variables and data structures and to store data over long timescales, owing to the lack of an external memory. Here we introduce a machine learning model called a differentiable neural computer (DNC), which consists of a neural network that can read from and write to an external memory matrix, analogous to the random-access memory in a conventional computer. Like a conventional computer, it can use its memory to represent and manipulate complex data structures, but, like a neural network, it can learn to do so from data. When trained with supervised learning, we demonstrate that a DNC can successfully answer synthetic questions designed to emulate reasoning and inference problems in natural language. We show that it can learn tasks such as finding the shortest path between specified points and inferring the missing links in randomly generated graphs, and then generalize these tasks to specific graphs such as transport networks and family trees. When trained with reinforcement learning, a DNC can complete a moving blocks puzzle in which changing goals are specified by sequences of symbols. Taken together, our results demonstrate that DNCs have the capacity to solve complex, structured tasks that are inaccessible to neural networks without external read-write memory.

  15. Identification of Cannabis sativa L. using the 1-kbTHCA synthase-fluorescence in situ hybridization probe.

    Science.gov (United States)

    Jeangkhwoa, Pattraporn; Bandhaya, Achirapa; Umpunjun, Puangpaka; Chuenboonngarm, Ngarmnij; Panvisavas, Nathinee

    2017-03-01

    This study reports a successful application of fluorescence in situ hybridization (FISH) technique in the identification of Cannabis sativa L. cells recovered from fresh and dried powdered plant materials. Two biotin-16-dUTP-labeled FISH probes were designed from the Cannabis-specific tetrahydrocannabinolic acid synthase (THCAS) gene and the ITS region of the 45S rRNA gene. Specificity of probe-target hybridization was tested against the target and 4 non-target plant species, i.e., Humulus lupulus, Mitragyna speciosa, Papaver sp., and Nicotiana tabacum. The 1-kb THCA synthase hybridization probe gave Cannabis-specific hybridization signals, unlike the 700-bp Cannabis-ITS hybridization probe. Probe-target hybridization was also confirmed against 20 individual Cannabis plant samples. The 1-kb THCA synthase and 700-bp Cannabis-ITS hybridization probes clearly showed 2 hybridization signals per cell with reproducibility. The 1-kb THCA synthase probe did not give any FISH signal when tested against H. lupulus, its closely related member of the Canabaceae family. It was also showed that 1-kb THCA synthase FISH probe can be applied to identify small amount of dried powdered Cannabis material with an addition of rehydration step prior to the experimental process. This study provided an alternative identification method for Cannabis trace. Copyright © 2016. Published by Elsevier B.V.

  16. Petascale computation performance of lightweight multiscale cardiac models using hybrid programming models.

    Science.gov (United States)

    Pope, Bernard J; Fitch, Blake G; Pitman, Michael C; Rice, John J; Reumann, Matthias

    2011-01-01

    Future multiscale and multiphysics models must use the power of high performance computing (HPC) systems to enable research into human disease, translational medical science, and treatment. Previously we showed that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message passing processes (e.g. the message passing interface (MPI)) with multithreading (e.g. OpenMP, POSIX pthreads). The objective of this work is to compare the performance of such hybrid programming models when applied to the simulation of a lightweight multiscale cardiac model. Our results show that the hybrid models do not perform favourably when compared to an implementation using only MPI which is in contrast to our results using complex physiological models. Thus, with regards to lightweight multiscale cardiac models, the user may not need to increase programming complexity by using a hybrid programming approach. However, considering that model complexity will increase as well as the HPC system size in both node count and number of cores per node, it is still foreseeable that we will achieve faster than real time multiscale cardiac simulations on these systems using hybrid programming models.

  17. Hybrid slime mould-based system for unconventional computing

    Science.gov (United States)

    Berzina, T.; Dimonte, A.; Cifarelli, A.; Erokhin, V.

    2015-04-01

    Physarum polycephalum is considered to be promising for the realization of unconventional computational systems. In this work, we present results of three slime mould-based systems. We have demonstrated the possibility of transporting biocompatible microparticles using attractors, repellents and a DEFLECTOR. The latter is an external tool that enables to conduct Physarum motion. We also present interactions between slime mould and conducting polymers, resulting in a variation of their colour and conductivity. Finally, incorporation of the Physarum into the organic memristive device resulted in a variation of its electrical characteristics due to the slime mould internal activity.

  18. Multi-resolution Analysis of Multi-spectral Palmprints using Hybrid Wavelets for Identification

    Directory of Open Access Journals (Sweden)

    Dr. H.B. Kekre

    2013-04-01

    Full Text Available Palmprint is a relatively new physiological biometric used in identification systems due to its stable and unique characteristics. The vivid texture information of palmprint present at different resolutions offers abundant prospects in personal recognition. This paper describes a new method to authenticate individuals based on palmprint identification. In order to analyze the texture information at various resolutions, we introduce a new hybrid wavelet, which is generated using two or more component transforms incorporating both their properties. A unique property of this wavelet is its flexibility to vary the number of components at each level of resolution and hence can be made suitable for various applications. Multi-spectral palmprints have been identified using energy compaction of the hybrid wavelet transform coefficients. The scores generated for each set of palmprint images under red, green and blue illuminations are combined using score-level fusion using AND and OR operators. Comparatively low values of equal error rate and high security index have been obtained for all fusion techniques. The experimental results demonstrate the effectiveness and accuracy of the proposed method.

  19. Identification and Purity Test of Super Hybrid Rice with SSR Molecular Markers

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Five super hybrid rice combinations, i.e. HYS-1/R105, Pei'ai 64S/E32, Liangyoupeijiu (Pei'ai 64S/9311 ), 88S/0293, and J23A/Q611, and their parental lines were tested by means of SSR analysis. A total of 144 SSR primer pairs distributed on 12 rice chromosomes were used, out of which 47 detected polymorphism among the tested rice lines. Among all these primers, RM337 and RM154 produced polymorphic patterns in four or more of the tested experimental materials respectively, and they could distinguish among most rice genotypes tested. Twenty-four primer pairs, two on each rice chromosome, were selected to make a reference SSR marker-based fingerprinting for the rice lines. For most of the primer pairs, F1 hybrids mainly showed complementary pattern of both parents, which could be very useful to distinguish the F1 from its parental lines. In addition, 5 primer pairs were selected as special primer pairs for five hybrid rice combinations respectively. By combining the rapid, simple method on DNA extraction, it is suggested that SSR technique has wide prospective in variety authentication and purity identification.

  20. All-optical quantum computing with a hybrid solid-state processing unit

    CERN Document Server

    Pei, Pei; Li, Chong

    2011-01-01

    We develop an architecture of hybrid quantum solid-state processing unit for universal quantum computing. The architecture allows distant and nonidentical solid-state qubits in distinct physical systems to interact and work collaboratively. All the quantum computing procedures are controlled by optical methods using classical fields and cavity QED. Our methods have prominent advantage of the insensitivity to dissipation process due to the virtual excitation of subsystems. Moreover, the QND measurements and state transfer for the solid-state qubits are proposed. The architecture opens promising perspectives for implementing scalable quantum computation in a broader sense that different solid systems can merge and be integrated into one quantum processor afterwards.

  1. Special purpose hybrid transfinite elements and unified computational methodology for accurately predicting thermoelastic stress waves

    Science.gov (United States)

    Tamma, Kumar K.; Railkar, Sudhir B.

    1988-01-01

    This paper represents an attempt to apply extensions of a hybrid transfinite element computational approach for accurately predicting thermoelastic stress waves. The applicability of the present formulations for capturing the thermal stress waves induced by boundary heating for the well known Danilovskaya problems is demonstrated. A unique feature of the proposed formulations for applicability to the Danilovskaya problem of thermal stress waves in elastic solids lies in the hybrid nature of the unified formulations and the development of special purpose transfinite elements in conjunction with the classical Galerkin techniques and transformation concepts. Numerical test cases validate the applicability and superior capability to capture the thermal stress waves induced due to boundary heating.

  2. Application of Computational Intelligence in Order to Develop Hybrid Orbit Propagation Methods

    Directory of Open Access Journals (Sweden)

    Iván Pérez

    2013-01-01

    Full Text Available We present a new approach in astrodynamics and celestial mechanics fields, called hybrid perturbation theory. A hybrid perturbation theory combines an integrating technique, general perturbation theory or special perturbation theory or semianalytical method, with a forecasting technique, statistical time series model or computational intelligence method. This combination permits an increase in the accuracy of the integrating technique, through the modeling of higher-order terms and other external forces not considered in the integrating technique. In this paper, neural networks have been used as time series forecasters in order to help two economic general perturbation theories describe the motion of an orbiter only perturbed by the Earth’s oblateness.

  3. Computational RNomics:Structure identification and functional prediction of non-coding RNAs in silico

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The eukaryotic genome contains varying numbers of non-coding RNA(ncRNA) genes."Computational RNomics" takes a multidisciplinary approach,like information science,to resolve the structure and function of ncRNAs.Here,we review the main issues in "Computational RNomics" of data storage and management,ncRNA gene identification and characterization,ncRNA target identification and functional prediction,and we summarize the main methods and current content of "computational RNomics".

  4. Hybrid VLSI/QCA Architecture for Computing FFTs

    Science.gov (United States)

    Fijany, Amir; Toomarian, Nikzad; Modarres, Katayoon; Spotnitz, Matthew

    2003-01-01

    A data-processor architecture that would incorporate elements of both conventional very-large-scale integrated (VLSI) circuitry and quantum-dot cellular automata (QCA) has been proposed to enable the highly parallel and systolic computation of fast Fourier transforms (FFTs). The proposed circuit would complement the QCA-based circuits described in several prior NASA Tech Briefs articles, namely Implementing Permutation Matrices by Use of Quantum Dots (NPO-20801), Vol. 25, No. 10 (October 2001), page 42; Compact Interconnection Networks Based on Quantum Dots (NPO-20855) Vol. 27, No. 1 (January 2003), page 32; and Bit-Serial Adder Based on Quantum Dots (NPO-20869), Vol. 27, No. 1 (January 2003), page 35. The cited prior articles described the limitations of very-large-scale integrated (VLSI) circuitry and the major potential advantage afforded by QCA. To recapitulate: In a VLSI circuit, signal paths that are required not to interact with each other must not cross in the same plane. In contrast, for reasons too complex to describe in the limited space available for this article, suitably designed and operated QCAbased signal paths that are required not to interact with each other can nevertheless be allowed to cross each other in the same plane without adverse effect. In principle, this characteristic could be exploited to design compact, coplanar, simple (relative to VLSI) QCA-based networks to implement complex, advanced interconnection schemes.

  5. Secure Data Sharing in Cloud Computing using Hybrid cloud

    Directory of Open Access Journals (Sweden)

    Er. Inderdeep Singh

    2015-06-01

    Full Text Available Cloud computing is fast growing technology that enables the users to store and access their data remotely. Using cloud services users can enjoy the benefits of on-demand cloud applications and data with limited local infrastructure available with them. While accessing the data from cloud, different users may have relationship among them depending on some attributes, and thus sharing of data along with user privacy and data security becomes important to get effective results. Most of the research has been done to secure the data authentication so that user’s don’t lose their private data stored on public cloud. But still data sharing is a significant hurdle to overcome by researchers. Research is going on to provide secure data sharing with enhanced user privacy and data access security. In this paper various research and challenges in this area are discussed in detail. It will definitely help the cloud users to understand the topic and researchers to develop a method to overcome these challenges.

  6. UCIMssp: Ubiquitous Computing Identification Mechanism Based on SPKI/SDSI and P2P

    Institute of Scientific and Technical Information of China (English)

    SUN Dao-qing; PU Fang; CAO Qi-ying

    2008-01-01

    Ubiquitous computing systems typically have lots of security problems in the area of identification supply by means of classical Public Key Infrastructure(PKI)methods.The limited computing resources,the disconnection network,the classification requirements of ideatification,the requirement of trust transfer and cross identification,the bidirectional identification,the security delegation and the privacy protection etc are all these unsolved problems.In this paper,UCIMssp,a new novel ubiquitous computing identification mechanism based on SPKI/SDSI and Peer-to-Peer(P2P)is presented.SPKI based authorization Is exploited in UCIMssp to solve the above problems in the small-scale ubiquitous computing environment.The DHT and flooding technology of P2P overlay network over the Internet is expanded to solve the routing search in the large-scale ubiquitous computing environment.The architecture of ubiquitous computing environment,the validation of identification requisition,the identification authorization processes and the identification supply processes etc of UCIMssp are described in the paper.The performance analysis shows that UCIMssp is a suitable security solution used in the large-scale ubiquitous computing environment.

  7. Computational identification of strain-, species- and genus-specific proteins

    Directory of Open Access Journals (Sweden)

    Thiagarajan Rathi

    2005-11-01

    Full Text Available Abstract Background The identification of unique proteins at different taxonomic levels has both scientific and practical value. Strain-, species- and genus-specific proteins can provide insight into the criteria that define an organism and its relationship with close relatives. Such proteins can also serve as taxon-specific diagnostic targets. Description A pipeline using a combination of computational and manual analyses of BLAST results was developed to identify strain-, species-, and genus-specific proteins and to catalog the closest sequenced relative for each protein in a proteome. Proteins encoded by a given strain are preliminarily considered to be unique if BLAST, using a comprehensive protein database, fails to retrieve (with an e-value better than 0.001 any protein not encoded by the query strain, species or genus (for strain-, species- and genus-specific proteins respectively, or if BLAST, using the best hit as the query (reverse BLAST, does not retrieve the initial query protein. Results are manually inspected for homology if the initial query is retrieved in the reverse BLAST but is not the best hit. Sequences unlikely to retrieve homologs using the default BLOSUM62 matrix (usually short sequences are re-tested using the PAM30 matrix, thereby increasing the number of retrieved homologs and increasing the stringency of the search for unique proteins. The above protocol was used to examine several food- and water-borne pathogens. We find that the reverse BLAST step filters out about 22% of proteins with homologs that would otherwise be considered unique at the genus and species levels. Analysis of the annotations of unique proteins reveals that many are remnants of prophage proteins, or may be involved in virulence. The data generated from this study can be accessed and further evaluated from the CUPID (Core and Unique Protein Identification system web site (updated semi-annually at http://pir.georgetown.edu/cupid. Conclusion CUPID

  8. Fatigue of hybrid glass/carbon composites: 3D computational studies

    DEFF Research Database (Denmark)

    Dai, Gaoming; Mishnaevsky, Leon

    2014-01-01

    3D computational simulations of fatigue of hybrid carbon/glass fiber reinforced composites is carried out using X-FEM and multifiber unit cell models. A new software code for the automatic generation of unit cell multifiber models of composites with randomly misaligned fibers of various properties...... and geometrical parameters is developed. With the use of this program code and the X-FEM method, systematic investigations of the effect of microstructure of hybrid composites (fraction of carbon versus glass fibers, misalignment, and interface strength) and the loading conditions (tensile versus compression...... cyclic loading effects) on fatigue behavior of the materials are carried out. It was demonstrated that the higher fraction of carbon fibers in hybrid composites is beneficial for the fatigue lifetime of the composites under tension-tension cyclic loading, but might have negative effect on the lifetime...

  9. Decoding of four movement directions using hybrid NIRS-EEG brain-computer interface

    Directory of Open Access Journals (Sweden)

    M. Jawad Khan

    2014-04-01

    Full Text Available The hybrid brain-computer interface (BCI’s multimodal technology enables precision brain-signal classification that can be used in the formulation of control commands. In the present study, an experimental hybrid near-infrared spectroscopy-electroencephalography (NIRS-EEG technique was used to extract and decode four different types of brain signals. The NIRS setup was positioned over the prefrontal brain region, and the EEG over the left and right motor cortex regions. Twelve subjects participating in the experiment were shown four direction symbols, namely, forward, backward, left and right. The control commands for forward and backward movement were estimated by performing arithmetic mental tasks related to oxy-hemoglobin (HbO changes. The left and right directions commands were associated with right and left hand tapping, respectively. The high classification accuracies achieved showed that the four different control signals can be accurately estimated using the hybrid NIRS-EEG technology.

  10. Carbon nanotube reinforced hybrid composites: Computational modeling of environmental fatigue and usability for wind blades

    DEFF Research Database (Denmark)

    Dai, Gaoming; Mishnaevsky, Leon

    2015-01-01

    The potential of advanced carbon/glass hybrid reinforced composites with secondary carbon nanotube reinforcement for wind energy applications is investigated here with the use of computational experiments. Fatigue behavior of hybrid as well as glass and carbon fiber reinforced composites...... with and without secondary CNT reinforcement is simulated using multiscale 3D unit cells. The materials behavior under both mechanical cyclic loading and combined mechanical and environmental loading (with phase properties degraded due to the moisture effects) is studied. The multiscale unit cells are generated...... with the secondary CNT reinforcements (especially, aligned tubes) present superior fatigue performances than those without reinforcements, also under combined environmental and cyclic mechanical loading. This effect is stronger for carbon composites, than for hybrid and glass composites....

  11. Applications integration in a hybrid cloud computing environment: modelling and platform

    Science.gov (United States)

    Li, Qing; Wang, Ze-yuan; Li, Wei-hua; Li, Jun; Wang, Cheng; Du, Rui-yang

    2013-08-01

    With the development of application services providers and cloud computing, more and more small- and medium-sized business enterprises use software services and even infrastructure services provided by professional information service companies to replace all or part of their information systems (ISs). These information service companies provide applications, such as data storage, computing processes, document sharing and even management information system services as public resources to support the business process management of their customers. However, no cloud computing service vendor can satisfy the full functional IS requirements of an enterprise. As a result, enterprises often have to simultaneously use systems distributed in different clouds and their intra enterprise ISs. Thus, this article presents a framework to integrate applications deployed in public clouds and intra ISs. A run-time platform is developed and a cross-computing environment process modelling technique is also developed to improve the feasibility of ISs under hybrid cloud computing environments.

  12. Computer-aided identification of polymorphism sets diagnostic for groups of bacterial and viral genetic variants

    Directory of Open Access Journals (Sweden)

    Huygens Flavia

    2007-08-01

    Full Text Available Abstract Background Single nucleotide polymorphisms (SNPs and genes that exhibit presence/absence variation have provided informative marker sets for bacterial and viral genotyping. Identification of marker sets optimised for these purposes has been based on maximal generalized discriminatory power as measured by Simpson's Index of Diversity, or on the ability to identify specific variants. Here we describe the Not-N algorithm, which is designed to identify small sets of genetic markers diagnostic for user-specified subsets of known genetic variants. The algorithm does not treat the user-specified subset and the remaining genetic variants equally. Rather Not-N analysis is designed to underpin assays that provide 0% false negatives, which is very important for e.g. diagnostic procedures for clinically significant subgroups within microbial species. Results The Not-N algorithm has been incorporated into the "Minimum SNPs" computer program and used to derive genetic markers diagnostic for multilocus sequence typing-defined clonal complexes, hepatitis C virus (HCV subtypes, and phylogenetic clades defined by comparative genome hybridization (CGH data for Campylobacter jejuni, Yersinia enterocolitica and Clostridium difficile. Conclusion Not-N analysis is effective for identifying small sets of genetic markers diagnostic for microbial sub-groups. The best results to date have been obtained with CGH data from several bacterial species, and HCV sequence data.

  13. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    OpenAIRE

    Lukas Falat; Dusan Marcek; Maria Durisova

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the sug...

  14. Solving Problems in Various Domains by Hybrid Models of High Performance Computations

    Directory of Open Access Journals (Sweden)

    Yurii Rogozhin

    2014-03-01

    Full Text Available This work presents a hybrid model of high performance computations. The model is based on membrane system (P~system where some membranes may contain quantum device that is triggered by the data entering the membrane. This model is supposed to take advantages of both biomolecular and quantum paradigms and to overcome some of their inherent limitations. The proposed approach is demonstrated through two selected problems: SAT, and image retrieving.

  15. Identification of natural images and computer-generated graphics based on statistical and textural features.

    Science.gov (United States)

    Peng, Fei; Li, Jiao-ting; Long, Min

    2015-03-01

    To discriminate the acquisition pipelines of digital images, a novel scheme for the identification of natural images and computer-generated graphics is proposed based on statistical and textural features. First, the differences between them are investigated from the view of statistics and texture, and 31 dimensions of feature are acquired for identification. Then, LIBSVM is used for the classification. Finally, the experimental results are presented. The results show that it can achieve an identification accuracy of 97.89% for computer-generated graphics, and an identification accuracy of 97.75% for natural images. The analyses also demonstrate the proposed method has excellent performance, compared with some existing methods based only on statistical features or other features. The method has a great potential to be implemented for the identification of natural images and computer-generated graphics. © 2014 American Academy of Forensic Sciences.

  16. Bayesian mixture modeling using a hybrid sampler with application to protein subfamily identification.

    Science.gov (United States)

    Fong, Youyi; Wakefield, Jon; Rice, Kenneth

    2010-01-01

    Predicting protein function is essential to advancing our knowledge of biological processes. This article is focused on discovering the functional diversification within a protein family. A Bayesian mixture approach is proposed to model a protein family as a mixture of profile hidden Markov models. For a given mixture size, a hybrid Markov chain Monte Carlo sampler comprising both Gibbs sampling steps and hierarchical clustering-based split/merge proposals is used to obtain posterior inference. Inference for mixture size concentrates on comparing the integrated likelihoods. The choice of priors is critical with respect to the performance of the procedure. Through simulation studies, we show that 2 priors that are based on independent data sets allow correct identification of the mixture size, both when the data are homogeneous and when the data are generated from a mixture. We illustrate our method using 2 sets of real protein sequences.

  17. Performance of hybrid programming models for multiscale cardiac simulations: preparing for petascale computation.

    Science.gov (United States)

    Pope, Bernard J; Fitch, Blake G; Pitman, Michael C; Rice, John J; Reumann, Matthias

    2011-10-01

    Future multiscale and multiphysics models that support research into human disease, translational medical science, and treatment can utilize the power of high-performance computing (HPC) systems. We anticipate that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message-passing processes [e.g., the message-passing interface (MPI)] with multithreading (e.g., OpenMP, Pthreads). The objective of this study is to compare the performance of such hybrid programming models when applied to the simulation of a realistic physiological multiscale model of the heart. Our results show that the hybrid models perform favorably when compared to an implementation using only the MPI and, furthermore, that OpenMP in combination with the MPI provides a satisfactory compromise between performance and code complexity. Having the ability to use threads within MPI processes enables the sophisticated use of all processor cores for both computation and communication phases. Considering that HPC systems in 2012 will have two orders of magnitude more cores than what was used in this study, we believe that faster than real-time multiscale cardiac simulations can be achieved on these systems.

  18. Computationally efficient double hybrid density functional theory using dual basis methods

    CERN Document Server

    Byrd, Jason N

    2015-01-01

    We examine the application of the recently developed dual basis methods of Head-Gordon and co-workers to double hybrid density functional computations. Using the B2-PLYP, B2GP-PLYP, DSD-BLYP and DSD-PBEP86 density functionals, we assess the performance of dual basis methods for the calculation of conformational energy changes in C$_4$-C$_7$ alkanes and for the S22 set of noncovalent interaction energies. The dual basis methods, combined with resolution-of-the-identity second-order M{\\o}ller-Plesset theory, are shown to give results in excellent agreement with conventional methods at a much reduced computational cost.

  19. Usability Studies in Virtual and Traditional Computer Aided Design Environments for Fault Identification

    Science.gov (United States)

    2017-08-08

    IDENTIFICATION) 1. Description In a typical design review process, a design space is presented to the reviewer(s) who examine the space for design ...Usability Studies In Virtual And Traditional Computer Aided Design Environments For Fault Identification Dr. Syed Adeel Ahmed, Xavier University...sacrificing accuracy. The research team timed each task, and recorded activity on evaluation sheets for Fault Identification Test. At the

  20. Identification and characterization of a de novo partial trisomy 10p by comparative genomic hybridization (CGH).

    Science.gov (United States)

    Benzacken, B; Lapierre, J M; Siffroi, J P; Chalvon, A; Tachdjian, G

    1998-10-01

    We report the characterization of a de novo unbalanced chromosome rearrangement by comparative genomic hybridization (CGH) in a 15-day-old child with hypotonia and dysmorphia. We describe the combined use of CGH and fluorescence in situ hybridization (FISH) to identify the origin of the additional chromosomal material on the short arm of chromosome 6. Investigation with FISH revealed that the excess material was not derived from chromosome 6. Identification of unknown unbalanced aberrations that could not be identified by traditional cytogenetics procedures is possible by CGH analysis. Visual analysis of digital images from CGH-metaphase spreads revealed a predominantly green signal on the telomeric region of chromosome 10p. After quantitative digital ratio imaging of 10 CGH-metaphase spreads, a region of gain was found in the chromosome band 10p14-pter. The CGH finding was confirmed by FISH analysis, using a whole chromosome 10 paint probe. These results show the usefulness of CGH for a rapid characterization of de novo unbalanced translocation, unidentifiable by karyotype alone.

  1. Site-specific identification of heparan and chondroitin sulfate glycosaminoglycans in hybrid proteoglycans

    Science.gov (United States)

    Noborn, Fredrik; Gomez Toledo, Alejandro; Green, Anders; Nasir, Waqas; Sihlbom, Carina; Nilsson, Jonas; Larson, Göran

    2016-01-01

    Heparan sulfate (HS) and chondroitin sulfate (CS) are complex polysaccharides that regulate important biological pathways in virtually all metazoan organisms. The polysaccharides often display opposite effects on cell functions with HS and CS structural motifs presenting unique binding sites for specific ligands. Still, the mechanisms by which glycan biosynthesis generates complex HS and CS polysaccharides required for the regulation of mammalian physiology remain elusive. Here we present a glycoproteomic approach that identifies and differentiates between HS and CS attachment sites and provides identity to the core proteins. Glycopeptides were prepared from perlecan, a complex proteoglycan known to be substituted with both HS and CS chains, further digested with heparinase or chondroitinase ABC to reduce the HS and CS chain lengths respectively, and thereafter analyzed by nLC-MS/MS. This protocol enabled the identification of three consensus HS sites and one hybrid site, carrying either a HS or a CS chain. Inspection of the amino acid sequence at the hybrid attachment locus indicates that certain peptide motifs may encode for the chain type selection process. This analytical approach will become useful when addressing fundamental questions in basic biology specifically in elucidating the functional roles of site-specific glycosylations of proteoglycans. PMID:27694851

  2. Hybrid EEG—Eye Tracker: Automatic Identification and Removal of Eye Movement and Blink Artifacts from Electroencephalographic Signal

    Directory of Open Access Journals (Sweden)

    Malik M. Naeem Mannan

    2016-02-01

    Full Text Available Contamination of eye movement and blink artifacts in Electroencephalogram (EEG recording makes the analysis of EEG data more difficult and could result in mislead findings. Efficient removal of these artifacts from EEG data is an essential step in improving classification accuracy to develop the brain-computer interface (BCI. In this paper, we proposed an automatic framework based on independent component analysis (ICA and system identification to identify and remove ocular artifacts from EEG data by using hybrid EEG and eye tracker system. The performance of the proposed algorithm is illustrated using experimental and standard EEG datasets. The proposed algorithm not only removes the ocular artifacts from artifactual zone but also preserves the neuronal activity related EEG signals in non-artifactual zone. The comparison with the two state-of-the-art techniques namely ADJUST based ICA and REGICA reveals the significant improved performance of the proposed algorithm for removing eye movement and blink artifacts from EEG data. Additionally, results demonstrate that the proposed algorithm can achieve lower relative error and higher mutual information values between corrected EEG and artifact-free EEG data.

  3. Hybrid EEG--Eye Tracker: Automatic Identification and Removal of Eye Movement and Blink Artifacts from Electroencephalographic Signal.

    Science.gov (United States)

    Mannan, Malik M Naeem; Kim, Shinjung; Jeong, Myung Yung; Kamran, M Ahmad

    2016-02-19

    Contamination of eye movement and blink artifacts in Electroencephalogram (EEG) recording makes the analysis of EEG data more difficult and could result in mislead findings. Efficient removal of these artifacts from EEG data is an essential step in improving classification accuracy to develop the brain-computer interface (BCI). In this paper, we proposed an automatic framework based on independent component analysis (ICA) and system identification to identify and remove ocular artifacts from EEG data by using hybrid EEG and eye tracker system. The performance of the proposed algorithm is illustrated using experimental and standard EEG datasets. The proposed algorithm not only removes the ocular artifacts from artifactual zone but also preserves the neuronal activity related EEG signals in non-artifactual zone. The comparison with the two state-of-the-art techniques namely ADJUST based ICA and REGICA reveals the significant improved performance of the proposed algorithm for removing eye movement and blink artifacts from EEG data. Additionally, results demonstrate that the proposed algorithm can achieve lower relative error and higher mutual information values between corrected EEG and artifact-free EEG data.

  4. Secure Human-Computer Identification against Peeping Attacks (SecHCI): A Survey

    OpenAIRE

    Li, SJ; Shum, HY

    2003-01-01

    This paper focuses on human-computer identification systems against peeping attacks, in which adversaries can observe (and even control) interactions between humans (provers) and computers (verifiers). Real cases on peeping attacks were reported by Ross J. Anderson ten years before. Fixed passwords are insecure to peeping attacks since adversaries can simply replay the observed passwords. Some identification techniques can be used to defeat peeping attacks, but auxiliary devices must be used ...

  5. Detection and identification of beta-lactam residues in milk using a hybrid biosensor.

    Science.gov (United States)

    Ferrini, Anna Maria; Mannoni, Veruscka; Carpico, Graziella; Pellegrini, Guido Enrico

    2008-02-13

    A novel application of a hybrid biosensor is here employed as an analytical method for the detection and presumptive identification of beta-lactam residues in milk. The method is based on measurements of carbon dioxide (CO2), the production of which is related to the microbial growth of the test microorganism Bacillus stearothermophilus var. calidolactis. The presence of beta-lactams in milk inhibits microbial growth and, consequently, the CO2 production rate. The analysis is based on the variation of CO2 between a milk sample spiked with beta-lactams and a twin milk sample containing beta-lactams plus a broad spectrum beta-lactamase, using an electrochemical device of biosensor. A blank milk sample is included as control. The result is obtained starting from the first 120 min. Moreover, the ability to recognize all of the beta-lactams speeds the total time of analysis when chemical identification and quantification are required. The analytical method appears to be adequate for milk control for qualitative screening purposes, complying with the requirements stated in Decision 2002/657/EC.

  6. 16th International Conference on Hybrid Intelligent Systems and the 8th World Congress on Nature and Biologically Inspired Computing

    CERN Document Server

    Haqiq, Abdelkrim; Alimi, Adel; Mezzour, Ghita; Rokbani, Nizar; Muda, Azah

    2017-01-01

    This book presents the latest research in hybrid intelligent systems. It includes 57 carefully selected papers from the 16th International Conference on Hybrid Intelligent Systems (HIS 2016) and the 8th World Congress on Nature and Biologically Inspired Computing (NaBIC 2016), held on November 21–23, 2016 in Marrakech, Morocco. HIS - NaBIC 2016 was jointly organized by the Machine Intelligence Research Labs (MIR Labs), USA; Hassan 1st University, Settat, Morocco and University of Sfax, Tunisia. Hybridization of intelligent systems is a promising research field in modern artificial/computational intelligence and is concerned with the development of the next generation of intelligent systems. The conference’s main aim is to inspire further exploration of the intriguing potential of hybrid intelligent systems and bio-inspired computing. As such, the book is a valuable resource for practicing engineers /scientists and researchers working in the field of computational intelligence and artificial intelligence.

  7. A Program for the Identification of the Enterobacteriaceae for Use in Teaching the Principles of Computer Identification of Bacteria.

    Science.gov (United States)

    Hammonds, S. J.

    1990-01-01

    A technique for the numerical identification of bacteria using normalized likelihoods calculated from a probabilistic database is described, and the principles of the technique are explained. The listing of the computer program is included. Specimen results from the program, and examples of how they should be interpreted, are given. (KR)

  8. Computer-Aided Design of Drugs on Emerging Hybrid High Performance Computers

    Science.gov (United States)

    2013-09-01

    Clustering using MapReduce , Workshop on Trends in High-Performance Distributed Computing, Vrije Universiteit, Amsterdam, NL. (Invited Talk) [25] February...and middleware packages for polarizable force fields on multi-core and GPU systems, supported by the MapReduce paradigm. NSF MRI #0922657, $451,051...High-throughput Molecular Datasets for Scalable Clustering using MapReduce , Workshop on Trends in High-Performance Distributed Computing, Vrije

  9. Hybrid imbalanced data classifier models for computational discovery of antibiotic drug targets.

    Science.gov (United States)

    Kocyigit, Yucel; Seker, Huseyin

    2014-01-01

    Identification of drug candidates is an important but also difficult process. Given drug resistance bacteria that we face, this process has become more important to identify protein candidates that demonstrate antibacterial activity. The aim of this study is therefore to develop a bioinformatics approach that is more capable of identifying a small but effective set of proteins that are expected to show antibacterial activity, subsequently to be used as antibiotic drug targets. As this is regarded as an imbalanced data classification problem due to smaller number of antibiotic drugs available, a hybrid classification model was developed and applied to the identification of antibiotic drugs. The model was developed by taking into account of various statistical models leading to the development of six different hybrid models. The best model has reached the accuracy of as high as 50% compared to earlier study with the accuracy of less than 1% as far as the proportion of the candidates identified and actual antibiotics in the candidate list is concerned.

  10. Improvement of Text Dependent Speaker Identification System Using Neuro-Genetic Hybrid Algorithm in Office Environmental Conditions

    Directory of Open Access Journals (Sweden)

    Md. Fayzur Rahman

    2009-08-01

    Full Text Available In this paper, an improved strategy for automated text dependent speaker identification system has been proposed in noisy environment. The identification process incorporates the Neuro-Genetic hybrid algorithm with cepstral based features. To remove the background noise from the source utterance, wiener filter has been used. Different speech pre-processing techniques such as start-end point detection algorithm, pre-emphasis filtering, frame blocking and windowing have been used to process the speech utterances. RCC, MFCC, ^MFCC, ^^MFCC, LPC and LPCC have been used to extract the features. After feature extraction of the speech, Neuro-Genetic hybrid algorithm has been used in the learning and identification purposes. Features are extracted by using different techniques to optimize the performance of the identification. According to the VALID speech database, the highest speaker identification rate of 100.000% for studio environment and 82.33% for office environmental conditions have been achieved in the close set text dependent speaker identification system.

  11. Hybrid Cloud Computing Environment for EarthCube and Geoscience Community

    Science.gov (United States)

    Yang, C. P.; Qin, H.

    2016-12-01

    The NSF EarthCube Integration and Test Environment (ECITE) has built a hybrid cloud computing environment to provides cloud resources from private cloud environments by using cloud system software - OpenStack and Eucalyptus, and also manages public cloud - Amazon Web Service that allow resource synchronizing and bursting between private and public cloud. On ECITE hybrid cloud platform, EarthCube and geoscience community can deploy and manage the applications by using base virtual machine images or customized virtual machines, analyze big datasets by using virtual clusters, and real-time monitor the virtual resource usage on the cloud. Currently, a number of EarthCube projects have deployed or started migrating their projects to this platform, such as CHORDS, BCube, CINERGI, OntoSoft, and some other EarthCube building blocks. To accomplish the deployment or migration, administrator of ECITE hybrid cloud platform prepares the specific needs (e.g. images, port numbers, usable cloud capacity, etc.) of each project in advance base on the communications between ECITE and participant projects, and then the scientists or IT technicians in those projects launch one or multiple virtual machines, access the virtual machine(s) to set up computing environment if need be, and migrate their codes, documents or data without caring about the heterogeneity in structure and operations among different cloud platforms.

  12. Rugoscopy: Human identification by computer-assisted photographic superimposition technique

    Directory of Open Access Journals (Sweden)

    Rezwana Begum Mohammed

    2013-01-01

    Full Text Available Background: Human identification has been studied since fourteenth century and it has gradually advanced for forensic purposes. Traditional methods such as dental, fingerprint, and DNA comparisons are probably the most common techniques used in this context, allowing fast and secure identification processes. But, in circumstances where identification of an individual by fingerprint or dental record comparison is difficult, palatal rugae may be considered as an alternative source of material. Aim: The present study was done to evaluate the individualistic nature and use of palatal rugae patterns for personal identification and also to test the efficiency of computerized software for forensic identification by photographic superimposition of palatal photographs obtained from casts. Materials and Methods: Two sets of Alginate impressions were made from the upper arches of 100 individuals (50 males and 50 females with one month interval in between and the casts were poured. All the teeth except the incisors were removed to ensure that only the palate could be used in identification process. In one set of the casts, the palatal rugae were highlighted with a graphite pencil. All the 200 casts were randomly numbered, and then, they were photographed with a 10.1 Mega Pixel Kodak digital camera using standardized method. Using computerized software, the digital photographs of the models without highlighting the palatal rugae were overlapped over the images (transparent of the palatal rugae with highlighted palatal rugae, in order to identify the pairs by superimposition technique. Incisors were remained and used as landmarks to determine the magnification required to bring the two set of photographs to the same size, in order to make perfect superimposition of images. Results: The result of the overlapping of the digital photographs of highlighted palatal rugae over normal set of models without highlighted palatal rugae resulted in 100% positive

  13. Prioritization of putative metabolite identifications in LC-MS/MS experiments using a computational pipeline.

    Science.gov (United States)

    Zhou, Bin; Xiao, Jun Feng; Ressom, Habtom W

    2013-01-01

    One of the major bottle-necks in current LC-MS-based metabolomic investigations is metabolite identification. An often-used approach is to first look up metabolites from databases through peak mass, followed by verification of the obtained putative identifications using MS/MS data. However, the mass-based search may provide inappropriate putative identifications when the observed peak is from isotopes, fragments, or adducts. In addition, a large fraction of peaks is often left with multiple putative identifications. To differentiate these putative identifications, manual verification of metabolites through comparison between biological samples and authentic compounds is necessary. However, such experiments are laborious, especially when multiple putative identifications are encountered. It is desirable to use computational approaches to obtain more reliable putative identifications and prioritize them before performing experimental verification of the metabolites. In this article, a computational pipeline is proposed to assist metabolite identification with improved metabolome coverage and prioritization capability. Multiple publicly available software tools and databases, along with in-house developed algorithms, are utilized to fully exploit the information acquired from LC-MS/MS experiments. The pipeline is successfully applied to identify metabolites on the basis of LC-MS as well as MS/MS data. Using accurate masses, retention time values, MS/MS spectra, and metabolic pathways/networks, more appropriate putative identifications are retrieved and prioritized to guide subsequent metabolite verification experiments.

  14. Contributions to Desktop Grid Computing : From High Throughput Computing to Data-Intensive Sciences on Hybrid Distributed Computing Infrastructures

    OpenAIRE

    Fedak, Gilles

    2015-01-01

    Since the mid 90’s, Desktop Grid Computing - i.e the idea of using a large number of remote PCs distributed on the Internet to execute large parallel applications - has proved to be an efficient paradigm to provide a large computational power at the fraction of the cost of a dedicated computing infrastructure.This document presents my contributions over the last decade to broaden the scope of Desktop Grid Computing. My research has followed three different directions. The first direction has ...

  15. Numerical approach for solving kinetic equations in two-dimensional case on hybrid computational clusters

    Science.gov (United States)

    Malkov, Ewgenij A.; Poleshkin, Sergey O.; Kudryavtsev, Alexey N.; Shershnev, Anton A.

    2016-10-01

    The paper presents the software implementation of the Boltzmann equation solver based on the deterministic finite-difference method. The solver allows one to carry out parallel computations of rarefied flows on a hybrid computational cluster with arbitrary number of central processor units (CPU) and graphical processor units (GPU). Employment of GPUs leads to a significant acceleration of the computations, which enables us to simulate two-dimensional flows with high resolution in a reasonable time. The developed numerical code was validated by comparing the obtained solutions with the Direct Simulation Monte Carlo (DSMC) data. For this purpose the supersonic flow past a flat plate at zero angle of attack is used as a test case.

  16. Hybrid annealing using a quantum simulator coupled to a classical computer

    CERN Document Server

    Graß, Tobias

    2016-01-01

    Finding the global minimum in a rugged potential landscape is a computationally hard task, often equivalent to relevant optimization problems. Simulated annealing is a computational technique which explores the configuration space by mimicking thermal noise. By slow cooling, it freezes the system in a low-energy configuration, but the algorithm often gets stuck in local minima. In quantum annealing, the thermal noise is replaced by controllable quantum fluctuations, and the technique can be implemented in modern quantum simulators. However, quantum-adiabatic schemes become prohibitively slow in the presence of quasidegeneracies. Here we propose a strategy which combines ideas from simulated annealing and quantum annealing. In such hybrid algorithm, the outcome of a quantum simulator is processed on a classical device. While the quantum simulator explores the configuration space by repeatedly applying quantum fluctuations and performing projective measurements, the classical computer evaluates each configurati...

  17. Step Response Enhancement of Hybrid Stepper Motors Using Soft Computing Techniques

    Directory of Open Access Journals (Sweden)

    Amged S. El-Wakeel

    2014-05-01

    Full Text Available This paper presents the use of different soft computing techniques for step response enhancement of Hybrid Stepper Motors. The basic differential equations of hybrid stepper motor are used to build up a model using MATLAB software package. The implementation of Fuzzy Logic (FL and Proportional-Integral-Derivative (PID controllers are used to improve the motor performance. The numerical simulations by a PC-based controller show that the PID controller tuned by Genetic Algorithm (GA produces better performance than that tuned by Fuzzy controller. They show that, the Fuzzy PID-like controller produces better performance than the other linear Fuzzy controllers. Finally, the comparison between PID controllers tuned by genetic algorithm and the Fuzzy PID-like controller shows that, the Fuzzy PID-like controller produces better performance.

  18. Nonlinear system identification with global and local soft computing methods

    Energy Technology Data Exchange (ETDEWEB)

    Runkler, T.A. [Siemens AG, Muenchen (Germany). Zentralabt. Technik Information und Kommunikation

    2000-10-01

    An important step in the design of control systems is system identification. Data driven system identification finds functional models for the system's input output behavior. Regression methods are simple and effective, but may cause overshoots for complicated characteristics. Neural network approaches such as the multilayer perceptron yield very accurate models, but are black box approaches which leads to problems in system and stability analysis. In contrast to these global modeling methods crisp and fuzzy rule bases represent local models that can be extracted from data by clustering methods. Depending on the type and number of models different degrees of model accuracy can be achieved. (orig.)

  19. Computational Identification of Mechanistic Factors That Determine the Timing and Intensity of the Inflammatory Response

    Science.gov (United States)

    2016-05-09

    Nagaraja, Jaques Reifman*, Alexander Y. Mitrophanov Department of Defense Biotechnology High Performance Computing Software Applications Institute...demonstrated the utility of mathematical models in the study of inflammation in specific disease scenarios and in the identification of crucial...of our simulations reflected a 20-day period after inflammation initiation. We performed all computations in the software suite MATLAB R2012a

  20. Contours identification of elements in a cone beam computed tomography for investigating maxillary cysts

    Science.gov (United States)

    Chioran, Doina; Nicoarǎ, Adrian; Roşu, Şerban; Cǎrligeriu, Virgil; Ianeş, Emilia

    2013-10-01

    Digital processing of two-dimensional cone beam computer tomography slicesstarts by identification of the contour of elements within. This paper deals with the collective work of specialists in medicine and applied mathematics in computer science on elaborating and implementation of algorithms in dental 2D imagery.

  1. The UF family of hybrid phantoms of the developing human fetus for computational radiation dosimetry

    Energy Technology Data Exchange (ETDEWEB)

    Maynard, Matthew R; Geyer, John W; Bolch, Wesley [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL (United States); Aris, John P [Department of Anatomy and Cell Biology, University of Florida, Gainesville, FL (United States); Shifrin, Roger Y, E-mail: wbolch@ufl.edu [Department of Radiology, University of Florida, Gainesville, FL (United States)

    2011-08-07

    Historically, the development of computational phantoms for radiation dosimetry has primarily been directed at capturing and representing adult and pediatric anatomy, with less emphasis devoted to models of the human fetus. As concern grows over possible radiation-induced cancers from medical and non-medical exposures of the pregnant female, the need to better quantify fetal radiation doses, particularly at the organ-level, also increases. Studies such as the European Union's SOLO (Epidemiological Studies of Exposed Southern Urals Populations) hope to improve our understanding of cancer risks following chronic in utero radiation exposure. For projects such as SOLO, currently available fetal anatomic models do not provide sufficient anatomical detail for organ-level dose assessment. To address this need, two fetal hybrid computational phantoms were constructed using high-quality magnetic resonance imaging and computed tomography image sets obtained for two well-preserved fetal specimens aged 11.5 and 21 weeks post-conception. Individual soft tissue organs, bone sites and outer body contours were segmented from these images using 3D-DOCTOR(TM) and then imported to the 3D modeling software package Rhinoceros(TM) for further modeling and conversion of soft tissue organs, certain bone sites and outer body contours to deformable non-uniform rational B-spline surfaces. The two specimen-specific phantoms, along with a modified version of the 38 week UF hybrid newborn phantom, comprised a set of base phantoms from which a series of hybrid computational phantoms was derived for fetal ages 8, 10, 15, 20, 25, 30, 35 and 38 weeks post-conception. The methodology used to construct the series of phantoms accounted for the following age-dependent parameters: (1) variations in skeletal size and proportion, (2) bone-dependent variations in relative levels of bone growth, (3) variations in individual organ masses and total fetal masses and (4) statistical percentile variations

  2. The UF family of hybrid phantoms of the developing human fetus for computational radiation dosimetry

    Science.gov (United States)

    Maynard, Matthew R.; Geyer, John W.; Aris, John P.; Shifrin, Roger Y.; Bolch, Wesley

    2011-08-01

    Historically, the development of computational phantoms for radiation dosimetry has primarily been directed at capturing and representing adult and pediatric anatomy, with less emphasis devoted to models of the human fetus. As concern grows over possible radiation-induced cancers from medical and non-medical exposures of the pregnant female, the need to better quantify fetal radiation doses, particularly at the organ-level, also increases. Studies such as the European Union's SOLO (Epidemiological Studies of Exposed Southern Urals Populations) hope to improve our understanding of cancer risks following chronic in utero radiation exposure. For projects such as SOLO, currently available fetal anatomic models do not provide sufficient anatomical detail for organ-level dose assessment. To address this need, two fetal hybrid computational phantoms were constructed using high-quality magnetic resonance imaging and computed tomography image sets obtained for two well-preserved fetal specimens aged 11.5 and 21 weeks post-conception. Individual soft tissue organs, bone sites and outer body contours were segmented from these images using 3D-DOCTOR™ and then imported to the 3D modeling software package Rhinoceros™ for further modeling and conversion of soft tissue organs, certain bone sites and outer body contours to deformable non-uniform rational B-spline surfaces. The two specimen-specific phantoms, along with a modified version of the 38 week UF hybrid newborn phantom, comprised a set of base phantoms from which a series of hybrid computational phantoms was derived for fetal ages 8, 10, 15, 20, 25, 30, 35 and 38 weeks post-conception. The methodology used to construct the series of phantoms accounted for the following age-dependent parameters: (1) variations in skeletal size and proportion, (2) bone-dependent variations in relative levels of bone growth, (3) variations in individual organ masses and total fetal masses and (4) statistical percentile variations in

  3. A hybrid model for the computationally-efficient simulation of the cerebellar granular layer

    Directory of Open Access Journals (Sweden)

    Anna eCattani

    2016-04-01

    Full Text Available The aim of the present paper is to efficiently describe the membrane potential dynamics of neural populations formed by species having a high density difference in specific brain areas. We propose a hybrid model whose main ingredients are a conductance-based model (ODE system and its continuous counterpart (PDE system obtained through a limit process in which the number of neurons confined in a bounded region of the brain tissue is sent to infinity. Specifically, in the discrete model, each cell is described by a set of time-dependent variables, whereas in the continuum model, cells are grouped into populations that are described by a set of continuous variables.Communications between populations, which translate into interactions among the discrete and the continuous models, are the essence of the hybrid model we present here. The cerebellum and cerebellum-like structures show in their granular layer a large difference in the relative density of neuronal species making them a natural testing ground for our hybrid model. By reconstructing the ensemble activity of the cerebellar granular layer network and by comparing our results to a more realistic computational network, we demonstrate that our description of the network activity, even though it is not biophysically detailed, is still capable of reproducing salient features of neural network dynamics. Our modeling approach yields a significant computational cost reduction by increasing the simulation speed at least $270$ times. The hybrid model reproduces interesting dynamics such as local microcircuit synchronization, traveling waves, center-surround and time-windowing.

  4. Identification of risk factors of computer information technologies in education.

    OpenAIRE

    Hrebniak M.P.; Shchudro S.A.; Yakimova K.O.

    2014-01-01

    The basic direction of development of secondary school and vocational training is computer training of schoolchildren and students, including distance forms of education and widespread usage of world information systems. The purpose of the work is to determine risk factors for schoolchildren and students, when using modern information and computer technologies. Results of researches allowed to establish dynamics of formation of skills using computer information technologies in education and c...

  5. Computational and experimental determinations of the UV adsorption of polyvinylsilsesquioxane-silica and titanium dioxide hybrids.

    Science.gov (United States)

    Wang, Haiyan; Lin, Derong; Wang, Di; Hu, Lijiang; Huang, Yudong; Liu, Li; Loy, Douglas A

    2014-01-01

    Sunscreens that absorb UV light without photodegradation could reduce skin cancer. Polyvinyl silsesquioxanes are known to have greater thermal and photochemical stability than organic compounds, such as those in sunscreens. This paper evaluates the UV transparency of vinyl silsesquioxanes (VS) and its hybrids with SiO2(VSTE) and TiO2(VSTT) experimentally and computationally. Based on films of VS prepared by sol-gel polymerization, using benzoyl peroxide as an initiator, vinyltrimethoxysilane (VMS) formulated oligomer through thermal curing. Similarly, VSTE films were prepared from VMS and 5-25 wt-% tetraethoxysilane (TEOS) and VSTT films were prepared from VMS and 5-25 wt-% titanium tetrabutoxide (TTB). Experimental average transparencies of the modified films were found to be about 9-14% between 280-320 nm, 67-73% between 320-350nm, and 86-89% between 350-400nm. Computation of the band gap was absorption edges for the hybrids in excellent agreement with experimental data. VS, VSTE and VSTT showed good absorption in UV-C and UV-B range, but absorbed virtually no UV-A. Addition of SiO2 or TiO2 does not improve UV-B absorption, but on the opposite increases transparency of thin films to UV. This increase was validated with molecular simulations. Results show computational design can predict better sunscreens and reduce the effort of creating sunscreens that are capable of absorbing more UV-B and UV-A.

  6. Higher Order Modeling in Hybrid Approaches to the Computation of Electromagnetic Fields

    Science.gov (United States)

    Wilton, Donald R.; Fink, Patrick W.; Graglia, Roberto D.

    2000-01-01

    Higher order geometry representations and interpolatory basis functions for computational electromagnetics are reviewed. Two types of vector-valued basis functions are described: curl-conforming bases, used primarily in finite element solutions, and divergence-conforming bases used primarily in integral equation formulations. Both sets satisfy Nedelec constraints, which optimally reduce the number of degrees of freedom required for a given order. Results are presented illustrating the improved accuracy and convergence properties of higher order representations for hybrid integral equation and finite element methods.

  7. Public vs Private vs Hybrid vs Community - Cloud Computing: A Critical Review

    Directory of Open Access Journals (Sweden)

    Sumit Goyal

    2014-02-01

    Full Text Available These days cloud computing is booming like no other technology. Every organization whether it's small, mid-sized or big, wants to adapt this cutting edge technology for its business. As cloud technology becomes immensely popular among these businesses, the question arises: Which cloud model to consider for your business? There are four types of cloud models available in the market: Public, Private, Hybrid and Community. This review paper answers the question, which model would be most beneficial for your business. All the four models are defined, discussed and compared with the benefits and pitfalls, thus giving you a clear idea, which model to adopt for your organization.

  8. Quantum computation in a quantum-dot-Majorana-fermion hybrid system

    CERN Document Server

    Xue, Zheng-Yuan

    2012-01-01

    We propose a scheme to implement universal quantum computation in a quantum-dot-Majorana-fermion hybrid system. Quantum information is encoded on pairs of Majorana fermions, which live on the the interface between topologically trivial and nontrivial sections of a quantum nanowire deposited on an s-wave superconductor. Universal single-qubit gates on topological qubit can be achieved. A measurement-based two-qubit Controlled-Not gate is produced with the help of parity measurements assisted by the quantum-dot and followed by prescribed single-qubit gates. The parity measurement, on the quantum-dot and a topological qubit, is achieved by the Aharonov- Casher effect.

  9. Hybrid EEG-EOG brain-computer interface system for practical machine control.

    Science.gov (United States)

    Punsawad, Yunyong; Wongsawat, Yodchanan; Parnichkun, Manukid

    2010-01-01

    Practical issues such as accuracy with various subjects, number of sensors, and time for training are important problems of existing brain-computer interface (BCI) systems. In this paper, we propose a hybrid framework for the BCI system that can make machine control more practical. The electrooculogram (EOG) is employed to control the machine in the left and right directions while the electroencephalogram (EEG) is employed to control the forword, no action, and complete stop motions of the machine. By using only 2-channel biosignals, the average classification accuracy of more than 95% can be achieved.

  10. Treatment of early and late reflections in a hybrid computer model for room acoustics

    DEFF Research Database (Denmark)

    Naylor, Graham

    1992-01-01

    The ODEON computer model for acoustics in large rooms is intended for use both in design (by predicting room acoustical indices quickly and easily) and in research (by forming the basis of an auralization system and allowing study of various room acoustical phenomena). These conflicting demands...... preclude the use of both ``pure'' image source and ``pure'' particle tracing methods. A hybrid model has been developed, in which rays discover potential image sources up to a specified order. Thereafter, the same ray tracing process is used in a different way to rapidly generate a dense reverberant decay...

  11. Assessment of asthmatic inflammation using hybrid fluorescence molecular tomography-x-ray computed tomography

    Science.gov (United States)

    Ma, Xiaopeng; Prakash, Jaya; Ruscitti, Francesca; Glasl, Sarah; Stellari, Fabio Franco; Villetti, Gino; Ntziachristos, Vasilis

    2016-01-01

    Nuclear imaging plays a critical role in asthma research but is limited in its readings of biology due to the short-lived signals of radio-isotopes. We employed hybrid fluorescence molecular tomography (FMT) and x-ray computed tomography (XCT) for the assessment of asthmatic inflammation based on resolving cathepsin activity and matrix metalloproteinase activity in dust mite, ragweed, and Aspergillus species-challenged mice. The reconstructed multimodal fluorescence distribution showed good correspondence with ex vivo cryosection images and histological images, confirming FMT-XCT as an interesting alternative for asthma research.

  12. Results of Short-Period Helicopter System Identification Using Output-Error and Hybrid Search-Gradient Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Ronaldo Vieira Cruz

    2010-01-01

    Full Text Available This article focuses on the problem of parameter estimation of the uncoupled, linear, short-period aerodynamic derivatives of a “Twin Squirrel” helicopter in level flight and constant speed. A flight test campaign is described with respect to maneuver specification, flight test instrumentation, and experimental data collection used to estimate the aerodynamic derivatives. The identification problem is solved in the time domain using the output-error approach, with a combination of Genetic Algorithm (GA and Levenberg-Marquardt optimization algorithms. The advantages of this hybrid GA and gradient-search methodology in helicopter system identification are discussed.

  13. Hybrid simulation of scatter intensity in industrial cone-beam computed tomography

    Science.gov (United States)

    Thierry, R.; Miceli, A.; Hofmann, J.; Flisch, A.; Sennhauser, U.

    2009-01-01

    A cone-beam computed tomography (CT) system using a 450 kV X-ray tube has been developed to challenge the three-dimensional imaging of parts of the automotive industry in short acquisition time. Because the probability of detecting scattered photons is high regarding the energy range and the area of detection, a scattering correction becomes mandatory for generating reliable images with enhanced contrast detectability. In this paper, we present a hybrid simulator for the fast and accurate calculation of the scattering intensity distribution. The full acquisition chain, from the generation of a polyenergetic photon beam, its interaction with the scanned object and the energy deposit in the detector is simulated. Object phantoms can be spatially described in form of voxels, mathematical primitives or CAD models. Uncollided radiation is treated with a ray-tracing method and scattered radiation is split into single and multiple scattering. The single scattering is calculated with a deterministic approach accelerated with a forced detection method. The residual noisy signal is subsequently deconvoluted with the iterative Richardson-Lucy method. Finally the multiple scattering is addressed with a coarse Monte Carlo (MC) simulation. The proposed hybrid method has been validated on aluminium phantoms with varying size and object-to-detector distance, and found in good agreement with the MC code Geant4. The acceleration achieved by the hybrid method over the standard MC on a single projection is approximately of three orders of magnitude.

  14. Hybrid Numerical Solvers for Massively Parallel Eigenvalue Computation and Their Benchmark with Electronic Structure Calculations

    CERN Document Server

    Imachi, Hiroto

    2015-01-01

    Optimally hybrid numerical solvers were constructed for massively parallel generalized eigenvalue problem (GEP).The strong scaling benchmark was carried out on the K computer and other supercomputers for electronic structure calculation problems in the matrix sizes of M = 10^4-10^6 with upto 105 cores. The procedure of GEP is decomposed into the two subprocedures of the reducer to the standard eigenvalue problem (SEP) and the solver of SEP. A hybrid solver is constructed, when a routine is chosen for each subprocedure from the three parallel solver libraries of ScaLAPACK, ELPA and EigenExa. The hybrid solvers with the two newer libraries, ELPA and EigenExa, give better benchmark results than the conventional ScaLAPACK library. The detailed analysis on the results implies that the reducer can be a bottleneck in next-generation (exa-scale) supercomputers, which indicates the guidance for future research. The code was developed as a middleware and a mini-application and will appear online.

  15. Data identification for improving gene network inference using computational algebra.

    Science.gov (United States)

    Dimitrova, Elena; Stigler, Brandilyn

    2014-11-01

    Identification of models of gene regulatory networks is sensitive to the amount of data used as input. Considering the substantial costs in conducting experiments, it is of value to have an estimate of the amount of data required to infer the network structure. To minimize wasted resources, it is also beneficial to know which data are necessary to identify the network. Knowledge of the data and knowledge of the terms in polynomial models are often required a priori in model identification. In applications, it is unlikely that the structure of a polynomial model will be known, which may force data sets to be unnecessarily large in order to identify a model. Furthermore, none of the known results provides any strategy for constructing data sets to uniquely identify a model. We provide a specialization of an existing criterion for deciding when a set of data points identifies a minimal polynomial model when its monomial terms have been specified. Then, we relax the requirement of the knowledge of the monomials and present results for model identification given only the data. Finally, we present a method for constructing data sets that identify minimal polynomial models.

  16. Research related to improved computer aided design software package. [comparative efficiency of finite, boundary, and hybrid element methods in elastostatics

    Science.gov (United States)

    Walston, W. H., Jr.

    1986-01-01

    The comparative computational efficiencies of the finite element (FEM), boundary element (BEM), and hybrid boundary element-finite element (HVFEM) analysis techniques are evaluated for representative bounded domain interior and unbounded domain exterior problems in elastostatics. Computational efficiency is carefully defined in this study as the computer time required to attain a specified level of solution accuracy. The study found the FEM superior to the BEM for the interior problem, while the reverse was true for the exterior problem. The hybrid analysis technique was found to be comparable or superior to both the FEM and BEM for both the interior and exterior problems.

  17. Identification of the specificity of isolated phage display single-chain antibodies using yeast two-hybrid screens

    DEFF Research Database (Denmark)

    Rasmussen, Nicolaj; Ditzel, Henrik

    2009-01-01

    A method is described for the identification of the antigen recognised by an scFv isolated from an antibody phage display library using selection against a complex mixture of proteins (e.g. intact cells, purified cell surface membranes, and tissue sections). The method takes advantage of a yeast ...... two-hybrid system that additionally allows for reorganization of post-translational modifications to the bait and target proteins. This technique is therefore especially useful for identifying surface-expressed antigens....

  18. Identification of risk factors of computer information technologies in education

    Directory of Open Access Journals (Sweden)

    Hrebniak M.P.

    2014-03-01

    Full Text Available The basic direction of development of secondary school and vocational training is computer training of schoolchildren and students, including distance forms of education and widespread usage of world information systems. The purpose of the work is to determine risk factors for schoolchildren and students, when using modern information and computer technologies. Results of researches allowed to establish dynamics of formation of skills using computer information technologies in education and characteristics of mental ability among schoolchildren and students during training in high school. Common risk factors, while operating CIT, are: intensification and formalization of intellectual activity, adverse ergonomic parameters, unfavorable working posture, excess of hygiene standards by chemical and physical characteristics. The priority preventive directions in applying computer information technology in education are: improvement of optimal visual parameters of activity, rationalization of ergonomic parameters, minimizing of adverse effects of chemical and physical conditions, rationalization of work and rest activity.

  19. Identification of novel genes involved in gastric carcinogenesis by suppression subtractive hybridization.

    Science.gov (United States)

    Mottaghi-Dastjerdi, N; Soltany-Rezaee-Rad, M; Sepehrizadeh, Z; Roshandel, G; Ebrahimifard, F; Setayesh, N

    2015-01-01

    Gastric cancer (GC) is one of the most common and life-threatening types of malignancies. Identification of the differentially expressed genes in GC is one of the best approaches for establishing new diagnostic and therapeutic targets. Furthermore, these investigations could advance our knowledge about molecular biology and the carcinogenesis of this cancer. To screen for the overexpressed genes in gastric adenocarcinoma, we performed suppression subtractive hybridization (SSH) on gastric adenocarcinoma tissue and the corresponding normal gastric tissue, and eight genes were found to be overexpressed in the tumor compared with those of the normal tissue. The genes were ribosomal protein L18A, RNase H2 subunit B, SEC13, eukaryotic translation initiation factor 4A1, tetraspanin 8, cytochrome c oxidase subunit 2, NADH dehydrogenase subunit 4, and mitochondrially encoded ATP synthase 6. The common functions among the identified genes include involvement in protein synthesis, involvement in genomic stability maintenance, metastasis, metabolic improvement, cell signaling pathways, and chemoresistance. Our results provide new insights into the molecular biology of GC and drug discovery: each of the identified genes could be further investigated as targets for prognosis evaluation, diagnosis, treatment, evaluation of the response to new anticancer drugs, and determination of the molecular pathogenesis of GC.

  20. Fluorescence in situ hybridization for the identification of Treponema pallidum in tissue sections.

    Science.gov (United States)

    Petrich, Annett; Rojas, Pablo; Schulze, Julia; Loddenkemper, Christoph; Giacani, Lorenzo; Schneider, Thomas; Hertel, Moritz; Kikhney, Judith; Moter, Annette

    2015-10-01

    Syphilis is often called the great imitator because of its frequent atypical clinical manifestations that make the disease difficult to recognize. Because Treponema pallidum subsp. pallidum, the infectious agent of syphilis, is yet uncultivated in vitro, diagnosis is usually made using serology; however, in cases where serology is inconclusive or in patients with immunosuppression where these tests may be difficult to interpret, the availability of a molecular tool for direct diagnosis may be of pivotal importance. Here we present a fluorescence in situ hybridization (FISH) assay that simultaneously identifies and analyzes spatial distribution of T. pallidum in histological tissue sections. For this assay the species-specific FISH probe TPALL targeting the 16S rRNA of T. pallidum was designed in silico and evaluated using T. pallidum infected rabbit testicular tissue and a panel of non-syphilis spirochetes as positive and negative controls, respectively, before application to samples from four syphilis-patients. In a HIV positive patient, FISH showed the presence of T. pallidum in inguinal lymph node tissue. In a patient not suspected to suffer from syphilis but underwent surgery for phimosis, numerous T. pallidum cells were found in preputial tissue. In two cases with oral involvement, FISH was able to differentiate T. pallidum from oral treponemes and showed infection of the oral mucosa and tonsils, respectively. The TPALL FISH probe is now readily available for in situ identification of T. pallidum in selected clinical samples as well as T. pallidum research applications and animal models.

  1. A Hybrid Computational Intelligence Approach Combining Genetic Programming And Heuristic Classification for Pap-Smear Diagnosis

    DEFF Research Database (Denmark)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan;

    2001-01-01

    The paper suggests the combined use of different computational intelligence (CI) techniques in a hybrid scheme, as an effective approach to medical diagnosis. Getting to know the advantages and disadvantages of each computational intelligence technique in the recent years, the time has come...... diagnoses. The final result is a short but robust rule based classification scheme, achieving high degree of classification accuracy (exceeding 90% of accuracy for most classes) in a meaningful and user-friendly representation form for the medical expert. The domain of application analyzed through the paper...... is the well-known Pap-Test problem, corresponding to a numerical database, which consists of 450 medical records, 25 diagnostic attributes and 5 different diagnostic classes. Experimental data are divided in two equal parts for the training and testing phase, and 8 mutually dependent rules for diagnosis...

  2. PWR hybrid computer model for assessing the safety implications of control systems

    Energy Technology Data Exchange (ETDEWEB)

    Smith, O L; Renier, J P; Difilippo, F C; Clapp, N E; Sozer, A; Booth, R S; Craddick, W G; Morris, D G

    1986-03-01

    The ORNL study of safety-related aspects of nuclear power plant control systems consists of two interrelated tasks: (1) failure mode and effects analysis (FMEA) that identified single and multiple component failures that might lead to significant plant upsets and (2) computer models that used these failures as initial conditions and traced the dynamic impact on the control system and remainder of the plant. This report describes the simulation of Oconee Unit 1, the first plant analyzed. A first-principles, best-estimate model was developed and implemented on a hybrid computer consisting of AD-4 analog and PDP-10 digital machines. Controls were placed primarily on the analog to use its interactive capability to simulate operator action. 48 refs., 138 figs., 15 tabs.

  3. Semiempirical Quantum Chemical Calculations Accelerated on a Hybrid Multicore CPU-GPU Computing Platform.

    Science.gov (United States)

    Wu, Xin; Koslowski, Axel; Thiel, Walter

    2012-07-10

    In this work, we demonstrate that semiempirical quantum chemical calculations can be accelerated significantly by leveraging the graphics processing unit (GPU) as a coprocessor on a hybrid multicore CPU-GPU computing platform. Semiempirical calculations using the MNDO, AM1, PM3, OM1, OM2, and OM3 model Hamiltonians were systematically profiled for three types of test systems (fullerenes, water clusters, and solvated crambin) to identify the most time-consuming sections of the code. The corresponding routines were ported to the GPU and optimized employing both existing library functions and a GPU kernel that carries out a sequence of noniterative Jacobi transformations during pseudodiagonalization. The overall computation times for single-point energy calculations and geometry optimizations of large molecules were reduced by one order of magnitude for all methods, as compared to runs on a single CPU core.

  4. Use of a Computer-Assisted Identification System in the Identification of the Remains of Deceased USAF Personnel.

    Science.gov (United States)

    1988-04-01

    1987 he completed a Master of Arts degree in Computer Resource Management. Major Triplett also graduated from AFIP’s Forensic Odontology Course and...Thomas, 1973. Articles and Periodicals 4. Brannon, Lawrence S., Capt, USA. " Forensic Odontology : An Application for the Army Dentist." Military...34 Military Medicine, Vol. 146 (April 1981), pp. 262-264. 12. Kim, Ho Wohn. "The Role of Forensic Odontology in the Field of Human Identification

  5. The UF family of reference hybrid phantoms for computational radiation dosimetry

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Choonsik [Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Bethesda, MD 20852 (United States); Lodwick, Daniel; Hurtado, Jorge; Pafundi, Deanna [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL 32611 (United States); Williams, Jonathan L [Department of Radiology, University of Florida, Gainesville, FL 32611 (United States); Bolch, Wesley E [Departments of Nuclear and Radiological and Biomedical Engineering, University of Florida, Gainesville, FL 32611 (United States)], E-mail: wbolch@ufl.edu

    2010-01-21

    Computational human phantoms are computer models used to obtain dose distributions within the human body exposed to internal or external radiation sources. In addition, they are increasingly used to develop detector efficiencies for in vivo whole-body counters. Two classes of computational human phantoms have been widely utilized for dosimetry calculation: stylized and voxel phantoms that describe human anatomy through mathematical surface equations and 3D voxel matrices, respectively. Stylized phantoms are flexible in that changes to organ position and shape are possible given avoidance of region overlap, while voxel phantoms are typically fixed to a given patient anatomy, yet can be proportionally scaled to match individuals of larger or smaller stature, but of equivalent organ anatomy. Voxel phantoms provide much better anatomical realism as compared to stylized phantoms which are intrinsically limited by mathematical surface equations. To address the drawbacks of these phantoms, hybrid phantoms based on non-uniform rational B-spline (NURBS) surfaces have been introduced wherein anthropomorphic flexibility and anatomic realism are both preserved. Researchers at the University of Florida have introduced a series of hybrid phantoms representing the ICRP Publication 89 reference newborn, 15 year, and adult male and female. In this study, six additional phantoms are added to the UF family of hybrid phantoms-those of the reference 1 year, 5 year and 10 year child. Head and torso CT images of patients whose ages were close to the targeted ages were obtained under approved protocols. Major organs and tissues were segmented from these images using an image processing software, 3D-DOCTOR(TM). NURBS and polygon mesh surfaces were then used to model individual organs and tissues after importing the segmented organ models to the 3D NURBS modeling software, Rhinoceros(TM). The phantoms were matched to four reference datasets: (1) standard anthropometric data, (2) reference

  6. BF-PSO-TS: Hybrid Heuristic Algorithms for Optimizing Task Schedulingon Cloud Computing Environment

    Directory of Open Access Journals (Sweden)

    Hussin M. Alkhashai

    2016-06-01

    Full Text Available Task Scheduling is a major problem in Cloud computing because the cloud provider has to serve many users. Also, a good scheduling algorithm helps in the proper and efficient utilization of the resources. So, task scheduling is considered as one of the major issues on the Cloud computing systems. The objective of this paper is to assign the tasks to multiple computing resources. Consequently, the total cost of execution is to be minimum and load to be shared between these computing resources. Therefore, two hybrid algorithms based on Particle Swarm Optimization (PSO have been introduced to schedule the tasks; Best-Fit-PSO (BFPSO and PSO-Tabu Search (PSOTS. According to BFPSO algorithm, Best-Fit (BF algorithm has been merged into the PSO algorithm to improve the performance. The main principle of the modified BFSOP algorithm is that BF algorithm is used to generate the initial population of the standard PSO algorithm instead of being initiated randomly. According to the proposed PSOTS algorithm, the Tabu-Search (TS has been used to improve the local research by avoiding the trap of the local optimality which could be occurred using the standard PSO algorithm. The two proposed algorithms (i.e., BFPSO and PSOTS have been implemented using Cloudsim and evaluated comparing to the standard PSO algorithm using five problems with different number of independent tasks and resources. The performance parameters have been considered are the execution time (Makspan, cost, and resources utilization. The implementation results prove that the proposed hybrid algorithms (i.e., BFPSO, PSOTS outperform the standard PSO algorithm.

  7. A simplified computational fluid-dynamic approach to the oxidizer injector design in hybrid rockets

    Science.gov (United States)

    Di Martino, Giuseppe D.; Malgieri, Paolo; Carmicino, Carmine; Savino, Raffaele

    2016-12-01

    Fuel regression rate in hybrid rockets is non-negligibly affected by the oxidizer injection pattern. In this paper a simplified computational approach developed in an attempt to optimize the oxidizer injector design is discussed. Numerical simulations of the thermo-fluid-dynamic field in a hybrid rocket are carried out, with a commercial solver, to investigate into several injection configurations with the aim of increasing the fuel regression rate and minimizing the consumption unevenness, but still favoring the establishment of flow recirculation at the motor head end, which is generated with an axial nozzle injector and has been demonstrated to promote combustion stability, and both larger efficiency and regression rate. All the computations have been performed on the configuration of a lab-scale hybrid rocket motor available at the propulsion laboratory of the University of Naples with typical operating conditions. After a preliminary comparison between the two baseline limiting cases of an axial subsonic nozzle injector and a uniform injection through the prechamber, a parametric analysis has been carried out by varying the oxidizer jet flow divergence angle, as well as the grain port diameter and the oxidizer mass flux to study the effect of the flow divergence on heat transfer distribution over the fuel surface. Some experimental firing test data are presented, and, under the hypothesis that fuel regression rate and surface heat flux are proportional, the measured fuel consumption axial profiles are compared with the predicted surface heat flux showing fairly good agreement, which allowed validating the employed design approach. Finally an optimized injector design is proposed.

  8. Genome-wide Studies of Mycolic Acid Bacteria: Computational Identification and Analysis of a Minimal Genome

    KAUST Repository

    Kamanu, Frederick Kinyua

    2012-12-01

    The mycolic acid bacteria are a distinct suprageneric group of asporogenous Grampositive, high GC-content bacteria, distinguished by the presence of mycolic acids in their cell envelope. They exhibit great diversity in their cell and morphology; although primarily non-pathogens, this group contains three major pathogens Mycobacterium leprae, Mycobacterium tuberculosis complex, and Corynebacterium diphtheria. Although the mycolic acid bacteria are a clearly defined group of bacteria, the taxonomic relationships between its constituent genera and species are less well defined. Two approaches were tested for their suitability in describing the taxonomy of the group. First, a Multilocus Sequence Typing (MLST) experiment was assessed and found to be superior to monophyletic (16S small ribosomal subunit) in delineating a total of 52 mycolic acid bacterial species. Phylogenetic inference was performed using the neighbor-joining method. To further refine phylogenetic analysis and to take advantage of the widespread availability of bacterial genome data, a computational framework that simulates DNA-DNA hybridisation was developed and validated using multiscale bootstrap resampling. The tool classifies microbial genomes based on whole genome DNA, and was deployed as a web-application using PHP and Javascript. It is accessible online at http://cbrc.kaust.edu.sa/dna_hybridization/ A third study was a computational and statistical methods in the identification and analysis of a putative minimal mycolic acid bacterial genome so as to better understand (1) the genomic requirements to encode a mycolic acid bacterial cell and (2) the role and type of genes and genetic elements that lead to the massive increase in genome size in environmental mycolic acid bacteria. Using a reciprocal comparison approach, a total of 690 orthologous gene clusters forming a putative minimal genome were identified across 24 mycolic acid bacterial species. In order to identify new potential drug

  9. A hybrid multi-scale computational scheme for advection-diffusion-reaction equation

    Science.gov (United States)

    Karimi, S.; Nakshatrala, K. B.

    2016-12-01

    Simulation of transport and reaction processes in porous media and subsurface science has become more vital than ever. Over the past few decades, a variety of mathematical models and numerical methodologies for porous media simulations have been developed. As the demand for higher accuracy and validity of the models grows, the issue of disparate temporal and spatial scales becomes more problematic. The variety of reaction processes and complexity of pore geometry poses a huge computational burden in a real-world or reservoir scale simulation. Meanwhile, methods based on averaging or up- scaling techniques do not provide reliable estimates to pore-scale processes. To overcome this problem, development of hybrid and multi-scale computational techniques is considered a promising approach. In these methods, pore-scale and continuum-scale models are combined, hence, a more reliable estimate to pore-scale processes is obtained without having to deal with the tremendous computational overhead of pore-scale methods. In this presentation, we propose a computational framework that allows coupling of lattice Boltzmann method (for pore-scale simulation) and finite element method (for continuum-scale simulation) for advection-diffusion-reaction equations. To capture disparate in time and length events, non-matching grid and time-steps are allowed. Apart from application of this method to benchmark problems, multi-scale simulation of chemical reactions in porous media is also showcased.

  10. Computational identification of candidate nucleotide cyclases in higher plants

    KAUST Repository

    Wong, Aloysius Tze

    2013-09-03

    In higher plants guanylyl cyclases (GCs) and adenylyl cyclases (ACs) cannot be identified using BLAST homology searches based on annotated cyclic nucleotide cyclases (CNCs) of prokaryotes, lower eukaryotes, or animals. The reason is that CNCs are often part of complex multifunctional proteins with different domain organizations and biological functions that are not conserved in higher plants. For this reason, we have developed CNC search strategies based on functionally conserved amino acids in the catalytic center of annotated and/or experimentally confirmed CNCs. Here we detail this method which has led to the identification of >25 novel candidate CNCs in Arabidopsis thaliana, several of which have been experimentally confirmed in vitro and in vivo. We foresee that the application of this method can be used to identify many more members of the growing family of CNCs in higher plants. © Springer Science+Business Media New York 2013.

  11. Computational identification of candidate nucleotide cyclases in higher plants.

    Science.gov (United States)

    Wong, Aloysius; Gehring, Chris

    2013-01-01

    In higher plants guanylyl cyclases (GCs) and adenylyl cyclases (ACs) cannot be identified using BLAST homology searches based on annotated cyclic nucleotide cyclases (CNCs) of prokaryotes, lower eukaryotes, or animals. The reason is that CNCs are often part of complex multifunctional proteins with different domain organizations and biological functions that are not conserved in higher plants. For this reason, we have developed CNC search strategies based on functionally conserved amino acids in the catalytic center of annotated and/or experimentally confirmed CNCs. Here we detail this method which has led to the identification of >25 novel candidate CNCs in Arabidopsis thaliana, several of which have been experimentally confirmed in vitro and in vivo. We foresee that the application of this method can be used to identify many more members of the growing family of CNCs in higher plants.

  12. Identification of Intergeneric Hybrid Plants Between Oryza sativa and O. minuta via GISH and RAPD

    Institute of Scientific and Technical Information of China (English)

    YU Shun-wu; CHEN Bao-tang; TAO Ai-lin; ZHANG Duan-pin

    2003-01-01

    To transfer desirable resistance traits from O. minuta to O. sativa, intergeneric hybrid plants between O. sativa (AA, 2n=2X=24) and O. minuta (BBCC, 2n=4X=48) were produced by embryo rescue after sexual cross. Morphological observation and chromosome counts indicated their hybrid status (ABC, 2n =3X=36). Genomic in situ hybridization (GISH) was further applied to confirm the parentage of the chromosomes of F1 hybrids. Chromosomes of O. minuta and O. sativa were distinguishable in the hybrids in different fluorescence colors. GISH indicated that A and BC chromosomes were not randomly assembled in a cell.RAPD profiles unequivocally revealed their hybrids with double parent patterns. The results of blast tests showed that the hybrids had obtained disease resistance from O. minuta, and had a level of susceptibility between the parents.

  13. Parallel computing-based sclera recognition for human identification

    Science.gov (United States)

    Lin, Yong; Du, Eliza Y.; Zhou, Zhi

    2012-06-01

    Compared to iris recognition, sclera recognition which uses line descriptor can achieve comparable recognition accuracy in visible wavelengths. However, this method is too time-consuming to be implemented in a real-time system. In this paper, we propose a GPU-based parallel computing approach to reduce the sclera recognition time. We define a new descriptor in which the information of KD tree structure and sclera edge are added. Registration and matching task is divided into subtasks in various sizes according to their computation complexities. Every affine transform parameters are generated by searching on KD tree. Texture memory, constant memory, and shared memory are used to store templates and transform matrixes. The experiment results show that the proposed method executed on GPU can dramatically improve the sclera matching speed in hundreds of times without accuracy decreasing.

  14. Molecular identification and histopathological study of natural Streptococcus agalactiae infection in hybrid tilapia (Oreochromis niloticus)

    Science.gov (United States)

    Laith, AA; Ambak, Mohd Azmi; Hassan, Marina; Sheriff, Shahreza Md.; Nadirah, Musa; Draman, Ahmad Shuhaimi; Wahab, Wahidah; Ibrahim, Wan Nurhafizah Wan; Aznan, Alia Syafiqah; Jabar, Amina; Najiah, Musa

    2017-01-01

    Aim: The main objective of this study was to emphasize on histopathological examinations and molecular identification of Streptococcus agalactiae isolated from natural infections in hybrid tilapia (Oreochromis niloticus) in Temerloh Pahang, Malaysia, as well as to determine the susceptibility of the pathogen strains to various currently available antimicrobial agents. Materials and Methods: The diseased fishes were observed for variable clinical signs including fin hemorrhages, alterations in behavior associated with erratic swimming, exophthalmia, and mortality. Tissue samples from the eyes, brain, kidney, liver, and spleen were taken for bacterial isolation. Identification of S. agalactiae was screened by biochemical methods and confirmed by VITEK 2 and 16S rRNA gene sequencing. The antibiogram profiling of the isolate was tested against 18 standard antibiotics included nitrofurantoin, flumequine, florfenicol, amoxylin, doxycycline, oleandomycin, tetracycline, ampicillin, lincomycin, colistin sulfate, oxolinic acid, novobiocin, spiramycin, erythromycin, fosfomycin, neomycin, gentamycin, and polymyxin B. The histopathological analysis of eyes, brain, liver, kidney, and spleen was observed for abnormalities related to S. agalactiae infection. Results: The suspected colonies of S. agalactiae identified by biochemical methods was observed as Gram-positive chained cocci, β-hemolytic, and non-motile. The isolate was confirmed as S. agalactiae by VITEK 2 (99% similarity), reconfirmed by 16S rRNA gene sequencing (99% similarity) and deposited in GenBank with accession no. KT869025. The isolate was observed to be resistance to neomycin and gentamicin. The most consistent gross findings were marked hemorrhages, erosions of caudal fin, and exophthalmos. Microscopic examination confirmed the presence of marked congestion and infiltration of inflammatory cell in the eye, brain, kidney, liver, and spleen. Eye samples showed damage of the lens capsule, hyperemic and

  15. Resource-Efficient, Hierarchical Auto-Tuning of a Hybrid Lattice Boltzmann Computation on the Cray XT4

    OpenAIRE

    Williams, Samuel; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA; NERSC, Lawrence Berkeley National Laboratory; Computer Science Department, University of California, Irvine, CA

    2009-01-01

    We apply auto-tuning to a hybrid MPI-pthreads lattice Boltzmann computation running on the Cray XT4 at National Energy Research Scientific Computing Center (NERSC). Previous work showed that multicore-specific auto-tuning can improve the performance of lattice Boltzmann magnetohydrodynamics (LBMHD) by a factor of 4x when running on dual- and quad-core Opteron dual-socket SMPs. We extend these studies to the distributed memory arena via a hybrid MPI/pthreads implementation. In addition to con...

  16. Parallel Computing Characteristics of CUPID code under MPI and Hybrid environment

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jae Ryong; Yoon, Han Young [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Jeon, Byoung Jin; Choi, Hyoung Gwon [Seoul National Univ. of Science and Technology, Seoul (Korea, Republic of)

    2014-05-15

    In this paper, a characteristic of parallel algorithm is presented for solving an elliptic type equation of CUPID via domain decomposition method using the MPI and the parallel performance is estimated in terms of a scalability which shows the speedup ratio. In addition, the time-consuming pattern of major subroutines is studied. Two different grid systems are taken into account: 40,000 meshes for coarse system and 320,000 meshes for fine system. Since the matrix of the CUPID code differs according to whether the flow is single-phase or two-phase, the effect of matrix shape is evaluated. Finally, the effect of the preconditioner for matrix solver is also investigated. Finally, the hybrid (OpenMP+MPI) parallel algorithm is introduced and discussed in detail for solving pressure solver. Component-scale thermal-hydraulics code, CUPID has been developed for two-phase flow analysis, which adopts a three-dimensional, transient, three-field model, and parallelized to fulfill a recent demand for long-transient and highly resolved multi-phase flow behavior. In this study, the parallel performance of the CUPID code was investigated in terms of scalability. The CUPID code was parallelized with domain decomposition method. The MPI library was adopted to communicate the information at the neighboring domain. For managing the sparse matrix effectively, the CSR storage format is used. To take into account the characteristics of the pressure matrix which turns to be asymmetric for two-phase flow, both single-phase and two-phase calculations were run. In addition, the effect of the matrix size and preconditioning was also investigated. The fine mesh calculation shows better scalability than the coarse mesh because the number of coarse mesh does not need to decompose the computational domain excessively. The fine mesh can be present good scalability when dividing geometry with considering the ratio between computation and communication time. For a given mesh, single-phase flow

  17. Detecting awareness in patients with disorders of consciousness using a hybrid brain-computer interface

    Science.gov (United States)

    Pan, Jiahui; Xie, Qiuyou; He, Yanbin; Wang, Fei; Di, Haibo; Laureys, Steven; Yu, Ronghao; Li, Yuanqing

    2014-10-01

    Objective. The bedside detection of potential awareness in patients with disorders of consciousness (DOC) currently relies only on behavioral observations and tests; however, the misdiagnosis rates in this patient group are historically relatively high. In this study, we proposed a visual hybrid brain-computer interface (BCI) combining P300 and steady-state evoked potential (SSVEP) responses to detect awareness in severely brain injured patients. Approach. Four healthy subjects, seven DOC patients who were in a vegetative state (VS, n = 4) or minimally conscious state (MCS, n = 3), and one locked-in syndrome (LIS) patient attempted a command-following experiment. In each experimental trial, two photos were presented to each patient; one was the patient's own photo, and the other photo was unfamiliar. The patients were instructed to focus on their own or the unfamiliar photos. The BCI system determined which photo the patient focused on with both P300 and SSVEP detections. Main results. Four healthy subjects, one of the 4 VS, one of the 3 MCS, and the LIS patient were able to selectively attend to their own or the unfamiliar photos (classification accuracy, 66-100%). Two additional patients (one VS and one MCS) failed to attend the unfamiliar photo (50-52%) but achieved significant accuracies for their own photo (64-68%). All other patients failed to show any significant response to commands (46-55%). Significance. Through the hybrid BCI system, command following was detected in four healthy subjects, two of 7 DOC patients, and one LIS patient. We suggest that the hybrid BCI system could be used as a supportive bedside tool to detect awareness in patients with DOC.

  18. MAX--An Interactive Computer Program for Teaching Identification of Clay Minerals by X-ray Diffraction.

    Science.gov (United States)

    Kohut, Connie K.; And Others

    1993-01-01

    Discusses MAX, an interactive computer program for teaching identification of clay minerals based on standard x-ray diffraction characteristics. The program provides tutorial-type exercises for identification of 16 clay standards, self-evaluation exercises, diffractograms of 28 soil clay minerals, and identification of nonclay minerals. (MDH)

  19. MAX--An Interactive Computer Program for Teaching Identification of Clay Minerals by X-ray Diffraction.

    Science.gov (United States)

    Kohut, Connie K.; And Others

    1993-01-01

    Discusses MAX, an interactive computer program for teaching identification of clay minerals based on standard x-ray diffraction characteristics. The program provides tutorial-type exercises for identification of 16 clay standards, self-evaluation exercises, diffractograms of 28 soil clay minerals, and identification of nonclay minerals. (MDH)

  20. Genetic and computational identification of a conserved bacterial metabolic module.

    Directory of Open Access Journals (Sweden)

    Cara C Boutte

    2008-12-01

    Full Text Available We have experimentally and computationally defined a set of genes that form a conserved metabolic module in the alpha-proteobacterium Caulobacter crescentus and used this module to illustrate a schema for the propagation of pathway-level annotation across bacterial genera. Applying comprehensive forward and reverse genetic methods and genome-wide transcriptional analysis, we (1 confirmed the presence of genes involved in catabolism of the abundant environmental sugar myo-inositol, (2 defined an operon encoding an ABC-family myo-inositol transmembrane transporter, and (3 identified a novel myo-inositol regulator protein and cis-acting regulatory motif that control expression of genes in this metabolic module. Despite being encoded from non-contiguous loci on the C. crescentus chromosome, these myo-inositol catabolic enzymes and transporter proteins form a tightly linked functional group in a computationally inferred network of protein associations. Primary sequence comparison was not sufficient to confidently extend annotation of all components of this novel metabolic module to related bacterial genera. Consequently, we implemented the Graemlin multiple-network alignment algorithm to generate cross-species predictions of genes involved in myo-inositol transport and catabolism in other alpha-proteobacteria. Although the chromosomal organization of genes in this functional module varied between species, the upstream regions of genes in this aligned network were enriched for the same palindromic cis-regulatory motif identified experimentally in C. crescentus. Transposon disruption of the operon encoding the computationally predicted ABC myo-inositol transporter of Sinorhizobium meliloti abolished growth on myo-inositol as the sole carbon source, confirming our cross-genera functional prediction. Thus, we have defined regulatory, transport, and catabolic genes and a cis-acting regulatory sequence that form a conserved module required for myo

  1. Near-term hybrid vehicle program, phase 1. Appendix B: Design trade-off studies report. Volume 3: Computer program listings

    Science.gov (United States)

    1979-01-01

    A description and listing is presented of two computer programs: Hybrid Vehicle Design Program (HYVELD) and Hybrid Vehicle Simulation Program (HYVEC). Both of the programs are modifications and extensions of similar programs developed as part of the Electric and Hybrid Vehicle System Research and Development Project.

  2. Adaptation of hybrid human-computer interaction systems using EEG error-related potentials.

    Science.gov (United States)

    Chavarriaga, Ricardo; Biasiucci, Andrea; Forster, Killian; Roggen, Daniel; Troster, Gerhard; Millan, Jose Del R

    2010-01-01

    Performance improvement in both humans and artificial systems strongly relies in the ability of recognizing erroneous behavior or decisions. This paper, that builds upon previous studies on EEG error-related signals, presents a hybrid approach for human computer interaction that uses human gestures to send commands to a computer and exploits brain activity to provide implicit feedback about the recognition of such commands. Using a simple computer game as a case study, we show that EEG activity evoked by erroneous gesture recognition can be classified in single trials above random levels. Automatic artifact rejection techniques are used, taking into account that subjects are allowed to move during the experiment. Moreover, we present a simple adaptation mechanism that uses the EEG signal to label newly acquired samples and can be used to re-calibrate the gesture recognition system in a supervised manner. Offline analysis show that, although the achieved EEG decoding accuracy is far from being perfect, these signals convey sufficient information to significantly improve the overall system performance.

  3. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    Directory of Open Access Journals (Sweden)

    Lukas Falat

    2016-01-01

    Full Text Available This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  4. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network.

    Science.gov (United States)

    Falat, Lukas; Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  5. Requirements for Control Room Computer-Based Procedures for use in Hybrid Control Rooms

    Energy Technology Data Exchange (ETDEWEB)

    Le Blanc, Katya Lee [Idaho National Lab. (INL), Idaho Falls, ID (United States); Oxstrand, Johanna Helene [Idaho National Lab. (INL), Idaho Falls, ID (United States); Joe, Jeffrey Clark [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-05-01

    Many plants in the U.S. are currently undergoing control room modernization. The main drivers for modernization are the aging and obsolescence of existing equipment, which typically results in a like-for-like replacement of analogue equipment with digital systems. However, the modernization efforts present an opportunity to employ advanced technology that would not only extend the life, but enhance the efficiency and cost competitiveness of nuclear power. Computer-based procedures (CBPs) are one example of near-term advanced technology that may provide enhanced efficiencies above and beyond like for like replacements of analog systems. Researchers in the LWRS program are investigating the benefits of advanced technologies such as CBPs, with the goal of assisting utilities in decision making during modernization projects. This report will describe the existing research on CBPs, discuss the unique issues related to using CBPs in hybrid control rooms (i.e., partially modernized analog control rooms), and define the requirements of CBPs for hybrid control rooms.

  6. Optimization of a Continuous Hybrid Impeller Mixer via Computational Fluid Dynamics

    Directory of Open Access Journals (Sweden)

    N. Othman

    2014-01-01

    Full Text Available This paper presents the preliminary steps required for conducting experiments to obtain the optimal operating conditions of a hybrid impeller mixer and to determine the residence time distribution (RTD using computational fluid dynamics (CFD. In this paper, impeller speed and clearance parameters are examined. The hybrid impeller mixer consists of a single Rushton turbine mounted above a single pitched blade turbine (PBT. Four impeller speeds, 50, 100, 150, and 200 rpm, and four impeller clearances, 25, 50, 75, and 100 mm, were the operation variables used in this study. CFD was utilized to initially screen the parameter ranges to reduce the number of actual experiments needed. Afterward, the residence time distribution (RTD was determined using the respective parameters. Finally, the Fluent-predicted RTD and the experimentally measured RTD were compared. The CFD investigations revealed that an impeller speed of 50 rpm and an impeller clearance of 25 mm were not viable for experimental investigations and were thus eliminated from further analyses. The determination of RTD using a k-ε turbulence model was performed using CFD techniques. The multiple reference frame (MRF was implemented and a steady state was initially achieved followed by a transient condition for RTD determination.

  7. SWNT-DNA and SWNT-polyC hybrids: AFM study and computer modeling.

    Science.gov (United States)

    Karachevtsev, M V; Lytvyn, O S; Stepanian, S G; Leontiev, V S; Adamowicz, L; Karachevtsev, V A

    2008-03-01

    Hybrids of carbon single-walled nanotubes (SWNT) with fragmented single or double-stranded DNA (fss- or fds-DNA) or polyC were studied by Atom Force Microscopy (AFM) and computer modeling. It was found that fragments of the polymer wrap in several layers around the nanotube, forming a strand-like spindle. In contrast to the fss-DNA, the fds-DNA also forms compact structures near the tube surface due to the formation of self-assembly structures consisting of a few DNA fragments. The hybrids of SWNT with wrapped single-, double- or triple strands of the biopolymer were simulated, and it was shown that such structures are stable. To explain the reason of multi-layer polymeric coating of the nanotube surface, the energy of the intermolecular interactions between different components of polyC was calculated at the MP2/6-31++G** level as well as the interaction energy in the SWNT-cytosine complex.

  8. Feasibility of a Hybrid Brain-Computer Interface for Advanced Functional Electrical Therapy

    Directory of Open Access Journals (Sweden)

    Andrej M. Savić

    2014-01-01

    Full Text Available We present a feasibility study of a novel hybrid brain-computer interface (BCI system for advanced functional electrical therapy (FET of grasp. FET procedure is improved with both automated stimulation pattern selection and stimulation triggering. The proposed hybrid BCI comprises the two BCI control signals: steady-state visual evoked potentials (SSVEP and event-related desynchronization (ERD. The sequence of the two stages, SSVEP-BCI and ERD-BCI, runs in a closed-loop architecture. The first stage, SSVEP-BCI, acts as a selector of electrical stimulation pattern that corresponds to one of the three basic types of grasp: palmar, lateral, or precision. In the second stage, ERD-BCI operates as a brain switch which activates the stimulation pattern selected in the previous stage. The system was tested in 6 healthy subjects who were all able to control the device with accuracy in a range of 0.64–0.96. The results provided the reference data needed for the planned clinical study. This novel BCI may promote further restoration of the impaired motor function by closing the loop between the “will to move” and contingent temporally synchronized sensory feedback.

  9. Single-Board-Computer-Based Traffic Generator for a Heterogeneous and Hybrid Smart Grid Communication Network

    Directory of Open Access Journals (Sweden)

    Do Nguyet Quang

    2014-02-01

    Full Text Available In smart grid communication implementation, network traffic pattern is one of the main factors that affect the system’s performance. Examining different traffic patterns in smart grid is therefore crucial when analyzing the network performance. Due to the heterogeneous and hybrid nature of smart grid, the type of traffic distribution in the network is still unknown. The traffic that popularly used for simulation and analysis no longer reflects the real traffic in a multi-technology and bi-directional communication system. Hence, in this study, a single-board computer is implemented as a traffic generator which can generate network traffic similar to those generated by various applications in the fully operational smart grid. By placing in a strategic and appropriate position, a collection of traffic generators allow network administrators to investigate and test the effect of heavy traffic on performance of smart grid communication system.

  10. Apps for Angiosperms: The Usability of Mobile Computers and Printed Field Guides for UK Wild Flower and Winter Tree Identification

    Science.gov (United States)

    Stagg, Bethan C.; Donkin, Maria E.

    2017-01-01

    We investigated usability of mobile computers and field guide books with adult botanical novices, for the identification of wildflowers and deciduous trees in winter. Identification accuracy was significantly higher for wildflowers using a mobile computer app than field guide books but significantly lower for deciduous trees. User preference…

  11. Computer-Aided Identification and Validation of Privacy Requirements

    Directory of Open Access Journals (Sweden)

    Rene Meis

    2016-05-01

    Full Text Available Privacy is a software quality that is closely related to security. The main difference is that security properties aim at the protection of assets that are crucial for the considered system, and privacy aims at the protection of personal data that are processed by the system. The identification of privacy protection needs in complex systems is a hard and error prone task. Stakeholders whose personal data are processed might be overlooked, or the sensitivity and the need of protection of the personal data might be underestimated. The later personal data and the needs to protect them are identified during the development process, the more expensive it is to fix these issues, because the needed changes of the system-to-be often affect many functionalities. In this paper, we present a systematic method to identify the privacy needs of a software system based on a set of functional requirements by extending the problem-based privacy analysis (ProPAn method. Our method is tool-supported and automated where possible to reduce the effort that has to be spent for the privacy analysis, which is especially important when considering complex systems. The contribution of this paper is a semi-automatic method to identify the relevant privacy requirements for a software-to-be based on its functional requirements. The considered privacy requirements address all dimensions of privacy that are relevant for software development. As our method is solely based on the functional requirements of the system to be, we enable users of our method to identify the privacy protection needs that have to be addressed by the software-to-be at an early stage of the development. As initial evaluation of our method, we show its applicability on a small electronic health system scenario.

  12. DNA sequence analysis by hybridization with oligonucleotide microchips : MALDI mass spectrometry identification of 5mers contiguously stacked to microchip oligonucleotides.

    Energy Technology Data Exchange (ETDEWEB)

    Stomakhin, A. A.; Vasiliskov, V. A.; Timofeev, E.; Schulga, D.; Cotter, R. J.; Mirzabekov, A. D.; Biochip Technology Center; Engelhardt Inst. of Molecular Biology; Moscow Inst. of Physics and Technology; Middle Atlantic Mass Spectrometry Lab.; Johns Hopkins Univ. School of Medicine

    2000-01-01

    Matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) has been applied to increase the informational output from DNA sequence analysis. It has been used to analyze DNA by hybridization with microarrays of gel-immobilized oligonucleotides extended with stacked 5mers. In model experiments, a 28 nt long DNA fragment was hybridized with 10 immobilized, overlapping 8mers. Then, in a second round of hybridization DNA-8mer duplexes were hybridized with a mixture of 10 5mers. The stability of the 5mer complex with DNA was increased to raise the melting temperature of the duplex by 10-15{sup o}C as a result of stacking interaction with 8mers. Contiguous 13 bp duplexes containing an internal break were formed. MALDI MS identified one or, in some cases, two 5mers contiguously stacked to each DNA-8mer duplex formed on the microchip. Incorporating a mass label into 5mers optimized MALDI MS monitoring. This procedure enabled us to reconstitute the sequence of a model DNA fragment and identify polymorphic nucleotides. The application of MALDI MS identification of contiguously stacked 5mers to increase the length of DNA for sequence analysis is discussed.

  13. An Efficient Framework for EEG Analysis with Application to Hybrid Brain Computer Interfaces Based on Motor Imagery and P300

    Directory of Open Access Journals (Sweden)

    Jinyi Long

    2017-01-01

    Full Text Available The hybrid brain computer interface (BCI based on motor imagery (MI and P300 has been a preferred strategy aiming to improve the detection performance through combining the features of each. However, current methods used for combining these two modalities optimize them separately, which does not result in optimal performance. Here, we present an efficient framework to optimize them together by concatenating the features of MI and P300 in a block diagonal form. Then a linear classifier under a dual spectral norm regularizer is applied to the combined features. Under this framework, the hybrid features of MI and P300 can be learned, selected, and combined together directly. Experimental results on the data set of hybrid BCI based on MI and P300 are provided to illustrate competitive performance of the proposed method against other conventional methods. This provides an evidence that the method used here contributes to the discrimination performance of the brain state in hybrid BCI.

  14. An Efficient Framework for EEG Analysis with Application to Hybrid Brain Computer Interfaces Based on Motor Imagery and P300

    Science.gov (United States)

    Wang, Jue; Yu, Tianyou

    2017-01-01

    The hybrid brain computer interface (BCI) based on motor imagery (MI) and P300 has been a preferred strategy aiming to improve the detection performance through combining the features of each. However, current methods used for combining these two modalities optimize them separately, which does not result in optimal performance. Here, we present an efficient framework to optimize them together by concatenating the features of MI and P300 in a block diagonal form. Then a linear classifier under a dual spectral norm regularizer is applied to the combined features. Under this framework, the hybrid features of MI and P300 can be learned, selected, and combined together directly. Experimental results on the data set of hybrid BCI based on MI and P300 are provided to illustrate competitive performance of the proposed method against other conventional methods. This provides an evidence that the method used here contributes to the discrimination performance of the brain state in hybrid BCI. PMID:28316617

  15. A hybrid method for the computation of quasi-3D seismograms.

    Science.gov (United States)

    Masson, Yder; Romanowicz, Barbara

    2013-04-01

    The development of powerful computer clusters and efficient numerical computation methods, such as the Spectral Element Method (SEM) made possible the computation of seismic wave propagation in a heterogeneous 3D earth. However, the cost of theses computations is still problematic for global scale tomography that requires hundreds of such simulations. Part of the ongoing research effort is dedicated to the development of faster modeling methods based on the spectral element method. Capdeville et al. (2002) proposed to couple SEM simulations with normal modes calculation (C-SEM). Nissen-Meyer et al. (2007) used 2D SEM simulations to compute 3D seismograms in a 1D earth model. Thanks to these developments, and for the first time, Lekic et al. (2011) developed a 3D global model of the upper mantle using SEM simulations. At the local and continental scale, adjoint tomography that is using a lot of SEM simulation can be implemented on current computers (Tape, Liu et al. 2009). Due to their smaller size, these models offer higher resolution. They provide us with images of the crust and the upper part of the mantle. In an attempt to teleport such local adjoint tomographic inversions into the deep earth, we are developing a hybrid method where SEM computation are limited to a region of interest within the earth. That region can have an arbitrary shape and size. Outside this region, the seismic wavefield is extrapolated to obtain synthetic data at the Earth's surface. A key feature of the method is the use of a time reversal mirror to inject the wavefield induced by distant seismic source into the region of interest (Robertsson and Chapman 2000). We compute synthetic seismograms as follow: Inside the region of interest, we are using regional spectral element software RegSEM to compute wave propagation in 3D. Outside this region, the wavefield is extrapolated to the surface by convolution with the Green's functions from the mirror to the seismic stations. For now, these

  16. Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment.

    Science.gov (United States)

    Abdullahi, Mohammed; Ngadi, Md Asri

    2016-01-01

    Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS) has been shown to perform competitively with Particle Swarm Optimization (PSO). The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA) based SOS (SASOS) in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs) which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan.

  17. Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment.

    Directory of Open Access Journals (Sweden)

    Mohammed Abdullahi

    Full Text Available Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS has been shown to perform competitively with Particle Swarm Optimization (PSO. The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA based SOS (SASOS in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan.

  18. Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment

    Science.gov (United States)

    Abdullahi, Mohammed; Ngadi, Md Asri

    2016-01-01

    Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS) has been shown to perform competitively with Particle Swarm Optimization (PSO). The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA) based SOS (SASOS) in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs) which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan. PMID:27348127

  19. COED Transactions, Vol. IX, No. 3, March 1977. Evaluation of a Complex Variable Using Analog/Hybrid Computation Techniques.

    Science.gov (United States)

    Marcovitz, Alan B., Ed.

    Described is the use of an analog/hybrid computer installation to study those physical phenomena that can be described through the evaluation of an algebraic function of a complex variable. This is an alternative way to study such phenomena on an interactive graphics terminal. The typical problem used, involving complex variables, is that of…

  20. Identification of Dekkera bruxellensis (Brettanomyces) from wine by fluorescence in situ hybridization using peptide nucleic acid probes.

    Science.gov (United States)

    Stender, H; Kurtzman, C; Hyldig-Nielsen, J J; Sørensen, D; Broomer, A; Oliveira, K; Perry-O'Keefe, H; Sage, A; Young, B; Coull, J

    2001-02-01

    A new fluorescence in situ hybridization method using peptide nucleic acid (PNA) probes for identification of Brettanomyces is described. The test is based on fluorescein-labeled PNA probes targeting a species-specific sequence of the rRNA of Dekkera bruxellensis. The PNA probes were applied to smears of colonies, and results were interpreted by fluorescence microscopy. The results obtained from testing 127 different yeast strains, including 78 Brettanomyces isolates from wine, show that the spoilage organism Brettanomyces belongs to the species D. bruxellensis and that the new method is able to identify Brettanomyces (D. bruxellensis) with 100% sensitivity and 100% specificity.

  1. Computational identification and analysis of novel sugarcane microRNAs

    Directory of Open Access Journals (Sweden)

    Thiebaut Flávia

    2012-07-01

    Full Text Available Abstract Background MicroRNA-regulation of gene expression plays a key role in the development and response to biotic and abiotic stresses. Deep sequencing analyses accelerate the process of small RNA discovery in many plants and expand our understanding of miRNA-regulated processes. We therefore undertook small RNA sequencing of sugarcane miRNAs in order to understand their complexity and to explore their role in sugarcane biology. Results A bioinformatics search was carried out to discover novel miRNAs that can be regulated in sugarcane plants submitted to drought and salt stresses, and under pathogen infection. By means of the presence of miRNA precursors in the related sorghum genome, we identified 623 candidates of new mature miRNAs in sugarcane. Of these, 44 were classified as high confidence miRNAs. The biological function of the new miRNAs candidates was assessed by analyzing their putative targets. The set of bona fide sugarcane miRNA includes those likely targeting serine/threonine kinases, Myb and zinc finger proteins. Additionally, a MADS-box transcription factor and an RPP2B protein, which act in development and disease resistant processes, could be regulated by cleavage (21-nt-species and DNA methylation (24-nt-species, respectively. Conclusions A large scale investigation of sRNA in sugarcane using a computational approach has identified a substantial number of new miRNAs and provides detailed genotype-tissue-culture miRNA expression profiles. Comparative analysis between monocots was valuable to clarify aspects about conservation of miRNA and their targets in a plant whose genome has not yet been sequenced. Our findings contribute to knowledge of miRNA roles in regulatory pathways in the complex, polyploidy sugarcane genome.

  2. Identification of metabolites with anticancer properties by computational metabolomics

    Directory of Open Access Journals (Sweden)

    Bowen Nathan J

    2008-06-01

    Full Text Available Abstract Background Certain endogenous metabolites can influence the rate of cancer cell growth. For example, diacylglycerol, ceramides and sphingosine, NAD+ and arginine exert this effect by acting as signaling molecules, while carrying out other important cellular functions. Metabolites can also be involved in the control of cell proliferation by directly regulating gene expression in ways that are signaling pathway-independent, e.g. by direct activation of transcription factors or by inducing epigenetic processes. The fact that metabolites can affect the cancer process on so many levels suggests that the change in concentration of some metabolites that occurs in cancer cells could have an active role in the progress of the disease. Results CoMet, a fully automated Computational Metabolomics method to predict changes in metabolite levels in cancer cells compared to normal references has been developed and applied to Jurkat T leukemia cells with the goal of testing the following hypothesis: Up or down regulation in cancer cells of the expression of genes encoding for metabolic enzymes leads to changes in intracellular metabolite concentrations that contribute to disease progression. All nine metabolites predicted to be lowered in Jurkat cells with respect to lymphoblasts that were examined (riboflavin, tryptamine, 3-sulfino-L-alanine, menaquinone, dehydroepiandrosterone, α-hydroxystearic acid, hydroxyacetone, seleno-L-methionine and 5,6-dimethylbenzimidazole, exhibited antiproliferative activity that has not been reported before, while only two (bilirubin and androsterone of the eleven tested metabolites predicted to be increased or unchanged in Jurkat cells displayed significant antiproliferative activity. Conclusion These results: a demonstrate that CoMet is a valuable method to identify potential compounds for experimental validation, b indicate that cancer cell metabolism may be regulated to reduce the intracellular concentration of

  3. Computer modeling for investigating the stress-strainstate of beams with hybrid reinforcement

    Directory of Open Access Journals (Sweden)

    Rakhmonov Ahmadzhon Dzhamoliddinovich

    2014-01-01

    Full Text Available In this article the operation of a continuous double-span beam with hybrid reinforcement, steel and composite reinforcement under the action of concentrated forces is considered. The nature of stress-strain state of structures is investigated with the help of computer modeling using a three-dimensional model. Five models of beams with different characteristics were studied. According to the results of numerical studies the data on the distribution of stresses and displacements in continuous beams was provided. The dependence of the stress-strain state on increasing the percentage of the top reinforcement (composite of fittings and change in the concrete class is determined and presented in the article. Currently, the interest in the use of composite reinforcement as a working reinforcement of concrete structures in Russia has increased significantly, which is reflected in the increase of the number of scientific and practical publications devoted to the study of the properties and use of composite materials in construction, as well as emerging draft documents for design of such structures. One of the proposals for basalt reinforcement application is to use it in bending elements with combined reinforcement. For theoretical justification of the proposed nature of reinforcement and improvement of the calculation method the authors conduct a study of stress-strain state of continuous beams with the use of modern computing systems. The software program LIRA is most often used compared to other programs representing strain-stress state analysis of concrete structures.

  4. A Hybrid Scheme for Fine-Grained Search and Access Authorization in Fog Computing Environment

    Science.gov (United States)

    Xiao, Min; Zhou, Jing; Liu, Xuejiao; Jiang, Mingda

    2017-01-01

    In the fog computing environment, the encrypted sensitive data may be transferred to multiple fog nodes on the edge of a network for low latency; thus, fog nodes need to implement a search over encrypted data as a cloud server. Since the fog nodes tend to provide service for IoT applications often running on resource-constrained end devices, it is necessary to design lightweight solutions. At present, there is little research on this issue. In this paper, we propose a fine-grained owner-forced data search and access authorization scheme spanning user-fog-cloud for resource constrained end users. Compared to existing schemes only supporting either index encryption with search ability or data encryption with fine-grained access control ability, the proposed hybrid scheme supports both abilities simultaneously, and index ciphertext and data ciphertext are constructed based on a single ciphertext-policy attribute based encryption (CP-ABE) primitive and share the same key pair, thus the data access efficiency is significantly improved and the cost of key management is greatly reduced. Moreover, in the proposed scheme, the resource constrained end devices are allowed to rapidly assemble ciphertexts online and securely outsource most of decryption task to fog nodes, and mediated encryption mechanism is also adopted to achieve instantaneous user revocation instead of re-encrypting ciphertexts with many copies in many fog nodes. The security and the performance analysis show that our scheme is suitable for a fog computing environment. PMID:28629131

  5. Hybrid hierarchical bio-based materials: Development and characterization through experimentation and computational simulations

    Science.gov (United States)

    Haq, Mahmoodul

    Environmentally friendly bio-based composites with improved properties can be obtained by harnessing the synergy offered by hybrid constituents such as multiscale (nano- and micro-scale) reinforcement in bio-based resins composed of blends of synthetic and natural resins. Bio-based composites have recently gained much attention due to their low cost, environmental appeal and their potential to compete with synthetic composites. The advantage of multiscale reinforcement is that it offers synergy at various length scales, and when combined with bio-based resins provide stiffness-toughness balance, improved thermal and barrier properties, and increased environmental appeal to the resulting composites. Moreover, these hybrid materials are tailorable in performance and in environmental impact. While the use of different concepts of multiscale reinforcement has been studied for synthetic composites, the study of mukiphase/multiscale reinforcements for developing new types of sustainable materials is limited. The research summarized in this dissertation focused on development of multiscale reinforced bio-based composites and the effort to understand and exploit the synergy of its constituents through experimental characterization and computational simulations. Bio-based composites consisting of petroleum-based resin (unsaturated polyester), natural or bio-resin (epoxidized soybean and linseed oils), natural fibers (industrial hemp), and nanosilicate (nanoclay) inclusions were developed. The work followed the "materials by Mahmoodul Haq design" philosophy by incorporating an integrated experimental and computational approach to strategically explore the design possibilities and limits. Experiments demonstrated that the drawbacks of bio-resin addition, which lowers stiffness, strength and increases permeability, can be counter-balanced through nanoclay reinforcement. Bio-resin addition yields benefits in impact strength and ductility. Conversely, nanoclay enhances stiffness

  6. Identification of warm day and cool night conditions induced flowering-related genes in a Phalaenopsis orchid hybrid by suppression subtractive hybridization.

    Science.gov (United States)

    Li, D M; Lü, F B; Zhu, G F; Sun, Y B; Xu, Y C; Jiang, M D; Liu, J W; Wang, Z

    2014-02-14

    The influence of warm day and cool night conditions on induction of spikes in Phalaenopsis orchids has been studied with respect to photosynthetic efficiency, metabolic cycles and physiology. However, molecular events involved in spike emergence induced by warm day and cool night conditions are not clearly understood. We examined gene expression induced by warm day and cool night conditions in the Phalaenopsis hybrid Fortune Saltzman through suppression subtractive hybridization, which allowed identification of flowering-related genes in warm day and cool night conditions in spikes and leaves at vegetative phase grown under warm daily temperatures. In total, 450 presumably regulated expressed sequence tags (ESTs) were identified and classified into functional categories, including metabolism, development, transcription factor, signal transduction, transportation, cell defense, and stress. Furthermore, database comparisons revealed a notable number of Phalaenopsis hybrid Fortune Saltzman ESTs that matched genes with unknown function. The expression profiles of 24 genes (from different functional categories) have been confirmed by quantitative real-time PCR in induced spikes and juvenile apical leaves. The results of the real-time PCR showed that, compared to the vegetative apical leaves, the transcripts of genes encoding flowering locus T, AP1, AP2, KNOX1, knotted1-like homeobox protein, R2R3-like MYB, adenosine kinase 2, S-adenosylmethionine synthetase, dihydroflavonol 4-reductase, and naringenin 3-dioxygenase accumulated significantly higher levels, and genes encoding FCA, retrotransposon protein Ty3 and C3HC4-type RING finger protein accumulated remarkably lower levels in spikes of early developmental stages. These results suggested that the genes of two expression changing trends may play positive and negative roles in the early floral transition of Phalaenopsis orchids. In conclusion, spikes induced by warm day and cool night conditions were complex in

  7. Identification of Culex pipiens complex mosquitoes in a hybrid zone of West Nile virus transmission in Fresno County, California.

    Science.gov (United States)

    McAbee, Rory D; Green, Emily N; Holeman, Jodie; Christiansen, Julie; Frye, Niki; Dealey, Katherine; Mulligan, F Steve; Brault, Aaron C; Cornel, Anthony J

    2008-02-01

    Culex pipiens sensu lato mosquitoes were collected from 24 gravid traps (mid-June to mid-October, 2005) in Fresno County, CA. Captured gravid females were allowed to oviposit before sibling species identification by Ace.2 PCR and detection of West Nile virus (WNV) RNA by RT-PCR were performed on the mother and her offspring. Of the 442 Cx. pipiens s.l. female mosquitoes collected, 88 were positive for WNV viral RNA (peaked in August) with no significant differences among complex members or habitat. Vertical transmission was detected in 4 out of 20 families originating from WNV-positive mothers, however, in only a small number of offspring from each family. Out of 101 families that had PCR-based maternal and offspring identifications, the offspring from 15 families produced inexplicable amplicon patterns, suggesting ambiguities in the PCR assay identifications. Male genitalia (DV/D ratio) and Ace.2 PCR identifications revealed numerous discrepancies in our ability to accurately determine the identity of Cx. pipiens complex members in the hybrid zone of Fresno County.

  8. Automatic artefact removal in a self-paced hybrid brain- computer interface system

    Directory of Open Access Journals (Sweden)

    Yong Xinyi

    2012-07-01

    Full Text Available Abstract Background A novel artefact removal algorithm is proposed for a self-paced hybrid brain-computer interface (BCI system. This hybrid system combines a self-paced BCI with an eye-tracker to operate a virtual keyboard. To select a letter, the user must gaze at the target for at least a specific period of time (dwell time and then activate the BCI by performing a mental task. Unfortunately, electroencephalogram (EEG signals are often contaminated with artefacts. Artefacts change the quality of EEG signals and subsequently degrade the BCI’s performance. Methods To remove artefacts in EEG signals, the proposed algorithm uses the stationary wavelet transform combined with a new adaptive thresholding mechanism. To evaluate the performance of the proposed algorithm and other artefact handling/removal methods, semi-simulated EEG signals (i.e., real EEG signals mixed with simulated artefacts and real EEG signals obtained from seven participants are used. For real EEG signals, the hybrid BCI system’s performance is evaluated in an online-like manner, i.e., using the continuous data from the last session as in a real-time environment. Results With semi-simulated EEG signals, we show that the proposed algorithm achieves lower signal distortion in both time and frequency domains. With real EEG signals, we demonstrate that for dwell time of 0.0s, the number of false-positives/minute is 2 and the true positive rate (TPR achieved by the proposed algorithm is 44.7%, which is more than 15.0% higher compared to other state-of-the-art artefact handling methods. As dwell time increases to 1.0s, the TPR increases to 73.1%. Conclusions The proposed artefact removal algorithm greatly improves the BCI’s performance. It also has the following advantages: a it does not require additional electrooculogram/electromyogram channels, long data segments or a large number of EEG channels, b it allows real-time processing, and c it reduces signal distortion.

  9. Computer-aided identification of prostatic adenocarcinoma: Segmentation of glandular structures

    Directory of Open Access Journals (Sweden)

    Yahui Peng

    2011-01-01

    Full Text Available Background: Identification of individual prostatic glandular structures is an important prerequisite to quantitative histological analysis of prostate cancer with the aid of a computer. We have developed a computer method to segment individual glandular units and to extract quantitative image features, for computer identification of prostatic adenocarcinoma. Methods: Two sets of digital histology images were used: database I (n = 57 for developing and testing the computer technique, and database II (n = 116 for independent validation. The segmentation technique was based on a k-means clustering and a region-growing method. Computer segmentation results were evaluated subjectively and also compared quantitatively against manual gland outlines, using the Jaccard similarity measure. Quantitative features that were extracted from the computer segmentation results include average gland size, spatial gland density, and average gland circularity. Linear discriminant analysis (LDA was used to combine quantitative image features. Classification performance was evaluated with receiver operating characteristic (ROC analysis and the area under the ROC curve (AUC. Results: Jaccard similarity coefficients between computer segmentation and manual outlines of individual glands were between 0.63 and 0.72 for non-cancer and between 0.48 and 0.54 for malignant glands, respectively, similar to an interobserver agreement of 0.79 for non-cancer and 0.75 for malignant glands, respectively. The AUC value for the features of average gland size and gland density combined via LDA was 0.91 for database I and 0.96 for database II. Conclusions: Using a computer, we are able to delineate individual prostatic glands automatically and identify prostatic adenocarcinoma accurately, based on the quantitative image features extracted from computer-segmented glandular structures.

  10. Hybrid grammar-based approach to nonlinear dynamical system identification from biological time series

    Science.gov (United States)

    McKinney, B. A.; Crowe, J. E., Jr.; Voss, H. U.; Crooke, P. S.; Barney, N.; Moore, J. H.

    2006-02-01

    We introduce a grammar-based hybrid approach to reverse engineering nonlinear ordinary differential equation models from observed time series. This hybrid approach combines a genetic algorithm to search the space of model architectures with a Kalman filter to estimate the model parameters. Domain-specific knowledge is used in a context-free grammar to restrict the search space for the functional form of the target model. We find that the hybrid approach outperforms a pure evolutionary algorithm method, and we observe features in the evolution of the dynamical models that correspond with the emergence of favorable model components. We apply the hybrid method to both artificially generated time series and experimentally observed protein levels from subjects who received the smallpox vaccine. From the observed data, we infer a cytokine protein interaction network for an individual’s response to the smallpox vaccine.

  11. Peptide nucleic acid fluorescence in situ hybridization for identification of Listeria genus, Listeria monocytogenes and Listeria ivanovii.

    Science.gov (United States)

    Zhang, Xiaofeng; Wu, Shan; Li, Ke; Shuai, Jiangbing; Dong, Qiang; Fang, Weihuan

    2012-07-02

    A fluorescent in situ hybridization (FISH) method in conjunction with fluorescin-labeled peptide nucleic acid (PNA) probes (PNA-FISH) for detection of Listeria species was developed. In silico analysis showed that three PNA probes Lis-16S-1, Lm-16S-2 and Liv-16S-5 were suitable for specific identification of Listeria genus, Listeria monocytogenes and Listeria ivanovii, respectively. These probes were experimentally verified by their reactivity against 19 strains of six Listeria species (excluding newly described species Listeria marthii and Listeria rocourtiae) and eight other bacterial species. The PNA-FISH method was optimized as 30 min of hybridization with 0.2% Triton X-100 in the solution and used to identify 85 Listeria strains from individual putative Listeria colonies on PALCAM agar plates streaked from selectively enriched cultures of 780 food or food-related samples. Of the 85 Listeria strains, thirty-seven were identified as L. monocytogenes with the probe Lm-16S-2 and two as L. ivanovii with the probe Liv-16S-5 which was in agreement with the results obtained by the API LISTERIA method. Thus, the PNA-FISH protocol has the potential for identification of pathogenic Listeria spp. from food or food-related samples.

  12. HyCFS, a high-resolution shock capturing code for numerical simulation on hybrid computational clusters

    Science.gov (United States)

    Shershnev, Anton A.; Kudryavtsev, Alexey N.; Kashkovsky, Alexander V.; Khotyanovsky, Dmitry V.

    2016-10-01

    The present paper describes HyCFS code, developed for numerical simulation of compressible high-speed flows on hybrid CPU/GPU (Central Processing Unit / Graphical Processing Unit) computational clusters on the basis of full unsteady Navier-Stokes equations, using modern shock capturing high-order TVD (Total Variation Diminishing) and WENO (Weighted Essentially Non-Oscillatory) schemes on general curvilinear structured grids. We discuss the specific features of hybrid architecture and details of program implementation and present the results of code verification.

  13. Blind source computer device identification from recorded VoIP calls for forensic investigation.

    Science.gov (United States)

    Jahanirad, Mehdi; Anuar, Nor Badrul; Wahab, Ainuddin Wahid Abdul

    2017-03-01

    The VoIP services provide fertile ground for criminal activity, thus identifying the transmitting computer devices from recorded VoIP call may help the forensic investigator to reveal useful information. It also proves the authenticity of the call recording submitted to the court as evidence. This paper extended the previous study on the use of recorded VoIP call for blind source computer device identification. Although initial results were promising but theoretical reasoning for this is yet to be found. The study suggested computing entropy of mel-frequency cepstrum coefficients (entropy-MFCC) from near-silent segments as an intrinsic feature set that captures the device response function due to the tolerances in the electronic components of individual computer devices. By applying the supervised learning techniques of naïve Bayesian, linear logistic regression, neural networks and support vector machines to the entropy-MFCC features, state-of-the-art identification accuracy of near 99.9% has been achieved on different sets of computer devices for both call recording and microphone recording scenarios. Furthermore, unsupervised learning techniques, including simple k-means, expectation-maximization and density-based spatial clustering of applications with noise (DBSCAN) provided promising results for call recording dataset by assigning the majority of instances to their correct clusters. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

  14. Potential of Hybrid Computational Phantoms for Retrospective Heart Dosimetry After Breast Radiation Therapy: A Feasibility Study

    Energy Technology Data Exchange (ETDEWEB)

    Moignier, Alexandra, E-mail: alexandra.moignier@irsn.fr [Institut de Radioprotection et de Surete Nucleaire, Fontenay-aux-Roses (France); Derreumaux, Sylvie; Broggio, David; Beurrier, Julien [Institut de Radioprotection et de Surete Nucleaire, Fontenay-aux-Roses (France); Chea, Michel; Boisserie, Gilbert [Groupe Hospitalier Pitie Salpetriere, Service de Radiotherapie, Paris (France); Franck, Didier; Aubert, Bernard [Institut de Radioprotection et de Surete Nucleaire, Fontenay-aux-Roses (France); Mazeron, Jean-Jacques [Groupe Hospitalier Pitie Salpetriere, Service de Radiotherapie, Paris (France)

    2013-02-01

    Purpose: Current retrospective cardiovascular dosimetry studies are based on a representative patient or simple mathematic phantoms. Here, a process of patient modeling was developed to personalize the anatomy of the thorax and to include a heart model with coronary arteries. Methods and Materials: The patient models were hybrid computational phantoms (HCPs) with an inserted detailed heart model. A computed tomography (CT) acquisition (pseudo-CT) was derived from HCP and imported into a treatment planning system where treatment conditions were reproduced. Six current patients were selected: 3 were modeled from their CT images (A patients) and the others were modelled from 2 orthogonal radiographs (B patients). The method performance and limitation were investigated by quantitative comparison between the initial CT and the pseudo-CT, namely, the morphology and the dose calculation were compared. For the B patients, a comparison with 2 kinds of representative patients was also conducted. Finally, dose assessment was focused on the whole coronary artery tree and the left anterior descending coronary. Results: When 3-dimensional anatomic information was available, the dose calculations performed on the initial CT and the pseudo-CT were in good agreement. For the B patients, comparison of doses derived from HCP and representative patients showed that the HCP doses were either better or equivalent. In the left breast radiation therapy context and for the studied cases, coronary mean doses were at least 5-fold higher than heart mean doses. Conclusions: For retrospective dose studies, it is suggested that HCP offers a better surrogate, in terms of dose accuracy, than representative patients. The use of a detailed heart model eliminates the problem of identifying the coronaries on the patient's CT.

  15. Prediction of monthly regional groundwater levels through hybrid soft-computing techniques

    Science.gov (United States)

    Chang, Fi-John; Chang, Li-Chiu; Huang, Chien-Wei; Kao, I.-Feng

    2016-10-01

    Groundwater systems are intrinsically heterogeneous with dynamic temporal-spatial patterns, which cause great difficulty in quantifying their complex processes, while reliable predictions of regional groundwater levels are commonly needed for managing water resources to ensure proper service of water demands within a region. In this study, we proposed a novel and flexible soft-computing technique that could effectively extract the complex high-dimensional input-output patterns of basin-wide groundwater-aquifer systems in an adaptive manner. The soft-computing models combined the Self Organized Map (SOM) and the Nonlinear Autoregressive with Exogenous Inputs (NARX) network for predicting monthly regional groundwater levels based on hydrologic forcing data. The SOM could effectively classify the temporal-spatial patterns of regional groundwater levels, the NARX could accurately predict the mean of regional groundwater levels for adjusting the selected SOM, the Kriging was used to interpolate the predictions of the adjusted SOM into finer grids of locations, and consequently the prediction of a monthly regional groundwater level map could be obtained. The Zhuoshui River basin in Taiwan was the study case, and its monthly data sets collected from 203 groundwater stations, 32 rainfall stations and 6 flow stations during 2000 and 2013 were used for modelling purpose. The results demonstrated that the hybrid SOM-NARX model could reliably and suitably predict monthly basin-wide groundwater levels with high correlations (R2 > 0.9 in both training and testing cases). The proposed methodology presents a milestone in modelling regional environmental issues and offers an insightful and promising way to predict monthly basin-wide groundwater levels, which is beneficial to authorities for sustainable water resources management.

  16. Computing membrane-AQP5-phosphatidylserine binding affinities with hybrid steered molecular dynamics approach.

    Science.gov (United States)

    Chen, Liao Y

    2015-01-01

    In order to elucidate how phosphatidylserine (PS6) interacts with AQP5 in a cell membrane, we developed a hybrid steered molecular dynamics (hSMD) method that involved: (1) Simultaneously steering two centers of mass of two selected segments of the ligand, and (2) equilibrating the ligand-protein complex with and without biasing the system. Validating hSMD, we first studied vascular endothelial growth factor receptor 1 (VEGFR1) in complex with N-(4-Chlorophenyl)-2-((pyridin-4-ylmethyl)amino)benzamide (8ST), for which the binding energy is known from in vitro experiments. In this study, our computed binding energy well agreed with the experimental value. Knowing the accuracy of this hSMD method, we applied it to the AQP5-lipid-bilayer system to answer an outstanding question relevant to AQP5's physiological function: Will the PS6, a lipid having a single long hydrocarbon tail that was found in the central pore of the AQP5 tetramer crystal, actually bind to and inhibit AQP5's central pore under near-physiological conditions, namely, when AQP5 tetramer is embedded in a lipid bilayer? We found, in silico, using the CHARMM 36 force field, that binding PS6 to AQP5 was a factor of 3 million weaker than "binding" it in the lipid bilayer. This suggests that AQP5's central pore will not be inhibited by PS6 or a similar lipid in a physiological environment.

  17. Tools for Brain-Computer Interaction: a general concept for a hybrid BCI (hBCI

    Directory of Open Access Journals (Sweden)

    Gernot R. Mueller-Putz

    2011-11-01

    Full Text Available The aim of this work is to present the development of a hybrid Brain-Computer Interface (hBCI which combines existing input devices with a BCI. Thereby, the BCI should be available if the user wishes to extend the types of inputs available to an assistive technology system, but the user can also choose not to use the BCI at all; the BCI is active in the background. The hBCI might decide on the one hand which input channel(s offer the most reliable signal(s and switch between input channels to improve information transfer rate, usability, or other factors, or on the other hand fuse various input channels. One major goal therefore is to bring the BCI technology to a level where it can be used in a maximum number of scenarios in a simple way. To achieve this, it is of great importance that the hBCI is able to operate reliably for long periods, recognizing and adapting to changes as it does so. This goal is only possible if many different subsystems in the hBCI can work together. Since one research institute alone cannot provide such different functionality, collaboration between institutes is necessary. To allow for such a collaboration, a common software framework was investigated.

  18. sBCI-Headset—Wearable and Modular Device for Hybrid Brain-Computer Interface

    Directory of Open Access Journals (Sweden)

    Tatsiana Malechka

    2015-02-01

    Full Text Available Severely disabled people, like completely paralyzed persons either with tetraplegia or similar disabilities who cannot use their arms and hands, are often considered as a user group of Brain Computer Interfaces (BCI. In order to achieve high acceptance of the BCI by this user group and their supporters, the BCI system has to be integrated into their support infrastructure. Critical disadvantages of a BCI are the time consuming preparation of the user for the electroencephalography (EEG measurements and the low information transfer rate of EEG based BCI. These disadvantages become apparent if a BCI is used to control complex devices. In this paper, a hybrid BCI is described that enables research for a Human Machine Interface (HMI that is optimally adapted to requirements of the user and the tasks to be carried out. The solution is based on the integration of a Steady-state visual evoked potential (SSVEP-BCI, an Event-related (de-synchronization (ERD/ERS-BCI, an eye tracker, an environmental observation camera, and a new EEG head cap for wearing comfort and easy preparation. The design of the new fast multimodal BCI (called sBCI system is described and first test results, obtained in experiments with six healthy subjects, are presented. The sBCI concept may also become useful for healthy people in cases where a “hands-free” handling of devices is necessary.

  19. Two molecular markers based on mitochondrial genomes for varieties identification of the northern snakehead (Channa argus) and blotched snakehead (Channa maculata) and their reciprocal hybrids.

    Science.gov (United States)

    Xincheng, Zhang; Kunci, Chen; Xinping, Zhu; Jian, Zhao; Qing, Luo; Xiaoyou, Hong; Wei, Li; Fengfang, Xiao

    2015-08-01

    The northern snakehead (Channa argus) and blotched snakehead (Channa maculata) and their reciprocal hybrids have played important roles in the Chinese freshwater aquaculture industry, with an annual production in China exceeding 400 thousand tons. While these are popular aquaculture breeds in China, it is not easy to identify northern snakehead, blotched snakehead, and their hybrids. Thus, a method should be developed to identify these varieties. To distinguish between the reciprocal hybrids (C. argus ♀ × C. maculata ♂ and C. maculata ♀ × C. argus ♂), the mitochondrial genome sequences of northern snakehead and blotched snakehead and their reciprocal hybrids were compared. Following the alignment and analysis of mtDNA sequences of northern snakehead, blotched snakehead and their hybrids, two pairs of specific primers were designed based on identified differences ranging from 12S rRNA to 16S rRNA gene. The BY1 primers amplified the same bands in the blotched snakehead and the hybrid (C. maculata ♀ × C. argus ♂), while producing no products in northern snakehead and the hybrid (C. argus ♀ × C. maculata ♂). Amplification with WY1 yielded the opposite results. Then, 30 individuals per fish were randomized to verify the primers, and the results showed that the primers were specific for breeds, as intended. The specific primers can not only simply distinguish between two kinds of hybrids, but also rapidly identify the two parents. This study provides a method of molecular marker identification to identify reciprocal hybrids.

  20. Identification of misexpressed genetic elements in hybrids between Drosophila-related species

    Science.gov (United States)

    Lopez-Maestre, Hélène; Carnelossi, Elias A. G.; Lacroix, Vincent; Burlet, Nelly; Mugat, Bruno; Chambeyron, Séverine; Carareto, Claudia M. A.; Vieira, Cristina

    2017-01-01

    Crosses between close species can lead to genomic disorders, often considered to be the cause of hybrid incompatibility, one of the initial steps in the speciation process. How these incompatibilities are established and what are their causes remain unclear. To understand the initiation of hybrid incompatibility, we performed reciprocal crosses between two species of Drosophila (D. mojavensis and D. arizonae) that diverged less than 1 Mya. We performed a genome-wide transcriptomic analysis on ovaries from parental lines and on hybrids from reciprocal crosses. Using an innovative procedure of co-assembling transcriptomes, we show that parental lines differ in the expression of their genes and transposable elements. Reciprocal hybrids presented specific gene categories and few transposable element families misexpressed relative to the parental lines. Because TEs are mainly silenced by piwi-interacting RNAs (piRNAs), we hypothesize that in hybrids the deregulation of specific TE families is due to the absence of such small RNAs. Small RNA sequencing confirmed our hypothesis and we therefore propose that TEs can indeed be major players of genome differentiation and be implicated in the first steps of genomic incompatibilities through small RNA regulation. PMID:28091568

  1. Identification of recent hybridization between gray wolves and domesticated dogs by SNP genotyping.

    Science.gov (United States)

    vonHoldt, Bridgett M; Pollinger, John P; Earl, Dent A; Parker, Heidi G; Ostrander, Elaine A; Wayne, Robert K

    2013-02-01

    The ability to detect recent hybridization between dogs and wolves is important for conservation and legal actions, which often require accurate and rapid resolution of ancestry. The availability of a genetic test for dog-wolf hybrids would greatly support federal and legal enforcement efforts, particularly when the individual in question lacks prior ancestry information. We have developed a panel of 100 unlinked ancestry-informative SNP markers that can detect mixed ancestry within up to four generations of dog-wolf hybridization based on simulations of seven genealogical classes constructed following the rules of Mendelian inheritance. We establish 95 % confidence regions around the spatial clustering of each genealogical class using a tertiary plot of allele dosage and heterozygosity. The first- and second-backcrossed-generation hybrids were the most distinct from parental populations, with >90 % correctly assigned to genealogical class. In this article we provide a tool kit with population-level statistical quantification that can detect recent dog-wolf hybridization using a panel of dog-wolf ancestry-informative SNPs with divergent allele frequency distributions.

  2. Hybrid computational phantoms of the male and female newborn patient: NURBS-based whole-body models

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Choonsik [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL 32611 (United States); Lodwick, Daniel [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL 32611 (United States); Hasenauer, Deanna [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL 32611 (United States); Williams, Jonathan L [Department of Radiology, University of Florida, Gainesville, FL 32611 (United States); Lee, Choonik [MD Anderson Cancer Center-Orlando, Orlando, FL 32806 (United States); Bolch, Wesley E [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL 32611 (United States)

    2007-07-21

    Anthropomorphic computational phantoms are computer models of the human body for use in the evaluation of dose distributions resulting from either internal or external radiation sources. Currently, two classes of computational phantoms have been developed and widely utilized for organ dose assessment: (1) stylized phantoms and (2) voxel phantoms which describe the human anatomy via mathematical surface equations or 3D voxel matrices, respectively. Although stylized phantoms based on mathematical equations can be very flexible in regard to making changes in organ position and geometrical shape, they are limited in their ability to fully capture the anatomic complexities of human internal anatomy. In turn, voxel phantoms have been developed through image-based segmentation and correspondingly provide much better anatomical realism in comparison to simpler stylized phantoms. However, they themselves are limited in defining organs presented in low contrast within either magnetic resonance or computed tomography images-the two major sources in voxel phantom construction. By definition, voxel phantoms are typically constructed via segmentation of transaxial images, and thus while fine anatomic features are seen in this viewing plane, slice-to-slice discontinuities become apparent in viewing the anatomy of voxel phantoms in the sagittal or coronal planes. This study introduces the concept of a hybrid computational newborn phantom that takes full advantage of the best features of both its stylized and voxel counterparts: flexibility in phantom alterations and anatomic realism. Non-uniform rational B-spline (NURBS) surfaces, a mathematical modeling tool traditionally applied to graphical animation studies, was adopted to replace the limited mathematical surface equations of stylized phantoms. A previously developed whole-body voxel phantom of the newborn female was utilized as a realistic anatomical framework for hybrid phantom construction. The construction of a hybrid

  3. Hybrid computational phantoms of the male and female newborn patient: NURBS-based whole-body models

    Science.gov (United States)

    Lee, Choonsik; Lodwick, Daniel; Hasenauer, Deanna; Williams, Jonathan L.; Lee, Choonik; Bolch, Wesley E.

    2007-07-01

    Anthropomorphic computational phantoms are computer models of the human body for use in the evaluation of dose distributions resulting from either internal or external radiation sources. Currently, two classes of computational phantoms have been developed and widely utilized for organ dose assessment: (1) stylized phantoms and (2) voxel phantoms which describe the human anatomy via mathematical surface equations or 3D voxel matrices, respectively. Although stylized phantoms based on mathematical equations can be very flexible in regard to making changes in organ position and geometrical shape, they are limited in their ability to fully capture the anatomic complexities of human internal anatomy. In turn, voxel phantoms have been developed through image-based segmentation and correspondingly provide much better anatomical realism in comparison to simpler stylized phantoms. However, they themselves are limited in defining organs presented in low contrast within either magnetic resonance or computed tomography images—the two major sources in voxel phantom construction. By definition, voxel phantoms are typically constructed via segmentation of transaxial images, and thus while fine anatomic features are seen in this viewing plane, slice-to-slice discontinuities become apparent in viewing the anatomy of voxel phantoms in the sagittal or coronal planes. This study introduces the concept of a hybrid computational newborn phantom that takes full advantage of the best features of both its stylized and voxel counterparts: flexibility in phantom alterations and anatomic realism. Non-uniform rational B-spline (NURBS) surfaces, a mathematical modeling tool traditionally applied to graphical animation studies, was adopted to replace the limited mathematical surface equations of stylized phantoms. A previously developed whole-body voxel phantom of the newborn female was utilized as a realistic anatomical framework for hybrid phantom construction. The construction of a hybrid

  4. Identification of Streptococcus agalactiae by fluorescent in situ hybridization compared to culturing and the determination of prevalence of Streptococcus agalactiae colonization among pregnant women in Bushehr, Iran

    OpenAIRE

    Tajbakhsh, Saeed; Norouzi Esfahani, Marjan; Emaneini, Mohammad; Motamed, Niloofar; Rahmani, Elham; Gharibi, Somayyeh

    2013-01-01

    Background Pregnant women colonized by Streptococcus agalactiae (group B streptococci [GBS]) may transfer this microorganism to their newborns. S. agalactiae is an important cause of pneumonia, sepsis, and meningitis in newborns. Fluorescent in situ hybridization (FISH) is considered as a method of identification in the field of diagnostic microbiology. In this paper, we have designed a study to compare the DNA FISH after 7 h Lim broth enrichment and culturing for the identification of S. aga...

  5. Large-Scale, Multi-Sensor Atmospheric Data Fusion Using Hybrid Cloud Computing

    Science.gov (United States)

    Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

    2015-12-01

    NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, MODIS, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. HySDS is a Hybrid-Cloud Science Data System that has been developed and applied under NASA AIST, MEaSUREs, and ACCESS grants. HySDS uses the SciFlow workflow engine to partition analysis workflows into parallel tasks (e.g. segmenting by time or space) that are pushed into a durable job queue. The tasks are "pulled" from the queue by worker Virtual Machines (VM's) and executed in an on-premise Cloud (Eucalyptus or OpenStack) or at Amazon in the public Cloud or govCloud. In this way, years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the transferred data. We are using HySDS to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a MEASURES grant. We will present the architecture of HySDS, describe the achieved "clock time" speedups in fusing datasets on our own nodes and in the Amazon Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer. Our system demonstrates how one can pull A-Train variables (Levels 2 & 3) on-demand into the Amazon Cloud, and cache only those variables that are heavily used, so that any number of compute jobs can be

  6. Dynamic provisioning of a HEP computing infrastructure on a shared hybrid HPC system

    Science.gov (United States)

    Meier, Konrad; Fleig, Georg; Hauth, Thomas; Janczyk, Michael; Quast, Günter; von Suchodoletz, Dirk; Wiebelt, Bernd

    2016-10-01

    Experiments in high-energy physics (HEP) rely on elaborate hardware, software and computing systems to sustain the high data rates necessary to study rare physics processes. The Institut fr Experimentelle Kernphysik (EKP) at KIT is a member of the CMS and Belle II experiments, located at the LHC and the Super-KEKB accelerators, respectively. These detectors share the requirement, that enormous amounts of measurement data must be processed and analyzed and a comparable amount of simulated events is required to compare experimental results with theoretical predictions. Classical HEP computing centers are dedicated sites which support multiple experiments and have the required software pre-installed. Nowadays, funding agencies encourage research groups to participate in shared HPC cluster models, where scientist from different domains use the same hardware to increase synergies. This shared usage proves to be challenging for HEP groups, due to their specialized software setup which includes a custom OS (often Scientific Linux), libraries and applications. To overcome this hurdle, the EKP and data center team of the University of Freiburg have developed a system to enable the HEP use case on a shared HPC cluster. To achieve this, an OpenStack-based virtualization layer is installed on top of a bare-metal cluster. While other user groups can run their batch jobs via the Moab workload manager directly on bare-metal, HEP users can request virtual machines with a specialized machine image which contains a dedicated operating system and software stack. In contrast to similar installations, in this hybrid setup, no static partitioning of the cluster into a physical and virtualized segment is required. As a unique feature, the placement of the virtual machine on the cluster nodes is scheduled by Moab and the job lifetime is coupled to the lifetime of the virtual machine. This allows for a seamless integration with the jobs sent by other user groups and honors the fairshare

  7. Identification of bacterial invasion in necrotizing enterocolitis specimens using fluorescent in situ hybridization

    NARCIS (Netherlands)

    Heida, F H; Harmsen, H J M; Timmer, A; Kooi, E M W; Bos, A F; Hulscher, J B F

    2016-01-01

    OBJECTIVE: Investigation of bacterial invasion into the intestinal wall in necrotizing enterocolitis (NEC) specimens. STUDY DESIGN: We compared 43 surgical NEC specimens with 43 age-matched controls. We used fluorescent in situ hybridization (FISH), a universal bacterial probe together with species-

  8. Identification of a pheA gene associated with Streptococcus mitis by using suppression subtractive hybridization.

    Science.gov (United States)

    Park, Hee Kuk; Dang, Hien Thanh; Myung, Soon Chul; Kim, Wonyong

    2012-04-01

    We performed suppression subtractive hybridization to identify genomic differences between Streptococcus mitis and Streptococcus pneumoniae. Based on the pheA gene, a primer set specific to S. mitis detection was found in 18 out of 103 S. mitis-specific clones. Our findings would be useful for discrimination of S. mitis from other closely related cocci in the oral environment.

  9. Identification by Suppression Subtractive Hybridization of Frankia Genes Induced under Nitrogen-Fixing Conditions▿ †

    OpenAIRE

    Yamaura, Masatoshi; UCHIUMI, Toshiki; Higashi, Shiro; Abe, Mikiko; Kucho, Ken-ichi

    2010-01-01

    Frankia is an actinobacterium that fixes nitrogen under both symbiotic and free-living conditions. We identified genes upregulated in free-living nitrogen-fixing cells by using suppression subtractive hybridization. They included genes with predicted functions related to nitrogen fixation, as well as with unknown function. Their upregulation was a novel finding in Frankia.

  10. Identification of a pheA Gene Associated with Streptococcus mitis by Using Suppression Subtractive Hybridization

    OpenAIRE

    Park, Hee Kuk; Dang, Hien Thanh; Myung, Soon Chul; Kim, Wonyong

    2012-01-01

    We performed suppression subtractive hybridization to identify genomic differences between Streptococcus mitis and Streptococcus pneumoniae. Based on the pheA gene, a primer set specific to S. mitis detection was found in 18 out of 103 S. mitis-specific clones. Our findings would be useful for discrimination of S. mitis from other closely related cocci in the oral environment.

  11. Mixed model approaches for the identification of QTLs within a maize hybrid breeding program.

    NARCIS (Netherlands)

    Eeuwijk, van F.A.; Boer, M.; Totir, L.; Bink, M.C.A.M.; Wright, D.; Winkler, C.; Podlich, D.; Boldman, K.; Baumgarten, R.; Smalley, M.; Arbelbide, M.; Braak, ter C.J.F.; Cooper, M.

    2010-01-01

    Two outlines for mixed model based approaches to quantitative trait locus (QTL) mapping in existing maize hybrid selection programs are presented: a restricted maximum likelihood (REML) and a Bayesian Markov Chain Monte Carlo (MCMC) approach. The methods use the in-silico-mapping procedure developed

  12. Identification of the Sex of Earlier Embryos from Generic Hybrids of Chicken-Quail by Wpkci

    Institute of Scientific and Technical Information of China (English)

    QIAO Ai-jun; MA Wen-xia; LI Da-quan; MENG Qing-mei

    2008-01-01

    In this study,a protocol was deveolped the sex of earlier embryos of chicken(♂)-quail(♀)hybrids and successfully tested the sex proportion of each period (66-120 h). We acquired cross bred eggs by artificial insemination, hatched them in the same batch according to the standard hatching condition of chicken, and collected earlier living embryos at 66,72,78, 84,90,96,102,108,114, and 120 h randomly. We adopted RT-PCR protocol and multiple PCR, made the known sex quail as the external control, employed β-actin as the internal control, and used primers that were designed according to conservative area of gene Wpkci of quail to identify the sex of earlier hybrid embryos. The results indicated that the primer of Wpkci can be used to identify the sex of hybrid embryos accurately; there were more male than female in earlier embryos, the sex proportion of earlier embryos compared with academic numerical value was significantly different (P0.05). In the present study, we concluded that a simple, fast, credible and stable protocol to identify the sex of earlier hybrids embryos had been established by using primer of Wpkci; in earlier embryos, the death rate of female was higher than that of male and there was no fluctuant peak.

  13. De Novo Identification of Single Nucleotide Mutations in Caenorhabditis elegans Using Array Comparative Genomic Hybridization

    Science.gov (United States)

    Maydan, Jason S.; Okada, H. Mark; Flibotte, Stephane; Edgley, Mark L.; Moerman, Donald G.

    2009-01-01

    Array comparative genomic hybridization (aCGH) has been used primarily to detect copy-number variants between two genomes. Here we report using aCGH to detect single nucleotide mutations on oligonucleotide microarrays with overlapping 50-mer probes. This technique represents a powerful method for rapidly detecting novel homozygous single nucleotide mutations in any organism with a sequenced reference genome. PMID:19189945

  14. MATHEMATICAL MODEL OF HYBRID ELECTRIC VEHICLE HIGH-VOLTAGE BATTERY IDENTIFICATION

    Directory of Open Access Journals (Sweden)

    S. Serikov

    2010-01-01

    Full Text Available The mathematical model of hybrid electric vehicle NiMH high-voltage battery is obtained. This model allows to explore the interaction of vehicle tractive electric drive and high-voltage battery at the electric motive power motion and in the process of recuperation of braking kinetic energy.

  15. Establishment and Identification of Cytoplasmic Male Sterility in Brassica napus by Intergeneric Somatic Hybridization

    Institute of Scientific and Technical Information of China (English)

    HU Qiong; LI Yun-chang; MEI De-sheng; FANG Xiao-ping; Lise N Hansen; Sven B Andersen

    2003-01-01

    Exploitation of novel cytoplasmic male sterility(CMS)is a main approach for widening the cytoplasmic genetic background of hybrid oilseed rape and avoiding epidemic risk in oilseed rape production.In this study,symmetric somatic hybrids between Brassicanapus var.Zhongshuang4 and Sinapis arvensis(Yeyou18)were produced by protoplast fusion.Two of the six established hybrids were male sterile showing trace or no pollen release upon flowering with non-or slightly extended stamens.Using Zhongshuang4 as a recurrent parent to pollinate the male sterile plants,the ratio of male sterile plants increased with the number of backcrosses.As early as in BC3 generation,most of the sterile families had nearly 100%sterile plants.Up to BC4 generation,the male sterility became stable and no fertility segregation was observed.All F1 progenies from tested crosses using restorer and maintainer lines of Polima CMS were 100%sterile,indicating that the established CMS by somatic hybridization is different from Polima CMS.The origin of the cytoplasm and potential use of this hovel CMS in oilseed rape breeding were discussed.Key wotds:Oilseed rape,Protoplast fusion,Cytoplasmic male sterility,Sinapis arvensis

  16. Computer-assisted photo identification outperforms visible implant elastomers in an endangered salamander, Eurycea tonkawae.

    Directory of Open Access Journals (Sweden)

    Nathan F Bendik

    Full Text Available Despite recognition that nearly one-third of the 6300 amphibian species are threatened with extinction, our understanding of the general ecology and population status of many amphibians is relatively poor. A widely-used method for monitoring amphibians involves injecting captured individuals with unique combinations of colored visible implant elastomer (VIE. We compared VIE identification to a less-invasive method - computer-assisted photographic identification (photoID - in endangered Jollyville Plateau salamanders (Eurycea tonkawae, a species with a known range limited to eight stream drainages in central Texas. We based photoID on the unique pigmentation patterns on the dorsal head region of 1215 individual salamanders using identification software Wild-ID. We compared the performance of photoID methods to VIEs using both 'high-quality' and 'low-quality' images, which were taken using two different camera types and technologies. For high-quality images, the photoID method had a false rejection rate of 0.76% compared to 1.90% for VIEs. Using a comparable dataset of lower-quality images, the false rejection rate was much higher (15.9%. Photo matching scores were negatively correlated with time between captures, suggesting that evolving natural marks could increase misidentification rates in longer term capture-recapture studies. Our study demonstrates the utility of large-scale capture-recapture using photo identification methods for Eurycea and other species with stable natural marks that can be reliably photographed.

  17. Numerical methodologies for investigation of moderate-velocity flow using a hybrid computational fluid dynamics - molecular dynamics simulation approach

    Energy Technology Data Exchange (ETDEWEB)

    Ko, Soon Heum [Linkoeping University, Linkoeping (Sweden); Kim, Na Yong; Nikitopoulos, Dimitris E.; Moldovan, Dorel [Louisiana State University, Baton Rouge (United States); Jha, Shantenu [Rutgers University, Piscataway (United States)

    2014-01-15

    Numerical approaches are presented to minimize the statistical errors inherently present due to finite sampling and the presence of thermal fluctuations in the molecular region of a hybrid computational fluid dynamics (CFD) - molecular dynamics (MD) flow solution. Near the fluid-solid interface the hybrid CFD-MD simulation approach provides a more accurate solution, especially in the presence of significant molecular-level phenomena, than the traditional continuum-based simulation techniques. It also involves less computational cost than the pure particle-based MD. Despite these advantages the hybrid CFD-MD methodology has been applied mostly in flow studies at high velocities, mainly because of the higher statistical errors associated with low velocities. As an alternative to the costly increase of the size of the MD region to decrease statistical errors, we investigate a few numerical approaches that reduce sampling noise of the solution at moderate-velocities. These methods are based on sampling of multiple simulation replicas and linear regression of multiple spatial/temporal samples. We discuss the advantages and disadvantages of each technique in the perspective of solution accuracy and computational cost.

  18. Identification and Characterization of VNI/VNII and Novel VNII/VNIV Hybrids and Impact of Hybridization on Virulence and Antifungal Susceptibility Within the C. neoformans/C. gattii Species Complex

    Science.gov (United States)

    Aminnejad, Mojgan; Cogliati, Massimo; Duan, Shuyao; Arabatzis, Michael; Tintelnot, Kathrin; Castañeda, Elizabeth; Lazéra, Marcia; Velegraki, Aristea; Ellis, David; Sorrell, Tania C.; Meyer, Wieland

    2016-01-01

    Cryptococcus neoformans and C. gattii are pathogenic basidiomycetous yeasts and the commonest cause of fungal infection of the central nervous system. Cryptococci are typically haploid but several inter-species, inter-varietal and intra-varietal hybrids have been reported. It has a bipolar mating system with sexual reproduction occurring normally between two individuals with opposite mating types, α and a. This study set out to characterize hybrid isolates within the C. neoformans/C. gattii species complex: seven unisexual mating intra-varietal VNI/VNII (αAAα) and six novel inter-varietal VNII/VNIV (aADα). The URA5-RFLP pattern for VNII/VNIV (aADα) differs from the VNIII (αADa) hybrids. Analysis of the allelic patterns of selected genes for AD hybrids showed 79% or more heterozygosis for the studied loci except for CBS132 (VNIII), which showed 50% of heterozygosity. MALDI-TOF MS was applied to hybrids belonging to different sero/mating type allelic patterns. All hybrid isolates were identified as belonging to the same hybrid group with identification scores ranging between 2.101 to 2.634. All hybrids were virulent when tested in the Galleria mellonella (wax moth) model, except for VNII/VNIV (aADα) hybrids. VNI/VGII hybrids were the most virulent hybrids. Hybrids recovered from larvae manifested a significant increase in capsule and total cell size and produced a low proportion (5–10%) of giant cells compared with the haploid control strains. All strains expressed the major virulence factors—capsule, melanin and phospholipase B—and grew well at 37°C. The minimal inhibitory concentration of nine drugs was measured by micro-broth dilution and compared with published data on haploid strains. MICs were similar amongst hybrids and haploid parental strains. This is the first study reporting natural same sex αAAα intra-varietal VNI/VNII hybrids and aADα inter-varietal VNII/VNIV hybrids. PMID:27764108

  19. Design and performance evaluation of dynamic wavelength scheduled hybrid WDM/TDM PON for distributed computing applications.

    Science.gov (United States)

    Zhu, Min; Guo, Wei; Xiao, Shilin; Dong, Yi; Sun, Weiqiang; Jin, Yaohui; Hu, Weisheng

    2009-01-19

    This paper investigates the design and implementation of distributed computing applications in local area network. We propose a novel Dynamical Wavelength Scheduled Hybrid WDM/TDM Passive Optical Network, which is termed as DWS-HPON. The system is implemented by using spectrum slicing techniques of broadband light source and overlay broadcast-signaling scheme. The Time-Wavelength Co-Allocation (TWCA) Problem is defined and an effective greedy approach to this problem is presented for aggregating large files in distributed computing applications. The simulations demonstrate that the performance is improved significantly compared with the conventional TDM-over-WDM PON.

  20. A Hybrid Approach for Scheduling and Replication based on Multi-criteria Decision Method in Grid Computing

    Directory of Open Access Journals (Sweden)

    Nadia Hadi

    2012-09-01

    Full Text Available Grid computing environments have emerged following the demand of scientists to have a very high computing power and storage capacity. One among the challenges imposed in the use of these environments is the performance problem. To improve performance, scheduling and replicating techniques are used. In this paper we propose an approach to task scheduling combined with data replication decision based on multi criteria principle. This is to improve performance by reducing the response time of tasks and the load of system. This hybrid approach is based on a non-hierarchical model that allows scalability.

  1. Hybrid MPI/OpenMP parallelization of the explicit Volterra integral equation solver for multi-core computer architectures

    KAUST Repository

    Al Jarro, Ahmed

    2011-08-01

    A hybrid MPI/OpenMP scheme for efficiently parallelizing the explicit marching-on-in-time (MOT)-based solution of the time-domain volume (Volterra) integral equation (TD-VIE) is presented. The proposed scheme equally distributes tested field values and operations pertinent to the computation of tested fields among the nodes using the MPI standard; while the source field values are stored in all nodes. Within each node, OpenMP standard is used to further accelerate the computation of the tested fields. Numerical results demonstrate that the proposed parallelization scheme scales well for problems involving three million or more spatial discretization elements. © 2011 IEEE.

  2. MapReduce implementation of a hybrid spectral library-database search method for large-scale peptide identification.

    Science.gov (United States)

    Kalyanaraman, Ananth; Cannon, William R; Latt, Benjamin; Baxter, Douglas J

    2011-11-01

    A MapReduce-based implementation called MR-MSPolygraph for parallelizing peptide identification from mass spectrometry data is presented. The underlying serial method, MSPolygraph, uses a novel hybrid approach to match an experimental spectrum against a combination of a protein sequence database and a spectral library. Our MapReduce implementation can run on any Hadoop cluster environment. Experimental results demonstrate that, relative to the serial version, MR-MSPolygraph reduces the time to solution from weeks to hours, for processing tens of thousands of experimental spectra. Speedup and other related performance studies are also reported on a 400-core Hadoop cluster using spectral datasets from environmental microbial communities as inputs. The source code along with user documentation are available on http://compbio.eecs.wsu.edu/MR-MSPolygraph. ananth@eecs.wsu.edu; william.cannon@pnnl.gov. Supplementary data are available at Bioinformatics online.

  3. A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI.

    Science.gov (United States)

    Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

    2015-10-01

    In this paper, we propose a novel method for modelling functional dynamics in resting-state fMRI (rs-fMRI) for Mild Cognitive Impairment (MCI) identification. Specifically, we devise a hybrid architecture by combining Deep Auto-Encoder (DAE) and Hidden Markov Model (HMM). The roles of DAE and HMM are, respectively, to discover hierarchical non-linear relations among features, by which we transform the original features into a lower dimension space, and to model dynamic characteristics inherent in rs-fMRI, i.e., internal state changes. By building a generative model with HMMs for each class individually, we estimate the data likelihood of a test subject as MCI or normal healthy control, based on which we identify the clinical label. In our experiments, we achieved the maximal accuracy of 81.08% with the proposed method, outperforming state-of-the-art methods in the literature.

  4. A Hybrid Computational Model to Explore the Topological Characteristics of Epithelial Tissues.

    Science.gov (United States)

    González-Valverde, Ismael; García Aznar, José Manuel

    2017-03-01

    Epithelial tissues show a particular topology where cells resemble a polygon-like shape, but some biological processes can alter this tissue topology. During cell proliferation, mitotic cell dilation deforms the tissue and modifies the tissue topology. Additionally, cells are reorganized in the epithelial layer and these rearrangements also alter the polygon distribution. We present here a computer-based hybrid framework focused on the simulation of epithelial layer dynamics that combines discrete and continuum numerical models. In this framework, we consider topological and mechanical aspects of the epithelial tissue. Individual cells in the tissue are simulated by an off-lattice agent-based model, which keeps the information of each cell. In addition, we model the cell-cell interaction forces and the cell cycle. Otherwise, we simulate the passive mechanical behaviour of the cell monolayer using a material that approximates the mechanical properties of the cell. This continuum approach is solved by the finite element method, which uses a dynamic mesh generated by the triangulation of cell polygons. Forces generated by cell-cell interaction in the agent-based model are also applied on the finite element mesh. Cell movement in the agent-based model is driven by the displacements obtained from the deformed finite element mesh of the continuum mechanical approach. We successfully compare the results of our simulations with some experiments about the topology of proliferating epithelial tissues in Drosophila. Our framework is able to model the emergent behaviour of the cell monolayer that is due to local cell-cell interactions, which have a direct influence on the dynamics of the epithelial tissue.

  5. A hybrid three-class brain-computer interface system utilizing SSSEPs and transient ERPs

    Science.gov (United States)

    Breitwieser, Christian; Pokorny, Christoph; Müller-Putz, Gernot R.

    2016-12-01

    Objective. This paper investigates the fusion of steady-state somatosensory evoked potentials (SSSEPs) and transient event-related potentials (tERPs), evoked through tactile simulation on the left and right-hand fingertips, in a three-class EEG based hybrid brain-computer interface. It was hypothesized, that fusing the input signals leads to higher classification rates than classifying tERP and SSSEP individually. Approach. Fourteen subjects participated in the studies, consisting of a screening paradigm to determine person dependent resonance-like frequencies and a subsequent online paradigm. The whole setup of the BCI system was based on open interfaces, following suggestions for a common implementation platform. During the online experiment, subjects were instructed to focus their attention on the stimulated fingertips as indicated by a visual cue. The recorded data were classified during runtime using a multi-class shrinkage LDA classifier and the outputs were fused together applying a posterior probability based fusion. Data were further analyzed offline, involving a combined classification of SSSEP and tERP features as a second fusion principle. The final results were tested for statistical significance applying a repeated measures ANOVA. Main results. A significant classification increase was achieved when fusing the results with a combined classification compared to performing an individual classification. Furthermore, the SSSEP classifier was significantly better in detecting a non-control state, whereas the tERP classifier was significantly better in detecting control states. Subjects who had a higher relative band power increase during the screening session also achieved significantly higher classification results than subjects with lower relative band power increase. Significance. It could be shown that utilizing SSSEP and tERP for hBCIs increases the classification accuracy and also that tERP and SSSEP are not classifying control- and non

  6. Noise Threshold and Resource Cost of Fault-Tolerant Quantum Computing with Majorana Fermions in Hybrid Systems

    Science.gov (United States)

    Li, Ying

    2016-09-01

    Fault-tolerant quantum computing in systems composed of both Majorana fermions and topologically unprotected quantum systems, e.g., superconducting circuits or quantum dots, is studied in this Letter. Errors caused by topologically unprotected quantum systems need to be corrected with error-correction schemes, for instance, the surface code. We find that the error-correction performance of such a hybrid topological quantum computer is not superior to a normal quantum computer unless the topological charge of Majorana fermions is insusceptible to noise. If errors changing the topological charge are rare, the fault-tolerance threshold is much higher than the threshold of a normal quantum computer and a surface-code logical qubit could be encoded in only tens of topological qubits instead of about 1,000 normal qubits.

  7. Dynamic modelling of an adsorption storage tank using a hybrid approach combining computational fluid dynamics and process simulation

    Science.gov (United States)

    Mota, J.P.B.; Esteves, I.A.A.C.; Rostam-Abadi, M.

    2004-01-01

    A computational fluid dynamics (CFD) software package has been coupled with the dynamic process simulator of an adsorption storage tank for methane fuelled vehicles. The two solvers run as independent processes and handle non-overlapping portions of the computational domain. The codes exchange data on the boundary interface of the two domains to ensure continuity of the solution and of its gradient. A software interface was developed to dynamically suspend and activate each process as necessary, and be responsible for data exchange and process synchronization. This hybrid computational tool has been successfully employed to accurately simulate the discharge of a new tank design and evaluate its performance. The case study presented here shows that CFD and process simulation are highly complementary computational tools, and that there are clear benefits to be gained from a close integration of the two. ?? 2004 Elsevier Ltd. All rights reserved.

  8. Computer aided identification of the Ficus L. species by the lamina shape

    Directory of Open Access Journals (Sweden)

    Alexander Z. Gluhov

    2014-04-01

    Full Text Available The development of computer aided plant species determination is the urgent task of the botanical science. Identification is often bases on the morphology of the lamina. It is promising to describe the leaf shapes through the harmonic values of elliptic Fourier decomposition, but the effectiveness of this approach requires further verification. Another task is a comparative evaluation of different classification algorithms. The work was conducted on the 2812 leaves images of the 15 Ficus L. species. To solve the described tasks the optimal set of the Fourier decomposition parameters was determined. The best results are achievable by using the classification with 18 Fourier harmonics. Number of reference points on the outline does not affect the result of the models. We compared an identification accuracy of the 30 classification algorithms. Random forest algorithm had the highest classification accuracy – 98%. Combining different prediction algorithms by stacking improves the efficiency of the leaf shapes recognition.

  9. Computational Acoustic Beamforming for Noise Source Identification for Small Wind Turbines.

    Science.gov (United States)

    Ma, Ping; Lien, Fue-Sang; Yee, Eugene

    2017-01-01

    This paper develops a computational acoustic beamforming (CAB) methodology for identification of sources of small wind turbine noise. This methodology is validated using the case of the NACA 0012 airfoil trailing edge noise. For this validation case, the predicted acoustic maps were in excellent conformance with the results of the measurements obtained from the acoustic beamforming experiment. Following this validation study, the CAB methodology was applied to the identification of noise sources generated by a commercial small wind turbine. The simulated acoustic maps revealed that the blade tower interaction and the wind turbine nacelle were the two primary mechanisms for sound generation for this small wind turbine at frequencies between 100 and 630 Hz.

  10. Computational Acoustic Beamforming for Noise Source Identification for Small Wind Turbines

    Directory of Open Access Journals (Sweden)

    Ping Ma

    2017-01-01

    Full Text Available This paper develops a computational acoustic beamforming (CAB methodology for identification of sources of small wind turbine noise. This methodology is validated using the case of the NACA 0012 airfoil trailing edge noise. For this validation case, the predicted acoustic maps were in excellent conformance with the results of the measurements obtained from the acoustic beamforming experiment. Following this validation study, the CAB methodology was applied to the identification of noise sources generated by a commercial small wind turbine. The simulated acoustic maps revealed that the blade tower interaction and the wind turbine nacelle were the two primary mechanisms for sound generation for this small wind turbine at frequencies between 100 and 630 Hz.

  11. Learning support assessment study of a computer simulation for the development of microbial identification strategies.

    Science.gov (United States)

    Johnson, T E; Gedney, C

    2001-05-01

    This paper describes a study that examined how microbiology students construct knowledge of bacterial identification while using a computer simulation. The purpose of this study was to understand how the simulation affects the cognitive processing of students during thinking, problem solving, and learning about bacterial identification and to determine how the simulation facilitates the learning of a domain-specific problem-solving strategy. As part of an upper-division microbiology course, five students participated in several simulation assignments. The data were collected using think-aloud protocol and video action logs as the students used the simulation. The analysis revealed two major themes that determined the performance of the students: Simulation Usage-how the students used the software features and Problem-Solving Strategy Development-the strategy level students started with and the skill level they achieved when they completed their use of the simulation. SEVERAL CONCLUSIONS EMERGED FROM THE ANALYSIS OF THE DATA: (i) The simulation affects various aspects of cognitive processing by creating an environment that makes it possible to practice the application of a problem-solving strategy. The simulation was used as an environment that allowed students to practice the cognitive skills required to solve an unknown. (ii) Identibacter (the computer simulation) may be considered to be a cognitive tool to facilitate the learning of a bacterial identification problem-solving strategy. (iii) The simulation characteristics did support student learning of a problem-solving strategy. (iv) Students demonstrated problem-solving strategy development specific to bacterial identification. (v) Participants demonstrated an improved performance from their repeated use of the simulation.

  12. Learning Support Assessment Study of a Computer Simulation for the Development of Microbial Identification Strategies

    Directory of Open Access Journals (Sweden)

    Tristan E. Johnson

    2009-12-01

    Full Text Available This paper describes a study that examined how microbiology students construct knowledge of bacterial identification while using a computer simulation. The purpose of this study was to understand how the simulation affects the cognitive processing of students during thinking, problem solving, and learning about bacterial identification and to determine how the simulation facilitates the learning of a domain-specific problem-solving strategy. As part of an upper-division microbiology course, five students participated in several simulation assignments. The data were collected using think-aloud protocol and video action logs as the students used the simulation. The analysis revealed two major themes that determined the performance of the students: Simulation Usage—how the students used the software features and Problem-Solving Strategy Development—the strategy level students started with and the skill level they achieved when they completed their use of the simulation. Several conclusions emerged from the analysis of the data: (i The simulation affects various aspects of cognitive processing by creating an environment that makes it possible to practice the application of a problem-solving strategy. The simulation was used as an environment that allowed students to practice the cognitive skills required to solve an unknown. (ii Identibacter (the computer simulation may be considered to be a cognitive tool to facilitate the learning of a bacterial identification problem-solving strategy. (iii The simulation characteristics did support student learning of a problem-solving strategy. (iv Students demonstrated problem-solving strategy development specific to bacterial identification. (v Participants demonstrated an improved performance from their repeated use of the simulation.

  13. Identification of Hybrids in Potamogeton: Incongruence between Plastid and ITS Regions Solved by a Novel Barcoding Marker PHYB

    Science.gov (United States)

    Yang, Tao; Zhang, Tian-lei; Guo, You-hao; Liu, Xing

    2016-01-01

    Potamogeton is one of the most difficult groups to clarify in aquatic plants, which has an extensive range of interspecific morphological and ecological diversity. Internal transcribed spacer (ITS) is prevalent for phylogenetic analysis in plants. However, most researches demonstrate that ITS has a high percentage of homoplasy in phylogenetic datasets. In this study, eighteen materials were collected in Potamogeton from China and incongruence was shown between the rbcL and ITS phylogenies. To solve the discrepancy, we employed a novel barcode PHYB to improve resolution and accuracy of the phylogenetic relationships. The PHYB phylogeny successfully resolved the incongruence between the rbcL and ITS phylogenies. In addition, six hybrids were confirmed using PHYB, including P. compressus × P. pusillus, P. octandrus × P. oxyphyllus, P. gramineus × P. lucens, P. distinctus × P. natans, P. distinctus × P. wrightii, and S. pectinata × S. amblyophylla. Whereas, only one hybrid was identified (P. compressus × P. pusillus) by ITS, indicating that ITS homoplasy was present in Potamogeton and ITS was completely homogenized to one parental lineage. Thus, ITS might have limited utility for phylogenetic relationships in Potamogeton. It is recommended that a three-locus combination of chloroplast DNA gene, ITS and PHYB is potential to effectively reveal more robust phylogenetic relationships and species identification. PMID:27855191

  14. VALIDATION OF AN ALGORITHM FOR NONMETALLIC INTRAOCULAR FOREIGN BODIES' COMPOSITION IDENTIFICATION BASED ON COMPUTED TOMOGRAPHY AND MAGNETIC RESONANCE IMAGING.

    Science.gov (United States)

    Moisseiev, Elad; Barequet, Dana; Zunz, Eran; Barak, Adiel; Mardor, Yael; Last, David; Goez, David; Segal, Zvi; Loewenstein, Anat

    2015-09-01

    To validate and evaluate the accuracy of an algorithm for the identification of nonmetallic intraocular foreign body composition based on computed tomography and magnetic resonance imaging. An algorithm for the identification of 10 nonmetallic materials based on computed tomography and magnetic resonance imaging has been previously determined in an ex vivo porcine model. Materials were classified into 4 groups (plastic, glass, stone, and wood). The algorithm was tested by 40 ophthalmologists, which completed a questionnaire including 10 sets of computed tomography and magnetic resonance images of eyes with intraocular foreign bodies and were asked to use the algorithm to identify their compositions. Rates of exact material identification and group identification were measured. Exact material identification was achieved in 42.75% of the cases, and correct group identification in 65%. Using the algorithm, 6 of the materials were exactly identified by over 50% of the participants, and 7 were correctly classified according to their groups by over 75% of the materials. The algorithm was validated and was found to enable correct identification of nonmetallic intraocular foreign body composition in the majority of cases. This is the first study to report and validate a clinical tool allowing intraocular foreign body composition based on their appearance in computed tomography and magnetic resonance imaging, which was previously impossible.

  15. Detection and identification of intestinal pathogenic bacteria by hybridization to oligonucleotide microarrays

    Institute of Scientific and Technical Information of China (English)

    Lian-Qun Jin; Jun-Wen Li; Sheng-Qi Wang; Fu-Huan Chao; Xin-Wei Wang; Zheng-Quan Yuan

    2005-01-01

    AIM: To detect the common intestinal pathogenic bacteria quickly and accurately.METHODS: A rapid (<3 h) experimental procedure was set up based upon the gene chip technology. Target genes were amplified and hybridized by oligonucleotide microarrays.RESULTS: One hundred and seventy strains of bacteria in pure culture belonging to 11 genera were successfully discriminated under comparatively same conditions, and a series of specific hybridization maps corresponding to each kind of bacteria were obtained. When this method was applied to 26 divided cultures, 25 (96.2%) were identified.CONCLUSION: Salmonella sp., Escherichia coli, Shigella sp., Listeria monocytogenes, Vibrio parahaemolyticus,Staphylococcus aureus, Proteus sp., Bacillus cereus,Vibrio cholerae, Enterococcus faecalis, Yersinia enterocolitica, and Campylobacter jejuni can be detected and identified by our microarrays. The accuracy, range,and discrimination power of this assay can be continually improved by adding further oligonucleotides to the arrays without any significant increase of complexity or cost.

  16. Identification of mosaicism in Prader-Willi syndrome using fluorescent in situ hybridization

    Energy Technology Data Exchange (ETDEWEB)

    Mowery-Rushton, P.A.; Surti, U. [Univ. of Pittsburgh, PA (United States); Hanchett, J.M. [Rehabilitation Inst., Pittsburgh, PA (United States)] [and others

    1996-12-30

    We report on our findings of 4 patients with mosaicism for a deletion of chromosome 15, most commonly associated with Prader-Willi syndrome (PWS). We examined a series of typical and atypical PWS patients in order to identify cytogenetically undetected deletions, using fluorescence in situ hybridization. In 4 of the patients analyzed we detected a deletion in 14-60% of peripheral blood leukocytes, using four commercially available probes. Our results indicate that mosaicism may play a role in the etiology of some PWS cases. These findings may be especially useful in patients who display discrepancies between clinical phenotype and established diagnostic criteria. Methylation and microsatellite polymorphism analyses of 2 patients with low-level mosaicism failed to identify the deletion. We propose that fluorescence in situ hybridization is the most effective method for detecting somatic mosaicism, since a large number of cells can be individually examined for the presence or absence of a specific deletion. 47 refs., 5 figs., 3 tabs.

  17. Identification of sorghum hybrids with high phenotypic stability using GGE biplot methodology.

    Science.gov (United States)

    Teodoro, P E; Almeida Filho, J E; Daher, R F; Menezes, C B; Cardoso, M J; Godinho, V P C; Torres, F E; Tardin, F D

    2016-06-10

    The aim of this study was to identify sorghum hybrids that have both high yield and phenotypic stability in Brazilian environments. Seven trials were conducted between February and March 2011. The experimental design was a randomized complete block with 25 treatments and three replicates. The treatments consisted of 20 simple pre-commercial hybrids and five witnesses of grain sorghum. Sorghum genotypes were analyzed by the genotype main effects + genotype environment interaction (GGE) biplot method if significant genotype x environment interaction, adaptability, and phenotypic stability were detected. GGE biplot methodology identified two groups of environments, the first composed of Água Comprida-MG, Montividiu-GO, and Vilhena- RO and the second of Guaíra-SP and Sete Lagoas-MG. The BRS 308 and 1G282 genotypes were found to have high grain yield, adaptability, and phenotypic stability and are thus indicated for cultivation in the first and second groups of environments, respectively.

  18. Identification of defect-related emissions in ZnO hybrid materials

    Energy Technology Data Exchange (ETDEWEB)

    Niu, Wei; Wang, Xuefeng, E-mail: xfwang@nju.edu.cn; Ye, Jiandong; Gu, Shulin; Shi, Yi; Zhang, Rong [National Laboratory of Solid State Microstructures, Collaborative Innovation Center of Advanced Microstructures, and School of Electronic Science and Engineering, Nanjing University, Nanjing 210093 (China); Zhu, Hao [National Laboratory of Solid State Microstructures, Collaborative Innovation Center of Advanced Microstructures, and Department of Physics, Nanjing University, Nanjing 210093 (China); Department of Materials Science and Engineering, College of Engineering and Applied Sciences, Nanjing University, Nanjing 210093 (China); Song, Fengqi [National Laboratory of Solid State Microstructures, Collaborative Innovation Center of Advanced Microstructures, and Department of Physics, Nanjing University, Nanjing 210093 (China); Zhou, Jianfeng [Department of Materials Science and Engineering, College of Engineering and Applied Sciences, Nanjing University, Nanjing 210093 (China); Xu, Yongbing [National Laboratory of Solid State Microstructures, Collaborative Innovation Center of Advanced Microstructures, and School of Electronic Science and Engineering, Nanjing University, Nanjing 210093 (China); Spintronics and Nanodevice Laboratory, Department of Electronics, University of York, York YO10 5DD (United Kingdom)

    2015-07-13

    ZnO hybrid materials with singly precipitated ZnO nanocrystals embedded in the glass surface were fabricated by melt-quenching method followed by the annealing process. A series of samples containing different densities and species of intrinsic defects were obtained under different annealing conditions in a controllable manner, which was an ideal platform to identify the complicated defect origins. By employing photoluminescence (PL), excitation-dependent PL, PL excitation (PLE), and Raman spectroscopy, the radiative transitions of visible emission bands at around 401, 490, and 528 nm were unambiguously involved with zinc interstitial-related defect levels as initial states, and the corresponding terminal states were suggested to be valence band, oxygen vacancies, and zinc vacancies, respectively. This study may deepen the fundamental understanding of defect-related emissions and physics in ZnO and benefit potential applications of ZnO hybrid materials in optoelectronics.

  19. Identification of cDNAs by direct hybridization using cosmid probes

    Energy Technology Data Exchange (ETDEWEB)

    Lennon, G.G.; Lieuallen, K.

    1993-12-01

    The goal of this effort is to quickly obtain as many chromosome-specific cDNAs with as much map and sequence detail as possible. Many techniques have been proposed to isolate and identify genes within defined genomic regions; the technique discussed here is direct hybridization of a relatively complex genomic probe, an entire cosmid clone, to cDNA libraries. This method continues to be a straightforward technique with a fair number of successes.

  20. Identification and Prediction of Large Pedestrian Flow in Urban Areas Based on a Hybrid Detection Approach

    OpenAIRE

    Kaisheng Zhang; Mei Wang; Bangyang Wei; Daniel(Jian) Sun

    2016-01-01

    Recently, population density has grown quickly with the increasing acceleration of urbanization. At the same time, overcrowded situations are more likely to occur in populous urban areas, increasing the risk of accidents. This paper proposes a synthetic approach to recognize and identify the large pedestrian flow. In particular, a hybrid pedestrian flow detection model was constructed by analyzing real data from major mobile phone operators in China, including information from smartphones and...

  1. Digital processing of in situ hybridization images: identification and spatial allocation of specific labels

    OpenAIRE

    2007-01-01

    In situ hybridization (ISH) method allows to reveal specific genes expression, identify specific cell types and detect areas or tissues, displaying differential gene expression. This work describes a standardized procedure of digital image processing that allows detailed analyses of ISH preparations. We have developed a software that allows through a graphical interface (a) to reliably identify and quantify ISH labels, (b) to locate each label within the image reference system (c) to assemble...

  2. Identification and Prediction of Large Pedestrian Flow in Urban Areas Based on a Hybrid Detection Approach

    OpenAIRE

    Kaisheng Zhang; Mei Wang; Bangyang Wei; Daniel (Jian) Sun

    2016-01-01

    Recently, population density has grown quickly with the increasing acceleration of urbanization. At the same time, overcrowded situations are more likely to occur in populous urban areas, increasing the risk of accidents. This paper proposes a synthetic approach to recognize and identify the large pedestrian flow. In particular, a hybrid pedestrian flow detection model was constructed by analyzing real data from major mobile phone operators in China, including information from smartphones and...

  3. A new method for identification of Trichomonas vaginalis by fluorescent DNA in situ hybridization.

    OpenAIRE

    Muresu, R; Rubino, S.; Rizzu, P.; Baldini, A.; Colombo, M; Cappuccinelli, P.

    1994-01-01

    The protozoan flagellate Trichomonas vaginalis is responsible for human trichomoniasis, one of the most widespread sexually transmitted diseases in the world. Several methods are currently used for laboratory diagnosis, including direct microscopic observation, cell culture, immunological techniques, and more recently, DNA probing and gene amplification. This report describes an in situ hybridization technique with specific DNA probes labeled with either biotin, rhodamine, or fluorescein for ...

  4. AN HYBRID STOCHASTIC-DETERMINISTIC OPTIMIZATION ALGORITHM FOR STRUCTURAL DAMAGE IDENTIFICATION

    OpenAIRE

    Nhamage, Idilson António; Lopez, Rafael Holdorf; Miguel, Leandro Fleck Fadel; Miguel, Letícia Fleck Fadel; Torii, André Jacomel

    2017-01-01

    Abstract. This paper presents a hybrid stochastic/deterministic optimization algorithm to solve the target optimization problem of vibration-based damage detection. The use of a numerical solution of the representation formula to locate the region of the global solution, i.e., to provide a starting point for the local optimizer, which is chosen to be the Nelder-Mead algorithm (NMA), is proposed. A series of numerical examples with different damage scenarios and noise levels was performed unde...

  5. Identification of Shc Src homology 2 domain-binding peptoid-peptide hybrids.

    Science.gov (United States)

    Choi, Won Jun; Kim, Sung-Eun; Stephen, Andrew G; Weidlich, Iwona; Giubellino, Alessio; Liu, Fa; Worthy, Karen M; Bindu, Lakshman; Fivash, Matthew J; Nicklaus, Marc C; Bottaro, Donald P; Fisher, Robert J; Burke, Terrence R

    2009-03-26

    A fluorescence anisotropy (FA) competition-based Shc Src homology 2 (SH2) domain-binding was established using the high affinity fluorescein isothiocyanate (FITC) containing peptide, FITC-NH-(CH2)4-CO-pY-Q-G-L-S-amide (8; Kd = 0.35 microM). Examination of a series of open-chain bis-alkenylamide containing peptides, prepared as ring-closing metathesis precursors, showed that the highest affinities were obtained by replacement of the original Gly residue with N alpha-substituted Gly (NSG) "peptoid" residues. This provided peptoid-peptide hybrids of the form "Ac-pY-Q-[NSG]-L-amide." Depending on the NSG substituent, certain of these hybrids exhibited up to 40-fold higher Shc SH2 domain-binding affinity than the parent Gly-containing peptide (IC50 = 248 microM) (for example, for N-homoallyl analogue 50, IC50 = 6 microM). To our knowledge, this work represents the first successful example of the application of peptoid-peptide hybrids in the design of SH2 domain-binding antagonists. These results could provide a foundation for further structural optimization of Shc SH2 domain-binding peptide mimetics.

  6. Induction and Genetic Identification of Embryogenic Calli from Hybrids of Shatian Pummelo

    Institute of Scientific and Technical Information of China (English)

    SONG Jian-kun; DENG Xiu-xin

    2006-01-01

    Shatian pummelo (Citrus grandis L. Osbeck cv. Shatian) is an elite variety in China, and the regeneration of the embryogenic callus is difficult. Diploid Shatian pummelo was used as the female and crossed with the al lotetraploid somatic hybrid NS (Nova Tangelo + Succari Sweet orange), [ ( C reticulata Blanco × C. paradisi Macf.) cv. Nova + C sinensis L. Osbeck cv.Succari]. About 90 days after pollination, the embryos obtained from crosses were cultured on the solid media of MT + ME (malt extraction, 500 mg L-1) and MT + GA3 (1 mg L-1). The embryogenic callus was initiated from the embryoids and plantlets' hypocotyls and could be subcultured. Flow cytometry and SSR analysis verified that the callus was from the triploid hybrids. The callus had embryogenesis capacity and produced a large number of embryoids on MT + Lactose (50 g L-1) medium after being subcultured for two years. It is comparatively easier to obtain the callus from the hybrid embryo than from Shatian pummelo itself. The callus is valuable for the conservation and utilization of Shatian pummelo.

  7. Bridging Social and Semantic Computing - Design and Evaluation of User Interfaces for Hybrid Systems

    Science.gov (United States)

    Bostandjiev, Svetlin Alex I.

    2012-01-01

    The evolution of the Web brought new interesting problems to computer scientists that we loosely classify in the fields of social and semantic computing. Social computing is related to two major paradigms: computations carried out by a large amount of people in a collective intelligence fashion (i.e. wikis), and performing computations on social…

  8. Assessment of peroxidase isozyme marker-based model for cross identifications in hybrids (F(1)) of urdbean [ Vigna mungo (L.) Hepper].

    Science.gov (United States)

    Upadhyay, R.; Shukla, A.; Gaur, K.

    2002-12-01

    Four hybrids (4 F(1)s) were chosen out of crosses in the urdbean [ Vigna mungo (L.) Hepper, 2n = 22] having contrasting morphological characters. Zymograms for isozyme peroxidase were drawn from the patterns obtained from parents and their respective F(1) hybrids on the basis of relative similarities to parental bands. The selfed or crossed nature of hybrid pods was determined from the zymograms and their analysis. The number of bands and their intensities gave an idea about the extent of crossing in F(1) populations. Genetic identity (I) values were indicative of their selfed nature. Dendrograms were constructed on the basis of genetic identity values to display the relative similarities between the populations. Analysis was based on individual pods to confirm their hybrid or selfed nature. Possible use of this technique for identification of F(1) pods and elimination of selfed pods might be implemented to shorten the breeding operations during crossing.

  9. Social Identification and Interpersonal Communication in Computer-Mediated Communication: What You Do versus Who You Are in Virtual Groups

    Science.gov (United States)

    Wang, Zuoming; Walther, Joseph B.; Hancock, Jeffrey T.

    2009-01-01

    This study investigates the influence of interpersonal communication and intergroup identification on members' evaluations of computer-mediated groups. Participants (N= 256) in 64 four-person groups interacted through synchronous computer chat. Subgroup assignments to minimal groups instilled significantly greater in-group versus out-group…

  10. Toward accurate tooth segmentation from computed tomography images using a hybrid level set model

    Energy Technology Data Exchange (ETDEWEB)

    Gan, Yangzhou; Zhao, Qunfei [Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240 (China); Xia, Zeyang, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn; Hu, Ying [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, and The Chinese University of Hong Kong, Shenzhen 518055 (China); Xiong, Jing, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 510855 (China); Zhang, Jianwei [TAMS, Department of Informatics, University of Hamburg, Hamburg 22527 (Germany)

    2015-01-15

    Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slice and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm{sup 3}) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm{sup 3}, 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm{sup 3}, 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0

  11. Computer-aided system for hazard zone identification in ship power plants

    Institute of Scientific and Technical Information of China (English)

    PODSIADLO A; TARELKO W

    2005-01-01

    The most dangerous places in ships are their power plants. Particularly, they are very unsafe for operators carrying out various necessary operation and maintenance activities. For this reason, ship machinery should be designed to ensure the maximum safety for its operators. It is a very difficult task. Therefore, it could not be solved by means of conventional design methods, which are used for design of uncomplicated technical equipment. One of the possible ways of solving this problem is to provide appropriate tools, which allow us to take the operator's safety into account during a design process, especially at its early stages. A computer-aided system supporting design of safe ship power plants could be such a tool. This paper deals with developing process of a prototype of the computer-aided system for hazard zone identification in ship power plants.

  12. Computational aspects of hot-wire identification of thermal conductivity and diffusivity under high temperature

    Science.gov (United States)

    Vala, Jiří; Jarošová, Petra

    2016-07-01

    Development of advanced materials resistant to high temperature, needed namely for the design of heat storage for low-energy and passive buildings, requires simple, inexpensive and reliable methods of identification of their temperature-sensitive thermal conductivity and diffusivity, covering both well-advised experimental setting and implementation of robust and effective computational algorithms. Special geometrical configurations offer a possibility of quasi-analytical evaluation of temperature development for direct problems, whereas inverse problems of simultaneous evaluation of thermal conductivity and diffusivity must be handled carefully, using some least-squares (minimum variance) arguments. This paper demonstrates the proper mathematical and computational approach to such model problem, thanks to the radial symmetry of hot-wire measurements, including its numerical implementation.

  13. Structure-based virtual screening of the nociceptin receptor: hybrid docking and shape-based approaches for improved hit identification.

    Science.gov (United States)

    Daga, Pankaj R; Polgar, Willma E; Zaveri, Nurulain T

    2014-10-27

    of top-scoring hits resulted in identification of several compounds with measurable binding affinity at the NOP receptor, one of which had a new chemotype for NOP receptor binding. The hybrid ligand-based and structure-based methodology demonstrates an effective approach for virtual screening that leverages existing SAR and receptor structure information for identifying novel hits for NOP receptor binding. The refined active-state NOP homology models obtained from the enrichment studies can be further used for structure-based optimization of these new chemotypes to obtain potent and selective NOP receptor ligands for therapeutic development.

  14. pISTil: a pipeline for yeast two-hybrid Interaction Sequence Tags identification and analysis

    Directory of Open Access Journals (Sweden)

    de Chassey Benoît

    2009-10-01

    Full Text Available Abstract Background High-throughput screening of protein-protein interactions opens new systems biology perspectives for the comprehensive understanding of cell physiology in normal and pathological conditions. In this context, yeast two-hybrid system appears as a promising approach to efficiently reconstruct protein interaction networks at the proteome-wide scale. This protein interaction screening method generates a large amount of raw sequence data, i.e. the ISTs (Interaction Sequence Tags, which urgently need appropriate tools for their systematic and standardised analysis. Findings We develop pISTil, a bioinformatics pipeline combined with a user-friendly web-interface: (i to establish a standardised system to analyse and to annotate ISTs generated by two-hybrid technologies with high performance and flexibility and (ii to provide high-quality protein-protein interaction datasets for systems-level approach. This pipeline has been validated on a large dataset comprising more than 11.000 ISTs. As a case study, a detailed analysis of ISTs obtained from yeast two-hybrid screens of Hepatitis C Virus proteins against human cDNA libraries is also provided. Conclusion We have developed pISTil, an open source pipeline made of a collection of several applications governed by a Perl script. The pISTil pipeline is intended to laboratories, with IT-expertise in system administration, scripting and database management, willing to automatically process large amount of ISTs data for accurate reconstruction of protein interaction networks in a systems biology perspective. pISTil is publicly available for download at http://sourceforge.net/projects/pistil.

  15. Identification of differentially expressed genes after partial rat liver ischemia/reperfusion by suppression subtractive hybridization

    Institute of Scientific and Technical Information of China (English)

    Christine Fallsehr; Christina Zapletal; Michael Kremer; Resit Demir; Magnus von Knebel Doeberitz; Ernst Klar

    2005-01-01

    AIM: To identify potential diagnostic target genes in early reperfusion periods following warm liver ischemia before irreversible liver damage occurs.METHODS: We used two strategies (SSH suppression subtractive hybridization and hybridization of cDNA arrays)to determine early changes in gene expression profiles in a rat model of partial WI/R, comparing postischemic and adjacent nonischemic liver lobes. Differential gene expression was verified (WT/R; 1 h/2 h) and analyzed in more detail after warm ischemia (1 h) in a reperfusion time kinetics (0, 1, 2 and 6 h) and compared to untreated livers by Northern blot hybridizations. Protein expression was examined on Western blots and by immunohistochemistry for four differentially expressed target genes (Hsp70,Hsp27, Gadd45a and IL-1rl).RESULTS: Thirty-two individual WI/R target genes showing altered RNA levels after confirmation by Northern blot analyzes were identified. Among them, six functionally uncharacteristic expressed sequences and 26 known genes (12 induced in postischemic liver lobes, 14 with higher transcriptional expression in adjacent nonischemic liver lobes). Functional categories of the verified marker genes indicate on the one hand cellular stress and tissue damage but otherwise activation of protective cellular reactions (AP-1 transcription factors, apoptosis related genes, heat shock genes). In order to assign the transcriptional status to the biological relevant protein level we demonstrated that Hsp70, Hsp27, Gadd45a and IL-1rI were clearly up-regulated comparing postischemic and untreated rat livers, suggesting their involvement in the WI/R context.CONCLUSION: This study unveils a WI/R response gene set that will help to explore molecular pathways involved in the tissue damage after WI/R. In addition, these genes especially Hsp70and Gadd45a might represent promising new candidates indicating WI/R liver damage.

  16. Application of system identification modelling to solar hybrid systems for predicting radiation, temperature and load

    Energy Technology Data Exchange (ETDEWEB)

    Sinha, S.; Matsumoto, Tsuyoshi; Kojima, Toshinori [Seikei University, Tokyo (Japan). Dept. of Industrial Chemistry; Sanjay Kumar [Kyoto University (Japan). Dept. of Global Environment Engineering

    2001-03-01

    Uncertainties in local solar radiation, ambient temperature and thermal load data have been one of the major factors limiting the reliability and efficiency of solar thermal hybrid systems. In the present paper, moving average auto regressive erogenous (ARX) model based reasoning has been mooted and modified to include moving average method, as an effective tool for predictions of these data. The results show that the method is quite robust and is capable of predicting fairly accurate results, which would make these systems more viable in areas where meteorological data are not available or vague. (author)

  17. Identification of Differentially Expressed Genes During Ethylene Climacteric of Melon Fruit by Suppression Subtractive Hybridization

    Institute of Scientific and Technical Information of China (English)

    GAO Feng; NIU Yi-ding; HAO Jin-feng; BADE Rengui; ZHANG Li-quan; HASI Agula

    2013-01-01

    Melon (Cucumis melo L.) is an important horticultural crop worldwide. Ethylene regulates the ripening process and affects the ripening rate. To screen genes that are differentially expressed at the burst of ethylene climacteric in melon fruit, we performed suppression subtractive hybridization (SSH) to generate forward and reverse libraries, for which we sequenced 439 and 445 clones, respectively. Our BLAST analysis showed that the genes from the 2 libraries were involved in metabolism, signal transduction, cell structure, transcription, translation, and defense. Six genes were analyzed by qRT-PCR during the differential developmental stage of melon fruit. Our results provide new insight into the understanding of climacteric ripening of melon fruit.

  18. A Multi-Compartment Hybrid Computational Model Predicts Key Roles for Dendritic Cells in Tuberculosis Infection

    Directory of Open Access Journals (Sweden)

    Simeone Marino

    2016-10-01

    Full Text Available Tuberculosis (TB is a world-wide health problem with approximately 2 billion people infected with Mycobacterium tuberculosis (Mtb, the causative bacterium of TB. The pathologic hallmark of Mtb infection in humans and Non-Human Primates (NHPs is the formation of spherical structures, primarily in lungs, called granulomas. Infection occurs after inhalation of bacteria into lungs, where resident antigen-presenting cells (APCs, take up bacteria and initiate the immune response to Mtb infection. APCs traffic from the site of infection (lung to lung-draining lymph nodes (LNs where they prime T cells to recognize Mtb. These T cells, circulating back through blood, migrate back to lungs to perform their immune effector functions. We have previously developed a hybrid agent-based model (ABM, labeled GranSim describing in silico immune cell, bacterial (Mtb and molecular behaviors during tuberculosis infection and recently linked that model to operate across three physiological compartments: lung (infection site where granulomas form, lung draining lymph node (LN, site of generation of adaptive immunity and blood (a measurable compartment. Granuloma formation and function is captured by a spatio-temporal model (i.e., ABM, while LN and blood compartments represent temporal dynamics of the whole body in response to infection and are captured with ordinary differential equations (ODEs. In order to have a more mechanistic representation of APC trafficking from the lung to the lymph node, and to better capture antigen presentation in a draining LN, this current study incorporates the role of dendritic cells (DCs in a computational fashion into GranSim. Results: The model was calibrated using experimental data from the lungs and blood of NHPs. The addition of DCs allowed us to investigate in greater detail mechanisms of recruitment, trafficking and antigen presentation and their role in tuberculosis infection. Conclusion: The main conclusion of this study is

  19. Taxonomic identification of mediterranean pines and their hybrids based on the high resolution melting (HRM and trnL approaches: from cytoplasmic inheritance to timber tracing.

    Directory of Open Access Journals (Sweden)

    Ioannis Ganopoulos

    Full Text Available Fast and accurate detection of plant species and their hybrids using molecular tools will facilitate the assessment and monitoring of local biodiversity in an era of climate and environmental change. Herein, we evaluate the utility of the plastid trnL marker for species identification applied to Mediterranean pines (Pinus spp.. Our results indicate that trnL is a very sensitive marker for delimiting species biodiversity. Furthermore, High Resolution Melting (HRM analysis was exploited as a molecular fingerprint for fast and accurate discrimination of Pinus spp. DNA sequence variants. The trnL approach and the HRM analyses were extended to wood samples of two species (Pinus nigra and Pinus sylvestris with excellent results, congruent to those obtained using leaf tissue. Both analyses demonstrate that hybrids from the P. brutia (maternal parent × P. halepensis (paternal parent cross, exhibit the P. halepensis profile, confirming paternal plastid inheritance in Group Halepensis pines. Our study indicates that a single one-step reaction method and DNA marker are sufficient for the identification of Mediterranean pines, their hybrids and the origin of pine wood. Furthermore, our results underline the potential for certain DNA regions to be used as novel biological information markers combined with existing morphological characters and suggest a relatively reliable and open taxonomic system that can link DNA variation to phenotype-based species or hybrid assignment status and direct taxa identification from recalcitrant tissues such as wood samples.

  20. Precision of cephalometric landmark identification: Cone-beam computed tomography vs conventional cephalometric views

    Science.gov (United States)

    Ludlow, John B.; Gubler, Maritzabel; Cevidanes, Lucia; Mol, André

    2009-01-01

    Introduction In this study, we compared the precision of landmark identification using displays of multi-planar cone-beam computed tomographic (CBCT) volumes and conventional lateral cephalograms (Ceph). Methods Twenty presurgical orthodontic patients were radiographed with conventional Ceph and CBCT techniques. Five observers plotted 24 landmarks using computer displays of multi-planer reconstruction (MPR) CBCT and Ceph views during separate sessions. Absolute differences between each observer’s plot and the mean of all observers were averaged as 1 measure of variability (ODM). The absolute difference of each observer from any other observer was averaged as a second measure of variability (DEO). ANOVA and paired t tests were used to analyze variability differences. Results Radiographic modality and landmark were significant at P <0.0001 for DEO and ODM calculations. DEO calculations of observer variability were consistently greater than ODM. The overall correlation of 1920 paired ODM and DEO measurements was excellent at 0.972. All bilateral landmarks had increased precision when identified in the MPR views. Mediolateral variability was statistically greater than anteroposterior or caudal-cranial variability for 5 landmarks in the MPR views. Conclusions The MPR displays of CBCT volume images provide generally more precise identification of traditional cephalometric landmarks. More precise location of condylion, gonion, and orbitale overcomes the problem of superimposition of these bilateral landmarks seen in Ceph. Greater variability of certain landmarks in the mediolateral direction is probably related to inadequate definition of the landmarks in the third dimension. PMID:19732656

  1. Data of NODDI diffusion metrics in the brain and computer simulation of hybrid diffusion imaging (HYDI acquisition scheme

    Directory of Open Access Journals (Sweden)

    Chandana Kodiweera

    2016-06-01

    Full Text Available This article provides NODDI diffusion metrics in the brains of 52 healthy participants and computer simulation data to support compatibility of hybrid diffusion imaging (HYDI, “Hybrid diffusion imaging” [1] acquisition scheme in fitting neurite orientation dispersion and density imaging (NODDI model, “NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain” [2]. HYDI is an extremely versatile diffusion magnetic resonance imaging (dMRI technique that enables various analyzes methods using a single diffusion dataset. One of the diffusion data analysis methods is the NODDI computation, which models the brain tissue with three compartments: fast isotropic diffusion (e.g., cerebrospinal fluid, anisotropic hindered diffusion (e.g., extracellular space, and anisotropic restricted diffusion (e.g., intracellular space. The NODDI model produces microstructural metrics in the developing brain, aging brain or human brain with neurologic disorders. The first dataset provided here are the means and standard deviations of NODDI metrics in 48 white matter region-of-interest (ROI averaging across 52 healthy participants. The second dataset provided here is the computer simulation with initial conditions guided by the first dataset as inputs and gold standard for model fitting. The computer simulation data provide a direct comparison of NODDI indices computed from the HYDI acquisition [1] to the NODDI indices computed from the originally proposed acquisition [2]. These data are related to the accompanying research article “Age Effects and Sex Differences in Human Brain White Matter of Young to Middle-Aged Adults: A DTI, NODDI, and q-Space Study” [3].

  2. Identification of differentially expressed genes in rat silicosis model by suppression subtractive hybridization analysis

    Institute of Scientific and Technical Information of China (English)

    Zhongyuan Jin; Chunyan Fu; Jifang Wen; Baoan Liu; Deyun Feng; Chen Chen; Xiang Li; Yongbin Hu; Jinwu Peng; Yu Liu; Jing Du

    2008-01-01

    The critical molecular mechanism in the development of the pulmonary fibrosis remains unknown, leaving diagnosed patients with a poor prognosis. To isolate the genes specifi-cally up-regulated in pulmonary fibrosis, we established a rat silicosis model 360 d after treatment with crystalline silica suspension. Radiographs of chests showed that some scattered high-density shadows appeared in the lung field.Typical microscopic fibrosing silicotic nodules formed in the lung,alveolar epithelial cells and bronchial epithelial cells,particularly around the partial fibrosing silicotic nodules;some of them showed atypical hyperplasia that suggested a correlation between silicosis and lung cancer.Suppression subtractive hybridization analysis was performed to compare gene expression in lung tissue with silicosis and normal lung tissue.Reverse transcription-polymerase chain rection showed that the expressions of seven novel cDNA sequences identified by suppression subtractive hybridization in lung tissue with silicosis differed from normal lung tissue. Bioinformatics analysis showed that 47 positive clones rep-resented 35 genes containing two putative proteins and four predicted similar proteins.The analysis also showed that some screened genes in silicosis,such as prolyl 4-hydroxylases,actin-related protein-2/3 complex and acidic mammalian chitinase,have not been previously reported.These genes may provide new clues for investigating the molecular mechanisms in the development of pulmonary fibrosis.

  3. Large Improvements in MS/MS Based Peptide Identification Rates using a Hybrid Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Cannon, William R.; Rawlins, Mitchell M.; Baxter, Douglas J.; Callister, Stephen J.; Lipton, Mary S.; Bryant, Donald A.

    2011-05-06

    We have developed a hybrid method for identifying peptides from global proteomics studies that significantly increases sensitivity and specificity in matching peptides to tandem mass spectra using database searches. The method increased the number of spectra that can be assigned to a peptide in a global proteomics study by 57-147% at an estimated false discovery rate of 5%, with clear room for even greater improvements. The approach combines the general utility of using consensus model spectra typical of database search methods1-3 with the accuracy of the intensity information contained in spectral libraries4-6. This hybrid approach is made possible by recent developments that elucidated the statistical framework common to both data analysis and statistical thermodynamics, resulting in a chemically inspired approach to incorporating fragment intensity information into both database searches and spectral library searches. We applied this approach to proteomics analysis of Synechococcus sp. PCC 7002, a cyanobacterium that is a model organism for studies of photosynthetic carbon fixation and biofuels development. The increased specificity and sensitivity of this approach allowed us to identify many more peptides involved in the processes important for photoautotrophic growth.

  4. Identification of FVIII gene mutations in patients with hemophilia A using new combinatorial sequencing by hybridization

    Directory of Open Access Journals (Sweden)

    Chetta M

    2008-01-01

    Full Text Available Background: Standard methods of mutation detection are time consuming in Hemophilia A (HA rendering their application unavailable in some analysis such as prenatal diagnosis. Objectives: To evaluate the feasibility of combinatorial sequencing-by-hybridization (cSBH as an alternative and reliable tool for mutation detection in FVIII gene. Patients/Methods: We have applied a new method of cSBH that uses two different colors for detection of multiple point mutations in the FVIII gene. The 26 exons encompassing the HA gene were analyzed in 7 newly diagnosed Italian patients and in 19 previously characterized individuals with FVIII deficiency. Results: Data show that, when solution-phase TAMRA and QUASAR labeled 5-mer oligonucleotide sets mixed with unlabeled target PCR templates are co-hybridized in the presence of DNA ligase to universal 6-mer oligonucleotide probe-based arrays, a number of mutations can be successfully detected. The technique was reliable also in identifying a mutant FVIII allele in an obligate heterozygote. A novel missense mutation (Leu1843Thr in exon 16 and three novel neutral polymorphisms are presented with an updated protocol for 2-color cSBH. Conclusions: cSBH is a reliable tool for mutation detection in FVIII gene and may represent a complementary method for the genetic screening of HA patients.

  5. Identification and Prediction of Large Pedestrian Flow in Urban Areas Based on a Hybrid Detection Approach

    Directory of Open Access Journals (Sweden)

    Kaisheng Zhang

    2016-12-01

    Full Text Available Recently, population density has grown quickly with the increasing acceleration of urbanization. At the same time, overcrowded situations are more likely to occur in populous urban areas, increasing the risk of accidents. This paper proposes a synthetic approach to recognize and identify the large pedestrian flow. In particular, a hybrid pedestrian flow detection model was constructed by analyzing real data from major mobile phone operators in China, including information from smartphones and base stations (BS. With the hybrid model, the Log Distance Path Loss (LDPL model was used to estimate the pedestrian density from raw network data, and retrieve information with the Gaussian Progress (GP through supervised learning. Temporal-spatial prediction of the pedestrian data was carried out with Machine Learning (ML approaches. Finally, a case study of a real Central Business District (CBD scenario in Shanghai, China using records of millions of cell phone users was conducted. The results showed that the new approach significantly increases the utility and capacity of the mobile network. A more reasonable overcrowding detection and alert system can be developed to improve safety in subway lines and other hotspot landmark areas, such as the Bundle, People’s Square or Disneyland, where a large passenger flow generally exists.

  6. Identification of cryptic microaberrations in osteosarcoma by high-definition oligonucleotide array comparative genomic hybridization.

    Science.gov (United States)

    Selvarajah, Shamini; Yoshimoto, Maisa; Maire, Georges; Paderova, Jana; Bayani, Jane; Squire, Jeremy A; Zielenska, Maria

    2007-11-01

    Osteosarcoma (OS) is an aggressive bone tumor characterized by complex abnormal karyotypes and a high level of genomic instability. Using high-resolution array comparative genomic hybridization (aCGH), a novel class of localized copy number variations called microaberrations has been detected. These genomic anomalies typically involve DNA imbalances affecting 700 kb to 1 Mb DNA, and are often associated with some type of genetic syndromes. Because the origin of instability in OS is poorly understood, we used aCGH to determine whether microaberrations were a characteristic of four OS cell lines: U-2 OS, HOS, MG-63, and SAOS-2. TP53 is mutated in SAOS-2, a line in which 17 microaberrations were found. In contrast, U-2 OS, which has a wild-type TP53, had only six such anomalies, the lowest incidence. A 500-kb microaberration within a region of gain at 5p15.33 in SAOS-2 was confirmed by fluorescence in situ hybridization. Significantly, this genomic location is close to the TERT gene, a region of gain in all four cell lines. To our knowledge, this is the first systematic analysis of the incidence of microaberrations in OS. The high levels of these anomalies detected suggest that the instability processes in OS that lead to a highly abnormal karyotypes may also be associated with acquisition of genomic microaberrations.

  7. Identification of control targets in Boolean molecular network models via computational algebra.

    Science.gov (United States)

    Murrugarra, David; Veliz-Cuba, Alan; Aguilar, Boris; Laubenbacher, Reinhard

    2016-09-23

    Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type considered is that of Boolean networks. The potential control targets can be represented by a set of nodes and edges that can be manipulated to produce a desired effect on the system. This paper presents a method for the identification of potential intervention targets in Boolean molecular network models using algebraic techniques. The approach exploits an algebraic representation of Boolean networks to encode the control candidates in the network wiring diagram as the solutions of a system of polynomials equations, and then uses computational algebra techniques to find such controllers. The control methods in this paper are validated through the identification of combinatorial interventions in the signaling pathways of previously reported control targets in two well studied systems, a p53-mdm2 network and a blood T cell lymphocyte granular leukemia survival signaling network. Supplementary data is available online and our code in Macaulay2 and Matlab are available via http://www.ms.uky.edu/~dmu228/ControlAlg . This paper presents a novel method for the identification of intervention targets in Boolean network models. The results in this paper show that the proposed methods are useful and efficient for moderately large networks.

  8. Identification of human rotavirus serotype by hybridization to polymerase chain reaction-generated probes derived from a hyperdivergent region of the gene encoding outer capsid protein VP7

    Energy Technology Data Exchange (ETDEWEB)

    Flores, J.; Sears, J.; Schael, I.P.; White, L.; Garcia, D.; Lanata, C.; Kapikian, A.Z. (National Institutes of Health, Bethesda, MD (USA))

    1990-08-01

    We have synthesized {sup 32}P-labeled hybridization probes from a hyperdivergent region (nucleotides 51 to 392) of the rotavirus gene encoding the VP7 glycoprotein by using the polymerase chain reaction method. Both RNA (after an initial reverse transcription step) and cloned cDNA from human rotavirus serotypes 1 through 4 could be used as templates to amplify this region. High-stringency hybridization of each of the four probes to rotavirus RNAs dotted on nylon membranes allowed the specific detection of corresponding sequences and thus permitted identification of the serotype of the strains dotted. The procedure was useful when applied to rotaviruses isolated from field studies.

  9. Computationally Probing the Performance of Hybrid, Heterogeneous, and Homogeneous Iridium-Based Catalysts for Water Oxidation

    Energy Technology Data Exchange (ETDEWEB)

    García-Melchor, Max [SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford CA (United States); Vilella, Laia [Institute of Chemical Research of Catalonia (ICIQ), The Barcelona Institute of Science and Technology (BIST),Tarragona (Spain); Departament de Quimica, Universitat Autonoma de Barcelona, Barcelona (Spain); López, Núria [Institute of Chemical Research of Catalonia (ICIQ), The Barcelona Institute of Science and Technology (BIST), Tarragona (Spain); Vojvodic, Aleksandra [SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park CA (United States)

    2016-04-29

    An attractive strategy to improve the performance of water oxidation catalysts would be to anchor a homogeneous molecular catalyst on a heterogeneous solid surface to create a hybrid catalyst. The idea of this combined system is to take advantage of the individual properties of each of the two catalyst components. We use Density Functional Theory to determine the stability and activity of a model hybrid water oxidation catalyst consisting of a dimeric Ir complex attached on the IrO2(110) surface through two oxygen atoms. We find that homogeneous catalysts can be bound to its matrix oxide without losing significant activity. Hence, designing hybrid systems that benefit from both the high tunability of activity of homogeneous catalysts and the stability of heterogeneous systems seems feasible.

  10. Assigning unique identification numbers to new user accounts and groups in a computing environment with multiple registries

    Science.gov (United States)

    DeRobertis, Christopher V.; Lu, Yantian T.

    2010-02-23

    A method, system, and program storage device for creating a new user account or user group with a unique identification number in a computing environment having multiple user registries is provided. In response to receiving a command to create a new user account or user group, an operating system of a clustered computing environment automatically checks multiple registries configured for the operating system to determine whether a candidate identification number for the new user account or user group has been assigned already to one or more existing user accounts or groups, respectively. The operating system automatically assigns the candidate identification number to the new user account or user group created in a target user registry if the checking indicates that the candidate identification number has not been assigned already to any of the existing user accounts or user groups, respectively.

  11. Person Identification Using Fingerprint by Hybridizing Core Point and Minutiae Features

    Directory of Open Access Journals (Sweden)

    M. Ezhilarasan

    2010-12-01

    Full Text Available Fingerprint recognition refers to the automated method of verifying a match between two human fingerprints. Fingerprints are one of many forms of biometrics used to identify an individual and verify their identity. The nonchangeability of Fingerprints during the human life span and the uniqueness of each individual’s fingerprints are the basis for using fingerprints for identification purposes. The main objective is to provide a high secure unibiometric system using thefingerprint of individuals. The fingerprint trait is chosen becauseof its availability, reliability and high accuracy. Moreover the fingerprint based biometric system can be implemented easily.

  12. [Identification of C(2)M interacting proteins by yeast two-hybrid screening].

    Science.gov (United States)

    Shanshan, Yue; Laixin, Xia

    2015-11-01

    The synaptonemal complex (SC) is a huge structure which assembles between the homologous chromosomes during meiotic prophase I. Drosophila germ cell-specific nucleoprotein C(2)M clustering at chromosomes can induce SC formation. To further study the molecular function and mechanism of C(2)M in meiosis, we constructed a bait vector for C(2)M and used the yeast two-hybrid system to identify C(2)M interacting proteins. Forty interacting proteins were obtained, including many DNA and histone binding proteins, ATP synthases and transcription factors. Gene silencing assays in Drosophila showed that two genes, wech and Psf1, may delay the disappearance of SC. These results indicate that Wech and Psf1 may form a complex with C(2)M to participate in the formation or stabilization of the SC complex.

  13. Online Identification of Power Required for Self-Sustainability of the Battery in Hybrid Electric Vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Malikopoulos, Andreas [ORNL

    2014-01-01

    Hybrid electric vehicles have shown great potential for enhancing fuel economy and reducing emissions. Deriving a power management control policy to distribute the power demanded by the driver optimally to the available subsystems (e.g., the internal combustion engine, motor, generator, and battery) has been a challenging control problem. One of the main aspects of the power management control algorithms is concerned with the self-sustainability of the electrical path, which must be guaranteed for the entire driving cycle. This paper considers the problem of identifying online the power required by the battery to maintain the state of charge within a range of the target value. An algorithm is presented that realizes how much power the engine needs to provide to the battery so that self-sustainability of the electrical path is maintained.

  14. Isolation and identification of genes expressed differentially in rice inflorescence meristem with suppression subtractive hybridization

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    A subtracted cDNA library of rice (Oryza sativa L.) inflorescence meristem (IM) was constructed using the sup-pression subtractive hybridization (SSH) method. The cDNAs of the rice shoot apical meristem (SAM) were used as "driver" and inflorescence meristem (IM) as "tester" in the experiment, respectively. Forty of 250 randomly chosen cDNA clones were identified by differential screening, which were IM-specific or IM-highly expressed. Most of the rice IM cDNAs cloned by SSH appear to represent rare transcripts, 40% of which were derived from truly differentially ex-pressed genes. Of all the forty sequenced cDNA inserts, eleven contain the regions with 60%-90% identity to their homolog in GenBank, eighteen are expected to be new genes, only two correspond to published rice genes.

  15. Identification of triclosan-degrading bacteria using stable isotope probing, fluorescence in situ hybridization and microautoradiography

    DEFF Research Database (Denmark)

    Lolas, Ihab Bishara Lolas; Chen, Xijuan; Bester, Kai

    2012-01-01

    Triclosan is considered a ubiquitous pollutant and can be detected in a wide range of environmental samples. Triclosan removal by wastewater treatment plants has been largely attributed to biodegradation processes; however, very little is known about the micro-organisms involved. In this study, DNA......-based stable isotope probing (DNA-SIP) combined with microautoradiography-fluorescence in situ hybridization (MAR-FISH) was applied to identify active triclosan degraders in an enrichment culture inoculated with activated sludge. Clone library sequences of 16S rRNA genes derived from the heavy DNA fractions...... of enrichment culture incubated with 13C-labelled triclosan showed a predominant enrichment of a single bacterial clade most closely related to the betaproteobacterial genus Methylobacillus. To verify that members of the genus Methylobacillus were actively utilizing triclosan, a specific probe targeting...

  16. Identification and biosynthesis of a novel xanthomonadin-dialkylresorcinol-hybrid from Azoarcus sp. BH72.

    Directory of Open Access Journals (Sweden)

    Tim A Schöner

    Full Text Available A novel xanthomonadin-dialkylresorcinol hybrid named arcuflavin was identified in Azoarcus sp. BH72 by a combination of feeding experiments, HPLC-MS and MALDI-MS and gene clusters encoding the biosynthesis of this non-isoprenoid aryl-polyene containing pigment are reported. A chorismate-utilizing enzyme from the XanB2-type producing 3- and 4-hydroxybenzoic acid and an AMP-ligase encoded by these gene clusters were characterized, that might perform the first two steps of the polyene biosynthesis. Furthermore, a detailed analysis of the already known or novel biosynthesis gene clusters involved in the biosynthesis of polyene containing pigments like arcuflavin, flexirubin and xanthomonadin revealed the presence of similar gene clusters in a wide range of bacterial taxa, suggesting that polyene and polyene-dialkylresorcinol pigments are more widespread than previously realized.

  17. Mode identification using stochastic hybrid models with applications to conflict detection and resolution

    Science.gov (United States)

    Naseri Kouzehgarani, Asal

    2009-12-01

    Most models of aircraft trajectories are non-linear and stochastic in nature; and their internal parameters are often poorly defined. The ability to model, simulate and analyze realistic air traffic management conflict detection scenarios in a scalable, composable, multi-aircraft fashion is an extremely difficult endeavor. Accurate techniques for aircraft mode detection are critical in order to enable the precise projection of aircraft conflicts, and for the enactment of altitude separation resolution strategies. Conflict detection is an inherently probabilistic endeavor; our ability to detect conflicts in a timely and accurate manner over a fixed time horizon is traded off against the increased human workload created by false alarms---that is, situations that would not develop into an actual conflict, or would resolve naturally in the appropriate time horizon-thereby introducing a measure of probabilistic uncertainty in any decision aid fashioned to assist air traffic controllers. The interaction of the continuous dynamics of the aircraft, used for prediction purposes, with the discrete conflict detection logic gives rise to the hybrid nature of the overall system. The introduction of the probabilistic element, common to decision alerting and aiding devices, places the conflict detection and resolution problem in the domain of probabilistic hybrid phenomena. A hidden Markov model (HMM) has two stochastic components: a finite-state Markov chain and a finite set of output probability distributions. In other words an unobservable stochastic process (hidden) that can only be observed through another set of stochastic processes that generate the sequence of observations. The problem of self separation in distributed air traffic management reduces to the ability of aircraft to communicate state information to neighboring aircraft, as well as model the evolution of aircraft trajectories between communications, in the presence of probabilistic uncertain dynamics as well

  18. Chromosome-Specific DNA Repeats: Rapid Identification in Silico and Validation Using Fluorescence in Situ Hybridization

    Directory of Open Access Journals (Sweden)

    Heinz-Ulrich G. Weier

    2012-12-01

    Full Text Available Chromosome enumeration in interphase and metaphase cells using fluorescence in situ hybridization (FISH is an established procedure for the rapid and accurate cytogenetic analysis of cell nuclei and polar bodies, the unambiguous gender determination, as well as the definition of tumor-specific signatures. Present bottlenecks in the procedure are a limited number of commercial, non-isotopically labeled probes that can be combined in multiplex FISH assays and the relatively high price and effort to develop additional probes. We describe a streamlined approach for rapid probe definition, synthesis and validation, which is based on the analysis of publicly available DNA sequence information, also known as “database mining”. Examples of probe preparation for the human gonosomes and chromosome 16 as a selected autosome outline the probe selection strategy, define a timeline for expedited probe production and compare this novel selection strategy to more conventional probe cloning protocols.

  19. Demand Side Management for Stand-Alone Hybrid Power Systems Based on Load Identification

    Directory of Open Access Journals (Sweden)

    Friederich Kupzog

    2012-11-01

    Full Text Available Within the field of Distributed Generation (DG, stand-alone Hybrid Power Systems (HPS are a suitable solution to provide energy to isolated facilities where the connection to a centralized grid is not affordable. The logical evolution of such systems involves the optimization of power resources and related control strategies, but also enhancements concerning the management of energy loads. This paper introduces Demand Side Management (DSM strategies specially designed for HPS. They are applied on a real and patented HPS that consists of PV panels, a diesel generator, an inverter and a set of batteries. DSM strategies are built up on a framework of distributed endpointdevices connected to a central control application where loads are identified according to their behavior. System network components, load definitions, the control application and DSM strategies are depicted. Finally, simulations show illustrative savings achieved by the application of some of the proposed strategies.

  20. Identification of up-regulated genes in human uterine leiomyoma by suppression subtractive hybridization

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    In searching for differentially expressed genes in human uterine leiomyomas (ULs), suppression sub-tractive hybridization was used to construct an UL up-regulated library, which turned out to represent 88genes. After two rounds of screening by reverse Northern analysis, twenty genes were proved to be up-regulated, including seventeen known genes and three genes with unknown function. All these genes werefirstly associated with UL. Three genes with notable difference were selected for Northern confirmationOur results proved the authenticity of the twenty genes. One gene named Phospholipase A2 (PLA2) showedup-regulation in 4/6 of the patients and investigation of tissue distribution indicated that it had obviousexpression in prostate, testis, liver, heart and skeletal muscle.

  1. Identification of cold responsive genes in Pacific white shrimp (Litopenaeus vannamei) by suppression subtractive hybridization.

    Science.gov (United States)

    Peng, Jinxia; Wei, Pinyuan; Chen, Xiuli; Zeng, Digang; Chen, Xiaohan

    2016-01-10

    The Pacific white shrimp (Litopenaeus vannamei) is one of the most widely cultured shrimp species in the world. Despite L. vannamei having tropical origins, it is being reared subtropically, with low temperature stress being one of the most severe threats to its growth, survival and distribution. To unravel the molecular basis of cold tolerance in L. vannamei, the suppression subtractive hybridization (SSH) platform was employed to identify cold responsive genes in the hepatopancreas of L. vannamei. Both forward and reverse cDNA libraries were constructed, followed by dot blot hybridization, cloning, sequence analysis and quantitative real-time PCR. These approaches identified 92 cold induced and 48 cold inhibited ESTs to give a total of 37 cold induced and 17 cold inhibited contigs. Some of the identified genes related to stress response or cell defense, such as tetraspanins (TSPANs), DEAD-box helicase, heat shock proteins (HSPs) and metallothionein (MT), which were more abundant in the forward SSH library than in the reverse SSH library. The most abundant Est was a tetraspanin-8 (TSPAN8) homolog dubbed LvTSPAN8. A multiple sequence alignment and transmembrane domain prediction was also performed for LvTSPAN8. LvTSPAN8 expression was also examined in the gills, muscle, heart and hepatopancreas following cold exposure and showed the highest expression levels in the hepatopancreas. Overall, this study was able to identify several known genes and novel genes via SSH that appear to be associated with cold stress and will help to provide further insights into the molecular mechanisms regulating cold tolerance in L. vannamei.

  2. Identification of differentially expressed genes in Mongolian sheep ovaries by suppression subtractive hybridization.

    Science.gov (United States)

    He, Xiaolong; Li, Bei; Wang, Feng; Tian, Chunying; Rong, Weiheng; Liu, Yongbin

    2012-07-01

    Fecundity is an important trait in sheep. Because it is directly related to production costs and efficiency, it has great economic impact in sheep husbandry. Because Mongolian sheep are a longstanding, indigenous breed, they are genetically related to most other breeds of sheep in China. The study of genes related to reproductive traits is essential to improving the fecundity of Mongolian sheep. In the present study, suppression subtractive hybridization (SSH) was performed using forward and reverse nested primers on cDNA libraries from ovarian tissue of single-bearing (S) and biparous (B) Mongolian sheep (MS). This yielded 768 clones. The length of the inserted fragments ranged from 150 to 1000 bp. From these, dot blot hybridization followed by sequencing and homology blast search in GenBank resolved 373 differentially expressed clones, representing 185 gene sequences (homology >85% and length >200 bp), 10 expressed sequence tags (ESTs; homology >95% and length >100 bp), and 4 unknown ESTs. The analysis of the differentially expressed gene functions allowed these genes to be categorized into seven groups: cell/body or immune defense, metabolism, transportation, nucleic acid modification, cell development, signal transduction, and cell structure. Four differentially expressed genes, a disintegrin and metalloproteinase with thrombospondin motifs 1 (ADAMTS1), inhibitor of DNA binding 3 (ID3), bone morphogenetic protein 6 (BMP6), and integrin beta 1 (ITGB1), were randomly selected and verified using relative quantitative real-time polymerase chain reaction (RQ-PCR). The expression of these genes in BMS ovaries was 30.06, 11.55, 0.82, and 1.12-fold that of SMS ovaries, respectively.

  3. Engine control strategy for a series hybrid electric vehicle incorporating load-leveling and computer controlled energy management

    Energy Technology Data Exchange (ETDEWEB)

    Hochgraf, C.G.; Ryan, M.J.; Wiegman, H.L. [Univ. of Wisconsin, Madison, WI (United States)

    1996-09-01

    This paper identifies important engine, alternator and battery characteristics needed for determining an appropriate engine control strategy for a series hybrid electric vehicle. Examination of these characteristics indicates that a load-leveling strategy applied to the small engine will provide better fuel economy than a power-tracking scheme. An automatic energy management strategy is devised whereby a computer controller determines the engine-alternator turn-on and turn-off conditions and controls the engine-alternator autonomously. Battery state of charge is determined from battery voltage and current measurements. Experimental results of the system`s performance in a test vehicle during city driving are presented.

  4. A selective hybrid stochastic strategy for fuel-cell multi-parameter identification

    Science.gov (United States)

    Guarnieri, Massimo; Negro, Enrico; Di Noto, Vito; Alotto, Piergiorgio

    2016-11-01

    The in situ identification of fuel-cell material parameters is crucial both for guiding the research for advanced functionalized materials and for fitting multiphysics models, which can be used in fuel cell performance evaluation and optimization. However, this identification still remains challenging when dealing with direct measurements. This paper presents a method for achieving this aim by stochastic optimization. Such techniques have been applied to the analysis of fuel cells for ten years, but typically to specific problems and by means of semi-empirical models, with an increased number of articles published in the last years. We present an original formulation that makes use of an accurate zero-dimensional multi-physical model of a polymer electrolyte membrane fuel cell and of two cooperating stochastic algorithms, particle swarm optimization and differential evolution, to extract multiple material parameters (exchange current density, mass transfer coefficient, diffusivity, conductivity, activation barriers …) from the experimental data of polarization curves (i.e. in situ measurements) under some controlled temperature, gas back pressure and humidification. The method is suitable for application in other fields where fitting of multiphysics nonlinear models is involved.

  5. Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review

    Science.gov (United States)

    Fahimi, Farzad; Yaseen, Zaher Mundher; El-shafie, Ahmed

    2017-05-01

    Since the middle of the twentieth century, artificial intelligence (AI) models have been used widely in engineering and science problems. Water resource variable modeling and prediction are the most challenging issues in water engineering. Artificial neural network (ANN) is a common approach used to tackle this problem by using viable and efficient models. Numerous ANN models have been successfully developed to achieve more accurate results. In the current review, different ANN models in water resource applications and hydrological variable predictions are reviewed and outlined. In addition, recent hybrid models and their structures, input preprocessing, and optimization techniques are discussed and the results are compared with similar previous studies. Moreover, to achieve a comprehensive view of the literature, many articles that applied ANN models together with other techniques are included. Consequently, coupling procedure, model evaluation, and performance comparison of hybrid models with conventional ANN models are assessed, as well as, taxonomy and hybrid ANN models structures. Finally, current challenges and recommendations for future researches are indicated and new hybrid approaches are proposed.

  6. Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review

    Science.gov (United States)

    Fahimi, Farzad; Yaseen, Zaher Mundher; El-shafie, Ahmed

    2016-02-01

    Since the middle of the twentieth century, artificial intelligence (AI) models have been used widely in engineering and science problems. Water resource variable modeling and prediction are the most challenging issues in water engineering. Artificial neural network (ANN) is a common approach used to tackle this problem by using viable and efficient models. Numerous ANN models have been successfully developed to achieve more accurate results. In the current review, different ANN models in water resource applications and hydrological variable predictions are reviewed and outlined. In addition, recent hybrid models and their structures, input preprocessing, and optimization techniques are discussed and the results are compared with similar previous studies. Moreover, to achieve a comprehensive view of the literature, many articles that applied ANN models together with other techniques are included. Consequently, coupling procedure, model evaluation, and performance comparison of hybrid models with conventional ANN models are assessed, as well as, taxonomy and hybrid ANN models structures. Finally, current challenges and recommendations for future researches are indicated and new hybrid approaches are proposed.

  7. Introduction and evaluation of a novel hybrid brattice for improved dust control in underground mining faces:A computational study

    Institute of Scientific and Technical Information of China (English)

    Kurnia Jundika C.; Sasmito Agus P.; Hassani Ferri P.; Mujumdar Arun S.

    2015-01-01

    A proper control and management of dust dispersion is essential to ensure safe and productive under-ground working environment. Brattice installation to direct the flow from main shaft to the mining face was found to be the most effective method to disperse dust particle away from the mining face. However, it limits the movement and disturbs the flexibility of the mining fleets and operators at the tunnel. This study proposes a hybrid brattice system-a combination of a physical brattice together with suitable and flexible directed and located air curtains-to mitigate dust dispersion from the mining face and reduce dust concentration to a safe level for the working operators. A validated three-dimensional computa-tional fluid dynamic model utilizing Eulerian–Lagrangian approach is employed to track the dispersion of dust particle. Several possible hybrid brattice scenarios are evaluated with the objective to improve dust management in underground mine. The results suggest that implementation of hybrid brattice is beneficial for the mining operation:up to three times lower dust concentration is achieved as compared to that of the physical brattice without air curtain.

  8. Computational model for supporting SHM systems design: Damage identification via numerical analyses

    Science.gov (United States)

    Sartorato, Murilo; de Medeiros, Ricardo; Vandepitte, Dirk; Tita, Volnei

    2017-02-01

    This work presents a computational model to simulate thin structures monitored by piezoelectric sensors in order to support the design of SHM systems, which use vibration based methods. Thus, a new shell finite element model was proposed and implemented via a User ELement subroutine (UEL) into the commercial package ABAQUS™. This model was based on a modified First Order Shear Theory (FOST) for piezoelectric composite laminates. After that, damaged cantilever beams with two piezoelectric sensors in different positions were investigated by using experimental analyses and the proposed computational model. A maximum difference in the magnitude of the FRFs between numerical and experimental analyses of 7.45% was found near the resonance regions. For damage identification, different levels of damage severity were evaluated by seven damage metrics, including one proposed by the present authors. Numerical and experimental damage metrics values were compared, showing a good correlation in terms of tendency. Finally, based on comparisons of numerical and experimental results, it is shown a discussion about the potentials and limitations of the proposed computational model to be used for supporting SHM systems design.

  9. Dynamic parameters’ identification for the feeding system of computer numerical control machine tools stimulated by G-code

    Directory of Open Access Journals (Sweden)

    Guangsheng Chen

    2015-08-01

    Full Text Available This study proposed a dynamic parameters’ identification method for the feeding system of computer numerical control machine tools based on internal sensor. A simplified control model and linear identification model of the feeding system were established, in which the input and output signals are from sensors embedded in computer numerical control machine tools, and the dynamic parameters of the feeding system, including the equivalent inertia, equivalent damping, worktable damping, and the overall stiffness of the mechanical system, were solved by the least square method. Using the high-order Taylor expansion, the nonlinear Stribeck friction model was linearized and the parameters of the Stribeck friction model were obtained by the same way. To verify the validity and effectiveness of the identification method, identification experiments, circular motion testing, and simulations were conducted. The results obtained were stable and suggested that inertia and damping identification experiments converged fast. Stiffness identification experiments showed some deviation from simulation due to the influences of geometric error and nonlinear of stiffness. However, the identification results were still of reference significance and the method is convenient, effective, and suited for industrial condition.

  10. Identification of genetic loci in Lactobacillus plantarum that modulate the immune response of dendritic cells using comparative genome hybridization.

    Directory of Open Access Journals (Sweden)

    Marjolein Meijerink

    Full Text Available BACKGROUND: Probiotics can be used to stimulate or regulate epithelial and immune cells of the intestinal mucosa and generate beneficial mucosal immunomodulatory effects. Beneficial effects of specific strains of probiotics have been established in the treatment and prevention of various intestinal disorders, including allergic diseases and diarrhea. However, the precise molecular mechanisms and the strain-dependent factors involved are poorly understood. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we aimed to identify gene loci in the model probiotic organism Lactobacillus plantarum WCFS1 that modulate the immune response of host dendritic cells. The amounts of IL-10 and IL-12 secreted by dendritic cells (DCs after stimulation with 42 individual L. plantarum strains were measured and correlated with the strain-specific genomic composition using comparative genome hybridisation and the Random Forest algorithm. This in silico "gene-trait matching" approach led to the identification of eight candidate genes in the L. plantarum genome that might modulate the DC cytokine response to L. plantarum. Six of these genes were involved in bacteriocin production or secretion, one encoded a bile salt hydrolase and one encoded a transcription regulator of which the exact function is unknown. Subsequently, gene deletions mutants were constructed in L. plantarum WCFS1 and compared to the wild-type strain in DC stimulation assays. All three bacteriocin mutants as well as the transcription regulator (lp_2991 had the predicted effect on cytokine production confirming their immunomodulatory effect on the DC response to L. plantarum. Transcriptome analysis and qPCR data showed that transcript level of gtcA3, which is predicted to be involved in glycosylation of cell wall teichoic acids, was substantially increased in the lp_2991 deletion mutant (44 and 29 fold respectively. CONCLUSION: Comparative genome hybridization led to the identification of gene loci in L

  11. Identification of miRNAs Potentially Involved in Bronchiolitis Obliterans Syndrome: A Computational Study.

    Science.gov (United States)

    Di Carlo, Stefano; Rossi, Elena; Politano, Gianfranco; Inghilleri, Simona; Morbini, Patrizia; Calabrese, Fiorella; Benso, Alfredo; Savino, Alessandro; Cova, Emanuela; Zampieri, Davide; Meloni, Federica

    2016-01-01

    The pathogenesis of Bronchiolitis Obliterans Syndrome (BOS), the main clinical phenotype of chronic lung allograft dysfunction, is poorly understood. Recent studies suggest that epigenetic regulation of microRNAs might play a role in its development. In this paper we present the application of a complex computational pipeline to perform enrichment analysis of miRNAs in pathways applied to the study of BOS. The analysis considered the full set of miRNAs annotated in miRBase (version 21), and applied a sequence of filtering approaches and statistical analyses to reduce this set and to score the candidate miRNAs according to their potential involvement in BOS development. Dysregulation of two of the selected candidate miRNAs-miR-34a and miR-21 -was clearly shown in in-situ hybridization (ISH) on five explanted human BOS lungs and on a rat model of acute and chronic lung rejection, thus definitely identifying miR-34a and miR-21 as pathogenic factors in BOS and confirming the effectiveness of the computational pipeline.

  12. Identification of miRNAs Potentially Involved in Bronchiolitis Obliterans Syndrome: A Computational Study

    Science.gov (United States)

    Politano, Gianfranco; Inghilleri, Simona; Morbini, Patrizia; Calabrese, Fiorella; Benso, Alfredo; Savino, Alessandro; Cova, Emanuela; Zampieri, Davide; Meloni, Federica

    2016-01-01

    The pathogenesis of Bronchiolitis Obliterans Syndrome (BOS), the main clinical phenotype of chronic lung allograft dysfunction, is poorly understood. Recent studies suggest that epigenetic regulation of microRNAs might play a role in its development. In this paper we present the application of a complex computational pipeline to perform enrichment analysis of miRNAs in pathways applied to the study of BOS. The analysis considered the full set of miRNAs annotated in miRBase (version 21), and applied a sequence of filtering approaches and statistical analyses to reduce this set and to score the candidate miRNAs according to their potential involvement in BOS development. Dysregulation of two of the selected candidate miRNAs–miR-34a and miR-21 –was clearly shown in in-situ hybridization (ISH) on five explanted human BOS lungs and on a rat model of acute and chronic lung rejection, thus definitely identifying miR-34a and miR-21 as pathogenic factors in BOS and confirming the effectiveness of the computational pipeline. PMID:27564214

  13. Combined fluorescent-chromogenic in situ hybridization for identification and laser microdissection of interphase chromosomes.

    Directory of Open Access Journals (Sweden)

    Nerea Paz

    Full Text Available Chromosome territories constitute the most conspicuous feature of nuclear architecture, and they exhibit non-random distribution patterns in the interphase nucleus. We observed that in cell nuclei from humans with Down Syndrome two chromosomes 21 frequently localize proximal to one another and distant from the third chromosome. To systematically investigate whether the proximally positioned chromosomes were always the same in all cells, we developed an approach consisting of sequential FISH and CISH combined with laser-microdissection of chromosomes from the interphase nucleus and followed by subsequent chromosome identification by microsatellite allele genotyping. This approach identified proximally positioned chromosomes from cultured cells, and the analysis showed that the identity of the chromosomes proximally positioned varies. However, the data suggest that there may be a tendency of the same chromosomes to be positioned close to each other in the interphase nucleus of trisomic cells. The protocol described here represents a powerful new method for genome analysis.

  14. Boechera microsatellite website: an online portal for species identification and determination of hybrid parentage.

    Science.gov (United States)

    Li, Fay-Wei; Rushworth, Catherine A; Beck, James B; Windham, Michael D

    2017-01-01

    Boechera (Brassicaceae) has many features to recommend it as a model genus for ecological and evolutionary research, including species richness, ecological diversity, experimental tractability and close phylogenetic proximity to Arabidopsis . However, efforts to realize the full potential of this model system have been thwarted by the frequent inability of researchers to identify their samples and place them in a broader evolutionary context. Here we present the Boechera Microsatellite Website (BMW), a portal that archives over 55 000 microsatellite allele calls from 4471 specimens (including 133 nomenclatural types). The portal includes analytical tools that utilize data from 15 microsatellite loci as a highly effective DNA barcoding system. The BMW facilitates the accurate identification of Boechera samples and the investigation of reticulate evolution among the ±83 sexual diploid taxa in the genus, thereby greatly enhancing Boechera 's potential as a model system.

  15. FDTD Acceleration for Cylindrical Resonator Design Based on the Hybrid of Single and Double Precision Floating-Point Computation

    Directory of Open Access Journals (Sweden)

    Hasitha Muthumala Waidyasooriya

    2014-01-01

    Full Text Available Acceleration of FDTD (finite-difference time-domain is very important for the fields such as computational electromagnetic simulation. We consider the FDTD simulation model of cylindrical resonator design that requires double precision floating-point and cannot be done using single precision. Conventional FDTD acceleration methods have a common problem of memory-bandwidth limitation due to the large amount of parallel data access. To overcome this problem, we propose a hybrid of single and double precision floating-point computation method that reduces the data-transfer amount. We analyze the characteristics of the FDTD simulation to find out when we can use single precision instead of double precision. According to the experimental results, we achieved over 15 times of speed-up compared to the CPU single-core implementation and over 1.52 times of speed-up compared to the conventional GPU-based implementation.

  16. A low-cost EEG system-based hybrid brain-computer interface for humanoid robot navigation and recognition.

    Science.gov (United States)

    Choi, Bongjae; Jo, Sungho

    2013-01-01

    This paper describes a hybrid brain-computer interface (BCI) technique that combines the P300 potential, the steady state visually evoked potential (SSVEP), and event related de-synchronization (ERD) to solve a complicated multi-task problem consisting of humanoid robot navigation and control along with object recognition using a low-cost BCI system. Our approach enables subjects to control the navigation and exploration of a humanoid robot and recognize a desired object among candidates. This study aims to demonstrate the possibility of a hybrid BCI based on a low-cost system for a realistic and complex task. It also shows that the use of a simple image processing technique, combined with BCI, can further aid in making these complex tasks simpler. An experimental scenario is proposed in which a subject remotely controls a humanoid robot in a properly sized maze. The subject sees what the surrogate robot sees through visual feedback and can navigate the surrogate robot. While navigating, the robot encounters objects located in the maze. It then recognizes if the encountered object is of interest to the subject. The subject communicates with the robot through SSVEP and ERD-based BCIs to navigate and explore with the robot, and P300-based BCI to allow the surrogate robot recognize their favorites. Using several evaluation metrics, the performances of five subjects navigating the robot were quite comparable to manual keyboard control. During object recognition mode, favorite objects were successfully selected from two to four choices. Subjects conducted humanoid navigation and recognition tasks as if they embodied the robot. Analysis of the data supports the potential usefulness of the proposed hybrid BCI system for extended applications. This work presents an important implication for the future work that a hybridization of simple BCI protocols provide extended controllability to carry out complicated tasks even with a low-cost system.

  17. Identification of Bacillus anthracis specific chromosomal sequences by suppressive subtractive hybridization

    Directory of Open Access Journals (Sweden)

    Redkar Rajendra

    2004-02-01

    Full Text Available Abstract Background Bacillus anthracis, Bacillus thuringiensis and Bacillus cereus are closely related members of the B. cereus-group of bacilli. Suppressive subtractive hybridization (SSH was used to identify specific chromosomal sequences unique to B. anthracis. Results Two SSH libraries were generated. Genomic DNA from plasmid-cured B. anthracis was used as the tester DNA in both libraries, while genomic DNA from either B. cereus or B. thuringiensis served as the driver DNA. Progressive screening of the libraries by colony filter and Southern blot analyses identified 29 different clones that were specific for the B. anthracis chromosome relative not only to the respective driver DNAs, but also to seven other different strains of B. cereus and B. thuringiensis included in the process. The nucleotide sequences of the clones were compared with those found in genomic databases, revealing that over half of the clones were located into 2 regions on the B. anthracis chromosome. Conclusions Genes encoding potential cell wall synthesis proteins dominated one region, while bacteriophage-related sequences dominated the other region. The latter supports the hypothesis that acquisition of these bacteriophage sequences occurred during or after speciation of B. anthracis relative to B. cereus and B. thuringiensis. This study provides insight into the chromosomal differences between B. anthracis and its closest phylogenetic relatives.

  18. Identification of mycosis-related genes in the eastern subterranean termite by suppression subtractive hybridization.

    Science.gov (United States)

    Gao, Qi; Tancredi, Sarah E; Thompson, Graham J

    2012-07-01

    The Eastern subterranean termite Reticulitermes flavipes (Isoptera, Rhinotermitidae) is a cosmopolitan, structural pest that is the target of research into termite innate immunity. In this study, we use suppression subtractive hybridization to construct a normalized cDNA library of genes excessively expressed upon fungal infection. At 24 h postinfection with Metarhizium anisopliae, the library revealed 182 expressed sequence tag (EST) clones that potentially represent immune responsive genes. The nucleotide sequence from a majority (97%) of ESTs assembled into a small number (n = 13) of contiguous sequences, with the remainder (n = 6) representing singletons. Our screen therefore captured as many as 19 different mRNAs highly expressed in response to the fungal pathogen at this time. Primary sequencing of all loci revealed that approximately half (n = 10) contained open reading frames with significant similarity to known proteins. These clones represent nuclear and mitochondrial coding genes, as well as putative long noncoding RNA genes. Quantitative polymerase chain reaction analysis of coding genes on independently infected groups of worker termites confirms in each case that the transcripts identified from the library are up-regulated postfungal infection. The genes identified here are relevant to future studies on termite biocontrol and social insect immunity.

  19. Identification of Differentially Expressed Genes Associated with Apple Fruit Ripening and Softening by Suppression Subtractive Hybridization.

    Directory of Open Access Journals (Sweden)

    Zongying Zhang

    Full Text Available Apple is one of the most economically important horticultural fruit crops worldwide. It is critical to gain insights into fruit ripening and softening to improve apple fruit quality and extend shelf life. In this study, forward and reverse suppression subtractive hybridization libraries were generated from 'Taishanzaoxia' apple fruits sampled around the ethylene climacteric to isolate ripening- and softening-related genes. A set of 648 unigenes were derived from sequence alignment and cluster assembly of 918 expressed sequence tags. According to gene ontology functional classification, 390 out of 443 unigenes (88% were assigned to the biological process category, 356 unigenes (80% were classified in the molecular function category, and 381 unigenes (86% were allocated to the cellular component category. A total of 26 unigenes differentially expressed during fruit development period were analyzed by quantitative RT-PCR. These genes were involved in cell wall modification, anthocyanin biosynthesis, aroma production, stress response, metabolism, transcription, or were non-annotated. Some genes associated with cell wall modification, anthocyanin biosynthesis and aroma production were up-regulated and significantly correlated with ethylene production, suggesting that fruit texture, coloration and aroma may be regulated by ethylene in 'Taishanzaoxia'. Some of the identified unigenes associated with fruit ripening and softening have not been characterized in public databases. The results contribute to an improved characterization of changes in gene expression during apple fruit ripening and softening.

  20. Identification of differentially expressed radiation-induced genes in cervix carcinoma cells using suppression subtractive hybridization

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jun Sang; Lee, Young Sook; Lee, Jeung Hoon; Lee, Woong Hee; Seo, Eun Young; Cho, Moon June [Chungnam National University, Daejeon (Korea, Republic of)

    2005-03-15

    A number of genes and their products are induced early or late following exposure of cells to ionizing radiation. These radiation-induced genes have various effects of irradiated cells and tissues. Suppression subtractive hybridization (SSH) based on PCR was used to identify the differentially expressed genes by radiation in cervix carcinoma cells. Total RNA and poly (A){sup +} mRNA were isolated from irradiated and non-irradiated HeLa cells. Forward-and reverse-subtracted cDNA libraries were constructed using SSH. Eighty-eight clones of each were used to randomly select differentially expressed genes using reverse Northern blotting (dot blot analysis). Northern blotting was used to verify the screened genes. Of the 176 clones, 10 genes in the forward-subtracted library and 9 genes in the reverse-subtracted library were identified as differentially expressed radiation-induced genes by PCR-select differential screening. Three clones from the forward-subtracted library were confirmed by Northern blotting, and showed increased expression in a dose-dependent manner, including a telomerase catalytic subunit and sodium channel-like protein gene, and an ESTs (expressed sequence tags) gene. We identified differentially expressed radiation-induced genes with low-abundance genes with SSH, but further characterization of theses genes are necessary to clarify the biological functions of them.

  1. Identification of immunity-related genes in the burying beetle Nicrophorus vespilloides by suppression subtractive hybridization.

    Science.gov (United States)

    Vogel, H; Badapanda, C; Vilcinskas, A

    2011-12-01

    Burying beetles reproduce on small vertebrate cadavers which they bury in the soil after localization through volatiles emitted from the carcass. They then chemically preserve the carcass and prepare it as a diet for the adults and their offspring. It is predicted that exposure to high loads of soil and/or carrion-associated microbes necessitates an effective immune system. In the present paper, we report experimental screening for immunity-related genes in the burying beetle Nicrophorus vespilloides using the suppression subtractive hybridization approach. A total of 1179 putative gene objects were identified in the Nicrophorus cDNA library, which was enriched for transcripts differentially expressed upon challenge with heat-inactivated bacteria. In addition to genes known to be involved in immunity-related recognition and signalling, we found transcripts encoding for antimicrobial peptides and for an array of enzymes that can be linked to immunity or to stress-induced pathways. We also determined proteins that may contribute to detoxification of toxins produced by microbial competitors. In addition, factors involved in mRNA stability determination and central components of the RNA interference machinery were identified, implying transcriptional reprogramming and potential stress-induced retrotransposon elimination. The identified candidate immune effector and stress-related genes may provide important information about the unusual ecology and evolution of the burying beetles.

  2. Identification of calcium stress induced genes in amaranth leaves through suppression subtractive hybridization.

    Science.gov (United States)

    Aguilar-Hernández, Hugo S; Santos, Leticia; León-Galván, Fabiola; Barrera-Pacheco, Alberto; Espitia-Rangel, Eduardo; De León-Rodríguez, Antonio; Guevara-González, Ramón G; Barba de la Rosa, Ana P

    2011-11-15

    Calcium (Ca(2+)) is a critical ion for the growth and development of plants and plays an important role in signal transduction pathways in response to biotic and abiotic stresses. We investigated the Ca(2+) stress responsive-genes in amaranth leaves by using the suppression subtractive hybridization technique. Screening of the libraries generated 420 up-regulated transcripts and 199 down-regulated transcripts. The differentially expressed transcripts were associated with general stress response, transcription factors, gene regulation, signal transduction, and some other with unknown function. Selected genes were used to study their differential regulation by sqRT-PCR. Among the up-regulated transcripts, a fragment containing the motif of C3HC4-type RING-Zinc family was further characterized. The ORF of amaranth zinc finger protein (AhZnf) has a closer relationship with its ortholog from Ricinus communis while is distantly related to the Arabidopsis thaliana C3HC4-type ortholog. We have identified a novel putative zinc finger protein along with other novel proteins such as the wall associated kinase, phosphoinositide binding protein, and rhomboid protease involved in response to Ca(2+) stress in amaranth leaves.

  3. Identification of cold tolerance genes from leaves of mangrove plant Kandelia obovata by suppression subtractive hybridization.

    Science.gov (United States)

    Fei, Jiao; Wang, You-Shao; Jiang, Zhao-Yu; Cheng, Hao; Zhang, Jian-Dong

    2015-10-01

    Low temperature is a major abiotic stress that seriously limits mangrove productivity and distribution, the molecular mechanisms of cold tolerance involved in mangroves are still poorly understood at present. It was used to identify the potential cold-related genes in Kandelia obovata (K. obovata) by suppression subtractive hybridization. 334 cold-related expressed sequence tags (ESTs) out of 670 clones were isolated and sequenced. Among these ESTs, 143 unique cDNAs were identified and classified into ten groups, such as metabolism, energy, cell rescue and defense, transcription and photosynthesis according to NCBI blast. Based on bioinformatics analysis, these ESTs were mainly related to response to stimulus and metabolic process, and were included to 72 KEGG pathways. Two selected genes (e.g., aquaporin gene and zinc family protein gene) from the library were further analyzed by quantitative real-time PCR analysis. Both the two genes were found to be transcriptionally up-regulated under cold stress, which partly approve the construction of the subtractive cDNA library. The diversity of the putative functions of these genes indicated that cold stress resulted in a complex response in K. obovata. Further investigation on the functions and potential pathways of these genes will facilitate the understanding of the molecular adaptations to cold tolerance in mangrove plants.

  4. Identification of cadmium-induced Agaricus blazei genes through suppression subtractive hybridization.

    Science.gov (United States)

    Wang, Liling; Li, Haibo; Wei, Hailong; Wu, Xueqian; Ke, Leqin

    2014-01-01

    Cadmium (Cd) is one of the most serious environmental pollutants. Filamentous fungi are very promising organisms for controlling and reducing the amount of heavy metals released by human and industrial activities. However, the molecular mechanisms involved in Cd accumulation and tolerance of filamentous fungi are not fully understood. Agaricus blazei Murrill, an edible mushroom with medicinal properties, demonstrates high tolerance for heavy metals, especially Cd. To investigate the molecular mechanisms underlying the response of A. blazei after Cd exposure, we constructed a forward subtractive library that represents cadmium-induced genes in A. blazei under 4 ppm Cd stress for 14 days using suppression subtractive hybridization combined with mirror orientation selection. Differential screening allowed us to identify 39 upregulated genes, 26 of which are involved in metabolism, protein fate, cellular transport, transport facilitation and transport routes, cell rescue, defense and virulence, transcription, and the action of proteins with a binding function, and 13 are encoding hypothetical proteins with unknown functions. Induction of six A. blazei genes after Cd exposure was further confirmed by RT-qPCR. The cDNAs isolated in this study contribute to our understanding of genes involved in the biochemical pathways that participate in the response of filamentous fungi to Cd exposure.

  5. Identification of Differentially Expressed Genes Associated with Apple Fruit Ripening and Softening by Suppression Subtractive Hybridization.

    Science.gov (United States)

    Zhang, Zongying; Jiang, Shenghui; Wang, Nan; Li, Min; Ji, Xiaohao; Sun, Shasha; Liu, Jingxuan; Wang, Deyun; Xu, Haifeng; Qi, Sumin; Wu, Shujing; Fei, Zhangjun; Feng, Shouqian; Chen, Xuesen

    2015-01-01

    Apple is one of the most economically important horticultural fruit crops worldwide. It is critical to gain insights into fruit ripening and softening to improve apple fruit quality and extend shelf life. In this study, forward and reverse suppression subtractive hybridization libraries were generated from 'Taishanzaoxia' apple fruits sampled around the ethylene climacteric to isolate ripening- and softening-related genes. A set of 648 unigenes were derived from sequence alignment and cluster assembly of 918 expressed sequence tags. According to gene ontology functional classification, 390 out of 443 unigenes (88%) were assigned to the biological process category, 356 unigenes (80%) were classified in the molecular function category, and 381 unigenes (86%) were allocated to the cellular component category. A total of 26 unigenes differentially expressed during fruit development period were analyzed by quantitative RT-PCR. These genes were involved in cell wall modification, anthocyanin biosynthesis, aroma production, stress response, metabolism, transcription, or were non-annotated. Some genes associated with cell wall modification, anthocyanin biosynthesis and aroma production were up-regulated and significantly correlated with ethylene production, suggesting that fruit texture, coloration and aroma may be regulated by ethylene in 'Taishanzaoxia'. Some of the identified unigenes associated with fruit ripening and softening have not been characterized in public databases. The results contribute to an improved characterization of changes in gene expression during apple fruit ripening and softening.

  6. Identification of differentially expressed genes in parasitic phase Miamiensis avidus (Ciliophora: Scuticociliatia) using suppression subtractive hybridization.

    Science.gov (United States)

    Lee, Eun Hye; Kim, Ki Hong

    2011-04-06

    Miamiensis avidus, a causative agent of scuticociliatosis in cultured marine fish, can live not only in seawater as a free-living organism but also in fish as a parasite. In this study, a cDNA library of representative mRNAs more specific to parasitic phase M. avidus was generated using suppression subtractive hybridization (SSH), and 520 clones selected from the SSH library were single-run sequenced. The differential gene expression patterns were confirmed by semi-quantitative reverse-transcription PCR. Of the 510 SSH clones, 21 clones of 6 putative genes did not match sequences in the public database. The expectation values (E-values) of 117 clones encoding 9 putative genes were greater than 1 x 10(-5). The other 372 clones that met the criterion of E value <1 x 10-5 were matched to 26 known sequences in the database. Genes associated with signal transduction, cell proliferation, membrane transportation, protein translocation, and transcription regulation were preferentially expressed in parasitic phase M. avidus. The differential gene expression may be needed for the ciliates to survive in the host fish, and the corresponding proteins might be used as antigen candidates for development of scuticociliatosis vaccines.

  7. Hybrid swarm intelligence optimization approach for optimal data storage position identification in wireless sensor networks.

    Science.gov (United States)

    Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

    2015-01-01

    The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches.

  8. Yeast one-hybrid gγ recruitment system for identification of protein lipidation motifs.

    Science.gov (United States)

    Fukuda, Nobuo; Doi, Motomichi; Honda, Shinya

    2013-01-01

    Fatty acids and isoprenoids can be covalently attached to a variety of proteins. These lipid modifications regulate protein structure, localization and function. Here, we describe a yeast one-hybrid approach based on the Gγ recruitment system that is useful for identifying sequence motifs those influence lipid modification to recruit proteins to the plasma membrane. Our approach facilitates the isolation of yeast cells expressing lipid-modified proteins via a simple and easy growth selection assay utilizing G-protein signaling that induces diploid formation. In the current study, we selected the N-terminal sequence of Gα subunits as a model case to investigate dual lipid modification, i.e., myristoylation and palmitoylation, a modification that is widely conserved from yeast to higher eukaryotes. Our results suggest that both lipid modifications are required for restoration of G-protein signaling. Although we could not differentiate between myristoylation and palmitoylation, N-terminal position 7 and 8 play some critical role. Moreover, we tested the preference for specific amino-acid residues at position 7 and 8 using library-based screening. This new approach will be useful to explore protein-lipid associations and to determine the corresponding sequence motifs.

  9. Yeast one-hybrid gγ recruitment system for identification of protein lipidation motifs.

    Directory of Open Access Journals (Sweden)

    Nobuo Fukuda

    Full Text Available Fatty acids and isoprenoids can be covalently attached to a variety of proteins. These lipid modifications regulate protein structure, localization and function. Here, we describe a yeast one-hybrid approach based on the Gγ recruitment system that is useful for identifying sequence motifs those influence lipid modification to recruit proteins to the plasma membrane. Our approach facilitates the isolation of yeast cells expressing lipid-modified proteins via a simple and easy growth selection assay utilizing G-protein signaling that induces diploid formation. In the current study, we selected the N-terminal sequence of Gα subunits as a model case to investigate dual lipid modification, i.e., myristoylation and palmitoylation, a modification that is widely conserved from yeast to higher eukaryotes. Our results suggest that both lipid modifications are required for restoration of G-protein signaling. Although we could not differentiate between myristoylation and palmitoylation, N-terminal position 7 and 8 play some critical role. Moreover, we tested the preference for specific amino-acid residues at position 7 and 8 using library-based screening. This new approach will be useful to explore protein-lipid associations and to determine the corresponding sequence motifs.

  10. Identification of differentially expressed genes in uveal melanoma using suppressive subtractive hybridization

    Science.gov (United States)

    Landreville, Solange; Lupien, Caroline B.; Vigneault, Francois; Gaudreault, Manon; Mathieu, Mélissa; Rousseau, Alain P.; Guérin, Sylvain L.

    2011-01-01

    Purpose Uveal melanoma (UM) is the most common primary cancer of the eye, resulting not only in vision loss, but also in metastatic death. This study attempts to identify changes in the patterns of gene expression that lead to malignant transformation and proliferation of normal uveal melanocytes (UVM) using the Suppressive Subtractive Hybridization (SSH) technique. Methods The SSH technique was used to isolate genes that are differentially expressed in the TP31 cell line derived from a primary UM compared to UVM. The expression level of selected genes was further validated by microarray, semi-quantitative RT–PCR and western blot analyses. Results Analysis of the subtracted libraries revealed that 37 and 36 genes were, respectively, up- and downregulated in TP31 cells compared to UVM. Differential expression of the majority of these genes was confirmed by comparing UM cells with UVM by microarray. The expression pattern of selected genes was analyzed by semi-quantitative RT–PCR and western blot, and was found to be consistent with the SSH findings. Conclusions We demonstrated that the SSH technique is efficient to detect differentially expressed genes in UM. The genes identified in this study represent valuable candidates for further functional analysis in UM and should be informative in studying the biology of this tumor. PMID:21647268

  11. Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ranganathan Mohanasundaram

    2015-01-01

    Full Text Available The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches.

  12. Hybrid brain-computer interfaces and hybrid neuroprostheses for restoration of upper limb functions in individuals with high-level spinal cord injury.

    Science.gov (United States)

    Rohm, Martin; Schneiders, Matthias; Müller, Constantin; Kreilinger, Alex; Kaiser, Vera; Müller-Putz, Gernot R; Rupp, Rüdiger

    2013-10-01

    The bilateral loss of the grasp function associated with a lesion of the cervical spinal cord severely limits the affected individuals' ability to live independently and return to gainful employment after sustaining a spinal cord injury (SCI). Any improvement in lost or limited grasp function is highly desirable. With current neuroprostheses, relevant improvements can be achieved in end users with preserved shoulder and elbow, but missing hand function. The aim of this single case study is to show that (1) with the support of hybrid neuroprostheses combining functional electrical stimulation (FES) with orthoses, restoration of hand, finger and elbow function is possible in users with high-level SCI and (2) shared control principles can be effectively used to allow for a brain-computer interface (BCI) control, even if only moderate BCI performance is achieved after extensive training. The individual in this study is a right-handed 41-year-old man who sustained a traumatic SCI in 2009 and has a complete motor and sensory lesion at the level of C4. He is unable to generate functionally relevant movements of the elbow, hand and fingers on either side. He underwent extensive FES training (30-45min, 2-3 times per week for 6 months) and motor imagery (MI) BCI training (415 runs in 43 sessions over 12 months). To meet individual needs, the system was designed in a modular fashion including an intelligent control approach encompassing two input modalities, namely an MI-BCI and shoulder movements. After one year of training, the end user's MI-BCI performance ranged from 50% to 93% (average: 70.5%). The performance of the hybrid system was evaluated with different functional assessments. The user was able to transfer objects of the grasp-and-release-test and he succeeded in eating a pretzel stick, signing a document and eating an ice cream cone, which he was unable to do without the system. This proof-of-concept study has demonstrated that with the support of hybrid FES

  13. NLSCIDNT user's guide maximum likehood parameter identification computer program with nonlinear rotorcraft model

    Science.gov (United States)

    1979-01-01

    A nonlinear, maximum likelihood, parameter identification computer program (NLSCIDNT) is described which evaluates rotorcraft stability and control coefficients from flight test data. The optimal estimates of the parameters (stability and control coefficients) are determined (identified) by minimizing the negative log likelihood cost function. The minimization technique is the Levenberg-Marquardt method, which behaves like the steepest descent method when it is far from the minimum and behaves like the modified Newton-Raphson method when it is nearer the minimum. Twenty-one states and 40 measurement variables are modeled, and any subset may be selected. States which are not integrated may be fixed at an input value, or time history data may be substituted for the state in the equations of motion. Any aerodynamic coefficient may be expressed as a nonlinear polynomial function of selected 'expansion variables'.

  14. Energy loss and coronary flow simulation following hybrid stage I palliation: a hypoplastic left heart computational fluid dynamic model.

    Science.gov (United States)

    Shuhaiber, Jeffrey H; Niehaus, Justin; Gottliebson, William; Abdallah, Shaaban

    2013-08-01

    The theoretical differences in energy losses as well as coronary flow with different band sizes for branch pulmonary arteries (PA) in hypoplastic left heart syndrome (HLHS) remain unknown. Our objective was to develop a computational fluid dynamic model (CFD) to determine the energy losses and pulmonary-to-systemic flow rates. This study was done for three different PA band sizes. Three-dimensional computer models of the hybrid procedure were constructed using the standard commercial CFD softwares Fluent and Gambit. The computer models were controlled for bilateral PA reduction to 25% (restrictive), 50% (intermediate) and 75% (loose) of the native branch pulmonary artery diameter. Velocity and pressure data were calculated throughout the heart geometry using the finite volume numerical method. Coronary flow was measured simultaneously with each model. Wall shear stress and the ratio of pulmonary-to-systemic volume flow rates were calculated. Computer simulations were compared at fixed points utilizing echocardiographic and catheter-based metric dimensions. Restricting the PA band to a 25% diameter demonstrated the greatest energy loss. The 25% banding model produced an energy loss of 16.76% systolic and 24.91% diastolic vs loose banding at 7.36% systolic and 17.90% diastolic. Also, restrictive PA bands had greater coronary flow compared with loose PA bands (50.2 vs 41.9 ml/min). Shear stress ranged from 3.75 Pascals with restrictive PA banding to 2.84 Pascals with loose banding. Intermediate PA banding at 50% diameter achieved a Qp/Qs (closest to 1) at 1.46 systolic and 0.66 diastolic compared with loose or restrictive banding without excess energy loss. CFD provides a unique platform to simulate pressure, shear stress as well as energy losses of the hybrid procedure. PA banding at 50% provided a balanced pulmonary and systemic circulation with adequate coronary flow but without extra energy losses incurred.

  15. Contribute to quantitative identification of casting defects based on computer analysis of X-ray images

    Directory of Open Access Journals (Sweden)

    Z. Ignaszak

    2007-12-01

    Full Text Available The forecast of structure and properties of casting is based on results of computer simulation of physical processes which are carried out during the casting processes. For the effective using of simulation system it is necessary to validate mathematica-physical models describing process of casting formation and the creation of local discontinues, witch determinate the casting properties.In the paper the proposition for quantitative validation of VP system using solidification casting defects by information sources of II group (methods of NDT was introduced. It was named the VP/RT validation (virtual prototyping/radiographic testing validation. Nowadays identification of casting defects noticeable on X-ray images bases on comparison of X-ray image of casting with relates to the ASTM. The results of this comparison are often not conclusive because based on operator’s subjective assessment. In the paper the system of quantitative identification of iron casting defects on X-ray images and classification this defects to ASTM class is presented. The methods of pattern recognition and machine learning were applied.

  16. A hyperspectral X-ray computed tomography system for enhanced material identification

    Science.gov (United States)

    Wu, Xiaomei; Wang, Qian; Ma, Jinlei; Zhang, Wei; Li, Po; Fang, Zheng

    2017-08-01

    X-ray computed tomography (CT) can distinguish different materials according to their absorption characteristics. The hyperspectral X-ray CT (HXCT) system proposed in the present work reconstructs each voxel according to its X-ray absorption spectral characteristics. In contrast to a dual-energy or multi-energy CT system, HXCT employs cadmium telluride (CdTe) as the x-ray detector, which provides higher spectral resolution and separate spectral lines according to the material's photon-counter working principle. In this paper, a specimen containing ten different polymer materials randomly arranged was adopted for material identification by HXCT. The filtered back-projection algorithm was applied for image and spectral reconstruction. The first step was to sort the individual material components of the specimen according to their cross-sectional image intensity. The second step was to classify materials with similar intensities according to their reconstructed spectral characteristics. The results demonstrated the feasibility of the proposed material identification process and indicated that the proposed HXCT system has good prospects for a wide range of biomedical and industrial nondestructive testing applications.

  17. Hybrid Brain–Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review

    Directory of Open Access Journals (Sweden)

    Keum-Shik Hong

    2017-07-01

    Full Text Available In this article, non-invasive hybrid brain–computer interface (hBCI technologies for improving classification accuracy and increasing the number of commands are reviewed. Hybridization combining more than two modalities is a new trend in brain imaging and prosthesis control. Electroencephalography (EEG, due to its easy use and fast temporal resolution, is most widely utilized in combination with other brain/non-brain signal acquisition modalities, for instance, functional near infrared spectroscopy (fNIRS, electromyography (EMG, electrooculography (EOG, and eye tracker. Three main purposes of hybridization are to increase the number of control commands, improve classification accuracy and reduce the signal detection time. Currently, such combinations of EEG + fNIRS and EEG + EOG are most commonly employed. Four principal components (i.e., hardware, paradigm, classifiers, and features relevant to accuracy improvement are discussed. In the case of brain signals, motor imagination/movement tasks are combined with cognitive tasks to increase active brain–computer interface (BCI accuracy. Active and reactive tasks sometimes are combined: motor imagination with steady-state evoked visual potentials (SSVEP and motor imagination with P300. In the case of reactive tasks, SSVEP is most widely combined with P300 to increase the number of commands. Passive BCIs, however, are rare. After discussing the hardware and strategies involved in the development of hBCI, the second part examines the approaches used to increase the number of control commands and to enhance classification accuracy. The future prospects and the extension of hBCI in real-time applications for daily life scenarios are provided.

  18. An Improved LU-SGS Implicit Scheme for High Reynolds Number Flow Computations on Hybrid Unstructured Mesh

    Institute of Scientific and Technical Information of China (English)

    WANG Gang; JIANG Yuewen; YE Zhengyin

    2012-01-01

    The lower-upper symmetric Gauss-Seidel (LU-SGS) implicit relaxation has been widely used because it has the merits of less dependency on grid topology,low numerical complexity and modest memory requirements.In original LU-SGS scheme,the implicit system matrix is construeted based on the splitting of convective flux Jacobian according to its spectral radius.Although this treatment has the merit of reducing computational complexity and helps to ensure the diagonally dominant property of the implicit system marx,it can also cause serious distortions on the implicit system matrix because too many approximations are introduced by this splitting method if the contravariant velocity is small or close to sonic speed.To overcome this shortcoming,an improved LU-SGS scheme with a hybrid construction method for the implicit system matrix is developed in this paper.The hybrid way is that:on the cell faces having small contravariant velocity or transonic contravariant velocity,the accurate derivative of the convective flux term is used to construct more accurate implicit system matrix,while the original Jacobian splitting method is adopted on the other cell faces to reduce computational complexity and ensure the diagonally dominant property of the implicit system matrix.To investigate the convergence performance of the improved LU-SGS scheme,2D and 3D turbulent flows around the NACA0012 airfoil,RAE2822 airfoil and LANN wing are simulated on hybrid unstructured meshes.The numerical results show that the improved LU-SGS scheme is significantly more efficient than the original LU-SGS scheme.

  19. Resource-Efficient, Hierarchical Auto-Tuning of a Hybrid Lattice Boltzmann Computation on the Cray XT4

    Energy Technology Data Exchange (ETDEWEB)

    Computational Research Division, Lawrence Berkeley National Laboratory; NERSC, Lawrence Berkeley National Laboratory; Computer Science Department, University of California, Berkeley; Williams, Samuel; Carter, Jonathan; Oliker, Leonid; Shalf, John; Yelick, Katherine

    2009-05-04

    We apply auto-tuning to a hybrid MPI-pthreads lattice Boltzmann computation running on the Cray XT4 at National Energy Research Scientific Computing Center (NERSC). Previous work showed that multicore-specific auto-tuning can improve the performance of lattice Boltzmann magnetohydrodynamics (LBMHD) by a factor of 4x when running on dual- and quad-core Opteron dual-socket SMPs. We extend these studies to the distributed memory arena via a hybrid MPI/pthreads implementation. In addition to conventional auto-tuning at the local SMP node, we tune at the message-passing level to determine the optimal aspect ratio as well as the correct balance between MPI tasks and threads per MPI task. Our study presents a detailed performance analysis when moving along an isocurve of constant hardware usage: fixed total memory, total cores, and total nodes. Overall, our work points to approaches for improving intra- and inter-node efficiency on large-scale multicore systems for demanding scientific applications.

  20. A New Single-blade Based Hybrid CFD Method for Hovering and Forward-flight Rotor Computation

    Institute of Scientific and Technical Information of China (English)

    SHI Yongjie; ZHAO Qijun; FAN Feng; XU Guohua

    2011-01-01

    A hybrid Euler/full potential/Lagrangian wake method, based on single-blade simulation, for predicting unsteady aerodynamic flow around helicopter rotors in hover and forward flight has been developed. In this method, an Euler solver is used to model the near wake evolution and transonic flow phenomena in the vicinity of the blade, and a full potential equation (FPE) is used to model the isentropic potential flow region far away from the rotor, while the wake effects of other blades and the far wake are incorporated into the flow solution as an induced inflow distribution using a Lagrangian based wake analysis. To further reduce the execution time, the computational fluid dynamics (CFD) solution and rotor wake analysis (including induced velocity update) are conducted parallelly, and a load balancing strategy is employed to account for the information exchange between two solvers. By the developed method, several hover and forward-flight cases on Caradonna-Tung and Helishape 7A rotors are performed. Good agreements of the loadings on blade surface with available measured data demonstrate the validation of the method. Also, the CPU time required for different computation runs is compared in the paper, and the results show that the present hybrid method is superior to conventional CFD method in time cost, and will be more efficient with the number of blades increasing.

  1. A novel methodology for non-linear system identification of battery cells used in non-road hybrid electric vehicles

    Science.gov (United States)

    Unger, Johannes; Hametner, Christoph; Jakubek, Stefan; Quasthoff, Marcus

    2014-12-01

    An accurate state of charge (SoC) estimation of a traction battery in hybrid electric non-road vehicles, which possess higher dynamics and power densities than on-road vehicles, requires a precise battery cell terminal voltage model. This paper presents a novel methodology for non-linear system identification of battery cells to obtain precise battery models. The methodology comprises the architecture of local model networks (LMN) and optimal model based design of experiments (DoE). Three main novelties are proposed: 1) Optimal model based DoE, which aims to high dynamically excite the battery cells at load ranges frequently used in operation. 2) The integration of corresponding inputs in the LMN to regard the non-linearities SoC, relaxation, hysteresis as well as temperature effects. 3) Enhancements to the local linear model tree (LOLIMOT) construction algorithm, to achieve a physical appropriate interpretation of the LMN. The framework is applicable for different battery cell chemistries and different temperatures, and is real time capable, which is shown on an industrial PC. The accuracy of the obtained non-linear battery model is demonstrated on cells with different chemistries and temperatures. The results show significant improvement due to optimal experiment design and integration of the battery non-linearities within the LMN structure.

  2. Computational analysis of electrical conduction in hybrid nanomaterials with embedded non-penetrating conductive particles

    Science.gov (United States)

    Cai, Jizhe; Naraghi, Mohammad

    2016-08-01

    In this work, a comprehensive multi-resolution two-dimensional (2D) resistor network model is proposed to analyze the electrical conductivity of hybrid nanomaterials made of insulating matrix with conductive particles such as CNT reinforced nanocomposites and thick film resistors. Unlike existing approaches, our model takes into account the impenetrability of the particles and their random placement within the matrix. Moreover, our model presents a detailed description of intra-particle conductivity via finite element analysis, which to the authors’ best knowledge has not been addressed before. The inter-particle conductivity is assumed to be primarily due to electron tunneling. The model is then used to predict the electrical conductivity of electrospun carbon nanofibers as a function of microstructural parameters such as turbostratic domain alignment and aspect ratio. To simulate the microstructure of single CNF, randomly positioned nucleation sites were seeded and grown as turbostratic particles with anisotropic growth rates. Particle growth was in steps and growth of each particle in each direction was stopped upon contact with other particles. The study points to the significant contribution of both intra-particle and inter-particle conductivity to the overall conductivity of hybrid composites. Influence of particle alignment and anisotropic growth rate ratio on electrical conductivity is also discussed. The results show that partial alignment in contrast to complete alignment can result in maximum electrical conductivity of whole CNF. High degrees of alignment can adversely affect conductivity by lowering the probability of the formation of a conductive path. The results demonstrate approaches to enhance electrical conductivity of hybrid materials through controlling their microstructure which is applicable not only to carbon nanofibers, but also many other types of hybrid composites such as thick film resistors.

  3. Single-Board-Computer-Based Traffic Generator for a Heterogeneous and Hybrid Smart Grid Communication Network

    OpenAIRE

    Do Nguyet Quang; Ong Hang See; Lai Lee Chee; Che Yung Xuen; Shashiteran A/L. Karuppiah

    2014-01-01

    In smart grid communication implementation, network traffic pattern is one of the main factors that affect the system’s performance. Examining different traffic patterns in smart grid is therefore crucial when analyzing the network performance. Due to the heterogeneous and hybrid nature of smart grid, the type of traffic distribution in the network is still unknown. The traffic that popularly used for simulation and analysis no longer reflects the real traffic in a multi-technology and bi-dir...

  4. Identification of a centromeric exchange of acrocentric chromosomes by fluorescence in situ hybridization

    Energy Technology Data Exchange (ETDEWEB)

    Yu, C.W.; Immken, L.; Curry, C.J.R. [UCSF, Fresno, CA (United States)] [and others

    1994-09-01

    Exchanges of the peri-centromeric area of acrocentric chromosomes are difficult to identify using the conventional cytogenetic techniques. Fluorescence in situ hybridization (FISH) provides a new way for precisely identifying such rearrangements. Here we report a case of centromeric rearrangement in an amniotic fluid specimen with an extra marker chromosome. M.G., a 41-year-old G1, was referred for advanced maternal age. Chromosome studies revealed a 47,XX +mar karyotype. The marker appeared to be bi-satallited with a single C band. Chromosome studies from the parents were normal. The parents elected to terminate the pregnancy. Anatomical examination of the abortus revealed a very short neck, posteriorly rotated ears, high set cecum, absent hepatic lobation and low abdominal kidneys with short ureters. FISH studies with alpha-satellite probes of 13/21, 14/22, and 15, and the DiGeorge probe, indicated that there is a translocation of 21 alpha-satellite to the 22, and that the marker chromosome probably consists of 14/22 alpha-satellite material. FISH analysis of the parents chromosome revealed that father had the translocation of 21 alpha-satellite to the 22 as well. Exchanges of centromeric material among the acrocentric chromosomes may not be an uncommon event in humans. Although it probably has no clinical significance, it may result in non-disjunction or marker chromosome formation from an uncommon satellite association. With the use of FISH techniques, exchanges involving the centromeric regions of acrocentric chromosomes can be identified.

  5. Identification of Genes Associated with Morphology in Aspergillus Niger by Using Suppression Subtractive Hybridization

    Energy Technology Data Exchange (ETDEWEB)

    Dai, Ziyu; Mao, Xingxue; Magnuson, Jon K.; Lasure, Linda L.

    2004-04-01

    The morphology of citric acid production strains of Aspergillus niger is sensitive to a variety of factors including the concentration of manganese (Mn2+). Upon increasing the Mn2+ concentration in A. niger (ATCC 11414) cultures to 14 ppb or higher, the morphology switches from pelleted to filamentous, accompanied by a rapid decline in citric acid production. Molecular mechanisms through which Mn2+ exerts effects on morphology and citric acid production in A. niger have not been well defined, but our use of suppression subtractive hybridization has identified 22 genes responsive to Mn2+. Fifteen genes were differentially expressed when A. niger was grown in media containing 1000 ppb Mn2+ (filamentous form) and seven genes in 10 ppb Mn2+ (pelleted form). Of the fifteen filamentous-associated genes, seven are novel and eight share 47-100% identity to genes from other organisms. Five of the pellet-associated genes are novel, and the other two genes encode a pepsin-type protease and polyubiquitin. All ten genes with deduced functions are either involved in amino acid metabolism/protein catabolism or cell regulatory processes. Northern-blot analysis showed that the transcripts of all 22 genes were rapidly enhanced or suppressed by Mn2+. Steady-state mRNA levels of six selected filamentous associated genes remained high during five days of culture in a filamentous state and low under pelleted growth conditions. The opposite behavior was observed for four selected pellet-associated genes. The full-length cDNA of the filamentous-associated clone, Brsa-25 was isolated. Antisense expression of Brsa-25 permitted pelleted growth and increased citrate production at higher concentrations of Mn2+ than could be tolerated by the parent strain. The results suggest the involvement of the newly isolated genes in regulation of A. niger morphology.

  6. Identification and characterization of low temperature stress responsive genes in Poncirus trifoliata by suppression subtractive hybridization.

    Science.gov (United States)

    Peng, T; Zhu, X F; Fan, Q J; Sun, P P; Liu, J H

    2012-01-15

    Trifoliate orange (Poncirus trifoliata (L.) Raf.) is extremely cold hardy when fully acclimated, but knowledge relevant to the molecular events underlying the acclimation is still limited so far. In this study, forward (4 °C over 25 °C) and reverse (25 °C over 4 °C) suppression subtractive hybridization (SSH) libraries were constructed in order to identify the genes involved in cold acclimation in trifoliate orange. After reverse northern blotting analysis and sequencing, a total of 105 and 117 non-redundant differentially expressed sequence tags (ESTs) were obtained from the forward and reverse libraries, respectively. Blast2go analysis revealed that 91 ESTs, 31 from the forward library and 60 from the reverse library, displayed significant sequence homology to the genes with known or putative functions. They were categorized into various functional groups, including catalytic activity, binding protein, structural molecule, enzyme regulator, molecular transducer, electron carrier, and transport activity/transcription regulation. Expression analysis of the selected ESTs by reverse transcriptase polymerase chain reaction was consistent with the results of differential screening. In addition, time-course expression patterns of the genes further confirmed that they were responsive to low temperature treatment. Among the genes of known functions, many are related to maintenance of cell wall integrity, adjustment of osmotic potential and maintenance of reactive oxygen species homeostasis, implying that these physiological processes might be of paramount significance in rendering protective mechanisms against the low temperature stress. The data presented here gain an insight into the molecular changes underlying the cold acclimation of trifoliate orange, and the results can be of reference for unraveling candidate genes that hold great potential for genetic engineering in an effort to create novel germplasms with enhanced cold stress tolerance.

  7. Identification of two novel nodule-specific genes from Astragalus sinicus L. by suppressive subtractive hybridization

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    To identify the genes involved in nodule formation and to increase usable molecular probes, a cDNA library of Astragalus sinicus genes specifically expressed in infected roots by Mesorhizobium huakuii 7653R is generated using a PCR-based suppressive subtractive hybridization (SSH) technique with two mRNA populations of infected and uninfected control roots. Two nodule-specific genes, AsIIC259 and AsG2511, are identified from infected roots of A. sinicus. The amino acid sequences deduced from the open reading frames (ORFs) reveal that AsIIC259 and AsG2511 encodes a polypeptide with 134 and 58 amino acids, respectively. A signal peptide sequence is predicted with high probability at the N-termini of the AsIIC259 and AsG2511. The motif searches show that the deduced polypeptide of AsIIC259 contains two N-glycosylation sites, a cAMP- and cGMP-dependent protein kinase phosphorylation site and a casein kinase II phosphorylation site. BLASTP searches reveal that AsIIC259 putative protein displays a low degree of similarity to a unique nodulin from Lupinus luteus nodules. No significant identity is displayed over the predicted polypeptides of AsG2511 with any published sequences. Virtual Northern blot and semi-quantitative reverse transcription-polymerase chain reaction (RT-PCR) analyses indicate that the two genes are expressed exclusively in inoculated roots and that their expression is 2-4 d later than that of the leghaemoglobin (Lb) gene during nodule development.

  8. High-resolution comparative genomic hybridization of inflammatory breast cancer and identification of candidate genes.

    Directory of Open Access Journals (Sweden)

    Ismahane Bekhouche

    Full Text Available BACKGROUND: Inflammatory breast cancer (IBC is an aggressive form of BC poorly defined at the molecular level. We compared the molecular portraits of 63 IBC and 134 non-IBC (nIBC clinical samples. METHODOLOGY/FINDINGS: Genomic imbalances of 49 IBCs and 124 nIBCs were determined using high-resolution array-comparative genomic hybridization, and mRNA expression profiles of 197 samples using whole-genome microarrays. Genomic profiles of IBCs were as heterogeneous as those of nIBCs, and globally relatively close. However, IBCs showed more frequent "complex" patterns and a higher percentage of genes with CNAs per sample. The number of altered regions was similar in both types, although some regions were altered more frequently and/or with higher amplitude in IBCs. Many genes were similarly altered in both types; however, more genes displayed recurrent amplifications in IBCs. The percentage of genes whose mRNA expression correlated with CNAs was similar in both types for the gained genes, but ∼7-fold lower in IBCs for the lost genes. Integrated analysis identified 24 potential candidate IBC-specific genes. Their combined expression accurately distinguished IBCs and nIBCS in an independent validation set, and retained an independent prognostic value in a series of 1,781 nIBCs, reinforcing the hypothesis for a link with IBC aggressiveness. Consistent with the hyperproliferative and invasive phenotype of IBC these genes are notably involved in protein translation, cell cycle, RNA processing and transcription, metabolism, and cell migration. CONCLUSIONS: Our results suggest a higher genomic instability of IBC. We established the first repertory of DNA copy number alterations in this tumor, and provided a list of genes that may contribute to its aggressiveness and represent novel therapeutic targets.

  9. Genome-wide identification of the regulatory targets of a transcription factor using biochemical characterization and computational genomic analysis

    Directory of Open Access Journals (Sweden)

    Jolly Emmitt R

    2005-11-01

    Full Text Available Abstract Background A major challenge in computational genomics is the development of methodologies that allow accurate genome-wide prediction of the regulatory targets of a transcription factor. We present a method for target identification that combines experimental characterization of binding requirements with computational genomic analysis. Results Our method identified potential target genes of the transcription factor Ndt80, a key transcriptional regulator involved in yeast sporulation, using the combined information of binding affinity, positional distribution, and conservation of the binding sites across multiple species. We have also developed a mathematical approach to compute the false positive rate and the total number of targets in the genome based on the multiple selection criteria. Conclusion We have shown that combining biochemical characterization and computational genomic analysis leads to accurate identification of the genome-wide targets of a transcription factor. The method can be extended to other transcription factors and can complement other genomic approaches to transcriptional regulation.

  10. Hybrid Swarm Algorithms for Parameter Identification of an Actuator Model in an Electrical Machine

    Directory of Open Access Journals (Sweden)

    Ying Wu

    2011-01-01

    Full Text Available Efficient identification and control algorithms are needed, when active vibration suppression techniques are developed for industrial machines. In the paper a new actuator for reducing rotor vibrations in electrical machines is investigated. Model-based control is needed in designing the algorithm for voltage input, and therefore proper models for the actuator must be available. In addition to the traditional prediction error method a new knowledge-based Artificial Fish-Swarm optimization algorithm (AFA with crossover, CAFAC, is proposed to identify the parameters in the new model. Then, in order to obtain a fast convergence of the algorithm in the case of a 30 kW two-pole squirrel cage induction motor, we combine the CAFAC and Particle Swarm Optimization (PSO to identify parameters of the machine to construct a linear time-invariant(LTI state-space model. Besides that, the prediction error method (PEM is also employed to identify the induction motor to produce a black box model with correspondence to input-output measurements.

  11. Identification of floral genes for sex determination in Calamus palustris Griff. by using suppression subtractive hybridization.

    Science.gov (United States)

    Ng, C Y; Wickneswari, R; Choong, C Y

    2014-08-07

    Calamus palustris Griff. is an economically important dioecious rattan species in Southeast Asia. However, dioecy and onset of flowering at 3-4 years old render uncertainties in desired female:male seedling ratios to establish a productive seed orchard for this rattan species. We constructed a subtractive library for male floral tissue to understand the genetic mechanism for gender determination in C. palustris. The subtractive library produced 1536 clones with 1419 clones of high quality. Reverse Northern screening showed 313 clones with differential expression, and sequence analyses clustered them into 205 unigenes, including 32 contigs and 173 singletons. The subtractive library was further validated with reverse transcription-quantitative polymerase chain reaction analysis. Homology identification classified the unigenes into 12 putative functional proteins with 83% unigenes showing significant match to proteins in databases. Functional annotations of these unigenes revealed genes involved in male flower development, including MADS-box genes, pollen-related genes, phytohormones for flower development, and male flower organ development. Our results showed that the male floral genes may play a vital role in sex determination in C. palustris. The identified genes can be exploited to understand the molecular basis of sex determination in C. palustris.

  12. Grouping Based Job Scheduling Algorithm Using Priority Queue and Hybrid Algorithm in Grid Computing

    Directory of Open Access Journals (Sweden)

    Pinky Rosemarry

    2013-01-01

    Full Text Available Grid computing enlarge with computing platform which is collection of heterogeneous computing resources connected by a network across dynamic and geographically dispersed organization to form a distributed high performance computing infrastructure. Grid computing solves the complex computing problems amongst multiple machines. Grid computing solves the large scale computational demands in a high performance computing environment. The main emphasis in the grid computing is given to the resource management and the job scheduler .The goal of the job scheduler is to maximize the resource utilization and minimize the processing time of the jobs. Existing approaches of Grid scheduling doesn’t give much emphasis on the performance of a Grid scheduler in processing time parameter. Schedulers allocate resources to the jobs to be executed using the First come First serve algorithm. In this paper, we have provided an optimize algorithm to queue of the scheduler using various scheduling methods like Shortest Job First, First in First out, Round robin. The job scheduling system is responsible to select best suitable machines in a grid for user jobs. The management and scheduling system generates job schedules for each machine in the grid by taking static restrictions and dynamic parameters of jobs and machinesinto consideration. The main purpose of this paper is to develop an efficient job scheduling algorithm to maximize the resource utilization and minimize processing time of the jobs. Queues can be optimized byusing various scheduling algorithms depending upon the performance criteria to be improved e.g. response time, throughput. The work has been done in MATLAB using the parallel computing toolbox.

  13. Geocomputation over Hybrid Computer Architecture and Systems: Prior Works and On-going Initiatives at UARK

    Science.gov (United States)

    Shi, X.

    2015-12-01

    As NSF indicated - "Theory and experimentation have for centuries been regarded as two fundamental pillars of science. It is now widely recognized that computational and data-enabled science forms a critical third pillar." Geocomputation is the third pillar of GIScience and geosciences. With the exponential growth of geodata, the challenge of scalable and high performance computing for big data analytics become urgent because many research activities are constrained by the inability of software or tool that even could not complete the computation process. Heterogeneous geodata integration and analytics obviously magnify the complexity and operational time frame. Many large-scale geospatial problems may be not processable at all if the computer system does not have sufficient memory or computational power. Emerging computer architectures, such as Intel's Many Integrated Core (MIC) Architecture and Graphics Processing Unit (GPU), and advanced computing technologies provide promising solutions to employ massive parallelism and hardware resources to achieve scalability and high performance for data intensive computing over large spatiotemporal and social media data. Exploring novel algorithms and deploying the solutions in massively parallel computing environment to achieve the capability for scalable data processing and analytics over large-scale, complex, and heterogeneous geodata with consistent quality and high-performance has been the central theme of our research team in the Department of Geosciences at the University of Arkansas (UARK). New multi-core architectures combined with application accelerators hold the promise to achieve scalability and high performance by exploiting task and data levels of parallelism that are not supported by the conventional computing systems. Such a parallel or distributed computing environment is particularly suitable for large-scale geocomputation over big data as proved by our prior works, while the potential of such advanced

  14. Identification of rounded atelectasis in workers exposed to asbestos by contrast helical computed tomography

    Energy Technology Data Exchange (ETDEWEB)

    Terra-Filho, M. [Sao Paulo Univ., SP (Brazil). Instituto do Coracao (InCor). Disciplina de Pneumologia]. E-mail: pnemario@incor.usp.br; Kavakama, J. [Sao Paulo Univ., SP (Brazil). Faculdade de Medicina. Disciplina de Radiologia; Bagatin, E. [Universidade Estadual de Campinas, SP (Brazil). Faculdade de Medicina. Area de Medicina Ocupacional; Capelozzi, V.L. [Sao Paulo Univ., SP (Brazil). Faculdade de Medicina. Disciplina de Patologia; Nery, L.E. [Universidade Federal de Sao Paulo (UNIFESP), SP (Brazil). Escola Paulista de Medicina (EPM). Disciplina de Pneumologia; Tavares, R. [Universidade Federal de Sao Paulo (UNIFESP), SP (Brazil). Escola Paulista de Medicina (EPM). Disciplina de Radiologia

    2003-10-01

    Rounded atelectasis (RA) is a benign and unusual form of sub pleural lung collapse that has been described mostly in asbestos-exposed workers. This form of atelectasis manifests as a lung nodule and can be confused with bronchogenic carcinoma upon conventional radiologic examination. The objective of the present study was to evaluate the variation in contrast uptake in computed tomography for the identification of asbestos-related RA in Brazil. Between January 1998 and December 2000, high-resolution computed tomography (HRCT) was performed in 1658 asbestos-exposed workers. The diagnosis was made in nine patients based on a history of prior asbestos exposure, the presence of characteristic (HRCT) findings and lesions unchanged in size over 2 years or more. In three of them the diagnosis was confirmed during surgery. The dynamic contrast enhancement study was modified to evaluate nodules and pulmonary masses. All nine patients with R A received iodide contrast according to weight. The average enhancement after iodide contrast was infused, reported as Hounsfield units (HU), increased from 62.5{+-}9.7 to 125.4{+-}20.7 (P < 0.05), with a mean enhancement of 62.5{+-}19.7 (range 40 to 89) and with a uniform dense opacification. In conclusion, in this study all patients with R A showed contrast enhancement with uniform dense opacification. The main clinical implication of this finding is that this procedure does not permit differentiation between RA and malignant pulmonary neoplasm. (author)

  15. CaPSID: A bioinformatics platform for computational pathogen sequence identification in human genomes and transcriptomes

    Directory of Open Access Journals (Sweden)

    Borozan Ivan

    2012-08-01

    Full Text Available Abstract Background It is now well established that nearly 20% of human cancers are caused by infectious agents, and the list of human oncogenic pathogens will grow in the future for a variety of cancer types. Whole tumor transcriptome and genome sequencing by next-generation sequencing technologies presents an unparalleled opportunity for pathogen detection and discovery in human tissues but requires development of new genome-wide bioinformatics tools. Results Here we present CaPSID (Computational Pathogen Sequence IDentification, a comprehensive bioinformatics platform for identifying, querying and visualizing both exogenous and endogenous pathogen nucleotide sequences in tumor genomes and transcriptomes. CaPSID includes a scalable, high performance database for data storage and a web application that integrates the genome browser JBrowse. CaPSID also provides useful metrics for sequence analysis of pre-aligned BAM files, such as gene and genome coverage, and is optimized to run efficiently on multiprocessor computers with low memory usage. Conclusions To demonstrate the usefulness and efficiency of CaPSID, we carried out a comprehensive analysis of both a simulated dataset and transcriptome samples from ovarian cancer. CaPSID correctly identified all of the human and pathogen sequences in the simulated dataset, while in the ovarian dataset CaPSID’s predictions were successfully validated in vitro.

  16. Crop species identification using machine vision of computer extracted individual leaves

    Science.gov (United States)

    Camargo Neto, João; Meyer, George E.

    2005-11-01

    An unsupervised method for plant species identification was developed which uses computer extracted individual whole leaves from color images of crop canopies. Green canopies were isolated from soil/residue backgrounds using a modified Excess Green and Excess Red separation method. Connected components of isolated green regions of interest were changed into pixel fragments using the Gustafson-Kessel fuzzy clustering method. The fragments were reassembled as individual leaves using a genetic optimization algorithm and a fitness method. Pixels of whole leaves were then analyzed using the elliptic Fourier shape and Haralick's classical textural feature analyses. A binary template was constructed to represent each selected leaf region of interest. Elliptic Fourier descriptors were generated from a chain encoding of the leaf boundary. Leaf template orientation was corrected by rotating each extracted leaf to a standard horizontal position. This was done using information provided from the first harmonic set of coefficients. Textural features were computed from the grayscale co-occurrence matrix of the leaf pixel set. Standardized leaf orientation significantly improved the leaf textural venation results. Principle component analysis from SAS (R) was used to select the best Fourier descriptors and textural indices. Indices of local homogeneity, and entropy were found to contribute to improved classification rates. A SAS classification model was developed and correctly classified 83% of redroot pigweed, 100% of sunflower 83% of soybean, and 73% of velvetleaf species. An overall plant species correct classification rate of 86% was attained.

  17. A computational model for the identification of biochemical pathways in the krebs cycle.

    Science.gov (United States)

    Oliveira, Joseph S; Bailey, Colin G; Jones-Oliveira, Janet B; Dixon, David A; Gull, Dean W; Chandler, Mary L

    2003-01-01

    We have applied an algorithmic methodology which provably decomposes any complex network into a complete family of principal subcircuits to study the minimal circuits that describe the Krebs cycle. Every operational behavior that the network is capable of exhibiting can be represented by some combination of these principal subcircuits and this computational decomposition is linearly efficient. We have developed a computational model that can be applied to biochemical reaction systems which accurately renders pathways of such reactions via directed hypergraphs (Petri nets). We have applied the model to the citric acid cycle (Krebs cycle). The Krebs cycle, which oxidizes the acetyl group of acetyl CoA to CO(2) and reduces NAD and FAD to NADH and FADH(2), is a complex interacting set of nine subreaction networks. The Krebs cycle was selected because of its familiarity to the biological community and because it exhibits enough complexity to be interesting in order to introduce this novel analytic approach. This study validates the algorithmic methodology for the identification of significant biochemical signaling subcircuits, based solely upon the mathematical model and not upon prior biological knowledge. The utility of the algebraic-combinatorial model for identifying the complete set of biochemical subcircuits as a data set is demonstrated for this important metabolic process.

  18. Identification of rounded atelectasis in workers exposed to asbestos by contrast helical computed tomography

    Directory of Open Access Journals (Sweden)

    Terra-Filho M.

    2003-01-01

    Full Text Available Rounded atelectasis (RA is a benign and unusual form of subpleural lung collapse that has been described mostly in asbestos-exposed workers. This form of atelectasis manifests as a lung nodule and can be confused with bronchogenic carcinoma upon conventional radiologic examination. The objective of the present study was to evaluate the variation in contrast uptake in computed tomography for the identification of asbestos-related RA in Brazil. Between January 1998 and December 2000, high-resolution computed tomography (HRCT was performed in 1658 asbestos-exposed workers. The diagnosis was made in nine patients based on a history of prior asbestos exposure, the presence of characteristic (HRCT findings and lesions unchanged in size over 2 years or more. In three of them the diagnosis was confirmed during surgery. The dynamic contrast enhancement study was modified to evaluate nodules and pulmonary masses. All nine patients with RA received iodide contrast according to weight. The average enhancement after iodide contrast was infused, reported as Hounsfield units (HU, increased from 62.5 ± 9.7 to 125.4 ± 20.7 (P < 0.05, with a mean enhancement of 62.5 ± 19.7 (range 40 to 89 and with a uniform dense opacification. In conclusion, in this study all patients with RA showed contrast enhancement with uniform dense opacification. The main clinical implication of this finding is that this procedure does not permit differentiation between RA and malignant pulmonary neoplasm.

  19. Identification of proteins involved in the functioning of Riftia pachyptila symbiosis by Subtractive Suppression Hybridization

    Directory of Open Access Journals (Sweden)

    Lallier François H

    2007-09-01

    Full Text Available Abstract Background Since its discovery around deep sea hydrothermal vents of the Galapagos Rift about 30 years ago, the chemoautotrophic symbiosis between the vestimentiferan tubeworm Riftia pachyptila and its symbiotic sulfide-oxidizing γ-proteobacteria has been extensively studied. However, studies on the tubeworm host were essentially targeted, biochemical approaches. We decided to use a global molecular approach to identify new proteins involved in metabolite exchanges and assimilation by the host. We used a Subtractive Suppression Hybridization approach (SSH in an unusual way, by comparing pairs of tissues from a single individual. We chose to identify the sequences preferentially expressed in the branchial plume tissue (the only organ in contact with the sea water and in the trophosome (the organ housing the symbiotic bacteria using the body wall as a reference tissue because it is supposedly not involved in metabolite exchanges in this species. Results We produced four cDNA libraries: i body wall-subtracted branchial plume library (BR-BW, ii and its reverse library, branchial plume-subtracted body wall library (BW-BR, iii body wall-subtracted trophosome library (TR-BW, iv and its reverse library, trophosome-subtracted body wall library (BW-TR. For each library, we sequenced about 200 clones resulting in 45 different sequences on average in each library (58 and 59 cDNAs for BR-BW and TR-BW libraries respectively. Overall, half of the contigs matched records found in the databases with good E-values. After quantitative PCR analysis, it resulted that 16S, Major Vault Protein, carbonic anhydrase (RpCAbr, cathepsin and chitinase precursor transcripts were highly represented in the branchial plume tissue compared to the trophosome and the body wall tissues, whereas carbonic anhydrase (RpCAtr, myohemerythrin, a putative T-Cell receptor and one non identified transcript were highly specific of the trophosome tissue. Conclusion Quantitative PCR

  20. Hybrid incompatibilities in the parasitic wasp genus Nasonia : Negative effects of hemizygosity and the identification of transmission ratio distortion loci

    NARCIS (Netherlands)

    Koevoets, T.; Niehuis, O.; van de Zande, L.; Beukeboom, L. W.

    2012-01-01

    The occurrence of hybrid incompatibilities forms an important stage during the evolution of reproductive isolation. In early stages of speciation, males and females often respond differently to hybridization. Haldane's rule states that the heterogametic sex suffers more from hybridization than the h

  1. Hybrid incompatibilities in the parasitic wasp genus Nasonia : Negative effects of hemizygosity and the identification of transmission ratio distortion loci

    NARCIS (Netherlands)

    Koevoets, T.; Niehuis, O.; van de Zande, L.; Beukeboom, L. W.

    2012-01-01

    The occurrence of hybrid incompatibilities forms an important stage during the evolution of reproductive isolation. In early stages of speciation, males and females often respond differently to hybridization. Haldane's rule states that the heterogametic sex suffers more from hybridization than the h

  2. A Hybrid Approach Towards Intrusion Detection Based on Artificial Immune System and Soft Computing

    CERN Document Server

    Sanyal, Sugata

    2012-01-01

    A number of works in the field of intrusion detection have been based on Artificial Immune System and Soft Computing. Artificial Immune System based approaches attempt to leverage the adaptability, error tolerance, self- monitoring and distributed nature of Human Immune Systems. Whereas Soft Computing based approaches are instrumental in developing fuzzy rule based systems for detecting intrusions. They are computationally intensive and apply machine learning (both supervised and unsupervised) techniques to detect intrusions in a given system. A combination of these two approaches could provide significant advantages for intrusion detection. In this paper we attempt to leverage the adaptability of Artificial Immune System and the computation intensive nature of Soft Computing to develop a system that can effectively detect intrusions in a given network.

  3. Hybrid Simulation Environment for Construction Projects: Identification of System Design Criteria

    Directory of Open Access Journals (Sweden)

    Mohamed Moussa

    2014-01-01

    Full Text Available Large construction projects are complex, dynamic, and unpredictable. They are subject to external and uncontrollable events that affect their schedule and financial outcomes. Project managers take decisions along the lifecycle of the projects to align with projects objectives. These decisions are data dependent where data change over time. Simulation-based modeling and experimentation of such dynamic environment are a challenge. Modeling of large projects or multiprojects is difficult and impractical for standalone computers. This paper presents the criteria required in a simulation environment suitable for modeling large and complex systems such as construction projects to support their lifecycle management. Also presented is a platform that encompasses the identified criteria. The objective of the platform is to facilitate and simplify the simulation and modeling process and enable the inclusion of complexity in simulation models.

  4. Rapid identification of Candida spp. frequently involved in invasive mycoses by using flow-through hybridization and Gene Chip (FHGC) technology.

    Science.gov (United States)

    Li, Chen; Ding, Xiurong; Liu, Zhizhong; Zhu, Juanjuan

    2017-01-01

    The incidence of invasive fungal infections in immunocompromised patients has increased in recent decades. Rapid and accurate identification of these pathogenic fungi is crucial for initiating a timely, safe, and effective antifungal therapy. Here we developed a microarray based on flow-through hybridization gene chip technology. The microarray was tested for its specificity using a panel of reference and blinded clinical isolates. The results proved that this microarray was highly discriminative, leading to the unequivocal identification of each species, including Candida famata and the highly related species Candida parapsilosis, Candida orthopsilosis, and Candida metapsilosis. This new system represents a reliable method that is of potential use in clinical laboratories for the simultaneous detection and identification of the most common pathogenic fungi. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. Developing a computationally efficient dynamic multilevel hybrid optimization scheme using multifidelity model interactions.

    Energy Technology Data Exchange (ETDEWEB)

    Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA); Castro, Joseph Pete Jr. (; .); Giunta, Anthony Andrew

    2006-01-01

    Many engineering application problems use optimization algorithms in conjunction with numerical simulators to search for solutions. The formulation of relevant objective functions and constraints dictate possible optimization algorithms. Often, a gradient based approach is not possible since objective functions and constraints can be nonlinear, nonconvex, non-differentiable, or even discontinuous and the simulations involved can be computationally expensive. Moreover, computational efficiency and accuracy are desirable and also influence the choice of solution method. With the advent and increasing availability of massively parallel computers, computational speed has increased tremendously. Unfortunately, the numerical and model complexities of many problems still demand significant computational resources. Moreover, in optimization, these expenses can be a limiting factor since obtaining solutions often requires the completion of numerous computationally intensive simulations. Therefore, we propose a multifidelity optimization algorithm (MFO) designed to improve the computational efficiency of an optimization method for a wide range of applications. In developing the MFO algorithm, we take advantage of the interactions between multi fidelity models to develop a dynamic and computational time saving optimization algorithm. First, a direct search method is applied to the high fidelity model over a reduced design space. In conjunction with this search, a specialized oracle is employed to map the design space of this high fidelity model to that of a computationally cheaper low fidelity model using space mapping techniques. Then, in the low fidelity space, an optimum is obtained using gradient or non-gradient based optimization, and it is mapped back to the high fidelity space. In this paper, we describe the theory and implementation details of our MFO algorithm. We also demonstrate our MFO method on some example problems and on two applications: earth penetrators and

  6. Hybrid incompatibilities in the parasitic wasp genus Nasonia: negative effects of hemizygosity and the identification of transmission ratio distortion loci.

    Science.gov (United States)

    Koevoets, T; Niehuis, O; van de Zande, L; Beukeboom, L W

    2012-03-01

    The occurrence of hybrid incompatibilities forms an important stage during the evolution of reproductive isolation. In early stages of speciation, males and females often respond differently to hybridization. Haldane's rule states that the heterogametic sex suffers more from hybridization than the homogametic sex. Although haplodiploid reproduction (haploid males, diploid females) does not involve sex chromosomes, sex-specific incompatibilities are predicted to be prevalent in haplodiploid species. Here, we evaluate the effect of sex/ploidy level on hybrid incompatibilities and locate genomic regions that cause increased mortality rates in hybrid males of the haplodiploid wasps Nasonia vitripennis and Nasonia longicornis. Our data show that diploid F(1) hybrid females suffer less from hybridization than haploid F(2) hybrid males. The latter not only suffer from an increased mortality rate, but also from behavioural and spermatogenic sterility. Genetic mapping in recombinant F(2) male hybrids revealed that the observed hybrid mortality is most likely due to a disruption of cytonuclear interactions. As these sex-specific hybrid incompatibilities follow predictions based on Haldane's rule, our data accentuate the need to broaden the view of Haldane's rule to include species with haplodiploid sex determination, consistent with Haldane's original definition.

  7. A new finite element and finite difference hybrid method for computing electrostatics of ionic solvated biomolecule

    Science.gov (United States)

    Ying, Jinyong; Xie, Dexuan

    2015-10-01

    The Poisson-Boltzmann equation (PBE) is one widely-used implicit solvent continuum model for calculating electrostatics of ionic solvated biomolecule. In this paper, a new finite element and finite difference hybrid method is presented to solve PBE efficiently based on a special seven-overlapped box partition with one central box containing the solute region and surrounded by six neighboring boxes. In particular, an efficient finite element solver is applied to the central box while a fast preconditioned conjugate gradient method using a multigrid V-cycle preconditioning is constructed for solving a system of finite difference equations defined on a uniform mesh of each neighboring box. Moreover, the PBE domain, the box partition, and an interface fitted tetrahedral mesh of the central box can be generated adaptively for a given PQR file of a biomolecule. This new hybrid PBE solver is programmed in C, Fortran, and Python as a software tool for predicting electrostatics of a biomolecule in a symmetric 1:1 ionic solvent. Numerical results on two test models with analytical solutions and 12 proteins validate this new software tool, and demonstrate its high performance in terms of CPU time and memory usage.

  8. Short term load forecasting of anomalous load using hybrid soft computing methods

    Science.gov (United States)

    Rasyid, S. A.; Abdullah, A. G.; Mulyadi, Y.

    2016-04-01

    Load forecast accuracy will have an impact on the generation cost is more economical. The use of electrical energy by consumers on holiday, show the tendency of the load patterns are not identical, it is different from the pattern of the load on a normal day. It is then defined as a anomalous load. In this paper, the method of hybrid ANN-Particle Swarm proposed to improve the accuracy of anomalous load forecasting that often occur on holidays. The proposed methodology has been used to forecast the half-hourly electricity demand for power systems in the Indonesia National Electricity Market in West Java region. Experiments were conducted by testing various of learning rate and learning data input. Performance of this methodology will be validated with real data from the national of electricity company. The result of observations show that the proposed formula is very effective to short-term load forecasting in the case of anomalous load. Hybrid ANN-Swarm Particle relatively simple and easy as a analysis tool by engineers.

  9. Hybrid-PIC Computer Simulation of the Plasma and Erosion Processes in Hall Thrusters

    Science.gov (United States)

    Hofer, Richard R.; Katz, Ira; Mikellides, Ioannis G.; Gamero-Castano, Manuel

    2010-01-01

    HPHall software simulates and tracks the time-dependent evolution of the plasma and erosion processes in the discharge chamber and near-field plume of Hall thrusters. HPHall is an axisymmetric solver that employs a hybrid fluid/particle-in-cell (Hybrid-PIC) numerical approach. HPHall, originally developed by MIT in 1998, was upgraded to HPHall-2 by the Polytechnic University of Madrid in 2006. The Jet Propulsion Laboratory has continued the development of HPHall-2 through upgrades to the physical models employed in the code, and the addition of entirely new ones. Primary among these are the inclusion of a three-region electron mobility model that more accurately depicts the cross-field electron transport, and the development of an erosion sub-model that allows for the tracking of the erosion of the discharge chamber wall. The code is being developed to provide NASA science missions with a predictive tool of Hall thruster performance and lifetime that can be used to validate Hall thrusters for missions.

  10. Comparison of In-Flight Measured and Computed Aeroelastic Damping: Modal Identification Procedures and Modeling Approaches

    Directory of Open Access Journals (Sweden)

    Roberto da Cunha Follador

    2016-04-01

    Full Text Available The Operational Modal Analysis technique is a methodology very often applied for the identification of dynamic systems when the input signal is unknown. The applied methodology is based on a technique to estimate the Frequency Response Functions and extract the modal parameters using only the structural dynamic response data, without assuming the knowledge of the excitation forces. Such approach is an adequate way for measuring the aircraft aeroelastic response due to random input, like atmospheric turbulence. The in-flight structural response has been measured by accelerometers distributed along the aircraft wings, fuselage and empennages. The Enhanced Frequency Domain Decomposition technique was chosen to identify the airframe dynamic parameters. This technique is based on the hypothesis that the system is randomly excited with a broadband spectrum with almost constant power spectral density. The system identification procedure is based on the Single Value Decomposition of the power spectral densities of system output signals, estimated by the usual Fast Fourier Transform method. This procedure has been applied to different flight conditions to evaluate the modal parameters and the aeroelastic stability trends of the airframe under investigation. The experimental results obtained by this methodology were compared with the predicted results supplied by aeroelastic numerical models in order to check the consistency of the proposed output-only methodology. The objective of this paper is to compare in-flight measured aeroelastic damping against the corresponding parameters computed from numerical aeroelastic models. Different aerodynamic modeling approaches should be investigated such as the use of source panel body models, cruciform and flat plate projection. As a result of this investigation it is expected the choice of the better aeroelastic modeling and Operational Modal Analysis techniques to be included in a standard aeroelastic

  11. Identification of intracellular bacteria in adenoid and tonsil tissue specimens: the efficiency of culture versus fluorescent in situ hybridization (FISH).

    Science.gov (United States)

    Stępińska, M; Olszewska-Sosińska, O; Lau-Dworak, M; Zielnik-Jurkiewicz, B; Trafny, E A

    2014-01-01

    Monocyte/macrophage cells from human nasopharyngeal lymphoid tissue can be a source of bacteria responsible for human chronic and recurrent upper respiratory tract infection. Detection and characterization of pathogens surviving intracellularly could be a key element in bacteriological diagnosis of the infections as well as in the study on interactions between bacteria and their host. The present study was undertaken to assess the possibility of isolation of viable bacteria from the cells expressing monocyte/macrophage marker CD14 in nasopharyngeal lymphoid tissue. Overall, 74 adenotonsillectomy specimens (adenoids and tonsils) from 37 children with adenoid hypertrophy and recurrent infections as well as 15 specimens from nine children with adenoid hypertrophy, which do not suffer from upper respiratory tract infections (the control group), were studied. The suitability of immunomagnetic separation for extraction of CD14(+) cells from lymphoid tissue and for further isolation of the intracellular pathogens has been shown. The coexistence of living pathogens including Haemophilus influenzae, Staphylococcus aureus, and Streptococcus pyogenes with the bacteria representing normal nasopharyngeal microbiota inside CD14(+) cells was demonstrated. Twenty-four strains of these pathogens from 32.4 % of the lysates of CD14(+) cells were isolated. Concurrently, the fluorescent in situ hybridization (FISH) with a universal EUB388, and the species-specific probes demonstrated twice more often the persistence of these bacterial species in the lysates of CD14(+) cells than conventional culture. Although the FISH technique appears to be more sensitive than traditional culture in the intracellular bacteria identification, the doubts on whether the bacteria are alive, and therefore, pathogenic would still exist without the strain cultivation.

  12. Hybrid brain-computer interface for biomedical cyber-physical system application using wireless embedded EEG systems.

    Science.gov (United States)

    Chai, Rifai; Naik, Ganesh R; Ling, Sai Ho; Nguyen, Hung T

    2017-01-07

    One of the key challenges of the biomedical cyber-physical system is to combine cognitive neuroscience with the integration of physical systems to assist people with disabilities. Electroencephalography (EEG) has been explored as a non-invasive method of providing assistive technology by using brain electrical signals. This paper presents a unique prototype of a hybrid brain computer interface (BCI) which senses a combination classification of mental task, steady state visual evoked potential (SSVEP) and eyes closed detection using only two EEG channels. In addition, a microcontroller based head-mounted battery-operated wireless EEG sensor combined with a separate embedded system is used to enhance portability, convenience and cost effectiveness. This experiment has been conducted with five healthy participants and five patients with tetraplegia. Generally, the results show comparable classification accuracies between healthy subjects and tetraplegia patients. For the offline artificial neural network classification for the target group of patients with tetraplegia, the hybrid BCI system combines three mental tasks, three SSVEP frequencies and eyes closed, with average classification accuracy at 74% and average information transfer rate (ITR) of the system of 27 bits/min. For the real-time testing of the intentional signal on patients with tetraplegia, the average success rate of detection is 70% and the speed of detection varies from 2 to 4 s.

  13. Computational modelling of six speed hybrid gear box and its simulation using Simulinkas an interactive tool of MATLAB

    Directory of Open Access Journals (Sweden)

    Devesh Ramphal Upadhyay

    2016-02-01

    Full Text Available The paper introduces an idea which adds itself into contribution of getting best fuel economy of a passenger car when it is running at high speed on a highway. A six speed (forward gear box is addressed in the paper which is controlled manually and automatically as well. The paper introduces an advancement in manual transmission gear box for passenger cars. Hydraulic circuit is designed with mechatronics point of view and resulting in making the shifting of gear automatically. A computational design is made of the Hybrid Gear Box (HGB using CATIA P3 V5 as a designing software. A new gear meshing in 5 speed manual transmission gear box which synchronizes with the output shaft of the transmission automatically after getting command by the automated system designed. Parameters are considered on the basis of practical model and is been simulated by using Simdriveline as the Simulink tool of MATLAB r2010a. The mechanical properties of the components of the hybrid gear box is calculated on the basis of the functional parameters and with help of the fundamental and dependent properties formulation. The final result is the graphical analysis of the model forobtaining at least 15% fuel efficient than any of the vehicle of same configurations.

  14. Iodinated silica/porphyrin hybrid nanoparticles for X-ray computed tomography/fluorescence dual-modal imaging of tumors

    Directory of Open Access Journals (Sweden)

    Koichiro Hayashi

    2014-12-01

    Full Text Available Silica nanoparticles containing covalently linked iodine and a near-infrared (NIR fluorescence dye, namely porphyrin, have been synthesized through a one-pot sol–gel reaction. These particles are called iodinated silica/porphyrin hybrid nanoparticles (ISP HNPs. The ISP HNPs have both high X-ray absorption coefficient and NIR fluorescence. The ISP HNPs modified with folic acid (FA and polyethylene glycol (PEG, denoted as FA-PEG-ISP HNPs, enabled the successful visualization of tumors in mice by both X-ray computed tomography (CT and fluorescence imaging (FI. Thus, the FA-PEG-ISP HNPs are useful as contrast agents or probes for CT/FI dual-modal imaging.

  15. Automated oral cancer identification using histopathological images: a hybrid feature extraction paradigm.

    Science.gov (United States)

    Krishnan, M Muthu Rama; Venkatraghavan, Vikram; Acharya, U Rajendra; Pal, Mousumi; Paul, Ranjan Rashmi; Min, Lim Choo; Ray, Ajoy Kumar; Chatterjee, Jyotirmoy; Chakraborty, Chandan

    2012-02-01

    Oral cancer (OC) is the sixth most common cancer in the world. In India it is the most common malignant neoplasm. Histopathological images have widely been used in the differential diagnosis of normal, oral precancerous (oral sub-mucous fibrosis (OSF)) and cancer lesions. However, this technique is limited by subjective interpretations and less accurate diagnosis. The objective of this work is to improve the classification accuracy based on textural features in the development of a computer assisted screening of OSF. The approach introduced here is to grade the histopathological tissue sections into normal, OSF without Dysplasia (OSFWD) and OSF with Dysplasia (OSFD), which would help the oral onco-pathologists to screen the subjects rapidly. The biopsy sections are stained with H&E. The optical density of the pixels in the light microscopic images is recorded and represented as matrix quantized as integers from 0 to 255 for each fundamental color (Red, Green, Blue), resulting in a M×N×3 matrix of integers. Depending on either normal or OSF condition, the image has various granular structures which are self similar patterns at different scales termed "texture". We have extracted these textural changes using Higher Order Spectra (HOS), Local Binary Pattern (LBP), and Laws Texture Energy (LTE) from the histopathological images (normal, OSFWD and OSFD). These feature vectors were fed to five different classifiers: Decision Tree (DT), Sugeno Fuzzy, Gaussian Mixture Model (GMM), K-Nearest Neighbor (K-NN), Radial Basis Probabilistic Neural Network (RBPNN) to select the best classifier. Our results show that combination of texture and HOS features coupled with Fuzzy classifier resulted in 95.7% accuracy, sensitivity and specificity of 94.5% and 98.8% respectively. Finally, we have proposed a novel integrated index called Oral Malignancy Index (OMI) using the HOS, LBP, LTE features, to diagnose benign or malignant tissues using just one number. We hope that this OMI can

  16. A hybrid solution using computational prediction and measured data to accurately determine process corrections with reduced overlay sampling

    Science.gov (United States)

    Noyes, Ben F.; Mokaberi, Babak; Mandoy, Ram; Pate, Alex; Huijgen, Ralph; McBurney, Mike; Chen, Owen

    2017-03-01

    Reducing overlay error via an accurate APC feedback system is one of the main challenges in high volume production of the current and future nodes in the semiconductor industry. The overlay feedback system directly affects the number of dies meeting overlay specification and the number of layers requiring dedicated exposure tools through the fabrication flow. Increasing the former number and reducing the latter number is beneficial for the overall efficiency and yield of the fabrication process. An overlay feedback system requires accurate determination of the overlay error, or fingerprint, on exposed wafers in order to determine corrections to be automatically and dynamically applied to the exposure of future wafers. Since current and future nodes require correction per exposure (CPE), the resolution of the overlay fingerprint must be high enough to accommodate CPE in the overlay feedback system, or overlay control module (OCM). Determining a high resolution fingerprint from measured data requires extremely dense overlay sampling that takes a significant amount of measurement time. For static corrections this is acceptable, but in an automated dynamic correction system this method creates extreme bottlenecks for the throughput of said system as new lots have to wait until the previous lot is measured. One solution is using a less dense overlay sampling scheme and employing computationally up-sampled data to a dense fingerprint. That method uses a global fingerprint model over the entire wafer; measured localized overlay errors are therefore not always represented in its up-sampled output. This paper will discuss a hybrid system shown in Fig. 1 that combines a computationally up-sampled fingerprint with the measured data to more accurately capture the actual fingerprint, including local overlay errors. Such a hybrid system is shown to result in reduced modelled residuals while determining the fingerprint, and better on-product overlay performance.

  17. The “Chimera”: An Off-The-Shelf CPU/GPGPU/FPGA Hybrid Computing Platform

    Directory of Open Access Journals (Sweden)

    Ra Inta

    2012-01-01

    Full Text Available The nature of modern astronomy means that a number of interesting problems exhibit a substantial computational bound and this situation is gradually worsening. Scientists, increasingly fighting for valuable resources on conventional high-performance computing (HPC facilities—often with a limited customizable user environment—are increasingly looking to hardware acceleration solutions. We describe here a heterogeneous CPU/GPGPU/FPGA desktop computing system (the “Chimera”, built with commercial-off-the-shelf components. We show that this platform may be a viable alternative solution to many common computationally bound problems found in astronomy, however, not without significant challenges. The most significant bottleneck in pipelines involving real data is most likely to be the interconnect (in this case the PCI Express bus residing on the CPU motherboard. Finally, we speculate on the merits of our Chimera system on the entire landscape of parallel computing, through the analysis of representative problems from UC Berkeley’s “Thirteen Dwarves.”

  18. A hybrid method for computing forces on curved dislocations threading to free surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Tang, M; Cai, W; Xu, G; Bulatov, V V

    2005-06-06

    Dislocations threading to free surfaces present a challenge for numerical implementation of traction-free boundary conditions. The difficulty arises when canonical (singular) solutions of dislocation mechanics are used in combination with the Finite Element or Boundary Element (Green's function) methods. A new hybrid method is developed here in which the singular part and the non-singular (regular) part of the image stress are dealt with separately. A special analytical solution for a semi-infinite straight dislocation intersecting the surface of a half-space is used to account for the singular part of the image stress, while the remaining regular part of the image stress field is treated using the standard Finite Element Method. The numerical advantages of such regularization are demonstrated with examples.

  19. Solving difficult problems creatively: A role for energy optimised deterministic/stochastic hybrid computing

    Directory of Open Access Journals (Sweden)

    Tim ePalmer

    2015-10-01

    Full Text Available How is the brain configured for creativity? What is the computational substrate for ‘eureka’ moments of insight? Here we argue that creative thinking arises ultimately from a synergy between low-energy stochastic and energy-intensive deterministic processing, and is a by-product of a nervous system whose signal-processing capability per unit of available energy has become highly energy optimised. We suggest that the stochastic component has its origin in thermal noise affecting the activity of neurons. Without this component, deterministic computational models of the brain are incomplete.

  20. Comparison between cone-beam and multislice computed tomography for identification of simulated bone lesions

    Energy Technology Data Exchange (ETDEWEB)

    Gaia, Bruno Felipe [University of Sao Paulo (USP), SP (Brazil). Dental School. Stomatology Dept.; Sales, Marcelo Augusto Oliveira de [University of Paraiba (UFPB), Joao Pessoa, PB (Brazil). Dental School. Dept. of Radiology; Perrella, Andreia; Fenyo-Pereira, Marlene; Cavalcanti, Marcelo Gusmao Paraiso, E-mail: mgpcaval@usp.b [University of Sao Paulo (USP), SP (Brazil). Dental School. Dept. of Radiology

    2011-07-15

    There are many studies that compare the accuracy of multislice (MSCT) and cone beam (CBCT) computed tomography for evaluations in the maxillofacial region. However, further studies comparing both acquisition techniques for the evaluation of simulated mandibular bone lesions are needed. The aim of this study was to compare the accuracy of MSCT and CBCT in the diagnosis of simulated mandibular bone lesions by means of cross sectional images and axial/MPR slices. Lesions with different dimensions, shape and locularity were produced in 15 dry mandibles. The images were obtained following the cross sectional and axial/MPR (Multiplanar Reconstruction) imaging protocols and were interpreted independently. CBCT and MSCT showed similar results in depicting the percentage of cortical bone involvement, with great sensitivity and specificity (p < 0.005). There were no significant intra- or inter-examiner differences between axial/MPR images and cross sectional images with regard to sensitivity and specificity. CBCT showed results similar to those of MSCT for the identification of the number of simulated bone lesions. Cross sectional slices and axial/MPR images presented high accuracy, proving useful for bone lesion diagnosis. (author)

  1. [Determination of antibiotype by a computer program. Epidemiological significance and antibiogram-identification correlates].

    Science.gov (United States)

    Fosse, T; Macone, F; Laffont, C

    1988-06-01

    By means of a computer program disk diffusion diameter were analysed and an antibiotic susceptibility code (antibiotype) was determined for enterobacteriaceae. This code was a 6 figure-number. Each figure summarised susceptibility (susceptible or resistant) to 3 antibiotics. Thus a 18 serial antibiotics was necessary to calculate the 6 figure-code. At least following antibiotics were chosen for their characteristic behavior: amoxycillin, ticarcillin, amoxycillin + clavulanic acid, cephalothin, ticarcillin + clavulanic acid, cefotaxime, gentamycin, tobramycin, amikacin, nalidixic acid, pefloxacin, ciprofloxacin, fosfomycin and colistin. This code allowed three kind of utilisation: epidemiology by comparing biochemical and susceptibility patterns of same isolated species; laboratory control: a data base with main antibiotic susceptibility patterns for each species allowed a rapid compatibility control of biochemical identification with antibiogram. An inconsistent result lead to a checking of biochemical and susceptibility tests or to record a new code in a file to a further enrichment of the data base. Impression of a message depending of the code for a therapeutic purpose.

  2. Identification of hot-spot residues in protein-protein interactions by computational docking

    Directory of Open Access Journals (Sweden)

    Fernández-Recio Juan

    2008-10-01

    Full Text Available Abstract Background The study of protein-protein interactions is becoming increasingly important for biotechnological and therapeutic reasons. We can define two major areas therein: the structural prediction of protein-protein binding mode, and the identification of the relevant residues for the interaction (so called 'hot-spots'. These hot-spot residues have high interest since they are considered one of the possible ways of disrupting a protein-protein interaction. Unfortunately, large-scale experimental measurement of residue contribution to the binding energy, based on alanine-scanning experiments, is costly and thus data is fairly limited. Recent computational approaches for hot-spot prediction have been reported, but they usually require the structure of the complex. Results We have applied here normalized interface propensity (NIP values derived from rigid-body docking with electrostatics and desolvation scoring for the prediction of interaction hot-spots. This parameter identifies hot-spot residues on interacting proteins with predictive rates that are comparable to other existing methods (up to 80% positive predictive value, and the advantage of not requiring any prior structural knowledge of the complex. Conclusion The NIP values derived from rigid-body docking can reliably identify a number of hot-spot residues whose contribution to the interaction arises from electrostatics and desolvation effects. Our method can propose residues to guide experiments in complexes of biological or therapeutic interest, even in cases with no available 3D structure of the complex.

  3. Safety and reliability of Radio Frequency Identification Devices in Magnetic Resonance Imaging and Computed Tomography

    Directory of Open Access Journals (Sweden)

    Fretz Christian

    2010-02-01

    Full Text Available Abstract Background Radio Frequency Identification (RFID devices are becoming more and more essential for patient safety in hospitals. The purpose of this study was to determine patient safety, data reliability and signal loss wearing on skin RFID devices during magnetic resonance imaging (MRI and computed tomography (CT scanning. Methods Sixty RFID tags of the type I-Code SLI, 13.56 MHz, ISO 18000-3.1 were tested: Thirty type 1, an RFID tag with a 76 × 45 mm aluminum-etched antenna and 30 type 2, a tag with a 31 × 14 mm copper-etched antenna. The signal loss, material movement and heat tests were performed in a 1.5 T and a 3 T MR system. For data integrity, the tags were tested additionally during CT scanning. Standardized function tests were performed with all transponders before and after all imaging studies. Results There was no memory loss or data alteration in the RFID tags after MRI and CT scanning. Concerning heating (a maximum of 3.6°C and device movement (below 1 N/kg no relevant influence was found. Concerning signal loss (artifacts 2 - 4 mm, interpretability of MR images was impaired when superficial structures such as skin, subcutaneous tissues or tendons were assessed. Conclusions Patients wearing RFID wristbands are safe in 1.5 T and 3 T MR scanners using normal operation mode for RF-field. The findings are specific to the RFID tags that underwent testing.

  4. A Hybrid Autonomic Computing-Based Approach to Distributed Constraint Satisfaction Problems

    Directory of Open Access Journals (Sweden)

    Abhishek Bhatia

    2015-03-01

    Full Text Available Distributed constraint satisfaction problems (DisCSPs are among the widely endeavored problems using agent-based simulation. Fernandez et al. formulated sensor and mobile tracking problem as a DisCSP, known as SensorDCSP In this paper, we adopt a customized ERE (environment, reactive rules and entities algorithm for the SensorDCSP, which is otherwise proven as a computationally intractable problem. An amalgamation of the autonomy-oriented computing (AOC-based algorithm (ERE and genetic algorithm (GA provides an early solution of the modeled DisCSP. Incorporation of GA into ERE facilitates auto-tuning of the simulation parameters, thereby leading to an early solution of constraint satisfaction. This study further contributes towards a model, built up in the NetLogo simulation environment, to infer the efficacy of the proposed approach.

  5. PHOTO: A computer simulation program for photovoltaic and hybrid energy systems. Document and user's guide

    Science.gov (United States)

    Manninen, L. M.; Lund, P. D.; Virkkula, A.

    1990-11-01

    The version 3.0 is described of the program package PHOTO for the simulation and sizing of hybrid power systems (photovoltaic and wind power plants) on IBM PC, XT, AT, PS/2 and compatibles. The minimum memory requirement is 260 kB. Graphical output is created with HALO'88 graphics subroutine library. In the simulation model, special attention is given to the battery storage unit. A backup generator can also be included in the system configuration. The dynamic method developed uses accurate system component models accounting for component interactions and losses in e.g. wiring and diodes. The photovoltaic array can operate in a maximum power mode or in a clamped voltage mode together with the other subsystems. Various control strategies can also be considered. Individual subsystem models were verified against real measurements. Illustrative simulation example is also discussed. The presented model can be used to simulate various system configurations accurately and evaluate system performance, such as energy flows and power losses in photovoltaic array, wind generator, backup generator, wiring, diodes, maximum power point tracking device, inverter and battery. Energy cost is also an important consideration.

  6. Prediction of peak ground acceleration of Iran's tectonic regions using a hybrid soft computing technique

    Directory of Open Access Journals (Sweden)

    Mostafa Gandomi

    2016-01-01

    Full Text Available A new model is derived to predict the peak ground acceleration (PGA utilizing a hybrid method coupling artificial neural network (ANN and simulated annealing (SA, called SA-ANN. The proposed model relates PGA to earthquake source to site distance, earthquake magnitude, average shear-wave velocity, faulting mechanisms, and focal depth. A database of strong ground-motion recordings of 36 earthquakes, which happened in Iran's tectonic regions, is used to establish the model. For more validity verification, the SA-ANN model is employed to predict the PGA of a part of the database beyond the training data domain. The proposed SA-ANN model is compared with the simple ANN in addition to 10 well-known models proposed in the literature. The proposed model performance is superior to the single ANN and other existing attenuation models. The SA-ANN model is highly correlated to the actual records (R = 0.835 and ρ = 0.0908 and it is subsequently converted into a tractable design equation.

  7. Computer aided decision making for heart disease detection using hybrid neural network-Genetic algorithm.

    Science.gov (United States)

    Arabasadi, Zeinab; Alizadehsani, Roohallah; Roshanzamir, Mohamad; Moosaei, Hossein; Yarifard, Ali Asghar

    2017-04-01

    Cardiovascular disease is one of the most rampant causes of death around the world and was deemed as a major illness in Middle and Old ages. Coronary artery disease, in particular, is a widespread cardiovascular malady entailing high mortality rates. Angiography is, more often than not, regarded as the best method for the diagnosis of coronary artery disease; on the other hand, it is associated with high costs and major side effects. Much research has, therefore, been conducted using machine learning and data mining so as to seek alternative modalities. Accordingly, we herein propose a highly accurate hybrid method for the diagnosis of coronary artery disease. As a matter of fact, the proposed method is able to increase the performance of neural network by approximately 10% through enhancing its initial weights using genetic algorithm which suggests better weights for neural network. Making use of such methodology, we achieved accuracy, sensitivity and specificity rates of 93.85%, 97% and 92% respectively, on Z-Alizadeh Sani dataset.

  8. Impact of Hybrid Intelligent Computing in Identifying Constructive Weather Parameters for Modeling Effective Rainfall Prediction

    Directory of Open Access Journals (Sweden)

    M. Sudha

    2015-12-01

    Full Text Available Uncertain atmosphere is a prevalent factor affecting the existing prediction approaches. Rough set and fuzzy set theories as proposed by Pawlak and Zadeh have become an effective tool for handling vagueness and fuzziness in the real world scenarios. This research work describes the impact of Hybrid Intelligent System (HIS for strategic decision support in meteorology. In this research a novel exhaustive search based Rough set reduct Selection using Genetic Algorithm (RSGA is introduced to identify the significant input feature subset. The proposed model could identify the most effective weather parameters efficiently than other existing input techniques. In the model evaluation phase two adaptive techniques were constructed and investigated. The proposed Artificial Neural Network based on Back Propagation learning (ANN-BP and Adaptive Neuro Fuzzy Inference System (ANFIS was compared with existing Fuzzy Unordered Rule Induction Algorithm (FURIA, Structural Learning Algorithm on Vague Environment (SLAVE and Particle Swarm OPtimization (PSO. The proposed rainfall prediction models outperformed when trained with the input generated using RSGA. A meticulous comparison of the performance indicates ANN-BP model as a suitable HIS for effective rainfall prediction. The ANN-BP achieved 97.46% accuracy with a nominal misclassification rate of 0.0254 %.

  9. Development of a computer-assisted forensic radiographic identification method using the lateral cervical and lumbar spine.

    Science.gov (United States)

    Derrick, Sharon M; Raxter, Michelle H; Hipp, John A; Goel, Priya; Chan, Elaine F; Love, Jennifer C; Wiersema, Jason M; Akella, N Shastry

    2015-01-01

    Medical examiners and coroners (ME/C) in the United States hold statutory responsibility to identify deceased individuals who fall under their jurisdiction. The computer-assisted decedent identification (CADI) project was designed to modify software used in diagnosis and treatment of spinal injuries into a mathematically validated tool for ME/C identification of fleshed decedents. CADI software analyzes the shapes of targeted vertebral bodies imaged in an array of standard radiographs and quantifies the likelihood that any two of the radiographs contain matching vertebral bodies. Six validation tests measured the repeatability, reliability, and sensitivity of the method, and the effects of age, sex, and number of radiographs in array composition. CADI returned a 92-100% success rate in identifying the true matching pair of vertebrae within arrays of five to 30 radiographs. Further development of CADI is expected to produce a novel identification method for use in ME/C offices that is reliable, timely, and cost-effective.

  10. Efficient Adjoint Computation of Hybrid Systems of Differential Algebraic Equations with Applications in Power Systems

    Energy Technology Data Exchange (ETDEWEB)

    Abhyankar, Shrirang [Argonne National Lab. (ANL), Argonne, IL (United States); Anitescu, Mihai [Argonne National Lab. (ANL), Argonne, IL (United States); Constantinescu, Emil [Argonne National Lab. (ANL), Argonne, IL (United States); Zhang, Hong [Argonne National Lab. (ANL), Argonne, IL (United States)

    2016-03-31

    Sensitivity analysis is an important tool to describe power system dynamic behavior in response to parameter variations. It is a central component in preventive and corrective control applications. The existing approaches for sensitivity calculations, namely, finite-difference and forward sensitivity analysis, require a computational effort that increases linearly with the number of sensitivity parameters. In this work, we investigate, implement, and test a discrete adjoint sensitivity approach whose computational effort is effectively independent of the number of sensitivity parameters. The proposed approach is highly efficient for calculating trajectory sensitivities of larger systems and is consistent, within machine precision, with the function whose sensitivity we are seeking. This is an essential feature for use in optimization applications. Moreover, our approach includes a consistent treatment of systems with switching, such as DC exciters, by deriving and implementing the adjoint jump conditions that arise from state and time-dependent discontinuities. The accuracy and the computational efficiency of the proposed approach are demonstrated in comparison with the forward sensitivity analysis approach.

  11. Computational medicinal chemistry for rational drug design: Identification of novel chemical structures with potential anti-tuberculosis activity.

    Science.gov (United States)

    Koseki, Yuji; Aoki, Shunsuke

    2014-01-01

    Tuberculosis (TB) is caused by the bacterium Mycobacterium tuberculosis and is a common infectious disease with high mortality and morbidity. The increasing prevalence of drug-resistant strains of TB presents a major public health problem. Due to the lack of effective drugs to treat these drug-resistant strains, the discovery or development of novel anti-TB drugs is important. Computer-aided drug design has become an established strategy for the identification of novel active chemicals through a combination of several drug design tools. In this review, we summarise the current chemotherapy for TB, describe attractive target proteins for the development of antibiotics against TB, and detail several computational drug design strategies that may contribute to the further identification of active chemicals for the treatment of not only TB but also other diseases.

  12. Computational investigations of organic materials for hybrid nanodevice and optoelectronic applications

    Science.gov (United States)

    Crenshaw, Jasmine Davenport

    2011-12-01

    formation are calculated for organic molecules using B3LYP, BMK, and B98 hybrid functionals. G3 and CBS-QB3 are used as standards in conjunction, due to their accurate thermochemistry parameters, with experimental values. The BMK functional proves to perform best with the selected organic molecules.

  13. MULTIPRED2: A computational system for large-scale identification of peptides predicted to bind to HLA supertypes and alleles

    DEFF Research Database (Denmark)

    Zhang, Guang Lan; DeLuca, David S.; Keskin, Derin B.;

    2011-01-01

    MULTIPRED2 is a computational system for facile prediction of peptide binding to multiple alleles belonging to human leukocyte antigen (HLA) class I and class II DR molecules. It enables prediction of peptide binding to products of individual HLA alleles, combination of alleles, or HLA supertypes...... groups in North America. MULTIPRED2 is an important tool to complement wet-lab experimental methods for identification of T-cell epitopes. It is available at http://cvc.dfci.harvard.edu/multipred2/....

  14. Identification and Endodontic Management of Middle Mesial Canal in Mandibular Second Molar Using Cone Beam Computed Tomography

    Directory of Open Access Journals (Sweden)

    Bonny Paul

    2015-01-01

    Full Text Available Endodontic treatments are routinely done with the help of radiographs. However, radiographs represent only a two-dimensional image of an object. Failure to identify aberrant anatomy can lead to endodontic failure. This case report presents the use of three-dimensional imaging with cone beam computed tomography (CBCT as an adjunct to digital radiography in identification and management of mandibular second molar with three mesial canals.

  15. Hybrid spin and valley quantum computing with singlet-triplet qubits.

    Science.gov (United States)

    Rohling, Niklas; Russ, Maximilian; Burkard, Guido

    2014-10-24

    The valley degree of freedom in the electronic band structure of silicon, graphene, and other materials is often considered to be an obstacle for quantum computing (QC) based on electron spins in quantum dots. Here we show that control over the valley state opens new possibilities for quantum information processing. Combining qubits encoded in the singlet-triplet subspace of spin and valley states allows for universal QC using a universal two-qubit gate directly provided by the exchange interaction. We show how spin and valley qubits can be separated in order to allow for single-qubit rotations.

  16. Customized Architecture for Complex Routing Analysis: Case Study for the Convey Hybrid-Core Computer

    Science.gov (United States)

    2014-02-18

    circuits  that  can   be  reconfigured  using  a  hardware  description  language  such  as   Verilog .  Current   state...a   Verilog -­‐based  design  environment,  is  used  to  implement  a  custom-­‐ designed  computer  architecture,  or

  17. Identification and quantification of Bifidobacterium species isolated from food with genus-specific 16S rRNA-targeted probes by colony hybridization and PCR.

    Science.gov (United States)

    Kaufmann, P; Pfefferkorn, A; Teuber, M; Meile, L

    1997-01-01

    A Bifidobacterium genus-specific target sequence in the V9 variable region of the 16S rRNA has been elaborated and was used to develop a hybridization probe. The specificity of this probe, named lm3 (5'-CGGGTGCTI*CCCACTTTCATG-3'), was used to identify all known type strains and distinguish them from other bacteria. All of the 30 type strains of Bifidobacterium which are available at the German culture collection Deutsche Sammlung von Mikroorganismen und Zellkulturen, 6 commercially available production strains, and 34 closely related relevant strains (as negative controls) were tested. All tested bifidobacteria showed distinct positive signals by colony hybridization, whereas all negative controls showed no distinct dots except Gardnerella vaginalis DSM4944 and Propionibacterium freudenreichii subsp. shermanii DSM4902, which gave slight signals. Furthermore, we established a method for isolation and identification of bifidobacteria from food by using a PCR assay without prior isolation of DNA but breaking the cells with proteinase K. By this method, all Bifidobacterium strains lead to a DNA product of the expected size. We also established a quick assay to quantitatively measure Bifidobacterium counts in food and feces by dilution plating and colony hybridization. We were able to demonstrate that 2.1 x 10(6) to 2.3 x 10(7) colonies/g of sour milk containing bifidobacteria hybridized with the specific nucleotide probe. With these two methods, genus-specific colony hybridization and genus-specific PCR, it is now possible to readily and accurately detect any bifidobacteria in food and fecal samples and to discriminate between them and members of other genera. PMID:9097423

  18. Computed tomography characterization of neuroendocrine tumors of the thymus can aid identification and treatment

    Energy Technology Data Exchange (ETDEWEB)

    Li, Hui; Wang, De-ling; Liu, Xue-wen; Geng, Zhi-jun; Xie, Chuan-miao [State Key Lab. of Oncology in Southern China, Guangzhou (China); Medical Imaging and Minimally Invasive Interventional Center, Cancer Center, Sun Yat-sen Univ., Guangzhou (China)], e-mail: xchuanm@sysucc.org.cn

    2013-03-15

    Background: Neuroendocrine tumors of the thymus are extremely rare anterior mediastinal tumors. The few studies reporting these tumors have focused on the clinical manifestations and do not provide a summary of characteristic computed tomography (CT) findings. Purpose: To investigate the CT appearances of neuroendocrine tumors of the thymus in order to improve the diagnostic and resection efficacy. Material and Methods: Nine cases of pathologically identified thymic neuroendocrine tumors were retrospectively analyzed by CT. All the patients underwent non-enhanced and contrast-enhanced CT. Multiple CT features were examined, including tumor location, shape, margins, CT attenuation, involvement of surrounding structures, and distant metastasis. Results: A total of nine masses were examined in this study. The maximum tumor diameter ranged from 5 to 14 cm (average, 9 cm). The shapes of six masses were lobulated and three were rounded or oval and the margins of seven masses were unclear while two masses were sharp. All the masses showed hypo density or isodensity compared to muscles in the anterior thoracic wall on non-enhanced CT images. Two masses showed homogeneous attenuation by non-enhanced CT imaging and moderate homogeneous enhancement after contrast administration, while seven masses showed heterogeneous attenuation with patchy low-attenuation foci and showed moderate to strong heterogeneous enhancement. Involvement of adjacent structures was observed in six cases. Five cases were observed to have lymph node metastases and four cases had distant metastases. Conclusion: Neuroendocrine tumors of the thymus are rare tumors of the anterior mediastinum with a number of distinct CT characteristics. Most importantly, the density of the tumors was heterogeneous with necrosis or cystic degeneration and moderately or strongly enhancement after bolus injection of contrast medium, which may allow for more efficient tumor identification. Thus, CT can improve of the diagnosis

  19. Low-bandwidth and non-compute intensive remote identification of microbes from raw sequencing reads.

    Directory of Open Access Journals (Sweden)

    Laurent Gautier

    Full Text Available Cheap DNA sequencing may soon become routine not only for human genomes but also for practically anything requiring the identification of living organisms from their DNA: tracking of infectious agents, control of food products, bioreactors, or environmental samples. We propose a novel general approach to the analysis of sequencing data where a reference genome does not have to be specified. Using a distributed architecture we are able to query a remote server for hints about what the reference might be, transferring a relatively small amount of data. Our system consists of a server with known reference DNA indexed, and a client with raw sequencing reads. The client sends a sample of unidentified reads, and in return receives a list of matching references. Sequences for the references can be retrieved and used for exhaustive computation on the reads, such as alignment. To demonstrate this approach we have implemented a web server, indexing tens of thousands of publicly available genomes and genomic regions from various organisms and returning lists of matching hits from query sequencing reads. We have also implemented two clients: one running in a web browser, and one as a python script. Both are able to handle a large number of sequencing reads and from portable devices (the browser-based running on a tablet, perform its task within seconds, and consume an amount of bandwidth compatible with mobile broadband networks. Such client-server approaches could develop in the future, allowing a fully automated processing of sequencing data and routine instant quality check of sequencing runs from desktop sequencers. A web access is available at http://tapir.cbs.dtu.dk. The source code for a python command-line client, a server, and supplementary data are available at http://bit.ly/1aURxkc.

  20. Computational identification and structural analysis of deleterious functional SNPs in MLL gene causing acute leukemia.

    Science.gov (United States)

    George Priya Doss, C; Rajasekaran, R; Sethumadhavan, Rao

    2010-09-01

    A promising application of the huge amounts of data from the Human Genome Project currently available offers new opportunities for identifying the genetic predisposition and developing a better understanding of complex diseases such as cancers. The main focus of cancer genetics is the study of mutations that are causally implicated in tumorigenesis. The identification of such causal mutations does not only provide insight into cancer biology but also presents anticancer therapeutic targets and diagnostic markers. In this study, we evaluated the Single Nucleotide Polymorphisms (SNPs) that can alter the expression and the function in MLL gene through computational methods. We applied an evolutionary perspective to screen the SNPs using a sequence homologybased SIFT tool, suggested that 10 non-synonymous SNPs (nsSNPs) (50%) were found to be deleterious. Structure based approach PolyPhen server suggested that 5 nsSNPS (25%) may disrupt protein function and structure. PupaSuite tool predicted the phenotypic effect of SNPs on the structure and function of the affected protein. Structure analysis was carried out with the major mutations that occurred in the native protein coded by MLL gene is at amino acid positions Q1198P and K1203Q. The solvent accessibility results showed that 7 residues changed from exposed state in the native type protein to buried state in Q1198P mutant protein and remained unchanged in the case of K1203Q. From the overall results obtained, nsSNP with id (rs1784246) at the amino acid position Q1198P could be considered as deleterious mutation in the acute leukemia caused by MLL gene.

  1. Computer-assisted identification of multitrace electrophoretic patterns in differential display experiments.

    Science.gov (United States)

    Vähämaa, Heidi; Ojala, Pekka; Pahikkala, Tapio; Nevalainen, Olli S; Lahesmaa, Riitta; Aittokallio, Tero

    2007-03-01

    Modern multicapillary devices allow researchers to address increasingly complex biological questions involving comparisons of gene expression patterns across electrophoretic samples under various experimental conditions. As labor-intensive visual evaluation of the electrophoretic results is often the bottleneck of large-scale differential display (DD) studies, one way to further streamline this process is to focus only on a highly compressed list of the most potential patterns that are likely to provide reliable findings. To enable the identification of such candidate patterns, we present a computer-assisted method for objective ranking of multitrace peak patterns in DD experiments. The fundamental component of the multitrace pattern ranking method (MRANK) is the multiple alignment algorithm that allows for discovery of patterns involving sets of peak complexes from various electrophoretic samples. A score value is attached to each detected pattern which characterizes how accurately the pattern resembles the desired pattern query, freely defined by the researcher. The ranked pattern list produced by MRANK is validated against visual evaluation in terms of detecting and ranking a group of relevant patterns in a DD analysis of T-helper cell differentiation. We demonstrate high enrichment of the desired patterns on top of the score-ranked list (e.g., 90% of the visually selected patterns are discovered by looking through the first 3% of patterns in the ranked list of all patterns). The results suggest that a substantial amount of manual labor can be saved without compromising the accuracy of the findings by prioritizing the patterns according to MRANK output in the visual confirmation phase.

  2. Computational fragment-based binding site identification by ligand competitive saturation.

    Directory of Open Access Journals (Sweden)

    Olgun Guvench

    2009-07-01

    Full Text Available Fragment-based drug discovery using NMR and x-ray crystallographic methods has proven utility but also non-trivial time, materials, and labor costs. Current computational fragment-based approaches circumvent these issues but suffer from limited representations of protein flexibility and solvation effects, leading to difficulties with rigorous ranking of fragment affinities. To overcome these limitations we describe an explicit solvent all-atom molecular dynamics methodology (SILCS: Site Identification by Ligand Competitive Saturation that uses small aliphatic and aromatic molecules plus water molecules to map the affinity pattern of a protein for hydrophobic groups, aromatic groups, hydrogen bond donors, and hydrogen bond acceptors. By simultaneously incorporating ligands representative of all these functionalities, the method is an in silico free energy-based competition assay that generates three-dimensional probability maps of fragment binding (FragMaps indicating favorable fragment:protein interactions. Applied to the two-fold symmetric oncoprotein BCL-6, the SILCS method yields two-fold symmetric FragMaps that recapitulate the crystallographic binding modes of the SMRT and BCOR peptides. These FragMaps account both for important sequence and structure differences in the C-terminal halves of the two peptides and also the high mobility of the BCL-6 His116 sidechain in the peptide-binding groove. Such SILCS FragMaps can be used to qualitatively inform the design of small-molecule inhibitors or as scoring grids for high-throughput in silico docking that incorporate both an atomic-level description of solvation and protein flexibility.

  3. Characterization of electrochemical response of a hybrid micro-nanochannel system using computational impedance spectroscopy (CIS)

    Science.gov (United States)

    Nandigana, Vishal; Aluru, Narayan

    2013-11-01

    Single molecule/particle sensing using micro/nanochannel integrated systems has attracted tremendous interest in recent years. The molecule in an aqueous ionic solution is translocated from the source microchannel towards the drain microchannel across a nanochannel under the influence of an external electric field. The translocated molecules are characterized from the electrical response of the system. In order to develop an efficient design for accurate characterization of single molecules, it is important to first understand the ion-transport dynamics in these integrated systems. To this end, we develop a computationally efficient area-averaged multi-ion transport model (AAM), considering an ion-selective nanochannel integrated with a microchannel on either side. Further, we study the ion transport dynamics both under equilibrium and non-equilibrium regimes. In each regime, the base state is perturbed with an external harmonic electrical disturbance over a wide range of frequency spectrum and the electrochemical impedance response is computed. We correlate each characteristic frequency present in the system to its corresponding physical phenomena and also characterize the microscopic diffusion boundary layer lengths (DBL) observed in the microchannel. This work was supported by the National Science Foundation (NSF) under Grants 0328162 (nano-CEMMS, UIUC), 0852657 and 0915718.

  4. Exploring a Hybrid of Geospatial Semantic Information in Ubiquitous Computing Environments

    Directory of Open Access Journals (Sweden)

    Raghda Fouad

    2011-11-01

    Full Text Available Nowadays, geospatial information plays a critical role. Searching and obtaining geospatial information, however, is a difficult and time-consuming task. The Semantic Web promises to facilitate this by improving the capability to search for information by better expressing the meaning of search queries. Combining the two approaches to create a Geospatial Semantic Web is an idea that is gaining acceptance in both areas. Here, we present a prototype that promises to prove that the meshing of these two areas is a promising field in conjunction with information retrieval and ubiquitous computing. The aim of this prototype is to exploit geospatial semantic information retrieved from multiple data sources ina mobile environment. Our prototype uses three geospatial data sources: GeoNames, LinkedGeoData, and DBpedia. Experimental results show how the merging of the geospatial data sources and the use ofmore than one level of indexing is more effective in terms of recall and precision.

  5. Exploring a Hybrid of Geospatial Semantic Information in Ubiquitous Computing Environments

    Directory of Open Access Journals (Sweden)

    Raghda A. Fouad

    2011-11-01

    Full Text Available Nowadays, geospatial information plays a critical role. Searching and obtaining geospatial information, however, is a difficult and time-consuming task. The Semantic Web promises to facilitate this by improving the capability to search for information by better expressing the meaning of search queries. Combining the two approaches to create a Geospatial Semantic Web is an idea that is gaining acceptance in both areas. Here, we present a prototype that promises to prove that the meshing of these two areas is a promising field in conjunction with information retrieval and ubiquitous computing. The aim of this prototype is to exploit geospatial semantic information retrieved from multiple data sources in a mobile environment. Our prototype uses three geospatial data sources: GeoNames, LinkedGeoData, and DBpedia. Experimental results show how the merging of the geospatial data sources and the use of more than one level of indexing is more effective in terms of recall and precision.

  6. Design Patterns for Sparse-Matrix Computations on Hybrid CPU/GPU Platforms

    Directory of Open Access Journals (Sweden)

    Valeria Cardellini

    2014-01-01

    Full Text Available We apply object-oriented software design patterns to develop code for scientific software involving sparse matrices. Design patterns arise when multiple independent developments produce similar designs which converge onto a generic solution. We demonstrate how to use design patterns to implement an interface for sparse matrix computations on NVIDIA GPUs starting from PSBLAS, an existing sparse matrix library, and from existing sets of GPU kernels for sparse matrices. We also compare the throughput of the PSBLAS sparse matrix–vector multiplication on two platforms exploiting the GPU with that obtained by a CPU-only PSBLAS implementation. Our experiments exhibit encouraging results regarding the comparison between CPU and GPU executions in double precision, obtaining a speedup of up to 35.35 on NVIDIA GTX 285 with respect to AMD Athlon 7750, and up to 10.15 on NVIDIA Tesla C2050 with respect to Intel Xeon X5650.

  7. Solution of the self-adjoint radiative transfer equation on hybrid computer systems

    Science.gov (United States)

    Gasilov, V. A.; Kuchugov, P. A.; Olkhovskaya, O. G.; Chetverushkin, B. N.

    2016-06-01

    A new technique for simulating three-dimensional radiative energy transfer for the use in the software designed for the predictive simulation of plasma with high energy density on parallel computers is proposed. A highly scalable algorithm that takes into account the angular dependence of the radiation intensity and is free of the ray effect is developed based on the solution of a second-order equation with a self-adjoint operator. A distinctive feature of this algorithm is a preliminary transformation of rotation to eliminate mixed derivatives with respect to the spatial variables, simplify the structure of the difference operator, and accelerate the convergence of the iterative solution of the equation. It is shown that the proposed method correctly reproduces the limiting cases—isotropic radiation and the directed radiation with a δ-shaped angular distribution.

  8. Implementation of a Hybrid Controller for Ventilation Control Using Soft Computing

    Energy Technology Data Exchange (ETDEWEB)

    Craig G. Rieger; D. Subbaram Naidu

    2005-06-01

    Many industrial facilities utilize pressure control gradients to prevent migration of hazardous species from containment areas to occupied zones, often using Proportional-Integral-Derivative (PID) control systems. When operators rebalance the facility, variation from the desired gradients can occur and the operating conditions can change enough that the PID parameters are no longer adequate to maintain a stable system. As the goal of the ventilation control system is to optimize the pressure gradients and associated flows for the facility, Linear Quadratic Tracking (LQT) is a method that provides a time-based approach to guiding facility interactions. However, LQT methods are susceptible to modeling and measurement errors, and therefore the additional use of Soft Computing methods are proposed for implementation to account for these errors and nonlinearities.

  9. Identification of transcriptome SNPs for assessing allele-specific gene expression in a super-hybrid rice Xieyou9308.

    Directory of Open Access Journals (Sweden)

    Rongrong Zhai

    Full Text Available Hybridization, a common process in nature, can give rise to a vast reservoir of allelic variants. Combination of these allelic variants may result in novel patterns of gene action and is thought to contribute to heterosis. In this study, we analyzed genome-wide allele-specific gene expression (ASGE in the super-hybrid rice variety Xieyou9308 using RNA sequencing technology (RNA-Seq. We identified 9325 reliable single nucleotide polymorphisms (SNPs distributed throughout the genome. Nearly 68% of the identified polymorphisms were CT and GA SNPs between R9308 and Xieqingzao B, suggesting the existence of DNA methylation, a heritable epigenetic mark, in the parents and their F1 hybrid. Of 2793 identified transcripts with consistent allelic biases, only 480 (17% showed significant allelic biases during tillering and/or heading stages, implying that trans effects may mediate most transcriptional differences in hybrid offspring. Approximately 67% and 62% of the 480 transcripts showed R9308 allelic expression biases at tillering and heading stages, respectively. Transcripts with higher levels of gene expression in R9308 also exhibited R9308 allelic biases in the hybrid. In addition, 125 transcripts were identified with significant allelic expression biases at both stages, of which 74% showed R9308 allelic expression biases. R9308 alleles may tend to preserve their characteristic states of activity in the hybrid and may play important roles in hybrid vigor at both stages. The allelic expression of 355 transcripts was highly stage-specific, with divergent allelic expression patterns observed at different developmental stages. Many transcripts associated with stress resistance were differently regulated in the F1 hybrid. The results of this study may provide valuable insights into molecular mechanisms of heterosis.

  10. Identification of a deletion in the mismatch repair gene, MSH2, using mouse-human cell hybrids monosomal for chromosome 2.

    Science.gov (United States)

    Pyatt, R E; Nakagawa, H; Hampel, H; Sedra, M; Fuchik, M B; Comeras, I; de la Chapelle, A; Prior, T W

    2003-03-01

    Hereditary non-polyposis colorectal cancer is characterized by mutations in one of the DNA mismatch repair genes, primarily MLH1, MSH2, or MSH6. We report here the identification of a genomic deletion of approximately 11.4 kb encompassing the first two exons of the MSH2 gene in two generations of an Ohio family. By Southern blot analysis, using a cDNA probe spanning the first seven exons of MSH2, an alteration in each of three different enzyme digests (including a unique 13-kb band on HindIII digests) was observed, which suggested the presence of a large alteration in the 5' region of this gene. Mouse-human cell hybrids from a mutation carrier were then generated which contained a single copy each of human chromosome 2 on which the MSH2 gene resides. Southern blots on DNA from the cell hybrids demonstrated the same, unique 13-kb band from one MSH2 allele, as seen in the diploid DNA. DNA from this same monosomal cell hybrid failed to amplify in polymerase chain reactions (PCRs) using primers to exons 1 and 2, demonstrating the deletion of these sequences in one MSH2 allele, and the breakpoints involving Alu repeats were identified by PCR amplification and sequence analysis.

  11. Hybrid EEG-fNIRS Asynchronous Brain-Computer Interface for Multiple Motor Tasks.

    Directory of Open Access Journals (Sweden)

    Alessio Paolo Buccino

    Full Text Available Non-invasive Brain-Computer Interfaces (BCI have demonstrated great promise for neuroprosthetics and assistive devices. Here we aim to investigate methods to combine Electroencephalography (EEG and functional Near-Infrared Spectroscopy (fNIRS in an asynchronous Sensory Motor rhythm (SMR-based BCI. We attempted to classify 4 different executed movements, namely, Right-Arm-Left-Arm-Right-Hand-Left-Hand tasks. Previous studies demonstrated the benefit of EEG-fNIRS combination. However, since normally fNIRS hemodynamic response shows a long delay, we investigated new features, involving slope indicators, in order to immediately detect changes in the signals. Moreover, Common Spatial Patterns (CSPs have been applied to both EEG and fNIRS signals. 15 healthy subjects took part in the experiments and since 25 trials per class were available, CSPs have been regularized with information from the entire population of participants and optimized using genetic algorithms. The different features have been compared in terms of performance and the dynamic accuracy over trials shows that the introduced methods diminish the fNIRS delay in the detection of changes.

  12. A Hybrid FPGA/Tilera Compute Element for Autonomous Hazard Detection and Navigation

    Science.gov (United States)

    Villalpando, Carlos Y.; Werner, Robert A.; Carson, John M., III; Khanoyan, Garen; Stern, Ryan A.; Trawny, Nikolas

    2013-01-01

    To increase safety for future missions landing on other planetary or lunar bodies, the Autonomous Landing and Hazard Avoidance Technology (ALHAT) program is developing an integrated sensor for autonomous surface analysis and hazard determination. The ALHAT Hazard Detection System (HDS) consists of a Flash LIDAR for measuring the topography of the landing site, a gimbal to scan across the terrain, and an Inertial Measurement Unit (IMU), along with terrain analysis algorithms to identify the landing site and the local hazards. An FPGA and Manycore processor system was developed to interface all the devices in the HDS, to provide high-resolution timing to accurately measure system state, and to run the surface analysis algorithms quickly and efficiently. In this paper, we will describe how we integrated COTS components such as an FPGA evaluation board, a TILExpress64, and multi-threaded/multi-core aware software to build the HDS Compute Element (HDSCE). The ALHAT program is also working with the NASA Morpheus Project and has integrated the HDS as a sensor on the Morpheus Lander. This paper will also describe how the HDS is integrated with the Morpheus lander and the results of the initial test flights with the HDS installed. We will also describe future improvements to the HDSCE.

  13. Neural networks with multiple general neuron models: a hybrid computational intelligence approach using Genetic Programming.

    Science.gov (United States)

    Barton, Alan J; Valdés, Julio J; Orchard, Robert

    2009-01-01

    Classical neural networks are composed of neurons whose nature is determined by a certain function (the neuron model), usually pre-specified. In this paper, a type of neural network (NN-GP) is presented in which: (i) each neuron may have its own neuron model in the form of a general function, (ii) any layout (i.e network interconnection) is possible, and (iii) no bias nodes or weights are associated to the connections, neurons or layers. The general functions associated to a neuron are learned by searching a function space. They are not provided a priori, but are rather built as part of an Evolutionary Computation process based on Genetic Programming. The resulting network solutions are evaluated based on a fitness measure, which may, for example, be based on classification or regression errors. Two real-world examples are presented to illustrate the promising behaviour on classification problems via construction of a low-dimensional representation of a high-dimensional parameter space associated to the set of all network solutions.

  14. A hybrid FPGA/Tilera compute element for autonomous hazard detection and navigation

    Science.gov (United States)

    Villalpando, C. Y.; Werner, R. A.; Carson, J. M.; Khanoyan, G.; Stern, R. A.; Trawny, N.

    To increase safety for future missions landing on other planetary or lunar bodies, the Autonomous Landing and Hazard Avoidance Technology (ALHAT) program is developing an integrated sensor for autonomous surface analysis and hazard determination. The ALHAT Hazard Detection System (HDS) consists of a Flash LIDAR for measuring the topography of the landing site, a gimbal to scan across the terrain, and an Inertial Measurement Unit (IMU), along with terrain analysis algorithms to identify the landing site and the local hazards. An FPGA and Manycore processor system was developed to interface all the devices in the HDS, to provide high-resolution timing to accurately measure system state, and to run the surface analysis algorithms quickly and efficiently. In this paper, we will describe how we integrated COTS components such as an FPGA evaluation board, a TILExpress64, and multi-threaded/multi-core aware software to build the HDS Compute Element (HDSCE). The ALHAT program is also working with the NASA Morpheus Project and has integrated the HDS as a sensor on the Morpheus Lander. This paper will also describe how the HDS is integrated with the Morpheus lander and the results of the initial test flights with the HDS installed. We will also describe future improvements to the HDSCE.

  15. A fully parallel, high precision, N-body code running on hybrid computing platforms

    CERN Document Server

    Capuzzo-Dolcetta, R; Punzo, D

    2012-01-01

    We present a new implementation of the numerical integration of the classical, gravitational, N-body problem based on a high order Hermite's integration scheme with block time steps, with a direct evaluation of the particle-particle forces. The main innovation of this code (called HiGPUs) is its full parallelization, exploiting both OpenMP and MPI in the use of the multicore Central Processing Units as well as either Compute Unified Device Architecture (CUDA) or OpenCL for the hosted Graphic Processing Units. We tested both performance and accuracy of the code using up to 256 GPUs in the supercomputer IBM iDataPlex DX360M3 Linux Infiniband Cluster provided by the italian supercomputing consortium CINECA, for values of N up to 8 millions. We were able to follow the evolution of a system of 8 million bodies for few crossing times, task previously unreached by direct summation codes. The code is freely available to the scientific community.

  16. Patient-specific reconstruction utilizing computer assisted 3D modelling for partial bone flap defect in hybrid cranioplasty

    Science.gov (United States)

    Hueh, Low Peh; Abdullah, Johari Yap; Abdullah, Abdul Manaf; Yahya, Suzana; Idris, Zamzuri; Mohamad, Dasmawati

    2016-12-01

    Autologous cranioplasty using a patient's original bone flap remain the commonest practice nowadays. However, partial bone flap defect is commonly encountered. Replacing the bone flap with pre-moulded synthetic bone flap is costly and not affordable to many patients. Hence most of the small to medium size defect was topped up with alloplastic material on a free hand basis intra-operatively which often resulted in inaccurate implant approximation with unsatisfactory cosmetic result. This study aims to evaluate implant accuracy and cosmetic outcome of cranioplasty candidates who underwent partial bone flap reconstruction utilising computer assisted 3D modelling. 3D images of the skull were obtained from post-craniectomy axial 1-mm spiral computed tomography (CT) scans and a virtual 3D model was generated using the Materialise Mimics software. The Materialise 3-Matic was then utilised to design a patient-specific implant. Prefabrication of the implant was performed by the 3D Objet printer, and a negative gypsum mold was created with the prefabricated cranial implant. Intraoperatively, a hybrid polymethyl methacrylate (PMMA)-autologous cranial implant was produced using the gypsum mold, and fit into the cranial defect. This study is still ongoing at the moment. To date, two men has underwent partial bone flap reconstruction utilising this technique and both revealed satisfactory implant alignment with favourable cosmesis. Mean implant size was 12cm2, and the mean duration of intraoperative reconstruction for the partial bone flap defect was 40 minutes. No significant complication was reported. As a conclusion, this new technique and approach resulted in satisfactory implant alignment and favourable cosmetic outcome. However, more study samples are needed to increase the validity of the study results.

  17. A hybrid stochastic-deterministic computational model accurately describes spatial dynamics and virus diffusion in HIV-1 growth competition assay.

    Science.gov (United States)

    Immonen, Taina; Gibson, Richard; Leitner, Thomas; Miller, Melanie A; Arts, Eric J; Somersalo, Erkki; Calvetti, Daniela

    2012-11-01

    We present a new hybrid stochastic-deterministic, spatially distributed computational model to simulate growth competition assays on a relatively immobile monolayer of peripheral blood mononuclear cells (PBMCs), commonly used for determining ex vivo fitness of human immunodeficiency virus type-1 (HIV-1). The novel features of our approach include incorporation of viral diffusion through a deterministic diffusion model while simulating cellular dynamics via a stochastic Markov chain model. The model accounts for multiple infections of target cells, CD4-downregulation, and the delay between the infection of a cell and the production of new virus particles. The minimum threshold level of infection induced by a virus inoculum is determined via a series of dilution experiments, and is used to determine the probability of infection of a susceptible cell as a function of local virus density. We illustrate how this model can be used for estimating the distribution of cells infected by either a single virus type or two competing viruses. Our model captures experimentally observed variation in the fitness difference between two virus strains, and suggests a way to minimize variation and dual infection in experiments.

  18. Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis

    Directory of Open Access Journals (Sweden)

    Chen Jiun-Ching

    2007-05-01

    Full Text Available Abstract Background Genome-wide identification of specific oligonucleotides (oligos is a computationally-intensive task and is a requirement for designing microarray probes, primers, and siRNAs. An artificial neural network (ANN is a machine learning technique that can effectively process complex and high noise data. Here, ANNs are applied to process the unique subsequence distribution for prediction of specific oligos. Results We present a novel and efficient algorithm, named the integration of ANN and BLAST (IAB algorithm, to identify specific oligos. We establish the unique marker database for human and rat gene index databases using the hash table algorithm. We then create the input vectors, via the unique marker database, to train and test the ANN. The trained ANN predicted the specific oligos with high efficiency, and these oligos were subsequently verified by BLAST. To improve the prediction performance, the ANN over-fitting issue was avoided by early stopping with the best observed error and a k-fold validation was also applied. The performance of the IAB algorithm was about 5.2, 7.1, and 6.7 times faster than the BLAST search without ANN for experimental results of 70-mer, 50-mer, and 25-mer specific oligos, respectively. In addition, the results of polymerase chain reactions showed that the primers predicted by the IAB algorithm could specifically amplify the corresponding genes. The IAB algorithm has been integrated into a previously published comprehensive web server to support microarray analysis and genome-wide iterative enrichment analysis, through which users can identify a group of desired genes and then discover the specific oligos of these genes. Conclusion The IAB algorithm has been developed to construct SpecificDB, a web server that provides a specific and valid oligo database of the probe, siRNA, and primer design for the human genome. We also demonstrate the ability of the IAB algorithm to predict specific oligos through

  19. Cloned polynucleotide and synthetic oligonucleotide probes used in colony hybridization are equally efficient in the identification of enterotoxigenic Escherichia coli

    Energy Technology Data Exchange (ETDEWEB)

    Sommerfelt, H.; Kalland, K.H.; Raj, P.; Moseley, S.L.; Bhan, M.K.; Bjorvatn, B.

    1988-11-01

    Restriction endonuclease-generated polynucleotide and synthetically produced oligonucleotide gene probes used in colony hybridization assays proved to be efficient for the detection and differentiation of enterotoxigenic Escherichia coli. To compare their relative efficiencies, these two sets of probes were radiolabeled with /sup 32/P and were applied to 74 strains of E. coli with known enterotoxin profiles and to 156 previously unexamined E. coli isolates. The enterotoxigenic bacteria Vibrio cholerae O1, Vibrio cholerae non-O1 (NAG), Yersinia enterocolitica, and E. coli harboring the plasmid vectors of the polynucleotide gene probes were examined for further evaluation of probe specificity. The two classes of probes showed a perfect concordance in their specific detection and differentiation of enterotoxigenic E. coli. In the analysis of six strains, the signal strength on autoradiography after hybridization with oligonucleotides was weaker than that obtained after hybridization with polynucleotide probes. The probes did not hybridize with DNA from V. cholerae O1, V. cholerae non-O1 (NAG), or Y. enterocolitica. The strains of E. coli harboring the plasmid vectors of the polynucleotide gene probes were, likewise, negative in the hybridization assays.

  20. Comparison of rapid hybridization-based pathogen identification and resistance evaluation in sepsis using the Verigene® device paired with "good old culture".

    Science.gov (United States)

    Berktold, Michael; Mutschlechner, Wolfgang; Orth-Höller, Dorothea

    2017-06-01

    Rapid microbial diagnostics is important for septicemic patients. The current gold standard is blood culture with consecutive pathogen identification and antimicrobial susceptibility testing. However, these culture-based methods need at least 48 h.The aim of this study was to compare Verigene(®) (Nanosphere, Northbrook, IL, USA), a rapid hybridization-based method, with conventional culture-based methods for detection of pathogens and resistance markers from positive blood cultures of septic patients.In 85 of 100 tested blood culture samples (85 %), pathogen identification as well as resistance profile were identical in Verigene and conventional culture. In 4 %, discordant results were observed. In 9 %, conventional culture revealed a pathogen ID or resistance phenotype not included in the Verigene panel. In 2 % no Verigene result was available.In conclusion, Verigene offers the availability of fast and reliable pathogen identification and resistance profile determination, which may result in an earlier start of adequate antimicrobial treatment.

  1. Linear equations and rap battles: how students in a wired classroom utilized the computer as a resource to coordinate personal and mathematical positional identities in hybrid spaces

    Science.gov (United States)

    Langer-Osuna, Jennifer

    2015-03-01

    This paper draws on the constructs of hybridity, figured worlds, and cultural capital to examine how a group of African-American students in a technology-driven, project-based algebra classroom utilized the computer as a resource to coordinate personal and mathematical positional identities during group work. Analyses of several vignettes of small group dynamics highlight how hybridity was established as the students engaged in multiple on-task and off-task computer-based activities, each of which drew on different lived experiences and forms of cultural capital. The paper ends with a discussion on how classrooms that make use of student-led collaborative work, and where students are afforded autonomy, have the potential to support the academic engagement of students from historically marginalized communities.

  2. Identification of Cognitive Processes of Effective and Ineffective Students during Computer Programming

    Science.gov (United States)

    Renumol, V. G.; Janakiram, Dharanipragada; Jayaprakash, S.

    2010-01-01

    Identifying the set of cognitive processes (CPs) a student can go through during computer programming is an interesting research problem. It can provide a better understanding of the human aspects in computer programming process and can also contribute to the computer programming education in general. The study identified the presence of a set of…

  3. 棉属三元杂种的合成及细胞遗传学鉴定%Synthesis and Cytogenetic Identification of Trispecific Hybrid in Cotton

    Institute of Scientific and Technical Information of China (English)

    荣二花; 李灵娇; 杨娜; 陈弟; 吴玉香

    2015-01-01

    棉属有丰富的种质资源,野生棉具有栽培棉种所缺乏的许多优良性状,为了将野生澳洲棉和达尔文棉的优良性状导入陆地棉,以期改良栽培种陆地棉。本研究通过陆地棉和 C 组野生澳洲棉远缘杂交获得杂种 F1,并对其进行染色体加倍,将加倍成的异源六倍体与野生四倍体达尔文棉杂交,获得陆地棉、澳洲棉、达尔文棉的三元杂种,并对该杂种进行形态学和细胞遗传学鉴定。形态学观察结果表明:三元杂种有三个亲本的遗传特性。花粉母细胞减数分裂结果表明后期存在异常行为,主要表现在65%的花粉母细胞减数分裂后期染色体不能均等分离,使得末期形成大量的多分体,这些多分体会进一步发育为败育花粉粒,统计结果表明正常花粉粒只占18.3%,导致该杂种高度不育。本研究不仅合成了综合三个亲本特性的三元杂种,也为该杂种不育提供了细胞遗传学证据,并为棉花新种质的创制提供了理论依据和中间材料。%There are rich germplasm resources in Gossypium and wild cotton species possess many valuable agronomic traits which cultivated cotton always lacks .In order to introgress the useful traits from wild species G .australe and G . darwinii into cultivated species ,tetraploid G . hirsutum was crossed directly with C‐genome species G . australe as male parent ,creating a triploid hybrid .Chromosome doubling of this triploid hybrid leads to a allohexaploid which was then crossed with wild tetraploid species G . darwinii ,resulting in trispecific hybrid (G .hirsutum ,G . australe ,G . darwinii ) .The morphology characteristic and cytogenetic identification of trispecific hybrid was further investigated in this study .The hybrid morphology performed combining characteristics from three parents .Results indicated that the meiosis of trispecific hybrid was abnormal ,and 65% abnormal multispores appeared in the

  4. Identification of a hybrid PKS-NRPS required for the biosynthesis of NG-391 in Metarhizium anisopliae var. anisopliae

    Science.gov (United States)

    A 19,818 kb genomic region harboring six predicted ORFs was identified in M. anisopliae ARSEF 2575. ORF4, putatively encoding a hybrid polyketide synthase-nonribosomal peptide synthetase (PKS-NRPS) was targeted using Agrobacterium-mediated gene knockout. Homologous recombinants failed to produce det...

  5. Identification of resistance to aflatoxin accumulation and yield potential in maize hybrids in the Southeast Regional Aflatoxin Trials (SERAT)

    Science.gov (United States)

    Aflatoxins pose a serious health hazard to humans and livestock, requiring significant economic cost in identifying and disposing of contaminated grain. Since 2003, a multi-environmental trial of public breeding maize (Zea mays L.) hybrids across multiple programs in the southeastern United States h...

  6. Molecular cytogenetics of Alstroemeria: identification of parental genomes in interspecific hybrids and characterization of repetitive DNA families in constitutive heterochromatin.

    Science.gov (United States)

    Kuipers, A G; van Os, D P; de Jong, J H; Ramanna, M S

    1997-02-01

    The genus Alstroemeria consists of diploid (2n = 2x = 16) species originating mainly from Chile and Brazil. Most cultivars are triploid or tetraploid interspecific hybrids. C-banding of eight species revealed obvious differentiation of constitutive heterochromatin within the genus. The present study focused on the molecular (cyto)genetic background of this differentiation. Genomic slot-blot analysis demonstrated strong conservation of major parts of the genomes among six species. The chromosomes of A. aurea and A. ligtu, species with pronounced interstitial C-bands, were found to contain large amounts of highly repetitive and species-specific DNA. The variation in size, number and intensity of strongly probed bands of major repetitive DNA families observed in genomic Southern blots of Sau3A, HaeIII, and MseI digests indicated a strong correlation between variation in genomic DNA composition and different C-banding patterns among Alstroemeria species. Genomic in situ hybridization (GISH) revealed a clear distinction between parental chromosomes in the hybrids between Chilean and Brazilian species and also between Chilean species, as long as at least one of the parental species possessed prominent C-banding. Regarding the latter, discriminative hybridization resulted from highly repetitive species specific DNA in the heterochromatic chromosome regions of A. aurea and A. ligtu, and caused GISH banding patterns that coincided with the C-banding patterns.

  7. Detection and identification of Vibrio parahaemolyticus by multiplex PCR and DNA-DNA hybridization on a microarray

    Institute of Scientific and Technical Information of China (English)

    Rongzhi Wang; Jiadong Huang; Wei Zhang; Guangmei Lin; Junwei Lian; Libin Jiang; Hongcong Lin; Songfa Wang; Shihua Wang

    2011-01-01

    In this paper,we developed a rapid and accurate method for the detection of Vibrio parahaemolyticus strains,using multiplex PCR and DNA-DNA hybridization.Multiplex PCR was used to simultaneously amplify three diagnostic genes(tlh,tdh and fia)that serve as molecular markers of V.parahaemolyticus.Biotinylated PCR products were hybridized to primers immobilized on a microarray,and detected by chemiluminesce with avidin-conjugated alkaline phosphatase.With this method,forty-five samples were tested.Eight known virulent strains (tlh+/tdh+/fia+)and four known avirulent strains(tlh+/tdh-/fla+)of the V.parahaemolyttcus were successtuny aetectea,ana no non-spectnc hybridization and cross-hybridization reaction were found from fifteen closely-related strains(tin-/tdh-/fta+)or the Vibrio spp.In addition,all the other eighteen strains of non-Vibrio bacteria(tlh-/tdh-/fla-)gave negative results.The DNA microarray successfully distinguished V.parahaemolyticus from other Vibrio spp.The results demonstrated that this was an efficient and robust method for identifying virulent strains of V.parahaemolyticus.

  8. Identification of environmental issues: Hybrid wood-geothermal power plant, Wendel-Amedee KGRA, Lassen County, California: First phase report

    Energy Technology Data Exchange (ETDEWEB)

    1981-08-14

    The development of a 55 MWe power plant in Lassen County, California, has been proposed. The proposed power plant is unique in that it will utilize goethermal heat and wood fuel to generate electrical power. This report identifies environmental issues and constraints which may impact the proposed hybrid wood-geothermal power plant. (ACR)

  9. Integrating Remote Sensing Data, Hybrid-Cloud Computing, and Event Notifications for Advanced Rapid Imaging & Analysis (Invited)

    Science.gov (United States)

    Hua, H.; Owen, S. E.; Yun, S.; Lundgren, P.; Fielding, E. J.; Agram, P.; Manipon, G.; Stough, T. M.; Simons, M.; Rosen, P. A.; Wilson, B. D.; Poland, M. P.; Cervelli, P. F.; Cruz, J.

    2013-12-01

    Space-based geodetic measurement techniques such as Interferometric Synthetic Aperture Radar (InSAR) and Continuous Global Positioning System (CGPS) are now important elements in our toolset for monitoring earthquake-generating faults, volcanic eruptions, hurricane damage, landslides, reservoir subsidence, and other natural and man-made hazards. Geodetic imaging's unique ability to capture surface deformation with high spatial and temporal resolution has revolutionized both earthquake science and volcanology. Continuous monitoring of surface deformation and surface change before, during, and after natural hazards improves decision-making from better forecasts, increased situational awareness, and more informed recovery. However, analyses of InSAR and GPS data sets are currently handcrafted following events and are not generated rapidly and reliably enough for use in operational response to natural disasters. Additionally, the sheer data volumes needed to handle a continuous stream of InSAR data sets also presents a bottleneck. It has been estimated that continuous processing of InSAR coverage of California alone over 3-years would reach PB-scale data volumes. Our Advanced Rapid Imaging and Analysis for Monitoring Hazards (ARIA-MH) science data system enables both science and decision-making communities to monitor areas of interest with derived geodetic data products via seamless data preparation, processing, discovery, and access. We will present our findings on the use of hybrid-cloud computing to improve the timely processing and delivery of geodetic data products, integrating event notifications from USGS to improve the timely processing for response, as well as providing browse results for quick looks with other tools for integrative analysis.

  10. A comparison of methods for computing the sigma-coordinate pressure gradient force for flow over sloped terrain in a hybrid theta-sigma model

    Science.gov (United States)

    Johnson, D. R.; Uccellini, L. W.

    1983-01-01

    In connection with the employment of the sigma coordinates introduced by Phillips (1957), problems can arise regarding an accurate finite-difference computation of the pressure gradient force. Over steeply sloped terrain, the calculation of the sigma-coordinate pressure gradient force involves computing the difference between two large terms of opposite sign which results in large truncation error. To reduce the truncation error, several finite-difference methods have been designed and implemented. The present investigation has the objective to provide another method of computing the sigma-coordinate pressure gradient force. Phillips' method is applied for the elimination of a hydrostatic component to a flux formulation. The new technique is compared with four other methods for computing the pressure gradient force. The work is motivated by the desire to use an isentropic and sigma-coordinate hybrid model for experiments designed to study flow near mountainous terrain.

  11. Identification of transcriptome SNPs between Xiphophorus lines and species for assessing allele specific gene expression within F₁ interspecies hybrids.

    Science.gov (United States)

    Shen, Yingjia; Catchen, Julian; Garcia, Tzintzuni; Amores, Angel; Beldorth, Ion; Wagner, Jonathan; Zhang, Ziping; Postlethwait, John; Warren, Wes; Schartl, Manfred; Walter, Ronald B

    2012-01-01

    Variations in gene expression are essential for the evolution of novel phenotypes and for speciation. Studying allelic specific gene expression (ASGE) within interspecies hybrids provides a unique opportunity to reveal underlying mechanisms of genetic variation. Using Xiphophorus interspecies hybrid fishes and high-throughput next generation sequencing technology, we were able to assess variations between two closely related vertebrate species, Xiphophorus maculatus and Xiphophorus couchianus, and their F(1) interspecies hybrids. We constructed transcriptome-wide SNP polymorphism sets between two highly inbred X. maculatus lines (JP 163 A and B), and between X. maculatus and a second species, X. couchianus. The X. maculatus JP 163 A and B parental lines have been separated in the laboratory for ≈70 years and we were able to identify SNPs at a resolution of 1 SNP per 49 kb of transcriptome. In contrast, SNP polymorphisms between X. couchianus and X. maculatus species, which diverged ≈5-10 million years ago, were identified about every 700 bp. Using 6524 transcripts with identified SNPs between the two parental species (X. maculatus and X. couchianus), we mapped RNA-seq reads to determine ASGE within F(1) interspecies hybrids. We developed an in silico X. couchianus transcriptome by replacing 90,788 SNP bases for X. maculatus transcriptome with the consensus X. couchianus SNP bases and provide evidence that this procedure overcomes read mapping biases. Employment of the in silico reference transcriptome and tolerating 5 mismatches during read mapping allow direct assessment of ASGE in the F(1) interspecies hybrids. Overall, these results show that Xiphophorus is a tractable vertebrate experimental model to investigate how genetic variations that occur during speciation may affect gene interactions and the regulation of gene expression.

  12. Applications of Multiple Nuclear Genes to the Molecular Phylogeny, Population Genetics and Hybrid Identification in the Mangrove Genus Rhizophora.

    Directory of Open Access Journals (Sweden)

    Yongmei Chen

    Full Text Available The genus Rhizophora is one of the most important components of mangrove forests. It is an ideal system for studying biogeography, molecular evolution, population genetics, hybridization and conservation genetics of mangroves. However, there are no sufficient molecular markers to address these topics. Here, we developed 77 pairs of nuclear gene primers, which showed successful PCR amplifications across all five Rhizophora species and sequencing in R. apiculata. Here, we present three tentative applications using a subset of the developed nuclear genes to (I reconstruct the phylogeny, (II examine the genetic structure and (III identify natural hybridization in Rhizophora. Phylogenetic analyses support the hypothesis that Rhizophora had disappeared in the Atlantic-East Pacific (AEP region and was re-colonized from the IWP region approximately 12.7 Mya. Population genetics analyses in four natural populations of R. apiculata in Hainan, China, revealed extremely low genetic diversity, strong population differentiation and extensive admixture, suggesting that the Pleistocene glaciations, particularly the last glacial maximum, greatly influenced the population dynamics of R. apiculata in Hainan. We also verified the hybrid status of a morphologically intermediate individual between R. apiculata and R. stylosa in Hainan. Based on the sequences of five nuclear genes and one chloroplast intergenic spacer, this individual is likely to be an F1 hybrid, with R. stylosa as its maternal parent. The nuclear gene markers developed in this study should be of great value for characterizing the hybridization and introgression patterns in other cases of this genus and testing the role of natural selection using population genomics approaches.

  13. Computer system for identification of tool wear model in hot forging

    Directory of Open Access Journals (Sweden)

    Wilkus Marek

    2016-01-01

    Full Text Available The aim of the research was to create a methodology that will enable effective and reliable prediction of the tool wear. The idea of the hybrid model, which accounts for various mechanisms of tool material deterioration, is proposed in the paper. The mechanisms, which were considered, include abrasive wear, adhesive wear, thermal fatigue, mechanical fatigue, oxidation and plastic deformation. Individual models of various complexity were used for separate phenomena and strategy of combination of these models in one hybrid system was developed to account for the synergy of various mechanisms. The complex hybrid model was built on the basis of these individual models for various wear mechanisms. The individual models expanded from phenomenological ones for abrasive wear to multi-scale methods for modelling micro cracks initiation and propagation utilizing virtual representations of granular microstructures. The latter have been intensively developed recently and they form potentially a powerful tool that allows modelling of thermal and mechanical fatigue, accounting explicitly for the tool material microstructure.

  14. Intraply Hybrid Composite Design

    Science.gov (United States)

    Chamis, C. C.; Sinclair, J. H.

    1986-01-01

    Several theoretical approaches combined in program. Intraply hybrid composites investigated theoretically and experimentally at Lewis Research Center. Theories developed during investigations and corroborated by attendant experiments used to develop computer program identified as INHYD (Intraply Hybrid Composite Design). INHYD includes several composites micromechanics theories, intraply hybrid composite theories, and integrated hygrothermomechanical theory. Equations from theories used by program as appropriate for user's specific applications.

  15. Analysis and identification of time-invariant systems, time-varying systems, and multi-delay systems using orthogonal hybrid functions theory and algorithms with Matlab

    CERN Document Server

    Deb, Anish; Sarkar, Gautam

    2016-01-01

    This book introduces a new set of orthogonal hybrid functions (HF) which approximates time functions in a piecewise linear manner which is very suitable for practical applications. The book presents an analysis of different systems namely, time-invariant system, time-varying system, multi-delay systems---both homogeneous and non-homogeneous type- and the solutions are obtained in the form of discrete samples. The book also investigates system identification problems for many of the above systems. The book is spread over 15 chapters and contains 180 black and white figures, 18 colour figures, 85 tables and 56 illustrative examples. MATLAB codes for many such examples are included at the end of the book.

  16.   In situ identification of streptococci and other bacteria in initial dental biofilm by confocal laser scanning microscopy and fluorescence in situ hybridization

    DEFF Research Database (Denmark)

    Dige, Irene; Kilian, Mogens; Nilsson, Holger

    2007-01-01

    Confocal laser scanning microscopy (CLSM) has been employed as a method for studying intact natural biofilm. When combined with fluorescence in situ hybridization (FISH) it is possible to analyze spatial relationships and changes of specific members of microbial populations over time. The aim...... of this study was to perform a systematic description of the pattern of initial dental biofilm formation by applying 16S rRNA- targeted oligonucleotide probes to the identification of streptococci and other bacteria, and to evaluate the usefulness of the combination of CLSM and FISH for structural studies......) and analysed by CLSM. The current approach of using FISH techniques enabled differentiation of streptococci from other bacteria and determination of their spatio-temporal organization. The presence of chimney-like multilayered microcolonies with different microbial compo- sitions demonstrated...

  17. Identification of the origin of marker chromosomes by two-color fluorescence in situ hybridization and polymerase chain reaction in azoospermic patients.

    Science.gov (United States)

    Wei, C L; Cheng, J L; Yang, W C; Li, L Y; Cheng, H C; Fu, J J

    2015-11-19

    Y chromosomal microdeletions at the azoospermia factor locus and chromosome abnormalities have been implicated as the major causes of idiopathic male infertility. A marker chromosome is a structurally abnormal chromosome in which no part can be identified by cytogenetics. In this study, to identify the origin of the marker chromosomes and to perform a genetic diagnosis of patients with azoospermia, two-color fluorescence in situ hybridization (FISH) and polymerase chain reaction (PCR) techniques were carried out. The marker chromosomes for the two patients with azoospermia originated in the Y chromosome; it was ascertained that the karyotype of both patients was 46,X, ish del(Y)(q11)(DYZ3+, DXZ1-). The combination of two-color FISH and PCR techniques is an important method for the identification of the origin of marker chromosomes. Thus, genetic counseling and a clear genetic diagnosis of patients with azoospermia before intracytoplasmic sperm injection or other clinical managements are important.

  18. Unambiguous Metabolite Identification in High-Throughput Metabolomics by Hybrid 1H-NMR/ESI-MS1 Approach

    Energy Technology Data Exchange (ETDEWEB)

    2016-10-18

    The invention improves accuracy of metabolite identification by combining direct infusion ESI-MS with one-dimensional 1H-NMR spectroscopy. First, we apply a standard 1H-NMR metabolite identification protocol by matching the chemical shift, J-coupling and intensity information of experimental NMR signals against the NMR signals of standard metabolites in a metabolomics reference libraries. This generates a list of candidate metabolites. The list contains both false positive and ambiguous identifications. The software tool (the invention) takes the list of candidate metabolites, generated from NMRbased metabolite identification, and then calculates, for each of the candidate metabolites, the monoisotopic mass-tocharge (m/z) ratios for each commonly observed ion, fragment and adduct feature. These are then used to assign m/z ratios in experimental ESI-MS spectra of the same sample. Detection of the signals of a given metabolite in both NMR and MS spectra resolves the ambiguities, and therefore, significantly improves the confidence of the identification.

  19. Rapid Genotyping of the Human Renin (REN Gene by the LightCycler® Instrument: Identification of Unexpected Nucleotide Substitutions within the Selected Hybridization Probe Area

    Directory of Open Access Journals (Sweden)

    Line Wee

    2010-01-01

    Full Text Available Preeclampsia is a serious disorder affecting nearly 3% of all in the Western world. It is associated with hypertension and proteinuria, and several lines of evidence suggest that the renin-angiotensin system (RAS may be involved in the development of hypertension at different stages of a preeclamptic pregnancy. In this study, we developed rapid genotyping assays on the LightCycler® instrument to allow the detection of genetic variants in the renin gene (REN that may predispose to preeclampsia. The method is based on real-time PCR and allele-specific hybridization probes, followed by fluorescent melting curve analysis to expose a change in melting temperature (Tm. Ninety-two mother-father-child triads (n=276 from preeclamptic pregnancies were genotyped for three haplotype-tagging single nucleotide polymorphisms (htSNPs in REN. All three htSNPs (rs5705, rs1464816 and rs3795575 were successfully genotyped. Furthermore, two unexpected nucleotide substitutions (rs11571084 and rs61757041 were identified within the selected hybridization probe area of rs1464816 and rs3795575 due to aberrant melting peaks. In conclusion, genotyping on the LightCycler® instrument proved to be rapid and highly reproducible. The ability to uncover additional nucleotide substitutions is particularly important in that it allows the identification of potentially etiological variants that might otherwise be overlooked by other genotyping methods.

  20. Automated design of probes for rRNA-targeted fluorescence in situ hybridization reveals the advantages of using dual probes for accurate identification.

    Science.gov (United States)

    Wright, Erik S; Yilmaz, L Safak; Corcoran, Andrew M; Ökten, Hatice E; Noguera, Daniel R

    2014-08-01

    Fluorescence in situ hybridization (FISH) is a common technique for identifying cells in their natural environment and is often used to complement next-generation sequencing approaches as an integral part of the full-cycle rRNA approach. A major challenge in FISH is the design of oligonucleotide probes with high sensitivity and specificity to their target group. The rapidly expanding number of rRNA sequences has increased awareness of the number of potential nontargets for every FISH probe, making the design of new FISH probes challenging using traditional methods. In this study, we conducted a systematic analysis of published probes that revealed that many have insufficient coverage or specificity for their intended target group. Therefore, we developed an improved thermodynamic model of FISH that can be applied at any taxonomic level, used the model to systematically design probes for all recognized genera of bacteria and archaea, and identified potential cross-hybridizations for the selected probes. This analysis resulted in high-specificity probes for 35.6% of the genera when a single probe was used in the absence of competitor probes and for 60.9% when up to two competitor probes were used. Requiring the hybridization of two independent probes for positive identification further increased specificity. In this case, we could design highly specific probe sets for up to 68.5% of the genera without the use of competitor probes and 87.7% when up to two competitor probes were used. The probes designed in this study, as well as tools for designing new probes, are available online (http://DECIPHER.cee.wisc.edu).

  1. Contrasting molecular and morphological evidence for the identification of an anomalous Buteo: a cautionary tale for hybrid diagnosis.

    Science.gov (United States)

    Clark, William S; Galen, Spencer C; Hull, Joshua M; Mayo, Megan A; Witt, Christopher C

    2017-01-01

    An adult Buteo was found dead as a road-kill south of Sacramento, California, and was thought to represent the first state record of the eastern Red-shouldered Hawk (B. lineatus lineatus;). It is now a specimen in the Museum of Wildlife and Fisheries Biology (WFB 4816) at the University of California, Davis. We examined this specimen and found that many of its plumage characters differed from all other adult Red-shouldered Hawks examined, including nominate adults. Plumage markings and measurements were intermediate between Red-tailed Hawk (Buteo jamaicensis, ssp calurus) and Red-shouldered Hawk (ssp elegans), leading us to hypothesize that the bird was a hybrid. However, mtDNA sequences and nuDNA microsatellites proved definitively that the bird was a Red-shouldered Hawk, most likely of eastern origin. This case illustrates that apparent hybrids or apparent vagrants could be individuals with anomalous phenotypes caused by rare genetic variation or novel epigenetic effects.

  2. Demonstration of a semi-autonomous hybrid brain-machine interface using human intracranial EEG, eye tracking, and computer vision to control a robotic upper limb prosthetic.

    Science.gov (United States)

    McMullen, David P; Hotson, Guy; Katyal, Kapil D; Wester, Brock A; Fifer, Matthew S; McGee, Timothy G; Harris, Andrew; Johannes, Matthew S; Vogelstein, R Jacob; Ravitz, Alan D; Anderson, William S; Thakor, Nitish V; Crone, Nathan E

    2014-07-01

    To increase the ability of brain-machine interfaces (BMIs) to control advanced prostheses such as the modular prosthetic limb (MPL), we are developing a novel system: the Hybrid Augmented Reality Multimodal Operation Neural Integration Environment (HARMONIE). This system utilizes hybrid input, supervisory control, and intelligent robotics to allow users to identify an object (via eye tracking and computer vision) and initiate (via brain-control) a semi-autonomous reach-grasp-and-drop of the object by the MPL. Sequential iterations of HARMONIE were tested in two pilot subjects implanted with electrocorticographic (ECoG) and depth electrodes within motor areas. The subjects performed the complex task in 71.4% (20/28) and 67.7% (21/31) of trials after minimal training. Balanced accuracy for detecting movements was 91.1% and 92.9%, significantly greater than chance accuracies (p system improvements implemented for the second subject. Our hybrid-BMI design prevented all but one baseline false positive from initiating the system. The novel approach demonstrated in this proof-of-principle study, using hybrid input, supervisory control, and intelligent robotics, addresses limitations of current BMIs.

  3. Zebra tape identification for the instantaneous angular speed computation and angular resampling of motorbike valve train measurements

    Science.gov (United States)

    Rivola, Alessandro; Troncossi, Marco

    2014-02-01

    An experimental test campaign was performed on the valve train of a racing motorbike engine in order to get insight into the dynamic of the system. In particular the valve motion was acquired in cold test conditions by means of a laser vibrometer able to acquire displacement and velocity signals. The valve time-dependent measurements needed to be referred to the camshaft angular position in order to analyse the data in the angular domain, as usually done for rotating machines. To this purpose the camshaft was fitted with a zebra tape whose dark and light stripes were tracked by means of an optical probe. Unfortunately, both manufacturing and mounting imperfections of the employed zebra tape, resulting in stripes with slightly different widths, precluded the possibility to directly obtain the correct relationship between camshaft angular position and time. In order to overcome this problem, the identification of the zebra tape was performed by means of the original and practical procedure that is the focus of the present paper. The method consists of three main steps: namely, an ad-hoc test corresponding to special operating conditions, the computation of the instantaneous angular speed, and the final association of the stripes with the corresponding shaft angular position. The results reported in the paper demonstrate the suitability of the simple procedure for the zebra tape identification performed with the final purpose to implement a computed order tracking technique for the data analysis.

  4. Identification of Provocentrum minimum and Takayama pulchella by fluorescence in situ hybridization through epifluorescence microscopy and flow cytometry

    Institute of Scientific and Technical Information of China (English)

    HOU Jianjun; LAI Hongyan; HUANG Bangqin; CHEN Jixin

    2009-01-01

    Partial rDNA sequences of Prorocentrum minimum and Takayama pulchella were amplified,cloned and sequenced,and these sequence data were deposited in the GenBank.Eight oligonucleotide probes(DNA probes)were designed based on the sequence analysis.The probes were employed to detect and identify P.minimum and T. pulchella in unialgal and mixed algal samples with a fuorescence in situ hybridization method using flow cytometry.Epifluorescence micrographs showed that these specific probes labeled with fluorescein isothiocyanate entered the algal cells and bound to target sequences,and the fluorescence signal resulting from whole-cell hybridization varied from probe to probe.These DNA probes and the hybridization protocol we developed were specific and effective for P.minimum and T. pulchella,without any specific binding to other algal species.The hyrbridization efficiency of difierent probes specific to P.minimum was in the order:PMl8S02>PM28S02>PM28S01>PM18S01,and that of the probes specific to T. pulchella was TP18S02>TP28S01>TP28S02>TP18S01.The djfferent hybridization efficiency of the DNA probes could also be shown in the fuorescent signals between the labeled and unlabeled cells demonstrated using flow cytometry.The DNA probes PM18S02,PM28S02,TPl8S02 and TP28S01,and the protocol,were also useful for the detection of algae in natural samples.

  5. Structure and weights optimisation of a modified Elman network emotion classifier using hybrid computational intelligence algorithms: a comparative study

    Science.gov (United States)

    Sheikhan, Mansour; Abbasnezhad Arabi, Mahdi; Gharavian, Davood

    2015-10-01

    Artificial neural networks are efficient models in pattern recognition applications, but their performance is dependent on employing suitable structure and connection weights. This study used a hybrid method for obtaining the optimal weight set and architecture of a recurrent neural emotion classifier based on gravitational search algorithm (GSA) and its binary version (BGSA), respectively. By considering the features of speech signal that were related to prosody, voice quality, and spectrum, a rich feature set was constructed. To select more efficient features, a fast feature selection method was employed. The performance of the proposed hybrid GSA-BGSA method was compared with similar hybrid methods based on particle swarm optimisation (PSO) algorithm and its binary version, PSO and discrete firefly algorithm, and hybrid of error back-propagation and genetic algorithm that were used for optimisation. Experimental tests on Berlin emotional database demonstrated the superior performance of the proposed method using a lighter network structure.

  6. Identification and characterization of marker chromosomes, de novo rearrangements and microdeletions in 100 cases with fluorescence in situ hybridization (FISH)

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, S.M.; Liu, Y.; Papenhausen, P.R. [Roche Biomedical Labs., Research Triangle Park, NC (United States)

    1994-09-01

    Results of molecular cytogenetic analysis are presented for 100 cases in which fluorescence in situ hybridization (FISH) was used as an adjunct to standard cytogenetics. Commercially available centromeric, telomeric, chromosome painting and unique sequence probes were used. Cases were from a 12-month period (June 1993-May 1994) and included examples of sex chromosome abnormalities (8), duplications (5), de novo translocations (6), satellited (12) and non-satellited (7) markers, and microdeletion syndromes (62). Satellited marker chromosomes were evaluated using a combination of DAPI/Distamycin A staining, hybridization with a classical satellite probe for chromosome 15 and hybridization with alpha-satellite probes for chromosomes 13, 14, 21 and 22. Markers positive for the chromosome 15 probe were further evaluated using unique sequence probes for the Prader-Willi/Angelman region. Microdeletion analysis was performed for Prader-Willi/Angelman (49) and DiGeorge/VCF (13) syndromes. Seven cases evaluated for Prader-Willi/Angelman syndrome demonstrated evidence of a deletion within this region. Uniparental disomy analysis was available in cases where a deletion was not detected by FISH, yet follow-up was clinically indicated. Two cases evaluated for DiGeorge/VCF syndrome demonstrated molecular evidence of a deletion. Included in our analysis is an example of familial DiGeorge syndrome.

  7. Screening and identification of male-specific DNA fragments in common carps Cyprinus carpio using suppression subtractive hybridization.

    Science.gov (United States)

    Chen, J J; Du, Q Y; Yue, Y Y; Dang, B J; Chang, Z J

    2010-08-01

    In this study, a sex subtractive genomic DNA library was constructed using suppression subtractive hybridization (SSH) between male and female Cyprinus carpio. Twenty-two clones with distinguishable hybridization signals were selected and sequenced. The specific primers were designed based on the sequence data. Those primers were then used to amplify the sex-specific fragments from the genomic DNA of male and female carp. The amplified fragments from two clones showed specificity to males but not to females, which were named as Ccmf2 [387 base pairs (bp)] and Ccmf3 (183 bp), respectively. The sex-specific pattern was analysed in a total of 40 individuals from three other different C. carpio. stocks and grass carp Ctenopharyngodon idella using Ccmf2 and Ccmf3 as dot-blotting probes. The results revealed that the molecular diversity exists on the Y chromosome of C. carpio. No hybridization signals, however, were detected from individuals of C. idella, suggesting that the two sequences are specific to C. carpio. No significant homologous sequences of Ccmf2 and Ccmf3 were found in GenBank. Therefore, it was interpreted that the results as that Ccmf2 and Ccmf3 are two novel male-specific sequences; and both fragments could be used as markers to rapidly and accurately identify the genetic sex of part of C. carpio. This may provide a very efficient selective tool for practically breeding monosex female populations in aquacultural production.

  8. Identification and ranking of the risk factors of cloud computing in State-Owned organizations

    Directory of Open Access Journals (Sweden)

    Noor Mohammad Yaghoubi

    2015-05-01

    Full Text Available Rapid development of processing and storage technologies and the success of the Internet have made computing resources cheaper, more powerful and more available than before. This technological trend has enabled the realization of a new computing model called cloud computing. Recently, the State-Owned organizations have begun to utilize cloud computing architectures, platforms, and applications to deliver services and meet constituents’ needs. Despite all of the advantages and opportunities of cloud computing technology, there are so many risks that State-Owned organizations need to know about before their migration to cloud environment. The purpose of this study is to identify and rank the risks factors of cloud computing in State-Owned organizations by making use of IT experts’ opinion. Firstly, by reviewing key articles, a comprehensive list of risks factors were extracted and classified into two categories: tangible and intangible. Then, six experts were interviewed about these risks and their classifications, and 10 risks were identified. After that, process of ranking the risks was done by seeking help from 52 experts and by fuzzy analytic hierarchy process. The results show that experts have identified intangible risks as the most important risks in cloud computing usage by State-Owned organizations. As the results indicate, "data confidentiality" risk has the highest place among the other risks.

  9. IDENTIFICATION OF A TUMOR-MARKER CHROMOSOME BY FLOW SORTING, DNA AMPLIFICATION INVITRO, AND INSITU HYBRIDIZATION OF THE AMPLIFIED PRODUCT

    NARCIS (Netherlands)

    BOSCHMAN, GA; BUYS, CHCM; VANDERVEEN, AY; RENS, W; OSINGA, J; SLATER, RM; ATEN, JA

    1993-01-01

    A method combining flow sorting and molecular cytogenetic techniques for the identification of unknown marker chromosomes is described. In this study, the bladder tumor cell line J82 was used, which was known to carry a marker chromosome of the size of chromosome 7 in every cell. From the cytogeneti

  10. COMPUTATIONALLY INEXPENSIVE SEQUENTIAL FORWARD FLOATING SELECTION FOR ACQUIRING SIGNIFICANT FEATURES FOR AUTHORSHIP INVARIANCENESS IN WRITER IDENTIFICATION

    OpenAIRE

    Satrya Fajri Pratama; Azah Kamilah Muda; Yun-Huoy Choo; and Noor Azilah Muda

    2011-01-01

    Handwriting is individualistic. The uniqueness of shape and style of handwriting can be used to identify the significant features in authenticating the author of writing. Acquiring these significant features leads to an important research in Writer Identification domain where to find the unique features of individual which also known as Individuality of Handwriting. This paper proposes an improved Sequential Forward Floating Selection method besides the exploration of significant features for...

  11. Application of in-situ hybridization for the detection and identification of avian malaria parasites in paraffin wax-embedded tissues from captive penguins.

    Science.gov (United States)

    Dinhopl, Nora; Mostegl, Meike M; Richter, Barbara; Nedorost, Nora; Maderner, Anton; Fragner, Karin; Weissenböck, Herbert

    2011-06-01

    In captive penguins, avian malaria due to Plasmodium parasites is a well-recognized disease problem as these protozoa may cause severe losses among valuable collections of zoo birds. In blood films from naturally infected birds, identification and differentiation of malaria parasites based on morphological criteria are difficult because parasitaemia is frequently light and blood stages, which are necessary for identification of parasites, are often absent. Post-mortem diagnosis by histological examination of tissue samples is sometimes inconclusive due to the difficulties in differentiating protozoal tissue stages from fragmented nuclei in necrotic tissue. The diagnosis of avian malaria would be facilitated by a technique with the ability to specifically identify developmental stages of Plasmodium in tissue samples. Thus, a chromogenic in-situ hybridization (ISH) procedure with a digoxigenin-labelled probe, targeting a fragment of the 18S rRNA, was developed for the detection of Plasmodium parasites in paraffin wax-embedded tissues. This method was validated in comparison with traditional techniques (histology, polymerase chain reaction), on various tissues from 48 captive penguins that died at the zoological garden Schönbrunn, Vienna, Austria. Meronts of Plasmodium gave clear signals and were easily identified using ISH. Potential cross-reactivity of the probe was ruled out by the negative outcome of the ISH against a number of protozoa and fungi. Thus, ISH proved to be a powerful, specific and sensitive tool for unambiguous detection of Plasmodium parasites in paraffin wax-embedded tissue samples.

  12. Construction, implementation and testing of an image identification system using computer vision methods for fruit flies with economic importance (Diptera: Tephritidae).

    Science.gov (United States)

    Wang, Jiang-Ning; Chen, Xiao-Lin; Hou, Xin-Wen; Zhou, Li-Bing; Zhu, Chao-Dong; Ji, Li-Qiang

    2017-07-01

    Many species of Tephritidae are damaging to fruit, which might negatively impact international fruit trade. Automatic or semi-automatic identification of fruit flies are greatly needed for diagnosing causes of damage and quarantine protocols for economically relevant insects. A fruit fly image identification system named AFIS1.0 has been developed using 74 species belonging to six genera, which include the majority of pests in the Tephritidae. The system combines automated image identification and manual verification, balancing operability and accuracy. AFIS1.0 integrates image analysis and expert system into a content-based image retrieval framework. In the the automatic identification module, AFIS1.0 gives candidate identification results. Afterwards users can do manual selection based on comparing unidentified images with a subset of images corresponding to the automatic identification result. The system uses Gabor surface features in automated identification and yielded an overall classification success rate of 87% to the species level by Independent Multi-part Image Automatic Identification Test. The system is useful for users with or without specific expertise on Tephritidae in the task of rapid and effective identification of fruit flies. It makes the application of computer vision technology to fruit fly recognition much closer to production level. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  13. Identification of chromosome aberrations in sporadic microsatellite stable and unstable colorectal cancers using array comparative genomic hybridization

    DEFF Research Database (Denmark)

    Jensen, Thomas Dyrsø; Li, Jian; Wang, Kai;

    2011-01-01

    Colorectal cancer (CRC) is one of the most common cancers in Denmark and in the western world in general, and the prognosis is generally poor. According to the traditional molecular classification of sporadic colorectal cancer, microsatellite stable (MSS)/chromosome unstable (CIN) colorectal...... cancers constitute approximately 85% of sporadic cases, whereas microsatellite unstable (MSI) cases constitute the remaining 15%. In this study, we used array comparative genomic hybridization (aCGH) to identify genomic hotspot regions that harbor recurrent copy number changes. The study material...

  14. 基于Spark的大数据混合计算模型%Big Data Hybrid Computing Mode Based on Spark

    Institute of Scientific and Technical Information of China (English)

    胡俊; 胡贤德; 程家兴

    2015-01-01

    The use of big data in the real world was complicated. It may contain different characteristic of data and computing. In this case, the single computing mode was mostly difficult to met the application requirements. Therefore we need to consider different computing mode of mix use. The ultimate evolution of hybrid computing mode is spark system which invented by UCBerkeley AMPLab. It covers almost all the typical big data computing mode, including iterative computing, batch computing, memory computing, flow computing (Spark Streaming), data query analysis (Shark), and map computing (GraphX). Spark provides a powerful memory computing engine and implents computing with excellent performance, while maintaining compatibility with the Hadoop platform. Therefore, with the continuous stable and mature, Spark is expected to be colocalized with Hadoop and became a new generation of big data processing systems and platforms. The paper has studied and analyed the Spark ecosystem, and set up the hybrid computing model architecture based on Spark platform, which also has illustrated the spark ecosystem can meet the application of hybrid computing model.%现实世界大数据应用复杂多样,可能会同时包含不同特征的数据和计算,在这种情况下单一的计算模式多半难以满足整个应用的需求,因此需要考虑不同计算模式的混搭使用。混合计算模式之集大成者当属UCBerkeley AMPLab的Spark系统,其涵盖了几乎所有典型的大数据计算模式,包括迭代计算、批处理计算、内存计算、流式计算(Spark Streaming)、数据查询分析计算(Shark)、以及图计算(GraphX)。 Spark提供了一个强大的内存计算引擎,实现了优异的计算性能,同时还保持与Hadoop平台的兼容性。因此,随着系统的不断稳定和成熟, Spark有望成为与Hadoop共存的新一代大数据处理系统和平台。本文详细研究和分析了Spark生态系统,建立了基于Spark平台

  15. Low-Bandwidth and Non-Compute Intensive Remote Identification of Microbes from Raw Sequencing Reads

    DEFF Research Database (Denmark)

    Gautier, Laurent; Lund, Ole

    2013-01-01

    Cheap DNA sequencing may soon become routine not only for human genomes but also for practically anything requiring the identification of living organisms from their DNA: tracking of infectious agents, control of food products, bioreactors, or environmental samples. We propose a novel general....... Both are able to handle a large number of sequencing reads and from portable devices (the browser-based running on a tablet), perform its task within seconds, and consume an amount of bandwidth compatible with mobile broadband networks. Such client-server approaches could develop in the future...

  16. On-Board Computing for Structural Health Monitoring with Smart Wireless Sensors by Modal Identification Using Hilbert-Huang Transform

    Directory of Open Access Journals (Sweden)

    Ning Wu

    2013-01-01

    Full Text Available Smart wireless sensors have been recognized as a promising technology to overcome many inherent difficulties and limitations associated with traditional wired structural health monitoring (SHM systems. Despite the advances in smart sensor technologies, on-board computing capability of smart sensors has been considered as one of the most difficult challenges in the application of the smart sensors in SHM. Taking the advantage of recent developments in microprocessor which provides powerful on-board computing functionality for smart sensors, this paper presents a new decentralized data processing approach for modal identification using the Hilbert-Huang transform (HHT algorithm, which is based on signal decomposition technique. It is shown that this method is suitable for implementation in the intrinsically distributed computing environment found in wireless smart sensor networks (WSSNs. The HHT-based decentralized data processing is, then, programmed and implemented on the Crossbow IRIS mote sensor platform. The effectiveness of the proposed techniques is demonstrated through a set of numerical studies and experimental validations on an in-house cable-stayed bridge model in terms of the accuracy of identified dynamic properties.

  17. Computer-aided modeling framework for efficient model development, analysis and identification

    DEFF Research Database (Denmark)

    Heitzig, Martina; Sin, Gürkan; Sales Cruz, Mauricio;

    2011-01-01

    branches; the first branch deals with single-scale model development while the second branch introduces features for multiscale model development to the methodology. In this paper, the emphasis is on single-scale model development and application part. The modeling framework and the supported stepwise......Model-based computer aided product-process engineering has attained increased importance in a number of industries, including pharmaceuticals, petrochemicals, fine chemicals, polymers, biotechnology, food, energy, and water. This trend is set to continue due to the substantial benefits computer......-aided methods introduce. The key prerequisite of computer-aided product-process engineering is however the availability of models of different types, forms, and application modes. The development of the models required for the systems under investigation tends to be a challenging and time-consuming task...

  18. Contrasting molecular and morphological evidence for the identification of an anomalous Buteo: a cautionary tale for hybrid diagnosis

    Directory of Open Access Journals (Sweden)

    William S. Clark

    2017-01-01

    Full Text Available An adult Buteo was found dead as a road-kill south of Sacramento, California, and was thought to represent the first state record of the eastern Red-shouldered Hawk (B. lineatus lineatus;. It is now a specimen in the Museum of Wildlife and Fisheries Biology (WFB 4816 at the University of California, Davis. We examined this specimen and found that many of its plumage characters differed from all other adult Red-shouldered Hawks examined, including nominate adults. Plumage markings and measurements were intermediate between Red-tailed Hawk (Buteo jamaicensis, ssp calurus and Red-shouldered Hawk (ssp elegans, leading us to hypothesize that the bird was a hybrid. However, mtDNA sequences and nuDNA microsatellites proved definitively that the bird was a Red-shouldered Hawk, most likely of eastern origin. This case illustrates that apparent hybrids or apparent vagrants could be individuals with anomalous phenotypes caused by rare genetic variation or novel epigenetic effects.

  19. Identification of differentially expressed genes in lung tissues of nickel-exposed rats using suppression subtractive hybridization.

    Science.gov (United States)

    Zhang, Jing; Zhang, Jun; Fan, Yingying; Liu, Lihong; Li, Mengjie; Zhou, Yang; Shao, Zhihua; Shi, Hongjun; Wang, Ying

    2011-11-01

    Occupational exposure to nickel compound, such as nickel refining, electroplating, and in conjunction with other metals, is harmful to the health, causing respiratory distress, and lung and nasal cancer. In this work, the different gene expression patterns of lung tissues from nickel-exposed rats and controls were investigated. The suppression subtractive hybridization (SSH) method was used to generate two subtracted cDNA libraries with gene transcripts differentially expressed after nickel inducing. Dot-blot hybridizations were used to confirm differential ratios of expression of obtained SSH clones. Out of 768 unique SSH clones, which were chosen randomly from the two subtraction libraries (384 of each), 319 could be verified as differentially expressed. According to blast screening and functional annotation, 28% genes in nickel-induced cDNA library were related to cell differentiation, whereas 21% in driver library were related to oxygen transport. Two novel expressed sequence tags (ESTs; NCBI Accession No. FC809414 and No. FC809411) in nickel-induced cDNA library were obtained. The genes detected in the present study are probably important genes associated with nickel-induced lung cancer.

  20. Identification of rifampin-resistant mycobacterium tuberculosis strains by hybridization, PCR, and ligase detaction reaction on oligonucleotide microchips.

    Energy Technology Data Exchange (ETDEWEB)

    Mikhailovich, V.; Lapa, S.; Gryadunov, D.; Sobolev, A.; Strizhkov, B.; Chernyh, N.; Skotnikova, O.; Irtuganova, O.; Moroz, A.; Litvinov, V.; Vladimirskii, M.; Perelman, M.; Chernousova, L.; Erokhin, V.; Mirzabekov, A.; Biochip Technology Center; Russian Academy of Sciences; Moscow Antituberculosis Center; Moscow Medical Academy; Russian Academy of Medical Sciences

    2001-07-01

    Three new molecular approaches were developed to identify drug-resistant strains of Mycobacterium tuberculosis using biochips with oligonucleotides immobilized in polyacrylamide gel pads. These approaches are significantly faster than traditional bacteriological methods. All three approaches -- hybridization, PCR, and ligase detection reaction -- were designed to analyze an 81-bp fragment of the gene rpoB encoding the {beta}-subunit of RNA polymerase, where most known mutations of rifampin resistance are located. The call set for hybridization analysis consisted of 42 immobilized oligonucleotides and enabled us to identify 30 mutant variants of the rpoB gene within 24 h. These variants are found in 95% of all mutants whose rifampin resistance is caused by mutations in the 81-bp fragment. Using the second approach, allele-specific on-chip PCR, it was possible to directly identify mutations in clinical samples within 1.5 h. The third approach, on-chip ligase detection reaction, was sensitive enough to reveal rifampin-resistant strains in a model mixture containing 1% of resistant and 99% of susceptible bacteria. This level of sensitivity is comparable to that from the determination of M. tuberculosis drug resistance by using standard bacteriological tests.

  1. A Method for Identification of Driving Patterns in Hybrid Electric Vehicles Based on a LVQ Neural Network

    Directory of Open Access Journals (Sweden)

    Xiaowei Zhang

    2012-09-01

    Full Text Available Driving patterns exert an important influence on the fuel economy of vehicles, especially hybrid electric vehicles. This paper aims to build a method to identify driving patterns with enough accuracy and less sampling time compared than other driving pattern recognition algorithms. Firstly a driving pattern identifier based on a Learning Vector Quantization neural network is established to analyze six selected representative standard driving cycles. Micro-trip extraction and Principal Component Analysis methods are applied to ensure the magnitude and diversity of the training samples. Then via Matlab/Simulink, sample training simulation is conducted to determine the minimum neuron number of the Learning Vector Quantization neural network and, as a result, to help simplify the identifier model structure and reduce the data convergence time. Simulation results have proved the feasibility of this method, which decreases the sampling window length from about 250–300 s to 120 s with an acceptable accuracy. The driving pattern identifier is further used in an optimized co-simulation together with a parallel hybrid vehicle model and improves the fuel economy by about 8%.

  2. Some Notes about the Generic Hybridation and the Identification of a Few Enunciative Strategies, through the Generic Categorization of Speech

    Directory of Open Access Journals (Sweden)

    Adán Brand

    2013-02-01

    Full Text Available This paper is situated in the area of Discourse Analysis. It shows, trough a current example, the increasing complexity of moderns discourses, even that some of them cannot be generically classified but as hybrids. Here it is pro posed that this phenomenon answers largely to the mediatization of discoursive samples as the one analyzed; and besides, that the modern production and distribution conditions of the mediated discourses, suggests the need to formulate new genre categories (which implies the proposal to increase the number of classification criteria. In order to prove both, the existence of such hybridation and the need for more specific classifications, the Aristotle’s classification of speech genres and the classificatory criteria of several contemporary authors are applied to the sample selected in this research. This also allows to observe a variety of strategies used by the sample, in order to build the collective identity of an audience without let it feel as an imposition. Among the most important strategies shed in this study, we highlight the complicated game between the emission and reception instances of the speech. This last thing confirms the need to unpack these instances, to distinguish what happens with them inside and outside any discourse.

  3. TPASS: a gamma-ray spectrum analysis and isotope identification computer code

    Energy Technology Data Exchange (ETDEWEB)

    Dickens, J.K.

    1981-03-01

    The gamma-ray spectral data-reduction and analysis computer code TPASS is described. This computer code is used to analyze complex Ge(Li) gamma-ray spectra to obtain peak areas corrected for detector efficiencies, from which are determined gamma-ray yields. These yields are compared with an isotope gamma-ray data file to determine the contributions to the observed spectrum from decay of specific radionuclides. A complete FORTRAN listing of the code and a complex test case are given.

  4. Identification of Chronic Obstructive Pulmonary Disease in Lung Cancer Screening Computed Tomographic Scans

    NARCIS (Netherlands)

    Mets, Onno M.; Buckens, Constantinus F. M.; Zanen, Pieter; Isgum, Ivana; van Ginneken, Bram; Prokop, Mathias; Gietema, Hester A.; Lammers, Jan-Willem J.; Vliegenthart, Rozemarijn; Oudkerk, Matthijs; van Klaveren, Rob J.; de Koning, Harry J.; Mali, Willem P. Th M.; de Jong, Pim A.

    2011-01-01

    Context Smoking is a major risk factor for both cancer and chronic obstructive pulmonary disease (COPD). Computed tomography (CT)-based lung cancer screening may provide an opportunity to detect additional individuals with COPD at an early stage. Objective To determine whether low-dose lung cancer

  5. Identification of chronic obstructive pulmonary disease in lung cancer screening computed tomographic scans

    NARCIS (Netherlands)

    Mets, O.M.; Buckens, C.F.; Zanen, P.; Isgum, I.; Ginneken, B. van; Prokop, M.; Gietema, H.A.; Lammers, J.W.; Vliegenthart, R.; Oudkerk, M.; Klaveren, R.J. van; Koning, H.J. de; Mali, W.P.Th.; Jong, P.A. de

    2011-01-01

    CONTEXT: Smoking is a major risk factor for both cancer and chronic obstructive pulmonary disease (COPD). Computed tomography (CT)-based lung cancer screening may provide an opportunity to detect additional individuals with COPD at an early stage. OBJECTIVE: To determine whether low-dose lung cancer

  6. Computational disease gene identification : a concert of methods prioritizes type 2 diabetes and obesity candidate genes

    NARCIS (Netherlands)

    Tiffin, N.; Adie, E.; Turner, F.; Brunner, H.G.; Driel, M.A. van; Oti, M.O.; Lopez-Bigas, N.; Ouzounis, C.A.; Perez-Iratxeta, C.; Andrade-Navarro, M.A.; Adeyemo, A.; Patti, M.E.; Semple, C.A.; Hide, W.

    2006-01-01

    Genome-wide experimental methods to identify disease genes, such as linkage analysis and association studies, generate increasingly large candidate gene sets for which comprehensive empirical analysis is impractical. Computational methods employ data from a variety of sources to identify the most

  7. Computational disease gene identification: a concert of methods prioritizes type 2 diabetes and obesity candidate genes.

    NARCIS (Netherlands)

    Tiffin, N.; Adie, E.; Turner, F.; Brunner, H.G.; Driel, M.A. van; Oti, M.O.; Lopez-Bigas, N.; Ouzounis, C.A.; Perez-Iratxeta, C.; Andrade-Navarro, M.A.; Adeyemo, A.; Patti, M.E.; Semple, C.A.; Hide, W.

    2006-01-01

    Genome-wide experimental methods to identify disease genes, such as linkage analysis and association studies, generate increasingly large candidate gene sets for which comprehensive empirical analysis is impractical. Computational methods employ data from a variety of sources to identify the most

  8. Computational disease gene identification: a concert of methods prioritizes type 2 diabetes and obesity candidate genes.

    NARCIS (Netherlands)

    Tiffin, N.; Adie, E.; Turner, F.; Brunner, H.G.; Driel, M.A. van; Oti, M.O.; Lopez-Bigas, N.; Ouzounis, C.A.; Perez-Iratxeta, C.; Andrade-Navarro, M.A.; Adeyemo, A.; Patti, M.E.; Semple, C.A.; Hide, W.

    2006-01-01

    Genome-wide experimental methods to identify disease genes, such as linkage analysis and association studies, generate increasingly large candidate gene sets for which comprehensive empirical analysis is impractical. Computational methods employ data from a variety of sources to identify the most li

  9. Computational disease gene identification : a concert of methods prioritizes type 2 diabetes and obesity candidate genes

    NARCIS (Netherlands)

    Tiffin, N.; Adie, E.; Turner, F.; Brunner, H.G.; Driel, M.A. van; Oti, M.O.; Lopez-Bigas, N.; Ouzounis, C.A.; Perez-Iratxeta, C.; Andrade-Navarro, M.A.; Adeyemo, A.; Patti, M.E.; Semple, C.A.; Hide, W.

    2006-01-01

    Genome-wide experimental methods to identify disease genes, such as linkage analysis and association studies, generate increasingly large candidate gene sets for which comprehensive empirical analysis is impractical. Computational methods employ data from a variety of sources to identify the most li

  10. Computer-aided identification of the water diffusion coefficient for maize kernels dried in a thin layer

    Science.gov (United States)

    Kujawa, Sebastian; Weres, Jerzy; Olek, Wiesław

    2016-07-01

    Uncertainties in mathematical modelling of water transport in cereal grain kernels during drying and storage are mainly due to implementing unreliable values of the water diffusion coefficient and simplifying the geometry of kernels. In the present study an attempt was made to reduce the uncertainties by developing a method for computer-aided identification of the water diffusion coefficient and more accurate 3D geometry modelling for individual kernels using original inverse finite element algorithms. The approach was exemplified by identifying the water diffusion coefficient for maize kernels subjected to drying. On the basis of the developed method, values of the water diffusion coefficient were estimated, 3D geometry of a maize kernel was represented by isoparametric finite elements, and the moisture content inside maize kernels dried in a thin layer was predicted. Validation of the results against experimental data showed significantly lower error values than in the case of results obtained for the water diffusion coefficient values available in the literature.

  11. Comparison between ultrasound and noncontrast helical computed tomography for identification of acute ureterolithiasis in a teaching hospital setting

    Directory of Open Access Journals (Sweden)

    Luís Ronan Marquez Ferreira de Souza

    2007-03-01

    Full Text Available CONTEXT AND OBJECTIVE: Recent studies have shown noncontrast computed tomography (NCT to be more effective than ultrasound (US for imaging acute ureterolithiasis. However, to our knowledge, there are few studies directly comparing these techniques in an emergency teaching hospital setting. The objectives of this study were to compare the diagnostic accuracy of US and NCT performed by senior radiology residents for diagnosing acute ureterolithiasis; and to assess interobserver agreement on tomography interpretations by residents and experienced abdominal radiologists. DESIGN AND SETTING: Prospective study of 52 consecutive patients, who underwent both US and NCT within an interval of eight hours, at Hospital São Paulo. METHODS: US scans were performed by senior residents and read by experienced radiologists. NCT scan images were read by senior residents, and subsequently by three abdominal radiologists. The interobserver variability was assessed using the kappa statistic. RESULTS: Ureteral calculi were found in 40 out of 52 patients (77%. US presented sensitivity of 22% and specificity of 100%. When collecting system dilatation was associated, US demonstrated 73% sensitivity, 82% specificity. The interobserver agreement in NCT analysis was very high with regard to identification of calculi, collecting system dilatation and stranding of perinephric fat. CONCLUSIONS: US has limited value for identifying ureteral calculi in comparison with NCT, even when collecting system dilatation is present. Residents and abdominal radiologists demonstrated excellent agreement rates for ureteral calculi, identification of collecting system dilatation and stranding of perinephric fat on NCT.

  12. Identification of immune response-related genes in the Chinese oak silkworm, Antheraea pernyi by suppression subtractive hybridization.

    Science.gov (United States)

    Liu, Qiu-Ning; Zhu, Bao-Jian; Wang, Lei; Wei, Guo-Qing; Dai, Li-Shang; Lin, Kun-Zhang; Sun, Yu; Qiu, Jian-Feng; Fu, Wei-Wei; Liu, Chao-Liang

    2013-11-01

    Insects possess an innate immune system that responds to invading microorganisms. In this study, a subtractive cDNA library was constructed to screen for immune response-related genes in the fat bodies of Antheraea pernyi (Lepidoptera: Saturniidae) pupa challenged with Escherichia coli. Four hundred putative EST clones were identified by suppression subtractive hybridization (SSH), including 50 immune response-related genes, three cytoskeleton genes, eight cell cycle and apoptosis genes, five respiration and energy metabolism genes, five transport genes, 40 metabolism genes, ten stress response genes, four transcription and translation regulation genes and 77 unknown genes. To verify the reliability of the SSH data, the transcription of a set of randomly selected immune response-related genes were confirmed by semi-quantitative reverse transcription-PCR (RT-PCR) and real-time quantitative reverse transcription-PCR (qRT-PCR). These identified immune response-related genes provide insight into understanding the innate immunity in A. pernyi.

  13. Identification of differentially expressed genes in Tetrahymena thermophila in response to dichlorodiphenyltrichloroethane (DDT) by suppression subtractive hybridization.

    Science.gov (United States)

    Miao, Wei; Yu, Ting; Orias, Eduardo; Wan, Mingliang; Fu, Chenjie

    2006-06-01

    The insecticide dichlorodiphenyltrichloroethane (DDT) is persistent in the environment, and continues to cause health problems. Tetrahymena has potential as a model organism for assaying low levels of DDT and for analysing the mechanisms of its toxicity. We constructed the suppression subtractive hybridization library of T. thermophila exposed to DDT, and screened out 90 Expressed Sequence Tags whose expressions were significantly up- or downregulated with DDT treatment. From this, a series of important genes related to the DDT metabolism and detoxification were discovered, such as P450 gene, glutathione S-transferase gene and sterol carrier protein 2 gene. Furthermore, their expressions under different concentrations of DDT treatment were detected by real-time fluorescent quantitative PCR. The results show that Tetrahymena is a relevant and useful model organism for detecting DDT in the environment and for discovering biomarkers that can be used to develop specific bio-reporters at the molecular and genomic levels.

  14. Operational Modal Identification of Time-Varying Structures via a Vector Multistage Recursive Approach in Hybrid Time and Frequency Domain

    Directory of Open Access Journals (Sweden)

    Si-Da Zhou

    2015-01-01

    Full Text Available Real-time estimation of modal parameters of time-varying structures can conduct an obvious contribution to some specific applications in structural dynamic area, such as health monitoring, damage detection, and vibration control; the recursive algorithm of modal parameter estimation supplies one of fundamentals for acquiring modal parameters in real-time. This paper presents a vector multistage recursive method of modal parameter estimation for time-varying structures in hybrid time and frequency domain, including stages of recursive estimation of time-dependent power spectra, frozen-time modal parameter estimation, recursive modal validation, and continuous-time estimation of modal parameters. An experimental example validates the proposed method finally.

  15. A comparative analysis of computational approaches and algorithms for protein subcomplex identification.

    Science.gov (United States)

    Zaki, Nazar; Mora, Antonio

    2014-01-01

    High-throughput AP-MS methods have allowed the identification of many protein complexes. However, most post-processing methods of this type of data have been focused on detection of protein complexes and not its subcomplexes. Here, we review the results of some existing methods that may allow subcomplex detection and propose alternative methods in order to detect subcomplexes from AP-MS data. We assessed and drew comparisons between the use of overlapping clustering methods, methods based in the core-attachment model and our own prediction strategy (TRIBAL). The hypothesis behind TRIBAL is that subcomplex-building information may be concealed in the multiple edges generated by an interaction repeated in different contexts in raw data. The CACHET method offered the best results when the evaluation of the predicted subcomplexes was carried out using both the hypergeometric and geometric scores. TRIBAL offered the best performance when using a strict meet-min score.

  16. Computational Identification of Novel MicroRNAs and Their Targets in Vigna unguiculata.

    Science.gov (United States)

    Lu, Yongzhong; Yang, Xiaoyun

    2010-01-01

    MicroRNAs (miRNAs) are a class of endogenous, noncoding, short RNAs directly involved in regulating gene expression at the posttranscriptional level. High conservation of miRNAs in plant provides the foundation for identification of new miRNAs in other plant species through homology alignment. Here, previous known plant miRNAs were BLASTed against the Expressed Sequence Tag (EST) and Genomic Survey Sequence (GSS) databases of Vigna unguiculata, and according to a series of filtering criteria, a total of 47 miRNAs belonging to 13 miRNA families were identified, and 30 potential target genes of them were subsequently predicted, most of which seemed to encode transcription factors or enzymes participating in regulation of development, growth, metabolism, and other physiological processes. Overall, our findings lay the foundation for further researches of miRNAs function in Vigna unguiculata.

  17. Hybrid propulsion technology program

    Science.gov (United States)

    1990-01-01

    Technology was identified which will enable application of hybrid propulsion to manned and unmanned space launch vehicles. Two design concepts are proposed. The first is a hybrid propulsion system using the classical method of regression (classical hybrid) resulting from the flow of oxidizer across a fuel grain surface. The second system uses a self-sustaining gas generator (gas generator hybrid) to produce a fuel rich exhaust that was mixed with oxidizer in a separate combustor. Both systems offer cost and reliability improvement over the existing solid rocket booster and proposed liquid boosters. The designs were evaluated using life cycle cost and reliability. The program consisted of: (1) identification and evaluation of candidate oxidizers and fuels; (2) preliminary evaluation of booster design concepts; (3) preparation of a detailed point design including life cycle costs and reliability analyses; (4) identification of those hybrid specific technologies needing improvement; and (5) preperation of a technology acquisition plan and large scale demonstration plan.

  18. Computational identification of protein methylation sites through bi-profile Bayes feature extraction.

    Directory of Open Access Journals (Sweden)

    Jianlin Shao

    Full Text Available Protein methylation is one type of reversible post-translational modifications (PTMs, which plays vital roles in many cellular processes such as transcription activity, DNA repair. Experimental identification of methylation sites on proteins without prior knowledge is costly and time-consuming. In silico prediction of methylation sites might not only provide researches with information on the candidate sites for further determination, but also facilitate to perform downstream characterizations and site-specific investigations. In the present study, a novel approach based on Bi-profile Bayes feature extraction combined with support vector machines (SVMs was employed to develop the model for Prediction of Protein Methylation Sites (BPB-PPMS from primary sequence. Methylation can occur at many residues including arginine, lysine, histidine, glutamine, and proline. For the present, BPB-PPMS is only designed to predict the methylation status for lysine and arginine residues on polypeptides due to the absence of enough experimentally verified data to build and train prediction models for other residues. The performance of BPB-PPMS is measured with a sensitivity of 74.71%, a specificity of 94.32% and an accuracy of 87.98% for arginine as well as a sensitivity of 70.05%, a specificity of 77.08% and an accuracy of 75.51% for lysine in 5-fold cross validation experiments. Results obtained from cross-validation experiments and test on independent data sets suggest that BPB-PPMS presented here might facilitate the identification and annotation of protein methylation. Besides, BPB-PPMS can be extended to build predictors for other types of PTM sites with ease. For public access, BPB-PPMS is available at http://www.bioinfo.bio.cuhk.edu.hk/bpbppms.

  19. Identification of strain fields in pure Al and hybrid Ni/Al metal foams using X-ray micro-tomography under loading

    Science.gov (United States)

    Fíla, T.; Jiroušek, O.; Jung, A.; Kumpová, I.

    2016-11-01

    Hybrid foams are materials formed by a core from a standard open cell metal foam that is during the process of electrodeposition coated by a thin layer of different nanocrystalline metals. The material properties of the base metal foam are in this way modified resulting in higher plateau stress and, more importantly, by introduction of strain-rate dependence to its deformation response. In this paper, we used time-lapse X-ray micro-tomography for the mechanical characterization of Ni/Al hybrid foams (aluminium open cell foams with nickel coating layer). To fully understand the effects of the coating layer on the material's effective properties, we compared the compressive response of the base uncoated foam to the response of the material with coating thickness of 50 and 75 μm. Digital volume correlation (DVC) was applied to obtain volumetric strain fields of the deforming micro-structure up to the densification region of the deforming cellular structure. The analysis was performed as a compressive mechanical test with simultaneous observation using X-ray radiography and tomography. A custom design experimental device was used for compression of the foam specimens in several deformation states directly in the X-ray setup. Planar X-ray images were taken during the loading phases and a X-ray tomography was performed at the end of each loading phase (up to engineering strain 22%). The samples were irradiated using micro-focus reflection type X-ray tube and images were taken using a large area flat panel detector. Tomography reconstructions were used for an identification of a strain distribution in the foam using digital volumetric correlation. A comparison of the deformation response of the coated and the uncoated foam in uniaxial quasi-static compression is summarized in the paper.

  20. Identification of nitrite-reducing bacteria using sequential mRNA fluorescence in situ hybridization and fluorescence-assisted cell sorting.

    Science.gov (United States)

    Mota, Cesar R; So, Mark Jason; de los Reyes, Francis L

    2012-07-01

    Sequential mRNA fluorescence in situ hybridization (mRNA FISH) and fluorescence-assisted cell sorting (SmRFF) was used for the identification of nitrite-reducing bacteria in mixed microbial communities. An oligonucleotide probe labeled with horseradish peroxidase (HRP) was used to target mRNA of nirS, the gene that encodes nitrite reductase, the enzyme responsible for the dissimilatory reduction of nitrite to nitric oxide. Clones for nirS expression were constructed and used to provide proof of concept for the SmRFF method. In addition, cells from pure cultures of Pseudomonas stutzeri and denitrifying activated sludge were hybridized with the HRP probe, and tyramide signal amplification was performed, conferring a strongly fluorescent signal to cells containing nirS mRNA. Flow cytometry-assisted cell sorting was used to detect and physically separate two subgroups from a mixed microbial community: non-fluorescent cells and an enrichment of fluorescent, nitrite-reducing cells. Denaturing gradient gel electrophoresis (DGGE) and subsequent sequencing of 16S ribosomal RNA (rRNA) genes were used to compare the fragments amplified from the two sorted subgroups. Sequences from bands isolated from DGGE profiles suggested that the dominant, active nitrite reducers were closely related to Acidovorax BSB421. Furthermore, following mRNA FISH detection of nitrite-reducing bacteria, 16S rRNA FISH was used to detect ammonia-oxidizing and nitrite-oxidizing bacteria on the same activated sludge sample. We believe that the molecular approach described can be useful as a tool to help address the longstanding challenge of linking function to identity in natural and engineered habitats.