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Sample records for pattern differentiation algorithm

  1. Differential harmony search algorithm to optimize PWRs loading pattern

    Energy Technology Data Exchange (ETDEWEB)

    Poursalehi, N., E-mail: npsalehi@yahoo.com [Engineering Department, Shahid Beheshti University, G.C, P.O.Box: 1983963113, Tehran (Iran, Islamic Republic of); Zolfaghari, A.; Minuchehr, A. [Engineering Department, Shahid Beheshti University, G.C, P.O.Box: 1983963113, Tehran (Iran, Islamic Republic of)

    2013-04-15

    Highlights: ► Exploit of DHS algorithm in LP optimization reveals its flexibility, robustness and reliability. ► Upshot of our experiments with DHS shows that the search approach to optimal LP is quickly. ► On the average, the final band width of DHS fitness values is narrow relative to HS and GHS. -- Abstract: The objective of this work is to develop a core loading optimization technique using differential harmony search algorithm in the context of obtaining an optimal configuration of fuel assemblies in pressurized water reactors. To implement and evaluate the proposed technique, differential harmony search nodal expansion package for 2-D geometry, DHSNEP-2D, is developed. The package includes two modules; in the first modules differential harmony search (DHS) is implemented and nodal expansion code which solves two dimensional-multi group neutron diffusion equations using fourth degree flux expansion with one node per a fuel assembly is in the second module. For evaluation of DHS algorithm, classical harmony search (HS) and global-best harmony search (GHS) algorithms are also included in DHSNEP-2D in order to compare the outcome of techniques together. For this purpose, two PWR test cases have been investigated to demonstrate the DHS algorithm capability in obtaining near optimal loading pattern. Results show that the convergence rate of DHS and execution times are quite promising and also is reliable for the fuel management operation. Moreover, numerical results show the good performance of DHS relative to other competitive algorithms such as genetic algorithm (GA), classical harmony search (HS) and global-best harmony search (GHS) algorithms.

  2. Differential harmony search algorithm to optimize PWRs loading pattern

    International Nuclear Information System (INIS)

    Poursalehi, N.; Zolfaghari, A.; Minuchehr, A.

    2013-01-01

    Highlights: ► Exploit of DHS algorithm in LP optimization reveals its flexibility, robustness and reliability. ► Upshot of our experiments with DHS shows that the search approach to optimal LP is quickly. ► On the average, the final band width of DHS fitness values is narrow relative to HS and GHS. -- Abstract: The objective of this work is to develop a core loading optimization technique using differential harmony search algorithm in the context of obtaining an optimal configuration of fuel assemblies in pressurized water reactors. To implement and evaluate the proposed technique, differential harmony search nodal expansion package for 2-D geometry, DHSNEP-2D, is developed. The package includes two modules; in the first modules differential harmony search (DHS) is implemented and nodal expansion code which solves two dimensional-multi group neutron diffusion equations using fourth degree flux expansion with one node per a fuel assembly is in the second module. For evaluation of DHS algorithm, classical harmony search (HS) and global-best harmony search (GHS) algorithms are also included in DHSNEP-2D in order to compare the outcome of techniques together. For this purpose, two PWR test cases have been investigated to demonstrate the DHS algorithm capability in obtaining near optimal loading pattern. Results show that the convergence rate of DHS and execution times are quite promising and also is reliable for the fuel management operation. Moreover, numerical results show the good performance of DHS relative to other competitive algorithms such as genetic algorithm (GA), classical harmony search (HS) and global-best harmony search (GHS) algorithms

  3. Composite Differential Search Algorithm

    Directory of Open Access Journals (Sweden)

    Bo Liu

    2014-01-01

    Full Text Available Differential search algorithm (DS is a relatively new evolutionary algorithm inspired by the Brownian-like random-walk movement which is used by an organism to migrate. It has been verified to be more effective than ABC, JDE, JADE, SADE, EPSDE, GSA, PSO2011, and CMA-ES. In this paper, we propose four improved solution search algorithms, namely “DS/rand/1,” “DS/rand/2,” “DS/current to rand/1,” and “DS/current to rand/2” to search the new space and enhance the convergence rate for the global optimization problem. In order to verify the performance of different solution search methods, 23 benchmark functions are employed. Experimental results indicate that the proposed algorithm performs better than, or at least comparable to, the original algorithm when considering the quality of the solution obtained. However, these schemes cannot still achieve the best solution for all functions. In order to further enhance the convergence rate and the diversity of the algorithm, a composite differential search algorithm (CDS is proposed in this paper. This new algorithm combines three new proposed search schemes including “DS/rand/1,” “DS/rand/2,” and “DS/current to rand/1” with three control parameters using a random method to generate the offspring. Experiment results show that CDS has a faster convergence rate and better search ability based on the 23 benchmark functions.

  4. Parallel Algorithms and Patterns

    Energy Technology Data Exchange (ETDEWEB)

    Robey, Robert W. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-06-16

    This is a powerpoint presentation on parallel algorithms and patterns. A parallel algorithm is a well-defined, step-by-step computational procedure that emphasizes concurrency to solve a problem. Examples of problems include: Sorting, searching, optimization, matrix operations. A parallel pattern is a computational step in a sequence of independent, potentially concurrent operations that occurs in diverse scenarios with some frequency. Examples are: Reductions, prefix scans, ghost cell updates. We only touch on parallel patterns in this presentation. It really deserves its own detailed discussion which Gabe Rockefeller would like to develop.

  5. Automatic differentiation algorithms in model analysis

    NARCIS (Netherlands)

    Huiskes, M.J.

    2002-01-01

    Title: Automatic differentiation algorithms in model analysis
    Author: M.J. Huiskes
    Date: 19 March, 2002

    In this thesis automatic differentiation algorithms and derivative-based methods

  6. Parallel Algorithm Solves Coupled Differential Equations

    Science.gov (United States)

    Hayashi, A.

    1987-01-01

    Numerical methods adapted to concurrent processing. Algorithm solves set of coupled partial differential equations by numerical integration. Adapted to run on hypercube computer, algorithm separates problem into smaller problems solved concurrently. Increase in computing speed with concurrent processing over that achievable with conventional sequential processing appreciable, especially for large problems.

  7. Algorithms For Integrating Nonlinear Differential Equations

    Science.gov (United States)

    Freed, A. D.; Walker, K. P.

    1994-01-01

    Improved algorithms developed for use in numerical integration of systems of nonhomogenous, nonlinear, first-order, ordinary differential equations. In comparison with integration algorithms, these algorithms offer greater stability and accuracy. Several asymptotically correct, thereby enabling retention of stability and accuracy when large increments of independent variable used. Accuracies attainable demonstrated by applying them to systems of nonlinear, first-order, differential equations that arise in study of viscoplastic behavior, spread of acquired immune-deficiency syndrome (AIDS) virus and predator/prey populations.

  8. Frequent Pattern Mining Algorithms for Data Clustering

    DEFF Research Database (Denmark)

    Zimek, Arthur; Assent, Ira; Vreeken, Jilles

    2014-01-01

    that frequent pattern mining was at the cradle of subspace clustering—yet, it quickly developed into an independent research field. In this chapter, we discuss how frequent pattern mining algorithms have been extended and generalized towards the discovery of local clusters in high-dimensional data......Discovering clusters in subspaces, or subspace clustering and related clustering paradigms, is a research field where we find many frequent pattern mining related influences. In fact, as the first algorithms for subspace clustering were based on frequent pattern mining algorithms, it is fair to say....... In particular, we discuss several example algorithms for subspace clustering or projected clustering as well as point out recent research questions and open topics in this area relevant to researchers in either clustering or pattern mining...

  9. Exponentially Convergent Algorithms for Abstract Differential Equations

    CERN Document Server

    Gavrilyuk, Ivan; Vasylyk, Vitalii

    2011-01-01

    This book presents new accurate and efficient exponentially convergent methods for abstract differential equations with unbounded operator coefficients in Banach space. These methods are highly relevant for the practical scientific computing since the equations under consideration can be seen as the meta-models of systems of ordinary differential equations (ODE) as well as the partial differential equations (PDEs) describing various applied problems. The framework of functional analysis allows one to obtain very general but at the same time transparent algorithms and mathematical results which

  10. Modelling Evolutionary Algorithms with Stochastic Differential Equations.

    Science.gov (United States)

    Heredia, Jorge Pérez

    2017-11-20

    There has been renewed interest in modelling the behaviour of evolutionary algorithms (EAs) by more traditional mathematical objects, such as ordinary differential equations or Markov chains. The advantage is that the analysis becomes greatly facilitated due to the existence of well established methods. However, this typically comes at the cost of disregarding information about the process. Here, we introduce the use of stochastic differential equations (SDEs) for the study of EAs. SDEs can produce simple analytical results for the dynamics of stochastic processes, unlike Markov chains which can produce rigorous but unwieldy expressions about the dynamics. On the other hand, unlike ordinary differential equations (ODEs), they do not discard information about the stochasticity of the process. We show that these are especially suitable for the analysis of fixed budget scenarios and present analogues of the additive and multiplicative drift theorems from runtime analysis. In addition, we derive a new more general multiplicative drift theorem that also covers non-elitist EAs. This theorem simultaneously allows for positive and negative results, providing information on the algorithm's progress even when the problem cannot be optimised efficiently. Finally, we provide results for some well-known heuristics namely Random Walk (RW), Random Local Search (RLS), the (1+1) EA, the Metropolis Algorithm (MA), and the Strong Selection Weak Mutation (SSWM) algorithm.

  11. Genetic algorithms in loading pattern optimization

    International Nuclear Information System (INIS)

    Yilmazbayhan, A.; Tombakoglu, M.; Bekar, K. B.; Erdemli, A. Oe

    2001-01-01

    Genetic Algorithm (GA) based systems are used for the loading pattern optimization. The use of Genetic Algorithm operators such as regional crossover, crossover and mutation, and selection of initial population size for PWRs are discussed. Antithetic variates are used to generate the initial population. The performance of GA with antithetic variates is compared to traditional GA. The results of multi-cycle optimization are discussed for objective function taking into account cycle burn-up and discharge burn-up

  12. Solving Partial Differential Equations Using a New Differential Evolution Algorithm

    Directory of Open Access Journals (Sweden)

    Natee Panagant

    2014-01-01

    Full Text Available This paper proposes an alternative meshless approach to solve partial differential equations (PDEs. With a global approximate function being defined, a partial differential equation problem is converted into an optimisation problem with equality constraints from PDE boundary conditions. An evolutionary algorithm (EA is employed to search for the optimum solution. For this approach, the most difficult task is the low convergence rate of EA which consequently results in poor PDE solution approximation. However, its attractiveness remains due to the nature of a soft computing technique in EA. The algorithm can be used to tackle almost any kind of optimisation problem with simple evolutionary operation, which means it is mathematically simpler to use. A new efficient differential evolution (DE is presented and used to solve a number of the partial differential equations. The results obtained are illustrated and compared with exact solutions. It is shown that the proposed method has a potential to be a future meshless tool provided that the search performance of EA is greatly enhanced.

  13. Algorithms for adaptive nonlinear pattern recognition

    Science.gov (United States)

    Schmalz, Mark S.; Ritter, Gerhard X.; Hayden, Eric; Key, Gary

    2011-09-01

    In Bayesian pattern recognition research, static classifiers have featured prominently in the literature. A static classifier is essentially based on a static model of input statistics, thereby assuming input ergodicity that is not realistic in practice. Classical Bayesian approaches attempt to circumvent the limitations of static classifiers, which can include brittleness and narrow coverage, by training extensively on a data set that is assumed to cover more than the subtense of expected input. Such assumptions are not realistic for more complex pattern classification tasks, for example, object detection using pattern classification applied to the output of computer vision filters. In contrast, we have developed a two step process, that can render the majority of static classifiers adaptive, such that the tracking of input nonergodicities is supported. Firstly, we developed operations that dynamically insert (or resp. delete) training patterns into (resp. from) the classifier's pattern database, without requiring that the classifier's internal representation of its training database be completely recomputed. Secondly, we developed and applied a pattern replacement algorithm that uses the aforementioned pattern insertion/deletion operations. This algorithm is designed to optimize the pattern database for a given set of performance measures, thereby supporting closed-loop, performance-directed optimization. This paper presents theory and algorithmic approaches for the efficient computation of adaptive linear and nonlinear pattern recognition operators that use our pattern insertion/deletion technology - in particular, tabular nearest-neighbor encoding (TNE) and lattice associative memories (LAMs). Of particular interest is the classification of nonergodic datastreams that have noise corruption with time-varying statistics. The TNE and LAM based classifiers discussed herein have been successfully applied to the computation of object classification in hyperspectral

  14. An algorithm of computing inhomogeneous differential equations for definite integrals

    OpenAIRE

    Nakayama, Hiromasa; Nishiyama, Kenta

    2010-01-01

    We give an algorithm to compute inhomogeneous differential equations for definite integrals with parameters. The algorithm is based on the integration algorithm for $D$-modules by Oaku. Main tool in the algorithm is the Gr\\"obner basis method in the ring of differential operators.

  15. Loading pattern optimization using ant colony algorithm

    International Nuclear Information System (INIS)

    Hoareau, Fabrice

    2008-01-01

    Electricite de France (EDF) operates 58 nuclear power plants (NPP), of the Pressurized Water Reactor type. The loading pattern optimization of these NPP is currently done by EDF expert engineers. Within this framework, EDF R and D has developed automatic optimization tools that assist the experts. LOOP is an industrial tool, developed by EDF R and D and based on a simulated annealing algorithm. In order to improve the results of such automatic tools, new optimization methods have to be tested. Ant Colony Optimization (ACO) algorithms are recent methods that have given very good results on combinatorial optimization problems. In order to evaluate the performance of such methods on loading pattern optimization, direct comparisons between LOOP and a mock-up based on the Max-Min Ant System algorithm (a particular variant of ACO algorithms) were made on realistic test-cases. It is shown that the results obtained by the ACO mock-up are very similar to those of LOOP. Future research will consist in improving these encouraging results by using parallelization and by hybridizing the ACO algorithm with local search procedures. (author)

  16. Algorithmic Verification of Linearizability for Ordinary Differential Equations

    KAUST Repository

    Lyakhov, Dmitry A.; Gerdt, Vladimir P.; Michels, Dominik L.

    2017-01-01

    one by a point transformation of the dependent and independent variables. The first algorithm is based on a construction of the Lie point symmetry algebra and on the computation of its derived algebra. The second algorithm exploits the differential

  17. A Unified Differential Evolution Algorithm for Global Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Qiang, Ji; Mitchell, Chad

    2014-06-24

    Abstract?In this paper, we propose a new unified differential evolution (uDE) algorithm for single objective global optimization. Instead of selecting among multiple mutation strategies as in the conventional differential evolution algorithm, this algorithm employs a single equation as the mutation strategy. It has the virtue of mathematical simplicity and also provides users the flexbility for broader exploration of different mutation strategies. Numerical tests using twelve basic unimodal and multimodal functions show promising performance of the proposed algorithm in comparison to convential differential evolution algorithms.

  18. Galois theory and algorithms for linear differential equations

    NARCIS (Netherlands)

    Put, Marius van der

    2005-01-01

    This paper is an informal introduction to differential Galois theory. It surveys recent work on differential Galois groups, related algorithms and some applications. (c) 2005 Elsevier Ltd. All rights reserved.

  19. GPU-accelerated adjoint algorithmic differentiation

    Science.gov (United States)

    Gremse, Felix; Höfter, Andreas; Razik, Lukas; Kiessling, Fabian; Naumann, Uwe

    2016-03-01

    Many scientific problems such as classifier training or medical image reconstruction can be expressed as minimization of differentiable real-valued cost functions and solved with iterative gradient-based methods. Adjoint algorithmic differentiation (AAD) enables automated computation of gradients of such cost functions implemented as computer programs. To backpropagate adjoint derivatives, excessive memory is potentially required to store the intermediate partial derivatives on a dedicated data structure, referred to as the ;tape;. Parallelization is difficult because threads need to synchronize their accesses during taping and backpropagation. This situation is aggravated for many-core architectures, such as Graphics Processing Units (GPUs), because of the large number of light-weight threads and the limited memory size in general as well as per thread. We show how these limitations can be mediated if the cost function is expressed using GPU-accelerated vector and matrix operations which are recognized as intrinsic functions by our AAD software. We compare this approach with naive and vectorized implementations for CPUs. We use four increasingly complex cost functions to evaluate the performance with respect to memory consumption and gradient computation times. Using vectorization, CPU and GPU memory consumption could be substantially reduced compared to the naive reference implementation, in some cases even by an order of complexity. The vectorization allowed usage of optimized parallel libraries during forward and reverse passes which resulted in high speedups for the vectorized CPU version compared to the naive reference implementation. The GPU version achieved an additional speedup of 7.5 ± 4.4, showing that the processing power of GPUs can be utilized for AAD using this concept. Furthermore, we show how this software can be systematically extended for more complex problems such as nonlinear absorption reconstruction for fluorescence-mediated tomography.

  20. Solving SAT Problem Based on Hybrid Differential Evolution Algorithm

    Science.gov (United States)

    Liu, Kunqi; Zhang, Jingmin; Liu, Gang; Kang, Lishan

    Satisfiability (SAT) problem is an NP-complete problem. Based on the analysis about it, SAT problem is translated equally into an optimization problem on the minimum of objective function. A hybrid differential evolution algorithm is proposed to solve the Satisfiability problem. It makes full use of strong local search capacity of hill-climbing algorithm and strong global search capability of differential evolution algorithm, which makes up their disadvantages, improves the efficiency of algorithm and avoids the stagnation phenomenon. The experiment results show that the hybrid algorithm is efficient in solving SAT problem.

  1. An Adaptive Unified Differential Evolution Algorithm for Global Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Qiang, Ji; Mitchell, Chad

    2014-11-03

    In this paper, we propose a new adaptive unified differential evolution algorithm for single-objective global optimization. Instead of the multiple mutation strate- gies proposed in conventional differential evolution algorithms, this algorithm employs a single equation unifying multiple strategies into one expression. It has the virtue of mathematical simplicity and also provides users the flexibility for broader exploration of the space of mutation operators. By making all control parameters in the proposed algorithm self-adaptively evolve during the process of optimization, it frees the application users from the burden of choosing appro- priate control parameters and also improves the performance of the algorithm. In numerical tests using thirteen basic unimodal and multimodal functions, the proposed adaptive unified algorithm shows promising performance in compari- son to several conventional differential evolution algorithms.

  2. Pattern Nulling of Linear Antenna Arrays Using Backtracking Search Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Kerim Guney

    2015-01-01

    Full Text Available An evolutionary method based on backtracking search optimization algorithm (BSA is proposed for linear antenna array pattern synthesis with prescribed nulls at interference directions. Pattern nulling is obtained by controlling only the amplitude, position, and phase of the antenna array elements. BSA is an innovative metaheuristic technique based on an iterative process. Various numerical examples of linear array patterns with the prescribed single, multiple, and wide nulls are given to illustrate the performance and flexibility of BSA. The results obtained by BSA are compared with the results of the following seventeen algorithms: particle swarm optimization (PSO, genetic algorithm (GA, modified touring ant colony algorithm (MTACO, quadratic programming method (QPM, bacterial foraging algorithm (BFA, bees algorithm (BA, clonal selection algorithm (CLONALG, plant growth simulation algorithm (PGSA, tabu search algorithm (TSA, memetic algorithm (MA, nondominated sorting GA-2 (NSGA-2, multiobjective differential evolution (MODE, decomposition with differential evolution (MOEA/D-DE, comprehensive learning PSO (CLPSO, harmony search algorithm (HSA, seeker optimization algorithm (SOA, and mean variance mapping optimization (MVMO. The simulation results show that the linear antenna array synthesis using BSA provides low side-lobe levels and deep null levels.

  3. Filter Pattern Search Algorithms for Mixed Variable Constrained Optimization Problems

    National Research Council Canada - National Science Library

    Abramson, Mark A; Audet, Charles; Dennis, Jr, J. E

    2004-01-01

    .... This class combines and extends the Audet-Dennis Generalized Pattern Search (GPS) algorithms for bound constrained mixed variable optimization, and their GPS-filter algorithms for general nonlinear constraints...

  4. Algorithmic Verification of Linearizability for Ordinary Differential Equations

    KAUST Repository

    Lyakhov, Dmitry A.

    2017-07-19

    For a nonlinear ordinary differential equation solved with respect to the highest order derivative and rational in the other derivatives and in the independent variable, we devise two algorithms to check if the equation can be reduced to a linear one by a point transformation of the dependent and independent variables. The first algorithm is based on a construction of the Lie point symmetry algebra and on the computation of its derived algebra. The second algorithm exploits the differential Thomas decomposition and allows not only to test the linearizability, but also to generate a system of nonlinear partial differential equations that determines the point transformation and the coefficients of the linearized equation. The implementation of both algorithms is discussed and their application is illustrated using several examples.

  5. A new taxonomy of sublinear keyword pattern matching algorithms

    NARCIS (Netherlands)

    Cleophas, L.G.W.A.; Watson, B.W.; Zwaan, G.

    2004-01-01

    Abstract This paper presents a new taxonomy of sublinear (multiple) keyword pattern matching algorithms. Based on an earlier taxonomy by Watson and Zwaan [WZ96, WZ95], this new taxonomy includes not only suffix-based algorithms related to the Boyer-Moore, Commentz-Walter and Fan-Su algorithms, but

  6. Low dose reconstruction algorithm for differential phase contrast imaging.

    Science.gov (United States)

    Wang, Zhentian; Huang, Zhifeng; Zhang, Li; Chen, Zhiqiang; Kang, Kejun; Yin, Hongxia; Wang, Zhenchang; Marco, Stampanoni

    2011-01-01

    Differential phase contrast imaging computed tomography (DPCI-CT) is a novel x-ray inspection method to reconstruct the distribution of refraction index rather than the attenuation coefficient in weakly absorbing samples. In this paper, we propose an iterative reconstruction algorithm for DPCI-CT which benefits from the new compressed sensing theory. We first realize a differential algebraic reconstruction technique (DART) by discretizing the projection process of the differential phase contrast imaging into a linear partial derivative matrix. In this way the compressed sensing reconstruction problem of DPCI reconstruction can be transformed to a resolved problem in the transmission imaging CT. Our algorithm has the potential to reconstruct the refraction index distribution of the sample from highly undersampled projection data. Thus it can significantly reduce the dose and inspection time. The proposed algorithm has been validated by numerical simulations and actual experiments.

  7. A Hybrid Backtracking Search Optimization Algorithm with Differential Evolution

    Directory of Open Access Journals (Sweden)

    Lijin Wang

    2015-01-01

    Full Text Available The backtracking search optimization algorithm (BSA is a new nature-inspired method which possesses a memory to take advantage of experiences gained from previous generation to guide the population to the global optimum. BSA is capable of solving multimodal problems, but it slowly converges and poorly exploits solution. The differential evolution (DE algorithm is a robust evolutionary algorithm and has a fast convergence speed in the case of exploitive mutation strategies that utilize the information of the best solution found so far. In this paper, we propose a hybrid backtracking search optimization algorithm with differential evolution, called HBD. In HBD, DE with exploitive strategy is used to accelerate the convergence by optimizing one worse individual according to its probability at each iteration process. A suit of 28 benchmark functions are employed to verify the performance of HBD, and the results show the improvement in effectiveness and efficiency of hybridization of BSA and DE.

  8. An algorithm, implementation and execution ontology design pattern

    NARCIS (Netherlands)

    Lawrynowicz, A.; Esteves, D.; Panov, P.; Soru, T.; Dzeroski, S.; Vanschoren, J.

    2016-01-01

    This paper describes an ontology design pattern for modeling algorithms, their implementations and executions. This pattern is derived from the research results on data mining/machine learning ontologies, but is more generic. We argue that the proposed pattern will foster the development of

  9. Application of a genetic algorithm to core reload pattern optimization

    International Nuclear Information System (INIS)

    Tanker, E.; Tanker, A.Z.

    1994-01-01

    A genetic algorithm is applied to reload pattern optimization of a PWR core. Evaluating all different distributions of a given batch load separately is found slow and ineffective. Allowing patterns from different distributions to combine reproduce, an optimized pattern better than that obtained from from linear programming is found, albeit in a longer time. (authors). 5 refs., 2 tabs

  10. A DIFFERENTIAL EVOLUTION ALGORITHM DEVELOPED FOR A NURSE SCHEDULING PROBLEM

    Directory of Open Access Journals (Sweden)

    Shahnazari-Shahrezaei, P.

    2012-11-01

    Full Text Available Nurse scheduling is a type of manpower allocation problem that tries to satisfy hospital managers objectives and nurses preferences as much as possible by generating fair shift schedules. This paper presents a nurse scheduling problem based on a real case study, and proposes two meta-heuristics a differential evolution algorithm (DE and a greedy randomised adaptive search procedure (GRASP to solve it. To investigate the efficiency of the proposed algorithms, two problems are solved. Furthermore, some comparison metrics are applied to examine the reliability of the proposed algorithms. The computational results in this paper show that the proposed DE outperforms the GRASP.

  11. DNA pattern recognition using canonical correlation algorithm.

    Science.gov (United States)

    Sarkar, B K; Chakraborty, Chiranjib

    2015-10-01

    We performed canonical correlation analysis as an unsupervised statistical tool to describe related views of the same semantic object for identifying patterns. A pattern recognition technique based on canonical correlation analysis (CCA) was proposed for finding required genetic code in the DNA sequence. Two related but different objects were considered: one was a particular pattern, and other was test DNA sequence. CCA found correlations between two observations of the same semantic pattern and test sequence. It is concluded that the relationship possesses maximum value in the position where the pattern exists. As a case study, the potential of CCA was demonstrated on the sequence found from HIV-1 preferred integration sites. The subsequences on the left and right flanking from the integration site were considered as the two views, and statistically significant relationships were established between these two views to elucidate the viral preference as an important factor for the correlation.

  12. A Self Adaptive Differential Evolution Algorithm for Global Optimization

    Science.gov (United States)

    Kumar, Pravesh; Pant, Millie

    This paper presents a new Differential Evolution algorithm based on hybridization of adaptive control parameters and trigonometric mutation. First we propose a self adaptive DE named ADE where choice of control parameter F and Cr is not fixed at some constant value but is taken iteratively. The proposed algorithm is further modified by applying trigonometric mutation in it and the corresponding algorithm is named as ATDE. The performance of ATDE is evaluated on the set of 8 benchmark functions and the results are compared with the classical DE algorithm in terms of average fitness function value, number of function evaluations, convergence time and success rate. The numerical result shows the competence of the proposed algorithm.

  13. Star pattern recognition algorithm aided by inertial information

    Science.gov (United States)

    Liu, Bao; Wang, Ke-dong; Zhang, Chao

    2011-08-01

    Star pattern recognition is one of the key problems of the celestial navigation. The traditional star pattern recognition approaches, such as the triangle algorithm and the star angular distance algorithm, are a kind of all-sky matching method whose recognition speed is slow and recognition success rate is not high. Therefore, the real time and reliability of CNS (Celestial Navigation System) is reduced to some extent, especially for the maneuvering spacecraft. However, if the direction of the camera optical axis can be estimated by other navigation systems such as INS (Inertial Navigation System), the star pattern recognition can be fulfilled in the vicinity of the estimated direction of the optical axis. The benefits of the INS-aided star pattern recognition algorithm include at least the improved matching speed and the improved success rate. In this paper, the direction of the camera optical axis, the local matching sky, and the projection of stars on the image plane are estimated by the aiding of INS firstly. Then, the local star catalog for the star pattern recognition is established in real time dynamically. The star images extracted in the camera plane are matched in the local sky. Compared to the traditional all-sky star pattern recognition algorithms, the memory of storing the star catalog is reduced significantly. Finally, the INS-aided star pattern recognition algorithm is validated by simulations. The results of simulations show that the algorithm's computation time is reduced sharply and its matching success rate is improved greatly.

  14. Real parameter optimization by an effective differential evolution algorithm

    Directory of Open Access Journals (Sweden)

    Ali Wagdy Mohamed

    2013-03-01

    Full Text Available This paper introduces an Effective Differential Evolution (EDE algorithm for solving real parameter optimization problems over continuous domain. The proposed algorithm proposes a new mutation rule based on the best and the worst individuals among the entire population of a particular generation. The mutation rule is combined with the basic mutation strategy through a linear decreasing probability rule. The proposed mutation rule is shown to promote local search capability of the basic DE and to make it faster. Furthermore, a random mutation scheme and a modified Breeder Genetic Algorithm (BGA mutation scheme are merged to avoid stagnation and/or premature convergence. Additionally, the scaling factor and crossover of DE are introduced as uniform random numbers to enrich the search behavior and to enhance the diversity of the population. The effectiveness and benefits of the proposed modifications used in EDE has been experimentally investigated. Numerical experiments on a set of bound-constrained problems have shown that the new approach is efficient, effective and robust. The comparison results between the EDE and several classical differential evolution methods and state-of-the-art parameter adaptive differential evolution variants indicate that the proposed EDE algorithm is competitive with , and in some cases superior to, other algorithms in terms of final solution quality, efficiency, convergence rate, and robustness.

  15. High-order quantum algorithm for solving linear differential equations

    International Nuclear Information System (INIS)

    Berry, Dominic W

    2014-01-01

    Linear differential equations are ubiquitous in science and engineering. Quantum computers can simulate quantum systems, which are described by a restricted type of linear differential equations. Here we extend quantum simulation algorithms to general inhomogeneous sparse linear differential equations, which describe many classical physical systems. We examine the use of high-order methods (where the error over a time step is a high power of the size of the time step) to improve the efficiency. These provide scaling close to Δt 2 in the evolution time Δt. As with other algorithms of this type, the solution is encoded in amplitudes of the quantum state, and it is possible to extract global features of the solution. (paper)

  16. Optimization Shape of Variable Capacitance Micromotor Using Differential Evolution Algorithm

    Directory of Open Access Journals (Sweden)

    A. Ketabi

    2010-01-01

    Full Text Available A new method for optimum shape design of variable capacitance micromotor (VCM using Differential Evolution (DE, a stochastic search algorithm, is presented. In this optimization exercise, the objective function aims to maximize torque value and minimize the torque ripple, where the geometric parameters are considered to be the variables. The optimization process is carried out using a combination of DE algorithm and FEM analysis. Fitness value is calculated by FEM analysis using COMSOL3.4, and the DE algorithm is realized by MATLAB7.4. The proposed method is applied to a VCM with 8 poles at the stator and 6 poles at the rotor. The results show that the optimized micromotor using DE algorithm had higher torque value and lower torque ripple, indicating the validity of this methodology for VCM design.

  17. AC-600 reactor reloading pattern optimization by using genetic algorithms

    International Nuclear Information System (INIS)

    Wu Hongchun; Xie Zhongsheng; Yao Dong; Li Dongsheng; Zhang Zongyao

    2000-01-01

    The use of genetic algorithms to optimize reloading pattern of the nuclear power plant reactor is proposed. And a new encoding and translating method is given. Optimization results of minimizing core power peak and maximizing cycle length for both low-leakage and out-in loading pattern of AC-600 reactor are obtained

  18. Research on parallel algorithm for sequential pattern mining

    Science.gov (United States)

    Zhou, Lijuan; Qin, Bai; Wang, Yu; Hao, Zhongxiao

    2008-03-01

    Sequential pattern mining is the mining of frequent sequences related to time or other orders from the sequence database. Its initial motivation is to discover the laws of customer purchasing in a time section by finding the frequent sequences. In recent years, sequential pattern mining has become an important direction of data mining, and its application field has not been confined to the business database and has extended to new data sources such as Web and advanced science fields such as DNA analysis. The data of sequential pattern mining has characteristics as follows: mass data amount and distributed storage. Most existing sequential pattern mining algorithms haven't considered the above-mentioned characteristics synthetically. According to the traits mentioned above and combining the parallel theory, this paper puts forward a new distributed parallel algorithm SPP(Sequential Pattern Parallel). The algorithm abides by the principal of pattern reduction and utilizes the divide-and-conquer strategy for parallelization. The first parallel task is to construct frequent item sets applying frequent concept and search space partition theory and the second task is to structure frequent sequences using the depth-first search method at each processor. The algorithm only needs to access the database twice and doesn't generate the candidated sequences, which abates the access time and improves the mining efficiency. Based on the random data generation procedure and different information structure designed, this paper simulated the SPP algorithm in a concrete parallel environment and implemented the AprioriAll algorithm. The experiments demonstrate that compared with AprioriAll, the SPP algorithm had excellent speedup factor and efficiency.

  19. Parameter Estimation of Damped Compound Pendulum Differential Evolution Algorithm

    Directory of Open Access Journals (Sweden)

    Saad Mohd Sazli

    2016-01-01

    Full Text Available This paper present the parameter identification of damped compound pendulum using differential evolution algorithm. The procedure used to achieve the parameter identification of the experimental system consisted of input output data collection, ARX model order selection and parameter estimation using conventional method least square (LS and differential evolution (DE algorithm. PRBS signal is used to be input signal to regulate the motor speed. Whereas, the output signal is taken from position sensor. Both, input and output data is used to estimate the parameter of the ARX model. The residual error between the actual and predicted output responses of the models is validated using mean squares error (MSE. Analysis showed that, MSE value for LS is 0.0026 and MSE value for DE is 3.6601×10-5. Based results obtained, it was found that DE have lower MSE than the LS method.

  20. Improved Differential Evolution Algorithm for Wireless Sensor Network Coverage Optimization

    Directory of Open Access Journals (Sweden)

    Xing Xu

    2014-04-01

    Full Text Available In order to serve for the ecological monitoring efficiency of Poyang Lake, an improved hybrid algorithm, mixed with differential evolution and particle swarm optimization, is proposed and applied to optimize the coverage problem of wireless sensor network. And then, the affect of the population size and the number of iterations on the coverage performance are both discussed and analyzed. The four kinds of statistical results about the coverage rate are obtained through lots of simulation experiments.

  1. Structure-preserving algorithms for oscillatory differential equations II

    CERN Document Server

    Wu, Xinyuan; Shi, Wei

    2015-01-01

    This book describes a variety of highly effective and efficient structure-preserving algorithms for second-order oscillatory differential equations. Such systems arise in many branches of science and engineering, and the examples in the book include systems from quantum physics, celestial mechanics and electronics. To accurately simulate the true behavior of such systems, a numerical algorithm must preserve as much as possible their key structural properties: time-reversibility, oscillation, symplecticity, and energy and momentum conservation. The book describes novel advances in RKN methods, ERKN methods, Filon-type asymptotic methods, AVF methods, and trigonometric Fourier collocation methods.  The accuracy and efficiency of each of these algorithms are tested via careful numerical simulations, and their structure-preserving properties are rigorously established by theoretical analysis. The book also gives insights into the practical implementation of the methods. This book is intended for engineers and sc...

  2. Differential Evolution Algorithm with Self-Adaptive Population Resizing Mechanism

    Directory of Open Access Journals (Sweden)

    Xu Wang

    2013-01-01

    Full Text Available A differential evolution (DE algorithm with self-adaptive population resizing mechanism, SapsDE, is proposed to enhance the performance of DE by dynamically choosing one of two mutation strategies and tuning control parameters in a self-adaptive manner. More specifically, more appropriate mutation strategies along with its parameter settings can be determined adaptively according to the previous status at different stages of the evolution process. To verify the performance of SapsDE, 17 benchmark functions with a wide range of dimensions, and diverse complexities are used. Nonparametric statistical procedures were performed for multiple comparisons between the proposed algorithm and five well-known DE variants from the literature. Simulation results show that SapsDE is effective and efficient. It also exhibits much more superiorresultsthan the other five algorithms employed in the comparison in most of the cases.

  3. Differential Evolution algorithm applied to FSW model calibration

    Science.gov (United States)

    Idagawa, H. S.; Santos, T. F. A.; Ramirez, A. J.

    2014-03-01

    Friction Stir Welding (FSW) is a solid state welding process that can be modelled using a Computational Fluid Dynamics (CFD) approach. These models use adjustable parameters to control the heat transfer and the heat input to the weld. These parameters are used to calibrate the model and they are generally determined using the conventional trial and error approach. Since this method is not very efficient, we used the Differential Evolution (DE) algorithm to successfully determine these parameters. In order to improve the success rate and to reduce the computational cost of the method, this work studied different characteristics of the DE algorithm, such as the evolution strategy, the objective function, the mutation scaling factor and the crossover rate. The DE algorithm was tested using a friction stir weld performed on a UNS S32205 Duplex Stainless Steel.

  4. Calibration of three-axis magnetometers with differential evolution algorithm

    International Nuclear Information System (INIS)

    Pang, Hongfeng; Zhang, Qi; Wang, Wei; Wang, Junya; Li, Ji; Luo, Shitu; Wan, Chengbiao; Chen, Dixiang; Pan, Mengchun; Luo, Feilu

    2013-01-01

    The accuracy of three-axis magnetometers is influenced by different scale and bias of each axis and nonorthogonality between axes. One limitation of traditional iteration methods is that initial parameters influence the calibration, thus leading to the local optimal or wrong results. In this paper, a new method is proposed to calibrate three-axis magnetometers. To employ this method, a nonmagnetic rotation platform, a proton magnetometer, a DM-050 three-axis magnetometer and the differential evolution (DE) algorithm are used. The performance of this calibration method is analyzed with simulation and experiment. In simulation, the calibration results of DE, unscented Kalman filter (UKF), recursive least squares (RLS) and genetic algorithm (GA) are compared. RMS error using DE is least, which is reduced from 81.233 nT to 1.567 nT. Experimental results show that comparing with UKF, RLS and GA, the DE algorithm has not only the least calibration error but also the best robustness. After calibration, RMS error is reduced from 68.914 nT to 2.919 nT. In addition, the DE algorithm is not sensitive to initial parameters, which is an important advantage compared with traditional iteration algorithms. The proposed algorithm can avoid the troublesome procedure to select suitable initial parameters, thus it can improve the calibration performance of three-axis magnetometers. - Highlights: • The calibration results and robustness of UKF, GA, RLS and DE algorithm are analyzed. • Calibration error of DE is the least in simulation and experiment. • Comparing with traditional calibration algorithms, DE is not sensitive to initial parameters. • It can improve the calibration performance of three-axis magnetometers

  5. Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm

    OpenAIRE

    Zeng, Yong; Liu, Dacheng; Lei, Zhou

    2014-01-01

    The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE). First, HFPE algorithm seeks similar indications from the history si...

  6. Algorithmic differentiation of pragma-defined parallel regions differentiating computer programs containing OpenMP

    CERN Document Server

    Förster, Michael

    2014-01-01

    Numerical programs often use parallel programming techniques such as OpenMP to compute the program's output values as efficient as possible. In addition, derivative values of these output values with respect to certain input values play a crucial role. To achieve code that computes not only the output values simultaneously but also the derivative values, this work introduces several source-to-source transformation rules. These rules are based on a technique called algorithmic differentiation. The main focus of this work lies on the important reverse mode of algorithmic differentiation. The inh

  7. Ripple/Carcinoid pattern sebaceoma with apocrine differentiation.

    Science.gov (United States)

    Misago, Noriyuki; Narisawa, Yutaka

    2011-02-01

    Sebaceoma is a benign sebaceous neoplasm, which has been reported to show characteristic growth patterns, such as, ripple, labyrinthine/sinusoidal, and carcinoid-like patterns. Another recent finding regarding in sebaceoma is the observation of apocrine differentiation within the sebaceoma lesion. This report describes a case of carcinoid (a partial ripple and labyrinthine) pattern sebaceoma with apocrine differentiation with a literature review and immunohistochemical studies. The various characteristic growth patterns in sebaceoma were suggested to simply be variations of the same growth pattern arranged in cords, namely, a unified term "ripple/carcinoid pattern." The primitive sebaceous germinative cells in sebaceoma may still have the ability to undergo apocrine differentiation. Most of the reports so far on sebaceoma with apocrine differentiation, including the present case, describe a ripple/carcinoid pattern, thus suggesting that ripple/carcinoid pattern sebaceoma is composed of more primitive sebaceous germinative cells than conventional sebaceoma.

  8. Assessment of the information content of patterns: an algorithm

    Science.gov (United States)

    Daemi, M. Farhang; Beurle, R. L.

    1991-12-01

    A preliminary investigation confirmed the possibility of assessing the translational and rotational information content of simple artificial images. The calculation is tedious, and for more realistic patterns it is essential to implement the method on a computer. This paper describes an algorithm developed for this purpose which confirms the results of the preliminary investigation. Use of the algorithm facilitates much more comprehensive analysis of the combined effect of continuous rotation and fine translation, and paves the way for analysis of more realistic patterns. Owing to the volume of calculation involved in these algorithms, extensive computing facilities were necessary. The major part of the work was carried out using an ICL 3900 series mainframe computer as well as other powerful workstations such as a RISC architecture MIPS machine.

  9. Synthesis of Steered Flat-top Beam Pattern Using Evolutionary Algorithm

    Directory of Open Access Journals (Sweden)

    D. Mandal

    2016-12-01

    Full Text Available In this paper a pattern synthesis method based on Evolutionary Algorithm is presented. A Flat-top beam pattern has been generated from a concentric ring array of isotropic elements by finding out the optimum set of elements amplitudes and phases using Differential Evolution algorithm. The said pattern is generated in three predefined azimuth planes instate of a single phi plane and also verified for a range of azimuth plane for the same optimum excitations. The main beam is steered to an elevation angle of 30 degree with lower peak SLL and ripple. Dynamic range ratio (DRR is also being improved by eliminating the weakly excited array elements, which simplify the design complexity of feed networks.

  10. Research reactor loading pattern optimization using estimation of distribution algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, S. [Dept. of Earth Science and Engineering, Applied Modeling and Computation Group AMCG, Imperial College, London, SW7 2AZ (United Kingdom); Ziver, K. [Dept. of Earth Science and Engineering, Applied Modeling and Computation Group AMCG, Imperial College, London, SW7 2AZ (United Kingdom); AMCG Group, RM Consultants, Abingdon (United Kingdom); Carter, J. N.; Pain, C. C.; Eaton, M. D.; Goddard, A. J. H. [Dept. of Earth Science and Engineering, Applied Modeling and Computation Group AMCG, Imperial College, London, SW7 2AZ (United Kingdom); Franklin, S. J.; Phillips, H. J. [Imperial College, Reactor Centre, Silwood Park, Buckhurst Road, Ascot, Berkshire, SL5 7TE (United Kingdom)

    2006-07-01

    A new evolutionary search based approach for solving the nuclear reactor loading pattern optimization problems is presented based on the Estimation of Distribution Algorithms. The optimization technique developed is then applied to the maximization of the effective multiplication factor (K{sub eff}) of the Imperial College CONSORT research reactor (the last remaining civilian research reactor in the United Kingdom). A new elitism-guided searching strategy has been developed and applied to improve the local convergence together with some problem-dependent information based on the 'stand-alone K{sub eff} with fuel coupling calculations. A comparison study between the EDAs and a Genetic Algorithm with Heuristic Tie Breaking Crossover operator has shown that the new algorithm is efficient and robust. (authors)

  11. Research reactor loading pattern optimization using estimation of distribution algorithms

    International Nuclear Information System (INIS)

    Jiang, S.; Ziver, K.; Carter, J. N.; Pain, C. C.; Eaton, M. D.; Goddard, A. J. H.; Franklin, S. J.; Phillips, H. J.

    2006-01-01

    A new evolutionary search based approach for solving the nuclear reactor loading pattern optimization problems is presented based on the Estimation of Distribution Algorithms. The optimization technique developed is then applied to the maximization of the effective multiplication factor (K eff ) of the Imperial College CONSORT research reactor (the last remaining civilian research reactor in the United Kingdom). A new elitism-guided searching strategy has been developed and applied to improve the local convergence together with some problem-dependent information based on the 'stand-alone K eff with fuel coupling calculations. A comparison study between the EDAs and a Genetic Algorithm with Heuristic Tie Breaking Crossover operator has shown that the new algorithm is efficient and robust. (authors)

  12. Application of differential evolution algorithm on self-potential data.

    Science.gov (United States)

    Li, Xiangtao; Yin, Minghao

    2012-01-01

    Differential evolution (DE) is a population based evolutionary algorithm widely used for solving multidimensional global optimization problems over continuous spaces, and has been successfully used to solve several kinds of problems. In this paper, differential evolution is used for quantitative interpretation of self-potential data in geophysics. Six parameters are estimated including the electrical dipole moment, the depth of the source, the distance from the origin, the polarization angle and the regional coefficients. This study considers three kinds of data from Turkey: noise-free data, contaminated synthetic data, and Field example. The differential evolution and the corresponding model parameters are constructed as regards the number of the generations. Then, we show the vibration of the parameters at the vicinity of the low misfit area. Moreover, we show how the frequency distribution of each parameter is related to the number of the DE iteration. Experimental results show the DE can be used for solving the quantitative interpretation of self-potential data efficiently compared with previous methods.

  13. Application of differential evolution algorithm on self-potential data.

    Directory of Open Access Journals (Sweden)

    Xiangtao Li

    Full Text Available Differential evolution (DE is a population based evolutionary algorithm widely used for solving multidimensional global optimization problems over continuous spaces, and has been successfully used to solve several kinds of problems. In this paper, differential evolution is used for quantitative interpretation of self-potential data in geophysics. Six parameters are estimated including the electrical dipole moment, the depth of the source, the distance from the origin, the polarization angle and the regional coefficients. This study considers three kinds of data from Turkey: noise-free data, contaminated synthetic data, and Field example. The differential evolution and the corresponding model parameters are constructed as regards the number of the generations. Then, we show the vibration of the parameters at the vicinity of the low misfit area. Moreover, we show how the frequency distribution of each parameter is related to the number of the DE iteration. Experimental results show the DE can be used for solving the quantitative interpretation of self-potential data efficiently compared with previous methods.

  14. New Collaborative Filtering Algorithms Based on SVD++ and Differential Privacy

    Directory of Open Access Journals (Sweden)

    Zhengzheng Xian

    2017-01-01

    Full Text Available Collaborative filtering technology has been widely used in the recommender system, and its implementation is supported by the large amount of real and reliable user data from the big-data era. However, with the increase of the users’ information-security awareness, these data are reduced or the quality of the data becomes worse. Singular Value Decomposition (SVD is one of the common matrix factorization methods used in collaborative filtering, which introduces the bias information of users and items and is realized by using algebraic feature extraction. The derivative model SVD++ of SVD achieves better predictive accuracy due to the addition of implicit feedback information. Differential privacy is defined very strictly and can be proved, which has become an effective measure to solve the problem of attackers indirectly deducing the personal privacy information by using background knowledge. In this paper, differential privacy is applied to the SVD++ model through three approaches: gradient perturbation, objective-function perturbation, and output perturbation. Through theoretical derivation and experimental verification, the new algorithms proposed can better protect the privacy of the original data on the basis of ensuring the predictive accuracy. In addition, an effective scheme is given that can measure the privacy protection strength and predictive accuracy, and a reasonable range for selection of the differential privacy parameter is provided.

  15. Historical feature pattern extraction based network attack situation sensing algorithm.

    Science.gov (United States)

    Zeng, Yong; Liu, Dacheng; Lei, Zhou

    2014-01-01

    The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE). First, HFPE algorithm seeks similar indications from the history situation sequence recorded and weighs the link intensity between occurred indication and subsequent effect. Then it calculates the probability that a certain effect reappears according to the current indication and makes a prediction after weighting. Meanwhile, HFPE method gives an evolution algorithm to derive the prediction deviation from the views of pattern and accuracy. This algorithm can continuously promote the adaptability of HFPE through gradual fine-tuning. The method preserves the rules in sequence at its best, does not need data preprocessing, and can track and adapt to the variation of situation sequence continuously.

  16. Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm

    Directory of Open Access Journals (Sweden)

    Yong Zeng

    2014-01-01

    Full Text Available The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE. First, HFPE algorithm seeks similar indications from the history situation sequence recorded and weighs the link intensity between occurred indication and subsequent effect. Then it calculates the probability that a certain effect reappears according to the current indication and makes a prediction after weighting. Meanwhile, HFPE method gives an evolution algorithm to derive the prediction deviation from the views of pattern and accuracy. This algorithm can continuously promote the adaptability of HFPE through gradual fine-tuning. The method preserves the rules in sequence at its best, does not need data preprocessing, and can track and adapt to the variation of situation sequence continuously.

  17. PWR loading pattern optimization using Harmony Search algorithm

    International Nuclear Information System (INIS)

    Poursalehi, N.; Zolfaghari, A.; Minuchehr, A.

    2013-01-01

    Highlights: ► Numerical results reveal that the HS method is reliable. ► The great advantage of HS is significant gain in computational cost. ► On the average, the final band width of search fitness values is narrow. ► Our experiments show that the search approaches the optimal value fast. - Abstract: In this paper a core reloading technique using Harmony Search, HS, is presented in the context of finding an optimal configuration of fuel assemblies, FA, in pressurized water reactors. To implement and evaluate the proposed technique a Harmony Search along Nodal Expansion Code for 2-D geometry, HSNEC2D, is developed to obtain nearly optimal arrangement of fuel assemblies in PWR cores. This code consists of two sections including Harmony Search algorithm and Nodal Expansion modules using fourth degree flux expansion which solves two dimensional-multi group diffusion equations with one node per fuel assembly. Two optimization test problems are investigated to demonstrate the HS algorithm capability in converging to near optimal loading pattern in the fuel management field and other subjects. Results, convergence rate and reliability of the method are quite promising and show the HS algorithm performs very well and is comparable to other competitive algorithms such as Genetic Algorithm and Particle Swarm Intelligence. Furthermore, implementation of nodal expansion technique along HS causes considerable reduction of computational time to process and analysis optimization in the core fuel management problems

  18. Algebraic dynamics solutions and algebraic dynamics algorithm for nonlinear ordinary differential equations

    Institute of Scientific and Technical Information of China (English)

    WANG; Shunjin; ZHANG; Hua

    2006-01-01

    The problem of preserving fidelity in numerical computation of nonlinear ordinary differential equations is studied in terms of preserving local differential structure and approximating global integration structure of the dynamical system.The ordinary differential equations are lifted to the corresponding partial differential equations in the framework of algebraic dynamics,and a new algorithm-algebraic dynamics algorithm is proposed based on the exact analytical solutions of the ordinary differential equations by the algebraic dynamics method.In the new algorithm,the time evolution of the ordinary differential system is described locally by the time translation operator and globally by the time evolution operator.The exact analytical piece-like solution of the ordinary differential equations is expressd in terms of Taylor series with a local convergent radius,and its finite order truncation leads to the new numerical algorithm with a controllable precision better than Runge Kutta Algorithm and Symplectic Geometric Algorithm.

  19. An optimized algorithm for detecting and annotating regional differential methylation.

    Science.gov (United States)

    Li, Sheng; Garrett-Bakelman, Francine E; Akalin, Altuna; Zumbo, Paul; Levine, Ross; To, Bik L; Lewis, Ian D; Brown, Anna L; D'Andrea, Richard J; Melnick, Ari; Mason, Christopher E

    2013-01-01

    DNA methylation profiling reveals important differentially methylated regions (DMRs) of the genome that are altered during development or that are perturbed by disease. To date, few programs exist for regional analysis of enriched or whole-genome bisulfate conversion sequencing data, even though such data are increasingly common. Here, we describe an open-source, optimized method for determining empirically based DMRs (eDMR) from high-throughput sequence data that is applicable to enriched whole-genome methylation profiling datasets, as well as other globally enriched epigenetic modification data. Here we show that our bimodal distribution model and weighted cost function for optimized regional methylation analysis provides accurate boundaries of regions harboring significant epigenetic modifications. Our algorithm takes the spatial distribution of CpGs into account for the enrichment assay, allowing for optimization of the definition of empirical regions for differential methylation. Combined with the dependent adjustment for regional p-value combination and DMR annotation, we provide a method that may be applied to a variety of datasets for rapid DMR analysis. Our method classifies both the directionality of DMRs and their genome-wide distribution, and we have observed that shows clinical relevance through correct stratification of two Acute Myeloid Leukemia (AML) tumor sub-types. Our weighted optimization algorithm eDMR for calling DMRs extends an established DMR R pipeline (methylKit) and provides a needed resource in epigenomics. Our method enables an accurate and scalable way of finding DMRs in high-throughput methylation sequencing experiments. eDMR is available for download at http://code.google.com/p/edmr/.

  20. Differential evolution and simulated annealing algorithms for mechanical systems design

    Directory of Open Access Journals (Sweden)

    H. Saruhan

    2014-09-01

    Full Text Available In this study, nature inspired algorithms – the Differential Evolution (DE and the Simulated Annealing (SA – are utilized to seek a global optimum solution for ball bearings link system assembly weight with constraints and mixed design variables. The Genetic Algorithm (GA and the Evolution Strategy (ES will be a reference for the examination and validation of the DE and the SA. The main purpose is to minimize the weight of an assembly system composed of a shaft and two ball bearings. Ball bearings link system is used extensively in many machinery applications. Among mechanical systems, designers pay great attention to the ball bearings link system because of its significant industrial importance. The problem is complex and a time consuming process due to mixed design variables and inequality constraints imposed on the objective function. The results showed that the DE and the SA performed and obtained convergence reliability on the global optimum solution. So the contribution of the DE and the SA application to the mechanical system design can be very useful in many real-world mechanical system design problems. Beside, the comparison confirms the effectiveness and the superiority of the DE over the others algorithms – the SA, the GA, and the ES – in terms of solution quality. The ball bearings link system assembly weight of 634,099 gr was obtained using the DE while 671,616 gr, 728213.8 gr, and 729445.5 gr were obtained using the SA, the ES, and the GA respectively.

  1. Corroboration of mechanoregulatory algorithms for tissue differentiation during fracture healing: comparison with in vivo results

    NARCIS (Netherlands)

    Isaksson, H.E.; Donkelaar, van C.C.; Huiskes, R.; Ito, K.

    2006-01-01

    Several mechanoregulation algorithms proposed to control tissue differentiation during bone healing have been shown to accurately predict temporal and spatial tissue distributions during normal fracture healing. As these algorithms are different in nature and biophysical parameters, it raises the

  2. Perturbation of convex risk minimization and its application in differential private learning algorithms

    Directory of Open Access Journals (Sweden)

    Weilin Nie

    2017-01-01

    Full Text Available Abstract Convex risk minimization is a commonly used setting in learning theory. In this paper, we firstly give a perturbation analysis for such algorithms, and then we apply this result to differential private learning algorithms. Our analysis needs the objective functions to be strongly convex. This leads to an extension of our previous analysis to the non-differentiable loss functions, when constructing differential private algorithms. Finally, an error analysis is then provided to show the selection for the parameters.

  3. Parareal algorithms with local time-integrators for time fractional differential equations

    Science.gov (United States)

    Wu, Shu-Lin; Zhou, Tao

    2018-04-01

    It is challenge work to design parareal algorithms for time-fractional differential equations due to the historical effect of the fractional operator. A direct extension of the classical parareal method to such equations will lead to unbalance computational time in each process. In this work, we present an efficient parareal iteration scheme to overcome this issue, by adopting two recently developed local time-integrators for time fractional operators. In both approaches, one introduces auxiliary variables to localized the fractional operator. To this end, we propose a new strategy to perform the coarse grid correction so that the auxiliary variables and the solution variable are corrected separately in a mixed pattern. It is shown that the proposed parareal algorithm admits robust rate of convergence. Numerical examples are presented to support our conclusions.

  4. Fringe pattern analysis for optical metrology theory, algorithms, and applications

    CERN Document Server

    Servin, Manuel; Padilla, Moises

    2014-01-01

    The main objective of this book is to present the basic theoretical principles and practical applications for the classical interferometric techniques and the most advanced methods in the field of modern fringe pattern analysis applied to optical metrology. A major novelty of this work is the presentation of a unified theoretical framework based on the Fourier description of phase shifting interferometry using the Frequency Transfer Function (FTF) along with the theory of Stochastic Process for the straightforward analysis and synthesis of phase shifting algorithms with desired properties such

  5. Continuous firefly algorithm applied to PWR core pattern enhancement

    Energy Technology Data Exchange (ETDEWEB)

    Poursalehi, N., E-mail: npsalehi@yahoo.com [Engineering Department, Shahid Beheshti University, G.C., P.O. Box 1983963113, Tehran (Iran, Islamic Republic of); Zolfaghari, A.; Minuchehr, A.; Moghaddam, H.K. [Engineering Department, Shahid Beheshti University, G.C., P.O. Box 1983963113, Tehran (Iran, Islamic Republic of)

    2013-05-15

    Highlights: ► Numerical results indicate the reliability of CFA for the nuclear reactor LPO. ► The major advantages of CFA are its light computational cost and fast convergence. ► Our experiments demonstrate the ability of CFA to obtain the near optimal loading pattern. -- Abstract: In this research, the new meta-heuristic optimization strategy, firefly algorithm, is developed for the nuclear reactor loading pattern optimization problem. Two main goals in reactor core fuel management optimization are maximizing the core multiplication factor (K{sub eff}) in order to extract the maximum cycle energy and minimizing the power peaking factor due to safety constraints. In this work, we define a multi-objective fitness function according to above goals for the core fuel arrangement enhancement. In order to evaluate and demonstrate the ability of continuous firefly algorithm (CFA) to find the near optimal loading pattern, we developed CFA nodal expansion code (CFANEC) for the fuel management operation. This code consists of two main modules including CFA optimization program and a developed core analysis code implementing nodal expansion method to calculate with coarse meshes by dimensions of fuel assemblies. At first, CFA is applied for the Foxholes test case with continuous variables in order to validate CFA and then for KWU PWR using a decoding strategy for discrete variables. Results indicate the efficiency and relatively fast convergence of CFA in obtaining near optimal loading pattern with respect to considered fitness function. At last, our experience with the CFA confirms that the CFA is easy to implement and reliable.

  6. Continuous firefly algorithm applied to PWR core pattern enhancement

    International Nuclear Information System (INIS)

    Poursalehi, N.; Zolfaghari, A.; Minuchehr, A.; Moghaddam, H.K.

    2013-01-01

    Highlights: ► Numerical results indicate the reliability of CFA for the nuclear reactor LPO. ► The major advantages of CFA are its light computational cost and fast convergence. ► Our experiments demonstrate the ability of CFA to obtain the near optimal loading pattern. -- Abstract: In this research, the new meta-heuristic optimization strategy, firefly algorithm, is developed for the nuclear reactor loading pattern optimization problem. Two main goals in reactor core fuel management optimization are maximizing the core multiplication factor (K eff ) in order to extract the maximum cycle energy and minimizing the power peaking factor due to safety constraints. In this work, we define a multi-objective fitness function according to above goals for the core fuel arrangement enhancement. In order to evaluate and demonstrate the ability of continuous firefly algorithm (CFA) to find the near optimal loading pattern, we developed CFA nodal expansion code (CFANEC) for the fuel management operation. This code consists of two main modules including CFA optimization program and a developed core analysis code implementing nodal expansion method to calculate with coarse meshes by dimensions of fuel assemblies. At first, CFA is applied for the Foxholes test case with continuous variables in order to validate CFA and then for KWU PWR using a decoding strategy for discrete variables. Results indicate the efficiency and relatively fast convergence of CFA in obtaining near optimal loading pattern with respect to considered fitness function. At last, our experience with the CFA confirms that the CFA is easy to implement and reliable

  7. Estimating Traffic Accidents in Turkey Using Differential Evolution Algorithm

    Science.gov (United States)

    Akgüngör, Ali Payıdar; Korkmaz, Ersin

    2017-06-01

    Estimating traffic accidents play a vital role to apply road safety procedures. This study proposes Differential Evolution Algorithm (DEA) models to estimate the number of accidents in Turkey. In the model development, population (P) and the number of vehicles (N) are selected as model parameters. Three model forms, linear, exponential and semi-quadratic models, are developed using DEA with the data covering from 2000 to 2014. Developed models are statistically compared to select the best fit model. The results of the DE models show that the linear model form is suitable to estimate the number of accidents. The statistics of this form is better than other forms in terms of performance criteria which are the Mean Absolute Percentage Errors (MAPE) and the Root Mean Square Errors (RMSE). To investigate the performance of linear DE model for future estimations, a ten-year period from 2015 to 2024 is considered. The results obtained from future estimations reveal the suitability of DE method for road safety applications.

  8. Optimizing Fukushima Emissions Through Pattern Matching and Genetic Algorithms

    Science.gov (United States)

    Lucas, D. D.; Simpson, M. D.; Philip, C. S.; Baskett, R.

    2017-12-01

    Hazardous conditions during the Fukushima Daiichi nuclear power plant (NPP) accident hindered direct observations of the emissions of radioactive materials into the atmosphere. A wide range of emissions are estimated from bottom-up studies using reactor inventories and top-down approaches based on inverse modeling. We present a new inverse modeling estimate of cesium-137 emitted from the Fukushima NPP. Our estimate considers weather uncertainty through a large ensemble of Weather Research and Forecasting model simulations and uses the FLEXPART atmospheric dispersion model to transport and deposit cesium. The simulations are constrained by observations of the spatial distribution of cumulative cesium deposited on the surface of Japan through April 2, 2012. Multiple spatial metrics are used to quantify differences between observed and simulated deposition patterns. In order to match the observed pattern, we use a multi-objective genetic algorithm to optimize the time-varying emissions. We find that large differences with published bottom-up estimates are required to explain the observations. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  9. Differential and coherent processing patterns from small RNAs

    DEFF Research Database (Denmark)

    Pundhir, Sachin; Gorodkin, Jan

    2015-01-01

    Post-transcriptional processing events related to short RNAs are often reflected in their read profile patterns emerging from high-throughput sequencing data. MicroRNA arm switching across different tissues is a well-known example of what we define as differential processing. Here, short RNAs from...

  10. The Monte Carlo method as a tool for statistical characterisation of differential and additive phase shifting algorithms

    International Nuclear Information System (INIS)

    Miranda, M; Dorrio, B V; Blanco, J; Diz-Bugarin, J; Ribas, F

    2011-01-01

    Several metrological applications base their measurement principle in the phase sum or difference between two patterns, one original s(r,φ) and another modified t(r,φ+Δφ). Additive or differential phase shifting algorithms directly recover the sum 2φ+Δφ or the difference Δφ of phases without requiring prior calculation of the individual phases. These algorithms can be constructed, for example, from a suitable combination of known phase shifting algorithms. Little has been written on the design, analysis and error compensation of these new two-stage algorithms. Previously we have used computer simulation to study, in a linear approach or with a filter process in reciprocal space, the response of several families of them to the main error sources. In this work we present an error analysis that uses Monte Carlo simulation to achieve results in good agreement with those obtained with spatial and temporal methods.

  11. Hybridizing Differential Evolution with a Genetic Algorithm for Color Image Segmentation

    Directory of Open Access Journals (Sweden)

    R. V. V. Krishna

    2016-10-01

    Full Text Available This paper proposes a hybrid of differential evolution and genetic algorithms to solve the color image segmentation problem. Clustering based color image segmentation algorithms segment an image by clustering the features of color and texture, thereby obtaining accurate prototype cluster centers. In the proposed algorithm, the color features are obtained using the homogeneity model. A new texture feature named Power Law Descriptor (PLD which is a modification of Weber Local Descriptor (WLD is proposed and further used as a texture feature for clustering. Genetic algorithms are competent in handling binary variables, while differential evolution on the other hand is more efficient in handling real parameters. The obtained texture feature is binary in nature and the color feature is a real value, which suits very well the hybrid cluster center optimization problem in image segmentation. Thus in the proposed algorithm, the optimum texture feature centers are evolved using genetic algorithms, whereas the optimum color feature centers are evolved using differential evolution.

  12. General asymmetric neutral networks and structure design by genetic algorithms: A learning rule for temporal patterns

    Energy Technology Data Exchange (ETDEWEB)

    Bornholdt, S. [Heidelberg Univ., (Germany). Inst., fuer Theoretische Physik; Graudenz, D. [Lawrence Berkeley Lab., CA (United States)

    1993-07-01

    A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback.

  13. General asymmetric neutral networks and structure design by genetic algorithms: A learning rule for temporal patterns

    International Nuclear Information System (INIS)

    Bornholdt, S.

    1993-07-01

    A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback

  14. Characteristic statistic algorithm (CSA) for in-core loading pattern optimization

    International Nuclear Information System (INIS)

    Liu Zhihong; Hu Yongming; Shi Gong

    2007-01-01

    To solve the problem of PWR in-core loading pattern optimization, a more suitable global optimization algorithm, i.e., Characteristic statistic algorithm (CSA), is used. The searching process of this algorithm and how to apply it to this problem are presented. Loading pattern optimization code SCYCLE is developed. Two different problems on real PWR models are calculated and the results are compared with other algorithms. It is shown that SCYCLE has high efficiency and good global performance on this problem. (authors)

  15. Optimizing Transmission Network Expansion Planning With The Mean Of Chaotic Differential Evolution Algorithm

    Directory of Open Access Journals (Sweden)

    Ahmed R. Abdelaziz

    2015-08-01

    Full Text Available This paper presents an application of Chaotic differential evolution optimization approach meta-heuristics in solving transmission network expansion planning TNEP using an AC model associated with reactive power planning RPP. The reliabilityredundancy of network analysis optimization problems implicate selection of components with multiple choices and redundancy levels that produce maximum benefits can be subject to the cost weight and volume constraints is presented in this paper. Classical mathematical methods have failed in handling non-convexities and non-smoothness in optimization problems. As an alternative to the classical optimization approaches the meta-heuristics have attracted lot of attention due to their ability to find an almost global optimal solution in reliabilityredundancy optimization problems. Evolutionary algorithms EAs paradigms of evolutionary computation field are stochastic and robust meta-heuristics useful to solve reliabilityredundancy optimization problems. EAs such as genetic algorithm evolutionary programming evolution strategies and differential evolution are being used to find global or near global optimal solution. The Differential Evolution Algorithm DEA population-based algorithm is an optimal algorithm with powerful global searching capability but it is usually in low convergence speed and presents bad searching capability in the later evolution stage. A new Chaotic Differential Evolution algorithm CDE based on the cat map is recommended which combines DE and chaotic searching algorithm. Simulation results and comparisons show that the chaotic differential evolution algorithm using Cat map is competitive and stable in performance with other optimization approaches and other maps.

  16. Enteric neural crest cells regulate vertebrate stomach patterning and differentiation.

    Science.gov (United States)

    Faure, Sandrine; McKey, Jennifer; Sagnol, Sébastien; de Santa Barbara, Pascal

    2015-01-15

    In vertebrates, the digestive tract develops from a uniform structure where reciprocal epithelial-mesenchymal interactions pattern this complex organ into regions with specific morphologies and functions. Concomitant with these early patterning events, the primitive GI tract is colonized by the vagal enteric neural crest cells (vENCCs), a population of cells that will give rise to the enteric nervous system (ENS), the intrinsic innervation of the GI tract. The influence of vENCCs on early patterning and differentiation of the GI tract has never been evaluated. In this study, we report that a crucial number of vENCCs is required for proper chick stomach development, patterning and differentiation. We show that reducing the number of vENCCs by performing vENCC ablations induces sustained activation of the BMP and Notch pathways in the stomach mesenchyme and impairs smooth muscle development. A reduction in vENCCs also leads to the transdifferentiation of the stomach into a stomach-intestinal mixed phenotype. In addition, sustained Notch signaling activity in the stomach mesenchyme phenocopies the defects observed in vENCC-ablated stomachs, indicating that inhibition of the Notch signaling pathway is essential for stomach patterning and differentiation. Finally, we report that a crucial number of vENCCs is also required for maintenance of stomach identity and differentiation through inhibition of the Notch signaling pathway. Altogether, our data reveal that, through the regulation of mesenchyme identity, vENCCs act as a new mediator in the mesenchymal-epithelial interactions that control stomach development. © 2015. Published by The Company of Biologists Ltd.

  17. Differential theory of learning for efficient neural network pattern recognition

    Science.gov (United States)

    Hampshire, John B., II; Vijaya Kumar, Bhagavatula

    1993-09-01

    We describe a new theory of differential learning by which a broad family of pattern classifiers (including many well-known neural network paradigms) can learn stochastic concepts efficiently. We describe the relationship between a classifier's ability to generate well to unseen test examples and the efficiency of the strategy by which it learns. We list a series of proofs that differential learning is efficient in its information and computational resource requirements, whereas traditional probabilistic learning strategies are not. The proofs are illustrated by a simple example that lends itself to closed-form analysis. We conclude with an optical character recognition task for which three different types of differentially generated classifiers generalize significantly better than their probabilistically generated counterparts.

  18. Improved Differential Evolution Algorithm for Parameter Estimation to Improve the Production of Biochemical Pathway

    Directory of Open Access Journals (Sweden)

    Chuii Khim Chong

    2012-06-01

    Full Text Available This paper introduces an improved Differential Evolution algorithm (IDE which aims at improving its performance in estimating the relevant parameters for metabolic pathway data to simulate glycolysis pathway for yeast. Metabolic pathway data are expected to be of significant help in the development of efficient tools in kinetic modeling and parameter estimation platforms. Many computation algorithms face obstacles due to the noisy data and difficulty of the system in estimating myriad of parameters, and require longer computational time to estimate the relevant parameters. The proposed algorithm (IDE in this paper is a hybrid of a Differential Evolution algorithm (DE and a Kalman Filter (KF. The outcome of IDE is proven to be superior than Genetic Algorithm (GA and DE. The results of IDE from experiments show estimated optimal kinetic parameters values, shorter computation time and increased accuracy for simulated results compared with other estimation algorithms

  19. Improved differential evolution algorithms for handling economic dispatch optimization with generator constraints

    International Nuclear Information System (INIS)

    Coelho, Leandro dos Santos; Mariani, Viviana Cocco

    2007-01-01

    Global optimization based on evolutionary algorithms can be used as the important component for many engineering optimization problems. Evolutionary algorithms have yielded promising results for solving nonlinear, non-differentiable and multi-modal optimization problems in the power systems area. Differential evolution (DE) is a simple and efficient evolutionary algorithm for function optimization over continuous spaces. It has reportedly outperformed search heuristics when tested over both benchmark and real world problems. This paper proposes improved DE algorithms for solving economic load dispatch problems that take into account nonlinear generator features such as ramp rate limits and prohibited operating zones in the power system operation. The DE algorithms and its variants are validated for two test systems consisting of 6 and 15 thermal units. Various DE approaches outperforms other state of the art algorithms reported in the literature in solving load dispatch problems with generator constraints

  20. Kernel Clustering with a Differential Harmony Search Algorithm for Scheme Classification

    Directory of Open Access Journals (Sweden)

    Yu Feng

    2017-01-01

    Full Text Available This paper presents a kernel fuzzy clustering with a novel differential harmony search algorithm to coordinate with the diversion scheduling scheme classification. First, we employed a self-adaptive solution generation strategy and differential evolution-based population update strategy to improve the classical harmony search. Second, we applied the differential harmony search algorithm to the kernel fuzzy clustering to help the clustering method obtain better solutions. Finally, the combination of the kernel fuzzy clustering and the differential harmony search is applied for water diversion scheduling in East Lake. A comparison of the proposed method with other methods has been carried out. The results show that the kernel clustering with the differential harmony search algorithm has good performance to cooperate with the water diversion scheduling problems.

  1. Identification of transcript regulatory patterns in cell differentiation.

    Science.gov (United States)

    Gusnanto, Arief; Gosling, John Paul; Pope, Christopher

    2017-10-15

    Studying transcript regulatory patterns in cell differentiation is critical in understanding its complex nature of the formation and function of different cell types. This is done usually by measuring gene expression at different stages of the cell differentiation. However, if the gene expression data available are only from the mature cells, we have some challenges in identifying transcript regulatory patterns that govern the cell differentiation. We propose to exploit the information of the lineage of cell differentiation in terms of correlation structure between cell types. We assume that two different cell types that are close in the lineage will exhibit many common genes that are co-expressed relative to those that are far in the lineage. Current analysis methods tend to ignore this correlation by testing for differential expression assuming some sort of independence between cell types. We employ a Bayesian approach to estimate the posterior distribution of the mean of expression in each cell type, by taking into account the cell formation path in the lineage. This enables us to infer genes that are specific in each cell type, indicating the genes are involved in directing the cell differentiation to that particular cell type. We illustrate the method using gene expression data from a study of haematopoiesis. R codes to perform the analysis are available in http://www1.maths.leeds.ac.uk/∼arief/R/CellDiff/. a.gusnanto@leeds.ac.uk. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  2. An implementation of Kovacic's algorithm for solving ordinary differential equations in FORMAC

    International Nuclear Information System (INIS)

    Zharkov, A.Yu.

    1987-01-01

    An implementation of Kovacic's algorithm for finding Liouvillian solutions of the differential equations y'' + a(x)y' + b(x)y = 0 with rational coefficients a(x) and b(x) in the Computer Algebra System FORMAC is described. The algorithm description is presented in such a way that one can easily implement it in a suitable Computer Algebra System

  3. Pulse Retrieval Algorithm for Interferometric Frequency-Resolved Optical Gating Based on Differential Evolution

    OpenAIRE

    Hyyti, Janne; Escoto, Esmerando; Steinmeyer, Günter

    2017-01-01

    A novel algorithm for the ultrashort laser pulse characterization method of interferometric frequency-resolved optical gating (iFROG) is presented. Based on a genetic method, namely differential evolution, the algorithm can exploit all available information of an iFROG measurement to retrieve the complex electric field of a pulse. The retrieval is subjected to a series of numerical tests to prove robustness of the algorithm against experimental artifacts and noise. These tests show that the i...

  4. A hybrid firefly algorithm and pattern search technique for SSSC based power oscillation damping controller design

    Directory of Open Access Journals (Sweden)

    Srikanta Mahapatra

    2014-12-01

    Full Text Available In this paper, a novel hybrid Firefly Algorithm and Pattern Search (h-FAPS technique is proposed for a Static Synchronous Series Compensator (SSSC-based power oscillation damping controller design. The proposed h-FAPS technique takes the advantage of global search capability of FA and local search facility of PS. In order to tackle the drawback of using the remote signal that may impact reliability of the controller, a modified signal equivalent to the remote speed deviation signal is constructed from the local measurements. The performances of the proposed controllers are evaluated in SMIB and multi-machine power system subjected to various transient disturbances. To show the effectiveness and robustness of the proposed design approach, simulation results are presented and compared with some recently published approaches such as Differential Evolution (DE and Particle Swarm Optimization (PSO. It is observed that the proposed approach yield superior damping performance compared to some recently reported approaches.

  5. An algorithm for numerical solution of Anisimov coupled differential ...

    African Journals Online (AJOL)

    This paper proposes a way of obtaining non-equilibrium transient electron-lattice temperature of several thousands of Kelvin in semiconductor thin films by applying satisfactorily boundary conditions to Anisimov coupled differential equations .This is possible by adjusting some of the parameters in the equations and ...

  6. Investigation on the improvement of genetic algorithm for PWR loading pattern search and its benchmark verification

    International Nuclear Information System (INIS)

    Li Qianqian; Jiang Xiaofeng; Zhang Shaohong

    2009-01-01

    In this study, the age technique, the concepts of relativeness degree and worth function are exploited to improve the performance of genetic algorithm (GA) for PWR loading pattern search. Among them, the age technique endows the algorithm be capable of learning from previous search 'experience' and guides it to do a better search in the vicinity ora local optimal; the introduction of the relativeness degree checks the relativeness of two loading patterns before performing crossover between them, which can significantly reduce the possibility of prematurity of the algorithm; while the application of the worth function makes the algorithm be capable of generating new loading patterns based on the statistics of common features of evaluated good loading patterns. Numerical verification against a loading pattern search benchmark problem ora two-loop reactor demonstrates that the adoption of these techniques is able to significantly enhance the efficiency of the genetic algorithm while improves the quality of the final solution as well. (authors)

  7. An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors.

    Science.gov (United States)

    Luo, Liyan; Xu, Luping; Zhang, Hua

    2015-07-07

    In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms.

  8. Parameter optimization of differential evolution algorithm for automatic playlist generation problem

    Science.gov (United States)

    Alamag, Kaye Melina Natividad B.; Addawe, Joel M.

    2017-11-01

    With the digitalization of music, the number of collection of music increased largely and there is a need to create lists of music that filter the collection according to user preferences, thus giving rise to the Automatic Playlist Generation Problem (APGP). Previous attempts to solve this problem include the use of search and optimization algorithms. If a music database is very large, the algorithm to be used must be able to search the lists thoroughly taking into account the quality of the playlist given a set of user constraints. In this paper we perform an evolutionary meta-heuristic optimization algorithm, Differential Evolution (DE) using different combination of parameter values and select the best performing set when used to solve four standard test functions. Performance of the proposed algorithm is then compared with normal Genetic Algorithm (GA) and a hybrid GA with Tabu Search. Numerical simulations are carried out to show better results from Differential Evolution approach with the optimized parameter values.

  9. An optimized digital watermarking algorithm in wavelet domain based on differential evolution for color image.

    Science.gov (United States)

    Cui, Xinchun; Niu, Yuying; Zheng, Xiangwei; Han, Yingshuai

    2018-01-01

    In this paper, a new color watermarking algorithm based on differential evolution is proposed. A color host image is first converted from RGB space to YIQ space, which is more suitable for the human visual system. Then, apply three-level discrete wavelet transformation to luminance component Y and generate four different frequency sub-bands. After that, perform singular value decomposition on these sub-bands. In the watermark embedding process, apply discrete wavelet transformation to a watermark image after the scrambling encryption processing. Our new algorithm uses differential evolution algorithm with adaptive optimization to choose the right scaling factors. Experimental results show that the proposed algorithm has a better performance in terms of invisibility and robustness.

  10. A Qualitative Comparison between the Proportional Navigation and Differential Geometry Guidance Algorithms

    Directory of Open Access Journals (Sweden)

    Yunes Sh. ALQUDSI

    2018-06-01

    Full Text Available This paper discusses and presents an overview of the proportional navigation (PN guidance law as well as the differential geometry (DG guidance algorithm that are used to develop the intercept course of a certain target. The intent of this study is to illustrate the advantages of the guidance algorithm generated based on the concepts of differential geometry against the well-known PN guidance law. The basic principles behind the both algorithms are mentioned. Moreover, the different versions of the PN approach is briefly clarified to show the essential improvement from one version to the other. The paper terminated with numerous two-dimension simulation figures to give a great value of visual aids, illustrating the significant relations and main features and properties of both algorithms.

  11. Parameter identification based on modified simulated annealing differential evolution algorithm for giant magnetostrictive actuator

    Science.gov (United States)

    Gao, Xiaohui; Liu, Yongguang

    2018-01-01

    There is a serious nonlinear relationship between input and output in the giant magnetostrictive actuator (GMA) and how to establish mathematical model and identify its parameters is very important to study characteristics and improve control accuracy. The current-displacement model is firstly built based on Jiles-Atherton (J-A) model theory, Ampere loop theorem and stress-magnetism coupling model. And then laws between unknown parameters and hysteresis loops are studied to determine the data-taking scope. The modified simulated annealing differential evolution algorithm (MSADEA) is proposed by taking full advantage of differential evolution algorithm's fast convergence and simulated annealing algorithm's jumping property to enhance the convergence speed and performance. Simulation and experiment results shows that this algorithm is not only simple and efficient, but also has fast convergence speed and high identification accuracy.

  12. Algebraic dynamics solutions and algebraic dynamics algorithm for nonlinear partial differential evolution equations of dynamical systems

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Using functional derivative technique in quantum field theory, the algebraic dy-namics approach for solution of ordinary differential evolution equations was gen-eralized to treat partial differential evolution equations. The partial differential evo-lution equations were lifted to the corresponding functional partial differential equations in functional space by introducing the time translation operator. The functional partial differential evolution equations were solved by algebraic dynam-ics. The algebraic dynamics solutions are analytical in Taylor series in terms of both initial functions and time. Based on the exact analytical solutions, a new nu-merical algorithm—algebraic dynamics algorithm was proposed for partial differ-ential evolution equations. The difficulty of and the way out for the algorithm were discussed. The application of the approach to and computer numerical experi-ments on the nonlinear Burgers equation and meteorological advection equation indicate that the algebraic dynamics approach and algebraic dynamics algorithm are effective to the solution of nonlinear partial differential evolution equations both analytically and numerically.

  13. A Pilot-Pattern Based Algorithm for MIMO-OFDM Channel Estimation

    Directory of Open Access Journals (Sweden)

    Guomin Li

    2016-12-01

    Full Text Available An improved pilot pattern algorithm for facilitating the channel estimation in multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM systems is proposed in this paper. The presented algorithm reconfigures the parameter in the least square (LS algorithm, which belongs to the space-time block-coded (STBC category for channel estimation in pilot-based MIMO-OFDM system. Simulation results show that the algorithm has better performance in contrast to the classical single symbol scheme. In contrast to the double symbols scheme, the proposed algorithm can achieve nearly the same performance with only half of the complexity of the double symbols scheme.

  14. An Improved Differential Evolution Algorithm for Maritime Collision Avoidance Route Planning

    Directory of Open Access Journals (Sweden)

    Yu-xin Zhao

    2014-01-01

    Full Text Available High accuracy navigation and surveillance systems are pivotal to ensure efficient ship route planning and marine safety. Based on existing ship navigation and maritime collision prevention rules, an improved approach for collision avoidance route planning using a differential evolution algorithm was developed. Simulation results show that the algorithm is capable of significantly enhancing the optimized route over current methods. It has the potential to be used as a tool to generate optimal vessel routing in the presence of conflicts.

  15. Dietary patterns as risk factors of differentiated thyroid carcinoma

    Directory of Open Access Journals (Sweden)

    Elwira Przybylik-Mazurek

    2012-01-01

    Full Text Available Nutritional factors are known to be important in the development of different metabolic diseases. The history of nodular or diffuse goiter is closely related to risk of thyroid carcinoma. On account of the function of the thyroid gland, many studies focus on iodine intake.The aim of the study was to assess whether dietary patterns could be risk factors of differentiated thyroid carcinoma.Material/Methods:The case-control study was based on a questionnaire, which included information about dietary patterns and was carried out on 284 patients comprising 30 males (mean age 58.4±13.7 years, and 254 females (mean age 52.1±13.8 years, as well as 345 randomly selected controls: 58 males (mean age 60.2±12 years and 287 females (mean age 53.4±14.3 years randomly selected from the Population Register and adjusted by age and gender to the group of TC. The main groups of nutritional products, i.e. starchy foods, meat, dairy products, vegetables, fruits, and beverages, were analyzed.Results:Consumption of vegetables, fruits, saltwater fish and cottage cheese was significantly lower in patients with differentiated thyroid carcinoma than in controls, quite the contrary to starchy foods, especially white bread.Conclusions:Dietary patterns appear to modify the risk of thyroid carcinoma. A diet rich in vegetables and fruit, as well as saltwater fish (a source of iodine and low-fat meat, could be an important protective factor.

  16. Algorithm that mimics human perceptual grouping of dot patterns

    NARCIS (Netherlands)

    Papari, G.; Petkov, N.; Gregorio, MD; DiMaio,; Frucci, M; Musio, C

    2005-01-01

    We propose an algorithm that groups points similarly to how human observers do. It is simple, totally unsupervised and able to find clusters of complex and not necessarily convex shape. Groups are identified as the connected components of a Reduced Delaunay Graph (RDG) that we define in this paper.

  17. Unified algorithm for partial differential equations and examples of numerical computation

    International Nuclear Information System (INIS)

    Watanabe, Tsuguhiro

    1999-01-01

    A new unified algorithm is proposed to solve partial differential equations which describe nonlinear boundary value problems, eigenvalue problems and time developing boundary value problems. The algorithm is composed of implicit difference scheme and multiple shooting scheme and is named as HIDM (Higher order Implicit Difference Method). A new prototype computer programs for 2-dimensional partial differential equations is constructed and tested successfully to several problems. Extension of the computer programs to 3 or more higher order dimension problems will be easy due to the direct product type difference scheme. (author)

  18. Pulse retrieval algorithm for interferometric frequency-resolved optical gating based on differential evolution.

    Science.gov (United States)

    Hyyti, Janne; Escoto, Esmerando; Steinmeyer, Günter

    2017-10-01

    A novel algorithm for the ultrashort laser pulse characterization method of interferometric frequency-resolved optical gating (iFROG) is presented. Based on a genetic method, namely, differential evolution, the algorithm can exploit all available information of an iFROG measurement to retrieve the complex electric field of a pulse. The retrieval is subjected to a series of numerical tests to prove the robustness of the algorithm against experimental artifacts and noise. These tests show that the integrated error-correction mechanisms of the iFROG method can be successfully used to remove the effect from timing errors and spectrally varying efficiency in the detection. Moreover, the accuracy and noise resilience of the new algorithm are shown to outperform retrieval based on the generalized projections algorithm, which is widely used as the standard method in FROG retrieval. The differential evolution algorithm is further validated with experimental data, measured with unamplified three-cycle pulses from a mode-locked Ti:sapphire laser. Additionally introducing group delay dispersion in the beam path, the retrieval results show excellent agreement with independent measurements with a commercial pulse measurement device based on spectral phase interferometry for direct electric-field retrieval. Further experimental tests with strongly attenuated pulses indicate resilience of differential-evolution-based retrieval against massive measurement noise.

  19. Parameter identification of PEMFC model based on hybrid adaptive differential evolution algorithm

    International Nuclear Information System (INIS)

    Sun, Zhe; Wang, Ning; Bi, Yunrui; Srinivasan, Dipti

    2015-01-01

    In this paper, a HADE (hybrid adaptive differential evolution) algorithm is proposed for the identification problem of PEMFC (proton exchange membrane fuel cell). Inspired by biological genetic strategy, a novel adaptive scaling factor and a dynamic crossover probability are presented to improve the adaptive and dynamic performance of differential evolution algorithm. Moreover, two kinds of neighborhood search operations based on the bee colony foraging mechanism are introduced for enhancing local search efficiency. Through testing the benchmark functions, the proposed algorithm exhibits better performance in convergent accuracy and speed. Finally, the HADE algorithm is applied to identify the nonlinear parameters of PEMFC stack model. Through experimental comparison with other identified methods, the PEMFC model based on the HADE algorithm shows better performance. - Highlights: • We propose a hybrid adaptive differential evolution algorithm (HADE). • The search efficiency is enhanced in low and high dimension search space. • The effectiveness is confirmed by testing benchmark functions. • The identification of the PEMFC model is conducted by adopting HADE.

  20. Pattern-set generation algorithm for the one-dimensional multiple stock sizes cutting stock problem

    Science.gov (United States)

    Cui, Yaodong; Cui, Yi-Ping; Zhao, Zhigang

    2015-09-01

    A pattern-set generation algorithm (PSG) for the one-dimensional multiple stock sizes cutting stock problem (1DMSSCSP) is presented. The solution process contains two stages. In the first stage, the PSG solves the residual problems repeatedly to generate the patterns in the pattern set, where each residual problem is solved by the column-generation approach, and each pattern is generated by solving a single large object placement problem. In the second stage, the integer linear programming model of the 1DMSSCSP is solved using a commercial solver, where only the patterns in the pattern set are considered. The computational results of benchmark instances indicate that the PSG outperforms existing heuristic algorithms and rivals the exact algorithm in solution quality.

  1. On integral and differential representations of Jordan chains and the confluent supersymmetry algorithm

    International Nuclear Information System (INIS)

    Contreras-Astorga, Alonso; Schulze-Halberg, Axel

    2015-01-01

    We construct a relationship between integral and differential representation of second-order Jordan chains. Conditions to obtain regular potentials through the confluent supersymmetry algorithm when working with the differential representation are obtained using this relationship. Furthermore, it is used to find normalization constants of wave functions of quantum systems that feature energy-dependent potentials. Additionally, this relationship is used to express certain integrals involving functions that are solution of Schrödinger equations through derivatives. (paper)

  2. A Convergent Differential Evolution Algorithm with Hidden Adaptation Selection for Engineering Optimization

    Directory of Open Access Journals (Sweden)

    Zhongbo Hu

    2014-01-01

    Full Text Available Many improved differential Evolution (DE algorithms have emerged as a very competitive class of evolutionary computation more than a decade ago. However, few improved DE algorithms guarantee global convergence in theory. This paper developed a convergent DE algorithm in theory, which employs a self-adaptation scheme for the parameters and two operators, that is, uniform mutation and hidden adaptation selection (haS operators. The parameter self-adaptation and uniform mutation operator enhance the diversity of populations and guarantee ergodicity. The haS can automatically remove some inferior individuals in the process of the enhancing population diversity. The haS controls the proposed algorithm to break the loop of current generation with a small probability. The breaking probability is a hidden adaptation and proportional to the changes of the number of inferior individuals. The proposed algorithm is tested on ten engineering optimization problems taken from IEEE CEC2011.

  3. The use of antenna radiation pattern in node localisation algorithms for wireless sensor networks

    CSIR Research Space (South Africa)

    Mwila, MK

    2014-08-01

    Full Text Available due to the limited accuracy inherent to the current ranging model. These models, however, make the assumption that the antenna radiation pattern is omnidirectional targeted to simplifying the complexity of the algorithms. An increasing number of sensor...

  4. Algorithmic acquisition of diagnostic patterns in district heating billing system

    International Nuclear Information System (INIS)

    Kiluk, Sebastian

    2012-01-01

    An application of algorithmic exploration of billing data is examined for fault detection, diagnosis (FDD) based on evaluation of present state and detection of unexpected changes in energy efficiency of buildings. Large data sets from district heating (DH) billing systems are used for construction of feature space, diagnostic rules and classification of the buildings according to their energy efficiency properties. The algorithmic approach automates discovering knowledge about common, thus accepted changes in buildings’ properties, in equipment and in habitants’ behavior reflecting progress in technology and life style. In this article implementation of Data Mining and Knowledge Discovery (DMKD) method in supervision system with exemplary results based on real data is presented. Crucial steps of data processing influencing diagnostic results are described in details.

  5. Self-karaoke patterns: an interactive audio-visual system for handsfree live algorithm performance

    OpenAIRE

    Eldridge, Alice

    2014-01-01

    Self-karaoke Patterns, is an audiovisual study for improvised cello and live algorithms. The work is motivated in part by addressing the practical needs of the performer in ‘handsfree’ live algorithm contexts and in part an aesthetic concern with resolving the tension between conceptual dedication to autonomous algorithms and musical dedication to coherent performance. The elected approach is inspired by recent work investing the role of ‘shape’ in musical performance.

  6. Development of pattern recognition algorithms for the central drift chamber of the Belle II detector

    Energy Technology Data Exchange (ETDEWEB)

    Trusov, Viktor

    2016-11-04

    In this thesis, the development of one of the pattern recognition algorithms for the Belle II experiment based on conformal and Legendre transformations is presented. In order to optimize the performance of the algorithm (CPU time and efficiency) specialized processing steps have been introduced. To show achieved results, Monte-Carlo based efficiency measurements of the tracking algorithms in the Central Drift Chamber (CDC) has been done.

  7. Use of artificial bee colonies algorithm as numerical approximation of differential equations solution

    Science.gov (United States)

    Fikri, Fariz Fahmi; Nuraini, Nuning

    2018-03-01

    The differential equation is one of the branches in mathematics which is closely related to human life problems. Some problems that occur in our life can be modeled into differential equations as well as systems of differential equations such as the Lotka-Volterra model and SIR model. Therefore, solving a problem of differential equations is very important. Some differential equations are difficult to solve, so numerical methods are needed to solve that problems. Some numerical methods for solving differential equations that have been widely used are Euler Method, Heun Method, Runge-Kutta and others. However, some of these methods still have some restrictions that cause the method cannot be used to solve more complex problems such as an evaluation interval that we cannot change freely. New methods are needed to improve that problems. One of the method that can be used is the artificial bees colony algorithm. This algorithm is one of metaheuristic algorithm method, which can come out from local search space and do exploration in solution search space so that will get better solution than other method.

  8. A Boyer-Moore (or Watson-Watson) type algorithm for regular tree pattern matching

    NARCIS (Netherlands)

    Watson, B.W.; Aarts, E.H.L.; Eikelder, ten H.M.M.; Hemerik, C.; Rem, M.

    1995-01-01

    In this chapter, I outline a new algorithm for regular tree pattern matching. The existence of this algorithm was first mentioned in the statements accompanying my dissertation, [2]. In order to avoid repeating the material in my dissertation, it is assumed that the reader is familiar with Chapters

  9. Two related algorithms for root-to-frontier tree pattern matching

    NARCIS (Netherlands)

    Cleophas, L.G.W.A.; Hemerik, C.; Zwaan, G.

    2006-01-01

    Tree pattern matching (TPM) algorithms on ordered, ranked trees play an important role in applications such as compilers and term rewriting systems. Many TPM algorithms appearing in the literature are based on tree automata. For efficiency, these automata should be deterministic, yet deterministic

  10. An Interval Bound Algorithm of optimizing reactor core loading pattern by using reactivity interval schema

    International Nuclear Information System (INIS)

    Gong Zhaohu; Wang Kan; Yao Dong

    2011-01-01

    Highlights: → We present a new Loading Pattern Optimization method - Interval Bound Algorithm (IBA). → IBA directly uses the reactivity of fuel assemblies and burnable poison. → IBA can optimize fuel assembly orientation in a coupled way. → Numerical experiment shows that IBA outperforms genetic algorithm and engineers. → We devise DDWF technique to deal with multiple objectives and constraints. - Abstract: In order to optimize the core loading pattern in Nuclear Power Plants, the paper presents a new optimization method - Interval Bound Algorithm (IBA). Similar to the typical population based algorithms, e.g. genetic algorithm, IBA maintains a population of solutions and evolves them during the optimization process. IBA acquires the solution by statistical learning and sampling the control variable intervals of the population in each iteration. The control variables are the transforms of the reactivity of fuel assemblies or the worth of burnable poisons, which are the crucial heuristic information for loading pattern optimization problems. IBA can deal with the relationship between the dependent variables by defining the control variables. Based on the IBA algorithm, a parallel Loading Pattern Optimization code, named IBALPO, has been developed. To deal with multiple objectives and constraints, the Dynamic Discontinuous Weight Factors (DDWF) for the fitness function have been used in IBALPO. Finally, the code system has been used to solve a realistic reloading problem and a better pattern has been obtained compared with the ones searched by engineers and genetic algorithm, thus the performance of the code is proved.

  11. Validation of differential gene expression algorithms: Application comparing fold-change estimation to hypothesis testing

    Directory of Open Access Journals (Sweden)

    Bickel David R

    2010-01-01

    Full Text Available Abstract Background Sustained research on the problem of determining which genes are differentially expressed on the basis of microarray data has yielded a plethora of statistical algorithms, each justified by theory, simulation, or ad hoc validation and yet differing in practical results from equally justified algorithms. Recently, a concordance method that measures agreement among gene lists have been introduced to assess various aspects of differential gene expression detection. This method has the advantage of basing its assessment solely on the results of real data analyses, but as it requires examining gene lists of given sizes, it may be unstable. Results Two methodologies for assessing predictive error are described: a cross-validation method and a posterior predictive method. As a nonparametric method of estimating prediction error from observed expression levels, cross validation provides an empirical approach to assessing algorithms for detecting differential gene expression that is fully justified for large numbers of biological replicates. Because it leverages the knowledge that only a small portion of genes are differentially expressed, the posterior predictive method is expected to provide more reliable estimates of algorithm performance, allaying concerns about limited biological replication. In practice, the posterior predictive method can assess when its approximations are valid and when they are inaccurate. Under conditions in which its approximations are valid, it corroborates the results of cross validation. Both comparison methodologies are applicable to both single-channel and dual-channel microarrays. For the data sets considered, estimating prediction error by cross validation demonstrates that empirical Bayes methods based on hierarchical models tend to outperform algorithms based on selecting genes by their fold changes or by non-hierarchical model-selection criteria. (The latter two approaches have comparable

  12. Reload pattern optimization by application of multiple cyclic interchange algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Geemert, R. van; Quist, A.J.; Hoogenboom, J.E. [Technische Univ. Delft (Netherlands)

    1996-09-01

    Reload pattern optimization procedures are proposed which are based on the multiple cyclic interchange approach, according to which the search for the reload pattern associated with the highest objective function value can be thought of as divided in multiple stages. The transition from the initial to the final stage is characterized by an increase in the degree of locality of the search procedure. The general idea is that, during the first stages, the `elite` cluster containing the group of best patterns must be located, after which the solution space is sampled in a more and more local sense to find the local optimum in this cluster. The transition(s) from global search behaviour to local search behaviour can be either prompt, by defining strictly separate search regimes, or gradual by introducing stochastic tests for the number of fuel bundles involved in a cyclic interchange. Equilibrium cycle optimization results are reported for a test PWR reactor core of modest size. (author)

  13. Reload pattern optimization by application of multiple cyclic interchange algorithms

    International Nuclear Information System (INIS)

    Geemert, R. van; Quist, A.J.; Hoogenboom, J.E.

    1996-01-01

    Reload pattern optimization procedures are proposed which are based on the multiple cyclic interchange approach, according to which the search for the reload pattern associated with the highest objective function value can be thought of as divided in multiple stages. The transition from the initial to the final stage is characterized by an increase in the degree of locality of the search procedure. The general idea is that, during the first stages, the 'elite' cluster containing the group of best patterns must be located, after which the solution space is sampled in a more and more local sense to find the local optimum in this cluster. The transition(s) from global search behaviour to local search behaviour can be either prompt, by defining strictly separate search regimes, or gradual by introducing stochastic tests for the number of fuel bundles involved in a cyclic interchange. Equilibrium cycle optimization results are reported for a test PWR reactor core of modest size. (author)

  14. RDEL: Restart Differential Evolution algorithm with Local Search Mutation for global numerical optimization

    Directory of Open Access Journals (Sweden)

    Ali Wagdy Mohamed

    2014-11-01

    Full Text Available In this paper, a novel version of Differential Evolution (DE algorithm based on a couple of local search mutation and a restart mechanism for solving global numerical optimization problems over continuous space is presented. The proposed algorithm is named as Restart Differential Evolution algorithm with Local Search Mutation (RDEL. In RDEL, inspired by Particle Swarm Optimization (PSO, a novel local mutation rule based on the position of the best and the worst individuals among the entire population of a particular generation is introduced. The novel local mutation scheme is joined with the basic mutation rule through a linear decreasing function. The proposed local mutation scheme is proven to enhance local search tendency of the basic DE and speed up the convergence. Furthermore, a restart mechanism based on random mutation scheme and a modified Breeder Genetic Algorithm (BGA mutation scheme is combined to avoid stagnation and/or premature convergence. Additionally, an exponent increased crossover probability rule and a uniform scaling factors of DE are introduced to promote the diversity of the population and to improve the search process, respectively. The performance of RDEL is investigated and compared with basic differential evolution, and state-of-the-art parameter adaptive differential evolution variants. It is discovered that the proposed modifications significantly improve the performance of DE in terms of quality of solution, efficiency and robustness.

  15. Culture belief based multi-objective hybrid differential evolutionary algorithm in short term hydrothermal scheduling

    International Nuclear Information System (INIS)

    Zhang Huifeng; Zhou Jianzhong; Zhang Yongchuan; Lu Youlin; Wang Yongqiang

    2013-01-01

    Highlights: ► Culture belief is integrated into multi-objective differential evolution. ► Chaotic sequence is imported to improve evolutionary population diversity. ► The priority of convergence rate is proved in solving hydrothermal problem. ► The results show the quality and potential of proposed algorithm. - Abstract: A culture belief based multi-objective hybrid differential evolution (CB-MOHDE) is presented to solve short term hydrothermal optimal scheduling with economic emission (SHOSEE) problem. This problem is formulated for compromising thermal cost and emission issue while considering its complicated non-linear constraints with non-smooth and non-convex characteristics. The proposed algorithm integrates a modified multi-objective differential evolutionary algorithm into the computation model of culture algorithm (CA) as well as some communication protocols between population space and belief space, three knowledge structures in belief space are redefined according to these problem-solving characteristics, and in the differential evolution a chaotic factor is embedded into mutation operator for avoiding the premature convergence by enlarging the search scale when the search trajectory reaches local optima. Furthermore, a new heuristic constraint-handling technique is utilized to handle those complex equality and inequality constraints of SHOSEE problem. After the application on hydrothermal scheduling system, the efficiency and stability of the proposed CB-MOHDE is verified by its more desirable results in comparison to other method established recently, and the simulation results also reveal that CB-MOHDE can be a promising alternative for solving SHOSEE.

  16. A stochastic differential equation model of diurnal cortisol patterns

    Science.gov (United States)

    Brown, E. N.; Meehan, P. M.; Dempster, A. P.

    2001-01-01

    Circadian modulation of episodic bursts is recognized as the normal physiological pattern of diurnal variation in plasma cortisol levels. The primary physiological factors underlying these diurnal patterns are the ultradian timing of secretory events, circadian modulation of the amplitude of secretory events, infusion of the hormone from the adrenal gland into the plasma, and clearance of the hormone from the plasma by the liver. Each measured plasma cortisol level has an error arising from the cortisol immunoassay. We demonstrate that all of these three physiological principles can be succinctly summarized in a single stochastic differential equation plus measurement error model and show that physiologically consistent ranges of the model parameters can be determined from published reports. We summarize the model parameters in terms of the multivariate Gaussian probability density and establish the plausibility of the model with a series of simulation studies. Our framework makes possible a sensitivity analysis in which all model parameters are allowed to vary simultaneously. The model offers an approach for simultaneously representing cortisol's ultradian, circadian, and kinetic properties. Our modeling paradigm provides a framework for simulation studies and data analysis that should be readily adaptable to the analysis of other endocrine hormone systems.

  17. Algorithm Design for Grip-Pattern Verification in Smart Gun

    NARCIS (Netherlands)

    Shang, X.; Veldhuis, Raymond N.J.; Bazen, A.M.; Ganzevoort, W.P.T.

    2005-01-01

    The Secure Grip project1 focuses on the development of a hand-grip pattern recognition system, as part of the smart gun. Its target customer is the police. To explore the authentication performance of this system, we collected data from a group of police officers, and made authentication simulations

  18. Cloud computing task scheduling strategy based on improved differential evolution algorithm

    Science.gov (United States)

    Ge, Junwei; He, Qian; Fang, Yiqiu

    2017-04-01

    In order to optimize the cloud computing task scheduling scheme, an improved differential evolution algorithm for cloud computing task scheduling is proposed. Firstly, the cloud computing task scheduling model, according to the model of the fitness function, and then used improved optimization calculation of the fitness function of the evolutionary algorithm, according to the evolution of generation of dynamic selection strategy through dynamic mutation strategy to ensure the global and local search ability. The performance test experiment was carried out in the CloudSim simulation platform, the experimental results show that the improved differential evolution algorithm can reduce the cloud computing task execution time and user cost saving, good implementation of the optimal scheduling of cloud computing tasks.

  19. Hybrid Discrete Differential Evolution Algorithm for Lot Splitting with Capacity Constraints in Flexible Job Scheduling

    Directory of Open Access Journals (Sweden)

    Xinli Xu

    2013-01-01

    Full Text Available A two-level batch chromosome coding scheme is proposed to solve the lot splitting problem with equipment capacity constraints in flexible job shop scheduling, which includes a lot splitting chromosome and a lot scheduling chromosome. To balance global search and local exploration of the differential evolution algorithm, a hybrid discrete differential evolution algorithm (HDDE is presented, in which the local strategy with dynamic random searching based on the critical path and a random mutation operator is developed. The performance of HDDE was experimented with 14 benchmark problems and the practical dye vat scheduling problem. The simulation results showed that the proposed algorithm has the strong global search capability and can effectively solve the practical lot splitting problems with equipment capacity constraints.

  20. Cloud Particles Differential Evolution Algorithm: A Novel Optimization Method for Global Numerical Optimization

    Directory of Open Access Journals (Sweden)

    Wei Li

    2015-01-01

    Full Text Available We propose a new optimization algorithm inspired by the formation and change of the cloud in nature, referred to as Cloud Particles Differential Evolution (CPDE algorithm. The cloud is assumed to have three states in the proposed algorithm. Gaseous state represents the global exploration. Liquid state represents the intermediate process from the global exploration to the local exploitation. Solid state represents the local exploitation. The best solution found so far acts as a nucleus. In gaseous state, the nucleus leads the population to explore by condensation operation. In liquid state, cloud particles carry out macrolocal exploitation by liquefaction operation. A new mutation strategy called cloud differential mutation is introduced in order to solve a problem that the misleading effect of a nucleus may cause the premature convergence. In solid state, cloud particles carry out microlocal exploitation by solidification operation. The effectiveness of the algorithm is validated upon different benchmark problems. The results have been compared with eight well-known optimization algorithms. The statistical analysis on performance evaluation of the different algorithms on 10 benchmark functions and CEC2013 problems indicates that CPDE attains good performance.

  1. [Algorithm for the differential diagnosis of precancerous and regenerative changes in the cervix uteri].

    Science.gov (United States)

    Sazonova, V Iu; Fedorova, V E; Danilova, N V

    2013-01-01

    Pretumoral changes in the epithelium of the cervix uteri include cervical intraepithelial neoplasia (CIN). CIN III should be differentiated with regenerative changes during epidermization of endocervicoses. Epidermization is proliferation of undifferentiated reserve cells that differentiate towards the squamous epithelium, by superseding the ectopic endocervical glandular epithelium. This process was called immature squamous metaplasia (ISM). The objective of the investigation was to define the significance of different morphological signs in the differential diagnosis of CIN III and ISM. One hundred and twelve cervical, CIN III, and immature squamous metaplasia biopsies were selected for examination. The selected cervical specimens were divided into 2 groups according to the presence or absence of p16 and CK17 expression. The p16+, CK17- cases were taken as true CIN III and the pl 6-, CK17+ as a regenerative process. The basis for this investigation is the signs included by O.K. Khmelnitsky into an algorithm for the differential diagnosis of epidermizing pseudoerosion and intraepithelial cancer of the cervix uteri. The algorithm was reconsidered to objectify. The investigation established great differences in the number of significant mitoses in the study groups. A clear trend was found for differences in the number of acanthotic strands. A new differential diagnostic algorithm for CIN III and ISM, which included the number of significant mitoses and acanthotic strands and p16 and CK17 expression, was proposed.

  2. An AUTONOMOUS STAR IDENTIFICATION ALGORITHM BASED ON THE DIRECTED CIRCULARITY PATTERN

    Directory of Open Access Journals (Sweden)

    J. Xie

    2012-07-01

    Full Text Available The accuracy of the angular distance may decrease due to lots of factors, such as the parameters of the stellar camera aren't calibrated on-orbit, or the location accuracy of the star image points is low, and so on, which can cause the low success rates of star identification. A robust directed circularity pattern algorithm is proposed in this paper, which is developed on basis of the matching probability algorithm. The improved algorithm retains the matching probability strategy to identify master star, and constructs a directed circularity pattern with the adjacent stars for unitary matching. The candidate matching group which has the longest chain will be selected as the final result. Simulation experiments indicate that the improved algorithm has high successful identification and reliability etc, compared with the original algorithm. The experiments with real data are used to verify it.

  3. Structural optimization of a motorcycle chassis by pattern search algorithm

    Science.gov (United States)

    Scappaticci, Lorenzo; Bartolini, Nicola; Guglielmino, Eugenio; Risitano, Giacomo

    2017-08-01

    Changes to the technical regulations of the motorcycle racing world classes introduced the new Moto2 category. The vehicles are prototypes that use single-brand tyres and engines derived from series production, supplied by a single manufacturer. The stability and handling of the vehicle are highly dependent on the geometric properties of the chassis. The performance of a racing motorcycle chassis can be primarily evaluated in terms of weight and stiffness. The aim of this work is to maximize the performance of a tubular frame designed for a motorcycle racing in the Moto2 category. The goal is the implementation of an optimization algorithm that acts on the dimensions of the single pipes of the frame and involves the design of an objective function to minimize the weight of the frame by controlling its stiffnesses.

  4. Engineering Algorithms for Finding Patterns in Biological Data

    DEFF Research Database (Denmark)

    Nielsen, Jesper

    2011-01-01

    similarity scores. Association mapping is a technique based on using large amounts of data on Single Nucleotide Polymorphisms (SNPs) to statistically infer associations between segments of DNA and effects in the host. Within the area of association mapping we develop an efficient file format and software...... library, called SNPFile. The file format is able to store both large amounts of SNP data and associated metadata, such as ids and affected-status of samples. Thus the file format can both speed-up SNP data access and simplify data management significantly. On the topic of molecular biological data, we...... analyze data from an experiment on exosome knockout. The exosome is a complex with a role in RNA degradation. We find that knockout of the exosome stabilize hitherto unknown RNA transcripts upstream active transcription start sites. With respect to Hidden Markov Models we develop two fast algorithms. We...

  5. Assessment of available integration algorithms for initial value ordinary differential equations

    International Nuclear Information System (INIS)

    Carver, M.B.; Stewart, D.G.

    1979-11-01

    There exists an extremely large number of algorithms designed for the ordinary differential equation initial value problem. The integration is normally done by a finite sum at time intervals which are chosen dynamically to satisfy an imposed error tolerance. This report describes the basic logistics of the integration process, identifies common areas of difficulty, and establishes a comprehensive test profile for integration algorithms. A number of algorithms are described, and selected published subroutines are evaluated using the test profile. It concludes that an effective library for general use need have only two such routines. The two selected are versions of the well-known Gear and Runge-Kutta-Fehlberg algorithms. Full documentation and listings are included. (auth)

  6. A Comparative Study of Frequent and Maximal Periodic Pattern Mining Algorithms in Spatiotemporal Databases

    Science.gov (United States)

    Obulesu, O.; Rama Mohan Reddy, A., Dr; Mahendra, M.

    2017-08-01

    Detecting regular and efficient cyclic models is the demanding activity for data analysts due to unstructured, vigorous and enormous raw information produced from web. Many existing approaches generate large candidate patterns in the occurrence of huge and complex databases. In this work, two novel algorithms are proposed and a comparative examination is performed by considering scalability and performance parameters. The first algorithm is, EFPMA (Extended Regular Model Detection Algorithm) used to find frequent sequential patterns from the spatiotemporal dataset and the second one is, ETMA (Enhanced Tree-based Mining Algorithm) for detecting effective cyclic models with symbolic database representation. EFPMA is an algorithm grows models from both ends (prefixes and suffixes) of detected patterns, which results in faster pattern growth because of less levels of database projection compared to existing approaches such as Prefixspan and SPADE. ETMA uses distinct notions to store and manage transactions data horizontally such as segment, sequence and individual symbols. ETMA exploits a partition-and-conquer method to find maximal patterns by using symbolic notations. Using this algorithm, we can mine cyclic models in full-series sequential patterns including subsection series also. ETMA reduces the memory consumption and makes use of the efficient symbolic operation. Furthermore, ETMA only records time-series instances dynamically, in terms of character, series and section approaches respectively. The extent of the pattern and proving efficiency of the reducing and retrieval techniques from synthetic and actual datasets is a really open & challenging mining problem. These techniques are useful in data streams, traffic risk analysis, medical diagnosis, DNA sequence Mining, Earthquake prediction applications. Extensive investigational outcomes illustrates that the algorithms outperforms well towards efficiency and scalability than ECLAT, STNR and MAFIA approaches.

  7. Patterns of population differentiation of candidate genes for cardiovascular disease

    Directory of Open Access Journals (Sweden)

    Ding Keyue

    2007-07-01

    Full Text Available Abstract Background The basis for ethnic differences in cardiovascular disease (CVD susceptibility is not fully understood. We investigated patterns of population differentiation (FST of a set of genes in etiologic pathways of CVD among 3 ethnic groups: Yoruba in Nigeria (YRI, Utah residents with European ancestry (CEU, and Han Chinese (CHB + Japanese (JPT. We identified 37 pathways implicated in CVD based on the PANTHER classification and 416 genes in these pathways were further studied; these genes belonged to 6 biological processes (apoptosis, blood circulation and gas exchange, blood clotting, homeostasis, immune response, and lipoprotein metabolism. Genotype data were obtained from the HapMap database. Results We calculated FST for 15,559 common SNPs (minor allele frequency ≥ 0.10 in at least one population in genes that co-segregated among the populations, as well as an average-weighted FST for each gene. SNPs were classified as putatively functional (non-synonymous and untranslated regions or non-functional (intronic and synonymous sites. Mean FST values for common putatively functional variants were significantly higher than FST values for nonfunctional variants. A significant variation in FST was also seen based on biological processes; the processes of 'apoptosis' and 'lipoprotein metabolism' showed an excess of genes with high FST. Thus, putative functional SNPs in genes in etiologic pathways for CVD show greater population differentiation than non-functional SNPs and a significant variance of FST values was noted among pairwise population comparisons for different biological processes. Conclusion These results suggest a possible basis for varying susceptibility to CVD among ethnic groups.

  8. Rating Algorithm for Pronunciation of English Based on Audio Feature Pattern Matching

    Directory of Open Access Journals (Sweden)

    Li Kun

    2015-01-01

    Full Text Available With the increasing internationalization of China, language communication has become an important channel for us to adapt to the political and economic environment. How to improve English learners’ language learning efficiency in limited conditions has turned into a problem demanding prompt solution at present. This paper applies two pronunciation patterns according to the actual needs of English pronunciation rating: to-be-evaluated pronunciation pattern and standard pronunciation pattern. It will translate the patterns into English pronunciation rating results through European distance. Besides, this paper will introduce the design philosophy of the whole algorithm in combination with CHMM matching pattern. Each link of the CHMM pattern will be given selective analysis while a contrast experiment between the CHMM matching pattern and the other two patterns will be conducted. From the experiment results, it can be concluded that CHMM pattern is the best option.

  9. An Orthogonal Learning Differential Evolution Algorithm for Remote Sensing Image Registration

    Directory of Open Access Journals (Sweden)

    Wenping Ma

    2014-01-01

    Full Text Available We introduce an area-based method for remote sensing image registration. We use orthogonal learning differential evolution algorithm to optimize the similarity metric between the reference image and the target image. Many local and global methods have been used to achieve the optimal similarity metric in the last few years. Because remote sensing images are usually influenced by large distortions and high noise, local methods will fail in some cases. For this reason, global methods are often required. The orthogonal learning (OL strategy is efficient when searching in complex problem spaces. In addition, it can discover more useful information via orthogonal experimental design (OED. Differential evolution (DE is a heuristic algorithm. It has shown to be efficient in solving the remote sensing image registration problem. So orthogonal learning differential evolution algorithm (OLDE is efficient for many optimization problems. The OLDE method uses the OL strategy to guide the DE algorithm to discover more useful information. Experiments show that the OLDE method is more robust and efficient for registering remote sensing images.

  10. Algorithms evaluation for transformers differential protection; Avaliacao de algoritmos para protecao diferencial de transformadores

    Energy Technology Data Exchange (ETDEWEB)

    Piovesan, Luis Sergio

    1997-07-01

    The appliance of two algorithms is evaluated, one based in Fourier analysis and other based in a rectangular transform technique over Fourier analysis, to be used in digital logical circuits (digital protection relays) for the purpose of differential protection of power transformers (ANSI 87T). The first chapter has a brief introduction about electrical protection. The second chapter discusses the general problems of transform protection, the development of digital technology and, with more detail, the differential protection associated to this technology. In this chapter are presented the particular aspects of transformers differential protection concerning sensibility, inrush current situations and harmonic distortions caused by transformer core saturations and the differential protection algorithms and their applications in a specific relay design. In chapter three, a method to make possible testing the protection performance is developed. This work applies digital simulations using EMTP to generate current signal of transformer operation and fault conditions. Digital simulation using Matlab is used to simulate the protection. The EMTP generated field signals are sent to the relay under test, furnishing data of normal operation, internal and external faults. The relay logic simulator at Matlab will work this data and so, it will be possible to verify and evaluate the algorithm behavior and performance. Chapter 4 shows the protection operation over simulations of several of transformer operation and fault conditions. The last chapter presents a conclusion about the protection performance, discussions about all the methods applied in this work and suggestions for further studies. (author)

  11. Moving Object Tracking and Avoidance Algorithm for Differential Driving AGV Based on Laser Measurement Technology

    Directory of Open Access Journals (Sweden)

    Pandu Sandi Pratama

    2012-12-01

    Full Text Available This paper proposed an algorithm to track the obstacle position and avoid the moving objects for differential driving Automatic Guided Vehicles (AGV system in industrial environment. This algorithm has several abilities such as: to detect the moving objects, to predict the velocity and direction of moving objects, to predict the collision possibility and to plan the avoidance maneuver. For sensing the local environment and positioning, the laser measurement system LMS-151 and laser navigation system NAV-200 are applied. Based on the measurement results of the sensors, the stationary and moving obstacles are detected and the collision possibility is calculated. The velocity and direction of the obstacle are predicted using Kalman filter algorithm. Collision possibility, time, and position can be calculated by comparing the AGV movement and obstacle prediction result obtained by Kalman filter. Finally the avoidance maneuver using the well known tangent Bug algorithm is decided based on the calculation data. The effectiveness of proposed algorithm is verified using simulation and experiment. Several examples of experiment conditions are presented using stationary obstacle, and moving obstacles. The simulation and experiment results show that the AGV can detect and avoid the obstacles successfully in all experimental condition. [Keywords— Obstacle avoidance, AGV, differential drive, laser measurement system, laser navigation system].

  12. A theoretically exact reconstruction algorithm for helical cone-beam differential phase-contrast computed tomography

    International Nuclear Information System (INIS)

    Li Jing; Sun Yi; Zhu Peiping

    2013-01-01

    Differential phase-contrast computed tomography (DPC-CT) reconstruction problems are usually solved by using parallel-, fan- or cone-beam algorithms. For rod-shaped objects, the x-ray beams cannot recover all the slices of the sample at the same time. Thus, if a rod-shaped sample is required to be reconstructed by the above algorithms, one should alternately perform translation and rotation on this sample, which leads to lower efficiency. The helical cone-beam CT may significantly improve scanning efficiency for rod-shaped objects over other algorithms. In this paper, we propose a theoretically exact filter-backprojection algorithm for helical cone-beam DPC-CT, which can be applied to reconstruct the refractive index decrement distribution of the samples directly from two-dimensional differential phase-contrast images. Numerical simulations are conducted to verify the proposed algorithm. Our work provides a potential solution for inspecting the rod-shaped samples using DPC-CT, which may be applicable with the evolution of DPC-CT equipments. (paper)

  13. Walking pattern classification and walking distance estimation algorithms using gait phase information.

    Science.gov (United States)

    Wang, Jeen-Shing; Lin, Che-Wei; Yang, Ya-Ting C; Ho, Yu-Jen

    2012-10-01

    This paper presents a walking pattern classification and a walking distance estimation algorithm using gait phase information. A gait phase information retrieval algorithm was developed to analyze the duration of the phases in a gait cycle (i.e., stance, push-off, swing, and heel-strike phases). Based on the gait phase information, a decision tree based on the relations between gait phases was constructed for classifying three different walking patterns (level walking, walking upstairs, and walking downstairs). Gait phase information was also used for developing a walking distance estimation algorithm. The walking distance estimation algorithm consists of the processes of step count and step length estimation. The proposed walking pattern classification and walking distance estimation algorithm have been validated by a series of experiments. The accuracy of the proposed walking pattern classification was 98.87%, 95.45%, and 95.00% for level walking, walking upstairs, and walking downstairs, respectively. The accuracy of the proposed walking distance estimation algorithm was 96.42% over a walking distance.

  14. Theoretical and Empirical Analyses of an Improved Harmony Search Algorithm Based on Differential Mutation Operator

    Directory of Open Access Journals (Sweden)

    Longquan Yong

    2012-01-01

    Full Text Available Harmony search (HS method is an emerging metaheuristic optimization algorithm. In this paper, an improved harmony search method based on differential mutation operator (IHSDE is proposed to deal with the optimization problems. Since the population diversity plays an important role in the behavior of evolution algorithm, the aim of this paper is to calculate the expected population mean and variance of IHSDE from theoretical viewpoint. Numerical results, compared with the HSDE, NGHS, show that the IHSDE method has good convergence property over a test-suite of well-known benchmark functions.

  15. A Comparative Study of Differential Evolution, Particle Swarm Optimization, and Evolutionary Algorithms on Numerical Benchmark Problems

    DEFF Research Database (Denmark)

    Vesterstrøm, Jacob Svaneborg; Thomsen, Rene

    2004-01-01

    Several extensions to evolutionary algorithms (EAs) and particle swarm optimization (PSO) have been suggested during the last decades offering improved performance on selected benchmark problems. Recently, another search heuristic termed differential evolution (DE) has shown superior performance...... in several real-world applications. In this paper, we evaluate the performance of DE, PSO, and EAs regarding their general applicability as numerical optimization techniques. The comparison is performed on a suite of 34 widely used benchmark problems. The results from our study show that DE generally...... outperforms the other algorithms. However, on two noisy functions, both DE and PSO were outperformed by the EA....

  16. A differential algebraic integration algorithm for symplectic mappings in systems with three-dimensional magnetic field

    International Nuclear Information System (INIS)

    Chang, P.; Lee, S.Y.; Yan, Y.T.

    2006-01-01

    A differential algebraic integration algorithm is developed for symplectic mapping through a three-dimensional (3-D) magnetic field. The self-consistent reference orbit in phase space is obtained by making a canonical transformation to eliminate the linear part of the Hamiltonian. Transfer maps from the entrance to the exit of any 3-D magnetic field are then obtained through slice-by-slice symplectic integration. The particle phase-space coordinates are advanced by using the integrable polynomial procedure. This algorithm is a powerful tool to attain nonlinear maps for insertion devices in synchrotron light source or complicated magnetic field in the interaction region in high energy colliders

  17. A Differential Algebraic Integration Algorithm for Symplectic Mappings in Systems with Three-Dimensional Magnetic Field

    International Nuclear Information System (INIS)

    Chang, P

    2004-01-01

    A differential algebraic integration algorithm is developed for symplectic mapping through a three-dimensional (3-D) magnetic field. The self-consistent reference orbit in phase space is obtained by making a canonical transformation to eliminate the linear part of the Hamiltonian. Transfer maps from the entrance to the exit of any 3-D magnetic field are then obtained through slice-by-slice symplectic integration. The particle phase-space coordinates are advanced by using the integrable polynomial procedure. This algorithm is a powerful tool to attain nonlinear maps for insertion devices in synchrotron light source or complicated magnetic field in the interaction region in high energy colliders

  18. A Numerical Algorithm for Solving a Four-Point Nonlinear Fractional Integro-Differential Equations

    Directory of Open Access Journals (Sweden)

    Er Gao

    2012-01-01

    Full Text Available We provide a new algorithm for a four-point nonlocal boundary value problem of nonlinear integro-differential equations of fractional order q∈(1,2] based on reproducing kernel space method. According to our work, the analytical solution of the equations is represented in the reproducing kernel space which we construct and so the n-term approximation. At the same time, the n-term approximation is proved to converge to the analytical solution. An illustrative example is also presented, which shows that the new algorithm is efficient and accurate.

  19. Accelerated Genetic Algorithm Solutions Of Some Parametric Families Of Stochastic Differential Equations

    Directory of Open Access Journals (Sweden)

    Eman Ali Hussain

    2015-01-01

    Full Text Available Absract In this project A new method for solving Stochastic Differential Equations SDEs deriving by Wiener process numerically will be construct and implement using Accelerated Genetic Algorithm AGA. An SDE is a differential equation in which one or more of the terms and hence the solutions itself is a stochastic process. Solving stochastic differential equations requires going away from the recognizable deterministic setting of ordinary and partial differential equations into a world where the evolution of a quantity has an inherent random component and where the expected behavior of this quantity can be described in terms of probability distributions. We applied our method on the Ito formula which is equivalent to the SDE to find approximation solution of the SDEs. Numerical experiments illustrate the behavior of the proposed method.

  20. Spline based iterative phase retrieval algorithm for X-ray differential phase contrast radiography.

    Science.gov (United States)

    Nilchian, Masih; Wang, Zhentian; Thuering, Thomas; Unser, Michael; Stampanoni, Marco

    2015-04-20

    Differential phase contrast imaging using grating interferometer is a promising alternative to conventional X-ray radiographic methods. It provides the absorption, differential phase and scattering information of the underlying sample simultaneously. Phase retrieval from the differential phase signal is an essential problem for quantitative analysis in medical imaging. In this paper, we formalize the phase retrieval as a regularized inverse problem, and propose a novel discretization scheme for the derivative operator based on B-spline calculus. The inverse problem is then solved by a constrained regularized weighted-norm algorithm (CRWN) which adopts the properties of B-spline and ensures a fast implementation. The method is evaluated with a tomographic dataset and differential phase contrast mammography data. We demonstrate that the proposed method is able to produce phase image with enhanced and higher soft tissue contrast compared to conventional absorption-based approach, which can potentially provide useful information to mammographic investigations.

  1. Cryptosystem Based On Finger Vein Patterns Using Vas Algorithm

    Directory of Open Access Journals (Sweden)

    G.Kanimozhi

    2015-08-01

    Full Text Available Cryptosystems based on biometrics authentication is developing areas in the field of modernize security schemes. Elastic distortion of fingerprints is one of the major causes for false non-match. While this problem affects all fingerprint identification function it is especially dangerous in opposite identification function such as note list and reduplication function. In such function malicious possessors may purposely distort their fingerprints to evade identification. Distortion rectification or equivalently distortion field estimation is viewed as a regression problem where the input is a distorted fingerprint and the output is the distortion field. The current document deals with the application of finger veins pattern as an approach for possessor confirmation and encryption key generation. The design of the optical imprison scheme by near infrared is described. We propose a step for the location of the vein crossing points and the quantification of the angles between the vein-branches this information is used to generate a personal key that allows the possessor to encrypt information after the confirmation is approved. In order to demonstrate the potential of the suggested approach and model of figure encryption is developed. All action biometric imprison figure presetting key generation and figure encryption are performed on the identical hidden platform adding an important portability and diminishing the execution time.

  2. Algorithmic Information Dynamics of Persistent Patterns and Colliding Particles in the Game of Life

    KAUST Repository

    Zenil, Hector

    2018-02-18

    We demonstrate the way to apply and exploit the concept of \\\\textit{algorithmic information dynamics} in the characterization and classification of dynamic and persistent patterns, motifs and colliding particles in, without loss of generalization, Conway\\'s Game of Life (GoL) cellular automaton as a case study. We analyze the distribution of prevailing motifs that occur in GoL from the perspective of algorithmic probability. We demonstrate how the tools introduced are an alternative to computable measures such as entropy and compression algorithms which are often nonsensitive to small changes and features of non-statistical nature in the study of evolving complex systems and their emergent structures.

  3. Long-Term Scheduling of Large-Scale Cascade Hydropower Stations Using Improved Differential Evolution Algorithm

    Directory of Open Access Journals (Sweden)

    Xiaohao Wen

    2018-03-01

    Full Text Available Long-term scheduling of large cascade hydropower stations (LSLCHS is a complex problem of high dimension, nonlinearity, coupling and complex constraint. In view of the above problem, we present an improved differential evolution (iLSHADE algorithm based on LSHADE, a state-of-the-art evolutionary algorithm. iLSHADE uses new mutation strategies “current to pbest/2-rand” to obtain wider search range and accelerate convergence with the preventing individual repeated failure evolution (PIRFE strategy. The handling of complicated constraints strategy of ε-constrained method is presented to handle outflow, water level and output constraints in the cascade reservoir operation. Numerical experiments of 10 benchmark functions have been done, showing that iLSHADE has stable convergence and high efficiency. Furthermore, we demonstrate the performance of the iLSHADE algorithm by comparing it with other improved differential evolution algorithms for LSLCHS in four large hydropower stations of the Jinsha River. With the applications of iLSHADE in reservoir operation, LSLCHS can obtain more power generation benefit than other alternatives in dry, normal, and wet years. The results of numerical experiments and case studies show that the iLSHADE has a distinct optimization effect and good stability, and it is a valid and reliable tool to solve LSLCHS problem.

  4. Parameter Identification of the 2-Chlorophenol Oxidation Model Using Improved Differential Search Algorithm

    Directory of Open Access Journals (Sweden)

    Guang-zhou Chen

    2015-01-01

    Full Text Available Parameter identification plays a crucial role for simulating and using model. This paper firstly carried out the sensitivity analysis of the 2-chlorophenol oxidation model in supercritical water using the Monte Carlo method. Then, to address the nonlinearity of the model, two improved differential search (DS algorithms were proposed to carry out the parameter identification of the model. One strategy is to adopt the Latin hypercube sampling method to replace the uniform distribution of initial population; the other is to combine DS with simplex method. The results of sensitivity analysis reveal the sensitivity and the degree of difficulty identified for every model parameter. Furthermore, the posteriori probability distribution of parameters and the collaborative relationship between any two parameters can be obtained. To verify the effectiveness of the improved algorithms, the optimization performance of improved DS in kinetic parameter estimation is studied and compared with that of the basic DS algorithm, differential evolution, artificial bee colony optimization, and quantum-behaved particle swarm optimization. And the experimental results demonstrate that the DS with the Latin hypercube sampling method does not present better performance, while the hybrid methods have the advantages of strong global search ability and local search ability and are more effective than the other algorithms.

  5. Genetic algorithm for the optimization of the loading pattern for reactor core fuel management

    International Nuclear Information System (INIS)

    Zhou Sheng; Hu Yongming; zheng Wenxiang

    2000-01-01

    The paper discusses the application of a genetic algorithm to the optimization of the loading pattern for in-core fuel management with the NP characteristics. The algorithm develops a matrix model for the fuel assembly loading pattern. The burnable poisons matrix was assigned randomly considering the distributed nature of the poisons. A method based on the traveling salesman problem was used to solve the problem. A integrated code for in-core fuel management was formed by combining this code with a reactor physics code

  6. Comparison of optimization of loading patterns on the basis of SA and PMA algorithms

    International Nuclear Information System (INIS)

    Beliczai, Botond

    2007-01-01

    Optimization of loading patterns is a very important task from economical point of view in a nuclear power plant. The optimization algorithms used for this purpose can be categorized basically into two categories: deterministic ones and stochastic ones. In the Paks nuclear power plant a deterministic optimization procedure is used to optimize the loading pattern at BOC, so that the core would have maximal reactivity reserve. To the group of stochastic optimization procedures belong mainly simulated annealing (SA) procedures and genetic algorithms (GA). There are new procedures as well, which try to combine the advantages of SAs and GAs. One of them is called population mutation annealing algorithm (PMA). In the Paks NPP we would like to introduce fuel assemblies including burnable poison (Gd) in the near future. In order to be able to find the optimal loading pattern (or near-optimal loading patterns) in that case, we have to optimize our core not only for objective functions defined at BOC, but at EOC as well. For this purpose I used stochastic algorithms (SA and PMA) to investigate loading pattern optimization results for different objective functions at BOC. (author)

  7. Algorithms

    Indian Academy of Sciences (India)

    polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming.

  8. A stochastic model for identifying differential gene pair co-expression patterns in prostate cancer progression

    Directory of Open Access Journals (Sweden)

    Mao Yu

    2009-07-01

    Full Text Available Abstract Background The identification of gene differential co-expression patterns between cancer stages is a newly developing method to reveal the underlying molecular mechanisms of carcinogenesis. Most researches of this subject lack an algorithm useful for performing a statistical significance assessment involving cancer progression. Lacking this specific algorithm is apparently absent in identifying precise gene pairs correlating to cancer progression. Results In this investigation we studied gene pair co-expression change by using a stochastic process model for approximating the underlying dynamic procedure of the co-expression change during cancer progression. Also, we presented a novel analytical method named 'Stochastic process model for Identifying differentially co-expressed Gene pair' (SIG method. This method has been applied to two well known prostate cancer data sets: hormone sensitive versus hormone resistant, and healthy versus cancerous. From these data sets, 428,582 gene pairs and 303,992 gene pairs were identified respectively. Afterwards, we used two different current statistical methods to the same data sets, which were developed to identify gene pair differential co-expression and did not consider cancer progression in algorithm. We then compared these results from three different perspectives: progression analysis, gene pair identification effectiveness analysis, and pathway enrichment analysis. Statistical methods were used to quantify the quality and performance of these different perspectives. They included: Re-identification Scale (RS and Progression Score (PS in progression analysis, True Positive Rate (TPR in gene pair analysis, and Pathway Enrichment Score (PES in pathway analysis. Our results show small values of RS and large values of PS, TPR, and PES; thus, suggesting that gene pairs identified by the SIG method are highly correlated with cancer progression, and highly enriched in disease-specific pathways. From

  9. Comparison of phase unwrapping algorithms for topography reconstruction based on digital speckle pattern interferometry

    Science.gov (United States)

    Li, Yuanbo; Cui, Xiaoqian; Wang, Hongbei; Zhao, Mengge; Ding, Hongbin

    2017-10-01

    Digital speckle pattern interferometry (DSPI) can diagnose the topography evolution in real-time, continuous and non-destructive, and has been considered as a most promising technique for Plasma-Facing Components (PFCs) topography diagnostic under the complicated environment of tokamak. It is important for the study of digital speckle pattern interferometry to enhance speckle patterns and obtain the real topography of the ablated crater. In this paper, two kinds of numerical model based on flood-fill algorithm has been developed to obtain the real profile by unwrapping from the wrapped phase in speckle interference pattern, which can be calculated through four intensity images by means of 4-step phase-shifting technique. During the process of phase unwrapping by means of flood-fill algorithm, since the existence of noise pollution, and other inevitable factors will lead to poor quality of the reconstruction results, this will have an impact on the authenticity of the restored topography. The calculation of the quality parameters was introduced to obtain the quality-map from the wrapped phase map, this work presents two different methods to calculate the quality parameters. Then quality parameters are used to guide the path of flood-fill algorithm, and the pixels with good quality parameters are given priority calculation, so that the quality of speckle interference pattern reconstruction results are improved. According to the comparison between the flood-fill algorithm which is suitable for speckle pattern interferometry and the quality-guided flood-fill algorithm (with two different calculation approaches), the errors which caused by noise pollution and the discontinuous of the strips were successfully reduced.

  10. A multi-pattern hash-binary hybrid algorithm for URL matching in the HTTP protocol.

    Directory of Open Access Journals (Sweden)

    Ping Zeng

    Full Text Available In this paper, based on our previous multi-pattern uniform resource locator (URL binary-matching algorithm called HEM, we propose an improved multi-pattern matching algorithm called MH that is based on hash tables and binary tables. The MH algorithm can be applied to the fields of network security, data analysis, load balancing, cloud robotic communications, and so on-all of which require string matching from a fixed starting position. Our approach effectively solves the performance problems of the classical multi-pattern matching algorithms. This paper explores ways to improve string matching performance under the HTTP protocol by using a hash method combined with a binary method that transforms the symbol-space matching problem into a digital-space numerical-size comparison and hashing problem. The MH approach has a fast matching speed, requires little memory, performs better than both the classical algorithms and HEM for matching fields in an HTTP stream, and it has great promise for use in real-world applications.

  11. Length-Bounded Hybrid CPU/GPU Pattern Matching Algorithm for Deep Packet Inspection

    Directory of Open Access Journals (Sweden)

    Yi-Shan Lin

    2017-01-01

    Full Text Available Since frequent communication between applications takes place in high speed networks, deep packet inspection (DPI plays an important role in the network application awareness. The signature-based network intrusion detection system (NIDS contains a DPI technique that examines the incoming packet payloads by employing a pattern matching algorithm that dominates the overall inspection performance. Existing studies focused on implementing efficient pattern matching algorithms by parallel programming on software platforms because of the advantages of lower cost and higher scalability. Either the central processing unit (CPU or the graphic processing unit (GPU were involved. Our studies focused on designing a pattern matching algorithm based on the cooperation between both CPU and GPU. In this paper, we present an enhanced design for our previous work, a length-bounded hybrid CPU/GPU pattern matching algorithm (LHPMA. In the preliminary experiment, the performance and comparison with the previous work are displayed, and the experimental results show that the LHPMA can achieve not only effective CPU/GPU cooperation but also higher throughput than the previous method.

  12. Multiwavelength Absolute Phase Retrieval from Noisy Diffractive Patterns: Wavelength Multiplexing Algorithm

    Directory of Open Access Journals (Sweden)

    Vladimir Katkovnik

    2018-05-01

    Full Text Available We study the problem of multiwavelength absolute phase retrieval from noisy diffraction patterns. The system is lensless with multiwavelength coherent input light beams and random phase masks applied for wavefront modulation. The light beams are formed by light sources radiating all wavelengths simultaneously. A sensor equipped by a Color Filter Array (CFA is used for spectral measurement registration. The developed algorithm targeted on optimal phase retrieval from noisy observations is based on maximum likelihood technique. The algorithm is specified for Poissonian and Gaussian noise distributions. One of the key elements of the algorithm is an original sparse modeling of the multiwavelength complex-valued wavefronts based on the complex-domain block-matching 3D filtering. Presented numerical experiments are restricted to noisy Poissonian observations. They demonstrate that the developed algorithm leads to effective solutions explicitly using the sparsity for noise suppression and enabling accurate reconstruction of absolute phase of high-dynamic range.

  13. An implementation of differential evolution algorithm for inversion of geoelectrical data

    Science.gov (United States)

    Balkaya, Çağlayan

    2013-11-01

    Differential evolution (DE), a population-based evolutionary algorithm (EA) has been implemented to invert self-potential (SP) and vertical electrical sounding (VES) data sets. The algorithm uses three operators including mutation, crossover and selection similar to genetic algorithm (GA). Mutation is the most important operator for the success of DE. Three commonly used mutation strategies including DE/best/1 (strategy 1), DE/rand/1 (strategy 2) and DE/rand-to-best/1 (strategy 3) were applied together with a binomial type crossover. Evolution cycle of DE was realized without boundary constraints. For the test studies performed with SP data, in addition to both noise-free and noisy synthetic data sets two field data sets observed over the sulfide ore body in the Malachite mine (Colorado) and over the ore bodies in the Neem-Ka Thana cooper belt (India) were considered. VES test studies were carried out using synthetically produced resistivity data representing a three-layered earth model and a field data set example from Gökçeada (Turkey), which displays a seawater infiltration problem. Mutation strategies mentioned above were also extensively tested on both synthetic and field data sets in consideration. Of these, strategy 1 was found to be the most effective strategy for the parameter estimation by providing less computational cost together with a good accuracy. The solutions obtained by DE for the synthetic cases of SP were quite consistent with particle swarm optimization (PSO) which is a more widely used population-based optimization algorithm than DE in geophysics. Estimated parameters of SP and VES data were also compared with those obtained from Metropolis-Hastings (M-H) sampling algorithm based on simulated annealing (SA) without cooling to clarify uncertainties in the solutions. Comparison to the M-H algorithm shows that DE performs a fast approximate posterior sampling for the case of low-dimensional inverse geophysical problems.

  14. Amplitude inversion of the 2D analytic signal of magnetic anomalies through the differential evolution algorithm

    Science.gov (United States)

    Ekinci, Yunus Levent; Özyalın, Şenol; Sındırgı, Petek; Balkaya, Çağlayan; Göktürkler, Gökhan

    2017-12-01

    In this work, analytic signal amplitude (ASA) inversion of total field magnetic anomalies has been achieved by differential evolution (DE) which is a population-based evolutionary metaheuristic algorithm. Using an elitist strategy, the applicability and effectiveness of the proposed inversion algorithm have been evaluated through the anomalies due to both hypothetical model bodies and real isolated geological structures. Some parameter tuning studies relying mainly on choosing the optimum control parameters of the algorithm have also been performed to enhance the performance of the proposed metaheuristic. Since ASAs of magnetic anomalies are independent of both ambient field direction and the direction of magnetization of the causative sources in a two-dimensional (2D) case, inversions of synthetic noise-free and noisy single model anomalies have produced satisfactory solutions showing the practical applicability of the algorithm. Moreover, hypothetical studies using multiple model bodies have clearly showed that the DE algorithm is able to cope with complicated anomalies and some interferences from neighbouring sources. The proposed algorithm has then been used to invert small- (120 m) and large-scale (40 km) magnetic profile anomalies of an iron deposit (Kesikköprü-Bala, Turkey) and a deep-seated magnetized structure (Sea of Marmara, Turkey), respectively to determine depths, geometries and exact origins of the source bodies. Inversion studies have yielded geologically reasonable solutions which are also in good accordance with the results of normalized full gradient and Euler deconvolution techniques. Thus, we propose the use of DE not only for the amplitude inversion of 2D analytical signals of magnetic profile anomalies having induced or remanent magnetization effects but also the low-dimensional data inversions in geophysics. A part of this paper was presented as an abstract at the 2nd International Conference on Civil and Environmental Engineering, 8

  15. Local fractional variational iteration algorithm iii for the diffusion model associated with non-differentiable heat transfer

    Directory of Open Access Journals (Sweden)

    Meng Zhi-Jun

    2016-01-01

    Full Text Available This paper addresses a new application of the local fractional variational iteration algorithm III to solve the local fractional diffusion equation defined on Cantor sets associated with non-differentiable heat transfer.

  16. Performance evaluation of Genetic Algorithms on loading pattern optimization of PWRs

    International Nuclear Information System (INIS)

    Tombakoglu, M.; Bekar, K.B.; Erdemli, A.O.

    2001-01-01

    Genetic Algorithm (GA) based systems are used for search and optimization problems. There are several applications of GAs in literature successfully applied for loading pattern optimization problems. In this study, we have selected loading pattern optimization problem of Pressurised Water Reactor (PWR). The main objective of this work is to evaluate the performance of Genetic Algorithm operators such as regional crossover, crossover and mutation, and selection and construction of initial population and its size for PWR loading pattern optimization problems. The performance of GA with antithetic variates is compared to traditional GA. Antithetic variates are used to generate the initial population and its use with GA operators are also discussed. Finally, the results of multi-cycle optimization problems are discussed for objective function taking into account cycle burn-up and discharge burn-up.(author)

  17. Identification of two-phase flow pattern by using specific spatial frequency of differential pressure signal

    International Nuclear Information System (INIS)

    Han Bin; Tong Yunxian; Wu Shaorong

    1992-11-01

    It is a classical method by using analysis of differential pressure fluctuation signal to identify two-phase flow pattern. The method which uses trait peak in the frequency-domain will result confusion between bubble flow and intermittent flow due to the influence of gas speed. Considering the spatial geometric significance of two-phase slow patterns and using the differential pressure gauge as a sensor, the Strouhal number 'Sr' is taken as the basis for distinguishing flow patterns. Using Strouhal number 'Sr' to identify flow pattern has clear physical meaning. The experimental results using the spatial analytical technique to measure the flow pattern are also given

  18. Parameter estimation by Differential Search Algorithm from horizontal loop electromagnetic (HLEM) data

    Science.gov (United States)

    Alkan, Hilal; Balkaya, Çağlayan

    2018-02-01

    We present an efficient inversion tool for parameter estimation from horizontal loop electromagnetic (HLEM) data using Differential Search Algorithm (DSA) which is a swarm-intelligence-based metaheuristic proposed recently. The depth, dip, and origin of a thin subsurface conductor causing the anomaly are the parameters estimated by the HLEM method commonly known as Slingram. The applicability of the developed scheme was firstly tested on two synthetically generated anomalies with and without noise content. Two control parameters affecting the convergence characteristic to the solution of the algorithm were tuned for the so-called anomalies including one and two conductive bodies, respectively. Tuned control parameters yielded more successful statistical results compared to widely used parameter couples in DSA applications. Two field anomalies measured over a dipping graphitic shale from Northern Australia were then considered, and the algorithm provided the depth estimations being in good agreement with those of previous studies and drilling information. Furthermore, the efficiency and reliability of the results obtained were investigated via probability density function. Considering the results obtained, we can conclude that DSA characterized by the simple algorithmic structure is an efficient and promising metaheuristic for the other relatively low-dimensional geophysical inverse problems. Finally, the researchers after being familiar with the content of developed scheme displaying an easy to use and flexible characteristic can easily modify and expand it for their scientific optimization problems.

  19. Intercept Algorithm for Maneuvering Targets Based on Differential Geometry and Lyapunov Theory

    Directory of Open Access Journals (Sweden)

    Yunes Sh. ALQUDSI

    2018-03-01

    Full Text Available Nowadays, the homing guidance is utilized in the existed and under development air defense systems (ADS to effectively intercept the targets. The targets became smarter and capable to fly and maneuver professionally and the tendency to design missile with a small warhead became greater, then there is a pressure to produce a more precise and accurate missile guidance system based on intelligent algorithms to ensure effective interception of highly maneuverable targets. The aim of this paper is to present an intelligent guidance algorithm that effectively and precisely intercept the maneuverable and smart targets by virtue of the differential geometry (DG concepts. The intercept geometry and engagement kinematics, in addition to the direct intercept condition are developed and expressed in DG terms. The guidance algorithm is then developed by virtue of DG and Lyapunov theory. The study terminates with 2D engagement simulation with illustrative examples, to demonstrate that, the derived DG guidance algorithm is a generalized guidance approach and the well-known proportional navigation (PN guidance law is a subset of this approach.

  20. Multi-objective optimum design of fast tool servo based on improved differential evolution algorithm

    International Nuclear Information System (INIS)

    Zhu, Zhiwei; Zhou, Xiaoqin; Liu, Qiang; Zhao, Shaoxin

    2011-01-01

    The flexure-based mechanism is a promising realization of fast tool servo (FTS), and the optimum determination of flexure hinge parameters is one of the most important elements in the FTS design. This paper presents a multi-objective optimization approach to optimizing the dimension and position parameters of the flexure-based mechanism, which is based on the improved differential evolution algorithm embedding chaos and nonlinear simulated anneal algorithm. The results of optimum design show that the proposed algorithm has excellent performance and a well-balanced compromise is made between two conflicting objectives, the stroke and natural frequency of the FTS mechanism. The validation tests based on finite element analysis (FEA) show good agreement with the results obtained by using the proposed theoretical algorithm of this paper. Finally, a series of experimental tests are conducted to validate the design process and assess the performance of the FTS mechanism. The designed FTS reaches up to a stroke of 10.25 μm with at least 2 kHz bandwidth. Both of the FEA and experimental results demonstrate that the parameters of the flexure-based mechanism determined by the proposed approaches can achieve the specified performance and the proposed approach is suitable for the optimum design of FTS mechanism and of excellent performances

  1. A dynamical regularization algorithm for solving inverse source problems of elliptic partial differential equations

    Science.gov (United States)

    Zhang, Ye; Gong, Rongfang; Cheng, Xiaoliang; Gulliksson, Mårten

    2018-06-01

    This study considers the inverse source problem for elliptic partial differential equations with both Dirichlet and Neumann boundary data. The unknown source term is to be determined by additional boundary conditions. Unlike the existing methods found in the literature, which usually employ the first-order in time gradient-like system (such as the steepest descent methods) for numerically solving the regularized optimization problem with a fixed regularization parameter, we propose a novel method with a second-order in time dissipative gradient-like system and a dynamical selected regularization parameter. A damped symplectic scheme is proposed for the numerical solution. Theoretical analysis is given for both the continuous model and the numerical algorithm. Several numerical examples are provided to show the robustness of the proposed algorithm.

  2. An Improved Binary Differential Evolution Algorithm to Infer Tumor Phylogenetic Trees.

    Science.gov (United States)

    Liang, Ying; Liao, Bo; Zhu, Wen

    2017-01-01

    Tumourigenesis is a mutation accumulation process, which is likely to start with a mutated founder cell. The evolutionary nature of tumor development makes phylogenetic models suitable for inferring tumor evolution through genetic variation data. Copy number variation (CNV) is the major genetic marker of the genome with more genes, disease loci, and functional elements involved. Fluorescence in situ hybridization (FISH) accurately measures multiple gene copy number of hundreds of single cells. We propose an improved binary differential evolution algorithm, BDEP, to infer tumor phylogenetic tree based on FISH platform. The topology analysis of tumor progression tree shows that the pathway of tumor subcell expansion varies greatly during different stages of tumor formation. And the classification experiment shows that tree-based features are better than data-based features in distinguishing tumor. The constructed phylogenetic trees have great performance in characterizing tumor development process, which outperforms other similar algorithms.

  3. Design of 2-D Recursive Filters Using Self-adaptive Mutation Differential Evolution Algorithm

    Directory of Open Access Journals (Sweden)

    Lianghong Wu

    2011-08-01

    Full Text Available This paper investigates a novel approach to the design of two-dimensional recursive digital filters using differential evolution (DE algorithm. The design task is reformulated as a constrained minimization problem and is solved by an Self-adaptive Mutation DE algorithm (SAMDE, which adopts an adaptive mutation operator that combines with the advantages of the DE/rand/1/bin strategy and the DE/best/2/bin strategy. As a result, its convergence performance is improved greatly. Numerical experiment results confirm the conclusion. The proposedSAMDE approach is effectively applied to test a numerical example and is compared with previous design methods. The computational experiments show that the SAMDE approach can obtain better results than previous design methods.

  4. Optimal Location and Sizing of UPQC in Distribution Networks Using Differential Evolution Algorithm

    Directory of Open Access Journals (Sweden)

    Seyed Abbas Taher

    2012-01-01

    Full Text Available Differential evolution (DE algorithm is used to determine optimal location of unified power quality conditioner (UPQC considering its size in the radial distribution systems. The problem is formulated to find the optimum location of UPQC based on an objective function (OF defined for improving of voltage and current profiles, reducing power loss and minimizing the investment costs considering the OF's weighting factors. Hence, a steady-state model of UPQC is derived to set in forward/backward sweep load flow. Studies are performed on two IEEE 33-bus and 69-bus standard distribution networks. Accuracy was evaluated by reapplying the procedures using both genetic (GA and immune algorithms (IA. Comparative results indicate that DE is capable of offering a nearer global optimal in minimizing the OF and reaching all the desired conditions than GA and IA.

  5. Distributed Storage Algorithm for Geospatial Image Data Based on Data Access Patterns.

    Directory of Open Access Journals (Sweden)

    Shaoming Pan

    Full Text Available Declustering techniques are widely used in distributed environments to reduce query response time through parallel I/O by splitting large files into several small blocks and then distributing those blocks among multiple storage nodes. Unfortunately, however, many small geospatial image data files cannot be further split for distributed storage. In this paper, we propose a complete theoretical system for the distributed storage of small geospatial image data files based on mining the access patterns of geospatial image data using their historical access log information. First, an algorithm is developed to construct an access correlation matrix based on the analysis of the log information, which reveals the patterns of access to the geospatial image data. Then, a practical heuristic algorithm is developed to determine a reasonable solution based on the access correlation matrix. Finally, a number of comparative experiments are presented, demonstrating that our algorithm displays a higher total parallel access probability than those of other algorithms by approximately 10-15% and that the performance can be further improved by more than 20% by simultaneously applying a copy storage strategy. These experiments show that the algorithm can be applied in distributed environments to help realize parallel I/O and thereby improve system performance.

  6. Distributed Storage Algorithm for Geospatial Image Data Based on Data Access Patterns.

    Science.gov (United States)

    Pan, Shaoming; Li, Yongkai; Xu, Zhengquan; Chong, Yanwen

    2015-01-01

    Declustering techniques are widely used in distributed environments to reduce query response time through parallel I/O by splitting large files into several small blocks and then distributing those blocks among multiple storage nodes. Unfortunately, however, many small geospatial image data files cannot be further split for distributed storage. In this paper, we propose a complete theoretical system for the distributed storage of small geospatial image data files based on mining the access patterns of geospatial image data using their historical access log information. First, an algorithm is developed to construct an access correlation matrix based on the analysis of the log information, which reveals the patterns of access to the geospatial image data. Then, a practical heuristic algorithm is developed to determine a reasonable solution based on the access correlation matrix. Finally, a number of comparative experiments are presented, demonstrating that our algorithm displays a higher total parallel access probability than those of other algorithms by approximately 10-15% and that the performance can be further improved by more than 20% by simultaneously applying a copy storage strategy. These experiments show that the algorithm can be applied in distributed environments to help realize parallel I/O and thereby improve system performance.

  7. Day-ahead distributed energy resource scheduling using differential search algorithm

    DEFF Research Database (Denmark)

    Soares, J.; Lobo, C.; Silva, M.

    2015-01-01

    The number of dispersed energy resources is growing every day, such as the use of more distributed generators. This paper deals with energy resource scheduling model in future smart grids. The methodology can be used by virtual power players (VPPs) considering day-ahead time horizon. This method...... considers that energy resources are managed by a VPP which establishes contracts with their owners. The full AC power flow calculation included in the model takes into account network constraints. This paper presents an application of differential search algorithm (DSA) for solving the day-ahead scheduling...

  8. A Numerical Algorithm for Solving a Four-Point Nonlinear Fractional Integro-Differential Equations

    OpenAIRE

    Gao, Er; Song, Songhe; Zhang, Xinjian

    2012-01-01

    We provide a new algorithm for a four-point nonlocal boundary value problem of nonlinear integro-differential equations of fractional order q∈(1,2] based on reproducing kernel space method. According to our work, the analytical solution of the equations is represented in the reproducing kernel space which we construct and so the n-term approximation. At the same time, the n-term approximation is proved to converge to the analytical solution. An illustrative example is also presented, which sh...

  9. Algorithms of estimation for nonlinear systems a differential and algebraic viewpoint

    CERN Document Server

    Martínez-Guerra, Rafael

    2017-01-01

    This book acquaints readers with recent developments in dynamical systems theory and its applications, with a strong focus on the control and estimation of nonlinear systems. Several algorithms are proposed and worked out for a set of model systems, in particular so-called input-affine or bilinear systems, which can serve to approximate a wide class of nonlinear control systems. These can either take the form of state space models or be represented by an input-output equation. The approach taken here further highlights the role of modern mathematical and conceptual tools, including differential algebraic theory, observer design for nonlinear systems and generalized canonical forms.

  10. Recent developments in structure-preserving algorithms for oscillatory differential equations

    CERN Document Server

    Wu, Xinyuan

    2018-01-01

    The main theme of this book is recent progress in structure-preserving algorithms for solving initial value problems of oscillatory differential equations arising in a variety of research areas, such as astronomy, theoretical physics, electronics, quantum mechanics and engineering. It systematically describes the latest advances in the development of structure-preserving integrators for oscillatory differential equations, such as structure-preserving exponential integrators, functionally fitted energy-preserving integrators, exponential Fourier collocation methods, trigonometric collocation methods, and symmetric and arbitrarily high-order time-stepping methods. Most of the material presented here is drawn from the recent literature. Theoretical analysis of the newly developed schemes shows their advantages in the context of structure preservation. All the new methods introduced in this book are proven to be highly effective compared with the well-known codes in the scientific literature. This book also addre...

  11. Identification of time-varying nonlinear systems using differential evolution algorithm

    DEFF Research Database (Denmark)

    Perisic, Nevena; Green, Peter L; Worden, Keith

    2013-01-01

    (DE) algorithm for the identification of time-varying systems. DE is an evolutionary optimisation method developed to perform direct search in a continuous space without requiring any derivative estimation. DE is modified so that the objective function changes with time to account for the continuing......, thus identification of time-varying systems with nonlinearities can be a very challenging task. In order to avoid conventional least squares and gradient identification methods which require uni-modal and double differentiable objective functions, this work proposes a modified differential evolution...... inclusion of new data within an error metric. This paper presents results of identification of a time-varying SDOF system with Coulomb friction using simulated noise-free and noisy data for the case of time-varying friction coefficient, stiffness and damping. The obtained results are promising and the focus...

  12. Algorithms bio-inspired for the pattern obtention of control bars in BWR reactors

    International Nuclear Information System (INIS)

    Ortiz, J.J.; Perusquia, R.; Montes, J.L.

    2003-01-01

    In this work methods based on Genetic Algorithms and Systems based on ant colonies for the obtention of the patterns of control bars of an equilibrium cycle of 18 months for the Laguna Verde nuclear power station are presented. A comparison of obtained results with the methods and with those of design of such equilibrium cycle is presented. As consequence of the study, it was found that the algorithm based on the ant colonies reached to diminish the coast down period (decrease of power at the end of the cycle) in five and half days with respect to the original design what represents an annual saving of $US 100,000. (Author)

  13. Dyslipidemia patterns are differentially associated with dietary factors.

    Science.gov (United States)

    Song, SuJin; Paik, Hee Young; Park, Minseon; Song, YoonJu

    2016-08-01

    Dyslipidemia, a strong predictor of cardiovascular diseases, is prevalent among Korean adults, but little is known about the associations between overall lipid profiles and dietary factors. We identified dyslipidemia patterns among lipid indicators and examined dietary factors associated with dyslipidemia patterns in Korean adults. Subjects in this cross-sectional study were recruited from the Family Medicine Division or the Health Examination Center of the general hospital in Seoul between 2010 and 2012. Measurements of biochemical and dietary variables repeated three times were collected from a total of 138 subjects at 3- to 4-month intervals when the subjects visited the hospital. Dietary intake data were obtained using 24-h recalls. In order to estimate typical values for biochemical and dietary variables, the averages of repeated measures for each subject were calculated. To identify dyslipidemia patterns, factor analysis was used based on total cholesterol (TC), low-density lipoprotein cholesterol (LDLC), triglycerides (TG), and high-density lipoprotein cholesterol (HDLC). Two dyslipidemia patterns, (1) TC & LDLC and (2) TG & HDLC, were identified. Dietary fat and cholesterol intakes were positively associated with the TC & LDLC pattern score, but not associated with the TG & HDLC pattern score. The TG & HDLC pattern was significantly associated with low intakes of calcium, potassium, milk and dairy products. Two dyslipidemia patterns were associated with dietary factors in Korean adults. Further studies should investigate specific dietary recommendations according to lipid profiles in the prevention and management of dyslipidemia in Korea. Copyright © 2015 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

  14. Iterative Observer-based Estimation Algorithms for Steady-State Elliptic Partial Differential Equation Systems

    KAUST Repository

    Majeed, Muhammad Usman

    2017-07-19

    Steady-state elliptic partial differential equations (PDEs) are frequently used to model a diverse range of physical phenomena. The source and boundary data estimation problems for such PDE systems are of prime interest in various engineering disciplines including biomedical engineering, mechanics of materials and earth sciences. Almost all existing solution strategies for such problems can be broadly classified as optimization-based techniques, which are computationally heavy especially when the problems are formulated on higher dimensional space domains. However, in this dissertation, feedback based state estimation algorithms, known as state observers, are developed to solve such steady-state problems using one of the space variables as time-like. In this regard, first, an iterative observer algorithm is developed that sweeps over regular-shaped domains and solves boundary estimation problems for steady-state Laplace equation. It is well-known that source and boundary estimation problems for the elliptic PDEs are highly sensitive to noise in the data. For this, an optimal iterative observer algorithm, which is a robust counterpart of the iterative observer, is presented to tackle the ill-posedness due to noise. The iterative observer algorithm and the optimal iterative algorithm are then used to solve source localization and estimation problems for Poisson equation for noise-free and noisy data cases respectively. Next, a divide and conquer approach is developed for three-dimensional domains with two congruent parallel surfaces to solve the boundary and the source data estimation problems for the steady-state Laplace and Poisson kind of systems respectively. Theoretical results are shown using a functional analysis framework, and consistent numerical simulation results are presented for several test cases using finite difference discretization schemes.

  15. A polynomial time biclustering algorithm for finding approximate expression patterns in gene expression time series

    Directory of Open Access Journals (Sweden)

    Madeira Sara C

    2009-06-01

    Full Text Available Abstract Background The ability to monitor the change in expression patterns over time, and to observe the emergence of coherent temporal responses using gene expression time series, obtained from microarray experiments, is critical to advance our understanding of complex biological processes. In this context, biclustering algorithms have been recognized as an important tool for the discovery of local expression patterns, which are crucial to unravel potential regulatory mechanisms. Although most formulations of the biclustering problem are NP-hard, when working with time series expression data the interesting biclusters can be restricted to those with contiguous columns. This restriction leads to a tractable problem and enables the design of efficient biclustering algorithms able to identify all maximal contiguous column coherent biclusters. Methods In this work, we propose e-CCC-Biclustering, a biclustering algorithm that finds and reports all maximal contiguous column coherent biclusters with approximate expression patterns in time polynomial in the size of the time series gene expression matrix. This polynomial time complexity is achieved by manipulating a discretized version of the original matrix using efficient string processing techniques. We also propose extensions to deal with missing values, discover anticorrelated and scaled expression patterns, and different ways to compute the errors allowed in the expression patterns. We propose a scoring criterion combining the statistical significance of expression patterns with a similarity measure between overlapping biclusters. Results We present results in real data showing the effectiveness of e-CCC-Biclustering and its relevance in the discovery of regulatory modules describing the transcriptomic expression patterns occurring in Saccharomyces cerevisiae in response to heat stress. In particular, the results show the advantage of considering approximate patterns when compared to state of

  16. Algorithm for solving the linear Cauchy problem for large systems of ordinary differential equations with the use of parallel computations

    Energy Technology Data Exchange (ETDEWEB)

    Moryakov, A. V., E-mail: sailor@orc.ru [National Research Centre Kurchatov Institute (Russian Federation)

    2016-12-15

    An algorithm for solving the linear Cauchy problem for large systems of ordinary differential equations is presented. The algorithm for systems of first-order differential equations is implemented in the EDELWEISS code with the possibility of parallel computations on supercomputers employing the MPI (Message Passing Interface) standard for the data exchange between parallel processes. The solution is represented by a series of orthogonal polynomials on the interval [0, 1]. The algorithm is characterized by simplicity and the possibility to solve nonlinear problems with a correction of the operator in accordance with the solution obtained in the previous iterative process.

  17. Algorithms

    Indian Academy of Sciences (India)

    to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted algorithm design paradigms. In this article, we illustrate algorithm design techniques such as balancing, greedy strategy, dynamic programming strategy, and backtracking or traversal of ...

  18. DSTATCOM allocation in distribution networks considering reconfiguration using differential evolution algorithm

    International Nuclear Information System (INIS)

    Jazebi, S.; Hosseinian, S.H.; Vahidi, B.

    2011-01-01

    Highlights: → Reconfiguration and DSTATCOM allocation are implemented for RDS planning. → Differential evolution algorithm is applied to solve the nonlinear problem. → Optimal status of tie switches, DSTATCOM size and location are determined. → The goal is to minimize network losses and to improve voltage profile. → The results show the effectiveness of the proposed method to satisfy objectives. -- Abstract: The main idea in distribution network reconfiguration is usually to reduce loss by changing the status of sectionalizing switches and determining appropriate tie switches. Recently Distribution FACTS (DFACTS) devices such as DSTATCOM also have been planned for loss reduction and voltage profile improvement in steady state conditions. This paper implements a combinatorial process based on reconfiguration and DSTATCOM allocation in order to mitigate losses and improve voltage profile in power distribution networks. The distribution system tie switches, DSTATCOM location and size have been optimally determined to obtain an appropriate operational condition. Differential evolution algorithm (DEA) has been used to solve and overcome the complicity of this combinatorial nonlinear optimization problem. To validate the accuracy of results a comparison with particle swarm optimization (PSO) has been made. Simulations have been applied on 69 and 83 busses distribution test systems. All optimization results show the effectiveness of the combinatorial approach in loss reduction and voltage profile improvement.

  19. Relating neuronal firing patterns to functional differentiation of cerebral cortex.

    Directory of Open Access Journals (Sweden)

    Shigeru Shinomoto

    2009-07-01

    Full Text Available It has been empirically established that the cerebral cortical areas defined by Brodmann one hundred years ago solely on the basis of cellular organization are closely correlated to their function, such as sensation, association, and motion. Cytoarchitectonically distinct cortical areas have different densities and types of neurons. Thus, signaling patterns may also vary among cytoarchitectonically unique cortical areas. To examine how neuronal signaling patterns are related to innate cortical functions, we detected intrinsic features of cortical firing by devising a metric that efficiently isolates non-Poisson irregular characteristics, independent of spike rate fluctuations that are caused extrinsically by ever-changing behavioral conditions. Using the new metric, we analyzed spike trains from over 1,000 neurons in 15 cortical areas sampled by eight independent neurophysiological laboratories. Analysis of firing-pattern dissimilarities across cortical areas revealed a gradient of firing regularity that corresponded closely to the functional category of the cortical area; neuronal spiking patterns are regular in motor areas, random in the visual areas, and bursty in the prefrontal area. Thus, signaling patterns may play an important role in function-specific cerebral cortical computation.

  20. Pattern recognition algorithms for data mining scalability, knowledge discovery and soft granular computing

    CERN Document Server

    Pal, Sankar K

    2004-01-01

    Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. This volume presents various theories, methodologies, and algorithms, using both classical approaches and hybrid paradigms. The authors emphasize large datasets with overlapping, intractable, or nonlinear boundary classes, and datasets that demonstrate granular computing in soft frameworks.Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery concepts. The authors analyze the tasks of multi-scale data condensation and dimensionality reduction, then explore the problem of learning with support vector machine (SVM). They conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.

  1. Development of a BWR loading pattern design system based on modified genetic algorithms and knowledge

    International Nuclear Information System (INIS)

    Martin-del-Campo, Cecilia; Francois, Juan Luis; Avendano, Linda; Gonzalez, Mario

    2004-01-01

    An optimization system based on Genetic Algorithms (GAs), in combination with expert knowledge coded in heuristics rules, was developed for the design of optimized boiling water reactor (BWR) fuel loading patterns. The system was coded in a computer program named Loading Pattern Optimization System based on Genetic Algorithms, in which the optimization code uses GAs to select candidate solutions, and the core simulator code CM-PRESTO to evaluate them. A multi-objective function was built to maximize the cycle energy length while satisfying power and reactivity constraints used as BWR design parameters. Heuristic rules were applied to satisfy standard fuel management recommendations as the Control Cell Core and Low Leakage loading strategies, and octant symmetry. To test the system performance, an optimized cycle was designed and compared against an actual operating cycle of Laguna Verde Nuclear Power Plant, Unit I

  2. Study of high speed complex number algorithms. [for determining antenna for field radiation patterns

    Science.gov (United States)

    Heisler, R.

    1981-01-01

    A method of evaluating the radiation integral on the curved surface of a reflecting antenna is presented. A three dimensional Fourier transform approach is used to generate a two dimensional radiation cross-section along a planer cut at any angle phi through the far field pattern. Salient to the method is an algorithm for evaluating a subset of the total three dimensional discrete Fourier transform results. The subset elements are selectively evaluated to yield data along a geometric plane of constant. The algorithm is extremely efficient so that computation of the induced surface currents via the physical optics approximation dominates the computer time required to compute a radiation pattern. Application to paraboloid reflectors with off-focus feeds in presented, but the method is easily extended to offset antenna systems and reflectors of arbitrary shapes. Numerical results were computed for both gain and phase and are compared with other published work.

  3. Searching for full power control rod patterns in a boiling water reactor using genetic algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Montes, Jose Luis [Departamento Sistemas Nucleares, ININ, Carr. Mexico-Toluca Km. 36.5, Ocoyoacac, Edo. de Mexico (Mexico)]. E-mail: jlmt@nuclear.inin.mx; Ortiz, Juan Jose [Departamento Sistemas Nucleares, ININ, Carr. Mexico-Toluca Km. 36.5, Ocoyoacac, Edo. de Mexico (Mexico)]. E-mail: jjortiz@nuclear.inin.mx; Requena, Ignacio [Departamento Ciencias Computacion e I.A. ETSII, Informatica, Universidad de Granada, C. Daniel Saucedo Aranda s/n. 18071 Granada (Spain)]. E-mail: requena@decsai.ugr.es; Perusquia, Raul [Departamento Sistemas Nucleares, ININ, Carr. Mexico-Toluca Km. 36.5, Ocoyoacac, Edo. de Mexico (Mexico)]. E-mail: rpc@nuclear.inin.mx

    2004-11-01

    One of the most important questions related to both safety and economic aspects in a nuclear power reactor operation, is without any doubt its reactivity control. During normal operation of a boiling water reactor, the reactivity control of its core is strongly determined by control rods patterns efficiency. In this paper, GACRP system is proposed based on the concepts of genetic algorithms for full power control rod patterns search. This system was carried out using LVNPP transition cycle characteristics, being applied too to an equilibrium cycle. Several operation scenarios, including core water flow variation throughout the cycle and different target axial power distributions, are considered. Genetic algorithm fitness function includes reactor security parameters, such as MLHGR, MCPR, reactor k{sub eff} and axial power density.

  4. An improved genetic algorithm for designing optimal temporal patterns of neural stimulation

    Science.gov (United States)

    Cassar, Isaac R.; Titus, Nathan D.; Grill, Warren M.

    2017-12-01

    Objective. Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach. We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. Main results. The proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. Significance. The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.

  5. Graphene-Based Patterning and Differentiation of C2C12 Myoblasts

    DEFF Research Database (Denmark)

    Bajaj, Piyush; Rivera, Jose A; Marchwiany, Daniel

    2014-01-01

    This study aims at generating highly aligned functional myotubes using graphene as the underlying scaffold. Graphene not only supports the growth of C2C12 muscle cells but also enhances its differentiation and leads to spontaneous patterning of myotubes....

  6. A Hybrid Multiobjective Differential Evolution Algorithm and Its Application to the Optimization of Grinding and Classification

    Directory of Open Access Journals (Sweden)

    Yalin Wang

    2013-01-01

    Full Text Available The grinding-classification is the prerequisite process for full recovery of the nonrenewable minerals with both production quality and quantity objectives concerned. Its natural formulation is a constrained multiobjective optimization problem of complex expression since the process is composed of one grinding machine and two classification machines. In this paper, a hybrid differential evolution (DE algorithm with multi-population is proposed. Some infeasible solutions with better performance are allowed to be saved, and they participate randomly in the evolution. In order to exploit the meaningful infeasible solutions, a functionally partitioned multi-population mechanism is designed to find an optimal solution from all possible directions. Meanwhile, a simplex method for local search is inserted into the evolution process to enhance the searching strategy in the optimization process. Simulation results from the test of some benchmark problems indicate that the proposed algorithm tends to converge quickly and effectively to the Pareto frontier with better distribution. Finally, the proposed algorithm is applied to solve a multiobjective optimization model of a grinding and classification process. Based on the technique for order performance by similarity to ideal solution (TOPSIS, the satisfactory solution is obtained by using a decision-making method for multiple attributes.

  7. Reloading pattern optimization of VVER-1000 reactors in transient cycles using genetic algorithm

    International Nuclear Information System (INIS)

    Rahmani, Yashar

    2017-01-01

    Highlights: • The genetic algorithm (GA) and the innovative weighting factors method were used. • The coupling of WIMSD5-B and CITATION-LDI2 neutronic codes with the thermohydraulic WERL code was employed. • Optimization of reloading patterns was carried out in two states. • First an arrangement with satisfactory excess reactivity and the flattest power distribution was searched. • Second, it is tried to obtain an arrangement with satisfactory safety threshold and the maximum K_e_f_f. - Abstract: The present paper proposes application of the genetic algorithm (GA) and the innovative weighting factor method to optimize the reloading pattern of Bushehr VVER-1000 reactor in the second cycle. To estimate the composition of fuel assemblies remaining from the first cycle and precisely calculate the objective parameters of each reloading pattern in the second cycle, coupling of WIMSD5-B and CITATION-LDI2 codes in the neutronic section and the WERL code in the thermo-hydraulic section was employed. Optimization of the reloading patterns was carried out in two states. To meet the mentioned objective, with application of the weighting factor method in the first state, the type and quantity of the loadable fresh assemblies were determined to enable the reactor core to maintain the core criticality over the entire cycle length. Afterwards, the genetic algorithm was used to optimize the reloading pattern of the reactor to obtain an arrangement with flat radial power distribution. In the second state, the optimization algorithm was free to select the type and number of fresh fuel assemblies to be able to search for an arrangement with the maximum effective multiplication factor and the safe power peaking factor. In addition, in order to ensure the safety and desirability of the proposed patterns in both states, a time-dependent examination of the thermo-neutronic behavior of the reactor core was carried out during the second cycle. With consideration of the new

  8. Optimal Refueling Pattern Search for a CANDU Reactor Using a Genetic Algorithm

    International Nuclear Information System (INIS)

    Quang Binh, DO; Gyuhong, ROH; Hangbok, CHOI

    2006-01-01

    This paper presents the results from the application of genetic algorithms to a refueling optimization of a Canada deuterium uranium (CANDU) reactor. This work aims at making a mathematical model of the refueling optimization problem including the objective function and constraints and developing a method based on genetic algorithms to solve the problem. The model of the optimization problem and the proposed method comply with the key features of the refueling strategy of the CANDU reactor which adopts an on-power refueling operation. In this study, a genetic algorithm combined with an elitism strategy was used to automatically search for the refueling patterns. The objective of the optimization was to maximize the discharge burn-up of the refueling bundles, minimize the maximum channel power, or minimize the maximum change in the zone controller unit (ZCU) water levels. A combination of these objectives was also investigated. The constraints include the discharge burn-up, maximum channel power, maximum bundle power, channel power peaking factor and the ZCU water level. A refueling pattern that represents the refueling rate and channels was coded by a one-dimensional binary chromosome, which is a string of binary numbers 0 and 1. A computer program was developed in FORTRAN 90 running on an HP 9000 workstation to conduct the search for the optimal refueling patterns for a CANDU reactor at the equilibrium state. The results showed that it was possible to apply genetic algorithms to automatically search for the refueling channels of the CANDU reactor. The optimal refueling patterns were compared with the solutions obtained from the AUTOREFUEL program and the results were consistent with each other. (authors)

  9. A Modified Differential Coherent Bit Synchronization Algorithm for BeiDou Weak Signals with Large Frequency Deviation.

    Science.gov (United States)

    Han, Zhifeng; Liu, Jianye; Li, Rongbing; Zeng, Qinghua; Wang, Yi

    2017-07-04

    BeiDou system navigation messages are modulated with a secondary NH (Neumann-Hoffman) code of 1 kbps, where frequent bit transitions limit the coherent integration time to 1 millisecond. Therefore, a bit synchronization algorithm is necessary to obtain bit edges and NH code phases. In order to realize bit synchronization for BeiDou weak signals with large frequency deviation, a bit synchronization algorithm based on differential coherent and maximum likelihood is proposed. Firstly, a differential coherent approach is used to remove the effect of frequency deviation, and the differential delay time is set to be a multiple of bit cycle to remove the influence of NH code. Secondly, the maximum likelihood function detection is used to improve the detection probability of weak signals. Finally, Monte Carlo simulations are conducted to analyze the detection performance of the proposed algorithm compared with a traditional algorithm under the CN0s of 20~40 dB-Hz and different frequency deviations. The results show that the proposed algorithm outperforms the traditional method with a frequency deviation of 50 Hz. This algorithm can remove the effect of BeiDou NH code effectively and weaken the influence of frequency deviation. To confirm the feasibility of the proposed algorithm, real data tests are conducted. The proposed algorithm is suitable for BeiDou weak signal bit synchronization with large frequency deviation.

  10. Differential diagnosis algorithm of endogenous catatonia, catatonia-morphic and catatonia-mimicking states

    Directory of Open Access Journals (Sweden)

    D. N. Safonov

    2017-08-01

    Full Text Available Subject relevance. The process of mental pathology pathomorphosis leads to the polymorphism of its clinical manifestations and, as a consequence – to difficulties in identification and differential diagnosis. The solution to this problem is in the adaption of diagnostic methodology to clinical realities by including into their structure instruments formed basing on pathomorphosis factors and trends. In this perspective, the most prominent example is endogenous catatonia, which in the academic tradition is conventionally affiliated with the form of schizophrenia with the same name. According to the classical understanding, endogenous catatonia, or, in the narrow sense – catatonic syndrome, is a group of intermittent motor disorders, arranged with polymorphic shell constellation of neuropsychiatric manifestations. The aim is to develop pathomorphosis adapted clinical algorithm of endogenous catatonia differential diagnostics. Materials and methods: 236 patients of Zaporizhzhia Regional Psychiatric Clinic were examined. Patients were divided into groups due to their mental disorders: – core group: patients with elements of endogenous catatonia in the structure of different clinical forms of schizophrenia (there were 144 patients in this group; – comparison group #1: 69 patients with late neurotropic effects of neuroleptic therapy (LNENT; – comparison group #2: 103 patients with catatonia-morphic dissociative disorders (CDD; – comparison group #3: 90 patients with organic catatonic disorder (OrCD; Results. Using Bush-Francis Catatonia Rating scale as an instrument of clinical analysis and statistical research of results with A. Wald’s sequential analysis (modificated by E. V. Gubler an algorithm of differential diagnostics of endogenus catatonia which includes 3 steps of Recognition Scale for Endogenous Catatonia is developed. Conclusion. Designed scales have a number of categorical differences from existing analogues, foremost by

  11. Genetic algorithms and artificial neural networks for loading pattern optimisation of advanced gas-cooled reactors

    Energy Technology Data Exchange (ETDEWEB)

    Ziver, A.K. E-mail: a.k.ziver@imperial.ac.uk; Pain, C.C; Carter, J.N.; Oliveira, C.R.E. de; Goddard, A.J.H.; Overton, R.S

    2004-03-01

    A non-generational genetic algorithm (GA) has been developed for fuel management optimisation of Advanced Gas-Cooled Reactors, which are operated by British Energy and produce around 20% of the UK's electricity requirements. An evolutionary search is coded using the genetic operators; namely selection by tournament, two-point crossover, mutation and random assessment of population for multi-cycle loading pattern (LP) optimisation. A detailed description of the chromosomes in the genetic algorithm coded is presented. Artificial Neural Networks (ANNs) have been constructed and trained to accelerate the GA-based search during the optimisation process. The whole package, called GAOPT, is linked to the reactor analysis code PANTHER, which performs fresh fuel loading, burn-up and power shaping calculations for each reactor cycle by imposing station-specific safety and operational constraints. GAOPT has been verified by performing a number of tests, which are applied to the Hinkley Point B and Hartlepool reactors. The test results giving loading pattern (LP) scenarios obtained from single and multi-cycle optimisation calculations applied to realistic reactor states of the Hartlepool and Hinkley Point B reactors are discussed. The results have shown that the GA/ANN algorithms developed can help the fuel engineer to optimise loading patterns in an efficient and more profitable way than currently available for multi-cycle refuelling of AGRs. Research leading to parallel GAs applied to LP optimisation are outlined, which can be adapted to present day LWR fuel management problems.

  12. User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm.

    Science.gov (United States)

    Bourobou, Serge Thomas Mickala; Yoo, Younghwan

    2015-05-21

    This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen's temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home.

  13. User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm

    Directory of Open Access Journals (Sweden)

    Serge Thomas Mickala Bourobou

    2015-05-01

    Full Text Available This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen’s temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home.

  14. Research on the Compression Algorithm of the Infrared Thermal Image Sequence Based on Differential Evolution and Double Exponential Decay Model

    Science.gov (United States)

    Zhang, Jin-Yu; Meng, Xiang-Bing; Xu, Wei; Zhang, Wei; Zhang, Yong

    2014-01-01

    This paper has proposed a new thermal wave image sequence compression algorithm by combining double exponential decay fitting model and differential evolution algorithm. This study benchmarked fitting compression results and precision of the proposed method was benchmarked to that of the traditional methods via experiment; it investigated the fitting compression performance under the long time series and improved model and validated the algorithm by practical thermal image sequence compression and reconstruction. The results show that the proposed algorithm is a fast and highly precise infrared image data processing method. PMID:24696649

  15. Research on the Compression Algorithm of the Infrared Thermal Image Sequence Based on Differential Evolution and Double Exponential Decay Model

    Directory of Open Access Journals (Sweden)

    Jin-Yu Zhang

    2014-01-01

    Full Text Available This paper has proposed a new thermal wave image sequence compression algorithm by combining double exponential decay fitting model and differential evolution algorithm. This study benchmarked fitting compression results and precision of the proposed method was benchmarked to that of the traditional methods via experiment; it investigated the fitting compression performance under the long time series and improved model and validated the algorithm by practical thermal image sequence compression and reconstruction. The results show that the proposed algorithm is a fast and highly precise infrared image data processing method.

  16. PASSion: a pattern growth algorithm-based pipeline for splice junction detection in paired-end RNA-Seq data.

    Science.gov (United States)

    Zhang, Yanju; Lameijer, Eric-Wubbo; 't Hoen, Peter A C; Ning, Zemin; Slagboom, P Eline; Ye, Kai

    2012-02-15

    RNA-seq is a powerful technology for the study of transcriptome profiles that uses deep-sequencing technologies. Moreover, it may be used for cellular phenotyping and help establishing the etiology of diseases characterized by abnormal splicing patterns. In RNA-Seq, the exact nature of splicing events is buried in the reads that span exon-exon boundaries. The accurate and efficient mapping of these reads to the reference genome is a major challenge. We developed PASSion, a pattern growth algorithm-based pipeline for splice site detection in paired-end RNA-Seq reads. Comparing the performance of PASSion to three existing RNA-Seq analysis pipelines, TopHat, MapSplice and HMMSplicer, revealed that PASSion is competitive with these packages. Moreover, the performance of PASSion is not affected by read length and coverage. It performs better than the other three approaches when detecting junctions in highly abundant transcripts. PASSion has the ability to detect junctions that do not have known splicing motifs, which cannot be found by the other tools. Of the two public RNA-Seq datasets, PASSion predicted ≈ 137,000 and 173,000 splicing events, of which on average 82 are known junctions annotated in the Ensembl transcript database and 18% are novel. In addition, our package can discover differential and shared splicing patterns among multiple samples. The code and utilities can be freely downloaded from https://trac.nbic.nl/passion and ftp://ftp.sanger.ac.uk/pub/zn1/passion.

  17. You're Just Like Your Dad: Intergenerational Patterns of Differential Treatment of Siblings.

    Science.gov (United States)

    Jensen, Alexander C; Whiteman, Shawn D; Rand, Joseph S; Fingerman, Karen L

    2017-10-01

    Past work highlights that parents' differential treatment has implications for offspring's mental and relational health across the life course. Although the current body of literature has examined offspring- and parent-level correlates of differential treatment, research has yet to consider whether and how patterns of differential treatment are transmitted across generations. As part of a two-wave longitudinal study of 157 families, both grandparents (M age = 76.50 years, SD = 6.20) and parents (M age = 51.10 years, SD = 4.41) reported on differential treatment of their own offspring at both phases. A series of residualized change models revealed support for both continuity and compensation hypotheses. Middle-aged parents tended to model the patterns of differential treatment exhibited by their fathers, but middle-aged men who experienced more differential treatment from their own parents in recent years tended to subsequently exhibit lower levels of differential treatment to their offspring. These findings suggest that patterns of differential treatment both continue and diverge across generations, and those patterns vary by gender. On a broader level, these results also suggest that siblings not only impact one another's development, but in adulthood, they may indirectly influence their nieces' and nephews' development by virtue of their influence on their siblings' parenting. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  18. Efficient frequent pattern mining algorithm based on node sets in cloud computing environment

    Science.gov (United States)

    Billa, V. N. Vinay Kumar; Lakshmanna, K.; Rajesh, K.; Reddy, M. Praveen Kumar; Nagaraja, G.; Sudheer, K.

    2017-11-01

    The ultimate goal of Data Mining is to determine the hidden information which is useful in making decisions using the large databases collected by an organization. This Data Mining involves many tasks that are to be performed during the process. Mining frequent itemsets is the one of the most important tasks in case of transactional databases. These transactional databases contain the data in very large scale where the mining of these databases involves the consumption of physical memory and time in proportion to the size of the database. A frequent pattern mining algorithm is said to be efficient only if it consumes less memory and time to mine the frequent itemsets from the given large database. Having these points in mind in this thesis we proposed a system which mines frequent itemsets in an optimized way in terms of memory and time by using cloud computing as an important factor to make the process parallel and the application is provided as a service. A complete framework which uses a proven efficient algorithm called FIN algorithm. FIN algorithm works on Nodesets and POC (pre-order coding) tree. In order to evaluate the performance of the system we conduct the experiments to compare the efficiency of the same algorithm applied in a standalone manner and in cloud computing environment on a real time data set which is traffic accidents data set. The results show that the memory consumption and execution time taken for the process in the proposed system is much lesser than those of standalone system.

  19. A Hybrid CPU/GPU Pattern-Matching Algorithm for Deep Packet Inspection.

    Directory of Open Access Journals (Sweden)

    Chun-Liang Lee

    Full Text Available The large quantities of data now being transferred via high-speed networks have made deep packet inspection indispensable for security purposes. Scalable and low-cost signature-based network intrusion detection systems have been developed for deep packet inspection for various software platforms. Traditional approaches that only involve central processing units (CPUs are now considered inadequate in terms of inspection speed. Graphic processing units (GPUs have superior parallel processing power, but transmission bottlenecks can reduce optimal GPU efficiency. In this paper we describe our proposal for a hybrid CPU/GPU pattern-matching algorithm (HPMA that divides and distributes the packet-inspecting workload between a CPU and GPU. All packets are initially inspected by the CPU and filtered using a simple pre-filtering algorithm, and packets that might contain malicious content are sent to the GPU for further inspection. Test results indicate that in terms of random payload traffic, the matching speed of our proposed algorithm was 3.4 times and 2.7 times faster than those of the AC-CPU and AC-GPU algorithms, respectively. Further, HPMA achieved higher energy efficiency than the other tested algorithms.

  20. Differential DNA methylation patterns define status epilepticus and epileptic tolerance.

    Science.gov (United States)

    Miller-Delaney, Suzanne F C; Das, Sudipto; Sano, Takanori; Jimenez-Mateos, Eva M; Bryan, Kenneth; Buckley, Patrick G; Stallings, Raymond L; Henshall, David C

    2012-02-01

    Prolonged seizures (status epilepticus) produce pathophysiological changes in the hippocampus that are associated with large-scale, wide-ranging changes in gene expression. Epileptic tolerance is an endogenous program of cell protection that can be activated in the brain by previous exposure to a non-harmful seizure episode before status epilepticus. A major transcriptional feature of tolerance is gene downregulation. Here, through methylation analysis of 34,143 discrete loci representing all annotated CpG islands and promoter regions in the mouse genome, we report the genome-wide DNA methylation changes in the hippocampus after status epilepticus and epileptic tolerance in adult mice. A total of 321 genes showed altered DNA methylation after status epilepticus alone or status epilepticus that followed seizure preconditioning, with >90% of the promoters of these genes undergoing hypomethylation. These profiles included genes not previously associated with epilepsy, such as the polycomb gene Phc2. Differential methylation events generally occurred throughout the genome without bias for a particular chromosomal region, with the exception of a small region of chromosome 4, which was significantly overrepresented with genes hypomethylated after status epilepticus. Surprisingly, only few genes displayed differential hypermethylation in epileptic tolerance. Nevertheless, gene ontology analysis emphasized the majority of differential methylation events between the groups occurred in genes associated with nuclear functions, such as DNA binding and transcriptional regulation. The present study reports select, genome-wide DNA methylation changes after status epilepticus and in epileptic tolerance, which may contribute to regulating the gene expression environment of the seizure-damaged hippocampus.

  1. Differential expression pattern of UBX family genes in Caenorhabditis elegans

    International Nuclear Information System (INIS)

    Yamauchi, Seiji; Sasagawa, Yohei; Ogura, Teru; Yamanaka, Kunitoshi

    2007-01-01

    UBX (ubiquitin regulatory X)-containing proteins belong to an evolutionary conserved protein family and determine the specificity of p97/VCP/Cdc48p function by binding as its adaptors. Caenorhabditis elegans was found to possess six UBX-containing proteins, named UBXN-1 to -6. However, no general or specific function of them has been revealed. During the course of understanding not only their function but also specified function of p97, we investigated spatial and temporal expression patterns of six ubxn genes in this study. Transcript analyses showed that the expression pattern of each ubxn gene was different throughout worm's development and may show potential developmental dynamics in their function, especially ubxn-5 was expressed specifically in the spermatogenic germline, suggesting a crucial role in spermatogenesis. In addition, as ubxn-4 expression was induced by ER stress, it would function as an ERAD factor in C. elegans. In vivo expression analysis by using GFP translational fusion constructs revealed that six ubxn genes show distinct expression patterns. These results altogether demonstrate that the expression of all six ubxn genes of C. elegans is differently regulated

  2. Indexing amyloid peptide diffraction from serial femtosecond crystallography: new algorithms for sparse patterns

    Energy Technology Data Exchange (ETDEWEB)

    Brewster, Aaron S. [Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); Sawaya, Michael R. [University of California, Los Angeles, CA 90095-1570 (United States); University of California, Los Angeles, CA 90095-1570 (United States); University of California, Los Angeles, CA 90095-1570 (United States); Rodriguez, Jose [University of California, Los Angeles, CA 90095-1570 (United States); University of California, Los Angeles, CA 90095-1570 (United States); Hattne, Johan; Echols, Nathaniel [Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); McFarlane, Heather T. [University of California, Los Angeles, CA 90095-1570 (United States); University of California, Los Angeles, CA 90095-1570 (United States); Cascio, Duilio [University of California, Los Angeles, CA 90095-1570 (United States); University of California, Los Angeles, CA 90095-1570 (United States); University of California, Los Angeles, CA 90095-1570 (United States); Adams, Paul D. [Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); University of California, Berkeley, CA 94720 (United States); Eisenberg, David S. [University of California, Los Angeles, CA 90095-1570 (United States); University of California, Los Angeles, CA 90095-1570 (United States); University of California, Los Angeles, CA 90095-1570 (United States); Sauter, Nicholas K., E-mail: nksauter@lbl.gov [Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States)

    2015-02-01

    Special methods are required to interpret sparse diffraction patterns collected from peptide crystals at X-ray free-electron lasers. Bragg spots can be indexed from composite-image powder rings, with crystal orientations then deduced from a very limited number of spot positions. Still diffraction patterns from peptide nanocrystals with small unit cells are challenging to index using conventional methods owing to the limited number of spots and the lack of crystal orientation information for individual images. New indexing algorithms have been developed as part of the Computational Crystallography Toolbox (cctbx) to overcome these challenges. Accurate unit-cell information derived from an aggregate data set from thousands of diffraction patterns can be used to determine a crystal orientation matrix for individual images with as few as five reflections. These algorithms are potentially applicable not only to amyloid peptides but also to any set of diffraction patterns with sparse properties, such as low-resolution virus structures or high-throughput screening of still images captured by raster-scanning at synchrotron sources. As a proof of concept for this technique, successful integration of X-ray free-electron laser (XFEL) data to 2.5 Å resolution for the amyloid segment GNNQQNY from the Sup35 yeast prion is presented.

  3. Basic pattern in CT of the lung and differential diagnosis

    International Nuclear Information System (INIS)

    Jacobi, V.; Thalhammer, A.

    2006-01-01

    Infectious, physical, chemical or other noxae elicit a limited number of reactions in lung tissue. As in the case of other organs and tissues, lung tissue has specific reactions that are often more indicative of the particular organ than the harmful agent. The resulting radiological features are usually ambiguous and therefore prevent definitive diagnosis. This complicates etiological categorization of the disease. Pathognomonic findings are rare. The same noxa can yield different radiographic features and clinical pictures for different patients. A diagnosis is generally not comprised of a single radiographic feature, but rather of a combination of a plurality of features. Although the number of possible diagnoses can be limited via radiological means, a final diagnosis is determined in conjunction with the medical history, the clinical picture, as well as lab and histopathological values. This article defines the most common pulmonary changes and also discusses differential diagnostic criteria. (orig.)

  4. Differential evolution algorithm-based kernel parameter selection for Fukunaga-Koontz Transform subspaces construction

    Science.gov (United States)

    Binol, Hamidullah; Bal, Abdullah; Cukur, Huseyin

    2015-10-01

    The performance of the kernel based techniques depends on the selection of kernel parameters. That's why; suitable parameter selection is an important problem for many kernel based techniques. This article presents a novel technique to learn the kernel parameters in kernel Fukunaga-Koontz Transform based (KFKT) classifier. The proposed approach determines the appropriate values of kernel parameters through optimizing an objective function constructed based on discrimination ability of KFKT. For this purpose we have utilized differential evolution algorithm (DEA). The new technique overcomes some disadvantages such as high time consumption existing in the traditional cross-validation method, and it can be utilized in any type of data. The experiments for target detection applications on the hyperspectral images verify the effectiveness of the proposed method.

  5. A Hybrid Differential Evolution and Tree Search Algorithm for the Job Shop Scheduling Problem

    Directory of Open Access Journals (Sweden)

    Rui Zhang

    2011-01-01

    Full Text Available The job shop scheduling problem (JSSP is a notoriously difficult problem in combinatorial optimization. In terms of the objective function, most existing research has been focused on the makespan criterion. However, in contemporary manufacturing systems, due-date-related performances are more important because they are essential for maintaining a high service reputation. Therefore, in this study we aim at minimizing the total weighted tardiness in JSSP. Considering the high complexity, a hybrid differential evolution (DE algorithm is proposed for the problem. To enhance the overall search efficiency, a neighborhood property of the problem is discovered, and then a tree search procedure is designed and embedded into the DE framework. According to the extensive computational experiments, the proposed approach is efficient in solving the job shop scheduling problem with total weighted tardiness objective.

  6. Multicycle Optimization of Advanced Gas-Cooled Reactor Loading Patterns Using Genetic Algorithms

    International Nuclear Information System (INIS)

    Ziver, A. Kemal; Carter, Jonathan N.; Pain, Christopher C.; Oliveira, Cassiano R.E. de; Goddard, Antony J. H.; Overton, Richard S.

    2003-01-01

    A genetic algorithm (GA)-based optimizer (GAOPT) has been developed for in-core fuel management of advanced gas-cooled reactors (AGRs) at HINKLEY B and HARTLEPOOL, which employ on-load and off-load refueling, respectively. The optimizer has been linked to the reactor analysis code PANTHER for the automated evaluation of loading patterns in a two-dimensional geometry, which is collapsed from the three-dimensional reactor model. GAOPT uses a directed stochastic (Monte Carlo) algorithm to generate initial population members, within predetermined constraints, for use in GAs, which apply the standard genetic operators: selection by tournament, crossover, and mutation. The GAOPT is able to generate and optimize loading patterns for successive reactor cycles (multicycle) within acceptable CPU times even on single-processor systems. The algorithm allows radial shuffling of fuel assemblies in a multicycle refueling optimization, which is constructed to aid long-term core management planning decisions. This paper presents the application of the GA-based optimization to two AGR stations, which apply different in-core management operational rules. Results obtained from the testing of GAOPT are discussed

  7. Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images

    Directory of Open Access Journals (Sweden)

    Marc Wieland

    2014-03-01

    Full Text Available In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS and very high resolution (WorldView-2, Quickbird, Ikonos multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognition tasks. Four classification algorithms, Normal Bayes, K Nearest Neighbors, Random Trees and Support Vector Machines, which represent different concepts in machine learning (probabilistic, nearest neighbor, tree-based, function-based, have been selected and implemented on a free and open-source basis. Particular focus is given to assess the generalization ability of machine learning algorithms and the transferability of trained learning machines between different image types and image scenes. Moreover, the influence of the number and choice of training data, the influence of the size and composition of the feature vector and the effect of image segmentation on the classification accuracy is evaluated.

  8. A comparative analysis of particle swarm optimization and differential evolution algorithms for parameter estimation in nonlinear dynamic systems

    International Nuclear Information System (INIS)

    Banerjee, Amit; Abu-Mahfouz, Issam

    2014-01-01

    The use of evolutionary algorithms has been popular in recent years for solving the inverse problem of identifying system parameters given the chaotic response of a dynamical system. The inverse problem is reformulated as a minimization problem and population-based optimizers such as evolutionary algorithms have been shown to be efficient solvers of the minimization problem. However, to the best of our knowledge, there has been no published work that evaluates the efficacy of using the two most popular evolutionary techniques – particle swarm optimization and differential evolution algorithm, on a wide range of parameter estimation problems. In this paper, the two methods along with their variants (for a total of seven algorithms) are applied to fifteen different parameter estimation problems of varying degrees of complexity. Estimation results are analyzed using nonparametric statistical methods to identify if an algorithm is statistically superior to others over the class of problems analyzed. Results based on parameter estimation quality suggest that there are significant differences between the algorithms with the newer, more sophisticated algorithms performing better than their canonical versions. More importantly, significant differences were also found among variants of the particle swarm optimizer and the best performing differential evolution algorithm

  9. Automatic boiling water reactor control rod pattern design using particle swarm optimization algorithm and local search

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Cheng-Der, E-mail: jdwang@iner.gov.tw [Nuclear Engineering Division, Institute of Nuclear Energy Research, No. 1000, Wenhua Rd., Jiaan Village, Longtan Township, Taoyuan County 32546, Taiwan, ROC (China); Lin, Chaung [National Tsing Hua University, Department of Engineering and System Science, 101, Section 2, Kuang Fu Road, Hsinchu 30013, Taiwan (China)

    2013-02-15

    Highlights: ► The PSO algorithm was adopted to automatically design a BWR CRP. ► The local search procedure was added to improve the result of PSO algorithm. ► The results show that the obtained CRP is the same good as that in the previous work. -- Abstract: This study developed a method for the automatic design of a boiling water reactor (BWR) control rod pattern (CRP) using the particle swarm optimization (PSO) algorithm. The PSO algorithm is more random compared to the rank-based ant system (RAS) that was used to solve the same BWR CRP design problem in the previous work. In addition, the local search procedure was used to make improvements after PSO, by adding the single control rod (CR) effect. The design goal was to obtain the CRP so that the thermal limits and shutdown margin would satisfy the design requirement and the cycle length, which is implicitly controlled by the axial power distribution, would be acceptable. The results showed that the same acceptable CRP found in the previous work could be obtained.

  10. Design of a fuzzy differential evolution algorithm to predict non-deposition sediment transport

    Science.gov (United States)

    Ebtehaj, Isa; Bonakdari, Hossein

    2017-12-01

    Since the flow entering a sewer contains solid matter, deposition at the bottom of the channel is inevitable. It is difficult to understand the complex, three-dimensional mechanism of sediment transport in sewer pipelines. Therefore, a method to estimate the limiting velocity is necessary for optimal designs. Due to the inability of gradient-based algorithms to train Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for non-deposition sediment transport prediction, a new hybrid ANFIS method based on a differential evolutionary algorithm (ANFIS-DE) is developed. The training and testing performance of ANFIS-DE is evaluated using a wide range of dimensionless parameters gathered from the literature. The input combination used to estimate the densimetric Froude number ( Fr) parameters includes the volumetric sediment concentration ( C V ), ratio of median particle diameter to hydraulic radius ( d/R), ratio of median particle diameter to pipe diameter ( d/D) and overall friction factor of sediment ( λ s ). The testing results are compared with the ANFIS model and regression-based equation results. The ANFIS-DE technique predicted sediment transport at limit of deposition with lower root mean square error (RMSE = 0.323) and mean absolute percentage of error (MAPE = 0.065) and higher accuracy ( R 2 = 0.965) than the ANFIS model and regression-based equations.

  11. Trajectory Evaluation of Rotor-Flying Robots Using Accurate Inverse Computation Based on Algorithm Differentiation

    Directory of Open Access Journals (Sweden)

    Yuqing He

    2014-01-01

    Full Text Available Autonomous maneuvering flight control of rotor-flying robots (RFR is a challenging problem due to the highly complicated structure of its model and significant uncertainties regarding many aspects of the field. As a consequence, it is difficult in many cases to decide whether or not a flight maneuver trajectory is feasible. It is necessary to conduct an analysis of the flight maneuvering ability of an RFR prior to test flight. Our aim in this paper is to use a numerical method called algorithm differentiation (AD to solve this problem. The basic idea is to compute the internal state (i.e., attitude angles and angular rates and input profiles based on predetermined maneuvering trajectory information denoted by the outputs (i.e., positions and yaw angle and their higher-order derivatives. For this purpose, we first present a model of the RFR system and show that it is flat. We then cast the procedure for obtaining the required state/input based on the desired outputs as a static optimization problem, which is solved using AD and a derivative based optimization algorithm. Finally, we test our proposed method using a flight maneuver trajectory to verify its performance.

  12. A computer algorithm for the differentiation between lung and gastrointestinal tract activities in the human body

    International Nuclear Information System (INIS)

    Mellor, R.A.; Harrington, C.L.; Bard, S.T.

    1984-01-01

    Proposed changes to 10CFR20 combining internal and external exposures will require accurate and precise in vivo bioassay data. One of the many uncertainties in the interpretation of in vivo bioassay data is the imprecise knowledge of the location of any observed radioactivity within the body of an individual. Attempts to minimize this uncertainty have been made by collimating the field of view of a single photon detector to each organ or body system of concern. In each of these cases, full removal of any potential gamma flux from organs other than the desired organ is not achieved. In certain commercially available systems this ''cross talk'' may range from 20 to 40 percent. A computerized algorithm has been developed which resolves this ''cross talk'' for all observed radionuclides in a system composed of two high purity germanium photon detectors separately viewing the lung and GI regions of a subject. The algorithm routinely applies cross talk correction factors and photopeak detection efficiencies to the net spectral photopeak areas determined by a peak search methodology. Separate lung and GI activities, corrected for cross talk, are calculated and reported. The logic utilized in the total software package, as well as the derivation of the cross talk correction factors, will be discussed. Any limitations of the computer algorithm when applied to various radioactivity levels will also be identified. An evaluation of the cross talk factors for potential use in differentiating surface contamination from true organ burdens will be presented. In addition, the capability to efficiently execute this software using a low cost, portable stand-alone computer system will be demonstrated

  13. Combination of oriented partial differential equation and shearlet transform for denoising in electronic speckle pattern interferometry fringe patterns.

    Science.gov (United States)

    Xu, Wenjun; Tang, Chen; Gu, Fan; Cheng, Jiajia

    2017-04-01

    It is a key step to remove the massive speckle noise in electronic speckle pattern interferometry (ESPI) fringe patterns. In the spatial-domain filtering methods, oriented partial differential equations have been demonstrated to be a powerful tool. In the transform-domain filtering methods, the shearlet transform is a state-of-the-art method. In this paper, we propose a filtering method for ESPI fringe patterns denoising, which is a combination of second-order oriented partial differential equation (SOOPDE) and the shearlet transform, named SOOPDE-Shearlet. Here, the shearlet transform is introduced into the ESPI fringe patterns denoising for the first time. This combination takes advantage of the fact that the spatial-domain filtering method SOOPDE and the transform-domain filtering method shearlet transform benefit from each other. We test the proposed SOOPDE-Shearlet on five experimentally obtained ESPI fringe patterns with poor quality and compare our method with SOOPDE, shearlet transform, windowed Fourier filtering (WFF), and coherence-enhancing diffusion (CEDPDE). Among them, WFF and CEDPDE are the state-of-the-art methods for ESPI fringe patterns denoising in transform domain and spatial domain, respectively. The experimental results have demonstrated the good performance of the proposed SOOPDE-Shearlet.

  14. Use of a machine learning algorithm to classify expertise: analysis of hand motion patterns during a simulated surgical task.

    Science.gov (United States)

    Watson, Robert A

    2014-08-01

    To test the hypothesis that machine learning algorithms increase the predictive power to classify surgical expertise using surgeons' hand motion patterns. In 2012 at the University of North Carolina at Chapel Hill, 14 surgical attendings and 10 first- and second-year surgical residents each performed two bench model venous anastomoses. During the simulated tasks, the participants wore an inertial measurement unit on the dorsum of their dominant (right) hand to capture their hand motion patterns. The pattern from each bench model task performed was preprocessed into a symbolic time series and labeled as expert (attending) or novice (resident). The labeled hand motion patterns were processed and used to train a Support Vector Machine (SVM) classification algorithm. The trained algorithm was then tested for discriminative/predictive power against unlabeled (blinded) hand motion patterns from tasks not used in the training. The Lempel-Ziv (LZ) complexity metric was also measured from each hand motion pattern, with an optimal threshold calculated to separately classify the patterns. The LZ metric classified unlabeled (blinded) hand motion patterns into expert and novice groups with an accuracy of 70% (sensitivity 64%, specificity 80%). The SVM algorithm had an accuracy of 83% (sensitivity 86%, specificity 80%). The results confirmed the hypothesis. The SVM algorithm increased the predictive power to classify blinded surgical hand motion patterns into expert versus novice groups. With further development, the system used in this study could become a viable tool for low-cost, objective assessment of procedural proficiency in a competency-based curriculum.

  15. Advanced and flexible genetic algorithms for BWR fuel loading pattern optimization

    International Nuclear Information System (INIS)

    Martin-del-Campo, Cecilia; Palomera-Perez, Miguel-Angel; Francois, Juan-Luis

    2009-01-01

    This work proposes advances in the implementation of a flexible genetic algorithm (GA) for fuel loading pattern optimization for Boiling Water Reactors (BWRs). In order to avoid specific implementations of genetic operators and to obtain a more flexible treatment, a binary representation of the solution was implemented; this representation had to take into account that a little change in the genotype must correspond to a little change in the phenotype. An identifier number is assigned to each assembly by means of a Gray Code of 7 bits and the solution (the loading pattern) is represented by a binary chain of 777 bits of length. Another important contribution is the use of a Fitness Function which includes a Heuristic Function and an Objective Function. The Heuristic Function which is defined to give flexibility on the application of a set of positioning rules based on knowledge, and the Objective Function that contains all the parameters which qualify the neutronic and thermal hydraulic performances of each loading pattern. Experimental results illustrating the effectiveness and flexibility of this optimization algorithm are presented and discussed.

  16. Application of the distributed genetic algorithm for loading pattern optimization problems

    International Nuclear Information System (INIS)

    Hashimoto, Hiroshi; Yamamoto, Akio

    2000-01-01

    The distributed genetic algorithm (DGA) is applied for loading pattern optimization problems of the pressurized water reactors (PWR). Due to stiff nature of the loading pattern optimizations (e.g. multi-modality and non-linearity), stochastic methods like the simulated annealing or the genetic algorithm (GA) are widely applied for these problems. A basic concept of DGA is based on that of GA. However, DGA equally distributes candidates of solutions (i.e. loading patterns) to several independent 'islands' and evolves them in each island. Migrations of some candidates are performed among islands with a certain period. Since candidates of solutions independently evolve in each island with accepting different genes of migrants from other islands, premature convergence in the traditional GA can be prevented. Because many candidate loading patterns should be evaluated in one generation of GA or DGA, the parallelization in these calculations works efficiently. Parallel efficiency was measured using our optimization code and good load balance was attained even in a heterogeneous cluster environment due to dynamic distribution of the calculation load. The optimization code is based on the client/server architecture with the TCP/IP native socket and a client (optimization module) and calculation server modules communicate the objects of loading patterns each other. Throughout the sensitivity study on optimization parameters of DGA, a suitable set of the parameters for a test problem was identified. Finally, optimization capability of DGA and the traditional GA was compared in the test problem and DGA provided better optimization results than the traditional GA. (author)

  17. Investigation of differential HDAC4 methylation patterns in eating disorders.

    Science.gov (United States)

    Subramanian, Subha; Braun, Patricia R; Han, Shizhong; Potash, James B

    2018-02-01

    The objective of this study was to investigate the relationship between methylation patterns of the histone deacetylase 4 gene and eating disorders in a site previously associated with anorexia nervosa (AN). Women with AN (N=28) or bulimia nervosa (BN) (N=19) were age-matched and sex-matched to controls (N=45). We obtained saliva-derived DNA and use bisulfite pyrosequencing to examine region-specific methylation differences between cases and controls. The region assayed includes 15 CpGs. We found no significant association between the previously implicated CpG and either AN or BN. We found that three CpGs were nominally associated with AN (P=0.02-0.03); the largest difference was a 9% hypermethylation in AN. One CpG was nominally associated with BN (P=0.04), with 4% hypomethylation. None of these results remained significant after correction for multiple testing. We did not replicate previous findings, though through expanded coverage, we identified additional CpGs that were nominally associated with eating disorders.

  18. Fear and disgust in women: Differentiation of cardiovascular regulation patterns.

    Science.gov (United States)

    Comtesse, Hannah; Stemmler, Gerhard

    2017-02-01

    Both fear and disgust facilitate avoidance of threat. From a functional view, however, cardiovascular responses to fear and disgust should differ as they prepare for appropriate behavior to protect from injury and infection, respectively. Therefore, we examined the cardiovascular responses to fear and contamination-related disgust in comparison to an emotionally neutral state induced with auditory scripts and film clips in female participants. Ten emotion and motivation self-reports and ninecardiovascular response factors derived from 23 cardiovascular variables served as dependent variables. Self-reports confirmed the specific induction of fear and disgust. In addition, fear and disgust differed in their cardiovascular response patterning. For fear, we observed specific increases in factors indicating vasoconstriction and cardiac pump function. For disgust, we found specific increases in vagal cardiac control and decreases in myocardial contractility. These findings provide support for the cardiovascular specificity of fear and disgust and are discussed in terms of a basic emotions approach. Copyright © 2016. Published by Elsevier B.V.

  19. Cognitive Machine-Learning Algorithm for Cardiac Imaging: A Pilot Study for Differentiating Constrictive Pericarditis From Restrictive Cardiomyopathy.

    Science.gov (United States)

    Sengupta, Partho P; Huang, Yen-Min; Bansal, Manish; Ashrafi, Ali; Fisher, Matt; Shameer, Khader; Gall, Walt; Dudley, Joel T

    2016-06-01

    Associating a patient's profile with the memories of prototypical patients built through previous repeat clinical experience is a key process in clinical judgment. We hypothesized that a similar process using a cognitive computing tool would be well suited for learning and recalling multidimensional attributes of speckle tracking echocardiography data sets derived from patients with known constrictive pericarditis and restrictive cardiomyopathy. Clinical and echocardiographic data of 50 patients with constrictive pericarditis and 44 with restrictive cardiomyopathy were used for developing an associative memory classifier-based machine-learning algorithm. The speckle tracking echocardiography data were normalized in reference to 47 controls with no structural heart disease, and the diagnostic area under the receiver operating characteristic curve of the associative memory classifier was evaluated for differentiating constrictive pericarditis from restrictive cardiomyopathy. Using only speckle tracking echocardiography variables, associative memory classifier achieved a diagnostic area under the curve of 89.2%, which improved to 96.2% with addition of 4 echocardiographic variables. In comparison, the area under the curve of early diastolic mitral annular velocity and left ventricular longitudinal strain were 82.1% and 63.7%, respectively. Furthermore, the associative memory classifier demonstrated greater accuracy and shorter learning curves than other machine-learning approaches, with accuracy asymptotically approaching 90% after a training fraction of 0.3 and remaining flat at higher training fractions. This study demonstrates feasibility of a cognitive machine-learning approach for learning and recalling patterns observed during echocardiographic evaluations. Incorporation of machine-learning algorithms in cardiac imaging may aid standardized assessments and support the quality of interpretations, particularly for novice readers with limited experience. © 2016

  20. A Cognitive Machine Learning Algorithm for Cardiac Imaging: A Pilot Study for Differentiating Constrictive Pericarditis from Restrictive Cardiomyopathy

    Science.gov (United States)

    Sengupta, Partho P.; Huang, Yen-Min; Bansal, Manish; Ashrafi, Ali; Fisher, Matt; Shameer, Khader; Gall, Walt; Dudley, Joel T

    2016-01-01

    Background Associating a patient’s profile with the memories of prototypical patients built through previous repeat clinical experience is a key process in clinical judgment. We hypothesized that a similar process using a cognitive computing tool would be well suited for learning and recalling multidimensional attributes of speckle tracking echocardiography (STE) data sets derived from patients with known constrictive pericarditis (CP) and restrictive cardiomyopathy (RCM). Methods and Results Clinical and echocardiographic data of 50 patients with CP and 44 with RCM were used for developing an associative memory classifier (AMC) based machine learning algorithm. The STE data was normalized in reference to 47 controls with no structural heart disease, and the diagnostic area under the receiver operating characteristic curve (AUC) of the AMC was evaluated for differentiating CP from RCM. Using only STE variables, AMC achieved a diagnostic AUC of 89·2%, which improved to 96·2% with addition of 4 echocardiographic variables. In comparison, the AUC of early diastolic mitral annular velocity and left ventricular longitudinal strain were 82.1% and 63·7%, respectively. Furthermore, AMC demonstrated greater accuracy and shorter learning curves than other machine learning approaches with accuracy asymptotically approaching 90% after a training fraction of 0·3 and remaining flat at higher training fractions. Conclusions This study demonstrates feasibility of a cognitive machine learning approach for learning and recalling patterns observed during echocardiographic evaluations. Incorporation of machine learning algorithms in cardiac imaging may aid standardized assessments and support the quality of interpretations, particularly for novice readers with limited experience. PMID:27266599

  1. Algorithms

    Indian Academy of Sciences (India)

    ticians but also forms the foundation of computer science. Two ... with methods of developing algorithms for solving a variety of problems but ... applications of computers in science and engineer- ... numerical calculus are as important. We will ...

  2. Simulation of small-angle scattering patterns using a CPU-efficient algorithm

    Science.gov (United States)

    Anitas, E. M.

    2017-12-01

    Small-angle scattering (of neutrons, x-ray or light; SAS) is a well-established experimental technique for structural analysis of disordered systems at nano and micro scales. For complex systems, such as super-molecular assemblies or protein molecules, analytic solutions of SAS intensity are generally not available. Thus, a frequent approach to simulate the corresponding patterns is to use a CPU-efficient version of the Debye formula. For this purpose, in this paper we implement the well-known DALAI algorithm in Mathematica software. We present calculations for a series of 2D Sierpinski gaskets and respectively of pentaflakes, obtained from chaos game representation.

  3. Local fractional variational iteration algorithm II for non-homogeneous model associated with the non-differentiable heat flow

    Directory of Open Access Journals (Sweden)

    Yu Zhang

    2015-10-01

    Full Text Available In this article, we begin with the non-homogeneous model for the non-differentiable heat flow, which is described using the local fractional vector calculus, from the first law of thermodynamics in fractal media point view. We employ the local fractional variational iteration algorithm II to solve the fractal heat equations. The obtained results show the non-differentiable behaviors of temperature fields of fractal heat flow defined on Cantor sets.

  4. Optimization of dynamic economic dispatch with valve-point effect using chaotic sequence based differential evolution algorithms

    International Nuclear Information System (INIS)

    He Dakuo; Dong Gang; Wang Fuli; Mao Zhizhong

    2011-01-01

    A chaotic sequence based differential evolution (DE) approach for solving the dynamic economic dispatch problem (DEDP) with valve-point effect is presented in this paper. The proposed method combines the DE algorithm with the local search technique to improve the performance of the algorithm. DE is the main optimizer, while an approximated model for local search is applied to fine tune in the solution of the DE run. To accelerate convergence of DE, a series of constraints handling rules are adopted. An initial population obtained by using chaotic sequence exerts optimal performance of the proposed algorithm. The combined algorithm is validated for two test systems consisting of 10 and 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects. The proposed combined method outperforms other algorithms reported in literatures for DEDP considering valve-point effects.

  5. A novel tree-based algorithm to discover seismic patterns in earthquake catalogs

    Science.gov (United States)

    Florido, E.; Asencio-Cortés, G.; Aznarte, J. L.; Rubio-Escudero, C.; Martínez-Álvarez, F.

    2018-06-01

    A novel methodology is introduced in this research study to detect seismic precursors. Based on an existing approach, the new methodology searches for patterns in the historical data. Such patterns may contain statistical or soil dynamics information. It improves the original version in several aspects. First, new seismicity indicators have been used to characterize earthquakes. Second, a machine learning clustering algorithm has been applied in a very flexible way, thus allowing the discovery of new data groupings. Third, a novel search strategy is proposed in order to obtain non-overlapped patterns. And, fourth, arbitrary lengths of patterns are searched for, thus discovering long and short-term behaviors that may influence in the occurrence of medium-large earthquakes. The methodology has been applied to seven different datasets, from three different regions, namely the Iberian Peninsula, Chile and Japan. Reported results show a remarkable improvement with respect to the former version, in terms of all evaluated quality measures. In particular, the number of false positives has decreased and the positive predictive values increased, both of them in a very remarkable manner.

  6. Optimization of Boiling Water Reactor Loading Pattern Using Two-Stage Genetic Algorithm

    International Nuclear Information System (INIS)

    Kobayashi, Yoko; Aiyoshi, Eitaro

    2002-01-01

    A new two-stage optimization method based on genetic algorithms (GAs) using an if-then heuristic rule was developed to generate optimized boiling water reactor (BWR) loading patterns (LPs). In the first stage, the LP is optimized using an improved GA operator. In the second stage, an exposure-dependent control rod pattern (CRP) is sought using GA with an if-then heuristic rule. The procedure of the improved GA is based on deterministic operators that consist of crossover, mutation, and selection. The handling of the encoding technique and constraint conditions by that GA reflects the peculiar characteristics of the BWR. In addition, strategies such as elitism and self-reproduction are effectively used in order to improve the search speed. The LP evaluations were performed with a three-dimensional diffusion code that coupled neutronic and thermal-hydraulic models. Strong axial heterogeneities and constraints dependent on three dimensions have always necessitated the use of three-dimensional core simulators for BWRs, so that optimization of computational efficiency is required. The proposed algorithm is demonstrated by successfully generating LPs for an actual BWR plant in two phases. One phase is only LP optimization applying the Haling technique. The other phase is an LP optimization that considers the CRP during reactor operation. In test calculations, candidates that shuffled fresh and burned fuel assemblies within a reasonable computation time were obtained

  7. Application of affinity propagation algorithm based on manifold distance for transformer PD pattern recognition

    Science.gov (United States)

    Wei, B. G.; Huo, K. X.; Yao, Z. F.; Lou, J.; Li, X. Y.

    2018-03-01

    It is one of the difficult problems encountered in the research of condition maintenance technology of transformers to recognize partial discharge (PD) pattern. According to the main physical characteristics of PD, three models of oil-paper insulation defects were set up in laboratory to study the PD of transformers, and phase resolved partial discharge (PRPD) was constructed. By using least square method, the grey-scale images of PRPD were constructed and features of each grey-scale image were 28 box dimensions and 28 information dimensions. Affinity propagation algorithm based on manifold distance (AP-MD) for transformers PD pattern recognition was established, and the data of box dimension and information dimension were clustered based on AP-MD. Study shows that clustering result of AP-MD is better than the results of affinity propagation (AP), k-means and fuzzy c-means algorithm (FCM). By choosing different k values of k-nearest neighbor, we find clustering accuracy of AP-MD falls when k value is larger or smaller, and the optimal k value depends on sample size.

  8. A hybrid algorithm for coupling partial differential equation and compartment-based dynamics.

    Science.gov (United States)

    Harrison, Jonathan U; Yates, Christian A

    2016-09-01

    Stochastic simulation methods can be applied successfully to model exact spatio-temporally resolved reaction-diffusion systems. However, in many cases, these methods can quickly become extremely computationally intensive with increasing particle numbers. An alternative description of many of these systems can be derived in the diffusive limit as a deterministic, continuum system of partial differential equations (PDEs). Although the numerical solution of such PDEs is, in general, much more efficient than the full stochastic simulation, the deterministic continuum description is generally not valid when copy numbers are low and stochastic effects dominate. Therefore, to take advantage of the benefits of both of these types of models, each of which may be appropriate in different parts of a spatial domain, we have developed an algorithm that can be used to couple these two types of model together. This hybrid coupling algorithm uses an overlap region between the two modelling regimes. By coupling fluxes at one end of the interface and using a concentration-matching condition at the other end, we ensure that mass is appropriately transferred between PDE- and compartment-based regimes. Our methodology gives notable reductions in simulation time in comparison with using a fully stochastic model, while maintaining the important stochastic features of the system and providing detail in appropriate areas of the domain. We test our hybrid methodology robustly by applying it to several biologically motivated problems including diffusion and morphogen gradient formation. Our analysis shows that the resulting error is small, unbiased and does not grow over time. © 2016 The Authors.

  9. The Ground Flash Fraction Retrieval Algorithm Employing Differential Evolution: Simulations and Applications

    Science.gov (United States)

    Koshak, William; Solakiewicz, Richard

    2012-01-01

    The ability to estimate the fraction of ground flashes in a set of flashes observed by a satellite lightning imager, such as the future GOES-R Geostationary Lightning Mapper (GLM), would likely improve operational and scientific applications (e.g., severe weather warnings, lightning nitrogen oxides studies, and global electric circuit analyses). A Bayesian inversion method, called the Ground Flash Fraction Retrieval Algorithm (GoFFRA), was recently developed for estimating the ground flash fraction. The method uses a constrained mixed exponential distribution model to describe a particular lightning optical measurement called the Maximum Group Area (MGA). To obtain the optimum model parameters (one of which is the desired ground flash fraction), a scalar function must be minimized. This minimization is difficult because of two problems: (1) Label Switching (LS), and (2) Parameter Identity Theft (PIT). The LS problem is well known in the literature on mixed exponential distributions, and the PIT problem was discovered in this study. Each problem occurs when one allows the numerical minimizer to freely roam through the parameter search space; this allows certain solution parameters to interchange roles which leads to fundamental ambiguities, and solution error. A major accomplishment of this study is that we have employed a state-of-the-art genetic-based global optimization algorithm called Differential Evolution (DE) that constrains the parameter search in such a way as to remove both the LS and PIT problems. To test the performance of the GoFFRA when DE is employed, we applied it to analyze simulated MGA datasets that we generated from known mixed exponential distributions. Moreover, we evaluated the GoFFRA/DE method by applying it to analyze actual MGAs derived from low-Earth orbiting lightning imaging sensor data; the actual MGA data were classified as either ground or cloud flash MGAs using National Lightning Detection Network[TM] (NLDN) data. Solution error

  10. A Markov Chain Monte Carlo version of the genetic algorithm Differential Evolution: easy Bayesian computing for real parameter spaces

    NARCIS (Netherlands)

    Braak, ter C.J.F.

    2006-01-01

    Differential Evolution (DE) is a simple genetic algorithm for numerical optimization in real parameter spaces. In a statistical context one would not just want the optimum but also its uncertainty. The uncertainty distribution can be obtained by a Bayesian analysis (after specifying prior and

  11. Deconvolution, differentiation and Fourier transformation algorithms for noise-containing data based on splines and global approximation

    NARCIS (Netherlands)

    Wormeester, Herbert; Sasse, A.G.B.M.; van Silfhout, Arend

    1988-01-01

    One of the main problems in the analysis of measured spectra is how to reduce the influence of noise in data processing. We show a deconvolution, a differentiation and a Fourier Transform algorithm that can be run on a small computer (64 K RAM) and suffer less from noise than commonly used routines.

  12. An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks

    Science.gov (United States)

    2014-01-01

    Background Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. Methods In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. Results The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. Conclusions The algorithm of probability graph isomorphism

  13. Algorithms

    Indian Academy of Sciences (India)

    algorithm design technique called 'divide-and-conquer'. One of ... Turtle graphics, September. 1996. 5. ... whole list named 'PO' is a pointer to the first element of the list; ..... Program for computing matrices X and Y and placing the result in C *).

  14. Algorithms

    Indian Academy of Sciences (India)

    algorithm that it is implicitly understood that we know how to generate the next natural ..... Explicit comparisons are made in line (1) where maximum and minimum is ... It can be shown that the function T(n) = 3/2n -2 is the solution to the above ...

  15. Differential and Cooperative Cell Adhesion Regulates Cellular Pattern in Sensory Epithelia.

    Science.gov (United States)

    Togashi, Hideru

    2016-01-01

    Animal tissues are composed of multiple cell types arranged in complex and elaborate patterns. In sensory epithelia, including the auditory epithelium and olfactory epithelium, different types of cells are arranged in unique mosaic patterns. These mosaic patterns are evolutionarily conserved, and are thought to be important for hearing and olfaction. Recent progress has provided accumulating evidence that the cellular pattern formation in epithelia involves cell rearrangements, movements, and shape changes. These morphogenetic processes are largely mediated by intercellular adhesion systems. Differential adhesion and cortical tension have been proposed to promote cell rearrangements. Many different types of cells in tissues express various types of cell adhesion molecules. Although cooperative mechanisms between multiple adhesive systems are likely to contribute to the production of complex cell patterns, our current understanding of the cooperative roles between multiple adhesion systems is insufficient to entirely explain the complex mechanisms underlying cellular patterning. Recent studies have revealed that nectins, in cooperation with cadherins, are crucial for the mosaic cellular patterning in sensory organs. The nectin and cadherin systems are interacted with one another, and these interactions provide cells with differential adhesive affinities for complex cellular pattern formations in sensory epithelia, which cannot be achieved by a single mechanism.

  16. A Receiver for Differential Space-Time -Shifted BPSK Modulation Based on Scalar-MSDD and the EM Algorithm

    Directory of Open Access Journals (Sweden)

    Kim Jae H

    2005-01-01

    Full Text Available In this paper, we consider the issue of blind detection of Alamouti-type differential space-time (ST modulation in static Rayleigh fading channels. We focus our attention on a -shifted BPSK constellation, introducing a novel transformation to the received signal such that this binary ST modulation, which has a second-order transmit diversity, is equivalent to QPSK modulation with second-order receive diversity. This equivalent representation allows us to apply a low-complexity detection technique specifically designed for receive diversity, namely, scalar multiple-symbol differential detection (MSDD. To further increase receiver performance, we apply an iterative expectation-maximization (EM algorithm which performs joint channel estimation and sequence detection. This algorithm uses minimum mean square estimation to obtain channel estimates and the maximum-likelihood principle to detect the transmitted sequence, followed by differential decoding. With receiver complexity proportional to the observation window length, our receiver can achieve the performance of a coherent maximal ratio combining receiver (with differential decoding in as few as a single EM receiver iteration, provided that the window size of the initial MSDD is sufficiently long. To further demonstrate that the MSDD is a vital part of this receiver setup, we show that an initial ST conventional differential detector would lead to strange convergence behavior in the EM algorithm.

  17. Algorithms to solve coupled systems of differential equations in terms of power series

    International Nuclear Information System (INIS)

    Ablinger, Jakob; Schneider, Carsten

    2016-08-01

    Using integration by parts relations, Feynman integrals can be represented in terms of coupled systems of differential equations. In the following we suppose that the unknown Feynman integrals can be given in power series representations, and that sufficiently many initial values of the integrals are given. Then there exist algorithms that decide constructively if the coefficients of their power series representations can be given within the class of nested sums over hypergeometric products. In this article we work out the calculation steps that solve this problem. First, we present a successful tactic that has been applied recently to challenging problems coming from massive 3-loop Feynman integrals. Here our main tool is to solve scalar linear recurrences within the class of nested sums over hypergeometric products. Second, we will present a new variation of this tactic which relies on more involved summation technologies but succeeds in reducing the problem to solve scalar recurrences with lower recurrence orders. The article works out the different challenges of this new tactic and demonstrates how they can be treated efficiently with our existing summation technologies.

  18. Differential evolution algorithm based automatic generation control for interconnected power systems with

    Directory of Open Access Journals (Sweden)

    Banaja Mohanty

    2014-09-01

    Full Text Available This paper presents the design and performance analysis of Differential Evolution (DE algorithm based Proportional–Integral (PI and Proportional–Integral–Derivative (PID controllers for Automatic Generation Control (AGC of an interconnected power system. Initially, a two area thermal system with governor dead-band nonlinearity is considered for the design and analysis purpose. In the proposed approach, the design problem is formulated as an optimization problem control and DE is employed to search for optimal controller parameters. Three different objective functions are used for the design purpose. The superiority of the proposed approach has been shown by comparing the results with a recently published Craziness based Particle Swarm Optimization (CPSO technique for the same interconnected power system. It is noticed that, the dynamic performance of DE optimized PI controller is better than CPSO optimized PI controllers. Additionally, controller parameters are tuned at different loading conditions so that an adaptive gain scheduling control strategy can be employed. The study is further extended to a more realistic network of two-area six unit system with different power generating units such as thermal, hydro, wind and diesel generating units considering boiler dynamics for thermal plants, Generation Rate Constraint (GRC and Governor Dead Band (GDB non-linearity.

  19. Identification of Differentially Expressed Genes between Original Breast Cancer and Xenograft Using Machine Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Deling Wang

    2018-03-01

    Full Text Available Breast cancer is one of the most common malignancies in women. Patient-derived tumor xenograft (PDX model is a cutting-edge approach for drug research on breast cancer. However, PDX still exhibits differences from original human tumors, thereby challenging the molecular understanding of tumorigenesis. In particular, gene expression changes after tissues are transplanted from human to mouse model. In this study, we propose a novel computational method by incorporating several machine learning algorithms, including Monte Carlo feature selection (MCFS, random forest (RF, and rough set-based rule learning, to identify genes with significant expression differences between PDX and original human tumors. First, 831 breast tumors, including 657 PDX and 174 human tumors, were collected. Based on MCFS and RF, 32 genes were then identified to be informative for the prediction of PDX and human tumors and can be used to construct a prediction model. The prediction model exhibits a Matthews coefficient correlation value of 0.777. Seven interpretable interactions within the informative gene were detected based on the rough set-based rule learning. Furthermore, the seven interpretable interactions can be well supported by previous experimental studies. Our study not only presents a method for identifying informative genes with differential expression but also provides insights into the mechanism through which gene expression changes after being transplanted from human tumor into mouse model. This work would be helpful for research and drug development for breast cancer.

  20. Identification of Differentially Expressed Genes between Original Breast Cancer and Xenograft Using Machine Learning Algorithms.

    Science.gov (United States)

    Wang, Deling; Li, Jia-Rui; Zhang, Yu-Hang; Chen, Lei; Huang, Tao; Cai, Yu-Dong

    2018-03-12

    Breast cancer is one of the most common malignancies in women. Patient-derived tumor xenograft (PDX) model is a cutting-edge approach for drug research on breast cancer. However, PDX still exhibits differences from original human tumors, thereby challenging the molecular understanding of tumorigenesis. In particular, gene expression changes after tissues are transplanted from human to mouse model. In this study, we propose a novel computational method by incorporating several machine learning algorithms, including Monte Carlo feature selection (MCFS), random forest (RF), and rough set-based rule learning, to identify genes with significant expression differences between PDX and original human tumors. First, 831 breast tumors, including 657 PDX and 174 human tumors, were collected. Based on MCFS and RF, 32 genes were then identified to be informative for the prediction of PDX and human tumors and can be used to construct a prediction model. The prediction model exhibits a Matthews coefficient correlation value of 0.777. Seven interpretable interactions within the informative gene were detected based on the rough set-based rule learning. Furthermore, the seven interpretable interactions can be well supported by previous experimental studies. Our study not only presents a method for identifying informative genes with differential expression but also provides insights into the mechanism through which gene expression changes after being transplanted from human tumor into mouse model. This work would be helpful for research and drug development for breast cancer.

  1. Improving Pattern Recognition and Neural Network Algorithms with Applications to Solar Panel Energy Optimization

    Science.gov (United States)

    Zamora Ramos, Ernesto

    Artificial Intelligence is a big part of automation and with today's technological advances, artificial intelligence has taken great strides towards positioning itself as the technology of the future to control, enhance and perfect automation. Computer vision includes pattern recognition and classification and machine learning. Computer vision is at the core of decision making and it is a vast and fruitful branch of artificial intelligence. In this work, we expose novel algorithms and techniques built upon existing technologies to improve pattern recognition and neural network training, initially motivated by a multidisciplinary effort to build a robot that helps maintain and optimize solar panel energy production. Our contributions detail an improved non-linear pre-processing technique to enhance poorly illuminated images based on modifications to the standard histogram equalization for an image. While the original motivation was to improve nocturnal navigation, the results have applications in surveillance, search and rescue, medical imaging enhancing, and many others. We created a vision system for precise camera distance positioning motivated to correctly locate the robot for capture of solar panel images for classification. The classification algorithm marks solar panels as clean or dirty for later processing. Our algorithm extends past image classification and, based on historical and experimental data, it identifies the optimal moment in which to perform maintenance on marked solar panels as to minimize the energy and profit loss. In order to improve upon the classification algorithm, we delved into feedforward neural networks because of their recent advancements, proven universal approximation and classification capabilities, and excellent recognition rates. We explore state-of-the-art neural network training techniques offering pointers and insights, culminating on the implementation of a complete library with support for modern deep learning architectures

  2. A Novel Discrete Differential Evolution Algorithm for the Vehicle Routing Problem in B2C E-Commerce

    Science.gov (United States)

    Xia, Chao; Sheng, Ying; Jiang, Zhong-Zhong; Tan, Chunqiao; Huang, Min; He, Yuanjian

    2015-12-01

    In this paper, a novel discrete differential evolution (DDE) algorithm is proposed to solve the vehicle routing problems (VRP) in B2C e-commerce, in which VRP is modeled by the incomplete graph based on the actual urban road system. First, a variant of classical VRP is described and a mathematical programming model for the variant is given. Second, the DDE is presented, where individuals are represented as the sequential encoding scheme, and a novel reparation operator is employed to repair the infeasible solutions. Furthermore, a FLOYD operator for dealing with the shortest route is embedded in the proposed DDE. Finally, an extensive computational study is carried out in comparison with the predatory search algorithm and genetic algorithm, and the results show that the proposed DDE is an effective algorithm for VRP in B2C e-commerce.

  3. Job characteristics and voluntary mobility in the Netherlands : differential education and gender patterns?

    NARCIS (Netherlands)

    Gesthuizen, M.

    2009-01-01

    Purpose – The purpose of this paper is to address the impact of the subjective evaluation of job characteristics on voluntary mobility, the impact of voluntary mobility on changes in these job characteristics, and differential education and gender patterns. Design/methodology/approach – Ordered and

  4. Job characteristics and voluntary mobility in The Netherlands: Differential education and gender patterns?

    NARCIS (Netherlands)

    Gesthuizen, M.J.W.

    2009-01-01

    Purpose - The purpose of this paper is to address the impact of the subjective evaluation of job characteristics on voluntary mobility, the impact of voluntary mobility on changes in these job characteristics, and differential education and gender patterns. Design/methodology/approach - Ordered and

  5. Preferential Trade Arrangements and the Pattern of Production and Trade when Inputs are Differentiated

    NARCIS (Netherlands)

    J.F. François (Joseph)

    2005-01-01

    textabstractThis paper is concerned with rules of origin when intermediate goods are differentiated. An analytical model emphasizes trade patterns and the relative importance of trade in intermediates given trade preferences. Econometric evidence based on intra-OECD trade in motor vehicles and motor

  6. Algorithms

    Indian Academy of Sciences (India)

    will become clear in the next article when we discuss a simple logo like programming language. ... Rod B may be used as an auxiliary store. The problem is to find an algorithm which performs this task. ... No disks are moved from A to Busing C as auxiliary rod. • move _disk (A, C);. (No + l)th disk is moved from A to C directly ...

  7. Multi-objective optimization of p-xylene oxidation process using an improved self-adaptive differential evolution algorithm

    Institute of Scientific and Technical Information of China (English)

    Lili Tao; Bin Xu; Zhihua Hu; Weimin Zhong

    2017-01-01

    The rise in the use of global polyester fiber contributed to strong demand of the Terephthalic acid (TPA). The liquid-phase catalytic oxidation of p-xylene (PX) to TPA is regarded as a critical and efficient chemical process in industry [1]. PX oxidation reaction involves many complex side reactions, among which acetic acid combustion and PX combustion are the most important. As the target product of this oxidation process, the quality and yield of TPA are of great concern. However, the improvement of the qualified product yield can bring about the high energy consumption, which means that the economic objectives of this process cannot be achieved simulta-neously because the two objectives are in conflict with each other. In this paper, an improved self-adaptive multi-objective differential evolution algorithm was proposed to handle the multi-objective optimization prob-lems. The immune concept is introduced to the self-adaptive multi-objective differential evolution algorithm (SADE) to strengthen the local search ability and optimization accuracy. The proposed algorithm is successfully tested on several benchmark test problems, and the performance measures such as convergence and divergence metrics are calculated. Subsequently, the multi-objective optimization of an industrial PX oxidation process is carried out using the proposed immune self-adaptive multi-objective differential evolution algorithm (ISADE). Optimization results indicate that application of ISADE can greatly improve the yield of TPA with low combustion loss without degenerating TA quality.

  8. Fuel spill identification by gas chromatography -- genetic algorithms/pattern recognition techniques

    International Nuclear Information System (INIS)

    Lavine, B.K.; Moores, A.J.; Faruque, A.

    1998-01-01

    Gas chromatography and pattern recognition methods were used to develop a potential method for typing jet fuels so a spill sample in the environment can be traced to its source. The test data consisted of 256 gas chromatograms of neat jet fuels. 31 fuels that have undergone weathering in a subsurface environment were correctly identified by type using discriminants developed from the gas chromatograms of the neat jet fuels. Coalescing poorly resolved peaks, which occurred during preprocessing, diminished the resolution and hence information content of the GC profiles. Nevertheless a genetic algorithm was able to extract enough information from these profiles to correctly classify the chromatograms of weathered fuels. This suggests that cheaper and simpler GC instruments ca be used to type jet fuels

  9. A MapReduce-Based Parallel Frequent Pattern Growth Algorithm for Spatiotemporal Association Analysis of Mobile Trajectory Big Data

    Directory of Open Access Journals (Sweden)

    Dawen Xia

    2018-01-01

    Full Text Available Frequent pattern mining is an effective approach for spatiotemporal association analysis of mobile trajectory big data in data-driven intelligent transportation systems. While existing parallel algorithms have been successfully applied to frequent pattern mining of large-scale trajectory data, two major challenges are how to overcome the inherent defects of Hadoop to cope with taxi trajectory big data including massive small files and how to discover the implicitly spatiotemporal frequent patterns with MapReduce. To conquer these challenges, this paper presents a MapReduce-based Parallel Frequent Pattern growth (MR-PFP algorithm to analyze the spatiotemporal characteristics of taxi operating using large-scale taxi trajectories with massive small file processing strategies on a Hadoop platform. More specifically, we first implement three methods, that is, Hadoop Archives (HAR, CombineFileInputFormat (CFIF, and Sequence Files (SF, to overcome the existing defects of Hadoop and then propose two strategies based on their performance evaluations. Next, we incorporate SF into Frequent Pattern growth (FP-growth algorithm and then implement the optimized FP-growth algorithm on a MapReduce framework. Finally, we analyze the characteristics of taxi operating in both spatial and temporal dimensions by MR-PFP in parallel. The results demonstrate that MR-PFP is superior to existing Parallel FP-growth (PFP algorithm in efficiency and scalability.

  10. Automatic boiling water reactor loading pattern design using ant colony optimization algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Wang, C.-D. [Department of Engineering and System Science, National Tsing Hua University, 101, Section 2 Kuang Fu Road, Hsinchu 30013, Taiwan (China); Nuclear Engineering Division, Institute of Nuclear Energy Research, No. 1000, Wenhua Rd., Jiaan Village, Longtan Township, Taoyuan County 32546, Taiwan (China)], E-mail: jdwang@iner.gov.tw; Lin Chaung [Department of Engineering and System Science, National Tsing Hua University, 101, Section 2 Kuang Fu Road, Hsinchu 30013, Taiwan (China)

    2009-08-15

    An automatic boiling water reactor (BWR) loading pattern (LP) design methodology was developed using the rank-based ant system (RAS), which is a variant of the ant colony optimization (ACO) algorithm. To reduce design complexity, only the fuel assemblies (FAs) of one eight-core positions were determined using the RAS algorithm, and then the corresponding FAs were loaded into the other parts of the core. Heuristic information was adopted to exclude the selection of the inappropriate FAs which will reduce search space, and thus, the computation time. When the LP was determined, Haling cycle length, beginning of cycle (BOC) shutdown margin (SDM), and Haling end of cycle (EOC) maximum fraction of limit for critical power ratio (MFLCPR) were calculated using SIMULATE-3 code, which were used to evaluate the LP for updating pheromone of RAS. The developed design methodology was demonstrated using FAs of a reference cycle of the BWR6 nuclear power plant. The results show that, the designed LP can be obtained within reasonable computation time, and has a longer cycle length than that of the original design.

  11. Algorithms for Image Analysis and Combination of Pattern Classifiers with Application to Medical Diagnosis

    Science.gov (United States)

    Georgiou, Harris

    2009-10-01

    Medical Informatics and the application of modern signal processing in the assistance of the diagnostic process in medical imaging is one of the more recent and active research areas today. This thesis addresses a variety of issues related to the general problem of medical image analysis, specifically in mammography, and presents a series of algorithms and design approaches for all the intermediate levels of a modern system for computer-aided diagnosis (CAD). The diagnostic problem is analyzed with a systematic approach, first defining the imaging characteristics and features that are relevant to probable pathology in mammo-grams. Next, these features are quantified and fused into new, integrated radio-logical systems that exhibit embedded digital signal processing, in order to improve the final result and minimize the radiological dose for the patient. In a higher level, special algorithms are designed for detecting and encoding these clinically interest-ing imaging features, in order to be used as input to advanced pattern classifiers and machine learning models. Finally, these approaches are extended in multi-classifier models under the scope of Game Theory and optimum collective deci-sion, in order to produce efficient solutions for combining classifiers with minimum computational costs for advanced diagnostic systems. The material covered in this thesis is related to a total of 18 published papers, 6 in scientific journals and 12 in international conferences.

  12. Development of pattern recognition algorithms for particles detection from atmospheric images

    International Nuclear Information System (INIS)

    Khatchadourian, S.

    2010-01-01

    The HESS experiment consists of a system of telescopes destined to observe cosmic rays. Since the project has achieved a high level of performances, a second phase of the project has been initiated. This implies the addition of a new telescope which is more sensitive than its predecessors and which is capable of collecting a huge amount of images. In this context, all data collected by the telescope can not be retained because of storage limitations. Therefore, a new real-time system trigger must be designed in order to select interesting events on the fly. The purpose of this thesis was to propose a trigger solution to efficiently discriminate events (images) which are captured by the telescope. The first part of this thesis was to develop pattern recognition algorithms to be implemented within the trigger. A processing chain based on neural networks and Zernike moments has been validated. The second part of the thesis has focused on the implementation of the proposed algorithms onto an FPGA target, taking into account the application constraints in terms of resources and execution time. (author)

  13. Hemodynamic and oxygen transport patterns for outcome prediction, therapeutic goals, and clinical algorithms to improve outcome. Feasibility of artificial intelligence to customize algorithms.

    Science.gov (United States)

    Shoemaker, W C; Patil, R; Appel, P L; Kram, H B

    1992-11-01

    A generalized decision tree or clinical algorithm for treatment of high-risk elective surgical patients was developed from a physiologic model based on empirical data. First, a large data bank was used to do the following: (1) describe temporal hemodynamic and oxygen transport patterns that interrelate cardiac, pulmonary, and tissue perfusion functions in survivors and nonsurvivors; (2) define optimal therapeutic goals based on the supranormal oxygen transport values of high-risk postoperative survivors; (3) compare the relative effectiveness of alternative therapies in a wide variety of clinical and physiologic conditions; and (4) to develop criteria for titration of therapy to the endpoints of the supranormal optimal goals using cardiac index (CI), oxygen delivery (DO2), and oxygen consumption (VO2) as proxy outcome measures. Second, a general purpose algorithm was generated from these data and tested in preoperatively randomized clinical trials of high-risk surgical patients. Improved outcome was demonstrated with this generalized algorithm. The concept that the supranormal values represent compensations that have survival value has been corroborated by several other groups. We now propose a unique approach to refine the generalized algorithm to develop customized algorithms and individualized decision analysis for each patient's unique problems. The present article describes a preliminary evaluation of the feasibility of artificial intelligence techniques to accomplish individualized algorithms that may further improve patient care and outcome.

  14. Heuristic rules embedded genetic algorithm to solve VVER loading pattern optimization problem

    International Nuclear Information System (INIS)

    Fatih, Alim; Kostandi, Ivanov

    2006-01-01

    Full text: Loading Pattern (LP) optimization is one of the most important aspects of the operation of nuclear reactors. A genetic algorithm (GA) code GARCO (Genetic Algorithm Reactor Optimization Code) has been developed with embedded heuristic techniques to perform optimization calculations for in-core fuel management tasks. GARCO is a practical tool that includes a unique methodology applicable for all types of Pressurized Water Reactor (PWR) cores having different geometries with an unlimited number of FA types in the inventory. GARCO was developed by modifying the classical representation of the genotype. Both the genotype representation and the basic algorithm have been modified to incorporate the in-core fuel management heuristics rules so as to obtain the best results in a shorter time. GARCO has three modes. Mode 1 optimizes the locations of the fuel assemblies (FAs) in the nuclear reactor core, Mode 2 optimizes the placement of the burnable poisons (BPs) in a selected LP, and Mode 3 optimizes simultaneously both the LP and the BP placement in the core. This study describes the basic algorithm for Mode 1. The GARCO code is applied to the VVER-1000 reactor hexagonal geometry core in this study. The M oby-Dick i s used as reactor physics code to deplete FAs in the core. It was developed to analyze the VVER reactors by SKODA Inc. To use these rules for creating the initial population with GA operators, the worth definition application is developed. Each FA has a worth value for each location. This worth is between 0 and 1. If worth of any FA for a location is larger than 0.5, this FA in this location is a good choice. When creating the initial population of LPs, a subroutine provides a percent of individuals, which have genes with higher than the 0.5 worth. The percentage of the population to be created without using worth definition is defined in the GARCO input. And also age concept has been developed to accelerate the GA calculation process in reaching the

  15. Differential diagnosis of periapical cyst using collagen birefringence pattern of the cyst wall

    Directory of Open Access Journals (Sweden)

    Hyo Jin Ji

    2017-05-01

    Full Text Available Objectives Periapical lesions, including periapical cyst (PC, periapical granuloma (PG, and periapical abscess (PA, are frequently affected by chemical/physical damage during root canal treatment or severe bacterial infection, and thus, the differential diagnosis of periapical lesions may be difficult due to the presence of severe inflammatory reaction. The aim of this study was to make differential diagnosis among PC, PG, and PA under polarizing microscope. Materials and Methods The collagen birefringence patterns of 319 cases of PC (n = 122, PG (n = 158, and PA (n = 39 obtained using a polarizing microscope were compared. In addition, 6 cases of periodontal fibroma (PF were used as positive controls. Results Collagen birefringence was condensed with a thick, linear band-like pattern in PC, but was short and irregularly scattered in PG, and scarce or absent in PA. PF showed intense collagen birefringence with a short, palisading pattern but no continuous band-like pattern. The linear band-like birefringence in PC was ascribed to pre-existing expansile tensile stress of the cyst wall. Conclusions In this study all PCs (n = 122 were distinguishable from PGs and PAs by their characteristic birefringence, despite the absence of lining epithelium (n = 20. Therefore, the authors suggest that the presence of linear band-like collagen birefringence of the cyst wall aids the diagnostic differentiation of PC from PG and PA.

  16. Differential diagnosis of periapical cyst using collagen birefringence pattern of the cyst wall.

    Science.gov (United States)

    Ji, Hyo Jin; Park, Se-Hee; Cho, Kyung-Mo; Lee, Suk Keun; Kim, Jin Woo

    2017-05-01

    Periapical lesions, including periapical cyst (PC), periapical granuloma (PG), and periapical abscess (PA), are frequently affected by chemical/physical damage during root canal treatment or severe bacterial infection, and thus, the differential diagnosis of periapical lesions may be difficult due to the presence of severe inflammatory reaction. The aim of this study was to make differential diagnosis among PC, PG, and PA under polarizing microscope. The collagen birefringence patterns of 319 cases of PC ( n = 122), PG ( n = 158), and PA ( n = 39) obtained using a polarizing microscope were compared. In addition, 6 cases of periodontal fibroma (PF) were used as positive controls. Collagen birefringence was condensed with a thick, linear band-like pattern in PC, but was short and irregularly scattered in PG, and scarce or absent in PA. PF showed intense collagen birefringence with a short, palisading pattern but no continuous band-like pattern. The linear band-like birefringence in PC was ascribed to pre-existing expansile tensile stress of the cyst wall. In this study all PCs ( n = 122) were distinguishable from PGs and PAs by their characteristic birefringence, despite the absence of lining epithelium ( n = 20). Therefore, the authors suggest that the presence of linear band-like collagen birefringence of the cyst wall aids the diagnostic differentiation of PC from PG and PA.

  17. Genetic Algorithm with Maximum-Minimum Crossover (GA-MMC) Applied in Optimization of Radiation Pattern Control of Phased-Array Radars for Rocket Tracking Systems

    Science.gov (United States)

    Silva, Leonardo W. T.; Barros, Vitor F.; Silva, Sandro G.

    2014-01-01

    In launching operations, Rocket Tracking Systems (RTS) process the trajectory data obtained by radar sensors. In order to improve functionality and maintenance, radars can be upgraded by replacing antennas with parabolic reflectors (PRs) with phased arrays (PAs). These arrays enable the electronic control of the radiation pattern by adjusting the signal supplied to each radiating element. However, in projects of phased array radars (PARs), the modeling of the problem is subject to various combinations of excitation signals producing a complex optimization problem. In this case, it is possible to calculate the problem solutions with optimization methods such as genetic algorithms (GAs). For this, the Genetic Algorithm with Maximum-Minimum Crossover (GA-MMC) method was developed to control the radiation pattern of PAs. The GA-MMC uses a reconfigurable algorithm with multiple objectives, differentiated coding and a new crossover genetic operator. This operator has a different approach from the conventional one, because it performs the crossover of the fittest individuals with the least fit individuals in order to enhance the genetic diversity. Thus, GA-MMC was successful in more than 90% of the tests for each application, increased the fitness of the final population by more than 20% and reduced the premature convergence. PMID:25196013

  18. Colchicine affects cell motility, pattern formation and stalk cell differentiation in Dictyostelium by altering calcium signaling.

    Science.gov (United States)

    Poloz, Yekaterina; O'Day, Danton H

    2012-04-01

    Previous work, verified here, showed that colchicine affects Dictyostelium pattern formation, disrupts morphogenesis, inhibits spore differentiation and induces terminal stalk cell differentiation. Here we show that colchicine specifically induces ecmB expression and enhances accumulation of ecmB-expressing cells at the posterior end of multicellular structures. Colchicine did not induce a nuclear translocation of DimB, a DIF-1 responsive transcription factor in vitro. It also induced terminal stalk cell differentiation in a mutant strain that does not produce DIF-1 (dmtA-) and after the treatment of cells with DIF-1 synthesis inhibitor cerulenin (100 μM). This suggests that colchicine induces the differentiation of ecmB-expressing cells independent of DIF-1 production and likely through a signaling pathway that is distinct from the one that is utilized by DIF-1. Depending on concentration, colchicine enhanced random cell motility, but not chemotaxis, by 3-5 fold (10-50 mM colchicine, respectively) through a Ca(2+)-mediated signaling pathway involving phospholipase C, calmodulin and heterotrimeric G proteins. Colchicine's effects were not due to microtubule depolymerization as other microtubule-depolymerizing agents did not have these effects. Finally normal morphogenesis and stalk and spore cell differentiation of cells treated with 10 mM colchicine were rescued through chelation of Ca2+ by BAPTA-AM and EDTA and calmodulin antagonism by W-7 but not PLC inhibition by U-73122. Morphogenesis or spore cell differentiation of cells treated with 50 mM colchicine could not be rescued by the above treatments but terminal stalk cell differentiation was inhibited by BAPTA-AM, EDTA and W-7, but not U-73122. Thus colchicine disrupts morphogenesis and induces stalk cell differentiation through a Ca(2+)-mediated signaling pathway involving specific changes in gene expression and cell motility. Copyright © 2011 International Society of Differentiation. Published by Elsevier B

  19. Automated Detection of Selective Logging in Amazon Forests Using Airborne Lidar Data and Pattern Recognition Algorithms

    Science.gov (United States)

    Keller, M. M.; d'Oliveira, M. N.; Takemura, C. M.; Vitoria, D.; Araujo, L. S.; Morton, D. C.

    2012-12-01

    Selective logging, the removal of several valuable timber trees per hectare, is an important land use in the Brazilian Amazon and may degrade forests through long term changes in structure, loss of forest carbon and species diversity. Similar to deforestation, the annual area affected by selected logging has declined significantly in the past decade. Nonetheless, this land use affects several thousand km2 per year in Brazil. We studied a 1000 ha area of the Antimary State Forest (FEA) in the State of Acre, Brazil (9.304 ○S, 68.281 ○W) that has a basal area of 22.5 m2 ha-1 and an above-ground biomass of 231 Mg ha-1. Logging intensity was low, approximately 10 to 15 m3 ha-1. We collected small-footprint airborne lidar data using an Optech ALTM 3100EA over the study area once each in 2010 and 2011. The study area contained both recent and older logging that used both conventional and technologically advanced logging techniques. Lidar return density averaged over 20 m-2 for both collection periods with estimated horizontal and vertical precision of 0.30 and 0.15 m. A relative density model comparing returns from 0 to 1 m elevation to returns in 1-5 m elevation range revealed the pattern of roads and skid trails. These patterns were confirmed by ground-based GPS survey. A GIS model of the road and skid network was built using lidar and ground data. We tested and compared two pattern recognition approaches used to automate logging detection. Both segmentation using commercial eCognition segmentation and a Frangi filter algorithm identified the road and skid trail network compared to the GIS model. We report on the effectiveness of these two techniques.

  20. Design Optimization of Mechanical Components Using an Enhanced Teaching-Learning Based Optimization Algorithm with Differential Operator

    Directory of Open Access Journals (Sweden)

    B. Thamaraikannan

    2014-01-01

    Full Text Available This paper studies in detail the background and implementation of a teaching-learning based optimization (TLBO algorithm with differential operator for optimization task of a few mechanical components, which are essential for most of the mechanical engineering applications. Like most of the other heuristic techniques, TLBO is also a population-based method and uses a population of solutions to proceed to the global solution. A differential operator is incorporated into the TLBO for effective search of better solutions. To validate the effectiveness of the proposed method, three typical optimization problems are considered in this research: firstly, to optimize the weight in a belt-pulley drive, secondly, to optimize the volume in a closed coil helical spring, and finally to optimize the weight in a hollow shaft. have been demonstrated. Simulation result on the optimization (mechanical components problems reveals the ability of the proposed methodology to find better optimal solutions compared to other optimization algorithms.

  1. Assessing the performance of a differential evolution algorithm in structural damage detection by varying the objective function

    OpenAIRE

    Villalba-Morales, Jesús Daniel; Laier, José Elias

    2014-01-01

    Structural damage detection has become an important research topic in certain segments of the engineering community. These methodologies occasionally formulate an optimization problem by defining an objective function based on dynamic parameters, with metaheuristics used to find the solution. In this study, damage localization and quantification is performed by an Adaptive Differential Evolution algorithm, which solves the associated optimization problem. Furthermore, this paper looks at the ...

  2. Algorithm for Overcoming the Curse of Dimensionality for Certain Non-convex Hamilton-Jacobi Equations, Projections and Differential Games

    Science.gov (United States)

    2016-05-01

    0.5 × 10−8. Our algorithm is implemented in C++ on an 1.7 GHz Intel Core i7-4650U CPU. Linear algebra packages BLAS [40] and LAPACK [41] are used to...subproblems. Our approach is expected to have wide applications in continuous dynamic games, control theory problems, and elsewhere. Mathematics...differential dynamic games, control theory problems, and dynamical systems coming from the physical world, e.g. [11]. An important application is to

  3. Six1 is essential for differentiation and patterning of the mammalian auditory sensory epithelium.

    Directory of Open Access Journals (Sweden)

    Ting Zhang

    2017-09-01

    Full Text Available The organ of Corti in the cochlea is a two-cell layered epithelium: one cell layer of mechanosensory hair cells that align into one row of inner and three rows of outer hair cells interdigitated with one cell layer of underlying supporting cells along the entire length of the cochlear spiral. These two types of epithelial cells are derived from common precursors in the four- to five-cell layered primordium and acquire functionally important shapes during terminal differentiation through the thinning process and convergent extension. Here, we have examined the role of Six1 in the establishment of the auditory sensory epithelium. Our data show that prior to terminal differentiation of the precursor cells, deletion of Six1 leads to formation of only a few hair cells and defective patterning of the sensory epithelium. Previous studies have suggested that downregulation of Sox2 expression in differentiating hair cells must occur after Atoh1 mRNA activation in order to allow Atoh1 protein accumulation due to antagonistic effects between Atoh1 and Sox2. Our analysis indicates that downregulation of Sox2 in the differentiating hair cells depends on Six1 activity. Furthermore, we found that Six1 is required for the maintenance of Fgf8 expression and dynamic distribution of N-cadherin and E-cadherin in the organ of Corti during differentiation. Together, our analyses uncover essential roles of Six1 in hair cell differentiation and formation of the organ of Corti in the mammalian cochlea.

  4. Repetition suppression and multi-voxel pattern similarity differentially track implicit and explicit visual memory.

    Science.gov (United States)

    Ward, Emily J; Chun, Marvin M; Kuhl, Brice A

    2013-09-11

    Repeated exposure to a visual stimulus is associated with corresponding reductions in neural activity, particularly within visual cortical areas. It has been argued that this phenomenon of repetition suppression is related to increases in processing fluency or implicit memory. However, repetition of a visual stimulus can also be considered in terms of the similarity of the pattern of neural activity elicited at each exposure--a measure that has recently been linked to explicit memory. Despite the popularity of each of these measures, direct comparisons between the two have been limited, and the extent to which they differentially (or similarly) relate to behavioral measures of memory has not been clearly established. In the present study, we compared repetition suppression and pattern similarity as predictors of both implicit and explicit memory. Using functional magnetic resonance imaging, we scanned 20 participants while they viewed and categorized repeated presentations of scenes. Repetition priming (facilitated categorization across repetitions) was used as a measure of implicit memory, and subsequent scene recognition was used as a measure of explicit memory. We found that repetition priming was predicted by repetition suppression in prefrontal, parietal, and occipitotemporal regions; however, repetition priming was not predicted by pattern similarity. In contrast, subsequent explicit memory was predicted by pattern similarity (across repetitions) in some of the same occipitotemporal regions that exhibited a relationship between priming and repetition suppression; however, explicit memory was not related to repetition suppression. This striking double dissociation indicates that repetition suppression and pattern similarity differentially track implicit and explicit learning.

  5. Multivoxel Patterns Reveal Functionally Differentiated Networks Underlying Auditory Feedback Processing of Speech

    DEFF Research Database (Denmark)

    Zheng, Zane Z.; Vicente-Grabovetsky, Alejandro; MacDonald, Ewen N.

    2013-01-01

    The everyday act of speaking involves the complex processes of speech motor control. An important component of control is monitoring, detection, and processing of errors when auditory feedback does not correspond to the intended motor gesture. Here we show, using fMRI and converging operations...... within a multivoxel pattern analysis framework, that this sensorimotor process is supported by functionally differentiated brain networks. During scanning, a real-time speech-tracking system was used to deliver two acoustically different types of distorted auditory feedback or unaltered feedback while...... human participants were vocalizing monosyllabic words, and to present the same auditory stimuli while participants were passively listening. Whole-brain analysis of neural-pattern similarity revealed three functional networks that were differentially sensitive to distorted auditory feedback during...

  6. Evidence for universality and cultural variation of differential emotion response patterning.

    Science.gov (United States)

    Scherer, K R; Wallbott, H G

    1994-02-01

    The major controversy concerning psychobiological universality of differential emotion patterning versus cultural relativity of emotional experience is briefly reviewed. Data from a series of cross-cultural questionnaire studies in 37 countries on 5 continents are reported and used to evaluate the respective claims of the proponents in the debate. Results show highly significant main effects and strong effect sizes for the response differences across 7 major emotions (joy, fear, anger, sadness, disgust, shame, and guilt). Profiles of cross-culturally stable differences among the emotions with respect to subjective feeling, physiological symptoms, and expressive behavior are also reported. The empirical evidence is interpreted as supporting theories that postulate both a high degree of universality of differential emotion patterning and important cultural differences in emotion elicitation, regulation, symbolic representation, and social sharing.

  7. Constructing and predicting solitary pattern solutions for nonlinear time-fractional dispersive partial differential equations

    Science.gov (United States)

    Arqub, Omar Abu; El-Ajou, Ahmad; Momani, Shaher

    2015-07-01

    Building fractional mathematical models for specific phenomena and developing numerical or analytical solutions for these fractional mathematical models are crucial issues in mathematics, physics, and engineering. In this work, a new analytical technique for constructing and predicting solitary pattern solutions of time-fractional dispersive partial differential equations is proposed based on the generalized Taylor series formula and residual error function. The new approach provides solutions in the form of a rapidly convergent series with easily computable components using symbolic computation software. For method evaluation and validation, the proposed technique was applied to three different models and compared with some of the well-known methods. The resultant simulations clearly demonstrate the superiority and potentiality of the proposed technique in terms of the quality performance and accuracy of substructure preservation in the construct, as well as the prediction of solitary pattern solutions for time-fractional dispersive partial differential equations.

  8. Consistent Differential Expression Pattern (CDEP) on microarray to identify genes related to metastatic behavior.

    Science.gov (United States)

    Tsoi, Lam C; Qin, Tingting; Slate, Elizabeth H; Zheng, W Jim

    2011-11-11

    To utilize the large volume of gene expression information generated from different microarray experiments, several meta-analysis techniques have been developed. Despite these efforts, there remain significant challenges to effectively increasing the statistical power and decreasing the Type I error rate while pooling the heterogeneous datasets from public resources. The objective of this study is to develop a novel meta-analysis approach, Consistent Differential Expression Pattern (CDEP), to identify genes with common differential expression patterns across different datasets. We combined False Discovery Rate (FDR) estimation and the non-parametric RankProd approach to estimate the Type I error rate in each microarray dataset of the meta-analysis. These Type I error rates from all datasets were then used to identify genes with common differential expression patterns. Our simulation study showed that CDEP achieved higher statistical power and maintained low Type I error rate when compared with two recently proposed meta-analysis approaches. We applied CDEP to analyze microarray data from different laboratories that compared transcription profiles between metastatic and primary cancer of different types. Many genes identified as differentially expressed consistently across different cancer types are in pathways related to metastatic behavior, such as ECM-receptor interaction, focal adhesion, and blood vessel development. We also identified novel genes such as AMIGO2, Gem, and CXCL11 that have not been shown to associate with, but may play roles in, metastasis. CDEP is a flexible approach that borrows information from each dataset in a meta-analysis in order to identify genes being differentially expressed consistently. We have shown that CDEP can gain higher statistical power than other existing approaches under a variety of settings considered in the simulation study, suggesting its robustness and insensitivity to data variation commonly associated with microarray

  9. A Memetic Differential Evolution Algorithm Based on Dynamic Preference for Constrained Optimization Problems

    Directory of Open Access Journals (Sweden)

    Ning Dong

    2014-01-01

    functions are executed, and comparisons with five state-of-the-art algorithms are made. The results illustrate that the proposed algorithm is competitive with and in some cases superior to the compared ones in terms of the quality, efficiency, and the robustness of the obtained results.

  10. A hybrid artificial bee colony algorithm and pattern search method for inversion of particle size distribution from spectral extinction data

    Science.gov (United States)

    Wang, Li; Li, Feng; Xing, Jian

    2017-10-01

    In this paper, a hybrid artificial bee colony (ABC) algorithm and pattern search (PS) method is proposed and applied for recovery of particle size distribution (PSD) from spectral extinction data. To be more useful and practical, size distribution function is modelled as the general Johnson's ? function that can overcome the difficulty of not knowing the exact type beforehand encountered in many real circumstances. The proposed hybrid algorithm is evaluated through simulated examples involving unimodal, bimodal and trimodal PSDs with different widths and mean particle diameters. For comparison, all examples are additionally validated by the single ABC algorithm. In addition, the performance of the proposed algorithm is further tested by actual extinction measurements with real standard polystyrene samples immersed in water. Simulation and experimental results illustrate that the hybrid algorithm can be used as an effective technique to retrieve the PSDs with high reliability and accuracy. Compared with the single ABC algorithm, our proposed algorithm can produce more accurate and robust inversion results while taking almost comparative CPU time over ABC algorithm alone. The superiority of ABC and PS hybridization strategy in terms of reaching a better balance of estimation accuracy and computation effort increases its potentials as an excellent inversion technique for reliable and efficient actual measurement of PSD.

  11. Real-time intelligent pattern recognition algorithm for surface EMG signals

    Directory of Open Access Journals (Sweden)

    Jahed Mehran

    2007-12-01

    Full Text Available Abstract Background Electromyography (EMG is the study of muscle function through the inquiry of electrical signals that the muscles emanate. EMG signals collected from the surface of the skin (Surface Electromyogram: sEMG can be used in different applications such as recognizing musculoskeletal neural based patterns intercepted for hand prosthesis movements. Current systems designed for controlling the prosthetic hands either have limited functions or can only be used to perform simple movements or use excessive amount of electrodes in order to achieve acceptable results. In an attempt to overcome these problems we have proposed an intelligent system to recognize hand movements and have provided a user assessment routine to evaluate the correctness of executed movements. Methods We propose to use an intelligent approach based on adaptive neuro-fuzzy inference system (ANFIS integrated with a real-time learning scheme to identify hand motion commands. For this purpose and to consider the effect of user evaluation on recognizing hand movements, vision feedback is applied to increase the capability of our system. By using this scheme the user may assess the correctness of the performed hand movement. In this work a hybrid method for training fuzzy system, consisting of back-propagation (BP and least mean square (LMS is utilized. Also in order to optimize the number of fuzzy rules, a subtractive clustering algorithm has been developed. To design an effective system, we consider a conventional scheme of EMG pattern recognition system. To design this system we propose to use two different sets of EMG features, namely time domain (TD and time-frequency representation (TFR. Also in order to decrease the undesirable effects of the dimension of these feature sets, principle component analysis (PCA is utilized. Results In this study, the myoelectric signals considered for classification consists of six unique hand movements. Features chosen for EMG signal

  12. Simulation of Cell Patterning Triggered by Cell Death and Differential Adhesion in Drosophila Wing.

    Science.gov (United States)

    Nagai, Tatsuzo; Honda, Hisao; Takemura, Masahiko

    2018-02-27

    The Drosophila wing exhibits a well-ordered cell pattern, especially along the posterior margin, where hair cells are arranged in a zigzag pattern in the lateral view. Based on an experimental result observed during metamorphosis of Drosophila, we considered that a pattern of initial cells autonomously develops to the zigzag pattern through cell differentiation, intercellular communication, and cell death (apoptosis) and performed computer simulations of a cell-based model of vertex dynamics for tissues. The model describes the epithelial tissue as a monolayer cell sheet of polyhedral cells. Their vertices move according to equations of motion, minimizing the sum total of the interfacial and elastic energies of cells. The interfacial energy densities between cells are introduced consistently with an ideal zigzag cell pattern, extracted from the experimental result. The apoptosis of cells is modeled by gradually reducing their equilibrium volume to zero and by assuming that the hair cells prohibit neighboring cells from undergoing apoptosis. Based on experimental observations, we also assumed wing elongation along the proximal-distal axis. Starting with an initial cell pattern similar to the micrograph experimentally obtained just before apoptosis, we carried out the simulations according to the model mentioned above and successfully reproduced the ideal zigzag cell pattern. This elucidates a physical mechanism of patterning triggered by cell apoptosis theoretically and exemplifies, to our knowledge, a new framework to study apoptosis-induced patterning. We conclude that the zigzag cell pattern is formed by an autonomous communicative process among the participant cells. Copyright © 2018 Biophysical Society. All rights reserved.

  13. Genetic Differentiation in Insular Lowland Rainforests: Insights from Historical Demographic Patterns in Philippine Birds.

    Science.gov (United States)

    Sánchez-González, Luis Antonio; Hosner, Peter A; Moyle, Robert G

    2015-01-01

    Phylogeographic studies of Philippine birds support that deep genetic structure occurs across continuous lowland forests within islands, despite the lack of obvious contemporary isolation mechanisms. To examine the pattern and tempo of diversification within Philippine island forests, and test if common mechanisms are responsible for observed differentiation, we focused on three co-distributed lowland bird taxa endemic to Greater Luzon and Greater Negros-Panay: Blue-headed Fantail (Rhipidura cyaniceps), White-browed Shama (Copsychus luzoniensis), and Lemon-throated Leaf-Warbler (Phylloscopus cebuensis). Each species has two described subspecies within Greater Luzon, and a single described subspecies on Greater Negros/Panay. Each of the three focal species showed a common geographic pattern of two monophyletic groups in Greater Luzon sister to a third monophyletic group found in Greater Negros-Panay, suggesting that common or similar biogeographic processes may have produced similar distributions. However, studied species displayed variable levels of mitochondrial DNA differentiation between clades, and genetic differentiation within Luzon was not necessarily concordant with described subspecies boundaries. Population genetic parameters for the three species suggested both rapid population growth from small numbers and geographic expansion across Luzon Island. Estimates of the timing of population expansion further supported that these events occurred asynchronously throughout the Pleistocene in the focal species, demanding particular explanations for differentiation, and support that co-distribution may be secondarily congruent.

  14. Numerical simulation for Jeffery-Hamel flow and heat transfer of micropolar fluid based on differential evolution algorithm

    Science.gov (United States)

    Ara, Asmat; Khan, Najeeb Alam; Naz, Farah; Raja, Muhammad Asif Zahoor; Rubbab, Qammar

    2018-01-01

    This article explores the Jeffery-Hamel flow of an incompressible non-Newtonian fluid inside non-parallel walls and observes the influence of heat transfer in the flow field. The fluid is considered to be micropolar fluid that flows in a convergent/divergent channel. The governing nonlinear partial differential equations (PDEs) are converted to nonlinear coupled ordinary differential equations (ODEs) with the help of a suitable similarity transformation. The resulting nonlinear analysis is determined analytically with the utilization of the Taylor optimization method based on differential evolution (DE) algorithm. In order to understand the flow field, the effects of pertinent parameters such as the coupling parameter, spin gradient viscosity parameter and the Reynolds number have been examined on velocity and temperature profiles. It concedes that the good results can be attained by an implementation of the proposed method. Ultimately, the accuracy of the method is confirmed by comparing the present results with the results obtained by Runge-Kutta method.

  15. Identifying differential miR and gene consensus patterns in peripheral blood of patients with cardiovascular diseases from literature data.

    Science.gov (United States)

    Šatrauskienė, Agnė; Navickas, Rokas; Laucevičius, Aleksandras; Huber, Heinrich J

    2017-06-30

    Numerous recent studies suggest the potential of circulating MicroRNAs (miRs) in peripheral blood samples as diagnostic or prognostic markers for coronary artery disease (CAD), acute coronary syndrome (ACS) and heart failure (HF). However, literature often remains inconclusive regarding as to which markers are most indicative for which of the above diseases. This shortcoming is mainly due to the lack of a systematic analyses and absence of information on the functional pathophysiological role of these miRs and their target genes. We here provide an-easy-to-use scoring approach to investigate the likelihood of regulation of several miRs and their target genes from literature by identifying consensus patterns of regulation. We therefore have screened over 1000 articles that study mRNA markers in cardiovascular and metabolic diseases, and devised a scoring algorithm to identify consensus means for miRs and genes regulation across several studies. We then aimed to identify differential markers between CAD, ACS and HF. We first identified miRs (miR-122, -126, -223, -138 and -370) as commonly regulated within a group of metabolic disease, while investigating cardiac-related pathologies (CAD, ACS, HF) revealed a decisive role of miR-1, -499, -208b, and -133a. Looking at differential markers between cardiovascular disease revealed miR-1, miR-208a and miR-133a to distinguish ACS and CAD to HF. Relating differentially expressed miRs to their putative gene targets using MirTarBase, we further identified HCN2/4 and LASP1 as potential markers of CAD and ACS, but not in HF. Likewise, BLC-2 was found oppositely regulated between CAD and HF. Interestingly, while studying overlap in target genes between CAD, ACS and HF only revealed little similarities, mapping these genes to gene ontology terms revealed a surprising similarity between CAD and ACS compared to HF. We conclude that our analysis using gene and miR scores allows the extraction of meaningful markers and the elucidation

  16. Iterative Observer-based Estimation Algorithms for Steady-State Elliptic Partial Differential Equation Systems

    KAUST Repository

    Majeed, Muhammad Usman

    2017-01-01

    the problems are formulated on higher dimensional space domains. However, in this dissertation, feedback based state estimation algorithms, known as state observers, are developed to solve such steady-state problems using one of the space variables as time

  17. A Lie-Deprit perturbation algorithm for linear differential equations with periodic coefficients

    OpenAIRE

    Casas Pérez, Fernando; Chiralt Monleon, Cristina

    2014-01-01

    A perturbative procedure based on the Lie-Deprit algorithm of classical mechanics is proposed to compute analytic approximations to the fundamental matrix of linear di erential equations with periodic coe cients. These approximations reproduce the structure assured by the Floquet theorem. Alternatively, the algorithm provides explicit approximations to the Lyapunov transformation reducing the original periodic problem to an autonomous sys- tem and also to its characteristic ...

  18. Using of FPGA coprocessor for improving the execution speed of the pattern recognition algorithm for ATLAS - high energy physics experiment

    CERN Document Server

    Hinkelbein, C; Kugel, A; Männer, R; Miiller, M

    2004-01-01

    Pattern recognition algorithms are used in experimental High Energy physics for getting parameters (features) of particles tracks in detectors. It is particularly important to have fast algorithms in trigger system. This paper investigates the suitability of using FPGA coprocessor for speedup of the TRT-LUT algorithm - one of the feature extraction algorithms for second level trigger for ATLAS experiment (CERN). Two realization of the same algorithm have been compared: C++ realization tested on a computer equipped with dual Xeon 2.4 GHz CPU, 64-bit, 66MHz PCI bus, 1024Mb DDR RAM main memories with Red Hat Linux 7.1 and hybrid C++ - VHDL realisation tested on same PC equipped in addition by MPRACE board (FPGA-Coprocessor board based on Xilinx Virtex-II FPGA and made as 64-bit, 66 MHz PCI card developed at the University of Mannheim). Usage of the FPGA coprocessor can give some reasonable speedup in contrast to general purpose processor only for those algorithms (or parts of algorithms), for which there is a po...

  19. Articular dysfunction patterns in patients with mechanical low back pain: A clinical algorithm to guide specific mobilization and manipulation techniques.

    Science.gov (United States)

    Dewitte, V; Cagnie, B; Barbe, T; Beernaert, A; Vanthillo, B; Danneels, L

    2015-06-01

    Recent systematic reviews have demonstrated reasonable evidence that lumbar mobilization and manipulation techniques are beneficial. However, knowledge on optimal techniques and doses, and its clinical reasoning is currently lacking. To address this, a clinical algorithm is presented so as to guide therapists in their clinical reasoning to identify patients who are likely to respond to lumbar mobilization and/or manipulation and to direct appropriate technique selection. Key features in subjective and clinical examination suggestive of mechanical nociceptive pain probably arising from articular structures, can categorize patients into distinct articular dysfunction patterns. Based on these patterns, specific mobilization and manipulation techniques are suggested. This clinical algorithm is merely based on empirical clinical expertise and complemented through knowledge exchange between international colleagues. The added value of the proposed articular dysfunction patterns should be considered within a broader perspective. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. [Characteristics of temporal-spatial differentiation in landscape pattern vulnerability in Nansihu Lake wetland, China.

    Science.gov (United States)

    Liang, Jia Xin; Li, Xin Ju

    2018-02-01

    With remote sensing images from 1985, 2000 Lantsat 5 TM and 2015 Lantsat 8 OLI as data sources, we tried to select the suitable research scale and examine the temporal-spatial diffe-rentiation with such scale in the Nansihu Lake wetland by using landscape pattern vulnerability index constructed by sensitivity index and adaptability index, and combined with space statistics such as semivariogram and spatial autocorrelation. The results showed that 1 km × 1 km equidistant grid was the suitable research scale, which could eliminate the influence of spatial heterogeneity induced by random factors. From 1985 to 2015, the landscape pattern vulnerability in the Nansihu Lake wetland deteriorated gradually. The high-risk area of landscape pattern vulnerability dramatically expanded with time. The spatial heterogeneity of landscape pattern vulnerability increased, and the influence of non-structural factors on landscape pattern vulnerability strengthened. Spatial variability affected by spatial autocorrelation slightly weakened. Landscape pattern vulnerability had strong general spatial positive correlation, with the significant form of spatial agglomeration. The positive spatial autocorrelation continued to increase and the phenomenon of spatial concentration was more and more obvious over time. The local autocorrelation mainly based on high-high accumulation zone and low-low accumulation zone had stronger spatial autocorrelation among neighboring space units. The high-high accumulation areas showed the strongest level of significance, and the significant level of low-low accumulation zone increased with time. Natural factors, such as temperature and precipitation, affected water-level and landscape distribution, and thus changed the landscape patterns vulnerability of Nansihu Lake wetland. The dominant driver for the deterioration of landscape patterns vulnerability was human activities, including social economy activity and policy system.

  1. A regression-based differential expression detection algorithm for microarray studies with ultra-low sample size.

    Directory of Open Access Journals (Sweden)

    Daniel Vasiliu

    Full Text Available Global gene expression analysis using microarrays and, more recently, RNA-seq, has allowed investigators to understand biological processes at a system level. However, the identification of differentially expressed genes in experiments with small sample size, high dimensionality, and high variance remains challenging, limiting the usability of these tens of thousands of publicly available, and possibly many more unpublished, gene expression datasets. We propose a novel variable selection algorithm for ultra-low-n microarray studies using generalized linear model-based variable selection with a penalized binomial regression algorithm called penalized Euclidean distance (PED. Our method uses PED to build a classifier on the experimental data to rank genes by importance. In place of cross-validation, which is required by most similar methods but not reliable for experiments with small sample size, we use a simulation-based approach to additively build a list of differentially expressed genes from the rank-ordered list. Our simulation-based approach maintains a low false discovery rate while maximizing the number of differentially expressed genes identified, a feature critical for downstream pathway analysis. We apply our method to microarray data from an experiment perturbing the Notch signaling pathway in Xenopus laevis embryos. This dataset was chosen because it showed very little differential expression according to limma, a powerful and widely-used method for microarray analysis. Our method was able to detect a significant number of differentially expressed genes in this dataset and suggest future directions for investigation. Our method is easily adaptable for analysis of data from RNA-seq and other global expression experiments with low sample size and high dimensionality.

  2. Robust stratification of breast cancer subtypes using differential patterns of transcript isoform expression.

    Directory of Open Access Journals (Sweden)

    Thomas P Stricker

    2017-03-01

    Full Text Available Breast cancer, the second leading cause of cancer death of women worldwide, is a heterogenous disease with multiple different subtypes. These subtypes carry important implications for prognosis and therapy. Interestingly, it is known that these different subtypes not only have different biological behaviors, but also have distinct gene expression profiles. However, it has not been rigorously explored whether particular transcriptional isoforms are also differentially expressed among breast cancer subtypes, or whether transcript isoforms from the same sets of genes can be used to differentiate subtypes. To address these questions, we analyzed the patterns of transcript isoform expression using a small set of RNA-sequencing data for eleven Estrogen Receptor positive (ER+ subtype and fourteen triple negative (TN subtype tumors. We identified specific sets of isoforms that distinguish these tumor subtypes with higher fidelity than standard mRNA expression profiles. We found that alternate promoter usage, alternative splicing, and alternate 3'UTR usage are differentially regulated in breast cancer subtypes. Profiling of isoform expression in a second, independent cohort of 68 tumors confirmed that expression of splice isoforms differentiates breast cancer subtypes. Furthermore, analysis of RNAseq data from 594 cases from the TCGA cohort confirmed the ability of isoform usage to distinguish breast cancer subtypes. Also using our expression data, we identified several RNA processing factors that were differentially expressed between tumor subtypes and/or regulated by estrogen receptor, including YBX1, YBX2, MAGOH, MAGOHB, and PCBP2. RNAi knock-down of these RNA processing factors in MCF7 cells altered isoform expression. These results indicate that global dysregulation of splicing in breast cancer occurs in a subtype-specific and reproducible manner and is driven by specific differentially expressed RNA processing factors.

  3. AGAMOUS controls GIANT KILLER, a multifunctional chromatin modifier in reproductive organ patterning and differentiation.

    Directory of Open Access Journals (Sweden)

    Kian-Hong Ng

    2009-11-01

    Full Text Available The Arabidopsis homeotic protein AGAMOUS (AG, a MADS domain transcription factor, specifies reproductive organ identity during flower development. Using a binding assay and expression analysis, we identified a direct target of AG, GIANT KILLER (GIK, which fine-tunes the expression of multiple genes downstream of AG. The GIK protein contains an AT-hook DNA binding motif that is widely found in chromosomal proteins and that binds to nuclear matrix attachment regions of DNA elements. Overexpression and loss of function of GIK cause wide-ranging defects in patterning and differentiation of reproductive organs. GIK directly regulates the expression of several key transcriptional regulators, including ETTIN/AUXIN RESPONSE FACTOR 3 (ETT/ARF3 that patterns the gynoecium, by binding to the matrix attachment regions of target promoters. Overexpression of GIK causes a swift and dynamic change in repressive histone modification in the ETT promoter. We propose that GIK acts as a molecular node downstream of the homeotic protein AG, regulating patterning and differentiation of reproductive organs through chromatin organization.

  4. Tremor pattern differentiates drug-induced resting tremor from Parkinson disease.

    Science.gov (United States)

    Nisticò, R; Fratto, A; Vescio, B; Arabia, G; Sciacca, G; Morelli, M; Labate, A; Salsone, M; Novellino, F; Nicoletti, A; Petralia, A; Gambardella, A; Zappia, M; Quattrone, A

    2016-04-01

    DAT-SPECT, is a well-established procedure for distinguishing drug-induced parkinsonism from Parkinson's disease (PD). We investigated the usefulness of blink reflex recovery cycle (BRrc) and of electromyographic parameters of resting tremor for the differentiation of patients with drug-induced parkinsonism with resting tremor (rDIP) from those with resting tremor due to PD. This was a cross-sectional study. In 16 patients with rDIP and 18 patients with PD we analysed electrophysiological parameters (amplitude, duration, burst and pattern) of resting tremor. BRrc at interstimulus intervals (ISI) of 100, 150, 200, 300, 400, 500 and 750 msec was also analysed in patients with rDIP, patients with PD and healthy controls. All patients and controls underwent DAT-SPECT. Rest tremor amplitude was higher in PD patients than in rDIP patients (p tremor showed a synchronous pattern in all patients with rDIP, whereas it had an alternating pattern in all PD patients (p tremor can be considered a useful investigation for differentiating rDIP from PD. Copyright © 2016. Published by Elsevier Ltd.

  5. Image processing and pattern recognition algorithms for evaluation of crossed immunoelectrophoretic patterns (crossed radioimmunoelectrophoresis analysis manager; CREAM)

    DEFF Research Database (Denmark)

    Søndergaard, I; Poulsen, L K; Hagerup, M

    1987-01-01

    points along the precipitation curve in the curve-fitting process. The system has been tested on crossed immunoelectrophoretic patterns as well as crossed radioimmunoelectrophoretic patterns and it has been shown that the system can recognize the same precipitation curves on different immunoplates...

  6. An efficient reconstruction algorithm for differential phase-contrast tomographic images from a limited number of views

    International Nuclear Information System (INIS)

    Sunaguchi, Naoki; Yuasa, Tetsuya; Gupta, Rajiv; Ando, Masami

    2015-01-01

    The main focus of this paper is reconstruction of tomographic phase-contrast image from a set of projections. We propose an efficient reconstruction algorithm for differential phase-contrast computed tomography that can considerably reduce the number of projections required for reconstruction. The key result underlying this research is a projection theorem that states that the second derivative of the projection set is linearly related to the Laplacian of the tomographic image. The proposed algorithm first reconstructs the Laplacian image of the phase-shift distribution from the second-derivative of the projections using total variation regularization. The second step is to obtain the phase-shift distribution by solving a Poisson equation whose source is the Laplacian image previously reconstructed under the Dirichlet condition. We demonstrate the efficacy of this algorithm using both synthetically generated simulation data and projection data acquired experimentally at a synchrotron. The experimental phase data were acquired from a human coronary artery specimen using dark-field-imaging optics pioneered by our group. Our results demonstrate that the proposed algorithm can reduce the number of projections to approximately 33% as compared with the conventional filtered backprojection method, without any detrimental effect on the image quality

  7. Quantification and differentiation of nuclear tracks in SSNTD by simulation of their diffraction pattern

    International Nuclear Information System (INIS)

    Palacios, D.; Palacios, F.; Vitoria, T.

    2001-01-01

    An alternative method to count and differentiate nuclear tracks in SSNTD is described. The method is based on the simulation and analysis of Fraunhofer diffraction pattern formed when coherent light passes through tracks of an etched detector. Transformation of the optical system was carried out by a digital procedure of Fourier Transform. Spectral analysis of the radial intensity distribution facilitated to quantify and differentiate tracks for its diameters. The formalism outlined is also applicable to elliptic tracks. Different components of the developed software (TRACKS) are shown. Results obtained by simulation and by the theoretical model gave satisfactory concordance. With the purpose of optimizing the proposed method, technical variants of optic microscopy are discussed. A model that considers the correction for track overlapping was developed and applied. Count error is small when track distribution changes in the field of view. The proposed method can differentiate genuine tracks from defects and anomalies of the detector. Analyzing the influence of illumination conditions and focus of the microscope on track counting and discrimination, the preliminary treatment of images obtained by the CCD camera was established. The proposed method allows, with low cost and operation simplicity, guaranteeing high speed in the obtaining of results, to calculate with good approximation track density in CR-39 detectors and to differentiate the energy of incident ions by track diameters with satisfactory accuracy and precision

  8. SINGLE VERSUS MULTIPLE TRIAL VECTORS IN CLASSICAL DIFFERENTIAL EVOLUTION FOR OPTIMIZING THE QUANTIZATION TABLE IN JPEG BASELINE ALGORITHM

    Directory of Open Access Journals (Sweden)

    B Vinoth Kumar

    2017-07-01

    Full Text Available Quantization Table is responsible for compression / quality trade-off in baseline Joint Photographic Experts Group (JPEG algorithm and therefore it is viewed as an optimization problem. In the literature, it has been found that Classical Differential Evolution (CDE is a promising algorithm to generate the optimal quantization table. However, the searching capability of CDE could be limited due to generation of single trial vector in an iteration which in turn reduces the convergence speed. This paper studies the performance of CDE by employing multiple trial vectors in a single iteration. An extensive performance analysis has been made between CDE and CDE with multiple trial vectors in terms of Optimization process, accuracy, convergence speed and reliability. The analysis report reveals that CDE with multiple trial vectors improves the convergence speed of CDE and the same is confirmed using a statistical hypothesis test (t-test.

  9. Environmental/economic dispatch problem of power system by using an enhanced multi-objective differential evolution algorithm

    International Nuclear Information System (INIS)

    Lu Youlin; Zhou Jianzhong; Qin Hui; Wang Ying; Zhang Yongchuan

    2011-01-01

    An enhanced multi-objective differential evolution algorithm (EMODE) is proposed in this paper to solve environmental/economic dispatch (EED) problem by considering the minimal of fuel cost and emission effects synthetically. In the proposed algorithm, an elitist archive technique is adopted to retain the non-dominated solutions obtained during the evolutionary process, and the operators of DE are modified according to the characteristics of multi-objective optimization problems. Moreover, in order to avoid premature convergence, a local random search (LRS) operator is integrated with the proposed method to improve the convergence performance. In view of the difficulties of handling the complicated constraints of EED problem, a new heuristic constraints handling method without any penalty factor settings is presented. The feasibility and effectiveness of the proposed EMODE method is demonstrated for a test power system. Compared with other methods, EMODE can get higher quality solutions by reducing the fuel cost and the emission effects synthetically.

  10. Reliability Analysis of Differential Relay as Main Protection Transformer Using Fuzzy Logic Algorithm

    Science.gov (United States)

    Mulyadi, Y.; Sucita, T.; Sumarto; Alpani, M.

    2018-02-01

    Electricity supply demand is increasing every year. It makes PT. PLN (Persero) is required to provide optimal customer service and satisfaction. Optimal service depends on the performance of the equipment of the power system owned, especially the transformer. Power transformer is an electrical equipment that transforms electricity from high voltage to low voltage or vice versa. However, in the electrical power system, is inseparable from interference included in the transformer. But, the disturbance can be minimized by the protection system. The main protection transformer is differential relays. Differential relays working system using Kirchoff law where inflows equal outflows. If there are excessive currents that interfere then the relays will work. But, the relay can also experience decreased performance. Therefore, this final project aims to analyze the reliability of the differential relay on the transformer in three different substations. Referring to the standard applied by the transmission line protection officer, the differential relay shall have slope characteristics of 30% in the first slope and 80% in the second slope when using two slopes and 80% when using one slope with an instant time and the corresponding ratio. So, the results obtained on the Siemens differential release have a reliable slope characteristic with a value of 30 on the fuzzy logic system. In a while, ABB a differential relay is only 80% reliable because two experiments are not reliable. For the time, all the differential relays are instant with a value of 0.06 on the fuzzy logic system. For ratios, the differential relays ABB have a better value than others brand with a value of 151 on the fuzzy logic system.

  11. A Variable Order Fractional Differential-Based Texture Enhancement Algorithm with Application in Medical Imaging.

    Directory of Open Access Journals (Sweden)

    Qiang Yu

    Full Text Available Texture enhancement is one of the most important techniques in digital image processing and plays an essential role in medical imaging since textures discriminate information. Most image texture enhancement techniques use classical integral order differential mask operators or fractional differential mask operators using fixed fractional order. These masks can produce excessive enhancement of low spatial frequency content, insufficient enhancement of large spatial frequency content, and retention of high spatial frequency noise. To improve upon existing approaches of texture enhancement, we derive an improved Variable Order Fractional Centered Difference (VOFCD scheme which dynamically adjusts the fractional differential order instead of fixing it. The new VOFCD technique is based on the second order Riesz fractional differential operator using a Lagrange 3-point interpolation formula, for both grey scale and colour image enhancement. We then use this method to enhance photographs and a set of medical images related to patients with stroke and Parkinson's disease. The experiments show that our improved fractional differential mask has a higher signal to noise ratio value than the other fractional differential mask operators. Based on the corresponding quantitative analysis we conclude that the new method offers a superior texture enhancement over existing methods.

  12. Koordinasi Optimal Capacitive Energy Storage (CES dan Kontroler PID Menggunakan Differential Evolution Algorithm (DEA pada Sistem Tenaga Listrik

    Directory of Open Access Journals (Sweden)

    Akbar Swandaru

    2012-09-01

    Full Text Available Peningkatan suplai daya listrik diperlukan untuk memenuhi kebutuhan daya listrik. Generator cenderung beroperasi dalam beban penuh.Hal ini berpengaruh pada keamanan generator dalam operasi sistem tenaga listrik.Salah satu masalah adalah osilasi frekuensi.Bila perubahan beban terjadi, kontroler diperlukan untuk meredam osilasi frekuensi ini.Pada tugas akhir ini diusulkan sebuah koordinasi antara Kontroler Capacitive Energy Storage (CES dan Kontroler PID. CES disini berfungsi untuk membantu kinerja Governor agar meredam osilasi frekuensi dengan cepat. Kontroler CES ini digunakan bersama dengan PID controller yang dioptimalkan dengan  Differential Evolution Algorithm (DEA.

  13. Algorithm for real-time detection of signal patterns using phase synchrony: an application to an electrode array

    Science.gov (United States)

    Sadeghi, Saman; MacKay, William A.; van Dam, R. Michael; Thompson, Michael

    2011-02-01

    Real-time analysis of multi-channel spatio-temporal sensor data presents a considerable technical challenge for a number of applications. For example, in brain-computer interfaces, signal patterns originating on a time-dependent basis from an array of electrodes on the scalp (i.e. electroencephalography) must be analyzed in real time to recognize mental states and translate these to commands which control operations in a machine. In this paper we describe a new technique for recognition of spatio-temporal patterns based on performing online discrimination of time-resolved events through the use of correlation of phase dynamics between various channels in a multi-channel system. The algorithm extracts unique sensor signature patterns associated with each event during a training period and ranks importance of sensor pairs in order to distinguish between time-resolved stimuli to which the system may be exposed during real-time operation. We apply the algorithm to electroencephalographic signals obtained from subjects tested in the neurophysiology laboratories at the University of Toronto. The extension of this algorithm for rapid detection of patterns in other sensing applications, including chemical identification via chemical or bio-chemical sensor arrays, is also discussed.

  14. Patterns of brain structural connectivity differentiate normal weight from overweight subjects.

    Science.gov (United States)

    Gupta, Arpana; Mayer, Emeran A; Sanmiguel, Claudia P; Van Horn, John D; Woodworth, Davis; Ellingson, Benjamin M; Fling, Connor; Love, Aubrey; Tillisch, Kirsten; Labus, Jennifer S

    2015-01-01

    Alterations in the hedonic component of ingestive behaviors have been implicated as a possible risk factor in the pathophysiology of overweight and obese individuals. Neuroimaging evidence from individuals with increasing body mass index suggests structural, functional, and neurochemical alterations in the extended reward network and associated networks. To apply a multivariate pattern analysis to distinguish normal weight and overweight subjects based on gray and white-matter measurements. Structural images (N = 120, overweight N = 63) and diffusion tensor images (DTI) (N = 60, overweight N = 30) were obtained from healthy control subjects. For the total sample the mean age for the overweight group (females = 32, males = 31) was 28.77 years (SD = 9.76) and for the normal weight group (females = 32, males = 25) was 27.13 years (SD = 9.62). Regional segmentation and parcellation of the brain images was performed using Freesurfer. Deterministic tractography was performed to measure the normalized fiber density between regions. A multivariate pattern analysis approach was used to examine whether brain measures can distinguish overweight from normal weight individuals. 1. White-matter classification: The classification algorithm, based on 2 signatures with 17 regional connections, achieved 97% accuracy in discriminating overweight individuals from normal weight individuals. For both brain signatures, greater connectivity as indexed by increased fiber density was observed in overweight compared to normal weight between the reward network regions and regions of the executive control, emotional arousal, and somatosensory networks. In contrast, the opposite pattern (decreased fiber density) was found between ventromedial prefrontal cortex and the anterior insula, and between thalamus and executive control network regions. 2. Gray-matter classification: The classification algorithm, based on 2 signatures with 42 morphological features, achieved 69

  15. Patterns of brain structural connectivity differentiate normal weight from overweight subjects

    Science.gov (United States)

    Gupta, Arpana; Mayer, Emeran A.; Sanmiguel, Claudia P.; Van Horn, John D.; Woodworth, Davis; Ellingson, Benjamin M.; Fling, Connor; Love, Aubrey; Tillisch, Kirsten; Labus, Jennifer S.

    2015-01-01

    Background Alterations in the hedonic component of ingestive behaviors have been implicated as a possible risk factor in the pathophysiology of overweight and obese individuals. Neuroimaging evidence from individuals with increasing body mass index suggests structural, functional, and neurochemical alterations in the extended reward network and associated networks. Aim To apply a multivariate pattern analysis to distinguish normal weight and overweight subjects based on gray and white-matter measurements. Methods Structural images (N = 120, overweight N = 63) and diffusion tensor images (DTI) (N = 60, overweight N = 30) were obtained from healthy control subjects. For the total sample the mean age for the overweight group (females = 32, males = 31) was 28.77 years (SD = 9.76) and for the normal weight group (females = 32, males = 25) was 27.13 years (SD = 9.62). Regional segmentation and parcellation of the brain images was performed using Freesurfer. Deterministic tractography was performed to measure the normalized fiber density between regions. A multivariate pattern analysis approach was used to examine whether brain measures can distinguish overweight from normal weight individuals. Results 1. White-matter classification: The classification algorithm, based on 2 signatures with 17 regional connections, achieved 97% accuracy in discriminating overweight individuals from normal weight individuals. For both brain signatures, greater connectivity as indexed by increased fiber density was observed in overweight compared to normal weight between the reward network regions and regions of the executive control, emotional arousal, and somatosensory networks. In contrast, the opposite pattern (decreased fiber density) was found between ventromedial prefrontal cortex and the anterior insula, and between thalamus and executive control network regions. 2. Gray-matter classification: The classification algorithm, based on 2 signatures with 42

  16. Equivalent construction of the infinitesimal time translation operator in algebraic dynamics algorithm for partial differential evolution equation

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    We give an equivalent construction of the infinitesimal time translation operator for partial differential evolution equation in the algebraic dynamics algorithm proposed by Shun-Jin Wang and his students. Our construction involves only simple partial differentials and avoids the derivative terms of δ function which appear in the course of computation by means of Wang-Zhang operator. We prove Wang’s equivalent theorem which says that our construction and Wang-Zhang’s are equivalent. We use our construction to deal with several typical equations such as nonlinear advection equation, Burgers equation, nonlinear Schrodinger equation, KdV equation and sine-Gordon equation, and obtain at least second order approximate solutions to them. These equations include the cases of real and complex field variables and the cases of the first and the second order time derivatives.

  17. Composition between mecd and runge-Kutta algorithm method for large system of second order differential equations

    International Nuclear Information System (INIS)

    Supriyono; Miyoshi, T.

    1997-01-01

    NECD Method and runge-Kutta method for large system of second order ordinary differential equations in comparing algorithm. The paper introduce a extrapolation method used for solving the large system of second order ordinary differential equation. We call this method the modified extrapolated central difference (MECD) method. for the accuracy and efficiency MECD method. we compare the method with 4-th order runge-Kutta method. The comparison results show that, this method has almost the same accuracy as the 4-th order runge-Kutta method, but the computation time is about half of runge-Kutta. The MECD was declare by the author and Tetsuhiko Miyoshi of the Dept. Applied Science Yamaguchi University Japan

  18. A constrained tracking algorithm to optimize plug patterns in multiple isocenter Gamma Knife radiosurgery planning

    International Nuclear Information System (INIS)

    Li Kaile; Ma Lijun

    2005-01-01

    We developed a source blocking optimization algorithm for Gamma Knife radiosurgery, which is based on tracking individual source contributions to arbitrarily shaped target and critical structure volumes. A scalar objective function and a direct search algorithm were used to produce near real-time calculation results. The algorithm allows the user to set and vary the total number of plugs for each shot to limit the total beam-on time. We implemented and tested the algorithm for several multiple-isocenter Gamma Knife cases. It was found that the use of limited number of plugs significantly lowered the integral dose to the critical structures such as an optical chiasm in pituitary adenoma cases. The main effect of the source blocking is the faster dose falloff in the junction area between the target and the critical structure. In summary, we demonstrated a useful source-plugging algorithm for improving complex multi-isocenter Gamma Knife treatment planning cases

  19. A new sine-Gordon equation expansion algorithm to investigate some special nonlinear differential equations

    International Nuclear Information System (INIS)

    Yan Zhenya

    2005-01-01

    A new transformation method is developed using the general sine-Gordon travelling wave reduction equation and a generalized transformation. With the aid of symbolic computation, this method can be used to seek more types of solutions of nonlinear differential equations, which include not only the known solutions derived by some known methods but new solutions. Here we choose the double sine-Gordon equation, the Magma equation and the generalized Pochhammer-Chree (PC) equation to illustrate the method. As a result, many types of new doubly periodic solutions are obtained. Moreover when using the method to these special nonlinear differential equations, some transformations are firstly needed. The method can be also extended to other nonlinear differential equations

  20. An improved Pattern Search based algorithm to solve the Dynamic Economic Dispatch problem with valve-point effect

    International Nuclear Information System (INIS)

    Alsumait, J.S.; Qasem, M.; Sykulski, J.K.; Al-Othman, A.K.

    2010-01-01

    In this paper, an improved algorithm based on Pattern Search method (PS) to solve the Dynamic Economic Dispatch is proposed. The algorithm maintains the essential unit ramp rate constraint, along with all other necessary constraints, not only for the time horizon of operation (24 h), but it preserves these constraints through the transaction period to the next time horizon (next day) in order to avoid the discontinuity of the power system operation. The Dynamic Economic and Emission Dispatch problem (DEED) is also considered. The load balance constraints, operating limits, valve-point loading and network losses are included in the models of both DED and DEED. The numerical results clarify the significance of the improved algorithm and verify its performance.

  1. Theoretical Aspects of the Patterns Recognition Statistical Theory Used for Developing the Diagnosis Algorithms for Complicated Technical Systems

    Science.gov (United States)

    Obozov, A. A.; Serpik, I. N.; Mihalchenko, G. S.; Fedyaeva, G. A.

    2017-01-01

    In the article, the problem of application of the pattern recognition (a relatively young area of engineering cybernetics) for analysis of complicated technical systems is examined. It is shown that the application of a statistical approach for hard distinguishable situations could be the most effective. The different recognition algorithms are based on Bayes approach, which estimates posteriori probabilities of a certain event and an assumed error. Application of the statistical approach to pattern recognition is possible for solving the problem of technical diagnosis complicated systems and particularly big powered marine diesel engines.

  2. Differentiation of tea varieties using UV-Vis spectra and pattern recognition techniques

    Science.gov (United States)

    Palacios-Morillo, Ana; Alcázar, Ángela.; de Pablos, Fernando; Jurado, José Marcos

    2013-02-01

    Tea, one of the most consumed beverages all over the world, is of great importance in the economies of a number of countries. Several methods have been developed to classify tea varieties or origins based in pattern recognition techniques applied to chemical data, such as metal profile, amino acids, catechins and volatile compounds. Some of these analytical methods become tedious and expensive to be applied in routine works. The use of UV-Vis spectral data as discriminant variables, highly influenced by the chemical composition, can be an alternative to these methods. UV-Vis spectra of methanol-water extracts of tea have been obtained in the interval 250-800 nm. Absorbances have been used as input variables. Principal component analysis was used to reduce the number of variables and several pattern recognition methods, such as linear discriminant analysis, support vector machines and artificial neural networks, have been applied in order to differentiate the most common tea varieties. A successful classification model was built by combining principal component analysis and multilayer perceptron artificial neural networks, allowing the differentiation between tea varieties. This rapid and simple methodology can be applied to solve classification problems in food industry saving economic resources.

  3. Differential DNA Methylation Patterns Are Related to Phellogen Origin and Quality of Quercus suber Cork.

    Science.gov (United States)

    Inácio, Vera; Barros, Pedro M; Costa, Augusta; Roussado, Cristóvão; Gonçalves, Elsa; Costa, Rita; Graça, José; Oliveira, M Margarida; Morais-Cecílio, Leonor

    2017-01-01

    DNA methylation is thought to influence Quercus suber cork quality, which is the main constraint for its economic valorisation. However, a deep knowledge of the cytosine methylation patterns disclosing the epigenetic variability of trees with different cork quality types is totally missing. This study investigates the hypothesis that variations in DNA methylation contribute to differences in cork cellular characteristics directly related to original or traumatic phellogen activity. We used MSAPs (Methylation Sensitive Amplified Polymorphism) to assess DNA methylation patterns of cork and leaf tissues of Q. suber adult trees growing in three cork oak stands. The relationship between the detected polymorphisms and the diversity of cork quality traits was explored by a marker-trait analysis focusing on the most relevant quality characteristics. Populations differed widely in cork quality, but only slightly in degree of epigenetic differentiation. Four MSAP markers (1.3% of the total) were significantly associated with the most noteworthy quality traits: wood inclusions (nails) and porosity. This evidence supports the potential role of cytosine methylation in the modulation of differential phellogen activity either involved in localized cell death or in pore production, resulting in different cork qualities. Although, the underlying basis of the methylation polymorphism of loci affecting cork quality traits remain unclear, the disclosure of markers statistically associated with cork quality strengthens the potential role of DNA methylation in the regulation of these traits, namely at the phellogen level.

  4. A rank-based algorithm of differential expression analysis for small cell line data with statistical control.

    Science.gov (United States)

    Li, Xiangyu; Cai, Hao; Wang, Xianlong; Ao, Lu; Guo, You; He, Jun; Gu, Yunyan; Qi, Lishuang; Guan, Qingzhou; Lin, Xu; Guo, Zheng

    2017-10-13

    To detect differentially expressed genes (DEGs) in small-scale cell line experiments, usually with only two or three technical replicates for each state, the commonly used statistical methods such as significance analysis of microarrays (SAM), limma and RankProd (RP) lack statistical power, while the fold change method lacks any statistical control. In this study, we demonstrated that the within-sample relative expression orderings (REOs) of gene pairs were highly stable among technical replicates of a cell line but often widely disrupted after certain treatments such like gene knockdown, gene transfection and drug treatment. Based on this finding, we customized the RankComp algorithm, previously designed for individualized differential expression analysis through REO comparison, to identify DEGs with certain statistical control for small-scale cell line data. In both simulated and real data, the new algorithm, named CellComp, exhibited high precision with much higher sensitivity than the original RankComp, SAM, limma and RP methods. Therefore, CellComp provides an efficient tool for analyzing small-scale cell line data. © The Author 2017. Published by Oxford University Press.

  5. Model parameter estimations from residual gravity anomalies due to simple-shaped sources using Differential Evolution Algorithm

    Science.gov (United States)

    Ekinci, Yunus Levent; Balkaya, Çağlayan; Göktürkler, Gökhan; Turan, Seçil

    2016-06-01

    An efficient approach to estimate model parameters from residual gravity data based on differential evolution (DE), a stochastic vector-based metaheuristic algorithm, has been presented. We have showed the applicability and effectiveness of this algorithm on both synthetic and field anomalies. According to our knowledge, this is a first attempt of applying DE for the parameter estimations of residual gravity anomalies due to isolated causative sources embedded in the subsurface. The model parameters dealt with here are the amplitude coefficient (A), the depth and exact origin of causative source (zo and xo, respectively) and the shape factors (q and ƞ). The error energy maps generated for some parameter pairs have successfully revealed the nature of the parameter estimation problem under consideration. Noise-free and noisy synthetic single gravity anomalies have been evaluated with success via DE/best/1/bin, which is a widely used strategy in DE. Additionally some complicated gravity anomalies caused by multiple source bodies have been considered, and the results obtained have showed the efficiency of the algorithm. Then using the strategy applied in synthetic examples some field anomalies observed for various mineral explorations such as a chromite deposit (Camaguey district, Cuba), a manganese deposit (Nagpur, India) and a base metal sulphide deposit (Quebec, Canada) have been considered to estimate the model parameters of the ore bodies. Applications have exhibited that the obtained results such as the depths and shapes of the ore bodies are quite consistent with those published in the literature. Uncertainty in the solutions obtained from DE algorithm has been also investigated by Metropolis-Hastings (M-H) sampling algorithm based on simulated annealing without cooling schedule. Based on the resulting histogram reconstructions of both synthetic and field data examples the algorithm has provided reliable parameter estimations being within the sampling limits of

  6. A numerical algorithm to find all feedback Nash equilibria in scalar affine quadratic differential games

    NARCIS (Netherlands)

    Engwerda, Jacob

    2015-01-01

    This note deals with solving scalar coupled algebraic Riccati equations. These equations arise in finding linear feedback Nash equilibria of the scalar N-player affine quadratic differential game. A numerical procedure is provided to compute all the stabilizing solutions. The main idea is to

  7. Differential gene expression patterns between smokers and non‐smokers: cause or consequence?

    Science.gov (United States)

    Jansen, Rick; Brooks, Andy; Willemsen, Gonneke; van Grootheest, Gerard; de Geus, Eco; Smit, Jan H.; Penninx, Brenda W.; Boomsma, Dorret I.

    2015-01-01

    Abstract The molecular mechanisms causing smoking‐induced health decline are largely unknown. To elucidate the molecular pathways involved in cause and consequences of smoking behavior, we conducted a genome‐wide gene expression study in peripheral blood samples targeting 18 238 genes. Data of 743 smokers, 1686 never smokers and 890 ex‐smokers were available from two population‐based cohorts from the Netherlands. In addition, data of 56 monozygotic twin pairs discordant for ever smoking were used. One hundred thirty‐two genes were differentially expressed between current smokers and never smokers (P smokers into account, expression of these 132 genes was classified into reversible (94 genes), slowly reversible (31 genes), irreversible (6 genes) or inconclusive (1 gene). Expression of 6 of the 132 genes (three reversible and three slowly reversible) was confirmed to be reactive to smoking as they were differentially expressed in monozygotic pairs discordant for smoking. Cis‐expression quantitative trait loci for GPR56 and RARRES3 (downregulated in smokers) were associated with increased number of cigarettes smoked per day in a large genome‐wide association meta‐analysis, suggesting a causative effect of GPR56 and RARRES3 expression on smoking behavior. In conclusion, differential gene expression patterns in smokers are extensive and cluster in several underlying disease pathways. Gene expression differences seem mainly direct consequences of smoking, and largely reversible after smoking cessation. However, we also identified DNA variants that may influence smoking behavior via the mediating gene expression. PMID:26594007

  8. Algorithms for Regular Tree Grammar Network Search and Their Application to Mining Human-viral Infection Patterns.

    Science.gov (United States)

    Smoly, Ilan; Carmel, Amir; Shemer-Avni, Yonat; Yeger-Lotem, Esti; Ziv-Ukelson, Michal

    2016-03-01

    Network querying is a powerful approach to mine molecular interaction networks. Most state-of-the-art network querying tools either confine the search to a prespecified topology in the form of some template subnetwork, or do not specify any topological constraints at all. Another approach is grammar-based queries, which are more flexible and expressive as they allow for expressing the topology of the sought pattern according to some grammar-based logic. Previous grammar-based network querying tools were confined to the identification of paths. In this article, we extend the patterns identified by grammar-based query approaches from paths to trees. For this, we adopt a higher order query descriptor in the form of a regular tree grammar (RTG). We introduce a novel problem and propose an algorithm to search a given graph for the k highest scoring subgraphs matching a tree accepted by an RTG. Our algorithm is based on the combination of dynamic programming with color coding, and includes an extension of previous k-best parsing optimization approaches to avoid isomorphic trees in the output. We implement the new algorithm and exemplify its application to mining viral infection patterns within molecular interaction networks. Our code is available online.

  9. Risk management algorithm for rear-side collision avoidance using a combined steering torque overlay and differential braking

    Science.gov (United States)

    Lee, Junyung; Yi, Kyongsu; Yoo, Hyunjae; Chong, Hyokjin; Ko, Bongchul

    2015-06-01

    This paper describes a risk management algorithm for rear-side collision avoidance. The proposed risk management algorithm consists of a supervisor and a coordinator. The supervisor is designed to monitor collision risks between the subject vehicle and approaching vehicle in the adjacent lane. An appropriate criterion of intervention, which satisfies high acceptance to drivers through the consideration of a realistic traffic, has been determined based on the analysis of the kinematics of the vehicles in longitudinal and lateral directions. In order to assist the driver actively and increase driver's safety, a coordinator is designed to combine lateral control using a steering torque overlay by motor-driven power steering and differential braking by vehicle stability control. In order to prevent the collision while limiting actuator's control inputs and vehicle dynamics to safe values for the assurance of the driver's comfort, the Lyapunov theory and linear matrix inequalities based optimisation methods have been used. The proposed risk management algorithm has been evaluated via simulation using CarSim and MATLAB/Simulink.

  10. 3D magnetization vector inversion based on fuzzy clustering: inversion algorithm, uncertainty analysis, and application to geology differentiation

    Science.gov (United States)

    Sun, J.; Li, Y.

    2017-12-01

    Magnetic data contain important information about the subsurface rocks that were magnetized in the geological history, which provides an important avenue to the study of the crustal heterogeneities associated with magmatic and hydrothermal activities. Interpretation of magnetic data has been widely used in mineral exploration, basement characterization and large scale crustal studies for several decades. However, interpreting magnetic data has been often complicated by the presence of remanent magnetizations with unknown magnetization directions. Researchers have developed different methods to deal with the challenges posed by remanence. We have developed a new and effective approach to inverting magnetic data for magnetization vector distributions characterized by region-wise consistency in the magnetization directions. This approach combines the classical Tikhonov inversion scheme with fuzzy C-means clustering algorithm, and constrains the estimated magnetization vectors to a specified small number of possible directions while fitting the observed magnetic data to within noise level. Our magnetization vector inversion recovers both the magnitudes and the directions of the magnetizations in the subsurface. Magnetization directions reflect the unique geological or hydrothermal processes applied to each geological unit, and therefore, can potentially be used for the purpose of differentiating various geological units. We have developed a practically convenient and effective way of assessing the uncertainty associated with the inverted magnetization directions (Figure 1), and investigated how geological differentiation results might be affected (Figure 2). The algorithm and procedures we have developed for magnetization vector inversion and uncertainty analysis open up new possibilities of extracting useful information from magnetic data affected by remanence. We will use a field data example from exploration of an iron-oxide-copper-gold (IOCG) deposit in Brazil to

  11. Detecting consistent patterns of directional adaptation using differential selection codon models.

    Science.gov (United States)

    Parto, Sahar; Lartillot, Nicolas

    2017-06-23

    Phylogenetic codon models are often used to characterize the selective regimes acting on protein-coding sequences. Recent methodological developments have led to models explicitly accounting for the interplay between mutation and selection, by modeling the amino acid fitness landscape along the sequence. However, thus far, most of these models have assumed that the fitness landscape is constant over time. Fluctuations of the fitness landscape may often be random or depend on complex and unknown factors. However, some organisms may be subject to systematic changes in selective pressure, resulting in reproducible molecular adaptations across independent lineages subject to similar conditions. Here, we introduce a codon-based differential selection model, which aims to detect and quantify the fine-grained consistent patterns of adaptation at the protein-coding level, as a function of external conditions experienced by the organism under investigation. The model parameterizes the global mutational pressure, as well as the site- and condition-specific amino acid selective preferences. This phylogenetic model is implemented in a Bayesian MCMC framework. After validation with simulations, we applied our method to a dataset of HIV sequences from patients with known HLA genetic background. Our differential selection model detects and characterizes differentially selected coding positions specifically associated with two different HLA alleles. Our differential selection model is able to identify consistent molecular adaptations as a function of repeated changes in the environment of the organism. These models can be applied to many other problems, ranging from viral adaptation to evolution of life-history strategies in plants or animals.

  12. Differential expression patterns of housekeeping genes increase diagnostic and prognostic value in lung cancer

    Directory of Open Access Journals (Sweden)

    Yu-Chun Chang

    2018-05-01

    Full Text Available Background Using DNA microarrays, we previously identified 451 genes expressed in 19 different human tissues. Although ubiquitously expressed, the variable expression patterns of these “housekeeping genes” (HKGs could separate one normal human tissue type from another. Current focus on identifying “specific disease markers” is problematic as single gene expression in a given sample represents the specific cellular states of the sample at the time of collection. In this study, we examine the diagnostic and prognostic potential of the variable expressions of HKGs in lung cancers. Methods Microarray and RNA-seq data for normal lungs, lung adenocarcinomas (AD, squamous cell carcinomas of the lung (SQCLC, and small cell carcinomas of the lung (SCLC were collected from online databases. Using 374 of 451 HKGs, differentially expressed genes between pairs of sample types were determined via two-sided, homoscedastic t-test. Principal component analysis and hierarchical clustering classified normal lung and lung cancers subtypes according to relative gene expression variations. We used uni- and multi-variate cox-regressions to identify significant predictors of overall survival in AD patients. Classifying genes were selected using a set of training samples and then validated using an independent test set. Gene Ontology was examined by PANTHER. Results This study showed that the differential expression patterns of 242, 245, and 99 HKGs were able to distinguish normal lung from AD, SCLC, and SQCLC, respectively. From these, 70 HKGs were common across the three lung cancer subtypes. These HKGs have low expression variation compared to current lung cancer markers (e.g., EGFR, KRAS and were involved in the most common biological processes (e.g., metabolism, stress response. In addition, the expression pattern of 106 HKGs alone was a significant classifier of AD versus SQCLC. We further highlighted that a panel of 13 HKGs was an independent predictor of

  13. A Regularized Approach for Solving Magnetic Differential Equations and a Revised Iterative Equilibrium Algorithm

    International Nuclear Information System (INIS)

    Hudson, S.R.

    2010-01-01

    A method for approximately solving magnetic differential equations is described. The approach is to include a small diffusion term to the equation, which regularizes the linear operator to be inverted. The extra term allows a 'source-correction' term to be defined, which is generally required in order to satisfy the solvability conditions. The approach is described in the context of computing the pressure and parallel currents in the iterative approach for computing magnetohydrodynamic equilibria.

  14. Differential pattern of semantic memory organization between bipolar I and II disorders.

    Science.gov (United States)

    Chang, Jae Seung; Choi, Sungwon; Ha, Kyooseob; Ha, Tae Hyon; Cho, Hyun Sang; Choi, Jung Eun; Cha, Boseok; Moon, Eunsoo

    2011-06-01

    Semantic cognition is one of the key factors in psychosocial functioning. The aim of this study was to explore the differences in pattern of semantic memory organization between euthymic patients with bipolar I and II disorders using the category fluency task. Study participants included 23 euthymic subjects with bipolar I disorder, 23 matched euthymic subjects with bipolar II disorder and 23 matched control subjects. All participants were assessed for verbal learning, recall, learning strategies, and fluency. The combined methods of hierarchical clustering and multidimensional scaling were used to compare the pattern of semantic memory organization among the three groups. Quantitative measures of verbal learning, recall, learning strategies, and fluency did not differ between the three groups. A two-cluster structure of semantic memory organization was identified for the three groups. Semantic structure was more disorganized in the bipolar I disorder group compared to the bipolar II disorder. In addition, patients with bipolar II disorder used less elaborate strategies of semantic memory organization than those of controls. Compared to healthy controls, strategies for categorization in semantic memory appear to be less knowledge-based in patients with bipolar disorders. A differential pattern of semantic memory organization between bipolar I and II disorders indicates a higher risk of cognitive abnormalities in patients with bipolar I disorder compared to patients with bipolar II disorder. Exploring qualitative nature of neuropsychological domains may provide an explanatory insight into the characteristic behaviors of patients with bipolar disorders. Copyright © 2011 Elsevier Inc. All rights reserved.

  15. Discordant patterns of genetic and phenotypic differentiation in five grasshopper species codistributed across a microreserve network.

    Science.gov (United States)

    Ortego, Joaquín; García-Navas, Vicente; Noguerales, Víctor; Cordero, Pedro J

    2015-12-01

    Conservation plans can be greatly improved when information on the evolutionary and demographic consequences of habitat fragmentation is available for several codistributed species. Here, we study spatial patterns of phenotypic and genetic variation among five grasshopper species that are codistributed across a network of microreserves but show remarkable differences in dispersal-related morphology (body size and wing length), degree of habitat specialization and extent of fragmentation of their respective habitats in the study region. In particular, we tested the hypothesis that species with preferences for highly fragmented microhabitats show stronger genetic and phenotypic structure than codistributed generalist taxa inhabiting a continuous matrix of suitable habitat. We also hypothesized a higher resemblance of spatial patterns of genetic and phenotypic variability among species that have experienced a higher degree of habitat fragmentation due to their more similar responses to the parallel large-scale destruction of their natural habitats. In partial agreement with our first hypothesis, we found that genetic structure, but not phenotypic differentiation, was higher in species linked to highly fragmented habitats. We did not find support for congruent patterns of phenotypic and genetic variability among any studied species, indicating that they show idiosyncratic evolutionary trajectories and distinctive demographic responses to habitat fragmentation across a common landscape. This suggests that conservation practices in networks of protected areas require detailed ecological and evolutionary information on target species to focus management efforts on those taxa that are more sensitive to the effects of habitat fragmentation. © 2015 John Wiley & Sons Ltd.

  16. On substructuring algorithms and solution techniques for the numerical approximation of partial differential equations

    Science.gov (United States)

    Gunzburger, M. D.; Nicolaides, R. A.

    1986-01-01

    Substructuring methods are in common use in mechanics problems where typically the associated linear systems of algebraic equations are positive definite. Here these methods are extended to problems which lead to nonpositive definite, nonsymmetric matrices. The extension is based on an algorithm which carries out the block Gauss elimination procedure without the need for interchanges even when a pivot matrix is singular. Examples are provided wherein the method is used in connection with finite element solutions of the stationary Stokes equations and the Helmholtz equation, and dual methods for second-order elliptic equations.

  17. Numerical simulation for Jeffery-Hamel flow and heat transfer of micropolar fluid based on differential evolution algorithm

    Directory of Open Access Journals (Sweden)

    Asmat Ara

    2018-01-01

    Full Text Available This article explores the Jeffery-Hamel flow of an incompressible non-Newtonian fluid inside non-parallel walls and observes the influence of heat transfer in the flow field. The fluid is considered to be micropolar fluid that flows in a convergent/divergent channel. The governing nonlinear partial differential equations (PDEs are converted to nonlinear coupled ordinary differential equations (ODEs with the help of a suitable similarity transformation. The resulting nonlinear analysis is determined analytically with the utilization of the Taylor optimization method based on differential evolution (DE algorithm. In order to understand the flow field, the effects of pertinent parameters such as the coupling parameter, spin gradient viscosity parameter and the Reynolds number have been examined on velocity and temperature profiles. It concedes that the good results can be attained by an implementation of the proposed method. Ultimately, the accuracy of the method is confirmed by comparing the present results with the results obtained by Runge-Kutta method.

  18. ICRPfinder: a fast pattern design algorithm for coding sequences and its application in finding potential restriction enzyme recognition sites

    Directory of Open Access Journals (Sweden)

    Stafford Phillip

    2009-09-01

    Full Text Available Abstract Background Restriction enzymes can produce easily definable segments from DNA sequences by using a variety of cut patterns. There are, however, no software tools that can aid in gene building -- that is, modifying wild-type DNA sequences to express the same wild-type amino acid sequences but with enhanced codons, specific cut sites, unique post-translational modifications, and other engineered-in components for recombinant applications. A fast DNA pattern design algorithm, ICRPfinder, is provided in this paper and applied to find or create potential recognition sites in target coding sequences. Results ICRPfinder is applied to find or create restriction enzyme recognition sites by introducing silent mutations. The algorithm is shown capable of mapping existing cut-sites but importantly it also can generate specified new unique cut-sites within a specified region that are guaranteed not to be present elsewhere in the DNA sequence. Conclusion ICRPfinder is a powerful tool for finding or creating specific DNA patterns in a given target coding sequence. ICRPfinder finds or creates patterns, which can include restriction enzyme recognition sites, without changing the translated protein sequence. ICRPfinder is a browser-based JavaScript application and it can run on any platform, in on-line or off-line mode.

  19. Forecasting of Power Grid Investment in China Based on Support Vector Machine Optimized by Differential Evolution Algorithm and Grey Wolf Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Shuyu Dai

    2018-04-01

    Full Text Available In recent years, the construction of China’s power grid has experienced rapid development, and its scale has leaped into the first place in the world. Accurate and effective prediction of power grid investment can not only help pool funds and rationally arrange investment in power grid construction, but also reduce capital costs and economic risks, which plays a crucial role in promoting power grid investment planning and construction process. In order to forecast the power grid investment of China accurately, firstly on the basis of analyzing the influencing factors of power grid investment, the influencing factors system for China’s power grid investment forecasting is constructed in this article. The method of grey relational analysis is used for screening the main influencing factors as the prediction model input. Then, a novel power grid investment prediction model based on DE-GWO-SVM (support vector machine optimized by differential evolution and grey wolf optimization algorithm is proposed. Next, two cases are taken for empirical analysis to prove that the DE-GWO-SVM model has strong generalization capacity and has achieved a good prediction effect for power grid investment forecasting in China. Finally, the DE-GWO-SVM model is adopted to forecast power grid investment in China from 2018 to 2022.

  20. Automated Peak Detection and Matching Algorithm for Gas Chromatography–Differential Mobility Spectrometry

    Science.gov (United States)

    Fong, Sim S.; Rearden, Preshious; Kanchagar, Chitra; Sassetti, Christopher; Trevejo, Jose; Brereton, Richard G.

    2013-01-01

    A gas chromatography–differential mobility spectrometer (GC-DMS) involves a portable and selective mass analyzer that may be applied to chemical detection in the field. Existing approaches examine whole profiles and do not attempt to resolve peaks. A new approach for peak detection in the 2D GC-DMS chromatograms is reported. This method is demonstrated on three case studies: a simulated case study; a case study of headspace gas analysis of Mycobacterium tuberculosis (MTb) cultures consisting of three matching GC-DMS and GC-MS chromatograms; a case study consisting of 41 GC-DMS chromatograms of headspace gas analysis of MTb culture and media. PMID:21204557

  1. Gastric cancer differentiation using Fourier transform near-infrared spectroscopy with unsupervised pattern recognition

    Science.gov (United States)

    Yi, Wei-song; Cui, Dian-sheng; Li, Zhi; Wu, Lan-lan; Shen, Ai-guo; Hu, Ji-ming

    2013-01-01

    The manuscript has investigated the application of near-infrared (NIR) spectroscopy for differentiation gastric cancer. The 90 spectra from cancerous and normal tissues were collected from a total of 30 surgical specimens using Fourier transform near-infrared spectroscopy (FT-NIR) equipped with a fiber-optic probe. Major spectral differences were observed in the CH-stretching second overtone (9000-7000 cm-1), CH-stretching first overtone (6000-5200 cm-1), and CH-stretching combination (4500-4000 cm-1) regions. By use of unsupervised pattern recognition, such as principal component analysis (PCA) and cluster analysis (CA), all spectra were classified into cancerous and normal tissue groups with accuracy up to 81.1%. The sensitivity and specificity was 100% and 68.2%, respectively. These present results indicate that CH-stretching first, combination band and second overtone regions can serve as diagnostic markers for gastric cancer.

  2. Apparent diffusion coefficient values and dynamic contrast enhancement patterns in differentiating seminomas from nonseminomatous testicular neoplasms

    International Nuclear Information System (INIS)

    Tsili, Athina C.; Sylakos, Anastasios; Ntorkou, Alexandra; Stavrou, Sotirios; Astrakas, Loukas G.; Sofikitis, Nikolaos; Argyropoulou, Maria I.

    2015-01-01

    Highlights: • Functional MRI in the characterization of testicular germ cell tumors was assessed. • ADC values proved useful in the characterization of testicular germ cell tumors. • Testicular germ cell tumors had similar enhancement patterns of dynamic MRI. - Abstract: Introduction: The aim of this study is to investigate the role of apparent diffusion coefficient (ADC) values and dynamic contrast enhancement (DCE) patterns in differentiating seminomas from nonseminomatous germ cell tumors (NSGCTs). Materials and methods: The MRI examinations of the scrotum of 26 men with histologically proven testicular GCTs were reviewed. DWI was performed in all patients, using a single shot, multi-slice spin-echo planar diffusion pulse sequence and b-values of 0 and 900 s/mm 2 . Subtraction DCE-MRI was performed in 20 cases using a 3D fast-field echo sequence after gadolinium administration. Time-signal intensity curves were created and semi-quantitative parameters (peak enhancement, time to peak, wash-in and wash-out rate) were calculated. The Student's t-test was used to compare the mean values of ADC, peak enhancement, time to peak, wash-in and wash-out rate between seminomas and NSGCTs. ROC analysis was also performed. Results: Histopathology disclosed the presence of 15 seminomas and 11 NSGCTs. The mean ± s.d. of ADC values (× 10 −3 mm 2 /s) of seminomas (0.59 ± 0.009) were significantly lower than those of NSGCTs (0.90 ± 0.33) (P = 0.01). The optimal ADC cut-off value was 0.68 × 10 −3 mm 2 /s. No differences between the two groups were observed for peak enhancement (P = 0.18), time to peak (P = 0.63) wash-in rate (P = 0.32) and wash-out rate (P = 0.18). Conclusions: ADC values may be used to preoperatively differentiate seminomas from NSGCTs

  3. Differential consolidation and pattern reverberations within episodic cell assemblies in the mouse hippocampus.

    Directory of Open Access Journals (Sweden)

    Remus Oşan

    2011-02-01

    Full Text Available One hallmark feature of consolidation of episodic memory is that only a fraction of original information, which is usually in a more abstract form, is selected for long-term memory storage. How does the brain perform these differential memory consolidations? To investigate the neural network mechanism that governs this selective consolidation process, we use a set of distinct fearful events to study if and how hippocampal CA1 cells engage in selective memory encoding and consolidation. We show that these distinct episodes activate a unique assembly of CA1 episodic cells, or neural cliques, whose response-selectivity ranges from general-to-specific features. A series of parametric analyses further reveal that post-learning CA1 episodic pattern replays or reverberations are mostly mediated by cells exhibiting event intensity-invariant responses, not by the intensity-sensitive cells. More importantly, reactivation cross-correlations displayed by intensity-invariant cells encoding general episodic features during immediate post-learning period tend to be stronger than those displayed by invariant cells encoding specific features. These differential reactivations within the CA1 episodic cell populations can thus provide the hippocampus with a selection mechanism to consolidate preferentially more generalized knowledge for long-term memory storage.

  4. Differential resting-state EEG patterns associated with comorbid depression in Internet addiction.

    Science.gov (United States)

    Lee, Jaewon; Hwang, Jae Yeon; Park, Su Mi; Jung, Hee Yeon; Choi, Sam-Wook; Kim, Dai Jin; Lee, Jun-Young; Choi, Jung-Seok

    2014-04-03

    Many researchers have reported a relationship between Internet addiction and depression. In the present study, we compared the resting-state quantitative electroencephalography (QEEG) activity of treatment-seeking patients with comorbid Internet addiction and depression with those of treatment-seeking patients with Internet addiction without depression, and healthy controls to investigate the neurobiological markers that differentiate pure Internet addiction from Internet addiction with comorbid depression. Thirty-five patients diagnosed with Internet addiction and 34 age-, sex-, and IQ-matched healthy controls were enrolled in this study. Patients with Internet addiction were divided into two groups according to the presence (N=18) or absence (N=17) of depression. Resting-state, eye-closed QEEG was recorded, and the absolute and relative power of the brain were analyzed. The Internet addiction group without depression had decreased absolute delta and beta powers in all brain regions, whereas the Internet addiction group with depression had increased relative theta and decreased relative alpha power in all regions. These neurophysiological changes were not related to clinical variables. The current findings reflect differential resting-state QEEG patterns between both groups of participants with Internet addiction and healthy controls and also suggest that decreased absolute delta and beta powers are neurobiological markers of Internet addiction. Copyright © 2013 Elsevier Inc. All rights reserved.

  5. Radiation Dose-rate Reduction Pattern in Well-differentiated Thyroid Cancer Treated with I-131.

    Science.gov (United States)

    Khan, Shahbaz Ahmad; Khan, Muhammad Saqib; Arif, Muhammad; Durr-e-Sabih; Rahim, Muhammad Kashif; Ahmad, Israr

    2015-07-01

    To determine the patterns of dose rate reduction in single and multiple radioiodine (I-131) therapies in cases of well differentiated thyroid cancer patients. Analytical series. Department of Nuclear Medicine and Radiation Physics, Multan Institute of Nuclear Medicine and Radiotherapy (MINAR), Multan, Pakistan, from December 2006 to December 2013. Ninety three patients (167 therapies) with well differentiated thyroid cancer treated with different doses of I-131 as an in-patient were inducted. Fifty four patients were given only single I-131 therapy dose ranging from 70 mCi (2590 MBq) to 150 mCi (5550 MBq). Thirty nine patients were treated with multiple I-131 radioisotope therapy doses ranging from 80 mCi (2960 MBq) to 250 mCi (9250 MBq). T-test was applied on the sample data showed statistically significant difference between the two groups with p-value (p < 0.01) less than 0.05 taken as significant. There were 68 females and 25 males with an age range of 15 to 80 years. Mean age of the patients were 36 years. Among the 93 cases of first time Radio Active Iodine (RAI) therapy, 59 cases (63%) were discharged after 48 hours. Among 39 patients who received RAI therapy second time or more, most were discharged earlier after achieving acceptable discharge dose rate i.e 25 µSv/hour; 2 out of 39 (5%) were discharged after 48 hours. In 58% patients, given single I-131 therapy dose, majority of these were discharged after 48 hours without any major complications. For well differentiated thyroid cancer patients, rapid dose rate reduction is seen in patients receiving second or subsequent radioiodine (RAI) therapy, as compared to first time receiving RAI therapy.

  6. Optimization of seasonal ARIMA models using differential evolution - simulated annealing (DESA) algorithm in forecasting dengue cases in Baguio City

    Science.gov (United States)

    Addawe, Rizavel C.; Addawe, Joel M.; Magadia, Joselito C.

    2016-10-01

    Accurate forecasting of dengue cases would significantly improve epidemic prevention and control capabilities. This paper attempts to provide useful models in forecasting dengue epidemic specific to the young and adult population of Baguio City. To capture the seasonal variations in dengue incidence, this paper develops a robust modeling approach to identify and estimate seasonal autoregressive integrated moving average (SARIMA) models in the presence of additive outliers. Since the least squares estimators are not robust in the presence of outliers, we suggest a robust estimation based on winsorized and reweighted least squares estimators. A hybrid algorithm, Differential Evolution - Simulated Annealing (DESA), is used to identify and estimate the parameters of the optimal SARIMA model. The method is applied to the monthly reported dengue cases in Baguio City, Philippines.

  7. A novel algorithm for discrimination between inrush current and internal faults in power transformer differential protection based on discrete wavelet transform

    Energy Technology Data Exchange (ETDEWEB)

    Eldin, A.A. Hossam; Refaey, M.A. [Electrical Engineering Department, Alexandria University, Alexandria (Egypt)

    2011-01-15

    This paper proposes a novel methodology for transformer differential protection, based on wave shape recognition of the discriminating criterion extracted of the instantaneous differential currents. Discrete wavelet transform has been applied to the differential currents due to internal fault and inrush currents. The diagnosis criterion is based on median absolute deviation (MAD) of wavelet coefficients over a specified frequency band. The proposed algorithm is examined using various simulated inrush and internal fault current cases on a power transformer that has been modeled using electromagnetic transients program EMTDC software. Results of evaluation study show that, proposed wavelet based differential protection scheme can discriminate internal faults from inrush currents. (author)

  8. Algorithmic Information Dynamics of Persistent Patterns and Colliding Particles in the Game of Life

    KAUST Repository

    Zenil, Hector; Kiani, Narsis A.; Tegner, Jesper

    2018-01-01

    , Conway's Game of Life (GoL) cellular automaton as a case study. We analyze the distribution of prevailing motifs that occur in GoL from the perspective of algorithmic probability. We demonstrate how the tools introduced are an alternative to computable

  9. Reconstructing Genetic Regulatory Networks Using Two-Step Algorithms with the Differential Equation Models of Neural Networks.

    Science.gov (United States)

    Chen, Chi-Kan

    2017-07-26

    -step algorithms can potentially incorporate with different nonlinear differential equation models to reconstruct the GRN.

  10. An Algorithm of Image Heterogeneity with Contrast-Enhanced Ultrasound in Differential Diagnosis of Solid Thyroid Nodules.

    Science.gov (United States)

    Jin, Lifang; Xu, Changsong; Xie, Xueqian; Li, Fan; Lv, Xiuhong; Du, Lianfang

    2017-01-01

    Enhancement heterogeneity on contrast-enhanced ultrasonography (CEUS) is used to differentiate between benign and malignant thyroid nodules. In this study, we used an algorithm to quantify enhancement heterogeneity of solid thyroid nodules on CEUS. The heterogeneity value (HV) is calculated as standard deviation/mean intensity × 100 (using Adobe Photoshop). The heterogeneity ratio (HR) is calculated as the ratio of the HV of the nodule to that of the surrounding parenchyma. Three phases-ascending, peak and descending phases-were studied. HV values at ascending (HV a ) and peak (HV p ) phases were significantly higher in malignant nodules than in benign nodules (95.57 ± 43.87 vs. 73.06 ± 44.04, p = 0.009, and 32.53 ± 10.73 vs. 26.44 ± 8.25, p = 0.002, respectively). HR a , HR p and HR d were significantly higher in malignant nodules than in benign nodules (1.93 ± 1.03 vs. 1.00 ± 0.47, p = 0.000, 1.43 ± 0.51 vs. 1.09 ± 0.28, p = 0.000, and 1.33 ± 0.40 vs. 1.08 ± 0.33, p = 0.001, respectively). HR a achieved optimal diagnostic performance on receiver operating characteristic curve analysis. The algorithm used for assessment of image heterogeneity on CEUS examination may be a useful adjunct to conventional ultrasound for differential diagnosis of solid thyroid nodules. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

  11. Solving the Telegraph and Oscillatory Differential Equations by a Block Hybrid Trigonometrically Fitted Algorithm

    Directory of Open Access Journals (Sweden)

    F. F. Ngwane

    2015-01-01

    Full Text Available We propose a block hybrid trigonometrically fitted (BHT method, whose coefficients are functions of the frequency and the step-size for directly solving general second-order initial value problems (IVPs, including systems arising from the semidiscretization of hyperbolic Partial Differential Equations (PDEs, such as the Telegraph equation. The BHT is formulated from eight discrete hybrid formulas which are provided by a continuous two-step hybrid trigonometrically fitted method with two off-grid points. The BHT is implemented in a block-by-block fashion; in this way, the method does not suffer from the disadvantages of requiring starting values and predictors which are inherent in predictor-corrector methods. The stability property of the BHT is discussed and the performance of the method is demonstrated on some numerical examples to show accuracy and efficiency advantages.

  12. Learning Qualitative Differential Equation models: a survey of algorithms and applications.

    Science.gov (United States)

    Pang, Wei; Coghill, George M

    2010-03-01

    Over the last two decades, qualitative reasoning (QR) has become an important domain in Artificial Intelligence. QDE (Qualitative Differential Equation) model learning (QML), as a branch of QR, has also received an increasing amount of attention; many systems have been proposed to solve various significant problems in this field. QML has been applied to a wide range of fields, including physics, biology and medical science. In this paper, we first identify the scope of this review by distinguishing QML from other QML systems, and then review all the noteworthy QML systems within this scope. The applications of QML in several application domains are also introduced briefly. Finally, the future directions of QML are explored from different perspectives.

  13. Optimization of the p-xylene oxidation process by a multi-objective differential evolution algorithm with adaptive parameters co-derived with the population-based incremental learning algorithm

    Science.gov (United States)

    Guo, Zhan; Yan, Xuefeng

    2018-04-01

    Different operating conditions of p-xylene oxidation have different influences on the product, purified terephthalic acid. It is necessary to obtain the optimal combination of reaction conditions to ensure the quality of the products, cut down on consumption and increase revenues. A multi-objective differential evolution (MODE) algorithm co-evolved with the population-based incremental learning (PBIL) algorithm, called PBMODE, is proposed. The PBMODE algorithm was designed as a co-evolutionary system. Each individual has its own parameter individual, which is co-evolved by PBIL. PBIL uses statistical analysis to build a model based on the corresponding symbiotic individuals of the superior original individuals during the main evolutionary process. The results of simulations and statistical analysis indicate that the overall performance of the PBMODE algorithm is better than that of the compared algorithms and it can be used to optimize the operating conditions of the p-xylene oxidation process effectively and efficiently.

  14. Articular dysfunction patterns in patients with mechanical neck pain: a clinical algorithm to guide specific mobilization and manipulation techniques.

    Science.gov (United States)

    Dewitte, Vincent; Beernaert, Axel; Vanthillo, Bart; Barbe, Tom; Danneels, Lieven; Cagnie, Barbara

    2014-02-01

    In view of a didactical approach for teaching cervical mobilization and manipulation techniques to students as well as their use in daily practice, it is mandatory to acquire sound clinical reasoning to optimally apply advanced technical skills. The aim of this Masterclass is to present a clinical algorithm to guide (novice) therapists in their clinical reasoning to identify patients who are likely to respond to mobilization and/or manipulation. The presented clinical reasoning process is situated within the context of pain mechanisms and is narrowed to and applicable in patients with a dominant input pain mechanism. Based on key features in subjective and clinical examination, patients with mechanical nociceptive pain probably arising from articular structures can be categorized into specific articular dysfunction patterns. Pending on these patterns, specific mobilization and manipulation techniques are warranted. The proposed patterns are illustrated in 3 case studies. This clinical algorithm is the corollary of empirical expertise and is complemented by in-depth discussions and knowledge exchange with international colleagues. Consequently, it is intended that a carefully targeted approach contributes to an increase in specificity and safety in the use of cervical mobilizations and manipulation techniques as valuable adjuncts to other manual therapy modalities. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Utility of the k-means clustering algorithm in differentiating apparent diffusion coefficient values of benign and malignant neck pathologies.

    Science.gov (United States)

    Srinivasan, A; Galbán, C J; Johnson, T D; Chenevert, T L; Ross, B D; Mukherji, S K

    2010-04-01

    Does the K-means algorithm do a better job of differentiating benign and malignant neck pathologies compared to only mean ADC? The objective of our study was to analyze the differences between ADC partitions to evaluate whether the K-means technique can be of additional benefit to whole-lesion mean ADC alone in distinguishing benign and malignant neck pathologies. MR imaging studies of 10 benign and 10 malignant proved neck pathologies were postprocessed on a PC by using in-house software developed in Matlab. Two neuroradiologists manually contoured the lesions, with the ADC values within each lesion clustered into 2 (low, ADC-ADC(L); high, ADC-ADC(H)) and 3 partitions (ADC(L); intermediate, ADC-ADC(I); ADC(H)) by using the K-means clustering algorithm. An unpaired 2-tailed Student t test was performed for all metrics to determine statistical differences in the means of the benign and malignant pathologies. A statistically significant difference between the mean ADC(L) clusters in benign and malignant pathologies was seen in the 3-cluster models of both readers (P = .03 and .022, respectively) and the 2-cluster model of reader 2 (P = .04), with the other metrics (ADC(H), ADC(I); whole-lesion mean ADC) not revealing any significant differences. ROC curves demonstrated the quantitative differences in mean ADC(H) and ADC(L) in both the 2- and 3-cluster models to be predictive of malignancy (2 clusters: P = .008, area under curve = 0.850; 3 clusters: P = .01, area under curve = 0.825). The K-means clustering algorithm that generates partitions of large datasets may provide a better characterization of neck pathologies and may be of additional benefit in distinguishing benign and malignant neck pathologies compared with whole-lesion mean ADC alone.

  16. Quantification of differences between nailfold capillaroscopy images with a scleroderma pattern and normal pattern using measures of geometric and algorithmic complexity.

    Science.gov (United States)

    Urwin, Samuel George; Griffiths, Bridget; Allen, John

    2017-02-01

    This study aimed to quantify and investigate differences in the geometric and algorithmic complexity of the microvasculature in nailfold capillaroscopy (NFC) images displaying a scleroderma pattern and those displaying a 'normal' pattern. 11 NFC images were qualitatively classified by a capillary specialist as indicative of 'clear microangiopathy' (CM), i.e. a scleroderma pattern, and 11 as 'not clear microangiopathy' (NCM), i.e. a 'normal' pattern. Pre-processing was performed, and fractal dimension (FD) and Kolmogorov complexity (KC) were calculated following image binarisation. FD and KC were compared between groups, and a k-means cluster analysis (n  =  2) on all images was performed, without prior knowledge of the group assigned to them (i.e. CM or NCM), using FD and KC as inputs. CM images had significantly reduced FD and KC compared to NCM images, and the cluster analysis displayed promising results that the quantitative classification of images into CM and NCM groups is possible using the mathematical measures of FD and KC. The analysis techniques used show promise for quantitative microvascular investigation in patients with systemic sclerosis.

  17. Differential Infection Patterns and Recent Evolutionary Origins of Equine Hepaciviruses in Donkeys

    Science.gov (United States)

    Walter, Stephanie; Rasche, Andrea; Moreira-Soto, Andrés; Pfaender, Stephanie; Bletsa, Magda; Corman, Victor Max; Aguilar-Setien, Alvaro; García-Lacy, Fernando; Hans, Aymeric; Todt, Daniel; Schuler, Gerhard; Shnaiderman-Torban, Anat; Steinman, Amir; Roncoroni, Cristina; Veneziano, Vincenzo; Rusenova, Nikolina; Sandev, Nikolay; Rusenov, Anton; Zapryanova, Dimitrinka; García-Bocanegra, Ignacio; Jores, Joerg; Carluccio, Augusto; Veronesi, Maria Cristina; Cavalleri, Jessika M. V.; Drosten, Christian; Lemey, Philippe

    2016-01-01

    , limiting the time span for potential horse-to-human infections in the past. Horses are genetically related to donkeys, and EqHV may have cospeciated with these host species. Here, we investigated a large panel of donkeys from various countries using serologic and molecular tools. We found EqHV to be globally widespread in donkeys and identify potential differences in EqHV infection patterns, with donkeys potentially showing enhanced EqHV clearance compared to horses. We provide strong evidence against EqHV cospeciation and for its capability to switch hosts among equines. Differential hepacivirus infection patterns in horses and donkeys may enable new insights into the chronic infection pattern associated with HCV. PMID:27795428

  18. Differential Infection Patterns and Recent Evolutionary Origins of Equine Hepaciviruses in Donkeys.

    Science.gov (United States)

    Walter, Stephanie; Rasche, Andrea; Moreira-Soto, Andrés; Pfaender, Stephanie; Bletsa, Magda; Corman, Victor Max; Aguilar-Setien, Alvaro; García-Lacy, Fernando; Hans, Aymeric; Todt, Daniel; Schuler, Gerhard; Shnaiderman-Torban, Anat; Steinman, Amir; Roncoroni, Cristina; Veneziano, Vincenzo; Rusenova, Nikolina; Sandev, Nikolay; Rusenov, Anton; Zapryanova, Dimitrinka; García-Bocanegra, Ignacio; Jores, Joerg; Carluccio, Augusto; Veronesi, Maria Cristina; Cavalleri, Jessika M V; Drosten, Christian; Lemey, Philippe; Steinmann, Eike; Drexler, Jan Felix

    2017-01-01

    potential horse-to-human infections in the past. Horses are genetically related to donkeys, and EqHV may have cospeciated with these host species. Here, we investigated a large panel of donkeys from various countries using serologic and molecular tools. We found EqHV to be globally widespread in donkeys and identify potential differences in EqHV infection patterns, with donkeys potentially showing enhanced EqHV clearance compared to horses. We provide strong evidence against EqHV cospeciation and for its capability to switch hosts among equines. Differential hepacivirus infection patterns in horses and donkeys may enable new insights into the chronic infection pattern associated with HCV. Copyright © 2016 American Society for Microbiology.

  19. Adaptive enhancement of optical fringe patterns by selective reconstruction using FABEMD algorithm and Hilbert spiral transform.

    Science.gov (United States)

    Trusiak, Maciej; Patorski, Krzysztof; Wielgus, Maciej

    2012-10-08

    Presented method for fringe pattern enhancement has been designed for processing and analyzing low quality fringe patterns. It uses a modified fast and adaptive bidimensional empirical mode decomposition (FABEMD) for the extraction of bidimensional intrinsic mode functions (BIMFs) from an interferogram. Fringe pattern is then selectively reconstructed (SR) taking the regions of selected BIMFs with high modulation values only. Amplitude demodulation and normalization of the reconstructed image is conducted using the spiral phase Hilbert transform (HS). It has been tested using computer generated interferograms and real data. The performance of the presented SR-FABEMD-HS method is compared with other normalization techniques. Its superiority, potential and robustness to high fringe density variations and the presence of noise, modulation and background illumination defects in analyzed fringe patterns has been corroborated.

  20. Optimal trajectory planning of free-floating space manipulator using differential evolution algorithm

    Science.gov (United States)

    Wang, Mingming; Luo, Jianjun; Fang, Jing; Yuan, Jianping

    2018-03-01

    The existence of the path dependent dynamic singularities limits the volume of available workspace of free-floating space robot and induces enormous joint velocities when such singularities are met. In order to overcome this demerit, this paper presents an optimal joint trajectory planning method using forward kinematics equations of free-floating space robot, while joint motion laws are delineated with application of the concept of reaction null-space. Bézier curve, in conjunction with the null-space column vectors, are applied to describe the joint trajectories. Considering the forward kinematics equations of the free-floating space robot, the trajectory planning issue is consequently transferred to an optimization issue while the control points to construct the Bézier curve are the design variables. A constrained differential evolution (DE) scheme with premature handling strategy is implemented to find the optimal solution of the design variables while specific objectives and imposed constraints are satisfied. Differ from traditional methods, we synthesize null-space and specialized curve to provide a novel viewpoint for trajectory planning of free-floating space robot. Simulation results are presented for trajectory planning of 7 degree-of-freedom (DOF) kinematically redundant manipulator mounted on a free-floating spacecraft and demonstrate the feasibility and effectiveness of the proposed method.

  1. Apparent diffusion coefficient values and dynamic contrast enhancement patterns in differentiating seminomas from nonseminomatous testicular neoplasms

    Energy Technology Data Exchange (ETDEWEB)

    Tsili, Athina C., E-mail: a_tsili@yahoo.gr [Department of Radiology, Medical School, University of Ioannina, 45110 Ioannina (Greece); Sylakos, Anastasios, E-mail: anasylakos@yahoo.gr [Department of Urology, Medical School, University of Ioannina, 45110 Ioannina (Greece); Ntorkou, Alexandra, E-mail: alexdorkou@yahoo.com [Department of Radiology, Medical School, University of Ioannina, 45110 Ioannina (Greece); Stavrou, Sotirios, E-mail: s.sotiris@yahoo.gr [Department of Urology, Medical School, University of Ioannina, 45110 Ioannina (Greece); Astrakas, Loukas G., E-mail: astrakas@uoi.gr [Department of Medical Physics, Medical School, University of Ioannina, 45110 Ioannina (Greece); Sofikitis, Nikolaos, E-mail: akrosnin@hotmail.com [Department of Urology, Medical School, University of Ioannina, 45110 Ioannina (Greece); Argyropoulou, Maria I., E-mail: margyrop@cc.uoi.gr [Department of Radiology, Medical School, University of Ioannina, 45110 Ioannina (Greece)

    2015-07-15

    Highlights: • Functional MRI in the characterization of testicular germ cell tumors was assessed. • ADC values proved useful in the characterization of testicular germ cell tumors. • Testicular germ cell tumors had similar enhancement patterns of dynamic MRI. - Abstract: Introduction: The aim of this study is to investigate the role of apparent diffusion coefficient (ADC) values and dynamic contrast enhancement (DCE) patterns in differentiating seminomas from nonseminomatous germ cell tumors (NSGCTs). Materials and methods: The MRI examinations of the scrotum of 26 men with histologically proven testicular GCTs were reviewed. DWI was performed in all patients, using a single shot, multi-slice spin-echo planar diffusion pulse sequence and b-values of 0 and 900 s/mm{sup 2}. Subtraction DCE-MRI was performed in 20 cases using a 3D fast-field echo sequence after gadolinium administration. Time-signal intensity curves were created and semi-quantitative parameters (peak enhancement, time to peak, wash-in and wash-out rate) were calculated. The Student's t-test was used to compare the mean values of ADC, peak enhancement, time to peak, wash-in and wash-out rate between seminomas and NSGCTs. ROC analysis was also performed. Results: Histopathology disclosed the presence of 15 seminomas and 11 NSGCTs. The mean ± s.d. of ADC values (× 10{sup −3} mm{sup 2}/s) of seminomas (0.59 ± 0.009) were significantly lower than those of NSGCTs (0.90 ± 0.33) (P = 0.01). The optimal ADC cut-off value was 0.68 × 10{sup −3} mm{sup 2}/s. No differences between the two groups were observed for peak enhancement (P = 0.18), time to peak (P = 0.63) wash-in rate (P = 0.32) and wash-out rate (P = 0.18). Conclusions: ADC values may be used to preoperatively differentiate seminomas from NSGCTs.

  2. Computed Tomography Image Origin Identification Based on Original Sensor Pattern Noise and 3-D Image Reconstruction Algorithm Footprints.

    Science.gov (United States)

    Duan, Yuping; Bouslimi, Dalel; Yang, Guanyu; Shu, Huazhong; Coatrieux, Gouenou

    2017-07-01

    In this paper, we focus on the "blind" identification of the computed tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-scanner footprint. Basically, we propose two approaches. The first one aims at identifying a CT scanner based on an original sensor pattern noise (OSPN) that is intrinsic to the X-ray detectors. The second one identifies an acquisition system based on the way this noise is modified by its three-dimensional (3-D) image reconstruction algorithm. As these reconstruction algorithms are manufacturer dependent and kept secret, our features are used as input to train a support vector machine (SVM) based classifier to discriminate acquisition systems. Experiments conducted on images issued from 15 different CT-scanner models of 4 distinct manufacturers demonstrate that our system identifies the origin of one CT image with a detection rate of at least 94% and that it achieves better performance than sensor pattern noise (SPN) based strategy proposed for general public camera devices.

  3. Multiple Memory Structure Bit Reversal Algorithm Based on Recursive Patterns of Bit Reversal Permutation

    Directory of Open Access Journals (Sweden)

    K. K. L. B. Adikaram

    2014-01-01

    Full Text Available With the increasing demand for online/inline data processing efficient Fourier analysis becomes more and more relevant. Due to the fact that the bit reversal process requires considerable processing time of the Fast Fourier Transform (FFT algorithm, it is vital to optimize the bit reversal algorithm (BRA. This paper is to introduce an efficient BRA with multiple memory structures. In 2009, Elster showed the relation between the first and the second halves of the bit reversal permutation (BRP and stated that it may cause serious impact on cache performance of the computer, if implemented. We found exceptions, especially when the said index mapping was implemented with multiple one-dimensional memory structures instead of multidimensional or one-dimensional memory structure. Also we found a new index mapping, even after the recursive splitting of BRP into equal sized slots. The four-array and the four-vector versions of BRA with new index mapping reported 34% and 16% improvement in performance in relation to similar versions of Linear BRA of Elster which uses single one-dimensional memory structure.

  4. PatternLab for proteomics: a tool for differential shotgun proteomics

    Directory of Open Access Journals (Sweden)

    Yates John R

    2008-07-01

    Full Text Available Abstract Background A goal of proteomics is to distinguish between states of a biological system by identifying protein expression differences. Liu et al. demonstrated a method to perform semi-relative protein quantitation in shotgun proteomics data by correlating the number of tandem mass spectra obtained for each protein, or "spectral count", with its abundance in a mixture; however, two issues have remained open: how to normalize spectral counting data and how to efficiently pinpoint differences between profiles. Moreover, Chen et al. recently showed how to increase the number of identified proteins in shotgun proteomics by analyzing samples with different MS-compatible detergents while performing proteolytic digestion. The latter introduced new challenges as seen from the data analysis perspective, since replicate readings are not acquired. Results To address the open issues above, we present a program termed PatternLab for proteomics. This program implements existing strategies and adds two new methods to pinpoint differences in protein profiles. The first method, ACFold, addresses experiments with less than three replicates from each state or having assays acquired by different protocols as described by Chen et al. ACFold uses a combined criterion based on expression fold changes, the AC test, and the false-discovery rate, and can supply a "bird's-eye view" of differentially expressed proteins. The other method addresses experimental designs having multiple readings from each state and is referred to as nSVM (natural support vector machine because of its roots in evolutionary computing and in statistical learning theory. Our observations suggest that nSVM's niche comprises projects that select a minimum set of proteins for classification purposes; for example, the development of an early detection kit for a given pathology. We demonstrate the effectiveness of each method on experimental data and confront them with existing strategies

  5. Salinity induced differential methylation patterns in contrasting cultivars of foxtail millet (Setaria italica L.).

    Science.gov (United States)

    Pandey, Garima; Yadav, Chandra Bhan; Sahu, Pranav Pankaj; Muthamilarasan, Mehanathan; Prasad, Manoj

    2017-05-01

    Genome-wide methylation analysis of foxtail millet cultivars contrastingly differing in salinity tolerance revealed DNA demethylation events occurring in tolerant cultivar under salinity stress, eventually modulating the expression of stress-responsive genes. Reduced productivity and significant yield loss are the adverse effects of environmental conditions on physiological and biochemical pathways in crop plants. In this context, understanding the epigenetic machinery underlying the tolerance traits in a naturally stress tolerant crop is imperative. Foxtail millet (Setaria italica) is known for its better tolerance to abiotic stresses compared to other cereal crops. In the present study, methylation-sensitive amplified polymorphism (MSAP) technique was used to quantify the salt-induced methylation changes in two foxtail millet cultivars contrastingly differing in their tolerance levels to salt stress. The study highlighted that the DNA methylation level was significantly reduced in tolerant cultivar compared to sensitive cultivar. A total of 86 polymorphic MSAP fragments were identified, sequenced and functionally annotated. These fragments showed sequence similarity to several genes including ABC transporter, WRKY transcription factor, serine threonine-protein phosphatase, disease resistance, oxidoreductases, cell wall-related enzymes and retrotransposon and transposase like proteins, suggesting salt stress-induced methylation in these genes. Among these, four genes were chosen for expression profiling which showed differential expression pattern between both cultivars of foxtail millet. Altogether, the study infers that salinity stress induces genome-wide DNA demethylation, which in turn, modulates expression of corresponding genes.

  6. Differential gene expression patterns during embryonic development of sea urchin exposed to triclosan.

    Science.gov (United States)

    Hwang, Jinik; Suh, Sung-Suk; Park, Mirye; Park, So Yun; Lee, Sukchan; Lee, Taek-Kyun

    2017-02-01

    Triclosan (TCS; 2,4,4'-trichloro-2'-hydroxydiphenyl ether) is a broad-spectrum antibacterial agent used in common industrial, personal care and household products which are eventually rinsed down the drain and discharged with wastewater effluent. It is therefore commonly found in the aquatic environment, leading to the continual exposure of aquatic organisms to TCS and the accumulation of the antimicrobial and its harmful degradation products in their bodies. Toxic effects of TCS on reproductive and developmental progression of some aquatic organisms have been suggested but the underlying molecular mechanisms have not been defined. We investigated the expression patterns of genes involved in the early development of TCS-treated sea urchin Strongylocentrotus nudus using cDNA microarrays. We observed that the predominant consequence of TCS treatment in this model system was the widespread repression of TCS-modulated genes. In particular, empty spiracles homeobox 1 (EMX-1), bone morphogenic protein, and chromosomal binding protein genes showed a significant decrease in expression in response to TCS. These results suggest that TCS can induce abnormal development of sea urchin embryos through the concomitant suppression of a number of genes that are necessary for embryonic differentiation in the blastula stage. Our data provide new insight into the crucial role of genes associated with embryonic development in response to TCS. © 2016 Wiley Periodicals, Inc. Environ Toxicol 32: 426-433, 2017. © 2016 Wiley Periodicals, Inc.

  7. Positive schizotypy and negative schizotypy are associated with differential patterns of episodic memory impairment

    Directory of Open Access Journals (Sweden)

    Lili Sahakyan

    2016-09-01

    Full Text Available Cognitive impairment is a hallmark of schizophrenia; however, studies have not comprehensively examined such impairments in non-clinically ascertained schizotypic young adults. The present study employed a series of measures to assess episodic memory in high positive schizotypy, high negative schizotypy, and comparison groups (each group n = 25. Consistent with diminished cognitive functioning seen in negative symptom schizophrenia, the negative schizotypy group exhibited deficits on free recall, recognition, and source memory tasks. The positive schizotypy group did not demonstrate deficits on the above mentioned tasks. However, in contrast to the other groups, the positive schizotypy group showed an unexpected set-size effect on the cued-recall task. Set-size effect, which refers to the finding that words that have smaller networks of associates tend to have a memory advantage, is usually found in associative-cuing, but not cued-recall, tasks. The finding for the positive schizotypy group is consistent with heightened spreading activation and reduced executive control suggested to underlie psychotic symptoms. The findings support a multidimensional model of schizotypy and schizophrenia, and suggest that positive and negative schizotypy involve differential patterns of cognitive impairment.

  8. Differential trends in the codon usage patterns in HIV-1 genes.

    Directory of Open Access Journals (Sweden)

    Aridaman Pandit

    Full Text Available Host-pathogen interactions underlie one of the most complex evolutionary phenomena resulting in continual adaptive genetic changes, where pathogens exploit the host's molecular resources for growth and survival, while hosts try to eliminate the pathogen. Deciphering the molecular basis of host-pathogen interactions is useful in understanding the factors governing pathogen evolution and disease propagation. In host-pathogen context, a balance between mutation, selection, and genetic drift is known to maintain codon bias in both organisms. Studies revealing determinants of the bias and its dynamics are central to the understanding of host-pathogen evolution. We considered the Human Immunodeficiency Virus (HIV type 1 and its human host to search for evolutionary signatures in the viral genome. Positive selection is known to dominate intra-host evolution of HIV-1, whereas high genetic variability underlies the belief that neutral processes drive inter-host differences. In this study, we analyze the codon usage patterns of HIV-1 genomes across all subtypes and clades sequenced over a period of 23 years. We show presence of unique temporal correlations in the codon bias of three HIV-1 genes illustrating differential adaptation of the HIV-1 genes towards the host preferred codons. Our results point towards gene-specific translational selection to be an important force driving the evolution of HIV-1 at the population level.

  9. The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

    Energy Technology Data Exchange (ETDEWEB)

    Acciarri, R.; Bagby, L.; Baller, B.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Greenlee, H.; James, C.; Jostlein, H.; Ketchum, W.; Kirby, M.; Kobilarcik, T.; Lockwitz, S.; Lundberg, B.; Marchionni, A.; Moore, C.D.; Palamara, O.; Pavlovic, Z.; Raaf, J.L.; Schukraft, A.; Snider, E.L.; Spentzouris, P.; Strauss, T.; Toups, M.; Wolbers, S.; Yang, T.; Zeller, G.P. [Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); Adams, C. [Harvard University, Cambridge, MA (United States); Yale University, New Haven, CT (United States); An, R.; Littlejohn, B.R.; Martinez Caicedo, D.A. [Illinois Institute of Technology (IIT), Chicago, IL (United States); Anthony, J.; Escudero Sanchez, L.; De Vries, J.J.; Marshall, J.; Smith, A.; Thomson, M. [University of Cambridge, Cambridge (United Kingdom); Asaadi, J. [University of Texas, Arlington, TX (United States); Auger, M.; Ereditato, A.; Goeldi, D.; Kreslo, I.; Lorca, D.; Luethi, M.; Rudolf von Rohr, C.; Sinclair, J.; Weber, M. [Universitaet Bern, Bern (Switzerland); Balasubramanian, S.; Fleming, B.T.; Gramellini, E.; Hackenburg, A.; Luo, X.; Russell, B.; Tufanli, S. [Yale University, New Haven, CT (United States); Barnes, C.; Mousseau, J.; Spitz, J. [University of Michigan, Ann Arbor, MI (United States); Barr, G.; Bass, M.; Del Tutto, M.; Laube, A.; Soleti, S.R.; De Pontseele, W.V. [University of Oxford, Oxford (United Kingdom); Bay, F. [TUBITAK Space Technologies Research Institute, Ankara (Turkey); Bishai, M.; Chen, H.; Joshi, J.; Kirby, B.; Li, Y.; Mooney, M.; Qian, X.; Viren, B.; Zhang, C. [Brookhaven National Laboratory (BNL), Upton, NY (United States); Blake, A.; Devitt, D.; Lister, A.; Nowak, J. [Lancaster University, Lancaster (United Kingdom); Bolton, T.; Horton-Smith, G.; Meddage, V.; Rafique, A. [Kansas State University (KSU), Manhattan, KS (United States); Camilleri, L.; Caratelli, D.; Crespo-Anadon, J.I.; Fadeeva, A.A.; Genty, V.; Kaleko, D.; Seligman, W.; Shaevitz, M.H. [Columbia University, New York, NY (United States); Church, E. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Cianci, D.; Karagiorgi, G. [Columbia University, New York, NY (United States); The University of Manchester (United Kingdom); Cohen, E.; Piasetzky, E. [Tel Aviv University, Tel Aviv (Israel); Collin, G.H.; Conrad, J.M.; Hen, O.; Hourlier, A.; Moon, J.; Wongjirad, T.; Yates, L. [Massachusetts Institute of Technology (MIT), Cambridge, MA (United States); Convery, M.; Eberly, B.; Rochester, L.; Tsai, Y.T.; Usher, T. [SLAC National Accelerator Laboratory, Menlo Park, CA (United States); Dytman, S.; Graf, N.; Jiang, L.; Naples, D.; Paolone, V.; Wickremasinghe, D.A. [University of Pittsburgh, Pittsburgh, PA (United States); Esquivel, J.; Hamilton, P.; Pulliam, G.; Soderberg, M. [Syracuse University, Syracuse, NY (United States); Foreman, W.; Ho, J.; Schmitz, D.W.; Zennamo, J. [University of Chicago, IL (United States); Furmanski, A.P.; Garcia-Gamez, D.; Hewes, J.; Hill, C.; Murrells, R.; Porzio, D.; Soeldner-Rembold, S.; Szelc, A.M. [The University of Manchester (United Kingdom); Garvey, G.T.; Huang, E.C.; Louis, W.C.; Mills, G.B.; De Water, R.G.V. [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Gollapinni, S. [Kansas State University (KSU), Manhattan, KS (United States); University of Tennessee, Knoxville, TN (United States); and others

    2018-01-15

    The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies. (orig.)

  10. The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

    Science.gov (United States)

    Acciarri, R.; Adams, C.; An, R.; Anthony, J.; Asaadi, J.; Auger, M.; Bagby, L.; Balasubramanian, S.; Baller, B.; Barnes, C.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Camilleri, L.; Caratelli, D.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Cohen, E.; Collin, G. H.; Conrad, J. M.; Convery, M.; Crespo-Anadón, J. I.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Fadeeva, A. A.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garcia-Gamez, D.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, G.; Hourlier, A.; Huang, E.-C.; James, C.; Jan de Vries, J.; Jen, C.-M.; Jiang, L.; Johnson, R. A.; Joshi, J.; Jostlein, H.; Kaleko, D.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, C.; Marshall, J.; Martinez Caicedo, D. A.; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Piasetzky, E.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; Rudolf von Rohr, C.; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sinclair, J.; Smith, A.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, J.; St. John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y.-T.; Tufanli, S.; Usher, T.; Van De Pontseele, W.; Van de Water, R. G.; Viren, B.; Weber, M.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Yates, L.; Zeller, G. P.; Zennamo, J.; Zhang, C.

    2018-01-01

    The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.

  11. Applied Swarm-based medicine: collecting decision trees for patterns of algorithms analysis.

    Science.gov (United States)

    Panje, Cédric M; Glatzer, Markus; von Rappard, Joscha; Rothermundt, Christian; Hundsberger, Thomas; Zumstein, Valentin; Plasswilm, Ludwig; Putora, Paul Martin

    2017-08-16

    The objective consensus methodology has recently been applied in consensus finding in several studies on medical decision-making among clinical experts or guidelines. The main advantages of this method are an automated analysis and comparison of treatment algorithms of the participating centers which can be performed anonymously. Based on the experience from completed consensus analyses, the main steps for the successful implementation of the objective consensus methodology were identified and discussed among the main investigators. The following steps for the successful collection and conversion of decision trees were identified and defined in detail: problem definition, population selection, draft input collection, tree conversion, criteria adaptation, problem re-evaluation, results distribution and refinement, tree finalisation, and analysis. This manuscript provides information on the main steps for successful collection of decision trees and summarizes important aspects at each point of the analysis.

  12. Imaging of chest trauma: radiological patterns of injury and diagnostic algorithms

    International Nuclear Information System (INIS)

    Lomoschitz, Fritz M.; Eisenhuber, Edith; Linnau, Ken F.; Peloschek, Philipp; Schoder, Maria; Bankier, Alexander A.

    2003-01-01

    In patients after chest trauma, imaging plays a key role for both, the primary diagnostic work-up, and the secondary assessment of potential treatment. Despite its well-known limitations, the anteroposterior chest radiograph remains the starting point of the imaging work-up. Adjunctive imaging with computed tomography, that recently is increasingly often performed on multidetector computed tomography units, adds essential information not readily available on the conventional radiograph. This allows better definition of trauma-associated thoracic injuries not only in acute traumatic aortic injury, but also in pulmonary, tracheobronchial, cardiac, diaphragmal, and thoracic skeletal injuries. This article reviews common radiographic findings in patients after chest trauma, shows typical imaging features resulting from thoracic injury, presents imaging algorithms, and recalls to the reader less common but clinically relevant entities encountered in patients after thoracic trauma

  13. A methodology for obtaining the control rod patterns in a BWR using genetic algorithms

    International Nuclear Information System (INIS)

    Ortiz S, J.J.; Montes T, J.L.; Requena R, I.

    2003-01-01

    In this work the GACRP system based on the genetic algorithms technique for the obtaining of the drivers of control bars in a BWR reactor is presented. This methodology was applied to a transition cycle and a one of balance of the Laguna Verde nuclear power station (CNLV). For each one of the studied cycles, it was executed the methodology with a fixed length of the cycle and it was compared the effective multiplication factor of neutrons at the end of the cycle that it is obtained with the proposed drivers of control bars and the multiplication factor of neutrons obtained by means of a Haling calculation. It was found that it is possible to extend several days the length of both cycles with regard to the one Haling calculation. (Author)

  14. Optimization of heliostat field layout in solar central receiver systems on annual basis using differential evolution algorithm

    International Nuclear Information System (INIS)

    Atif, Maimoon; Al-Sulaiman, Fahad A.

    2015-01-01

    Highlights: • Differential evolution optimization model was developed to optimize the heliostat field. • Five optical parameters were considered for the optimization of the optical efficiency. • Optimization using insolation weighted and un-weighted annual efficiency are developed. • The daily averaged annual optical efficiency was calculated to be 0.5023 while the monthly was 0.5025. • The insolation weighted daily averaged annual efficiency was 0.5634. - Abstract: Optimization of a heliostat field is an essential task to make a solar central receiver system effective because major optical losses are associated with the heliostat fields. In this study, a mathematical model was developed to effectively optimize the heliostat field on annual basis using differential evolution, which is an evolutionary algorithm. The heliostat field layout optimization is based on the calculation of five optical performance parameters: the mirror or the heliostat reflectivity, the cosine factor, the atmospheric attenuation factor, the shadowing and blocking factor, and the intercept factor. This model calculates all the aforementioned performance parameters at every stage of the optimization, until the best heliostat field layout based on annual performance is obtained. Two different approaches were undertaken to optimize the heliostat field layout: one with optimizing insolation weighted annual efficiency and the other with optimizing the un-weighted annual efficiency. Moreover, an alternate approach was also proposed to efficiently optimize the heliostat field in which the number of computational time steps was considerably reduced. It was observed that the daily averaged annual optical efficiency was calculated to be 0.5023 as compared to the monthly averaged annual optical efficiency, 0.5025. Moreover, the insolation weighted daily averaged annual efficiency of the heliostat field was 0.5634 for Dhahran, Saudi Arabia. The code developed can be used for any other

  15. A novel statistical algorithm for gene expression analysis helps differentiate pregnane X receptor-dependent and independent mechanisms of toxicity.

    Directory of Open Access Journals (Sweden)

    M Ann Mongan

    Full Text Available Genome-wide gene expression profiling has become standard for assessing potential liabilities as well as for elucidating mechanisms of toxicity of drug candidates under development. Analysis of microarray data is often challenging due to the lack of a statistical model that is amenable to biological variation in a small number of samples. Here we present a novel non-parametric algorithm that requires minimal assumptions about the data distribution. Our method for determining differential expression consists of two steps: 1 We apply a nominal threshold on fold change and platform p-value to designate whether a gene is differentially expressed in each treated and control sample relative to the averaged control pool, and 2 We compared the number of samples satisfying criteria in step 1 between the treated and control groups to estimate the statistical significance based on a null distribution established by sample permutations. The method captures group effect without being too sensitive to anomalies as it allows tolerance for potential non-responders in the treatment group and outliers in the control group. Performance and results of this method were compared with the Significant Analysis of Microarrays (SAM method. These two methods were applied to investigate hepatic transcriptional responses of wild-type (PXR(+/+ and pregnane X receptor-knockout (PXR(-/- mice after 96 h exposure to CMP013, an inhibitor of β-secretase (β-site of amyloid precursor protein cleaving enzyme 1 or BACE1. Our results showed that CMP013 led to transcriptional changes in hallmark PXR-regulated genes and induced a cascade of gene expression changes that explained the hepatomegaly observed only in PXR(+/+ animals. Comparison of concordant expression changes between PXR(+/+ and PXR(-/- mice also suggested a PXR-independent association between CMP013 and perturbations to cellular stress, lipid metabolism, and biliary transport.

  16. Glucose metabolite patterns as markers of functional differentiation in freshly isolated and cultured mouse mammary epithelial cells

    International Nuclear Information System (INIS)

    Emerman, J.T.; Bartley, J.C.; Bissel, M.J.

    1981-01-01

    In the mammary gland of non-ruminant animals, glucose is utilized in a characteristic and unique way during lacation. By measuring the incorporation of glucose carbon from [U- 14 C]glucose into intermediary metabolitees and metabolic products in mammary epithelia cells from virgin, pregnant, and lacating mice, we domonstrate that glucose metabolite patterns can be used to recognize stages of differentiated function. For these cells, the rates of synthesis of glycogen and lactose, the ratio of lactate to alanine, and the ratio of citrate to malate are important parameters in identifying the degree of expression of differentiation. We further show that these patterns can be used as markers to determine the differentiated state of cultured mammary epithelial cells. Cells maintained on plastic substrates lose their distinctive glucose metabolite patterns while those on floating collagen gels do not. Cells isolated from pregnant mice and cultured on collagen gels have a pattern similar to that of their freshly isolated counter-parts. When isolated from lacating mice, the metabolite patterns of cells cultured on collagen gels are different from that of the cells of origin, and resembles that of freshly isolated cells from pregnant mice. Our findings suggest that the floating collagen gels under the culture conditions used in these experiments provide an environment for the functional expression of the pregnant state, while additional factors are needed for the expression of the lactating state

  17. Multi-objective optimization of in-situ bioremediation of groundwater using a hybrid metaheuristic technique based on differential evolution, genetic algorithms and simulated annealing

    Directory of Open Access Journals (Sweden)

    Kumar Deepak

    2015-12-01

    Full Text Available Groundwater contamination due to leakage of gasoline is one of the several causes which affect the groundwater environment by polluting it. In the past few years, In-situ bioremediation has attracted researchers because of its ability to remediate the contaminant at its site with low cost of remediation. This paper proposed the use of a new hybrid algorithm to optimize a multi-objective function which includes the cost of remediation as the first objective and residual contaminant at the end of the remediation period as the second objective. The hybrid algorithm was formed by combining the methods of Differential Evolution, Genetic Algorithms and Simulated Annealing. Support Vector Machines (SVM was used as a virtual simulator for biodegradation of contaminants in the groundwater flow. The results obtained from the hybrid algorithm were compared with Differential Evolution (DE, Non Dominated Sorting Genetic Algorithm (NSGA II and Simulated Annealing (SA. It was found that the proposed hybrid algorithm was capable of providing the best solution. Fuzzy logic was used to find the best compromising solution and finally a pumping rate strategy for groundwater remediation was presented for the best compromising solution. The results show that the cost incurred for the best compromising solution is intermediate between the highest and lowest cost incurred for other non-dominated solutions.

  18. Reliable computation of roots in analytical waveguide modeling using an interval-Newton approach and algorithmic differentiation.

    Science.gov (United States)

    Bause, Fabian; Walther, Andrea; Rautenberg, Jens; Henning, Bernd

    2013-12-01

    For the modeling and simulation of wave propagation in geometrically simple waveguides such as plates or rods, one may employ the analytical global matrix method. That is, a certain (global) matrix depending on the two parameters wavenumber and frequency is built. Subsequently, one must calculate all parameter pairs within the domain of interest where the global matrix becomes singular. For this purpose, one could compute all roots of the determinant of the global matrix when the two parameters vary in the given intervals. This requirement to calculate all roots is actually the method's most concerning restriction. Previous approaches are based on so-called mode-tracers, which use the physical phenomenon that solutions, i.e., roots of the determinant of the global matrix, appear in a certain pattern, the waveguide modes, to limit the root-finding algorithm's search space with respect to consecutive solutions. In some cases, these reductions of the search space yield only an incomplete set of solutions, because some roots may be missed as a result of uncertain predictions. Therefore, we propose replacement of the mode-tracer approach with a suitable version of an interval- Newton method. To apply this interval-based method, we extended the interval and derivative computation provided by a numerical computing environment such that corresponding information is also available for Bessel functions used in circular models of acoustic waveguides. We present numerical results for two different scenarios. First, a polymeric cylindrical waveguide is simulated, and second, we show simulation results of a one-sided fluid-loaded plate. For both scenarios, we compare results obtained with the proposed interval-Newton algorithm and commercial software.

  19. Meta-algorithmics patterns for robust, low cost, high quality systems

    CERN Document Server

    Simske, Steven J

    2013-01-01

    The confluence of cloud computing, parallelism and advanced machine intelligence approaches has created a world in which the optimum knowledge system will usually be architected from the combination of two or more knowledge-generating systems. There is a need, then, to provide a reusable, broadly-applicable set of design patterns to empower the intelligent system architect to take advantage of this opportunity. This book explains how to design and build intelligent systems that are optimized for changing system requirements (adaptability), optimized for changing system input (robustness), an

  20. The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

    CERN Document Server

    Acciarri, R.; An, R.; Anthony, J.; Asaadi, J.; Auger, M.; Bagby, L.; Balasubramanian, S.; Baller, B.; Barnes, C.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Camilleri, L.; Caratelli, D.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Cohen, E.; Collin, G. H.; Conrad, J. M.; Convery, M.; Crespo-Anadón, J. I.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Fadeeva, A. A.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garcia-Gamez, D.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, G.; Hourlier, A.; Huang, E.-C.; James, C.; Jan de Vries, J.; Jen, C.-M.; Jiang, L.; Johnson, R. A.; Joshi, J.; Jostlein, H.; Kaleko, D.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, C.; Marshall, J.; Martinez Caicedo, D. A.; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Piasetzky, E.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; Rudolf von Rohr, C.; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sinclair, J.; Smith, A.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, J.; St. John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y.-T.; Tufanli, S.; Usher, T.; Van De Pontseele, W.; Van de Water, R. G.; Viren, B.; Weber, M.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Yates, L.; Zeller, G. P.; Zennamo, J.; Zhang, C.

    2017-01-01

    The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the...

  1. New methodologies for measuring Brugada ECG patterns cannot differentiate the ECG pattern of Brugada syndrome from Brugada phenocopy.

    Science.gov (United States)

    Gottschalk, Byron H; Garcia-Niebla, Javier; Anselm, Daniel D; Jaidka, Atul; De Luna, Antoni Bayés; Baranchuk, Adrian

    2016-01-01

    Brugada phenocopies (BrP) are clinical entities characterized by ECG patterns that are identical to true Brugada syndrome (BrS), but are elicited by various clinical circumstances. A recent study demonstrated that the patterns of BrP and BrS are indistinguishable under the naked eye, thereby validating the concept that the patterns are identical. The aim of our study was to determine whether recently developed ECG criteria would allow for discrimination between type-2 BrS ECG pattern and type-2 BrP ECG pattern. Ten ECGs from confirmed BrS (aborted sudden death, transformation into type 1 upon sodium channel blocking test and/or ventricular arrhythmias, positive genetics) cases and 9 ECGs from confirmed BrP were included in the study. Surface 12-lead ECGs were scanned, saved in JPEG format for blind measurement of two values: (i) β-angle; and (ii) the base of the triangle. Cut-off values of ≥58° for the β-angle and ≥4mm for the base of the triangle were used to determine the BrS ECG pattern. Mean values for the β-angle in leads V1 and V2 were 66.7±25.5 and 55.4±28.1 for BrS and 54.1±26.5 and 43.1±16.1 for BrP respectively (p=NS). Mean values for the base of the triangle in V1 and V2 were 7.5±3.9 and 5.7±3.9 for BrS and 5.6±3.2 and 4.7±2.7 for BrP respectively (p=NS). The β-angle had a sensitivity of 60%, specificity of 78% (LR+ 2.7, LR- 0.5). The base of the triangle had a sensitivity of 80%, specificity of 40% (LR+ 1.4, LR- 0.5). New ECG criteria presented relatively low sensitivity and specificity, positive and negative predictive values to discriminate between BrS and BrP ECG patterns, providing further evidence that the two patterns are identical. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. Differential expression pattern of antimicrobial peptides in nasal mucosa and secretion.

    Science.gov (United States)

    Laudien, Martin; Dressel, Stefanie; Harder, Jürgen; Gläser, Regine

    2011-03-01

    The intact nasal barrier is a prerequisite for a functioning defense of the upper airway system, in particular the permanent threat by inhaled potentially harmful microorganisms. Antimicrobial peptides (AMP) play an important role in maintaining barrier function. There is few data about AMP in respect of nasal mucosa. This study is addressed to gain further insight into the differential AMP expression and secretion pattern according to defined anatomical regions of the vestibulum nasi and turbinates. ELISA was applied to quantify concentrations of AMP RNase-7, psoriasin, hBD-2, hBD-3 and LL-37 in nasal secretions of 20 healthy volunteers. Immunohistochemistry was used to detect the local cellular sources of AMP in the vestibulum nasi (squamous epithelium) and compared to the mucosa of the turbinates (pseudostratified epithelium) in 10 healthy volunteers. Expression of RNase 7 and psoriasin was detected in all nasal secretion specimens, whereas LL-37 was detected in 16, hBD-2 in 5 and hBD-3 in 6 specimens. In the vestibulum nasi, luminal cell layers were demonstrated as local cellular sources for hBD-3 and RNase 7, whereas psoriasin was found in all layers of the stratified squamous epithelium. LL-37 was detected in 1 stroma cells sample, whereas hBD-2 was not detected at all. In turbinate biopsie,s hBD-3 and LL-37 were detectable in the epithelium, stroma cells and submucosal glands. RNase 7 was only present in submucosal glands. HBD-2 and psoriasin were not detected. These data demonstrate that the nasal epithelium contains a chemical defense shield through the expression and secretion of various AMP.

  3. Patterns of population differentiation and natural selection on the celiac disease background risk network.

    Science.gov (United States)

    Sams, Aaron; Hawks, John

    2013-01-01

    Celiac disease is a common small intestinal inflammatory condition induced by wheat gluten and related proteins from rye and barley. Left untreated, the clinical presentation of CD can include failure to thrive, malnutrition, and distension in juveniles. The disease can additionally lead to vitamin deficiencies, anemia, and osteoporosis. Therefore, CD potentially negatively affected fitness in past populations utilizing wheat, barley, and rye. Previous analyses of CD risk variants have uncovered evidence for positive selection on some of these loci. These studies also suggest the possibility that risk for common autoimmune conditions such as CD may be the result of positive selection on immune related loci in the genome to fight infection. Under this evolutionary scenario, disease phenotypes may be a trade-off from positive selection on immunity. If this hypothesis is generally true, we can expect to find a signal of natural selection when we survey across the network of loci known to influence CD risk. This study examines the non-HLA autosomal network of gene loci associated with CD risk in Europe. We reject the null hypothesis of neutrality on this network of CD risk loci. Additionally, we can localize evidence of selection in time and space by adding information from the genome of the Tyrolean Iceman. While we can show significant differentiation between continental regions across the CD network, the pattern of evidence is not consistent with primarily recent (Holocene) selection across this network in Europe. Further localization of ancient selection on this network may illuminate the ecological pressures acting on the immune system during this critically interesting phase of our evolution.

  4. Patterns of population differentiation and natural selection on the celiac disease background risk network.

    Directory of Open Access Journals (Sweden)

    Aaron Sams

    Full Text Available Celiac disease is a common small intestinal inflammatory condition induced by wheat gluten and related proteins from rye and barley. Left untreated, the clinical presentation of CD can include failure to thrive, malnutrition, and distension in juveniles. The disease can additionally lead to vitamin deficiencies, anemia, and osteoporosis. Therefore, CD potentially negatively affected fitness in past populations utilizing wheat, barley, and rye. Previous analyses of CD risk variants have uncovered evidence for positive selection on some of these loci. These studies also suggest the possibility that risk for common autoimmune conditions such as CD may be the result of positive selection on immune related loci in the genome to fight infection. Under this evolutionary scenario, disease phenotypes may be a trade-off from positive selection on immunity. If this hypothesis is generally true, we can expect to find a signal of natural selection when we survey across the network of loci known to influence CD risk. This study examines the non-HLA autosomal network of gene loci associated with CD risk in Europe. We reject the null hypothesis of neutrality on this network of CD risk loci. Additionally, we can localize evidence of selection in time and space by adding information from the genome of the Tyrolean Iceman. While we can show significant differentiation between continental regions across the CD network, the pattern of evidence is not consistent with primarily recent (Holocene selection across this network in Europe. Further localization of ancient selection on this network may illuminate the ecological pressures acting on the immune system during this critically interesting phase of our evolution.

  5. Comparison Spatial Pattern of Land Surface Temperature with Mono Window Algorithm and Split Window Algorithm: A Case Study in South Tangerang, Indonesia

    Science.gov (United States)

    Bunai, Tasya; Rokhmatuloh; Wibowo, Adi

    2018-05-01

    In this paper, two methods to retrieve the Land Surface Temperature (LST) from thermal infrared data supplied by band 10 and 11 of the Thermal Infrared Sensor (TIRS) onboard the Landsat 8 is compared. The first is mono window algorithm developed by Qin et al. and the second is split window algorithm by Rozenstein et al. The purpose of this study is to perform the spatial distribution of land surface temperature, as well as to determine more accurate algorithm for retrieving land surface temperature by calculated root mean square error (RMSE). Finally, we present comparison the spatial distribution of land surface temperature by both of algorithm, and more accurate algorithm is split window algorithm refers to the root mean square error (RMSE) is 7.69° C.

  6. Analysis and Classification of Stride Patterns Associated with Children Development Using Gait Signal Dynamics Parameters and Ensemble Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Meihong Wu

    2016-01-01

    Full Text Available Measuring stride variability and dynamics in children is useful for the quantitative study of gait maturation and neuromotor development in childhood and adolescence. In this paper, we computed the sample entropy (SampEn and average stride interval (ASI parameters to quantify the stride series of 50 gender-matched children participants in three age groups. We also normalized the SampEn and ASI values by leg length and body mass for each participant, respectively. Results show that the original and normalized SampEn values consistently decrease over the significance level of the Mann-Whitney U test (p<0.01 in children of 3–14 years old, which indicates the stride irregularity has been significantly ameliorated with the body growth. The original and normalized ASI values are also significantly changing when comparing between any two groups of young (aged 3–5 years, middle (aged 6–8 years, and elder (aged 10–14 years children. Such results suggest that healthy children may better modulate their gait cadence rhythm with the development of their musculoskeletal and neurological systems. In addition, the AdaBoost.M2 and Bagging algorithms were used to effectively distinguish the children’s gait patterns. These ensemble learning algorithms both provided excellent gait classification results in terms of overall accuracy (≥90%, recall (≥0.8, and precision (≥0.8077.

  7. Blackout risk prevention in a smart grid based flexible optimal strategy using Grey Wolf-pattern search algorithms

    International Nuclear Information System (INIS)

    Mahdad, Belkacem; Srairi, K.

    2015-01-01

    Highlights: • A generalized optimal security power system planning strategy for blackout risk prevention is proposed. • A Grey Wolf Optimizer dynamically coordinated with Pattern Search algorithm is proposed. • A useful optimized database dynamically generated considering margin loading stability under severe faults. • The robustness and feasibility of the proposed strategy is validated in the standard IEEE 30 Bus system. • The proposed planning strategy will be useful for power system protection coordination and control. - Abstract: Developing a flexible and reliable power system planning strategy under critical situations is of great importance to experts and industrials to minimize the probability of blackouts occurrence. This paper introduces the first stage of this practical strategy by the application of Grey Wolf Optimizer coordinated with pattern search algorithm for solving the security smart grid power system management under critical situations. The main objective of this proposed planning strategy is to prevent the practical power system against blackout due to the apparition of faults in generating units or important transmission lines. At the first stage the system is pushed to its margin stability limit, the critical loads shedding are selected using voltage stability index. In the second stage the generator control variables, the reactive power of shunt and dynamic compensators are adjusted in coordination with minimization the active and reactive power at critical loads to maintain the system at security state to ensure service continuity. The feasibility and efficiency of the proposed strategy is applied to IEEE 30-Bus test system. Results are promising and prove the practical efficiency of the proposed strategy to ensure system security under critical situations

  8. Optical pattern recognition architecture implementing the mean-square error correlation algorithm

    Science.gov (United States)

    Molley, Perry A.

    1991-01-01

    An optical architecture implementing the mean-square error correlation algorithm, MSE=.SIGMA.[I-R].sup.2 for discriminating the presence of a reference image R in an input image scene I by computing the mean-square-error between a time-varying reference image signal s.sub.1 (t) and a time-varying input image signal s.sub.2 (t) includes a laser diode light source which is temporally modulated by a double-sideband suppressed-carrier source modulation signal I.sub.1 (t) having the form I.sub.1 (t)=A.sub.1 [1+.sqroot.2m.sub.1 s.sub.1 (t)cos (2.pi.f.sub.o t)] and the modulated light output from the laser diode source is diffracted by an acousto-optic deflector. The resultant intensity of the +1 diffracted order from the acousto-optic device is given by: I.sub.2 (t)=A.sub.2 [+2m.sub.2.sup.2 s.sub.2.sup.2 (t)-2.sqroot.2m.sub.2 (t) cos (2.pi.f.sub.o t] The time integration of the two signals I.sub.1 (t) and I.sub.2 (t) on the CCD deflector plane produces the result R(.tau.) of the mean-square error having the form: R(.tau.)=A.sub.1 A.sub.2 {[T]+[2m.sub.2.sup.2.multidot..intg.s.sub.2.sup.2 (t-.tau.)dt]-[2m.sub.1 m.sub.2 cos (2.tau.f.sub.o .tau.).multidot..intg.s.sub.1 (t)s.sub.2 (t-.tau.)dt]} where: s.sub.1 (t) is the signal input to the diode modulation source: s.sub.2 (t) is the signal input to the AOD modulation source; A.sub.1 is the light intensity; A.sub.2 is the diffraction efficiency; m.sub.1 and m.sub.2 are constants that determine the signal-to-bias ratio; f.sub.o is the frequency offset between the oscillator at f.sub.c and the modulation at f.sub.c +f.sub.o ; and a.sub.o and a.sub.1 are constant chosen to bias the diode source and the acousto-optic deflector into their respective linear operating regions so that the diode source exhibits a linear intensity characteristic and the AOD exhibits a linear amplitude characteristic.

  9. Neural patterning of human induced pluripotent stem cells in 3-D cultures for studying biomolecule-directed differential cellular responses.

    Science.gov (United States)

    Yan, Yuanwei; Bejoy, Julie; Xia, Junfei; Guan, Jingjiao; Zhou, Yi; Li, Yan

    2016-09-15

    Appropriate neural patterning of human induced pluripotent stem cells (hiPSCs) is critical to generate specific neural cells/tissues and even mini-brains that are physiologically relevant to model neurological diseases. However, the capacity of signaling factors that regulate 3-D neural tissue patterning in vitro and differential responses of the resulting neural populations to various biomolecules have not yet been fully understood. By tuning neural patterning of hiPSCs with small molecules targeting sonic hedgehog (SHH) signaling, this study generated different 3-D neuronal cultures that were mainly comprised of either cortical glutamatergic neurons or motor neurons. Abundant glutamatergic neurons were observed following the treatment with an antagonist of SHH signaling, cyclopamine, while Islet-1 and HB9-expressing motor neurons were enriched by an SHH agonist, purmorphamine. In neurons derived with different neural patterning factors, whole-cell patch clamp recordings showed similar voltage-gated Na(+)/K(+) currents, depolarization-evoked action potentials and spontaneous excitatory post-synaptic currents. Moreover, these different neuronal populations exhibited differential responses to three classes of biomolecules, including (1) matrix metalloproteinase inhibitors that affect extracellular matrix remodeling; (2) N-methyl-d-aspartate that induces general neurotoxicity; and (3) amyloid β (1-42) oligomers that cause neuronal subtype-specific neurotoxicity. This study should advance our understanding of hiPSC self-organization and neural tissue development and provide a transformative approach to establish 3-D models for neurological disease modeling and drug discovery. Appropriate neural patterning of human induced pluripotent stem cells (hiPSCs) is critical to generate specific neural cells, tissues and even mini-brains that are physiologically relevant to model neurological diseases. However, the capability of sonic hedgehog-related small molecules to tune

  10. Pattern Extraction Algorithm for NetFlow-Based Botnet Activities Detection

    Directory of Open Access Journals (Sweden)

    Rafał Kozik

    2017-01-01

    Full Text Available As computer and network technologies evolve, the complexity of cybersecurity has dramatically increased. Advanced cyber threats have led to current approaches to cyber-attack detection becoming ineffective. Many currently used computer systems and applications have never been deeply tested from a cybersecurity point of view and are an easy target for cyber criminals. The paradigm of security by design is still more of a wish than a reality, especially in the context of constantly evolving systems. On the other hand, protection technologies have also improved. Recently, Big Data technologies have given network administrators a wide spectrum of tools to combat cyber threats. In this paper, we present an innovative system for network traffic analysis and anomalies detection to utilise these tools. The systems architecture is based on a Big Data processing framework, data mining, and innovative machine learning techniques. So far, the proposed system implements pattern extraction strategies that leverage batch processing methods. As a use case we consider the problem of botnet detection by means of data in the form of NetFlows. Results are promising and show that the proposed system can be a useful tool to improve cybersecurity.

  11. A novel iris patterns matching algorithm of weighted polar frequency correlation

    Science.gov (United States)

    Zhao, Weijie; Jiang, Linhua

    2014-11-01

    Iris recognition is recognized as one of the most accurate techniques for biometric authentication. In this paper, we present a novel correlation method - Weighted Polar Frequency Correlation(WPFC) - to match and evaluate two iris images, actually it can also be used for evaluating the similarity of any two images. The WPFC method is a novel matching and evaluating method for iris image matching, which is complete different from the conventional methods. For instance, the classical John Daugman's method of iris recognition uses 2D Gabor wavelets to extract features of iris image into a compact bit stream, and then matching two bit streams with hamming distance. Our new method is based on the correlation in the polar coordinate system in frequency domain with regulated weights. The new method is motivated by the observation that the pattern of iris that contains far more information for recognition is fine structure at high frequency other than the gross shapes of iris images. Therefore, we transform iris images into frequency domain and set different weights to frequencies. Then calculate the correlation of two iris images in frequency domain. We evaluate the iris images by summing the discrete correlation values with regulated weights, comparing the value with preset threshold to tell whether these two iris images are captured from the same person or not. Experiments are carried out on both CASIA database and self-obtained images. The results show that our method is functional and reliable. Our method provides a new prospect for iris recognition system.

  12. Cancer stem cell markers in patterning differentiation and in prognosis of oral squamous cell carcinoma.

    Science.gov (United States)

    Mohanta, Simple; Siddappa, Gangotri; Valiyaveedan, Sindhu Govindan; Dodda Thimmasandra Ramanjanappa, Ravindra; Das, Debashish; Pandian, Ramanan; Khora, Samanta Sekhar; Kuriakose, Moni Abraham; Suresh, Amritha

    2017-06-01

    Differentiation is a major histological parameter determining tumor aggressiveness and prognosis of the patient; cancer stem cells with their slow dividing and undifferentiated nature might be one of the factors determining the same. This study aims to correlate cancer stem cell markers (CD44 and CD147) with tumor differentiation and evaluate their subsequent effect on prognosis. Immunohistochemical analysis in treatment naïve oral cancer patients (n = 53) indicated that the expression of CD147 was associated with poorly differentiated squamous cell carcinoma and moderately differentiated squamous cell carcinoma (p squamous cell carcinoma and poorly differentiated squamous cell carcinoma patients were CD44 high /CD147 high as compared to only 10% of patients with well-differentiated squamous cell carcinoma. A three-way analysis indicated that differentiation correlated with recurrence and survival (p oral squamous cell carcinoma cell lines originating from different grades of oral cancer. Flowcytometry-based analysis indicated an increase in CD44 + /CD147 + cells in cell lines of poorly differentiated squamous cell carcinoma (94.35 ± 1.14%, p squamous cell carcinoma origin (93.49 ± 0.47%, p squamous cell carcinoma origin (23.12% ± 0.49%). Expression profiling indicated higher expression of cancer stem cell and epithelial-mesenchymal transition markers in SCC029B (poorly differentiated squamous cell carcinoma originated; p ≤ 0.001), which was further translated into increased spheroid formation, migration, and invasion (p squamous cell carcinoma origin. This study suggests that CD44 and CD147 together improve the prognostic efficacy of tumor differentiation; in vitro results further point out that these markers might be determinant of differentiation characteristics, imparting properties of increased self-renewal, migration, and invasion.

  13. Current constrained voltage scaled reconstruction (CCVSR) algorithm for MR-EIT and its performance with different probing current patterns

    International Nuclear Information System (INIS)

    Birguel, Oezlem; Eyueboglu, B Murat; Ider, Y Ziya

    2003-01-01

    Conventional injected-current electrical impedance tomography (EIT) and magnetic resonance imaging (MRI) techniques can be combined to reconstruct high resolution true conductivity images. The magnetic flux density distribution generated by the internal current density distribution is extracted from MR phase images. This information is used to form a fine detailed conductivity image using an Ohm's law based update equation. The reconstructed conductivity image is assumed to differ from the true image by a scale factor. EIT surface potential measurements are then used to scale the reconstructed image in order to find the true conductivity values. This process is iterated until a stopping criterion is met. Several simulations are carried out for opposite and cosine current injection patterns to select the best current injection pattern for a 2D thorax model. The contrast resolution and accuracy of the proposed algorithm are also studied. In all simulation studies, realistic noise models for voltage and magnetic flux density measurements are used. It is shown that, in contrast to the conventional EIT techniques, the proposed method has the capability of reconstructing conductivity images with uniform and high spatial resolution. The spatial resolution is limited by the larger element size of the finite element mesh and twice the magnetic resonance image pixel size

  14. Second-order oriented partial-differential equations for denoising in electronic-speckle-pattern interferometry fringes.

    Science.gov (United States)

    Tang, Chen; Han, Lin; Ren, Hongwei; Zhou, Dongjian; Chang, Yiming; Wang, Xiaohang; Cui, Xiaolong

    2008-10-01

    We derive the second-order oriented partial-differential equations (PDEs) for denoising in electronic-speckle-pattern interferometry fringe patterns from two points of view. The first is based on variational methods, and the second is based on controlling diffusion direction. Our oriented PDE models make the diffusion along only the fringe orientation. The main advantage of our filtering method, based on oriented PDE models, is that it is very easy to implement compared with the published filtering methods along the fringe orientation. We demonstrate the performance of our oriented PDE models via application to two computer-simulated and experimentally obtained speckle fringes and compare with related PDE models.

  15. Multilineage differentiation of porcine bone marrow stromal cells associated with specific gene expression pattern

    DEFF Research Database (Denmark)

    Zou, Lijin; Zou, Xuenong; Chen, Li

    2007-01-01

    There are increasing reports regarding differentiation of bone marrow stromal cells (BMSC) from human and various species of animals including pigs. The phenotype and function of BMSC along a mesenchymal lineage differentiation are well characterized by specific transcription factors and marker g...

  16. [Variables related to the emergence of differential patterns in work motivation].

    Science.gov (United States)

    Arrieta, Carlos; Navarro, José; Vicente, Susana

    2008-11-01

    Several longitudinal studies have shown that motivation at work acts chaotically. In very few cases, it may be linear or random. However, the factors that might explain why these different patterns emerge have not been analysed to date. In this exploratory study, we interviewed 73 employees whose motivational patterns were previously known. The results revealed that chaotic patterns were associated with high levels of motivation, self-efficacy beliefs, and perceptions of instrumentality, and also with intrinsic personal goal orientation and a perception of high work control. Linear patterns were associated with extrinsic goals and a perception of work as difficult, and random patterns were linked to high flexibility at work.

  17. Different patterns of amygdala priming differentially affect dentate gyrus plasticity and corticosterone, but not CA1 plasticity.

    Directory of Open Access Journals (Sweden)

    Rose-Marie eVouimba

    2013-05-01

    Full Text Available Stress-induced activation of the amygdala is involved in the modulation of memory processes in the hippocampus. However, stress effects on amygdala and memory remain complex. The activation of the basolateral amygdala (BLA was found to modulate plasticity in other brain areas, including the hippocampus. We previously demonstrated a differential effect of BLA priming on LTP in the CA1 and the dentate gyrus (DG. While BLA priming suppressed long term potentiation (LTP in CA1, it was found to enhance it in the DG. However, since the amygdala itself is amenable to experience-induced plasticity it is thus conceivable that when activity within the amygdala is modified this will have impact on the way the amygdala modulates activity and plasticity in other brain areas. In the current study we examined the effects of different patterns of BLA activation on the modulation of LTP in the DG and CA1, as well as on serum corticosterone (CORT. In CA1, BLA priming impaired LTP induction as was reported before. In contrast, in the DG, varying BLA stimulation intensity and frequency resulted in differential effects on LTP, ranging from no effect to strong impairment or enhancement. Varying BLA stimulation patterns resulted in also differential alterations in Serum CORT, leading to higher CORT levels being positively correlated with LTP magnitude in DG but not in CA1.The results support the notion of a differential role for the DG in aspects of memory, and add to this view the possibility that DG-associated aspects of memory will be enhanced under more emotional or stressful conditions. It is interesting to think of BLA patterns of activation and the differential levels of circulating CORT as two arms of the emotional and stress response that attempt to synchronize brain activity to best meet the challenge. It is foreseeable to think of abnormal such synchronization under extreme conditions, which would lead to the development of maladaptive behavior.

  18. Differential Resting-State Connectivity Patterns of the Right Anterior and Posterior Dorsolateral Prefrontal Cortices (DLPFC in Schizophrenia

    Directory of Open Access Journals (Sweden)

    Natalia Chechko

    2018-05-01

    Full Text Available In schizophrenia (SCZ, dysfunction of the dorsolateral prefrontal cortex (DLPFC has been linked to the deficits in executive functions and attention. It has been suggested that, instead of considering the right DLPFC as a cohesive functional entity, it can be divided into two parts (anterior and posterior based on its whole-brain connectivity patterns. Given these two subregions' differential association with cognitive processes, we investigated the functional connectivity (FC profile of both subregions through resting-state data to determine whether they are differentially affected in SCZ. Resting-state magnetic resonance imaging (MRI scans were obtained from 120 patients and 172 healthy controls (HC at 6 different MRI sites. The results showed differential FC patterns for the anterior and posterior parts of the right executive control-related DLPFC in SCZ with the parietal, the temporal and the cerebellar regions, along with a convergent reduction of connectivity with the striatum and the occipital cortex. An increased psychopathology level was linked to a higher difference in posterior vs. anterior FC for the left IFG/anterior insula, regions involved in higher-order cognitive processes. In sum, the current analysis demonstrated that even between two neighboring clusters connectivity could be differentially disrupted in SCZ. Lacking the necessary anatomical specificity, such notions may in fact be detrimental to a proper understanding of SCZ pathophysiology.

  19. Differential diagnosis between obsessive compulsive disorder and restrictive and repetitive behavioural patterns, activities and interests in autism spectrum disorders.

    Science.gov (United States)

    Paula-Pérez, Isabel

    2013-01-01

    The obsessive compulsive disorder (OCD) and the restricted and repetitive patterns of behavior, interests and activities inherent to autism spectrum disorders (ASD) share a number of features that can make the differential diagnosis between them extremely difficult and lead to erroneous overdiagnosis of OCD in people with autism. In both cases there may appear to have a fixation on routine, ritualized patterns of verbal and nonverbal behavior, resistance to change, and highly restrictive interests, which becomes a real challenge for differentiating rituals, stereotypes and adherence to routines in ASD from obsessions and compulsions in OCD. This article provides key points to clarify this differential diagnosis through the analysis of emotional valence, content, function and psychological theories that explain the obsessions and compulsions in OCD, and the desire for sameness, stereotyped movements and limited interest in autism. The terms "obsession" and "compulsion" should no longer be used when referring to patterns of behavior, interests or restricted and repetitive activities in autism due to syntonic characteristics, low perception of personal responsibility and low neutralizing efforts. Treatment focuses on changing the environment, the use of socio-communicative compensatory strategies and behavioral modification techniques to improve cognitive and behavioral flexibility. When there is comorbidity between, exposure behavioral and response prevention techniques are then used, followed by others of more cognitive orientation if necessary. Copyright © 2012 SEP y SEPB. Published by Elsevier Espana. All rights reserved.

  20. {sup 18}F-FDG uptake at the surgical margin after hepatic resection: Patterns of uptake and differential diagnosis

    Energy Technology Data Exchange (ETDEWEB)

    Peungjesada, Silanath [University New Mexico, Department of Radiology, Albuquerque, NM (United States); Aloia, Thomas A. [University of Texas MD Anderson Cancer Center, Department of Surgical Oncology, Unit 444, Houston, TX (United States); Fox, Patricia [University of Texas MD Anderson Cancer Center, Department of Biostatistics, Unit 1411, Houston, TX (United States); Chasen, Beth [University of Texas MD Anderson Cancer Center, Department of Nuclear Medicine, Unit 1483, Houston, TX (United States); Shin, Sooyoung; Loyer, Evelyne M. [University of Texas MD Anderson Cancer Center, Department of Diagnostic Radiology, Unit 1473, Houston, TX (United States); Baiomy, Ali [Cairo University, National Cancer Center, Cairo (Egypt)

    2015-08-15

    To evaluate the patterns of {sup 18}F-FDG uptake at the surgical margin after hepatectomy to identify features that may differentiate benign and malignant uptake. Patients who had undergone a PET/CT after hepatectomy were identified. Delay between resection and PET/CT, presence of uptake at the surgical margin, pattern of uptake, and maximal standardized value were recorded. The PET/CT findings were correlated with contrast-enhanced CT or MRI. There were 26 patients with increased 18F-FDG uptake; uptake was diffuse in seven and focal in 19. Diffuse uptake was due to inflammation in all cases. Focal uptake was due to recurrence in 12 and inflammation in seven cases. Defining a focal pattern only as a positive for malignancy yielded 100 % sensitivity, 87 % specificity, 37 % false positive rate. As expected, SUV{sub max} was significantly higher for recurrence than inflammation, but did overlap. Contrast-enhanced CT allowed differentiation between malignant and benign uptake in all cases. F-FDG uptake after hepatectomy does not equate to recurrence and yields a high false positive rate. Diffuse uptake did not require additional evaluation in our sample. Focal uptake, however, may be due to recurrence; differentiating benign and malignant nodular uptake relies on optimal contrast-enhanced CT or MRI. (orig.)

  1. Cell adhesion molecules expression pattern indicates that somatic cells arbitrate gonadal sex of differentiating bipotential fetal mouse gonad.

    Science.gov (United States)

    Piprek, Rafal P; Kolasa, Michal; Podkowa, Dagmara; Kloc, Malgorzata; Kubiak, Jacek Z

    2017-10-01

    Unlike other organ anlagens, the primordial gonad is sexually bipotential in all animals. In mouse, the bipotential gonad differentiates into testis or ovary depending on the genetic sex (XY or XX) of the fetus. During gonad development cells segregate, depending on genetic sex, into distinct compartments: testis cords and interstitium form in XY gonad, and germ cell cysts and stroma in XX gonad. However, our knowledge of mechanisms governing gonadal sex differentiation remains very vague. Because it is known that adhesion molecules (CAMs) play a key role in organogenesis, we suspected that diversified expression of CAMs should also play a crucial role in gonad development. Using microarray analysis we identified 129 CAMs and factors regulating cell adhesion during sexual differentiation of mouse gonad. To identify genes expressed differentially in three cell lines in XY and XX gonads: i) supporting (Sertoli or follicular cells), ii) interstitial or stromal cells, and iii) germ cells, we used transgenic mice expressing EGFP reporter gene and FACS cell sorting. Although a large number of CAMs expressed ubiquitously, expression of certain genes was cell line- and genetic sex-specific. The sets of CAMs differentially expressed in supporting versus interstitial/stromal cells may be responsible for segregation of these two cell lines during gonadal development. There was also a significant difference in CAMs expression pattern between XY supporting (Sertoli) and XX supporting (follicular) cells but not between XY and XX germ cells. This indicates that differential CAMs expression pattern in the somatic cells but not in the germ line arbitrates structural organization of gonadal anlagen into testis or ovary. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Regulation and patterns of endogenous and exogenous gene expression during differentiation of embryonal carcinoma cells

    International Nuclear Information System (INIS)

    Astigiano, S.; Sherman, M.I.; Abarzua, P.

    1989-01-01

    Embryonal carcinoma (EC) cells offer an interesting model system for evaluating differentiation because the cells are pluripotent, thus resembling germ cells and embryonic stem cells, and because a number of agents have been defined that are capable of promoting the differentiation of these cells. This chapter examines how EC cells might be triggered to differentiate, with emphasis on retinoic acid because this compound is a potent, naturally occurring inducer that has been studied extensively in this system. The nature of alterations in gene expression during EC cell differentiation is reviewed from the perspective of evaluating whether these changes are likely to be responsible for, or a result of, the differentiation event. Finally, the authors consider in molecular terms why EC cells, but not their differentiated derivatives, are refractory to the expression of many viral genomes following infection. Based upon these studies, they propose that fundamental changes in gene expression that are observed when differentiation is triggered in EC cells are likely to be due to the disappearance or neutralization of strong repressor elements

  3. Differential diagnosis of periapical cyst using collagen birefringence pattern of the cyst wall

    OpenAIRE

    Ji, Hyo Jin; Park, Se-Hee; Cho, Kyung-Mo; Lee, Suk Keun; Kim, Jin Woo

    2017-01-01

    Objectives Periapical lesions, including periapical cyst (PC), periapical granuloma (PG), and periapical abscess (PA), are frequently affected by chemical/physical damage during root canal treatment or severe bacterial infection, and thus, the differential diagnosis of periapical lesions may be difficult due to the presence of severe inflammatory reaction. The aim of this study was to make differential diagnosis among PC, PG, and PA under polarizing microscope. Materials and Methods ...

  4. Impatience versus achievement strivings in the Type A pattern: Differential effects on students' health and academic achievement

    Science.gov (United States)

    Spence, Janet T.; Helmreich, Robert L.; Pred, Robert S.

    1987-01-01

    Psychometric analyses of college students' responses to the Jenkins Activity Survey, a self-report measure of the Type A behavior pattern, revealed the presence of two relatively independent factors. Based on these analyses, two scales, labeled Achievement Strivings (AS) and Impatience and Irritability (II), were developed. In two samples of male and female college students, scores on AS but not on II were found to be significantly correlated with grade point average. Responses to a health survey, on the other hand, indicated that frequency of physical complaints was significantly correlated with II but not with AS. These results suggest that there are two relatively independent factors in the Type A pattern that have differential effects on performance and health. Future research on the personality factors related to coronary heart disease and other disorders might more profitably focus on the syndrome reflected in the II scale than on the Type A pattern.

  5. FDG PET/CT patterns of treatment failure of malignant pleural mesothelioma: relationship to histologic type, treatment algorithm, and survival

    Energy Technology Data Exchange (ETDEWEB)

    Gerbaudo, Victor H.; Mamede, Marcelo [Brigham and Women' s Hospital, Harvard Medical School, Division of Nuclear Medicine and Molecular Imaging, Boston, MA (United States); Trotman-Dickenson, Beatrice; Hatabu, Hiroto [Brigham and Women' s Hospital, Harvard Medical School, Division of Thoracic Radiology, Boston, MA (United States); Sugarbaker, David J. [Brigham and Women' s Hospital, Harvard Medical School, Division of Thoracic Surgery, Boston, MA (United States)

    2011-05-15

    This study investigated the diagnostic performance and prognostic value of fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT in suspected malignant pleural mesothelioma (MPM) recurrence, in the context of patterns and intensity of FDG uptake, histologic type, and treatment algorithm. Fifty patients with MPM underwent FDG PET/CT for restaging 11 {+-} 6 months after therapy. Tumor relapse was confirmed by histopathology, and by clinical evolution and subsequent imaging. Progression-free survival was defined as the time between treatment and the earliest clinical evidence of recurrence. Survival after FDG PET/CT was defined as the time between the scan and death or last follow-up. Overall survival was defined as the time between initial treatment and death or last follow-up date. Treatment failure was confirmed in 42 patients (30 epithelial and 12 non-epithelial MPM). Sensitivity, specificity, accuracy, negative predictive value, and positive predictive value for FDG PET/CT were 97.6, 75, 94, 86, and 95.3%, respectively. FDG PET/CT evidence of single site of recurrence was observed in the ipsilateral hemithorax in 18 patients (44%), contralaterally in 2 (5%), and in the abdomen in 1 patient (2%). Bilateral thoracic relapse was detected in three patients (7%). Simultaneous recurrence in the ipsilateral hemithorax and abdomen was observed in ten (24%) patients and in seven (17%) in all three cavities. Unsuspected distant metastases were detected in 11 patients (26%). Four patterns of uptake were observed in recurrent disease: focal, linear, mixed (focal/linear), and encasing, with a significant difference between the intensity of uptake in malignant lesions compared to benign post-therapeutic changes. Lesion uptake was lower in patients previously treated with more aggressive therapy and higher in intrathoracic lesions of patients with distant metastases. FDG PET/CT helped in the selection of 12 patients (29%) who benefited from additional previously

  6. FDG PET/CT patterns of treatment failure of malignant pleural mesothelioma: relationship to histologic type, treatment algorithm, and survival

    International Nuclear Information System (INIS)

    Gerbaudo, Victor H.; Mamede, Marcelo; Trotman-Dickenson, Beatrice; Hatabu, Hiroto; Sugarbaker, David J.

    2011-01-01

    This study investigated the diagnostic performance and prognostic value of fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT in suspected malignant pleural mesothelioma (MPM) recurrence, in the context of patterns and intensity of FDG uptake, histologic type, and treatment algorithm. Fifty patients with MPM underwent FDG PET/CT for restaging 11 ± 6 months after therapy. Tumor relapse was confirmed by histopathology, and by clinical evolution and subsequent imaging. Progression-free survival was defined as the time between treatment and the earliest clinical evidence of recurrence. Survival after FDG PET/CT was defined as the time between the scan and death or last follow-up. Overall survival was defined as the time between initial treatment and death or last follow-up date. Treatment failure was confirmed in 42 patients (30 epithelial and 12 non-epithelial MPM). Sensitivity, specificity, accuracy, negative predictive value, and positive predictive value for FDG PET/CT were 97.6, 75, 94, 86, and 95.3%, respectively. FDG PET/CT evidence of single site of recurrence was observed in the ipsilateral hemithorax in 18 patients (44%), contralaterally in 2 (5%), and in the abdomen in 1 patient (2%). Bilateral thoracic relapse was detected in three patients (7%). Simultaneous recurrence in the ipsilateral hemithorax and abdomen was observed in ten (24%) patients and in seven (17%) in all three cavities. Unsuspected distant metastases were detected in 11 patients (26%). Four patterns of uptake were observed in recurrent disease: focal, linear, mixed (focal/linear), and encasing, with a significant difference between the intensity of uptake in malignant lesions compared to benign post-therapeutic changes. Lesion uptake was lower in patients previously treated with more aggressive therapy and higher in intrathoracic lesions of patients with distant metastases. FDG PET/CT helped in the selection of 12 patients (29%) who benefited from additional previously

  7. Heterogeneous Patterns of Genetic Diversity and Differentiation in European and Siberian Chiffchaff (Phylloscopus collybita abietinus/P. tristis)

    Science.gov (United States)

    Talla, Venkat; Kalsoom, Faheema; Shipilina, Daria; Marova, Irina; Backström, Niclas

    2017-01-01

    Identification of candidate genes for trait variation in diverging lineages and characterization of mechanistic underpinnings of genome differentiation are key steps toward understanding the processes underlying the formation of new species. Hybrid zones provide a valuable resource for such investigations, since they allow us to study how genomes evolve as species exchange genetic material and to associate particular genetic regions with phenotypic traits of interest. Here, we use whole-genome resequencing of both allopatric and hybridizing populations of the European (Phylloscopus collybita abietinus) and the Siberian chiffchaff (P. tristis)—two recently diverged species which differ in morphology, plumage, song, habitat, and migration—to quantify the regional variation in genome-wide genetic diversity and differentiation, and to identify candidate regions for trait variation. We find that the levels of diversity, differentiation, and divergence are highly heterogeneous, with significantly reduced global differentiation, and more pronounced differentiation peaks in sympatry than in allopatry. This pattern is consistent with regional differences in effective population size and recurrent background selection or selective sweeps reducing the genetic diversity in specific regions prior to lineage divergence, but the data also suggest that postdivergence selection has resulted in increased differentiation and fixed differences in specific regions. We find that hybridization and backcrossing is common in sympatry, and that phenotype is a poor predictor of the genomic composition of sympatric birds. The combination of a differentiation scan approach with identification of fixed differences pinpoint a handful of candidate regions that might be important for trait variation between the two species. PMID:29054864

  8. Efficient constraint-based Sequential Pattern Mining (SPM algorithm to understand customers’ buying behaviour from time stamp-based sequence dataset

    Directory of Open Access Journals (Sweden)

    Niti Ashish Kumar Desai

    2015-12-01

    Full Text Available Business Strategies are formulated based on an understanding of customer needs. This requires development of a strategy to understand customer behaviour and buying patterns, both current and future. This involves understanding, first how an organization currently understands customer needs and second predicting future trends to drive growth. This article focuses on purchase trend of customer, where timing of purchase is more important than association of item to be purchased, and which can be found out with Sequential Pattern Mining (SPM methods. Conventional SPM algorithms worked purely on frequency identifying patterns that were more frequent but suffering from challenges like generation of huge number of uninteresting patterns, lack of user’s interested patterns, rare item problem, etc. Article attempts a solution through development of a SPM algorithm based on various constraints like Gap, Compactness, Item, Recency, Profitability and Length along with Frequency constraint. Incorporation of six additional constraints is as well to ensure that all patterns are recently active (Recency, active for certain time span (Compactness, profitable and indicative of next timeline for purchase (Length―Item―Gap. The article also attempts to throw light on how proposed Constraint-based Prefix Span algorithm is helpful to understand buying behaviour of customer which is in formative stage.

  9. A Contextualized, Differential Sequence Mining Method to Derive Students' Learning Behavior Patterns

    Science.gov (United States)

    Kinnebrew, John S.; Loretz, Kirk M.; Biswas, Gautam

    2013-01-01

    Computer-based learning environments can produce a wealth of data on student learning interactions. This paper presents an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs a novel combination of sequence mining techniques to identify deferentially…

  10. Patterns of brain structural connectivity differentiate normal weight from overweight subjects

    Directory of Open Access Journals (Sweden)

    Arpana Gupta

    2015-01-01

    Conclusions: 1. An increased BMI (i.e., overweight subjects is associated with distinct changes in gray-matter and fiber density of the brain. 2. Classification algorithms based on white-matter connectivity involving regions of the reward and associated networks can identify specific targets for mechanistic studies and future drug development aimed at abnormal ingestive behavior and in overweight/obesity.

  11. pSum-SaDE: A Modified p-Median Problem and Self-Adaptive Differential Evolution Algorithm for Text Summarization

    Directory of Open Access Journals (Sweden)

    Rasim M. Alguliev

    2011-01-01

    Full Text Available Extractive multidocument summarization is modeled as a modified p-median problem. The problem is formulated with taking into account four basic requirements, namely, relevance, information coverage, diversity, and length limit that should satisfy summaries. To solve the optimization problem a self-adaptive differential evolution algorithm is created. Differential evolution has been proven to be an efficient and robust algorithm for many real optimization problems. However, it still may converge toward local optimum solutions, need to manually adjust the parameters, and finding the best values for the control parameters is a consuming task. In the paper is proposed a self-adaptive scaling factor in original DE to increase the exploration and exploitation ability. This paper has found that self-adaptive differential evolution can efficiently find the best solution in comparison with the canonical differential evolution. We implemented our model on multi-document summarization task. Experiments have shown that the proposed model is competitive on the DUC2006 dataset.

  12. Modulating Functions Based Algorithm for the Estimation of the Coefficients and Differentiation Order for a Space-Fractional Advection-Dispersion Equation

    KAUST Repository

    Aldoghaither, Abeer

    2015-12-01

    In this paper, a new method, based on the so-called modulating functions, is proposed to estimate average velocity, dispersion coefficient, and differentiation order in a space-fractional advection-dispersion equation, where the average velocity and the dispersion coefficient are space-varying. First, the average velocity and the dispersion coefficient are estimated by applying the modulating functions method, where the problem is transformed into a linear system of algebraic equations. Then, the modulating functions method combined with a Newton\\'s iteration algorithm is applied to estimate the coefficients and the differentiation order simultaneously. The local convergence of the proposed method is proved. Numerical results are presented with noisy measurements to show the effectiveness and robustness of the proposed method. It is worth mentioning that this method can be extended to general fractional partial differential equations.

  13. Modulating Functions Based Algorithm for the Estimation of the Coefficients and Differentiation Order for a Space-Fractional Advection-Dispersion Equation

    KAUST Repository

    Aldoghaither, Abeer; Liu, Da-Yan; Laleg-Kirati, Taous-Meriem

    2015-01-01

    In this paper, a new method, based on the so-called modulating functions, is proposed to estimate average velocity, dispersion coefficient, and differentiation order in a space-fractional advection-dispersion equation, where the average velocity and the dispersion coefficient are space-varying. First, the average velocity and the dispersion coefficient are estimated by applying the modulating functions method, where the problem is transformed into a linear system of algebraic equations. Then, the modulating functions method combined with a Newton's iteration algorithm is applied to estimate the coefficients and the differentiation order simultaneously. The local convergence of the proposed method is proved. Numerical results are presented with noisy measurements to show the effectiveness and robustness of the proposed method. It is worth mentioning that this method can be extended to general fractional partial differential equations.

  14. Changing and Differentiated Urban Landscape in China: Spatiotemporal Patterns and Driving Forces.

    Science.gov (United States)

    Fang, Chuanglin; Li, Guangdong; Wang, Shaojian

    2016-03-01

    Urban landscape spatiotemporal change patterns and their driving mechanisms in China are poorly understood at the national level. Here we used remote sensing data, landscape metrics, and a spatial econometric model to characterize the spatiotemporal patterns of urban landscape change and investigate its driving forces in China between 1990 and 2005. The results showed that the urban landscape pattern has experienced drastic changes over the past 15 years. Total urban area has expanded approximately 1.61 times, with a 2.98% annual urban-growth rate. Compared to previous single-city studies, although urban areas are expanding rapidly, the overall fragmentation of the urban landscape is decreasing and is more irregular and complex at the national level. We also found a stair-stepping, urban-landscape changing pattern among eastern, central, and western counties. In addition, administrative level, urban size, and hierarchy have effects on the urban landscape pattern. We also found that a combination of landscape metrics can be used to supplement our understanding of the pattern of urbanization. The changes in these metrics are correlated with geographical indicators, socioeconomic factors, infrastructure variables, administrative level factors, policy factors, and historical factors. Our results indicate that the top priority should be strengthening the management of urban planning. A compact and congregate urban landscape may be a good choice of pattern for urban development in China.

  15. Investigation on the applicability of Piety's on-line PSD-pattern recognition algorithm to boiling detection by neutron-noise at a swimming-pool reactor

    International Nuclear Information System (INIS)

    Behringer, K.; Spiekerman, G.; Yadigaroglu, G.

    1984-11-01

    The neutron noise signal of an initiation-of-boiling experiment performed at the SAPHIR reactor has been analyzed by the PSD-pattern recognition algorithm of Piety (1977); the results indicate that the onset of boiling can be detected by this method. Improved confidence statements for the statistical decision discriminants are given. (Auth.)

  16. Differential Effects of Psychological and Physical Stress on the Sleep Pattern in Rats

    OpenAIRE

    Cui, Ranji; Li, Bingjin; Suemaru, Katsuya; Araki, Hiroaki

    2007-01-01

    In the present study, we investigated the acute effects of 2 different kinds of stress, namely physical stress (foot shock) and psychological stress (non-foot shock) induced by the communication box method, on the sleep patterns of rats. The sleep patterns were recorded for 6 h immediately after 1 h of stress. Physical and psychological stress had almost opposite effects on the sleep patterns: In the physical stress group, hourly total rapid eye movement (REM) sleep and total non-REM sleep we...

  17. Basal cell carcinoma: CD56 and cytokeratin 5/6 staining patterns in the differential diagnosis with Merkel cell carcinoma.

    Science.gov (United States)

    Panse, Gauri; McNiff, Jennifer M; Ko, Christine J

    2017-06-01

    Basal cell carcinoma (BCC) can resemble Merkel cell carcinoma (MCC) on histopathological examination and while CK20 is a useful marker in this differential, it is occasionally negative in MCC. CD56, a sensitive marker of neuroendocrine differentiation, is sometimes used to identify MCC, but has been reportedly variably positive in BCC as well. In contrast, CK5/6 consistently labels BCC but is not expressed in neuroendocrine tumors. We evaluated 20 cases of BCC for the pattern of CD56 and cytokeratin 5/6 (CK5/6) staining, hypothesizing that these 2 stains could differentiate BCC from MCC in difficult cases. Seventeen cases of MCC previously stained with CD56 were also examined. All BCCs showed patchy expression of CD56 except for 2 cases, which showed staining of greater than 70% of tumor. CK5/6 was diffusely positive in all cases of BCC. Fifteen of 17 MCCs were diffusely positive for CD56. The difference in the pattern of CD56 expression between MCC and BCC (diffuse vs patchy, respectively) was statistically significant (P < .05). BCC typically shows patchy CD56 expression and diffuse CK5/6 positivity. These 2 markers can be used to distinguish between BCC and MCC in challenging cases. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  18. Patterns and processes in the genetic differentiation of the Brachionus calyciflorus complex, a passively dispersing freshwater zooplankton.

    Science.gov (United States)

    Xiang, Xian-ling; Xi, Yi-long; Wen, Xin-li; Zhang, Gen; Wang, Jin-xia; Hu, Ke

    2011-05-01

    Elucidating the evolutionary patterns and processes of extant species is an important objective of any research program that seeks to understand population divergence and, ultimately, speciation. The island-like nature and temporal fluctuation of limnetic habitats create opportunities for genetic differentiation in rotifers through space and time. To gain further understanding of spatio-temporal patterns of genetic differentiation in rotifers other than the well-studied Brachionus plicatilis complex in brackish water, a total of 318 nrDNA ITS sequences from the B. calyciflorus complex in freshwater were analysed using phylogenetic and phylogeographic methods. DNA taxonomy conducted by both the sequence divergence and the GMYC model suggested the occurrence of six potential cryptic species, supported also by reproductive isolation among the tested lineages. The significant genetic differentiation and non-significant correlation between geographic and genetic distances existed in the most abundant cryptic species, BcI-W and Bc-SW. The large proportion of genetic variability for cryptic species Bc-SW was due to differences between sampling localities within seasons, rather than between different seasons. Nested Clade Analysis suggested allopatric or past fragmentation, contiguous range expansion and long-distance colonization possibly coupled with subsequent fragmentation as the probable main forces shaping the present-day phylogeographic structure of the B. calyciflorus species complex. Copyright © 2011 Elsevier Inc. All rights reserved.

  19. Average correlation clustering algorithm (ACCA) for grouping of co-regulated genes with similar pattern of variation in their expression values.

    Science.gov (United States)

    Bhattacharya, Anindya; De, Rajat K

    2010-08-01

    Distance based clustering algorithms can group genes that show similar expression values under multiple experimental conditions. They are unable to identify a group of genes that have similar pattern of variation in their expression values. Previously we developed an algorithm called divisive correlation clustering algorithm (DCCA) to tackle this situation, which is based on the concept of correlation clustering. But this algorithm may also fail for certain cases. In order to overcome these situations, we propose a new clustering algorithm, called average correlation clustering algorithm (ACCA), which is able to produce better clustering solution than that produced by some others. ACCA is able to find groups of genes having more common transcription factors and similar pattern of variation in their expression values. Moreover, ACCA is more efficient than DCCA with respect to the time of execution. Like DCCA, we use the concept of correlation clustering concept introduced by Bansal et al. ACCA uses the correlation matrix in such a way that all genes in a cluster have the highest average correlation values with the genes in that cluster. We have applied ACCA and some well-known conventional methods including DCCA to two artificial and nine gene expression datasets, and compared the performance of the algorithms. The clustering results of ACCA are found to be more significantly relevant to the biological annotations than those of the other methods. Analysis of the results show the superiority of ACCA over some others in determining a group of genes having more common transcription factors and with similar pattern of variation in their expression profiles. Availability of the software: The software has been developed using C and Visual Basic languages, and can be executed on the Microsoft Windows platforms. The software may be downloaded as a zip file from http://www.isical.ac.in/~rajat. Then it needs to be installed. Two word files (included in the zip file) need to

  20. Hedonic, Instrumental, and Normative Motives: Differentiating Patterns for Popular, Accepted, and Rejected Adolescents

    Science.gov (United States)

    Dijkstra, Jan Kornelis; Kretschmer, Tina; Lindenberg, Siegwart; Veenstra, René

    2015-01-01

    This study examined to what extent motives for behavior differentiated between popular, accepted, and rejected adolescents. Based on goal-framing theory, three types of motives were distinguished: hedonic (aimed at short-term gratification), instrumental (aimed at improvement of one's situation), and normative (aimed at acting in accordance with…

  1. Differential invasion success of salmonids in southern Chile: patterns and hypotheses

    Science.gov (United States)

    Ivan Arismendi; Brooke E. Penaluna; Jason B. Dunham; Carlos Garcia de Leaniz; Doris Soto; Ian A. Fleming; Daniel Gomez-Uchida; Gonzalo Gajardo; Pamela V. Varga; Jorge León-Muñoz

    2014-01-01

    Biological invasions create complex ecological and societal issues worldwide. Most of the knowledge about invasions comes only from successful invaders, but less is known about which processes determine the differential success of invasions. In this review, we develop a framework to identify the main dimensions driving the success and failure of invaders, including...

  2. Identification and expression patterns of adipokine genes during adipocyte differentiation in the Tibetan goat (Capra hircus).

    Science.gov (United States)

    Li, Xueying; Wang, Yan; Guo, Jiazhong; Zhong, Tao; Li, Li; Zhang, Hongping; Wang, Linjie

    2018-02-15

    Adipokines are secreted by adipose tissue and play an important role in the regulation of lipid metabolism. However, the information regarding adipokines in goats is limited. PPARγ is a key gene in adipocyte differentiation and activates adipokine genes. Rosiglitazone is a PPARγ agonist and can promote the expression of PPARγ to increase the expression of lipogenesis-related genes. Therefore, investigation of the relationship between rosiglitazone and adipokines will help us to better understand the function of PPARγ in lipid metabolism in Tibetan goats. In this study, we cloned the resistin (RETN), apelin (APLN), fibroblast growth factor 21 (FGF21), and visfatin (NAMPT) genes from non-pregnant female Tibetan goat adipose tissue. APLN and NAMPT were predominantly expressed in the kidney, and FGF21 was expressed at the highest levels in the liver in vivo. In fat tissues, the highest expression levels of FGF21 and RETN were detected in omental fat, whereas their expression in perirenal and subcutaneous fat was extremely weak. APLN and NAMPT were abundantly expressed in omental and subcutaneous fat in vivo. In addition, the four adipokines had different expression profiles during goat adipocyte differentiation in vitro. Oil red O staining showed that rosiglitazone could promote adipocyte differentiation and lipid droplet formation. In addition, rosiglitazone significantly increased the expression of FGF21 and RETN (pgoat adipocyte differentiation. And PPARγ could regulate the expression of the four adipokines, but the detailed regulatory mechanism still needs to be elucidated. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Surface N-glycoproteome patterns reveal key proteins of neuronal differentiation

    Czech Academy of Sciences Publication Activity Database

    Tylečková, Jiřina; Valeková, Ivona; Žižková, Martina; Rákocyová, Michaela; Maršala, S.; Maršala, M.; Gadher, S. J.; Kovářová, Hana

    2016-01-01

    Roč. 132, č. 1 (2016), s. 13-20 ISSN 1874-3919 R&D Projects: GA MŠk ED2.1.00/03.0124; GA TA ČR(CZ) TA01011466 Institutional support: RVO:67985904 Keywords : cell adhesion proteins * cell surface capture * neuronal differentiation Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.914, year: 2016

  4. Gene expression patterns related to osteogenic differentiation of bone marrow-derived mesenchymal stem cells during ex vivo expansion.

    Science.gov (United States)

    Granchi, Donatella; Ochoa, Gorka; Leonardi, Elisa; Devescovi, Valentina; Baglìo, Serena Rubina; Osaba, Lourdes; Baldini, Nicola; Ciapetti, Gabriela

    2010-06-01

    Bone marrow is commonly used as a source of adult multipotent mesenchymal stem cells (MSCs), defined for their ability to differentiate in vitro into multiple lineages. The ex vivo-expanded MSCs are currently being evaluated as a strategy for the restoration of function in damaged skeletal tissue, both in cell therapy and tissue engineering applications. The aim of this study was to define gene expression patterns underlying the differentiation of MSCs into mature osteoblasts during the expansion in vitro, and to explore a variety of cell functions that cannot be easily evaluated using morphological, cytochemical, and biochemical assays. Cell cultures were obtained from bone marrow samples of six individuals undergoing total hip replacement, and a large-scale transcriptome analysis, using Affymetrix HG-U133A Plus 2.0 array (Affymetrix((R)), Santa Clara, CA), was performed at the occurrence of specific events, including the appearance of MSC surface markers, formation of colonies, and deposition of mineral nodules. We focused our attention on 213 differentially upregulated genes, some belonging to well-known pathways and some having one or more Gene Ontology annotations related to bone cell biology, including angiogenesis, bone-related genes, cell communication, development and morphogenesis, transforming growth factor-beta signaling, and Wnt signaling. Twenty-nine genes, whose role in bone cell pathophysiology has not been described yet, were found. In conclusion, gene expression patterns that characterize the early, intermediate, and late phases of the osteogenic differentiation process of ex vivo-expanded MSCs were defined. These signatures represent a useful tool to monitor the osteogenic process, and to analyze a broad spectrum of functions of MSCs cultured on scaffolds, especially when the constructs are conceived for releasing growth factors or other signals to promote bone regeneration.

  5. Multilayered epithelium in a rat model and human Barrett's esophagus: Similar expression patterns of transcription factors and differentiation markers

    Directory of Open Access Journals (Sweden)

    Yang Chung S

    2008-01-01

    Full Text Available Abstract Background In rats, esophagogastroduodenal anastomosis (EGDA without concomitant chemical carcinogen treatment leads to gastroesophageal reflux disease, multilayered epithelium (MLE, a presumed precursor in intestinal metaplasia, columnar-lined esophagus, dysplasia, and esophageal adenocarcinoma. Previously we have shown that columnar-lined esophagus in EGDA rats resembled human Barrett's esophagus (BE in its morphology, mucin features and expression of differentiation markers (Lab. Invest. 2004;84:753–765. The purpose of this study was to compare the phenotype of rat MLE with human MLE, in order to gain insight into the nature of MLE and its potential role in the development of BE. Methods Serial sectioning was performed on tissue samples from 32 EGDA rats and 13 patients with established BE. Tissue sections were immunohistochemically stained for a variety of transcription factors and differentiation markers of esophageal squamous epithelium and intestinal columnar epithelium. Results We detected MLE in 56.3% (18/32 of EGDA rats, and in all human samples. As expected, both rat and human squamous epithelium, but not intestinal metaplasia, expressed squamous transcription factors and differentiation markers (p63, Sox2, CK14 and CK4 in all cases. Both rat and human intestinal metaplasia, but not squamous epithelium, expressed intestinal transcription factors and differentiation markers (Cdx2, GATA4, HNF1α, villin and Muc2 in all cases. Rat MLE shared expression patterns of Sox2, CK4, Cdx2, GATA4, villin and Muc2 with human MLE. However, p63 and CK14 were expressed in a higher proportion of rat MLE compared to humans. Conclusion These data indicate that rat MLE shares similar properties to human MLE in its expression pattern of these markers, not withstanding small differences, and support the concept that MLE may be a transitional stage in the metaplastic conversion of squamous to columnar epithelium in BE.

  6. Differentiation of specific ripple patterns helps to identify epileptogenic areas for surgical procedures.

    Science.gov (United States)

    Kerber, Karolin; Dümpelmann, Matthias; Schelter, Björn; Le Van, Pierre; Korinthenberg, Rudolf; Schulze-Bonhage, Andreas; Jacobs, Julia

    2014-07-01

    High frequency oscillations (HFOs) at 80-500 Hz are promising markers of epileptic areas. Several retrospective studies reported that surgical removal of areas generating HFOs was associated with a good seizure outcome. Recent reports suggested that ripple (80-200 Hz) HFO patterns co-existed with different background EEG activities. We hypothesized that the coexisting background EEG pattern may distinguish physiological from epileptic ripples. Rates of HFOs were analyzed in intracranial EEG recordings of 22 patients. Additionally, ripple patterns were classified for each channel depending either as coexisting with a flat or oscillatory background activity. A multi-variate analysis was performed to determine whether removal of areas showing the above EEG markers correlated with seizure outcome. Removal of areas generating high rates of 'fast ripples (>200 Hz)' and 'ripples on a flat background activity' showed a significant correlation with a seizure-free outcome. In contrast, removal of high rates of 'ripples' or 'ripple patterns in a continuously oscillating background' was not significantly associated with seizure outcome. Ripples occurring in an oscillatory background activity may be suggestive of physiological activity, while those on a flat background reflect epileptic activity. Consideration of coexisting background patterns may improve the delineation of the epileptogenic areas using ripple oscillations. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  7. Solving Bi-Objective Optimal Power Flow using Hybrid method of Biogeography-Based Optimization and Differential Evolution Algorithm: A case study of the Algerian Electrical Network

    Directory of Open Access Journals (Sweden)

    Ouafa Herbadji

    2016-03-01

    Full Text Available This paper proposes a new hybrid metaheuristique algorithm based on the hybridization of Biogeography-based optimization with the Differential Evolution for solving the optimal power flow problem with emission control. The biogeography-based optimization (BBO algorithm is strongly influenced by equilibrium theory of island biogeography, mainly through two steps: Migration and Mutation. Differential Evolution (DE is one of the best Evolutionary Algorithms for global optimization. The hybridization of these two methods is used to overcome traps of local optimal solutions and problems of time consumption. The objective of this paper is to minimize the total fuel cost of generation, total emission, total real power loss and also maintain an acceptable system performance in terms of limits on generator real power, bus voltages and power flow of transmission lines. In the present work, BBO/DE has been applied to solve the optimal power flow problems on IEEE 30-bus test system and the Algerian electrical network 114 bus. The results obtained from this method show better performances compared with DE, BBO and other well known metaheuristique and evolutionary optimization methods.

  8. Differential expression pattern of extracellular matrix molecules during chondrogenesis of mesenchymal stem cells from bone marrow and adipose tissue

    DEFF Research Database (Denmark)

    Mehlhorn, A T; Niemeyer, P; Kaiser, S

    2006-01-01

    Adipose-derived adult stem cells (ADASCs) or bone marrow-derived mesenchymal stem cells (BMSCs) are considered as alternative cell sources for cell-based cartilage repair due to their ability to produce cartilage-specific matrix. This article addresses the differential expression pattern...... chondroinduction. TGF-beta1 induces alternative splicing of the alpha(1)-procollagen type II transcript in BMSCs, but not in ADASCs. These findings may direct the development of a cell-specific culture environment either to prevent hypertrophy in BMSCs or to promote chondrogenic maturation in ADASCs....

  9. Different patterns of contingent stimulation differentially affect attention span in prelinguistic infants.

    Science.gov (United States)

    Miller, Jennifer L; Ables, Erin M; King, Andrew P; West, Meredith J

    2009-06-01

    The ability to sustain attention influences different domains including cognitive, motor, and communicative behavior. Previous research has demonstrated how an infant's parent can influence sustained attention. The purpose of our study was to expose infants systematically to both sensitive and redirective patterns of behavior to examine how unfamiliar individuals could influence attention. Results revealed infants changed their patterns of looking with the unfamiliar individuals. Infants had longer durations of sustained attention when interacting with a sensitive unfamiliar individual who followed into their attentional focus as opposed to an intrusive person who led their attentional focus. This study demonstrates that infants discriminate patterns of contingency to persons seen for only a short period of time broadening the range of potential mentors for learning.

  10. Differentiation of Melipona quadrifasciata L. (Hymenoptera, Apidae, Meliponini subspecies using cytochrome b PCR-RFLP patterns

    Directory of Open Access Journals (Sweden)

    Rogério O. Souza

    2008-01-01

    Full Text Available Melipona quadrifasciata quadrifasciata and M. quadrifasciata anthidioides are subspecies of M. quadrifasciata, a stingless bee species common in coastal Brazil. These subspecies are discriminated by the yellow stripe pattern of the abdominal tergites. We found Vsp I restriction patterns in the cytochrome b region closely associated to each subspecies in 155 M. quadrifasciata colonies of different geographical origin. This mitochondrial DNA molecular marker facilitates diagnosis of M. quadrifasciata subspecies matrilines and can be used to establish their natural distribution and identify hybrid colonies.

  11. Development and validation of algorithms to differentiate ductal carcinoma in situ from invasive breast cancer within administrative claims data.

    Science.gov (United States)

    Hirth, Jacqueline M; Hatch, Sandra S; Lin, Yu-Li; Giordano, Sharon H; Silva, H Colleen; Kuo, Yong-Fang

    2018-04-18

    Overtreatment is a common concern for patients with ductal carcinoma in situ (DCIS), but this entity is difficult to distinguish from invasive breast cancers in administrative claims data sets because DCIS often is coded as invasive breast cancer. Therefore, the authors developed and validated algorithms to select DCIS cases from administrative claims data to enable outcomes research in this type of data. This retrospective cohort using invasive breast cancer and DCIS cases included women aged 66 to 70 years in the 2004 through 2011 Texas Cancer Registry (TCR) data linked to Medicare administrative claims data. TCR records were used as "gold" standards to evaluate the sensitivity, specificity, and positive predictive value (PPV) of 2 algorithms. Women with a biopsy enrolled in Medicare parts A and B at 12 months before and 6 months after their first biopsy without a second incident diagnosis of DCIS or invasive breast cancer within 12 months in the TCR were included. Women in 2010 Medicare data were selected to test the algorithms in a general sample. In the TCR data set, a total of 6907 cases met inclusion criteria, with 1244 DCIS cases. The first algorithm had a sensitivity of 79%, a specificity of 89%, and a PPV of 62%. The second algorithm had a sensitivity of 50%, a specificity of 97%. and a PPV of 77%. Among women in the general sample, the specificity was high and the sensitivity was similar for both algorithms. However, the PPV was approximately 6% to 7% lower. DCIS frequently is miscoded as invasive breast cancer, and thus the proposed algorithms are useful to examine DCIS outcomes using data sets not linked to cancer registries. Cancer 2018. © 2018 American Cancer Society. © 2018 American Cancer Society.

  12. Cellular automata for spatiotemporal pattern formation from reaction–diffusion partial differential equations

    International Nuclear Information System (INIS)

    Ohmori, Shousuke; Yamazaki, Yoshihiro

    2016-01-01

    Ultradiscrete equations are derived from a set of reaction–diffusion partial differential equations, and cellular automaton rules are obtained on the basis of the ultradiscrete equations. Some rules reproduce the dynamical properties of the original reaction–diffusion equations, namely, bistability and pulse annihilation. Furthermore, other rules bring about soliton-like preservation and periodic pulse generation with a pacemaker, which are not obtained from the original reaction–diffusion equations. (author)

  13. Laser Raman detection of platelets for early and differential diagnosis of Alzheimer’s disease based on an adaptive Gaussian process classification algorithm

    International Nuclear Information System (INIS)

    Luo, Yusheng; Du, Z W; Yang, Y J; Chen, P; Wang, X H; Cheng, Y; Peng, J; Shen, A G; Hu, J M; Tian, Q; Shang, X L; Liu, Z C; Yao, X Q; Wang, J Z

    2013-01-01

    Early and differential diagnosis of Alzheimer’s disease (AD) has puzzled many clinicians. In this work, laser Raman spectroscopy (LRS) was developed to diagnose AD from platelet samples from AD transgenic mice and non-transgenic controls of different ages. An adaptive Gaussian process (GP) classification algorithm was used to re-establish the classification models of early AD, advanced AD and the control group with just two features and the capacity for noise reduction. Compared with the previous multilayer perceptron network method, the GP showed much better classification performance with the same feature set. Besides, spectra of platelets isolated from AD and Parkinson’s disease (PD) mice were also discriminated. Spectral data from 4 month AD (n = 39) and 12 month AD (n = 104) platelets, as well as control data (n = 135), were collected. Prospective application of the algorithm to the data set resulted in a sensitivity of 80%, a specificity of about 100% and a Matthews correlation coefficient of 0.81. Samples from PD (n = 120) platelets were also collected for differentiation from 12 month AD. The results suggest that platelet LRS detection analysis with the GP appears to be an easier and more accurate method than current ones for early and differential diagnosis of AD. (paper)

  14. Pattern of genetic differentiation of an incipient speciation process: The case of the high Andean killifish Orestias

    Science.gov (United States)

    Guerrero-Jiménez, Claudia Jimena; Peña, Fabiola; Morales, Pamela; Méndez, Marco; Sallaberry, Michel; Vila, Irma; Poulin, Elie

    2017-01-01

    During the Pleistocene and Holocene, the southwest Andean Altiplano (17°-22°S) was affected by repeated fluctuations in water levels, high volcanic activity and major tectonic movements. In the early Holocene the humid Tauca phase shifted to the arid conditions that have lasted until the present, producing endorheic rivers, lakes, lagoons and wetlands. The endemic fish Orestias (Cyprinodontidae) represents a good model to observe the genetic differentiation that characterizes an incipient speciation process in allopatry since the morphospecies described inhabit a restricted geographic area, with present habitat fragmentation. The genetic diversity and population structure of four endemic morphospecies of Orestias (Cyprinodontidae) found in the Lauca National Park (LNP) analyzed with mitochondrial markers (Control Region) and eight microsatellites, revealed the existence of genetic groups that matches the fragmentation of these systems. High values of genetic and phylogeographic differentiation indices were observed between Chungará Lake and Piacota lagoon. The group composed of the Lauca River, Copapujo and Chuviri wetlands sampling sites showed a clear signal of expansion, with a star-like haplotype network. Levels of genetic differentiation were lower than in Chungará and Piacota, suggesting that these localities would have differentiated after the bottlenecks linked to the collapse of Parinacota volcano. The Parinacota sample showed a population signal that differed from the other localities revealing greater genetic diversity and a disperse network, presenting haplotypes shared with other LNP localities. A mixing pattern of the different genetic groups was evident using the microsatellite markers. The chronology of the vicariance events in LNP may indicate that the partition process of the Orestias populations was gradual. Considering this, and in view of the genetic results, we may conclude that the morphospecies from LNP are populations in ongoing

  15. Temporal lobe epilepsy subtypes, differential patterns of cerebral perfusion on ictal SPECT

    NARCIS (Netherlands)

    Ho, SS; Berkovic, SF; McKay, WJ; Kalnins, RM; Bladin, PF

    Purpose: We studied cerebral perfusion patterns in the various subtypes of TLE, as determined by pathology and good outcome after temporal lobectomy (as confirmation of temporal origin). Methods: We studied clinical features and ictal technetium 99m hexamethyl-propyleneamineoxime (Tc-99m-HMPAO)

  16. A Generalized National Planning Approach for Admission Capacity in Higher Education: A Nonlinear Integer Goal Programming Model with a Novel Differential Evolution Algorithm.

    Science.gov (United States)

    El-Qulity, Said Ali; Mohamed, Ali Wagdy

    2016-01-01

    This paper proposes a nonlinear integer goal programming model (NIGPM) for solving the general problem of admission capacity planning in a country as a whole. The work aims to satisfy most of the required key objectives of a country related to the enrollment problem for higher education. The system general outlines are developed along with the solution methodology for application to the time horizon in a given plan. The up-to-date data for Saudi Arabia is used as a case study and a novel evolutionary algorithm based on modified differential evolution (DE) algorithm is used to solve the complexity of the NIGPM generated for different goal priorities. The experimental results presented in this paper show their effectiveness in solving the admission capacity for higher education in terms of final solution quality and robustness.

  17. Differential Gene Expression Patterns in Chicken Cardiomyocytes during Hydrogen Peroxide-Induced Apoptosis.

    Science.gov (United States)

    Wan, Chunyun; Xiang, Jinmei; Li, Youwen; Guo, Dingzong

    2016-01-01

    Hydrogen peroxide (H2O2) is both an exogenous and endogenous cytotoxic agent that can reliably induce apoptosis in numerous cell types for studies on apoptosis signaling pathways. However, little is known of these apoptotic processes in myocardial cells of chicken, a species prone to progressive heart failure. Sequencing of mRNA transcripts (RNA-Seq) allows for the identification of differentially expressed genes under various physiological and pathological conditions to elucidate the molecular pathways involved, including cellular responses to exogenous and endogenous toxins. We used RNA-seq to examine genes differentially expressed during H2O2-induced apoptosis in primary cultures of embryonic chicken cardiomyocytes. Following control or H2O2 treatment, RNA was extracted and sequencing performed to identify novel transcripts up- or downregulated in the H2O2 treatment group and construct protein-protein interaction networks. Of the 19,268 known and 2,160 novel transcripts identified in both control and H2O2 treatment groups, 4,650 showed significant differential expression. Among them, 55.63% were upregulated and 44.37% downregulated. Initiation of apoptosis by H2O2 was associated with upregulation of caspase-8, caspase-9, and caspase-3, and downregulation of anti-apoptotic genes API5 and TRIA1. Many other differentially expressed genes were associated with metabolic pathways (including 'Fatty acid metabolism', 'Alanine, aspartate, and glutamate metabolism', and 'Biosynthesis of unsaturated fatty acids') and cell signaling pathways (including 'PPAR signaling pathway', 'Adipocytokine signaling pathway', 'TGF-beta signaling pathway', 'MAPK signaling pathway', and 'p53 signaling pathway'). In chicken cardiomyocytes, H2O2 alters the expression of numerous genes linked to cell signaling and metabolism as well as genes directly associated with apoptosis. In particular, H2O2 also affects the biosynthesis and processing of proteins and unsaturated fatty acids. These

  18. Re-visioning local biologies: HIV-2 and the pattern of differential valuation in biomedical research.

    Science.gov (United States)

    Gilbert, Hannah

    2013-01-01

    The discovery of HIV-2, a distinctly West African variant of HIV, is often portrayed as the result of a straightforward, if serendipitous, error. This article reframes the history of how HIV-2 came to be a knowable scientific identity. Relying on narratives from an African laboratory and clinic, it suggests that the rise and fall of HIV-2 as a viable research entity is indicative of a differential visibility and valuation of both human bodies and viruses. Understanding how HIV-2 emerged as a local biology reveals the complex set of relations that contemporary African scientists face in navigating local moral economies and the mercurial politics of the contemporary global health industry.

  19. Does Violence in Adolescence Differentially Predict Offending Patterns in Early Adulthood?

    Science.gov (United States)

    Cardwell, Stephanie M; Piquero, Alex R

    2018-05-01

    Previous research is mixed on whether the commission of a violent offense in adolescence is predictive of criminal career characteristics. In the current study, we addressed the following: (a) What factors predict the commission of serious violence in mid-adolescence? and (b) Does involvement in serious violence in mid-adolescence lead to more chronic and/or more heterogeneous patterns of offending in early adulthood? Data were obtained from the Pathways to Desistance Study, a longitudinal study of serious adolescent offenders in Philadelphia, Pennsylvania, and Phoenix, Arizona. Prior arrests, violence exposure, and gang involvement distinguished adolescents who engaged in violence at baseline. A violent offense at baseline was not predictive of a higher frequency of rearrests but was associated with membership in the low offending trajectory. In conclusion, violent offending in adolescence might be a poor predictor of chronic and heterogeneous patterns of offending throughout the life course.

  20. Patterns of genetic differentiation at MHC class I genes and microsatellites identify conservation units in the giant panda.

    Science.gov (United States)

    Zhu, Ying; Wan, Qiu-Hong; Yu, Bin; Ge, Yun-Fa; Fang, Sheng-Guo

    2013-10-22

    Evaluating patterns of genetic variation is important to identify conservation units (i.e., evolutionarily significant units [ESUs], management units [MUs], and adaptive units [AUs]) in endangered species. While neutral markers could be used to infer population history, their application in the estimation of adaptive variation is limited. The capacity to adapt to various environments is vital for the long-term survival of endangered species. Hence, analysis of adaptive loci, such as the major histocompatibility complex (MHC) genes, is critical for conservation genetics studies. Here, we investigated 4 classical MHC class I genes (Aime-C, Aime-F, Aime-I, and Aime-L) and 8 microsatellites to infer patterns of genetic variation in the giant panda (Ailuropoda melanoleuca) and to further define conservation units. Overall, we identified 24 haplotypes (9 for Aime-C, 1 for Aime-F, 7 for Aime-I, and 7 for Aime-L) from 218 individuals obtained from 6 populations of giant panda. We found that the Xiaoxiangling population had the highest genetic variation at microsatellites among the 6 giant panda populations and higher genetic variation at Aime-MHC class I genes than other larger populations (Qinling, Qionglai, and Minshan populations). Differentiation index (FST)-based phylogenetic and Bayesian clustering analyses for Aime-MHC-I and microsatellite loci both supported that most populations were highly differentiated. The Qinling population was the most genetically differentiated. The giant panda showed a relatively higher level of genetic diversity at MHC class I genes compared with endangered felids. Using all of the loci, we found that the 6 giant panda populations fell into 2 ESUs: Qinling and non-Qinling populations. We defined 3 MUs based on microsatellites: Qinling, Minshan-Qionglai, and Daxiangling-Xiaoxiangling-Liangshan. We also recommended 3 possible AUs based on MHC loci: Qinling, Minshan-Qionglai, and Daxiangling-Xiaoxiangling-Liangshan. Furthermore, we recommend

  1. Randomized and quantum algorithms for solving initial-value problems in ordinary differential equations of order k

    Directory of Open Access Journals (Sweden)

    Maciej Goćwin

    2008-01-01

    Full Text Available The complexity of initial-value problems is well studied for systems of equations of first order. In this paper, we study the \\(\\varepsilon\\-complexity for initial-value problems for scalar equations of higher order. We consider two models of computation, the randomized model and the quantum model. We construct almost optimal algorithms adjusted to scalar equations of higher order, without passing to systems of first order equations. The analysis of these algorithms allows us to establish upper complexity bounds. We also show (almost matching lower complexity bounds. The \\(\\varepsilon\\-complexity in the randomized and quantum setting depends on the regularity of the right-hand side function, but is independent of the order of equation. Comparing the obtained bounds with results known in the deterministic case, we see that randomized algorithms give us a speed-up by \\(1/2\\, and quantum algorithms by \\(1\\ in the exponent. Hence, the speed-up does not depend on the order of equation, and is the same as for the systems of equations of first order. We also include results of some numerical experiments which confirm theoretical results.

  2. Spatiotemporal patterns of High Mountain Asia's snowmelt season identified with an automated snowmelt detection algorithm, 1987-2016

    Science.gov (United States)

    Smith, Taylor; Bookhagen, Bodo; Rheinwalt, Aljoscha

    2017-10-01

    High Mountain Asia (HMA) - encompassing the Tibetan Plateau and surrounding mountain ranges - is the primary water source for much of Asia, serving more than a billion downstream users. Many catchments receive the majority of their yearly water budget in the form of snow, which is poorly monitored by sparse in situ weather networks. Both the timing and volume of snowmelt play critical roles in downstream water provision, as many applications - such as agriculture, drinking-water generation, and hydropower - rely on consistent and predictable snowmelt runoff. Here, we examine passive microwave data across HMA with five sensors (SSMI, SSMIS, AMSR-E, AMSR2, and GPM) from 1987 to 2016 to track the timing of the snowmelt season - defined here as the time between maximum passive microwave signal separation and snow clearance. We validated our method against climate model surface temperatures, optical remote-sensing snow-cover data, and a manual control dataset (n = 2100, 3 variables at 25 locations over 28 years); our algorithm is generally accurate within 3-5 days. Using the algorithm-generated snowmelt dates, we examine the spatiotemporal patterns of the snowmelt season across HMA. The climatically short (29-year) time series, along with complex interannual snowfall variations, makes determining trends in snowmelt dates at a single point difficult. We instead identify trends in snowmelt timing by using hierarchical clustering of the passive microwave data to determine trends in self-similar regions. We make the following four key observations. (1) The end of the snowmelt season is trending almost universally earlier in HMA (negative trends). Changes in the end of the snowmelt season are generally between 2 and 8 days decade-1 over the 29-year study period (5-25 days total). The length of the snowmelt season is thus shrinking in many, though not all, regions of HMA. Some areas exhibit later peak signal separation (positive trends), but with generally smaller magnitudes

  3. Spatiotemporal patterns of High Mountain Asia's snowmelt season identified with an automated snowmelt detection algorithm, 1987–2016

    Directory of Open Access Journals (Sweden)

    T. Smith

    2017-10-01

    Full Text Available High Mountain Asia (HMA – encompassing the Tibetan Plateau and surrounding mountain ranges – is the primary water source for much of Asia, serving more than a billion downstream users. Many catchments receive the majority of their yearly water budget in the form of snow, which is poorly monitored by sparse in situ weather networks. Both the timing and volume of snowmelt play critical roles in downstream water provision, as many applications – such as agriculture, drinking-water generation, and hydropower – rely on consistent and predictable snowmelt runoff. Here, we examine passive microwave data across HMA with five sensors (SSMI, SSMIS, AMSR-E, AMSR2, and GPM from 1987 to 2016 to track the timing of the snowmelt season – defined here as the time between maximum passive microwave signal separation and snow clearance. We validated our method against climate model surface temperatures, optical remote-sensing snow-cover data, and a manual control dataset (n = 2100, 3 variables at 25 locations over 28 years; our algorithm is generally accurate within 3–5 days. Using the algorithm-generated snowmelt dates, we examine the spatiotemporal patterns of the snowmelt season across HMA. The climatically short (29-year time series, along with complex interannual snowfall variations, makes determining trends in snowmelt dates at a single point difficult. We instead identify trends in snowmelt timing by using hierarchical clustering of the passive microwave data to determine trends in self-similar regions. We make the following four key observations. (1 The end of the snowmelt season is trending almost universally earlier in HMA (negative trends. Changes in the end of the snowmelt season are generally between 2 and 8 days decade−1 over the 29-year study period (5–25 days total. The length of the snowmelt season is thus shrinking in many, though not all, regions of HMA. Some areas exhibit later peak signal separation (positive

  4. Differential patterns of cortical activation as a function of fluid reasoning complexity.

    Science.gov (United States)

    Perfetti, Bernardo; Saggino, Aristide; Ferretti, Antonio; Caulo, Massimo; Romani, Gian Luca; Onofrj, Marco

    2009-02-01

    Fluid intelligence (gf) refers to abstract reasoning and problem solving abilities. It is considered a human higher cognitive factor central to general intelligence (g). The regions of the cortex supporting gf have been revealed by recent bioimaging studies and valuable hypothesis on the neural correlates of individual differences have been proposed. However, little is known about the interaction between individual variability in gf and variation in cortical activity following task complexity increase. To further investigate this, two samples of participants (high-IQ, N = 8; low-IQ, N = 10) with significant differences in gf underwent two reasoning (moderate and complex) tasks and a control task adapted from the Raven progressive matrices. Functional magnetic resonance was used and the recorded signal analyzed between and within the groups. The present study revealed two opposite patterns of neural activity variation which were probably a reflection of the overall differences in cognitive resource modulation: when complexity increased, high-IQ subjects showed a signal enhancement in some frontal and parietal regions, whereas low-IQ subjects revealed a decreased activity in the same areas. Moreover, a direct comparison between the groups' activation patterns revealed a greater neural activity in the low-IQ sample when conducting moderate task, with a strong involvement of medial and lateral frontal regions thus suggesting that the recruitment of executive functioning might be different between the groups. This study provides evidence for neural differences in facing reasoning complexity among subjects with different gf level that are mediated by specific patterns of activation of the underlying fronto-parietal network.

  5. Modeling the differentiation of A- and C-type baroreceptor firing patterns

    DEFF Research Database (Denmark)

    Sturdy, Jacob; Ottesen, Johnny T.; Olufsen, Mette

    2017-01-01

    The baroreceptor neurons serve as the primary transducers of blood pressure for the autonomic nervous system and are thus critical in enabling the body to respond effectively to changes in blood pressure. These neurons can be separated into two types (A and C) based on the myelination...... of their axons and their distinct firing patterns elicited in response to specific pressure stimuli. This study has developed a comprehensive model of the afferent baroreceptor discharge built on physiological knowledge of arterial wall mechanics, firing rate responses to controlled pressure stimuli, and ion...

  6. Identification of differential gene expression patterns in human arteries from patients with chronic kidney disease

    DEFF Research Database (Denmark)

    Stubbe, Jane; Skov, Vibe; Thiesson, Helle Charlotte

    2018-01-01

    BACKGROUND: Uremia accelerates atherosclerosis but little is known about affected pathways in human vasculature. This study aimed to identify differentially expressed arterial transcripts in patients with chronic kidney disease (CKD) Methods: Global mRNA expression was estimated by microarray...... hybridization in iliac arteries (n=14) from renal transplant recipients and compared with renal arteries from healthy living kidney donors (n=19) in study 1. Study 2 compared non-atherosclerotic internal mammary arteries (IMA) from five patients with elevated plasma creatinine levels and age and gender matched...... controls with normal levels. Western blotting and immunohistochemistry for selected proteins was performed on a subset of study 1 samples. RESULTS: 15 gene transcripts with fold changes (FC)>1.05 were significantly different between the two groups in study 1, with false discovery rates (FDR) of

  7. Temporal expression pattern of genes during the period of sex differentiation in human embryonic gonads

    DEFF Research Database (Denmark)

    Mamsen, Linn S; Ernst, Emil H; Borup, Rehannah

    2017-01-01

    The precise timing and sequence of changes in expression of key genes and proteins during human sex-differentiation and onset of steroidogenesis was evaluated by whole-genome expression in 67 first trimester human embryonic and fetal ovaries and testis and confirmed by qPCR and immunohistochemistry...... (IHC). SRY/SOX9 expression initiated in testis around day 40 pc, followed by initiation of AMH and steroidogenic genes required for androgen production at day 53 pc. In ovaries, gene expression of RSPO1, LIN28, FOXL2, WNT2B, and ETV5, were significantly higher than in testis, whereas GLI1...... was significantly higher in testis than ovaries. Gene expression was confirmed by IHC for GAGE, SOX9, AMH, CYP17A1, LIN28, WNT2B, ETV5 and GLI1. Gene expression was not associated with the maternal smoking habits. Collectively, a precise temporal determination of changes in expression of key genes involved in human...

  8. Differential DNA methylation patterns of polycystic ovarian syndrome in whole blood of Chinese women

    DEFF Research Database (Denmark)

    Li, Shuxia; Zhu, Dongyi; Duan, Hongmei

    2017-01-01

    As a universally common endocrinopathy in women of reproductive age, the polycystic ovarian syndrome is characterized by composite clinical phenotypes reflecting the contributions of reproductive impact of ovarian dysfunction and metabolic abnormalities with widely varying symptoms resulting from...... interference of the genome with the environment through integrative biological mechanisms including epigenetics. We have performed a genome-wide DNA methylation analysis on polycystic ovarian syndrome and identified a substantial number of genomic sites differentially methylated in the whole blood of PCOS...... in the DNA methylome from ovarian tissue under PCOS condition. Most importantly, our genome-wide profiling focusing on PCOS patients revealed a large number of DNA methylation sites and their enriched functional pathways significantly associated with diverse clinical features (levels of prolactin, estradiol...

  9. Differential DNA methylation patterns of polycystic ovarian syndrome in whole blood of Chinese women.

    Science.gov (United States)

    Li, Shuxia; Zhu, Dongyi; Duan, Hongmei; Ren, Anran; Glintborg, Dorte; Andersen, Marianne; Skov, Vibe; Thomassen, Mads; Kruse, Torben; Tan, Qihua

    2017-03-28

    As a universally common endocrinopathy in women of reproductive age, the polycystic ovarian syndrome is characterized by composite clinical phenotypes reflecting the contributions of reproductive impact of ovarian dysfunction and metabolic abnormalities with widely varying symptoms resulting from interference of the genome with the environment through integrative biological mechanisms including epigenetics. We have performed a genome-wide DNA methylation analysis on polycystic ovarian syndrome and identified a substantial number of genomic sites differentially methylated in the whole blood of PCOS patients and healthy controls (52 sites, false discovery rate ovarian tissue under PCOS condition. Most importantly, our genome-wide profiling focusing on PCOS patients revealed a large number of DNA methylation sites and their enriched functional pathways significantly associated with diverse clinical features (levels of prolactin, estradiol, progesterone and menstrual cycle) that could serve as novel molecular basis of the clinical heterogeneity observed in PCOS women.

  10. Leukoencephalopathy with swelling in children and adolescents: MRI patterns and differential diagnosis

    International Nuclear Information System (INIS)

    Knaap, M.S. van der; Valk, J.; Barth, P.G.; Smit, L.M.E.; Engelen, B.G.M. van; Tortori Donati, P.

    1995-01-01

    In children, several neurological disorders are characterised by spongiform leukoencephalopathy. MRI of the brain typically shows white matter swelling, but does not enable differentiation of the various underlying disorders. The aim of this article is optimisation of the diagnostic value of MRI in leukoencephalopathy accompanied by swelling. MRI-based inclusion criteria were met by 20 patients in our database. The images were analysed using a detailed scoring list. In 13 of the 20 patients the clinical diagnosis was known (11 definite and 2 probable diagnoses). Characteristic MRI abnormalities could be defined in these patients. Of the 7 patients without a diagnosis, 5 had identical MRI abnormalities: diffuse hemisphere swelling and typical cysts in frontoparietal subcortical white matter and the tips of the temporal lobes. The clinical picture was also similar in these patients, suggesting a similar disease. (orig.). With 10 figs., 2 tabs

  11. Differential Lectin Binding Patterns Identify Distinct Heart Regions in Giant Danio (Devario aequipinnatus) and Zebrafish (Danio rerio) Hearts

    Science.gov (United States)

    Manalo, Trina; May, Adam; Quinn, Joshua; Lafontant, Dominique S.; Shifatu, Olubusola; He, Wei; Gonzalez-Rosa, Juan M.; Burns, Geoffrey C.; Burns, Caroline E.; Burns, Alan R.; Lafontant, Pascal J.

    2016-01-01

    Lectins are carbohydrate-binding proteins commonly used as biochemical and histochemical tools to study glycoconjugate (glycoproteins, glycolipids) expression patterns in cells, tissues, including mammalian hearts. However, lectins have received little attention in zebrafish (Danio rerio) and giant danio (Devario aequipinnatus) heart studies. Here, we sought to determine the binding patterns of six commonly used lectins—wheat germ agglutinin (WGA), Ulex europaeus agglutinin, Bandeiraea simplicifolia lectin (BS lectin), concanavalin A (Con A), Ricinus communis agglutinin I (RCA I), and Lycopersicon esculentum agglutinin (tomato lectin)—in these hearts. Con A showed broad staining in the myocardium. WGA stained cardiac myocyte borders, with binding markedly stronger in the compact heart and bulbus. BS lectin, which stained giant danio coronaries, was used to measure vascular reconstruction during regeneration. However, BS lectin reacted poorly in zebrafish. RCA I stained the compact heart of both fish. Tomato lectin stained the giant danio, and while low reactivity was seen in the zebrafish ventricle, staining was observed in their transitional cardiac myocytes. In addition, we observed unique staining patterns in the developing zebrafish heart. Lectins’ ability to reveal differential glycoconjugate expression in giant danio and zebrafish hearts suggests they can serve as simple but important tools in studies of developing, adult, and regenerating fish hearts. PMID:27680670

  12. Differentiation of organic and non-organic winter wheat cultivars from a controlled field trial by crystallization patterns.

    Science.gov (United States)

    Kahl, Johannes; Busscher, Nicolaas; Mergardt, Gaby; Mäder, Paul; Torp, Torfinn; Ploeger, Angelika

    2015-01-01

    There is a need for authentication tools in order to verify the existing certification system. Recently, markers for analytical authentication of organic products were evaluated. Herein, crystallization with additives was described as an interesting fingerprint approach which needs further evidence, based on a standardized method and well-documented sample origin. The fingerprint of wheat cultivars from a controlled field trial is generated from structure analysis variables of crystal patterns. Method performance was tested on factors such as crystallization chamber, day of experiment and region of interest of the patterns. Two different organic treatments and two different treatments of the non-organic regime can be grouped together in each of three consecutive seasons. When the k-nearest-neighbor classification method was applied, approximately 84% of Runal samples and 95% of Titlis samples were classified correctly into organic and non-organic origin using cross-validation. Crystallization with additive offers an interesting complementary fingerprint method for organic wheat samples. When the method is applied to winter wheat from the DOK trial, organic and non-organic treated samples can be differentiated significantly based on pattern recognition. Therefore crystallization with additives seems to be a promising tool in organic wheat authentication. © 2014 Society of Chemical Industry.

  13. Differential patterns of prefrontal MEG activation during verbal & visual encoding and retrieval.

    Science.gov (United States)

    Prendergast, Garreth; Limbrick-Oldfield, Eve; Ingamells, Ed; Gathercole, Susan; Baddeley, Alan; Green, Gary G R

    2013-01-01

    The spatiotemporal profile of activation of the prefrontal cortex in verbal and non-verbal recognition memory was examined using magnetoencephalography (MEG). Sixteen neurologically healthy right-handed participants were scanned whilst carrying out a modified version of the Doors and People Test of recognition memory. A pattern of significant prefrontal activity was found for non-verbal and verbal encoding and recognition. During the encoding, verbal stimuli activated an area in the left ventromedial prefrontal cortex, and non-verbal stimuli activated an area in the right. A region in the left dorsolateral prefrontal cortex also showed significant activation during the encoding of non-verbal stimuli. Both verbal and non-verbal stimuli significantly activated an area in the right dorsomedial prefrontal cortex and the right anterior prefrontal cortex during successful recognition, however these areas showed temporally distinct activation dependent on material, with non-verbal showing activation earlier than verbal stimuli. Additionally, non-verbal material activated an area in the left anterior prefrontal cortex during recognition. These findings suggest a material-specific laterality in the ventromedial prefrontal cortex during encoding for verbal and non-verbal but also support the HERA model for verbal material. The discovery of two process dependent areas during recognition that showed patterns of temporal activation dependent on material demonstrates the need for the application of more temporally sensitive techniques to the involvement of the prefrontal cortex in recognition memory.

  14. Differential patterns of prefrontal MEG activation during verbal & visual encoding and retrieval.

    Directory of Open Access Journals (Sweden)

    Garreth Prendergast

    Full Text Available The spatiotemporal profile of activation of the prefrontal cortex in verbal and non-verbal recognition memory was examined using magnetoencephalography (MEG. Sixteen neurologically healthy right-handed participants were scanned whilst carrying out a modified version of the Doors and People Test of recognition memory. A pattern of significant prefrontal activity was found for non-verbal and verbal encoding and recognition. During the encoding, verbal stimuli activated an area in the left ventromedial prefrontal cortex, and non-verbal stimuli activated an area in the right. A region in the left dorsolateral prefrontal cortex also showed significant activation during the encoding of non-verbal stimuli. Both verbal and non-verbal stimuli significantly activated an area in the right dorsomedial prefrontal cortex and the right anterior prefrontal cortex during successful recognition, however these areas showed temporally distinct activation dependent on material, with non-verbal showing activation earlier than verbal stimuli. Additionally, non-verbal material activated an area in the left anterior prefrontal cortex during recognition. These findings suggest a material-specific laterality in the ventromedial prefrontal cortex during encoding for verbal and non-verbal but also support the HERA model for verbal material. The discovery of two process dependent areas during recognition that showed patterns of temporal activation dependent on material demonstrates the need for the application of more temporally sensitive techniques to the involvement of the prefrontal cortex in recognition memory.

  15. Differential patterns of implicit emotional processing in Alzheimer's disease and healthy aging.

    Science.gov (United States)

    García-Rodríguez, Beatriz; Fusari, Anna; Rodríguez, Beatriz; Hernández, José Martín Zurdo; Ellgring, Heiner

    2009-01-01

    Implicit memory for emotional facial expressions (EFEs) was investigated in young adults, healthy old adults, and mild Alzheimer's disease (AD) patients. Implicit memory is revealed by the effect of experience on performance by studying previously encoded versus novel stimuli, a phenomenon referred to as perceptual priming. The aim was to assess the changes in the patterns of priming as a function of aging and dementia. Participants identified EFEs taken from the Facial Action Coding System and the stimuli used represented the emotions of happiness, sadness, surprise, fear, anger, and disgust. In the study phase, participants rated the pleasantness of 36 faces using a Likert-type scale. Subsequently, the response to the 36 previously studied and 36 novel EFEs was tested when they were randomly presented in a cued naming task. The results showed that implicit memory for EFEs is preserved in AD and aging, and no specific age-related effects on implicit memory for EFEs were observed. However, different priming patterns were evident in AD patients that may reflect pathological brain damage and the effect of stimulus complexity. These findings provide evidence of how progressive neuropathological changes in the temporal and frontal areas may affect emotional processing in more advanced stages of the disease.

  16. Differential Activation Patterns of fMRI in Sleep-Deprived Brain: Restoring Effects of Acupuncture

    Directory of Open Access Journals (Sweden)

    Lei Gao

    2014-01-01

    Full Text Available Previous studies suggested a remediation role of acupuncture in insomnia, and acupuncture also has been used in insomnia empirically and clinically. In this study, we employed fMRI to test the role of acupuncture in sleep deprivation (SD. Sixteen healthy volunteers (8 males were recruited and scheduled for three fMRI scanning procedures, one following the individual’s normal sleep and received acupuncture SP6 (NOR group and the other two after 24 h of total SD with acupuncture on SP6 (SD group or sham (Sham group. The sessions were counterbalanced approximately two weeks apart. Acupuncture stimuli elicited significantly different activation patterns of three groups. In NOR group, the right superior temporal lobe, left inferior parietal lobule, and left postcentral gyrus were activated; in SD group, the anterior cingulate cortex, bilateral insula, left basal ganglia, and thalamus were significantly activated while, in Sham group, the bilateral thalamus and left cerebellum were activated. Different activation patterns suggest a unique role of acupuncture on SP6 in remediation of SD. SP6 elicits greater and anatomically different activations than those of sham stimuli; that is, the salience network, a unique interoceptive autonomic circuit, may indicate the mechanism underlying acupuncture in restoring sleep deprivation.

  17. Differential Diptera succession patterns onto partially burned and unburned pig carrion in southeastern Brazil

    Directory of Open Access Journals (Sweden)

    J Oliveira-Costa

    Full Text Available In the present contribution we compared the entomological succession pattern of a burned carcass with that of an unburned one. For that, we used domestic pig carcasses and focused on Calliphoridae, Muscidae and Sarcophagidae flies, because they are the ones most commonly used in Postmortem Interval estimates. Adult and immature flies were collected daily. A total of 27 species and 2,498 specimens were collected, 1,295 specimens of 26 species from the partially burned carcass and 1,203 specimens of 22 species from the control carcass (unburned. The species composition in the two samples differed, and the results of the similarity measures were 0.875 by Sorensen and 0.756 by Bray-Curtis index. The results obtained for both carcasses also differ with respect to the decomposition process, indicating that the post mortem interval would be underestimated if the entomological succession pattern observed for a carcass under normal conditions was applied to a carbonized carcass.

  18. Differential scaling patterns of vertebrae and the evolution of neck length in mammals.

    Science.gov (United States)

    Arnold, Patrick; Amson, Eli; Fischer, Martin S

    2017-06-01

    Almost all mammals have seven vertebrae in their cervical spines. This consistency represents one of the most prominent examples of morphological stasis in vertebrae evolution. Hence, the requirements associated with evolutionary modifications of neck length have to be met with a fixed number of vertebrae. It has not been clear whether body size influences the overall length of the cervical spine and its inner organization (i.e., if the mammalian neck is subject to allometry). Here, we provide the first large-scale analysis of the scaling patterns of the cervical spine and its constituting cervical vertebrae. Our findings reveal that the opposite allometric scaling of C1 and C2-C7 accommodate the increase of neck bending moment with body size. The internal organization of the neck skeleton exhibits surprisingly uniformity in the vast majority of mammals. Deviations from this general pattern only occur under extreme loading regimes associated with particular functional and allometric demands. Our results indicate that the main source of variation in the mammalian neck stems from the disparity of overall cervical spine length. The mammalian neck reveals how evolutionary disparity manifests itself in a structure that is otherwise highly restricted by meristic constraints. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

  19. An algorithm for the classification of mRNA patterns in eosinophilic esophagitis: Integration of machine learning.

    Science.gov (United States)

    Sallis, Benjamin F; Erkert, Lena; Moñino-Romero, Sherezade; Acar, Utkucan; Wu, Rina; Konnikova, Liza; Lexmond, Willem S; Hamilton, Matthew J; Dunn, W Augustine; Szepfalusi, Zsolt; Vanderhoof, Jon A; Snapper, Scott B; Turner, Jerrold R; Goldsmith, Jeffrey D; Spencer, Lisa A; Nurko, Samuel; Fiebiger, Edda

    2018-04-01

    Diagnostic evaluation of eosinophilic esophagitis (EoE) remains difficult, particularly the assessment of the patient's allergic status. This study sought to establish an automated medical algorithm to assist in the evaluation of EoE. Machine learning techniques were used to establish a diagnostic probability score for EoE, p(EoE), based on esophageal mRNA transcript patterns from biopsies of patients with EoE, gastroesophageal reflux disease and controls. Dimensionality reduction in the training set established weighted factors, which were confirmed by immunohistochemistry. Following weighted factor analysis, p(EoE) was determined by random forest classification. Accuracy was tested in an external test set, and predictive power was assessed with equivocal patients. Esophageal IgE production was quantified with epsilon germ line (IGHE) transcripts and correlated with serum IgE and the T h 2-type mRNA profile to establish an IGHE score for tissue allergy. In the primary analysis, a 3-class statistical model generated a p(EoE) score based on common characteristics of the inflammatory EoE profile. A p(EoE) ≥ 25 successfully identified EoE with high accuracy (sensitivity: 90.9%, specificity: 93.2%, area under the curve: 0.985) and improved diagnosis of equivocal cases by 84.6%. The p(EoE) changed in response to therapy. A secondary analysis loop in EoE patients defined an IGHE score of ≥37.5 for a patient subpopulation with increased esophageal allergic inflammation. The development of intelligent data analysis from a machine learning perspective provides exciting opportunities to improve diagnostic precision and improve patient care in EoE. The p(EoE) and the IGHE score are steps toward the development of decision trees to define EoE subpopulations and, consequently, will facilitate individualized therapy. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

  20. "Contrasting patterns of selection at Pinus pinaster Ait. Drought stress candidate genes as revealed by genetic differentiation analyses".

    Science.gov (United States)

    Eveno, Emmanuelle; Collada, Carmen; Guevara, M Angeles; Léger, Valérie; Soto, Alvaro; Díaz, Luis; Léger, Patrick; González-Martínez, Santiago C; Cervera, M Teresa; Plomion, Christophe; Garnier-Géré, Pauline H

    2008-02-01

    The importance of natural selection for shaping adaptive trait differentiation among natural populations of allogamous tree species has long been recognized. Determining the molecular basis of local adaptation remains largely unresolved, and the respective roles of selection and demography in shaping population structure are actively debated. Using a multilocus scan that aims to detect outliers from simulated neutral expectations, we analyzed patterns of nucleotide diversity and genetic differentiation at 11 polymorphic candidate genes for drought stress tolerance in phenotypically contrasted Pinus pinaster Ait. populations across its geographical range. We compared 3 coalescent-based methods: 2 frequentist-like, including 1 approach specifically developed for biallelic single nucleotide polymorphisms (SNPs) here and 1 Bayesian. Five genes showed outlier patterns that were robust across methods at the haplotype level for 2 of them. Two genes presented higher F(ST) values than expected (PR-AGP4 and erd3), suggesting that they could have been affected by the action of diversifying selection among populations. In contrast, 3 genes presented lower F(ST) values than expected (dhn-1, dhn2, and lp3-1), which could represent signatures of homogenizing selection among populations. A smaller proportion of outliers were detected at the SNP level suggesting the potential functional significance of particular combinations of sites in drought-response candidate genes. The Bayesian method appeared robust to low sample sizes, flexible to assumptions regarding migration rates, and powerful for detecting selection at the haplotype level, but the frequentist-like method adapted to SNPs was more efficient for the identification of outlier SNPs showing low differentiation. Population-specific effects estimated in the Bayesian method also revealed populations with lower immigration rates, which could have led to favorable situations for local adaptation. Outlier patterns are discussed

  1. Issues in developing parallel iterative algorithms for solving partial differential equations on a (transputer-based) distributed parallel computing system

    International Nuclear Information System (INIS)

    Rajagopalan, S.; Jethra, A.; Khare, A.N.; Ghodgaonkar, M.D.; Srivenkateshan, R.; Menon, S.V.G.

    1990-01-01

    Issues relating to implementing iterative procedures, for numerical solution of elliptic partial differential equations, on a distributed parallel computing system are discussed. Preliminary investigations show that a speed-up of about 3.85 is achievable on a four transputer pipeline network. (author). 2 figs., 3 a ppendixes., 7 refs

  2. Electromyographic Pattern during Gait Initiation Differentiates Yoga Practitioners among Physically Active Older Subjects

    Directory of Open Access Journals (Sweden)

    Thierry Lelard

    2017-06-01

    Full Text Available During gait initiation, postural adjustments are needed to deal with balance and movement. With aging, gait initiation changes and reflects functional degradation of frailty individuals. However, physical activities have demonstrated beneficial effects of daily motor tasks. The aim of our study was to compare center of pressure (COP displacement and ankle muscle co-activation during gait initiation in two physically active groups: a group of walkers (n = 12; mean age ± SD 72.6 ± 3.2 years and a yoga group (n = 11; 71.5 ± 3.8 years. COP trajectory and electromyography of leg muscles were recorded simultaneously during five successive trials of gait initiation. Our main finding was that yoga practitioners had slower COP displacements (p < 0.01 and lower leg muscles % of coactivation (p < 0.01 in comparison with walkers. These parameters which characterized gait initiation control were correlated (r = 0.76; p < 0.01. Our results emphasize that lengthy ankle muscle co-activation and COP path in gait initiation differentiate yoga practitioners among physically active subjects.

  3. Differential patterns of contextual organization of memory in first-episode psychosis.

    Science.gov (United States)

    Murty, Vishnu P; McKinney, Rachel A; DuBrow, Sarah; Jalbrzikowski, Maria; Haas, Gretchen L; Luna, Beatriz

    2018-02-15

    Contextual information is used to support and organize episodic memory. Prior research has reliably shown memory deficits in psychosis; however, little research has characterized how this population uses contextual information during memory recall. We employed an approach founded in a computational framework of free recall to quantify how individuals with first episode of psychosis (FEP, N = 97) and controls (CON, N = 55) use temporal and semantic context to organize memory recall. Free recall was characterized using the Hopkins Verbal Learning Test-Revised (HVLT-R). We compared FEP and CON on three measures of free recall: proportion recalled, temporal clustering, and semantic clustering. Measures of temporal/semantic clustering quantified how individuals use contextual information to organize memory recall. We also assessed to what extent these measures relate to antipsychotic use and differentiated between different types of psychosis. We also explored the relationship between these measures and intelligence. In comparison to CON, FEP had reduced recall and less temporal clustering during free recall (p contextual organization of memory. IQ was related to free recall accuracy, but not the use of contextual information during recall in either group (p < 0.05, Bonferroni-corrected). These results show that in addition to deficits in memory recall, FEP differed in how they organize memories compared to CON.

  4. IDH1-associated primary glioblastoma in young adults displays differential patterns of tumour and vascular morphology.

    Directory of Open Access Journals (Sweden)

    Sergey Popov

    Full Text Available Glioblastoma is a highly aggressive tumour with marked heterogeneity at the morphological level in both the tumour cells and the associated highly prominent vasculature. As we begin to develop an increased biological insight into the underlying processes driving the disease, fewer attempts have thus far been made to understand these phenotypic differences. We sought to address this by carefully assessing the morphological characteristics of both the tumour cells and the associated vasculature, relating these observations to the IDH1/MGMT status, with a particular focus on the early onset population of young adults who develop primary glioblastoma. 276 primary glioblastoma specimens were classified into their predominant cell morphological type (fibrillary, gemistocytic, giant cell, small cell, oligodendroglial, sarcomatous, and assessed for specific tumour (cellularity, necrosis, palisades and vascular features (glomeruloid structures, arcades, pericyte proliferation. IDH1 positive glioblastomas were associated with a younger age at diagnosis, better clinical outcome, prominent oligodendroglial and small cell tumour cell morphology, pallisading necrosis and glomeruloid vascular proliferation in the absence of arcade-like structures. These features widen the phenotype of IDH1 mutation-positive primary glioblastoma in young adults and provide correlative evidence for a functional role of mutant IDH1 in the differential nature of neo-angiogenesis in different subtypes of glioblastoma.

  5. Multiplex protein pattern unmixing using a non-linear variable-weighted support vector machine as optimized by a particle swarm optimization algorithm.

    Science.gov (United States)

    Yang, Qin; Zou, Hong-Yan; Zhang, Yan; Tang, Li-Juan; Shen, Guo-Li; Jiang, Jian-Hui; Yu, Ru-Qin

    2016-01-15

    Most of the proteins locate more than one organelle in a cell. Unmixing the localization patterns of proteins is critical for understanding the protein functions and other vital cellular processes. Herein, non-linear machine learning technique is proposed for the first time upon protein pattern unmixing. Variable-weighted support vector machine (VW-SVM) is a demonstrated robust modeling technique with flexible and rational variable selection. As optimized by a global stochastic optimization technique, particle swarm optimization (PSO) algorithm, it makes VW-SVM to be an adaptive parameter-free method for automated unmixing of protein subcellular patterns. Results obtained by pattern unmixing of a set of fluorescence microscope images of cells indicate VW-SVM as optimized by PSO is able to extract useful pattern features by optimally rescaling each variable for non-linear SVM modeling, consequently leading to improved performances in multiplex protein pattern unmixing compared with conventional SVM and other exiting pattern unmixing methods. Copyright © 2015 Elsevier B.V. All rights reserved.

  6. Patterns of accentuated grey-white differentiation on diffusion-weighted imaging or the apparent diffusion coefficient maps in comatose survivors after global brain injury

    International Nuclear Information System (INIS)

    Kim, E.; Sohn, C.-H.; Chang, K.-H.; Chang, H.-W.; Lee, D.H.

    2011-01-01

    Aim: To determine what disease entities show accentuated grey-white differentiation of the cerebral hemisphere on diffusion-weighted images (DWI) or apparent diffusion coefficient (ADC) maps, and whether there is a correlation between the different patterns and the cause of the brain injury. Methods and materials: The DWI and ADC maps of 19 patients with global brain injury were reviewed and evaluated to investigate whether there was a correlation between the different patterns seen on the DWI and ADC maps and the cause of global brain injury. The ADC values were measured for quantitative analysis. Results: There were three different patterns of ADC decrease: a predominant ADC decrease in only the cerebral cortex (n = 8; pattern I); an ADC decrease in both the cerebral cortex and white matter (WM) and a predominant decrease in the WM (n = 9; pattern II); and a predominant ADC decrease in only the WM (n = 3; pattern III). Conclusion: Pattern I is cerebral cortical injury, suggesting cortical laminar necrosis in hypoxic brain injury. Pattern II is cerebral cortical and WM injury, frequently seen in brain death, while pattern 3 is mainly WM injury, especially found in hypoglycaemic brain injury. It is likely that pattern I is decorticate injury and pattern II is decerebrate injury in hypoxic ischaemic encephalopathy.Patterns I and II are found in severe hypoxic brain injury, and pattern II is frequently shown in brain death, whereas pattern III was found in severe hypoglycaemic injury.

  7. Differential bioaccumulation patterns of nanosized and dissolved silver in a land snail Achatina fulica.

    Science.gov (United States)

    Chen, Yuanzhen; Si, Youbin; Zhou, Dongmei; Dang, Fei

    2017-03-01

    With the increasing application in antimicrobial products, silver nanoparticles (AgNP) are inevitably released into the terrestrial environment, and pose potential risks to invertebrates such as land snails Achatina fulica, which take up AgNP from food and water. Here we differentiate Ag uptake biodynamic between Ag forms (i.e., PVP-AgNP vs. AgNO 3 ) and between exposure pathways. Snails assimilated Ag efficiently from lettuce leaves pre-exposed to AgNP, with assimilation efficiencies (AEs) averaging 62-85% and food ingestion rates of 0.11 ± 0.03 g g -1  d -1 . Dietary Ag bioavailability was independent on Ag forms, as revealed by comparable AEs between AgNP and AgNO 3 . However, the uptake rate constant from water was much lower for AgNP relative to AgNO 3 (2 × 10 -4 vs. 0.12 L g -1  d -1 ). The elimination rate constants were 0.0093 ± 0.0037 d -1 for AgNP and 0.019 ± 0.0077 d -1 for AgNO 3 . Biodynamic modeling further showed that dietary exposure was the dominant uptake pathway for AgNP in most circumstances, while for AgNO 3 the relative importance of waterborne and dietary exposure depended on Ag concentrations in food and water. Our findings highlight the importance of dietary uptake of AgNP during bioaccumulation, which should be considered in the risk assessment of these nanoparticles. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Differential pattern of deposition of nanoparticles in the airways of exposed workers

    Energy Technology Data Exchange (ETDEWEB)

    Fireman, Elizabeth, E-mail: fireman@tlvmc.gov.il [Tel Aviv University, Laboratory of Pulmonary and Allergic Diseases (Israel); Edelheit, Rinat [Tel Aviv University, Department of Occupational and Environmental Health School of Public Health, Sackler Faculty of Medicine (Israel); Stark, Moshe [Tel Aviv University, Laboratory of Pulmonary and Allergic Diseases (Israel); Shai, Amir Bar [Tel Aviv University, Pulmonology Department, Tel-Aviv Sourasky Medical Center affiliated to the Sackler Faculty of Medicine (Israel)

    2017-02-15

    Ultrafine particles (UFP) have been postulated to significantly contribute to the adverse health effects associated with exposure to particulate matter (PM). Due to their extremely small size (aerodynamic diameter <100 nm), UFP are able to deposit deep within the lung after inhalation and evade many mechanisms responsible for the clearance of larger particles. There is a lack of biologically relevant personal exposure metrics for exposure to occupational- and environmental-related micro- and nano-sized PM. The aim of the present study is to assess UFP in induced sputum (IS) and exhaled breath condensate (EBC) as possible biomarkers for assessing lung function impairment. Sputum induction and EBC testing were performed by conventional methods. UFP particles were assessed with the NanoSight LM20 (NanoSight Ltd, London, UK). The subjects included 35 exposed and 25 non-exposed workers. There were no group differences in pulmonary function test results and differential cell counts, but 63.6% of the exposed subjects had a higher percentage of neutrophils (OR3.28 p = 0.03) compared to the non-exposed subjects. The exposed subjects had higher percentages of UFP between 10 and 50 nm (69.45 ± 18.70 vs 60.11 ± 17.52 for the non-exposed group, p = 0.004). No differences were found in the IS samples. Years of exposure correlated positively to UFP content (r = 0.342 p = 0.01) and macrophage content (r = −0.327 p = 0.03). The percentage of small fraction of UFP in EBC, but not IS, is higher in exposed workers, and EBC may be a sensitive biomarker to assess exposure to nanoparticles.

  9. Treatment patterns, health state, and health care resource utilization of patients with radioactive iodine refractory differentiated thyroid cancer

    International Nuclear Information System (INIS)

    Gianoukakis, Andrew G; Flores, Natalia M; Pelletier, Corey L; Forsythe, Anna; Wolfe, Gregory R; Taylor, Matthew H

    2016-01-01

    Patients with differentiated thyroid cancer (DTC) often respond well to treatment but some become refractory to radioactive iodine (RAI) treatment, and treatment options are limited. Despite the humanistic and economic burden RAI refractory disease imposes on patients, published research concerning treatment patterns and health care resource utilization is sparse. Data were collected from an online retrospective chart review study in the US and five European Union (EU) countries (France, Germany, Italy, Spain, and UK) with physicians recruited from an online panel. Physicians (N=211) provided demographics, disease history, treatment information, and health care resource utilization for one to four of their patients with radioactive iodine refractory differentiated thyroid cancer (RR-DTC). The majority of the patients with RR-DTC (N=623) were female (56%), and their mean age was 58.2 years. In this sample, 63.2% had papillary thyroid cancer and 57.0% were in Stage IV when deemed RAI refractory. Patients with RR-DTC experienced regional recurrence in the thyroid bed/central neck area (25.3%) and had distant metastatic disease (53.6%). At the time data were collected, 50.7% were receiving systemic treatment. Of those, 78.5% were on first-line treatment and 62.7% were receiving multikinase inhibitors. Regional differences for prescribed treatments were observed; the US was more likely to have patients receiving multikinase inhibitors (79.2%) compared with UK (41.2%) and Italy (17.1%). Additional details regarding treatment patterns and resource utilization are discussed. The current study aimed to obtain a greater understanding of RR-DTC treatment globally. These results can assist in the development and implementation of treatment guidelines and ultimately enhance the care of patients with RR-DTC

  10. Differential expression patterns of metastasis suppressor proteins in basal cell carcinoma.

    Science.gov (United States)

    Bozdogan, Onder; Yulug, Isik G; Vargel, Ibrahim; Cavusoglu, Tarik; Karabulut, Ayse A; Karahan, Gurbet; Sayar, Nilufer

    2015-08-01

    Basal cell carcinomas (BCCs) are common malignant skin tumors. Despite having a significant invasion capacity, they metastasize only rarely. Our aim in this study was to detect the expression patterns of the NM23-H1, NDRG1, E-cadherin, RHOGDI2, CD82/KAI1, MKK4, and AKAP12 metastasis suppressor proteins in BCCs. A total of 96 BCC and 10 normal skin samples were included for the immunohistochemical study. Eleven frozen BCC samples were also studied by quantitative real time polymerase chain reaction (qRT-PCR) to detect the gene expression profile. NM23-H1 was strongly and diffusely expressed in all types of BCC. Significant cytoplasmic expression of NDRG1 and E-cadherin was also detected. However, AKAP12 and CD82/KAI1 expression was significantly decreased. The expressions of the other proteins were somewhere between the two extremes. Similarly, qRT-PCR analysis showed down-regulation of AKAP12 and up-regulation of NM23-H1 and NDRG1 in BCC. Morphologically aggressive BCCs showed significantly higher cytoplasmic NDRG1 expression scores and lower CD82/KAI1 scores than non-aggressive BCCs. The relatively preserved levels of NM23-H1, NDRG1, and E-cadherin proteins may have a positive effect on the non-metastasizing features of these tumors. © 2014 The International Society of Dermatology.

  11. Differential evolution of members of the rhomboid gene family with conservative and divergent patterns.

    Science.gov (United States)

    Li, Qi; Zhang, Ning; Zhang, Liangsheng; Ma, Hong

    2015-04-01

    Rhomboid proteins are intramembrane serine proteases that are involved in a plethora of biological functions, but the evolutionary history of the rhomboid gene family is not clear. We performed a comprehensive molecular evolutionary analysis of the rhomboid gene family and also investigated the organization and sequence features of plant rhomboids in different subfamilies. Our results showed that eukaryotic rhomboids could be divided into five subfamilies (RhoA-RhoD and PARL). Most orthology groups appeared to be conserved only as single or low-copy genes in all lineages in RhoB-RhoD and PARL, whereas RhoA genes underwent several duplication events, resulting in multiple gene copies. These duplication events were due to whole genome duplications in plants and animals and the duplicates might have experienced functional divergence. We also identified a novel group of plant rhomboid (RhoB1) that might have lost their enzymatic activity; their existence suggests that they might have evolved new mechanisms. Plant and animal rhomboids have similar evolutionary patterns. In addition, there are mutations affecting key active sites in RBL8, RBL9 and one of the Brassicaceae PARL duplicates. This study delineates a possible evolutionary scheme for intramembrane proteins and illustrates distinct fates and a mechanism of evolution of gene duplicates. © 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.

  12. Distinct spinning patterns gain differentiated loading tolerance of silk thread anchorages in spiders with different ecology.

    Science.gov (United States)

    Wolff, Jonas O; van der Meijden, Arie; Herberstein, Marie E

    2017-07-26

    Building behaviour in animals extends biological functions beyond bodies. Many studies have emphasized the role of behavioural programmes, physiology and extrinsic factors for the structure and function of buildings. Structure attachments associated with animal constructions offer yet unrealized research opportunities. Spiders build a variety of one- to three-dimensional structures from silk fibres. The evolution of economic web shapes as a key for ecological success in spiders has been related to the emergence of high performance silks and thread coating glues. However, the role of thread anchorages has been widely neglected in those models. Here, we show that orb-web (Araneidae) and hunting spiders (Sparassidae) use different silk application patterns that determine the structure and robustness of the joint in silk thread anchorages. Silk anchorages of orb-web spiders show a greater robustness against different loading situations, whereas the silk anchorages of hunting spiders have their highest pull-off resistance when loaded parallel to the substrate along the direction of dragline spinning. This suggests that the behavioural 'printing' of silk into attachment discs along with spinneret morphology was a prerequisite for the evolution of extended silk use in a three-dimensional space. This highlights the ecological role of attachments in the evolution of animal architectures. © 2017 The Author(s).

  13. Differential patterns of Batrachochytrium dendrobatidis infection in relict amphibian populations following severe disease-associated declines.

    Science.gov (United States)

    Whitfield, Steven M; Alvarado, Gilbert; Abarca, Juan; Zumbado, Hector; Zuñiga, Ibrahim; Wainwright, Mark; Kerby, Jacob

    2017-09-20

    Global amphibian biodiversity has declined dramatically in the past 4 decades, and many amphibian species have declined to near extinction as a result of emergence of the amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd). However, persistent or recovering populations of several amphibian species have recently been rediscovered, and such populations may illustrate how amphibian species that are highly susceptible to chytridiomycosis may survive in the presence of Bd. We conducted field surveys for Bd infection in 7 species of Costa Rican amphibians (all species that have declined to near extinction but for which isolated populations persist) to characterize infection profiles in highly Bd-susceptible amphibians post-decline. We found highly variable patterns in infection, with some species showing low prevalence (~10%) and low infection intensity and others showing high infection prevalence (>80%) and either low or high infection intensity. Across sites, infection rates were negatively associated with mean annual precipitation, and infection intensity across sites was negatively associated with mean average temperatures. Our results illustrate that even the most Bd-susceptible amphibians can persist in Bd-enzootic ecosystems, and that multiple ecological or evolutionary mechanisms likely exist for host-pathogen co-existence between Bd and the most Bd-susceptible amphibian species. Continued monitoring of these populations is necessary to evaluate population trends (continuing decline, stability, or population growth). These results should inform efforts to mitigate impacts of Bd on amphibians in the field.

  14. Utility of K-Means clustering algorithm in differentiating apparent diffusion coefficient values between benign and malignant neck pathologies

    Science.gov (United States)

    Srinivasan, A.; Galbán, C.J.; Johnson, T.D.; Chenevert, T.L.; Ross, B.D.; Mukherji, S.K.

    2014-01-01

    Purpose The objective of our study was to analyze the differences between apparent diffusion coefficient (ADC) partitions (created using the K-Means algorithm) between benign and malignant neck lesions and evaluate its benefit in distinguishing these entities. Material and methods MRI studies of 10 benign and 10 malignant proven neck pathologies were post-processed on a PC using in-house software developed in MATLAB (The MathWorks, Inc., Natick, MA). Lesions were manually contoured by two neuroradiologists with the ADC values within each lesion clustered into two (low ADC-ADCL, high ADC-ADCH) and three partitions (ADCL, intermediate ADC-ADCI, ADCH) using the K-Means clustering algorithm. An unpaired two-tailed Student’s t-test was performed for all metrics to determine statistical differences in the means between the benign and malignant pathologies. Results Statistically significant difference between the mean ADCL clusters in benign and malignant pathologies was seen in the 3 cluster models of both readers (p=0.03, 0.022 respectively) and the 2 cluster model of reader 2 (p=0.04) with the other metrics (ADCH, ADCI, whole lesion mean ADC) not revealing any significant differences. Receiver operating characteristics curves demonstrated the quantitative difference in mean ADCH and ADCL in both the 2 and 3 cluster models to be predictive of malignancy (2 clusters: p=0.008, area under curve=0.850, 3 clusters: p=0.01, area under curve=0.825). Conclusion The K-Means clustering algorithm that generates partitions of large datasets may provide a better characterization of neck pathologies and may be of additional benefit in distinguishing benign and malignant neck pathologies compared to whole lesion mean ADC alone. PMID:20007723

  15. Admixture patterns and genetic differentiation in negrito groups from West Malaysia estimated from genome-wide SNP data.

    Science.gov (United States)

    Jinam, Timothy A; Phipps, Maude E; Saitou, Naruya

    2013-01-01

    Southeast Asia houses various culturally and linguistically diverse ethnic groups. In Malaysia, where the Malay, Chinese, and Indian ethnic groups form the majority, there exist minority groups such as the "negritos" who are believed to be descendants of the earliest settlers of Southeast Asia. Here we report patterns of genetic substructure and admixture in two Malaysian negrito populations (Jehai and Kensiu), using ~50,000 genome-wide single-nucleotide polymorphism (SNP) data. We found traces of recent admixture in both the negrito populations, particularly in the Jehai, with the Malay through principal component analysis and STRUCTURE analysis software, which suggested that the admixture was as recent as one generation ago. We also identified significantly differentiated nonsynonymous SNPs and haplotype blocks related to intracellular transport, metabolic processes, and detection of stimulus. These results highlight the different levels of admixture experienced by the two Malaysian negritos. Delineating admixture and differentiated genomic regions should be of importance in designing and interpretation of molecular anthropology and disease association studies. Copyright © 2013 Wayne State University Press, Detroit, Michigan 48201-1309.

  16. Differential distribution patterns in cerebellar irrigation. A study with autopsy material

    Directory of Open Access Journals (Sweden)

    Hernando Yesid Estupiñan

    2018-02-01

    Full Text Available Aim: The aim of this investigation was characterize morphologically the cerebellar artery and its branches in a specimen of autopsy material. Methods: This descriptive cross-sectional study evaluated the anatomical characteristics of the cerebellar arteries and their branches in 93 brain stem and cerebellum blocks obtained from fresh cadavers. The specimens were perfused bilaterally channeling the proximal segments of the internal carotid and vertebral arteries with a semi-synthetic resin (Palatal GP40L 85%; styrene 15% impregnated with mineral red dye. We evaluated the distribution patterns of the cerebellar artery and its branches. Results: The calibers of the superior cerebellar artery (SCA, anterior inferior cerebellar artery (AICA and posterior inferior cerebellar artery (PICA were 1.46 ± 0.2 mm, 1.02 ± 0.35 mm and 1.45 ± 0.37 mm, respectively. Agenesis of the SCA was observed in six specimens (3.2%, AICA in 30 (16.1%, and PICA in 14 (7.5% specimens. Usual irrigation was observed in 44 (47.3% cerebellar blocks, whereas 49 (52.7% specimens showed irrigation variants, 23 (46.9% of which appeared bilaterally. The dominant distribution of the cerebellar arteries corresponded to SCA in 9 (12.5% cases, AICA in 46 (63.9% and PICA in 7 (9.7% specimens; shared dominance was found in 10 (13.9% specimens. Conclusion: The high variability of the cerebellar arteries observed in the present study is consistent with previous reports. The diverse anatomic expressions of the cerebellar arteries were typified in relation to their dominance and territories irrigated, useful for the diagnosis and clinical-surgical management of the cerebellum blood supply.

  17. Hybrid Adaptive Multilevel Monte Carlo Algorithm for Non-Smooth Observables of Itô Stochastic Differential Equations

    KAUST Repository

    Rached, Nadhir B.

    2014-01-06

    A new hybrid adaptive MC forward Euler algorithm for SDEs with singular coefficients and non-smooth observables is developed. This adaptive method is based on the derivation of a new error expansion with computable leading order terms. When a non-smooth binary payoff is considered, the new adaptive method achieves the same complexity as the uniform discretization with smooth problems. Moreover, the new developed algorithm is extended to the multilevel Monte Carlo (MLMC) forward Euler setting which reduces the complexity from O(TOL-3) to O(TOL-2(log(TOL))2). For the binary option case, it recovers the standard multilevel computational cost O(TOL-2(log(TOL))2). When considering a higher order Milstein scheme, a similar complexity result was obtained by Giles using the uniform time stepping for one dimensional SDEs, see [2]. The difficulty to extend Giles’ Milstein MLMC method to the multidimensional case is an argument for the flexibility of our new constructed adaptive MLMC forward Euler method which can be easily adapted to this setting. Similarly, the expected complexity O(TOL-2(log(TOL))2) is reached for the multidimensional case and verified numerically.

  18. Hybrid Adaptive Multilevel Monte Carlo Algorithm for Non-Smooth Observables of Itô Stochastic Differential Equations

    KAUST Repository

    Rached, Nadhir B.; Hoel, Haakon; Tempone, Raul

    2014-01-01

    A new hybrid adaptive MC forward Euler algorithm for SDEs with singular coefficients and non-smooth observables is developed. This adaptive method is based on the derivation of a new error expansion with computable leading order terms. When a non-smooth binary payoff is considered, the new adaptive method achieves the same complexity as the uniform discretization with smooth problems. Moreover, the new developed algorithm is extended to the multilevel Monte Carlo (MLMC) forward Euler setting which reduces the complexity from O(TOL-3) to O(TOL-2(log(TOL))2). For the binary option case, it recovers the standard multilevel computational cost O(TOL-2(log(TOL))2). When considering a higher order Milstein scheme, a similar complexity result was obtained by Giles using the uniform time stepping for one dimensional SDEs, see [2]. The difficulty to extend Giles’ Milstein MLMC method to the multidimensional case is an argument for the flexibility of our new constructed adaptive MLMC forward Euler method which can be easily adapted to this setting. Similarly, the expected complexity O(TOL-2(log(TOL))2) is reached for the multidimensional case and verified numerically.

  19. Mining a database of single amplified genomes from Red Sea brine pool extremophiles—improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA)

    Science.gov (United States)

    Grötzinger, Stefan W.; Alam, Intikhab; Ba Alawi, Wail; Bajic, Vladimir B.; Stingl, Ulrich; Eppinger, Jörg

    2014-01-01

    Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile's genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available

  20. Mining a database of single amplified genomes from Red Sea brine pool extremophiles – Improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA

    Directory of Open Access Journals (Sweden)

    Stefan Wolfgang Grötzinger

    2014-04-01

    Full Text Available Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs and poor homology of novel extremophile’s genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the INDIGO data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes may translate into false positives when searching for specific functions. The Profile & Pattern Matching (PPM strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO-terms (which represent enzyme function profiles and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern. The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2,577 E.C. numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from 6 different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter and PROSITE IDs (pattern filter. Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns are present. Scripts for annotation, as well as for the PPM algorithm, are available through the INDIGO website.

  1. Mining a database of single amplified genomes from Red Sea brine pool extremophiles-improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA).

    KAUST Repository

    Grötzinger, Stefan W.

    2014-04-07

    Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile\\'s genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available

  2. Modelling effects of diquat under realistic exposure patterns in genetically differentiated populations of the gastropod Lymnaea stagnalis.

    Science.gov (United States)

    Ducrot, Virginie; Péry, Alexandre R R; Lagadic, Laurent

    2010-11-12

    Pesticide use leads to complex exposure and response patterns in non-target aquatic species, so that the analysis of data from standard toxicity tests may result in unrealistic risk forecasts. Developing models that are able to capture such complexity from toxicity test data is thus a crucial issue for pesticide risk assessment. In this study, freshwater snails from two genetically differentiated populations of Lymnaea stagnalis were exposed to repeated acute applications of environmentally realistic concentrations of the herbicide diquat, from the embryo to the adult stage. Hatching rate, embryonic development duration, juvenile mortality, feeding rate and age at first spawning were investigated during both exposure and recovery periods. Effects of diquat on mortality were analysed using a threshold hazard model accounting for time-varying herbicide concentrations. All endpoints were significantly impaired at diquat environmental concentrations in both populations. Snail evolutionary history had no significant impact on their sensitivity and responsiveness to diquat, whereas food acted as a modulating factor of toxicant-induced mortality. The time course of effects was adequately described by the model, which thus appears suitable to analyse long-term effects of complex exposure patterns based upon full life cycle experiment data. Obtained model outputs (e.g. no-effect concentrations) could be directly used for chemical risk assessment.

  3. Spine formation pattern of adult-born neurons is differentially modulated by the induction timing and location of hippocampal plasticity.

    Directory of Open Access Journals (Sweden)

    Noriaki Ohkawa

    Full Text Available In the adult hippocampus dentate gyrus (DG, newly born neurons are functionally integrated into existing circuits and play important roles in hippocampus-dependent memory. However, it remains unclear how neural plasticity regulates the integration pattern of new neurons into preexisting circuits. Because dendritic spines are major postsynaptic sites for excitatory inputs, spines of new neurons were visualized by retrovirus-mediated labeling to evaluate integration. Long-term potentiation (LTP was induced at 12, 16, or 21 days postinfection (dpi, at which time new neurons have no, few, or many spines, respectively. The spine expression patterns were investigated at one or two weeks after LTP induction. Induction at 12 dpi increased later spinogenesis, although the new neurons at 12 dpi didn't respond to the stimulus for LTP induction. Induction at 21 dpi transiently mediated spine enlargement. Surprisingly, LTP induction at 16 dpi reduced the spine density of new neurons. All LTP-mediated changes specifically appeared within the LTP-induced layer. Therefore, neural plasticity differentially regulates the integration of new neurons into the activated circuit, dependent on their developmental stage. Consequently, new neurons at different developmental stages may play distinct roles in processing the acquired information by modulating the connectivity of activated circuits via their integration.

  4. Detection of boiling by Piety's on-line PSD-pattern recognition algorithm applied to neutron noise signals in the SAPHIR reactor

    International Nuclear Information System (INIS)

    Spiekerman, G.

    1988-09-01

    A partial blockage of the cooling channels of a fuel element in a swimming pool reactor could lead to vapour generation and to burn-out. To detect such anomalies, a pattern recognition algorithm based on power spectra density (PSD) proposed by Piety was further developed and implemented on a PDP 11/23 for on-line applications. This algorithm identifies anomalies by measuring the PSD on the process signal and comparing them with a standard baseline previously formed. Up to 8 decision discriminants help to recognize spectral changes due to anomalies. In our application, to detect boiling as quickly as possible with sufficient sensitivity, Piety's algorithm was modified using overlapped Fast-Fourier-Transform-Processing and the averaging of the PSDs over a large sample of preceding instantaneous PSDs. This processing allows high sensitivity in detecting weak disturbances without reducing response time. The algorithm was tested with simulation-of-boiling experiments where nitrogen in a cooling channel of a mock-up of a fuel element was injected. Void fractions higher than 30 % in the channel can be detected. In the case of boiling, it is believed that this limit is lower because collapsing bubbles could give rise to stronger fluctuations. The algorithm was also tested with a boiling experiment where the reactor coolant flow was actually reduced. The results showed that the discriminant D5 of Piety's algorithm based on neutron noise obtained from the existing neutron chambers of the reactor control system could sensitively recognize boiling. The detection time amounts to 7-30 s depending on the strength of the disturbances. Other events, which arise during a normal reactor run like scrams, removal of isotope elements without scramming or control rod movements and which could lead to false alarms, can be distinguished from boiling. 49 refs., 104 figs., 5 tabs

  5. A Hybrid One-Way ANOVA Approach for the Robust and Efficient Estimation of Differential Gene Expression with Multiple Patterns.

    Directory of Open Access Journals (Sweden)

    Mohammad Manir Hossain Mollah

    Full Text Available Identifying genes that are differentially expressed (DE between two or more conditions with multiple patterns of expression is one of the primary objectives of gene expression data analysis. Several statistical approaches, including one-way analysis of variance (ANOVA, are used to identify DE genes. However, most of these methods provide misleading results for two or more conditions with multiple patterns of expression in the presence of outlying genes. In this paper, an attempt is made to develop a hybrid one-way ANOVA approach that unifies the robustness and efficiency of estimation using the minimum β-divergence method to overcome some problems that arise in the existing robust methods for both small- and large-sample cases with multiple patterns of expression.The proposed method relies on a β-weight function, which produces values between 0 and 1. The β-weight function with β = 0.2 is used as a measure of outlier detection. It assigns smaller weights (≥ 0 to outlying expressions and larger weights (≤ 1 to typical expressions. The distribution of the β-weights is used to calculate the cut-off point, which is compared to the observed β-weight of an expression to determine whether that gene expression is an outlier. This weight function plays a key role in unifying the robustness and efficiency of estimation in one-way ANOVA.Analyses of simulated gene expression profiles revealed that all eight methods (ANOVA, SAM, LIMMA, EBarrays, eLNN, KW, robust BetaEB and proposed perform almost identically for m = 2 conditions in the absence of outliers. However, the robust BetaEB method and the proposed method exhibited considerably better performance than the other six methods in the presence of outliers. In this case, the BetaEB method exhibited slightly better performance than the proposed method for the small-sample cases, but the the proposed method exhibited much better performance than the BetaEB method for both the small- and large

  6. Differential expression patterns and clinical significance of estrogen receptor-α and β in papillary thyroid carcinoma

    International Nuclear Information System (INIS)

    Huang, Yanhong; Dong, Wenwu; Li, Jing; Zhang, Hao; Shan, Zhongyan; Teng, Weiping

    2014-01-01

    The incidence of papillary thyroid cancer (PTC) is markedly higher in women than men during the reproductive years. In vitro studies have suggested that estrogen may play an important role in the development and progression of PTC through estrogen receptors (ERs). This study aimed to investigate the expression patterns of the two main ER subtypes, α and β1 (wild-type ERβ), in PTC tissue and their clinical significance. Immunohistochemical staining of thyroid tissue sections was performed to detect ER expression in female patients with PTC (n = 89) and nodular thyroid goiter (NTG; n = 30) using the Elivision™ plus two-step system. The relationships between ER subtype expression and clinicopathological/biological factors were further analyzed. The positive percentage and expression levels of ERα were significantly higher in female PTC patients of reproductive age (18–45 years old; n = 50) than age-matched female NTG patients (n = 30), while ERβ1 exhibited the opposite pattern. There was no difference in ERα or ERβ1 expression between female PTC patients of reproductive age and those of advanced reproductive age (>45 years old; n = 39). In the female PTC patients of reproductive age, ERα expression level was positively correlated with that of Ki-67, while ERβ1 was negatively correlated with mutant P53. Furthermore, more patients with exclusively nuclear ERα expression had extrathyroidal extension (ETE) as compared with those with extranuclear ERα localization. VEGF expression was significantly decreased in female PTC patients of reproductive age with only nuclear ERβ1 expression when compared with those with extranuclear ERβ1 localization. In PTC patients of advanced reproductive age, neither ERα nor ERβ1 expression showed any correlation with that of Ki-67, mutant P53, VEGF, tumor size, TNM stage, ETE, or lymph node metastases. The differential expression patterns of the two ER subtypes between PTC and NTG indicate that ERα may be a useful

  7. Hybrid Adaptive Multilevel Monte Carlo Algorithm for Non-Smooth Observables of Itô Stochastic Differential Equations

    KAUST Repository

    Rached, Nadhir B.

    2013-12-01

    The Monte Carlo forward Euler method with uniform time stepping is the standard technique to compute an approximation of the expected payoff of a solution of an Itô SDE. For a given accuracy requirement TOL, the complexity of this technique for well behaved problems, that is the amount of computational work to solve the problem, is O(TOL-3). A new hybrid adaptive Monte Carlo forward Euler algorithm for SDEs with non-smooth coefficients and low regular observables is developed in this thesis. This adaptive method is based on the derivation of a new error expansion with computable leading-order terms. The basic idea of the new expansion is the use of a mixture of prior information to determine the weight functions and posterior information to compute the local error. In a number of numerical examples the superior efficiency of the hybrid adaptive algorithm over the standard uniform time stepping technique is verified. When a non-smooth binary payoff with either GBM or drift singularity type of SDEs is considered, the new adaptive method achieves the same complexity as the uniform discretization with smooth problems. Moreover, the new developed algorithm is extended to the MLMC forward Euler setting which reduces the complexity from O(TOL-3) to O(TOL-2(log(TOL))2). For the binary option case with the same type of Itô SDEs, the hybrid adaptive MLMC forward Euler recovers the standard multilevel computational cost O(TOL-2(log(TOL))2). When considering a higher order Milstein scheme, a similar complexity result was obtained by Giles using the uniform time stepping for one dimensional SDEs. The difficulty to extend Giles\\' Milstein MLMC method to the multidimensional case is an argument for the flexibility of our new constructed adaptive MLMC forward Euler method which can be easily adapted to this setting. Similarly, the expected complexity O(TOL-2(log(TOL))2) is reached for the multidimensional case and verified numerically.

  8. Simple algorithm to estimate mean-field effects from minor differential permeability curves based on the Preisach model

    International Nuclear Information System (INIS)

    Perevertov, Oleksiy

    2003-01-01

    The classical Preisach model (PM) of magnetic hysteresis requires that any minor differential permeability curve lies under minor curves with larger field amplitude. Measurements of ferromagnetic materials show that very often this is not true. By applying the classical PM formalism to measured minor curves one can discover that it leads to an oval-shaped region on each half of the Preisach plane where the calculations produce negative values in the Preisach function. Introducing an effective field, which differs from the applied one by a mean-field term proportional to the magnetization, usually solves this problem. Complex techniques exist to estimate the minimum necessary proportionality constant (the moving parameter). In this paper we propose a simpler way to estimate the mean-field effects for use in nondestructive testing, which is based on experience from the measurements of industrial steels. A new parameter (parameter of shift) is introduced, which monitors the mean-field effects. The relation between the shift parameter and the moving one was studied for a number of steels. From preliminary experiments no correlation was found between the shift parameter and the classical magnetic ones such as the coercive field, maximum differential permeability and remanent magnetization

  9. SU-C-BRF-07: A Pattern Fusion Algorithm for Multi-Step Ahead Prediction of Surrogate Motion

    International Nuclear Information System (INIS)

    Zawisza, I; Yan, H; Yin, F

    2014-01-01

    Purpose: To assure that tumor motion is within the radiation field during high-dose and high-precision radiosurgery, real-time imaging and surrogate monitoring are employed. These methods are useful in providing real-time tumor/surrogate motion but no future information is available. In order to anticipate future tumor/surrogate motion and track target location precisely, an algorithm is developed and investigated for estimating surrogate motion multiple-steps ahead. Methods: The study utilized a one-dimensional surrogate motion signal divided into three components: (a) training component containing the primary data including the first frame to the beginning of the input subsequence; (b) input subsequence component of the surrogate signal used as input to the prediction algorithm: (c) output subsequence component is the remaining signal used as the known output of the prediction algorithm for validation. The prediction algorithm consists of three major steps: (1) extracting subsequences from training component which best-match the input subsequence according to given criterion; (2) calculating weighting factors from these best-matched subsequence; (3) collecting the proceeding parts of the subsequences and combining them together with assigned weighting factors to form output. The prediction algorithm was examined for several patients, and its performance is assessed based on the correlation between prediction and known output. Results: Respiratory motion data was collected for 20 patients using the RPM system. The output subsequence is the last 50 samples (∼2 seconds) of a surrogate signal, and the input subsequence was 100 (∼3 seconds) frames prior to the output subsequence. Based on the analysis of correlation coefficient between predicted and known output subsequence, the average correlation is 0.9644±0.0394 and 0.9789±0.0239 for equal-weighting and relative-weighting strategies, respectively. Conclusion: Preliminary results indicate that the prediction

  10. Fitting Nonlinear Ordinary Differential Equation Models with Random Effects and Unknown Initial Conditions Using the Stochastic Approximation Expectation-Maximization (SAEM) Algorithm.

    Science.gov (United States)

    Chow, Sy-Miin; Lu, Zhaohua; Sherwood, Andrew; Zhu, Hongtu

    2016-03-01

    The past decade has evidenced the increased prevalence of irregularly spaced longitudinal data in social sciences. Clearly lacking, however, are modeling tools that allow researchers to fit dynamic models to irregularly spaced data, particularly data that show nonlinearity and heterogeneity in dynamical structures. We consider the issue of fitting multivariate nonlinear differential equation models with random effects and unknown initial conditions to irregularly spaced data. A stochastic approximation expectation-maximization algorithm is proposed and its performance is evaluated using a benchmark nonlinear dynamical systems model, namely, the Van der Pol oscillator equations. The empirical utility of the proposed technique is illustrated using a set of 24-h ambulatory cardiovascular data from 168 men and women. Pertinent methodological challenges and unresolved issues are discussed.

  11. A differential evolution algorithm for tooth profile optimization with respect to balancing specific sliding coefficients of involute cylindrical spur and helical gears

    Directory of Open Access Journals (Sweden)

    Hammoudi Abderazek

    2015-09-01

    Full Text Available Profile shift has an immense effect on the sliding, load capacity, and stability of involute cylindrical gears. Available standards such as ISO/DIS 6336 and BS 436 DIN/3990 currently give the recommendation for the selection of profile shift coefficients. It is, however, very approximate and usually given in the form of implicit graphs or charts. In this article, the optimal selection values of profile shift coefficients for cylindrical involute spur and helical gears are described, using a differential evolution algorithm. The optimization procedure is developed specifically for exact balancing specific sliding coefficients at extremes of contact path and account for gear design constraints. The obtained results are compared with those of standards and research of other authors. They demonstrate the effectiveness and robustness of the applied method. A substantial improvement in balancing specific sliding coefficients is found in this work.

  12. Using a combination of weighting factor method and imperialist competitive algorithm to improve speed and enhance process of reloading pattern optimization of VVER-1000 reactors in transient cycles

    Energy Technology Data Exchange (ETDEWEB)

    Rahmani, Yashar, E-mail: yashar.rahmani@gmail.com [Department of Physics, Faculty of Engineering, Islamic Azad University, Sari Branch, Sari (Iran, Islamic Republic of); Shahvari, Yaser [Department of Computer Engineering, Payame Noor University (PNU), P.O. Box 19395-3697, Tehran (Iran, Islamic Republic of); Kia, Faezeh [Golestan Institute of Higher Education, Gorgan 49139-83635 (Iran, Islamic Republic of)

    2017-03-15

    Highlights: • This article was an attempt to optimize reloading pattern of Bushehr VVER-1000 reactor. • A combination of weighting factor method and the imperialist competitive algorithm was used. • The speed of optimization and desirability of the proposed pattern increased considerably. • To evaluate arrangements, a coupling of WIMSD5-B, CITATION-LDI2 and WERL codes was used. • Results reflected the considerable superiority of the proposed method over direct optimization. - Abstract: In this research, an innovative solution is described which can be used with a combination of the new imperialist competitive algorithm and the weighting factor method to improve speed and increase globality of search in reloading pattern optimization of VVER-1000 reactors in transient cycles and even obtain more desirable results than conventional direct method. In this regard, to reduce the scope of the assumed searchable arrangements, first using the weighting factor method and based on values of these coefficients in each of the 16 types of loadable fuel assemblies in the second cycle, the fuel assemblies were classified in more limited groups. In consequence, the types of fuel assemblies were reduced from 16 to 6 and consequently the number of possible arrangements was reduced considerably. Afterwards, in the first phase of optimization the imperialist competitive algorithm was used to propose an optimum reloading pattern with 6 groups. In the second phase, the algorithm was reused for finding desirable placement of the subset assemblies of each group in the optimum arrangement obtained from the previous phase, and thus the retransformation of the optimum arrangement takes place from the virtual 6-group mode to the real mode with 16 fuel types. In this research, the optimization process was conducted in two states. In the first state, it was tried to obtain an arrangement with the maximum effective multiplication factor and the smallest maximum power peaking factor. In

  13. Swarm intelligence-based approach for optimal design of CMOS differential amplifier and comparator circuit using a hybrid salp swarm algorithm

    Science.gov (United States)

    Asaithambi, Sasikumar; Rajappa, Muthaiah

    2018-05-01

    In this paper, an automatic design method based on a swarm intelligence approach for CMOS analog integrated circuit (IC) design is presented. The hybrid meta-heuristics optimization technique, namely, the salp swarm algorithm (SSA), is applied to the optimal sizing of a CMOS differential amplifier and the comparator circuit. SSA is a nature-inspired optimization algorithm which mimics the navigating and hunting behavior of salp. The hybrid SSA is applied to optimize the circuit design parameters and to minimize the MOS transistor sizes. The proposed swarm intelligence approach was successfully implemented for an automatic design and optimization of CMOS analog ICs using Generic Process Design Kit (GPDK) 180 nm technology. The circuit design parameters and design specifications are validated through a simulation program for integrated circuit emphasis simulator. To investigate the efficiency of the proposed approach, comparisons have been carried out with other simulation-based circuit design methods. The performances of hybrid SSA based CMOS analog IC designs are better than the previously reported studies.

  14. Scheduling trucks in cross docking systems with temporary storage and dock repeat truck holding pattern using genetic algorithm

    Directory of Open Access Journals (Sweden)

    Ehsan Ghobadian

    2013-02-01

    Full Text Available Cross docking is one of the most important issues in management of supply chains. In cross docking, different items delivered to a warehouse by inbound trucks are directly arranged and reorganized based on customer demands, routed and loaded into outbound trucks for delivery purposes to customers without virtually keeping them at the warehouse. If any item is kept in storage, it is normally for a short amount of time, say less than 24 hours. In this paper, we consider a special case of cross docking where there is temporary storage and implements genetic algorithm to solve the resulted problem for some realistic test problems. In our method, we first use some heuristics as initial solutions and then improve the final solution using genetic algorithm. The performance of the proposed model is compared with alternative solution strategy, the GRASP method.

  15. A SELDI mass spectrometry study of experimental autoimmune encephalomyelitis: sample preparation, reproducibility, and differential protein expression patterns.

    Science.gov (United States)

    Azzam, Sausan; Broadwater, Laurie; Li, Shuo; Freeman, Ernest J; McDonough, Jennifer; Gregory, Roger B

    2013-05-01

    Da) levels were lower in EAE samples with advanced disease relative to controls, while an MBP fragment (12. 4kDa), likely due to calpain digestion, was increased in EAE relative to controls. The appearance of MBP in mitochondrially enriched fractions is due to tissue freezing and storage, as MBP was not found associated with mitochondria obtained from fresh tissue. SELDI mass spectrometry can be employed to explore the proteome of a complex tissue (brain) and obtain protein profiles of differentially expressed proteins from protein fractions. Appropriate homogenization protocols and protein fractionation using anion exchange beads can be employed to reduce sample complexity without introducing significant additional variation into the SELDI mass spectra beyond that inherent in the SELDI- MS method itself. SELDI-MS coupled with principal component analysis and hierarchical cluster analysis provides protein patterns that can clearly distinguish the disease state from controls. However, identification of individual differentially expressed proteins requires a separate purification of the proteins of interest by polyacrylamide electrophoresis prior to trypsin digestion and peptide mass fingerprint analysis, and unambiguous identification of differentially expressed proteins can be difficult if protein bands consist of several proteins with similar molecular weights.

  16. Multi-mode energy management strategy for fuel cell electric vehicles based on driving pattern identification using learning vector quantization neural network algorithm

    Science.gov (United States)

    Song, Ke; Li, Feiqiang; Hu, Xiao; He, Lin; Niu, Wenxu; Lu, Sihao; Zhang, Tong

    2018-06-01

    The development of fuel cell electric vehicles can to a certain extent alleviate worldwide energy and environmental issues. While a single energy management strategy cannot meet the complex road conditions of an actual vehicle, this article proposes a multi-mode energy management strategy for electric vehicles with a fuel cell range extender based on driving condition recognition technology, which contains a patterns recognizer and a multi-mode energy management controller. This paper introduces a learning vector quantization (LVQ) neural network to design the driving patterns recognizer according to a vehicle's driving information. This multi-mode strategy can automatically switch to the genetic algorithm optimized thermostat strategy under specific driving conditions in the light of the differences in condition recognition results. Simulation experiments were carried out based on the model's validity verification using a dynamometer test bench. Simulation results show that the proposed strategy can obtain better economic performance than the single-mode thermostat strategy under dynamic driving conditions.

  17. [Application of support vector machine-recursive feature elimination algorithm in Raman spectroscopy for differential diagnosis of benign and malignant breast diseases].

    Science.gov (United States)

    Zhang, Haipeng; Fu, Tong; Zhang, Zhiru; Fan, Zhimin; Zheng, Chao; Han, Bing

    2014-08-01

    To explore the value of application of support vector machine-recursive feature elimination (SVM-RFE) method in Raman spectroscopy for differential diagnosis of benign and malignant breast diseases. Fresh breast tissue samples of 168 patients (all female; ages 22-75) were obtained by routine surgical resection from May 2011 to May 2012 at the Department of Breast Surgery, the First Hospital of Jilin University. Among them, there were 51 normal tissues, 66 benign and 51 malignant breast lesions. All the specimens were assessed by Raman spectroscopy, and the SVM-RFE algorithm was used to process the data and build the mathematical model. Mahalanobis distance and spectral residuals were used as discriminating criteria to evaluate this data-processing method. 1 800 Raman spectra were acquired from the fresh samples of human breast tissues. Based on spectral profiles, the presence of 1 078, 1 267, 1 301, 1 437, 1 653, and 1 743 cm(-1) peaks were identified in the normal tissues; and 1 281, 1 341, 1 381, 1 417, 1 465, 1 530, and 1 637 cm(-1) peaks were found in the benign and malignant tissues. The main characteristic peaks differentiating benign and malignant lesions were 1 340 and 1 480 cm(-1). The accuracy of SVM-RFE in discriminating normal and malignant lesions was 100.0%, while that in the assessment of benign lesions was 93.0%. There are distinct differences among the Raman spectra of normal, benign and malignant breast tissues, and SVM-RFE method can be used to build differentiation model of breast lesions.

  18. Differential SPL gene expression patterns reveal candidate genes underlying flowering time and architectural differences in Mimulus and Arabidopsis.

    Science.gov (United States)

    Jorgensen, Stacy A; Preston, Jill C

    2014-04-01

    Evolutionary transitions in growth habit and flowering time responses to variable environmental signals have occurred multiple times independently across angiosperms and have major impacts on plant fitness. Proteins in the SPL family of transcription factors collectively regulate flowering time genes that have been implicated in interspecific shifts in annuality/perenniality. However, their potential importance in the evolution of angiosperm growth habit has not been extensively investigated. Here we identify orthologs representative of the major SPL gene clades in annual Arabidopsis thaliana and Mimulus guttatus IM767, and perennial A. lyrata and M. guttatus PR, and characterize their expression. Spatio-temporal expression patterns are complex across both diverse tissues of the same taxa and comparable tissues of different taxa, consistent with genic sub- or neo-functionalization. However, our data are consistent with a general role for several SPL genes in the promotion of juvenile to adult phase change and/or flowering time in Mimulus and Arabidopsis. Furthermore, several candidate genes were identified for future study whose differential expression correlates with growth habit and architectural variation in annual versus perennial taxa. Copyright © 2014 Elsevier Inc. All rights reserved.

  19. Non-uniform distribution pattern for differentially expressed genes of transgenic rice Huahui 1 at different developmental stages and environments.

    Directory of Open Access Journals (Sweden)

    Zhi Liu

    Full Text Available DNA microarray analysis is an effective method to detect unintended effects by detecting differentially expressed genes (DEG in safety assessment of genetically modified (GM crops. With the aim to reveal the distribution of DEG of GM crops under different conditions, we performed DNA microarray analysis using transgenic rice Huahui 1 (HH1 and its non-transgenic parent Minghui 63 (MH63 at different developmental stages and environmental conditions. Considerable DEG were selected in each group of HH1 under different conditions. For each group of HH1, the number of DEG was different; however, considerable common DEG were shared between different groups of HH1. These findings suggested that both DEG and common DEG were adequate for investigation of unintended effects. Furthermore, a number of significantly changed pathways were found in all groups of HH1, indicating genetic modification caused everlasting changes to plants. To our knowledge, our study for the first time provided the non-uniformly distributed pattern for DEG of GM crops at different developmental stages and environments. Our result also suggested that DEG selected in GM plants at specific developmental stage and environment could act as useful clues for further evaluation of unintended effects of GM plants.

  20. Control entropy identifies differential changes in complexity of walking and running gait patterns with increasing speed in highly trained runners.

    Science.gov (United States)

    McGregor, Stephen J; Busa, Michael A; Skufca, Joseph; Yaggie, James A; Bollt, Erik M

    2009-06-01

    Regularity statistics have been previously applied to walking gait measures in the hope of gaining insight into the complexity of gait under different conditions and in different populations. Traditional regularity statistics are subject to the requirement of stationarity, a limitation for examining changes in complexity under dynamic conditions such as exhaustive exercise. Using a novel measure, control entropy (CE), applied to triaxial continuous accelerometry, we report changes in complexity of walking and running during increasing speeds up to exhaustion in highly trained runners. We further apply Karhunen-Loeve analysis in a new and novel way to the patterns of CE responses in each of the three axes to identify dominant modes of CE responses in the vertical, mediolateral, and anterior/posterior planes. The differential CE responses observed between the different axes in this select population provide insight into the constraints of walking and running in those who may have optimized locomotion. Future comparisons between athletes, healthy untrained, and clinical populations using this approach may help elucidate differences between optimized and diseased locomotor control.

  1. Coexistence of atrial myxoma and lung cancer on fluorodeoxyglucose positron emission tomography/computed tomography: The impact of distinct fluorodeoxyglucose uptake pattern on differential diagnosis

    International Nuclear Information System (INIS)

    Koc, Kevser; Aras, Mustafa; Inanir, Sabahat

    2014-01-01

    The information regarding fluorodeoxyglucose (FDG) uptake in benign and malignant cardiac tumors is limited in the literature and most of the currrently available data were derived from single case reports. Herein we reported coexistence of atrial myxoma and lung cancer on FDG positron emission tomography/computed tomography with the aim of emphasizing the importance of distinct FDG uptake pattern on differential diagnosis

  2. Dietary Assessment on a Mobile Phone Using Image Processing and Pattern Recognition Techniques: Algorithm Design and System Prototyping

    Directory of Open Access Journals (Sweden)

    Yasmine Probst

    2015-07-01

    Full Text Available Dietary assessment, while traditionally based on pen-and-paper, is rapidly moving towards automatic approaches. This study describes an Australian automatic food record method and its prototype for dietary assessment via the use of a mobile phone and techniques of image processing and pattern recognition. Common visual features including scale invariant feature transformation (SIFT, local binary patterns (LBP, and colour are used for describing food images. The popular bag-of-words (BoW model is employed for recognizing the images taken by a mobile phone for dietary assessment. Technical details are provided together with discussions on the issues and future work.

  3. An Algorithm Computing the Local $b$ Function by an Approximate Division Algorithm in $\\hat{\\mathcal{D}}$

    OpenAIRE

    Nakayama, Hiromasa

    2006-01-01

    We give an algorithm to compute the local $b$ function. In this algorithm, we use the Mora division algorithm in the ring of differential operators and an approximate division algorithm in the ring of differential operators with power series coefficient.

  4. High cell density suppresses BMP4-induced differentiation of human pluripotent stem cells to produce macroscopic spatial patterning in a unidirectional perfusion culture chamber.

    Science.gov (United States)

    Tashiro, Shota; Le, Minh Nguyen Tuyet; Kusama, Yuta; Nakatani, Eri; Suga, Mika; Furue, Miho K; Satoh, Taku; Sugiura, Shinji; Kanamori, Toshiyuki; Ohnuma, Kiyoshi

    2018-04-19

    Spatial pattern formation is a critical step in embryogenesis. Bone morphogenetic protein 4 (BMP4) and its inhibitors are major factors for the formation of spatial patterns during embryogenesis. However, spatial patterning of the human embryo is unclear because of ethical issues and isotropic culture environments resulting from conventional culture dishes. Here, we utilized human pluripotent stem cells (hiPSCs) and a simple anisotropic (unidirectional perfusion) culture chamber, which creates unidirectional conditions, to measure the cell community effect. The influence of cell density on BMP4-induced differentiation was explored during static culture using a conventional culture dish. Immunostaining of the early differentiation marker SSEA-1 and the mesendoderm marker BRACHYURY revealed that high cell density suppressed differentiation, with small clusters of differentiated and undifferentiated cells formed. Addition of five-fold higher concentration of BMP4 showed similar results, suggesting that suppression was not caused by depletion of BMP4 but rather by high cell density. Quantitative RT-PCR array analysis showed that BMP4 induced multi-lineage differentiation, which was also suppressed under high-density conditions. We fabricated an elongated perfusion culture chamber, in which proteins were transported unidirectionally, and hiPSCs were cultured with BMP4. At low density, the expression was the same throughout the chamber. However, at high density, SSEA-1 and BRACHYURY were expressed only in upstream cells, suggesting that some autocrine/paracrine factors inhibited the action of BMP4 in downstream cells to form the spatial pattern. Human iPSCs cultured in a perfusion culture chamber might be useful for studying in vitro macroscopic pattern formation in human embryogenesis. Copyright © 2018 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  5. Pattern recognition, neural networks, genetic algorithms and high performance computing in nuclear reactor diagnostics. Results and perspectives

    International Nuclear Information System (INIS)

    Dzwinel, W.; Pepyolyshev, N.

    1996-01-01

    The main goal of this paper is the presentation of our experience in development of the diagnostic system for the IBR-2 (Russia - Dubna) nuclear reactor. The authors show the principal results of the system modifications to make it work more reliable and much faster. The former needs the adaptation of new techniques of data processing, the latter, implementation of the newest computational facilities. The results of application of the clustering techniques and a method of visualization of the multi-dimensional information directly on the operator display are presented. The experiences with neural nets, used for prediction of the reactor operation, are discussed. The genetic algorithms were also tested, to reduce the quantity of data nd extracting the most informative components of the analyzed spectra. (authors)

  6. Particles from wood smoke and traffic induce differential pro-inflammatory response patterns in co-cultures

    International Nuclear Information System (INIS)

    Kocbach, Anette; Herseth, Jan Inge; Lag, Marit; Refsnes, Magne; Schwarze, Per E.

    2008-01-01

    The inflammatory potential of particles from wood smoke and traffic has not been well elucidated. In this study, a contact co-culture of monocytes and pneumocytes was exposed to 10-40 μg/cm 2 of particles from wood smoke and traffic for 12, 40 and 64 h to determine their influence on pro-inflammatory cytokine release (TNF-α, IL-1, IL-6, IL-8) and viability. To investigate the role of organic constituents in cytokine release the response to particles, their organic extracts and the washed particles were compared. Antagonists were used to investigate source-dependent differences in intercellular signalling (TNF-α, IL-1). The cytotoxicity was low after exposure to particles from both sources. However, wood smoke, and to a lesser degree traffic-derived particles, induced a reduction in cell number, which was associated with the organic fraction. The release of pro-inflammatory cytokines was similar for both sources after 12 h, but traffic induced a greater release than wood smoke particles with increasing exposure time. The organic fraction accounted for the majority of the cytokine release induced by wood smoke, whereas the washed traffic particles induced a stronger response than the corresponding organic extract. TNF-α and IL-1 antagonists reduced the release of IL-8 induced by particles from both sources. In contrast, the IL-6 release was only reduced by the IL-1 antagonist during exposure to traffic-derived particles. In summary, particles from wood smoke and traffic induced differential pro-inflammatory response patterns with respect to cytokine release and cell number. Moreover, the influence of the organic particle fraction and intercellular signalling on the pro-inflammatory response seemed to be source-dependent

  7. Modelling hydrological connectivity in semi-arid flat areas: effect of the flow accumulation algorithm on the spatial pattern

    Science.gov (United States)

    López-Vicente, Manuel; Álvarez, Sara

    2017-04-01

    Much of the water and sediment fluxes in semi-arid landscapes are found to be concentrated in localized pathways. Identifying the location of these pathways is important for management and restoration. This task becomes more complicated in flat areas, such as alluvial terraces, where geomorphic features of concentrated overland flow (rills and ephemeral gullies) are scarce or inexistent. Field identification of sediment delivery pathways as well as depositional areas is also difficult and challenged. The concept of hydrological connectivity (HC) helps us to express the complexity of landscape non-linear responses to rainfall inputs. One of the unsolved issues in overland flow modelling studies is the choice of the right flow accumulation algorithm (FAA). There is an abundant literature on runoff generation under semi-arid conditions, and relating HC and land use management and changes. However, we found a scientific gap in the literature focussed on modelling of HC in flat areas under semi-arid conditions. This study aims to fill in this gap by modelling HC in alluvial terraces (28 ha) in NE Spain under semi-arid conditions (342 mm / year), mainly devoted to rain-fed cereal fields, by using eight FAA. For this purpose, we applied a modified version of the Borselli's index of runoff and sediment connectivity (IC). The study area includes seven fields on flat alluvial terraces, three fields on a gentle slope, small patches of scrubland, and twelve grass buffer strips that are located between each set of fields. Gentle and flat areas (S drone (model eBee by senseFly Ltd.). In order to minimize the effect of the vegetation on the photogrammetry restitution technique, pictures were taken in early spring, before the growth of the cereals. Then, several DEMs were generated independently. For this study, we chose the DEM at 0.5 x 0.5 m of spatial resolution. Before running the IC model, the continuity of the flow path lines throughout the landscape was ensured by removing

  8. Differential bioaccumulation and translocation patterns in three mangrove plants experimentally exposed to iron. Consequences for environmental sensing.

    Science.gov (United States)

    Arrivabene, Hiulana Pereira; Campos, Caroline Quenupe; Souza, Iara da Costa; Wunderlin, Daniel Alberto; Milanez, Camilla Rozindo Dias; Machado, Silvia Rodrigues

    2016-08-01

    Avicennia schaueriana, Laguncularia racemosa and Rhizophora mangle were experimentally exposed to increasing levels of iron (0, 10, 20 and 100 mg L(-1) added Fe(II) in Hoagland's nutritive medium). The uptake and translocation of iron from roots to stems and leaves, Fe-secretion through salt glands (Avicennia schaueriana and Laguncularia racemosa) as well as anatomical and histochemical changes in plant tissues were evaluated. The main goal of this work was to assess the diverse capacity of these plants to detect mangroves at risk in an area affected by iron pollution (Vitoria, Espírito Santo, Brazil). Results show that plants have differential patterns with respect to bioaccumulation, translocation and secretion of iron through salt glands. L. racemosa showed the best environmental sensing capacity since the bioaccumulation of iron in both Fe-plaque and roots was higher and increased as the amount of added-iron rose. Fewer changes in translocation factors throughout increasing added-iron were observed in this species. Furthermore, the amount of iron secreted through salt glands of L. racemosa was strongly inhibited when exposed to added-iron. Among three studied species, A. schaueriana showed the highest levels of iron in stems and leaves. On the other hand, Rhizophora mangle presented low values of iron in these compartments. Even so, there was a significant drop in the translocation factor between aerial parts with respect to roots, since the bioaccumulation in plaque and roots of R. mangle increased as iron concentration rose. Moreover, rhizophores of R. mangle did not show changes in bioaccumulation throughout the studied concentrations. So far, we propose L. racemosa as the best species for monitoring iron pollution in affected mangroves areas. To our knowledge, this is the first detailed report on the response of these plants to increasing iron concentration under controlled conditions, complementing existing data on the behavior of the same plants

  9. Use of Pattern Classification Algorithms to Interpret Passive and Active Data Streams from a Walking-Speed Robotic Sensor Platform

    Science.gov (United States)

    Dieckman, Eric Allen

    In order to perform useful tasks for us, robots must have the ability to notice, recognize, and respond to objects and events in their environment. This requires the acquisition and synthesis of information from a variety of sensors. Here we investigate the performance of a number of sensor modalities in an unstructured outdoor environment, including the Microsoft Kinect, thermal infrared camera, and coffee can radar. Special attention is given to acoustic echolocation measurements of approaching vehicles, where an acoustic parametric array propagates an audible signal to the oncoming target and the Kinect microphone array records the reflected backscattered signal. Although useful information about the target is hidden inside the noisy time domain measurements, the Dynamic Wavelet Fingerprint process (DWFP) is used to create a time-frequency representation of the data. A small-dimensional feature vector is created for each measurement using an intelligent feature selection process for use in statistical pattern classification routines. Using our experimentally measured data from real vehicles at 50 m, this process is able to correctly classify vehicles into one of five classes with 94% accuracy. Fully three-dimensional simulations allow us to study the nonlinear beam propagation and interaction with real-world targets to improve classification results.

  10. Development of an optimized algorithm for the characterization of microflow using speckle patterns present in optical coherence tomography signal

    International Nuclear Information System (INIS)

    Pretto, Lucas Ramos de

    2015-01-01

    This work discusses the Optical Coherence Tomography system (OCT) and its application to the microfluidics area. To this end, physical characterization of microfluidic circuits were performed using 3D (three-dimensional) models constructed from OCT images of such circuits. The technique was thus evaluated as a potential tool to aid in the inspection of microchannels. Going further, this work paper studies and develops analytical techniques for microfluidic flow, in particular techniques based on speckle pattern. In the first instance, existing methods were studied and improved, such as Speckle Variance - OCT, where a gain of 31% was obtained in processing time. Other methods, such as LASCA (Laser Speckle Contrast Analysis), based on speckle autocorrelation, are adapted to OCT images. Derived from LASCA, the developed analysis technique based on intensity autocorrelation motivated the development of a custom OCT system as well as an optimized acquisition software, with a sampling rate of 8 kHz. The proposed method was, then, able to distinguish different flow rates, and limits of detection were tested, proving its feasibility for implementation on Brownian motion analysis and flow rates below 10 μl/min. (author)

  11. A novel algorithm to detect glaucoma risk using texton and local configuration pattern features extracted from fundus images.

    Science.gov (United States)

    Acharya, U Rajendra; Bhat, Shreya; Koh, Joel E W; Bhandary, Sulatha V; Adeli, Hojjat

    2017-09-01

    Glaucoma is an optic neuropathy defined by characteristic damage to the optic nerve and accompanying visual field deficits. Early diagnosis and treatment are critical to prevent irreversible vision loss and ultimate blindness. Current techniques for computer-aided analysis of the optic nerve and retinal nerve fiber layer (RNFL) are expensive and require keen interpretation by trained specialists. Hence, an automated system is highly desirable for a cost-effective and accurate screening for the diagnosis of glaucoma. This paper presents a new methodology and a computerized diagnostic system. Adaptive histogram equalization is used to convert color images to grayscale images followed by convolution of these images with Leung-Malik (LM), Schmid (S), and maximum response (MR4 and MR8) filter banks. The basic microstructures in typical images are called textons. The convolution process produces textons. Local configuration pattern (LCP) features are extracted from these textons. The significant features are selected using a sequential floating forward search (SFFS) method and ranked using the statistical t-test. Finally, various classifiers are used for classification of images into normal and glaucomatous classes. A high classification accuracy of 95.8% is achieved using six features obtained from the LM filter bank and the k-nearest neighbor (kNN) classifier. A glaucoma integrative index (GRI) is also formulated to obtain a reliable and effective system. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Contrasting patterns of diversity and population differentiation at the innate immunity gene toll-like receptor 2 (TLR2) in two sympatric rodent species.

    Science.gov (United States)

    Tschirren, Barbara; Andersson, Martin; Scherman, Kristin; Westerdahl, Helena; Råberg, Lars

    2012-03-01

    Comparing patterns of diversity and divergence between populations at immune genes and neutral markers can give insights into the nature and geographic scale of parasite-mediated selection. To date, studies investigating such patterns of selection in vertebrates have primarily focused on the acquired branch of the immune system, whereas it remains largely unknown how parasite-mediated selection shapes innate immune genes both within and across vertebrate populations. Here, we present a study on the diversity and population differentiation at the innate immune gene Toll-like receptor 2 (TLR2) across nine populations of yellow-necked mice (Apodemus flavicollis) and bank voles (Myodes glareolus) in southern Sweden. In yellow-necked mice, TLR2 diversity was very low, as was TLR2 population differentiation compared to neutral loci. In contrast, several TLR2 haplotypes co-occurred at intermediate frequencies within and across bank vole populations, and pronounced isolation by distance between populations was observed. The diversity and differentiation at neutral loci was similar in the two species. These results indicate that parasite-mediated selection has been acting in dramatically different ways on a given immune gene in ecologically similar and sympatric species. Furthermore, the finding of TLR2 population differentiation at a small geographical scale in bank voles highlights that vertebrate innate immune defense may be evolutionarily more dynamic than has previously been appreciated. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.