Differential Evolution for Many-Particle Adaptive Quantum Metrology

NARCIS (Netherlands)

Lovett, N.B.; Crosnier, C.; Perarnau- Llobet, M.; Sanders, B.

2013-01-01

We devise powerful algorithms based on differential evolution for adaptive many-particle quantum metrology. Our new approach delivers adaptive quantum metrology policies for feedback control that are orders-of-magnitude more efficient and surpass the few-dozen-particle limitation arising in methods

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.

Differential evolution enhanced with multiobjective sorting-based mutation operators.

Science.gov (United States)

Wang, Jiahai; Liao, Jianjun; Zhou, Ying; Cai, Yiqiao

2014-12-01

Differential evolution (DE) is a simple and powerful population-based evolutionary algorithm. The salient feature of DE lies in its mutation mechanism. Generally, the parents in the mutation operator of DE are randomly selected from the population. Hence, all vectors are equally likely to be selected as parents without selective pressure at all. Additionally, the diversity information is always ignored. In order to fully exploit the fitness and diversity information of the population, this paper presents a DE framework with multiobjective sorting-based mutation operator. In the proposed mutation operator, individuals in the current population are firstly sorted according to their fitness and diversity contribution by nondominated sorting. Then parents in the mutation operators are proportionally selected according to their rankings based on fitness and diversity, thus, the promising individuals with better fitness and diversity have more opportunity to be selected as parents. Since fitness and diversity information is simultaneously considered for parent selection, a good balance between exploration and exploitation can be achieved. The proposed operator is applied to original DE algorithms, as well as several advanced DE variants. Experimental results on 48 benchmark functions and 12 real-world application problems show that the proposed operator is an effective approach to enhance the performance of most DE algorithms studied.

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.

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.

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.

An Enhanced Differential Evolution with Elite Chaotic Local Search

Directory of Open Access Journals (Sweden)

Zhaolu Guo

2015-01-01

Full Text Available Differential evolution (DE is a simple yet efficient evolutionary algorithm for real-world engineering problems. However, its search ability should be further enhanced to obtain better solutions when DE is applied to solve complex optimization problems. This paper presents an enhanced differential evolution with elite chaotic local search (DEECL. In DEECL, it utilizes a chaotic search strategy based on the heuristic information from the elite individuals to promote the exploitation power. Moreover, DEECL employs a simple and effective parameter adaptation mechanism to enhance the robustness. Experiments are conducted on a set of classical test functions. The experimental results show that DEECL is very competitive on the majority of the test functions.

Geometric differential evolution for combinatorial and programs spaces.

Science.gov (United States)

Moraglio, A; Togelius, J; Silva, S

2013-01-01

Geometric differential evolution (GDE) is a recently introduced formal generalization of traditional differential evolution (DE) that can be used to derive specific differential evolution algorithms for both continuous and combinatorial spaces retaining the same geometric interpretation of the dynamics of the DE search across representations. In this article, we first review the theory behind the GDE algorithm, then, we use this framework to formally derive specific GDE for search spaces associated with binary strings, permutations, vectors of permutations and genetic programs. The resulting algorithms are representation-specific differential evolution algorithms searching the target spaces by acting directly on their underlying representations. We present experimental results for each of the new algorithms on a number of well-known problems comprising NK-landscapes, TSP, and Sudoku, for binary strings, permutations, and vectors of permutations. We also present results for the regression, artificial ant, parity, and multiplexer problems within the genetic programming domain. Experiments show that overall the new DE algorithms are competitive with well-tuned standard search algorithms.

A SLAM based on auxiliary marginalised particle filter and differential evolution

Science.gov (United States)

Havangi, R.; Nekoui, M. A.; Teshnehlab, M.; Taghirad, H. D.

2014-09-01

FastSLAM is a framework for simultaneous localisation and mapping (SLAM) using a Rao-Blackwellised particle filter. In FastSLAM, particle filter is used for the robot pose (position and orientation) estimation, and parametric filter (i.e. EKF and UKF) is used for the feature location's estimation. However, in the long term, FastSLAM is an inconsistent algorithm. In this paper, a new approach to SLAM based on hybrid auxiliary marginalised particle filter and differential evolution (DE) is proposed. In the proposed algorithm, the robot pose is estimated based on auxiliary marginal particle filter that operates directly on the marginal distribution, and hence avoids performing importance sampling on a space of growing dimension. In addition, static map is considered as a set of parameters that are learned using DE. Compared to other algorithms, the proposed algorithm can improve consistency for longer time periods and also, improve the estimation accuracy. Simulations and experimental results indicate that the proposed algorithm is effective.

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.

Reliability-redundancy optimization by means of a chaotic differential evolution approach

International Nuclear Information System (INIS)

Coelho, Leandro dos Santos

2009-01-01

The reliability design is related to the performance analysis of many engineering systems. The reliability-redundancy optimization problems involve selection of components with multiple choices and redundancy levels that produce maximum benefits, can be subject to the cost, weight, and volume constraints. Classical mathematical methods have failed in handling nonconvexities and nonsmoothness in optimization problems. As an alternative to the classical optimization approaches, the meta-heuristics have been given much attention by many researchers due to their ability to find an almost global optimal solution in reliability-redundancy optimization problems. Evolutionary algorithms (EAs) - paradigms of evolutionary computation field - are stochastic and robust meta-heuristics useful to solve reliability-redundancy 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. A differential evolution approach based on chaotic sequences using Lozi's map for reliability-redundancy optimization problems is proposed in this paper. The proposed method has a fast convergence rate but also maintains the diversity of the population so as to escape from local optima. An application example in reliability-redundancy optimization based on the overspeed protection system of a gas turbine is given to show its usefulness and efficiency. Simulation results show that the application of deterministic chaotic sequences instead of random sequences is a possible strategy to improve the performance of differential evolution.

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.

Differential Evolution and Particle Swarm Optimization for Partitional Clustering

DEFF Research Database (Denmark)

Krink, Thiemo; Paterlini, Sandra

2006-01-01

for numerical optimisation, which are hardly known outside the search heuristics field, are particle swarm optimisation (PSO) and differential evolution (DE). The performance of GAs for a representative point evolution approach to clustering is compared with PSO and DE. The empirical results show that DE......Many partitional clustering algorithms based on genetic algorithms (GA) have been proposed to tackle the problem of finding the optimal partition of a data set. Very few studies considered alternative stochastic search heuristics other than GAs or simulated annealing. Two promising algorithms...

An Improved Differential Evolution Based Dynamic Economic Dispatch with Nonsmooth Fuel Cost Function

Directory of Open Access Journals (Sweden)

R. Balamurugan

2007-09-01

Full Text Available Dynamic economic dispatch (DED is one of the major operational decisions in electric power systems. DED problem is an optimization problem with an objective to determine the optimal combination of power outputs for all generating units over a certain period of time in order to minimize the total fuel cost while satisfying dynamic operational constraints and load demand in each interval. This paper presents an improved differential evolution (IDE method to solve the DED problem of generating units considering valve-point effects. Heuristic crossover technique and gene swap operator are introduced in the proposed approach to improve the convergence characteristic of the differential evolution (DE algorithm. To illustrate the effectiveness of the proposed approach, two test systems consisting of five and ten generating units have been considered. The results obtained through the proposed method are compared with those reported in the literature.

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.

Accelerating parameter identification of proton exchange membrane fuel cell model with ranking-based differential evolution

International Nuclear Information System (INIS)

Gong, Wenyin; Cai, Zhihua

2013-01-01

Parameter identification of PEM (proton exchange membrane) fuel cell model is a very active area of research. Generally, it can be treated as a numerical optimization problem with complex nonlinear and multi-variable features. DE (differential evolution), which has been successfully used in various fields, is a simple yet efficient evolutionary algorithm for global numerical optimization. In this paper, with the objective of accelerating the process of parameter identification of PEM fuel cell models and reducing the necessary computational efforts, we firstly present a generic and simple ranking-based mutation operator for the DE algorithm. Then, the ranking-based mutation operator is incorporated into five highly-competitive DE variants to solve the PEM fuel cell model parameter identification problems. The main contributions of this work are the proposed ranking-based DE variants and their application to the parameter identification problems of PEM fuel cell models. Experiments have been conducted by using both the simulated voltage–current data and the data obtained from the literature to validate the performance of our approach. The results indicate that the ranking-based DE methods provide better results with respect to the solution quality, the convergence rate, and the success rate compared with their corresponding original DE methods. In addition, the voltage–current characteristics obtained by our approach are in good agreement with the original voltage–current curves in all cases. - Highlights: • A simple and generic ranking-based mutation operator is presented in this paper. • Several DE (differential evolution) variants are used to solve the parameter identification of PEMFC (proton exchange membrane fuel cells) model. • Results show that our method accelerates the process of parameter identification. • The V–I characteristics are in very good agreement with experimental data

Cloud computing task scheduling strategy based on differential evolution and ant colony optimization

Science.gov (United States)

Ge, Junwei; Cai, Yu; Fang, Yiqiu

2018-05-01

This paper proposes a task scheduling strategy DEACO based on the combination of Differential Evolution (DE) and Ant Colony Optimization (ACO), aiming at the single problem of optimization objective in cloud computing task scheduling, this paper combines the shortest task completion time, cost and load balancing. DEACO uses the solution of the DE to initialize the initial pheromone of ACO, reduces the time of collecting the pheromone in ACO in the early, and improves the pheromone updating rule through the load factor. The proposed algorithm is simulated on cloudsim, and compared with the min-min and ACO. The experimental results show that DEACO is more superior in terms of time, cost, and load.

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.

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.

Differential evolution-simulated annealing for multiple sequence alignment

Science.gov (United States)

Addawe, R. C.; Addawe, J. M.; Sueño, M. R. K.; Magadia, J. C.

2017-10-01

Multiple sequence alignments (MSA) are used in the analysis of molecular evolution and sequence structure relationships. In this paper, a hybrid algorithm, Differential Evolution - Simulated Annealing (DESA) is applied in optimizing multiple sequence alignments (MSAs) based on structural information, non-gaps percentage and totally conserved columns. DESA is a robust algorithm characterized by self-organization, mutation, crossover, and SA-like selection scheme of the strategy parameters. Here, the MSA problem is treated as a multi-objective optimization problem of the hybrid evolutionary algorithm, DESA. Thus, we name the algorithm as DESA-MSA. Simulated sequences and alignments were generated to evaluate the accuracy and efficiency of DESA-MSA using different indel sizes, sequence lengths, deletion rates and insertion rates. The proposed hybrid algorithm obtained acceptable solutions particularly for the MSA problem evaluated based on the three objectives.

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.

Vinayaka : A Semi-Supervised Projected Clustering Method Using Differential Evolution

OpenAIRE

Satish Gajawada; Durga Toshniwal

2012-01-01

Differential Evolution (DE) is an algorithm for evolutionary optimization. Clustering problems have beensolved by using DE based clustering methods but these methods may fail to find clusters hidden insubspaces of high dimensional datasets. Subspace and projected clustering methods have been proposed inliterature to find subspace clusters that are present in subspaces of dataset. In this paper we proposeVINAYAKA, a semi-supervised projected clustering method based on DE. In this method DE opt...

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.

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.

Differential Evolution-Based PID Control of Nonlinear Full-Car Electrohydraulic Suspensions

Directory of Open Access Journals (Sweden)

Jimoh O. Pedro

2013-01-01

Full Text Available This paper presents a differential-evolution- (DE- optimized, independent multiloop proportional-integral-derivative (PID controller design for full-car nonlinear, electrohydraulic suspension systems. The multiloop PID control stabilises the actuator via force feedback and also improves the system performance. Controller gains are computed using manual tuning and through DE optimization to minimise a performance index, which addresses suspension travel, road holding, vehicle handling, ride comfort, and power consumption constraints. Simulation results showed superior performance of the DE-optimized PID-controlled active vehicle suspension system (AVSS over the manually tuned PID-controlled AVSS and the passive vehicle suspension system (PVSS.

Automatic Clustering Using FSDE-Forced Strategy Differential Evolution

Science.gov (United States)

Yasid, A.

2018-01-01

Clustering analysis is important in datamining for unsupervised data, cause no adequate prior knowledge. One of the important tasks is defining the number of clusters without user involvement that is known as automatic clustering. This study intends on acquiring cluster number automatically utilizing forced strategy differential evolution (AC-FSDE). Two mutation parameters, namely: constant parameter and variable parameter are employed to boost differential evolution performance. Four well-known benchmark datasets were used to evaluate the algorithm. Moreover, the result is compared with other state of the art automatic clustering methods. The experiment results evidence that AC-FSDE is better or competitive with other existing automatic clustering algorithm.

Differential evolution-based multi-objective optimization for the definition of a health indicator for fault diagnostics and prognostics

Science.gov (United States)

Baraldi, P.; Bonfanti, G.; Zio, E.

2018-03-01

The identification of the current degradation state of an industrial component and the prediction of its future evolution is a fundamental step for the development of condition-based and predictive maintenance approaches. The objective of the present work is to propose a general method for extracting a health indicator to measure the amount of component degradation from a set of signals measured during operation. The proposed method is based on the combined use of feature extraction techniques, such as Empirical Mode Decomposition and Auto-Associative Kernel Regression, and a multi-objective Binary Differential Evolution (BDE) algorithm for selecting the subset of features optimal for the definition of the health indicator. The objectives of the optimization are desired characteristics of the health indicator, such as monotonicity, trendability and prognosability. A case study is considered, concerning the prediction of the remaining useful life of turbofan engines. The obtained results confirm that the method is capable of extracting health indicators suitable for accurate prognostics.

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.

[Feature extraction for breast cancer data based on geometric algebra theory and feature selection using differential evolution].

Science.gov (United States)

Li, Jing; Hong, Wenxue

2014-12-01

The feature extraction and feature selection are the important issues in pattern recognition. Based on the geometric algebra representation of vector, a new feature extraction method using blade coefficient of geometric algebra was proposed in this study. At the same time, an improved differential evolution (DE) feature selection method was proposed to solve the elevated high dimension issue. The simple linear discriminant analysis was used as the classifier. The result of the 10-fold cross-validation (10 CV) classification of public breast cancer biomedical dataset was more than 96% and proved superior to that of the original features and traditional feature extraction method.

Differential evolution to enhance localization of mobile robots

DEFF Research Database (Denmark)

Lisowski, Michal; Fan, Zhun; Ravn, Ole

2011-01-01

. In addition, a novel mechanism for effective robot kidnap detection was proposed. Experiments were performed using computer simulations based on the odometer data and laser range finder measurements collected in advance by a robot in real-life. Experimental results showed that integrating DE enables MCL...... to provide more accurate robot pose estimations in shorter time while using fewer particles.......This paper focuses on the mobile robot localization problems: pose tracking, global localization and robot kidnap. Differential Evolution (DE) applied to extend Monte Carlo Localization (MCL) was investigated to better solve localization problem by increasing localization reliability and speed...

Multiple Active Contours Guided by Differential Evolution for Medical Image Segmentation

Science.gov (United States)

Cruz-Aceves, I.; Avina-Cervantes, J. G.; Lopez-Hernandez, J. M.; Rostro-Gonzalez, H.; Garcia-Capulin, C. H.; Torres-Cisneros, M.; Guzman-Cabrera, R.

2013-01-01

This paper presents a new image segmentation method based on multiple active contours guided by differential evolution, called MACDE. The segmentation method uses differential evolution over a polar coordinate system to increase the exploration and exploitation capabilities regarding the classical active contour model. To evaluate the performance of the proposed method, a set of synthetic images with complex objects, Gaussian noise, and deep concavities is introduced. Subsequently, MACDE is applied on datasets of sequential computed tomography and magnetic resonance images which contain the human heart and the human left ventricle, respectively. Finally, to obtain a quantitative and qualitative evaluation of the medical image segmentations compared to regions outlined by experts, a set of distance and similarity metrics has been adopted. According to the experimental results, MACDE outperforms the classical active contour model and the interactive Tseng method in terms of efficiency and robustness for obtaining the optimal control points and attains a high accuracy segmentation. PMID:23983809

Multiple Active Contours Guided by Differential Evolution for Medical Image Segmentation

Directory of Open Access Journals (Sweden)

I. Cruz-Aceves

2013-01-01

Full Text Available This paper presents a new image segmentation method based on multiple active contours guided by differential evolution, called MACDE. The segmentation method uses differential evolution over a polar coordinate system to increase the exploration and exploitation capabilities regarding the classical active contour model. To evaluate the performance of the proposed method, a set of synthetic images with complex objects, Gaussian noise, and deep concavities is introduced. Subsequently, MACDE is applied on datasets of sequential computed tomography and magnetic resonance images which contain the human heart and the human left ventricle, respectively. Finally, to obtain a quantitative and qualitative evaluation of the medical image segmentations compared to regions outlined by experts, a set of distance and similarity metrics has been adopted. According to the experimental results, MACDE outperforms the classical active contour model and the interactive Tseng method in terms of efficiency and robustness for obtaining the optimal control points and attains a high accuracy segmentation.

Optimal Decision Fusion for Urban Land-Use/Land-Cover Classification Based on Adaptive Differential Evolution Using Hyperspectral and LiDAR Data

Directory of Open Access Journals (Sweden)

Yanfei Zhong

2017-08-01

Full Text Available Hyperspectral images and light detection and ranging (LiDAR data have, respectively, the high spectral resolution and accurate elevation information required for urban land-use/land-cover (LULC classification. To combine the respective advantages of hyperspectral and LiDAR data, this paper proposes an optimal decision fusion method based on adaptive differential evolution, namely ODF-ADE, for urban LULC classification. In the ODF-ADE framework the normalized difference vegetation index (NDVI, gray-level co-occurrence matrix (GLCM and digital surface model (DSM are extracted to form the feature map. The three different classifiers of the maximum likelihood classifier (MLC, support vector machine (SVM and multinomial logistic regression (MLR are used to classify the extracted features. To find the optimal weights for the different classification maps, weighted voting is used to obtain the classification result and the weights of each classification map are optimized by the differential evolution algorithm which uses a self-adaptive strategy to obtain the parameter adaptively. The final classification map is obtained after post-processing based on conditional random fields (CRF. The experimental results confirm that the proposed algorithm is very effective in urban LULC classification.

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

Adaptive grid based multi-objective Cauchy differential evolution for stochastic dynamic economic emission dispatch with wind power uncertainty.

Science.gov (United States)

Zhang, Huifeng; Lei, Xiaohui; Wang, Chao; Yue, Dong; Xie, Xiangpeng

2017-01-01

Since wind power is integrated into the thermal power operation system, dynamic economic emission dispatch (DEED) has become a new challenge due to its uncertain characteristics. This paper proposes an adaptive grid based multi-objective Cauchy differential evolution (AGB-MOCDE) for solving stochastic DEED with wind power uncertainty. To properly deal with wind power uncertainty, some scenarios are generated to simulate those possible situations by dividing the uncertainty domain into different intervals, the probability of each interval can be calculated using the cumulative distribution function, and a stochastic DEED model can be formulated under different scenarios. For enhancing the optimization efficiency, Cauchy mutation operation is utilized to improve differential evolution by adjusting the population diversity during the population evolution process, and an adaptive grid is constructed for retaining diversity distribution of Pareto front. With consideration of large number of generated scenarios, the reduction mechanism is carried out to decrease the scenarios number with covariance relationships, which can greatly decrease the computational complexity. Moreover, the constraint-handling technique is also utilized to deal with the system load balance while considering transmission loss among thermal units and wind farms, all the constraint limits can be satisfied under the permitted accuracy. After the proposed method is simulated on three test systems, the obtained results reveal that in comparison with other alternatives, the proposed AGB-MOCDE can optimize the DEED problem while handling all constraint limits, and the optimal scheme of stochastic DEED can decrease the conservation of interval optimization, which can provide a more valuable optimal scheme for real-world applications.

Existence results for impulsive evolution differential equations with state-dependent delay

OpenAIRE

Eduardo Hernandez M.; Rathinasamy Sakthivel; Sueli Tanaka Aki

2008-01-01

We study the existence of mild solution for impulsive evolution abstract differential equations with state-dependent delay. A concrete application to partial delayed differential equations is considered.

Solving Partial Differential Equations Using a New Differential Evolution Algorithm

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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.

Differential Evolution Based IDWNN Controller for Fault Ride-Through of Grid-Connected Doubly Fed Induction Wind Generators.

Science.gov (United States)

Manonmani, N; Subbiah, V; Sivakumar, L

2015-01-01

The key objective of wind turbine development is to ensure that output power is continuously increased. It is authenticated that wind turbines (WTs) supply the necessary reactive power to the grid at the time of fault and after fault to aid the flowing grid voltage. At this juncture, this paper introduces a novel heuristic based controller module employing differential evolution and neural network architecture to improve the low-voltage ride-through rate of grid-connected wind turbines, which are connected along with doubly fed induction generators (DFIGs). The traditional crowbar-based systems were basically applied to secure the rotor-side converter during the occurrence of grid faults. This traditional controller is found not to satisfy the desired requirement, since DFIG during the connection of crowbar acts like a squirrel cage module and absorbs the reactive power from the grid. This limitation is taken care of in this paper by introducing heuristic controllers that remove the usage of crowbar and ensure that wind turbines supply necessary reactive power to the grid during faults. The controller is designed in this paper to enhance the DFIG converter during the grid fault and this controller takes care of the ride-through fault without employing any other hardware modules. The paper introduces a double wavelet neural network controller which is appropriately tuned employing differential evolution. To validate the proposed controller module, a case study of wind farm with 1.5 MW wind turbines connected to a 25 kV distribution system exporting power to a 120 kV grid through a 30 km 25 kV feeder is carried out by simulation.

Differential Evolution Based IDWNN Controller for Fault Ride-Through of Grid-Connected Doubly Fed Induction Wind Generators

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N. Manonmani

2015-01-01

Full Text Available The key objective of wind turbine development is to ensure that output power is continuously increased. It is authenticated that wind turbines (WTs supply the necessary reactive power to the grid at the time of fault and after fault to aid the flowing grid voltage. At this juncture, this paper introduces a novel heuristic based controller module employing differential evolution and neural network architecture to improve the low-voltage ride-through rate of grid-connected wind turbines, which are connected along with doubly fed induction generators (DFIGs. The traditional crowbar-based systems were basically applied to secure the rotor-side converter during the occurrence of grid faults. This traditional controller is found not to satisfy the desired requirement, since DFIG during the connection of crowbar acts like a squirrel cage module and absorbs the reactive power from the grid. This limitation is taken care of in this paper by introducing heuristic controllers that remove the usage of crowbar and ensure that wind turbines supply necessary reactive power to the grid during faults. The controller is designed in this paper to enhance the DFIG converter during the grid fault and this controller takes care of the ride-through fault without employing any other hardware modules. The paper introduces a double wavelet neural network controller which is appropriately tuned employing differential evolution. To validate the proposed controller module, a case study of wind farm with 1.5 MW wind turbines connected to a 25 kV distribution system exporting power to a 120 kV grid through a 30 km 25 kV feeder is carried out by simulation.

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.

Wavelength Selection Method Based on Differential Evolution for Precise Quantitative Analysis Using Terahertz Time-Domain Spectroscopy.

Science.gov (United States)

Li, Zhi; Chen, Weidong; Lian, Feiyu; Ge, Hongyi; Guan, Aihong

2017-12-01

Quantitative analysis of component mixtures is an important application of terahertz time-domain spectroscopy (THz-TDS) and has attracted broad interest in recent research. Although the accuracy of quantitative analysis using THz-TDS is affected by a host of factors, wavelength selection from the sample's THz absorption spectrum is the most crucial component. The raw spectrum consists of signals from the sample and scattering and other random disturbances that can critically influence the quantitative accuracy. For precise quantitative analysis using THz-TDS, the signal from the sample needs to be retained while the scattering and other noise sources are eliminated. In this paper, a novel wavelength selection method based on differential evolution (DE) is investigated. By performing quantitative experiments on a series of binary amino acid mixtures using THz-TDS, we demonstrate the efficacy of the DE-based wavelength selection method, which yields an error rate below 5%.

Parameter extraction of different fuel cell models with transferred adaptive differential evolution

International Nuclear Information System (INIS)

Gong, Wenyin; Yan, Xuesong; Liu, Xiaobo; Cai, Zhihua

2015-01-01

To improve the design and control of FC (fuel cell) models, it is important to extract their unknown parameters. Generally, the parameter extraction problems of FC models can be transformed as nonlinear and multi-variable optimization problems. To extract the parameters of different FC models exactly and fast, in this paper, we propose a transferred adaptive DE (differential evolution) framework, in which the successful parameters of the adaptive DE solving previous problems are properly transferred to solve new optimization problems in the similar problem-domains. Based on this framework, an improved adaptive DE method (TRADE, in short) is presented as an illustration. To verify the performance of our proposal, TRADE is used to extract the unknown parameters of two types of fuel cell models, i.e., PEMFC (proton exchange membrane fuel cell) and SOFC (solid oxide fuel cell). The results of TRADE are also compared with those of other state-of-the-art EAs (evolutionary algorithms). Even though the modification is very simple, the results indicate that TRADE can extract the parameters of both PEMFC and SOFC models exactly and fast. Moreover, the V–I characteristics obtained by TRADE agree well with the simulated and experimental data in all cases for both types of fuel cell models. Also, it improves the performance of the original adaptive DE significantly in terms of both the quality of final solutions and the convergence speed in all cases. Additionally, TRADE is able to provide better results compared with other EAs. - Highlights: • A framework of transferred adaptive differential evolution is proposed. • Based on the framework, an improved differential evolution (TRADE) is presented. • TRADE obtains very promising results to extract the parameters of PEMFC and SOFC models

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

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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.

An Efficient Binary Differential Evolution with Parameter Adaptation

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Dongli Jia

2013-04-01

Full Text Available Differential Evolution (DE has been applied to many scientific and engineering problems for its simplicity and efficiency. However, the standard DE cannot be used in a binary search space directly. This paper proposes an adaptive binary Differential Evolution algorithm, or ABDE, that has a similar framework as the standard DE but with an improved binary mutation strategy in which the best individual participates. To further enhance the search ability, the parameters of the ABDE are slightly disturbed in an adaptive manner. Experiments have been carried out by comparing ABDE with two binary DE variants, normDE and BDE, and the most used binary search technique, GA, on a set of 13 selected benchmark functions and the classical 0-1 knapsack problem. Results show that the ABDE performs better than, or at least comparable to, the other algorithms in terms of search ability, convergence speed, and solution accuracy.

Identification of fractional-order systems via a switching differential evolution subject to noise perturbations

Energy Technology Data Exchange (ETDEWEB)

Zhu, Wu, E-mail: dtzhuwu@gmail.com [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang, Jian-an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Tang, Yang, E-mail: yang.tang@pik-potsdam.de [Institute of Physics, Humboldt University, Berlin 12489 (Germany); Potsdam Institute for Climate Impact Research, Potsdam 14415 (Germany); Research Institute for Intelligent Control and System, Harbin Institute of Technology, Harbin 150006 (China); Zhang, Wenbing [Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hong Kong (China); Xu, Yulong [College of Information Science and Technology, Donghua University, Shanghai 201620 (China)

2012-10-01

In this Letter, a differential evolution variant, called switching DE (SDE), has been employed to estimate the orders and parameters in incommensurate fractional-order chaotic systems. The proposed algorithm includes a switching population utilization strategy, where the population size is adjusted dynamically based on the solution-searching status. Thus, this adaptive control method realizes the identification of fractional-order Lorenz, Lü and Chen systems in both deterministic and stochastic environments, respectively. Numerical simulations are provided, where comparisons are made with five other State-of-the-Art evolutionary algorithms (EAs) to verify the effectiveness of the proposed method. -- Highlights: ► Switching population utilization strategy is applied for differential evolution. ► The parameters are estimated in both deterministic and stochastic environments. ► Comparisons with five other EAs verify the effectiveness of the proposed method.

Identification of fractional-order systems via a switching differential evolution subject to noise perturbations

International Nuclear Information System (INIS)

Zhu, Wu; Fang, Jian-an; Tang, Yang; Zhang, Wenbing; Xu, Yulong

2012-01-01

In this Letter, a differential evolution variant, called switching DE (SDE), has been employed to estimate the orders and parameters in incommensurate fractional-order chaotic systems. The proposed algorithm includes a switching population utilization strategy, where the population size is adjusted dynamically based on the solution-searching status. Thus, this adaptive control method realizes the identification of fractional-order Lorenz, Lü and Chen systems in both deterministic and stochastic environments, respectively. Numerical simulations are provided, where comparisons are made with five other State-of-the-Art evolutionary algorithms (EAs) to verify the effectiveness of the proposed method. -- Highlights: ► Switching population utilization strategy is applied for differential evolution. ► The parameters are estimated in both deterministic and stochastic environments. ► Comparisons with five other EAs verify the effectiveness of the proposed method.

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

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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.

Contemporary evolution during invasion: evidence for differentiation, natural selection, and local adaptation.

Science.gov (United States)

Colautti, Robert I; Lau, Jennifer A

2015-05-01

Biological invasions are 'natural' experiments that can improve our understanding of contemporary evolution. We evaluate evidence for population differentiation, natural selection and adaptive evolution of invading plants and animals at two nested spatial scales: (i) among introduced populations (ii) between native and introduced genotypes. Evolution during invasion is frequently inferred, but rarely confirmed as adaptive. In common garden studies, quantitative trait differentiation is only marginally lower (~3.5%) among introduced relative to native populations, despite genetic bottlenecks and shorter timescales (i.e. millennia vs. decades). However, differentiation between genotypes from the native vs. introduced range is less clear and confounded by nonrandom geographic sampling; simulations suggest this causes a high false-positive discovery rate (>50%) in geographically structured populations. Selection differentials (¦s¦) are stronger in introduced than in native species, although selection gradients (¦β¦) are not, consistent with introduced species experiencing weaker genetic constraints. This could facilitate rapid adaptation, but evidence is limited. For example, rapid phenotypic evolution often manifests as geographical clines, but simulations demonstrate that nonadaptive trait clines can evolve frequently during colonization (~two-thirds of simulations). Additionally, QST-FST studies may often misrepresent the strength and form of natural selection acting during invasion. Instead, classic approaches in evolutionary ecology (e.g. selection analysis, reciprocal transplant, artificial selection) are necessary to determine the frequency of adaptive evolution during invasion and its influence on establishment, spread and impact of invasive species. These studies are rare but crucial for managing biological invasions in the context of global change. © 2015 John Wiley & Sons Ltd.

An Improved Differential Evolution Algorithm for Maritime Collision Avoidance Route Planning

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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.

A Differential Evolution Based MPPT Method for Photovoltaic Modules under Partial Shading Conditions

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Kok Soon Tey

2014-01-01

Full Text Available Partially shaded photovoltaic (PV modules have multiple peaks in the power-voltage (P-V characteristic curve and conventional maximum power point tracking (MPPT algorithm, such as perturbation and observation (P&O, which is unable to track the global maximum power point (GMPP accurately due to its localized search space. Therefore, this paper proposes a differential evolution (DE based optimization algorithm to provide the globalized search space to track the GMPP. The direction of mutation in the DE algorithm is modified to ensure that the mutation always converges to the best solution among all the particles in the generation. This helps to provide the rapid convergence of the algorithm. Simulation of the proposed PV system is carried out in PSIM and the results are compared to P&O algorithm. In the hardware implementation, a high step-up DC-DC converter is employed to verify the proposed algorithm experimentally on partial shading conditions, load variation, and solar intensity variation. The experimental results show that the proposed algorithm is able to converge to the GMPP within 1.2 seconds with higher efficiency than P&O.

Composite Differential Evolution with Modified Oracle Penalty Method for Constrained Optimization Problems

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Minggang Dong

2014-01-01

Full Text Available Motivated by recent advancements in differential evolution and constraints handling methods, this paper presents a novel modified oracle penalty function-based composite differential evolution (MOCoDE for constrained optimization problems (COPs. More specifically, the original oracle penalty function approach is modified so as to satisfy the optimization criterion of COPs; then the modified oracle penalty function is incorporated in composite DE. Furthermore, in order to solve more complex COPs with discrete, integer, or binary variables, a discrete variable handling technique is introduced into MOCoDE to solve complex COPs with mix variables. This method is assessed on eleven constrained optimization benchmark functions and seven well-studied engineering problems in real life. Experimental results demonstrate that MOCoDE achieves competitive performance with respect to some other state-of-the-art approaches in constrained optimization evolutionary algorithms. Moreover, the strengths of the proposed method include few parameters and its ease of implementation, rendering it applicable to real life. Therefore, MOCoDE can be an efficient alternative to solving constrained optimization problems.

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.

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.

A Hybrid Backtracking Search Optimization Algorithm with Differential Evolution

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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.

A DIFFERENTIAL EVOLUTION ALGORITHM DEVELOPED FOR A NURSE SCHEDULING PROBLEM

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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.

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

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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.

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.

Existence of solutions for quasilinear random impulsive neutral differential evolution equation

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B. Radhakrishnan

2018-07-01

Full Text Available This paper deals with the existence of solutions for quasilinear random impulsive neutral functional differential evolution equation in Banach spaces and the results are derived by using the analytic semigroup theory, fractional powers of operators and the Schauder fixed point approach. An application is provided to illustrate the theory. Keywords: Quasilinear differential equation, Analytic semigroup, Random impulsive neutral differential equation, Fixed point theorem, 2010 Mathematics Subject Classification: 34A37, 47H10, 47H20, 34K40, 34K45, 35R12

Long-term evolution and gravitational wave radiation of neutron stars with differential rotation induced by r-modes

International Nuclear Information System (INIS)

Yu Yunwei; Cao Xiaofeng; Zheng Xiaoping

2009-01-01

In a second-order r-mode theory, Sa and Tome found that the r-mode oscillation in neutron stars (NSs) could induce stellar differential rotation, which naturally leads to a saturated state of the oscillation. Based on a consideration of the coupling of the r-modes and the stellar spin and thermal evolution, we carefully investigate the influences of the differential rotation on the long-term evolution of isolated NSs and NSs in low-mass X-ray binaries, where the viscous damping of the r-modes and its resultant effects are taken into account. The numerical results show that, for both kinds of NSs, the differential rotation can significantly prolong the duration of the r-modes. As a result, the stars can keep nearly a constant temperature and constant angular velocity for over a thousand years. Moreover, the persistent radiation of a quasi-monochromatic gravitational wave would also be predicted due to the long-term steady r-mode oscillation and stellar rotation. This increases the detectability of gravitational waves from both young isolated and old accreting NSs. (research papers)

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.

A POPULATION MEMETICS APPROACH TO CULTURAL EVOLUTION IN CHAFFINCH SONG: DIFFERENTIATION AMONG POPULATIONS.

Science.gov (United States)

Lynch, Alejandro; Baker, Allan J

1994-04-01

We investigated cultural evolution in populations of common chaffinches (Fringilla coelebs) in the Atlantic islands (Azores, Madeira, and Canaries) and neighboring continental regions (Morocco and Iberia) by employing a population-memetic approach. To quantify differentiation, we used the concept of a song meme, defined as a single syllable or a series of linked syllables capable of being transmitted. The levels of cultural differentiation are higher among the Canaries populations than among the Azorean ones, even though the islands are on average closer to each other geographically. This is likely the result of reduced levels of migration, lower population sizes, and bottlenecks (possibly during the colonization of these populations) in the Canaries; all these factors produce a smaller effective population size and therefore accentuate the effects of differentiation by random drift. Significant levels of among-population differentiation in the Azores, in spite of substantial levels of migration, attest to the differentiating effects of high mutation rates of memes, which allow the accumulation of new mutants in different populations before migration can disperse them throughout the entire region. © 1994 The Society for the Study of Evolution.

Evidence of correlated evolution and adaptive differentiation of stem and leaf functional traits in the herbaceous genus, Helianthus.

Science.gov (United States)

Pilote, Alex J; Donovan, Lisa A

2016-12-01

Patterns of plant stem traits are expected to align with a "fast-slow" plant economic spectrum across taxa. Although broad patterns support such tradeoffs in field studies, tests of hypothesized correlated trait evolution and adaptive differentiation are more robust when taxa relatedness and environment are taken into consideration. Here we test for correlated evolution of stem and leaf traits and their adaptive differentiation across environments in the herbaceous genus, Helianthus. Stem and leaf traits of 14 species of Helianthus (28 populations) were assessed in a common garden greenhouse study. Phylogenetically independent contrasts were used to test for evidence of correlated evolution of stem hydraulic and biomechanical properties, correlated evolution of stem and leaf traits, and adaptive differentiation associated with source habitat environments. Among stem traits, there was evidence for correlated evolution of some hydraulic and biomechanical properties, supporting an expected tradeoff between stem theoretical hydraulic efficiency and resistance to bending stress. Population differentiation for suites of stem and leaf traits was found to be consistent with a "fast-slow" resource-use axis for traits related to water transport and use. Associations of population traits with source habitat characteristics supported repeated evolution of a resource-acquisitive "drought-escape" strategy in arid environments. This study provides evidence of correlated evolution of stem and leaf traits consistent with the fast-slow spectrum of trait combinations related to water transport and use along the stem-to-leaf pathway. Correlations of traits with source habitat characteristics further indicate that the correlated evolution is associated, at least in part, with adaptive differentiation of Helianthus populations among native habitats differing in climate. © 2016 Botanical Society of America.

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

Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds.

Science.gov (United States)

Uher, Vojtěch; Gajdoš, Petr; Radecký, Michal; Snášel, Václav

2016-01-01

The Differential Evolution (DE) is a widely used bioinspired optimization algorithm developed by Storn and Price. It is popular for its simplicity and robustness. This algorithm was primarily designed for real-valued problems and continuous functions, but several modified versions optimizing both integer and discrete-valued problems have been developed. The discrete-coded DE has been mostly used for combinatorial problems in a set of enumerative variants. However, the DE has a great potential in the spatial data analysis and pattern recognition. This paper formulates the problem as a search of a combination of distinct vertices which meet the specified conditions. It proposes a novel approach called the Multidimensional Discrete Differential Evolution (MDDE) applying the principle of the discrete-coded DE in discrete point clouds (PCs). The paper examines the local searching abilities of the MDDE and its convergence to the global optimum in the PCs. The multidimensional discrete vertices cannot be simply ordered to get a convenient course of the discrete data, which is crucial for good convergence of a population. A novel mutation operator utilizing linear ordering of spatial data based on the space filling curves is introduced. The algorithm is tested on several spatial datasets and optimization problems. The experiments show that the MDDE is an efficient and fast method for discrete optimizations in the multidimensional point clouds.

Size evolution of ultrafine particles: Differential signatures of normal and episodic events

International Nuclear Information System (INIS)

Joshi, Manish; Khan, Arshad; Anand, S.; Sapra, B.K.

2016-01-01

The effect of fireworks on the aerosol number characteristics of atmosphere was studied for an urban mega city. Measurements were made at 50 m height to assess the local changes around the festival days. Apart from the increase in total number concentration and characteristic accumulation mode, short-term increase of ultrafine particle concentration was noted. Total number concentration varies an order of magnitude during the measurement period in which peak occurs at a frequency of approximately one per day. On integral scale, it seems not possible to distinguish an episodic (e.g. firework bursting induced aerosol emission) and a normal (ambient atmospheric changes) event. However these events could be differentiated on the basis of size evolution analysis around number concentration peaks. The results are discussed relative to past studies and inferences are drawn towards aerosol signatures of firework bursting. The short-term burst in ultrafine particle concentration can pose an inhalation hazard. - Highlights: • Effect of firework emissions on atmospheric aerosol characteristics was studied. • Significant increase in ultrafine particle concentration was observed during firework bursting. • Size distribution evolution analysis of number concentration peaks has been performed. • Differential signatures of normal and episodic event were noted. - Notable increase in ultrafine particle concentration during firework bursting was seen. Normal and episodic event could be differentiated on the basis of size evolution analysis.

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.

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.

Kullback-Leibler Divergence-Based Differential Evolution Markov Chain Filter for Global Localization of Mobile Robots.

Science.gov (United States)

Martín, Fernando; Moreno, Luis; Garrido, Santiago; Blanco, Dolores

2015-09-16

One of the most important skills desired for a mobile robot is the ability to obtain its own location even in challenging environments. The information provided by the sensing system is used here to solve the global localization problem. In our previous work, we designed different algorithms founded on evolutionary strategies in order to solve the aforementioned task. The latest developments are presented in this paper. The engine of the localization module is a combination of the Markov chain Monte Carlo sampling technique and the Differential Evolution method, which results in a particle filter based on the minimization of a fitness function. The robot's pose is estimated from a set of possible locations weighted by a cost value. The measurements of the perceptive sensors are used together with the predicted ones in a known map to define a cost function to optimize. Although most localization methods rely on quadratic fitness functions, the sensed information is processed asymmetrically in this filter. The Kullback-Leibler divergence is the basis of a cost function that makes it possible to deal with different types of occlusions. The algorithm performance has been checked in a real map. The results are excellent in environments with dynamic and unmodeled obstacles, a fact that causes occlusions in the sensing area.

Existence of mild solutions of a semilinear evolution differential inclusions with nonlocal conditions

Directory of Open Access Journals (Sweden)

Reem A. Al-Omair

2009-03-01

Full Text Available In this paper we prove the existence of a mild solution for a semilinear evolution differential inclusion with nonlocal condition and governed by a family of linear operators, not necessarily bounded or closed, in a Banach space. No compactness assumption is assumed on the evolution operator generated by the family operators. Also, we prove that the set of mild solutions is compact.

Differential paralog divergence modulates genome evolution across yeast species.

Directory of Open Access Journals (Sweden)

Monica R Sanchez

2017-02-01

Full Text Available Evolutionary outcomes depend not only on the selective forces acting upon a species, but also on the genetic background. However, large timescales and uncertain historical selection pressures can make it difficult to discern such important background differences between species. Experimental evolution is one tool to compare evolutionary potential of known genotypes in a controlled environment. Here we utilized a highly reproducible evolutionary adaptation in Saccharomyces cerevisiae to investigate whether experimental evolution of other yeast species would select for similar adaptive mutations. We evolved populations of S. cerevisiae, S. paradoxus, S. mikatae, S. uvarum, and interspecific hybrids between S. uvarum and S. cerevisiae for ~200-500 generations in sulfate-limited continuous culture. Wild-type S. cerevisiae cultures invariably amplify the high affinity sulfate transporter gene, SUL1. However, while amplification of the SUL1 locus was detected in S. paradoxus and S. mikatae populations, S. uvarum cultures instead selected for amplification of the paralog, SUL2. We measured the relative fitness of strains bearing deletions and amplifications of both SUL genes from different species, confirming that, converse to S. cerevisiae, S. uvarum SUL2 contributes more to fitness in sulfate limitation than S. uvarum SUL1. By measuring the fitness and gene expression of chimeric promoter-ORF constructs, we were able to delineate the cause of this differential fitness effect primarily to the promoter of S. uvarum SUL1. Our data show evidence of differential sub-functionalization among the sulfate transporters across Saccharomyces species through recent changes in noncoding sequence. Furthermore, these results show a clear example of how such background differences due to paralog divergence can drive changes in genome evolution.

Many-Objective Distinct Candidates Optimization using Differential Evolution

DEFF Research Database (Denmark)

Justesen, Peter; Ursem, Rasmus Kjær

2010-01-01

for each objective. The Many-Objective Distinct Candidates Optimization using Differential Evolution (MODCODE) algorithm takes a novel approach by focusing search using a user-defined number of subpopulations each returning a distinct optimal solution within the preferred region of interest. In this paper......, we present the novel MODCODE algorithm incorporating the ROD measure to measure and control candidate distinctiveness. MODCODE is tested against GDE3 on three real world centrifugal pump design problems supplied by Grundfos. Our algorithm outperforms GDE3 on all problems with respect to all...

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 ...

Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling

Energy Technology Data Exchange (ETDEWEB)

Vrugt, Jasper A [Los Alamos National Laboratory; Hyman, James M [Los Alamos National Laboratory; Robinson, Bruce A [Los Alamos National Laboratory; Higdon, Dave [Los Alamos National Laboratory; Ter Braak, Cajo J F [NETHERLANDS; Diks, Cees G H [UNIV OF AMSTERDAM

2008-01-01

Markov chain Monte Carlo (MCMC) methods have found widespread use in many fields of study to estimate the average properties of complex systems, and for posterior inference in a Bayesian framework. Existing theory and experiments prove convergence of well constructed MCMC schemes to the appropriate limiting distribution under a variety of different conditions. In practice, however this convergence is often observed to be disturbingly slow. This is frequently caused by an inappropriate selection of the proposal distribution used to generate trial moves in the Markov Chain. Here we show that significant improvements to the efficiency of MCMC simulation can be made by using a self-adaptive Differential Evolution learning strategy within a population-based evolutionary framework. This scheme, entitled DiffeRential Evolution Adaptive Metropolis or DREAM, runs multiple different chains simultaneously for global exploration, and automatically tunes the scale and orientation of the proposal distribution in randomized subspaces during the search. Ergodicity of the algorithm is proved, and various examples involving nonlinearity, high-dimensionality, and multimodality show that DREAM is generally superior to other adaptive MCMC sampling approaches. The DREAM scheme significantly enhances the applicability of MCMC simulation to complex, multi-modal search problems.

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.

Kullback-Leibler Divergence-Based Differential Evolution Markov Chain Filter for Global Localization of Mobile Robots

Directory of Open Access Journals (Sweden)

Fernando Martín

2015-09-01

Full Text Available One of the most important skills desired for a mobile robot is the ability to obtain its own location even in challenging environments. The information provided by the sensing system is used here to solve the global localization problem. In our previous work, we designed different algorithms founded on evolutionary strategies in order to solve the aforementioned task. The latest developments are presented in this paper. The engine of the localization module is a combination of the Markov chain Monte Carlo sampling technique and the Differential Evolution method, which results in a particle filter based on the minimization of a fitness function. The robot’s pose is estimated from a set of possible locations weighted by a cost value. The measurements of the perceptive sensors are used together with the predicted ones in a known map to define a cost function to optimize. Although most localization methods rely on quadratic fitness functions, the sensed information is processed asymmetrically in this filter. The Kullback-Leibler divergence is the basis of a cost function that makes it possible to deal with different types of occlusions. The algorithm performance has been checked in a real map. The results are excellent in environments with dynamic and unmodeled obstacles, a fact that causes occlusions in the sensing area.

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

Science.gov (United States)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. These approaches are implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

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

Gradient decent based multi-objective cultural differential evolution for short-term hydrothermal optimal scheduling of economic emission with integrating wind power and photovoltaic power

International Nuclear Information System (INIS)

Zhang, Huifeng; Yue, Dong; Xie, Xiangpeng; Dou, Chunxia; Sun, Feng

2017-01-01

With the integration of wind power and photovoltaic power, optimal operation of hydrothermal power system becomes great challenge due to its non-convex, stochastic and complex-coupled constrained characteristics. This paper extends short-term hydrothermal system optimal model into short-term hydrothermal optimal scheduling of economic emission while considering integrated intermittent energy resources (SHOSEE-IIER). For properly solving SHOSEE-IIER problem, a gradient decent based multi-objective cultural differential evolution (GD-MOCDE) is proposed to improve the optimal efficiency of SHOSEE-IIER combined with three designed knowledge structures, which mainly enhances search ability of differential evolution in the shortest way. With considering those complex-coupled and stochastic constraints, a heuristic constraint-handling measurement is utilized to tackle with them both in coarse and fine tuning way, and probability constraint-handling procedures are taken to properly handle those stochastic constraints combined with their probability density functions. Ultimately, those approaches are implemented on five test systems, which testify the optimization efficiency of proposed GD-MOCDE and constraint-handling efficiency for system load balance, water balance and stochastic constraint-handling measurements, those obtained results reveal that the proposed GD-MOCDE can properly solve the SHOSEE-IIER problem combined with those constraint-handling approaches. - Highlights: • Gradient decent method is proposed to improve mutation operator. • Hydrothermal system is extended to hybrid energy system. • The uncertainty constraint is converted into deterministic constraint. • The results show the viability and efficiency of proposed algorithm.

A Global Multi-Objective Optimization Tool for Design of Mechatronic Components using Generalized Differential Evolution

DEFF Research Database (Denmark)

Bech, Michael Møller; Nørgård, Christian; Roemer, Daniel Beck

2016-01-01

This paper illustrates how the relatively simple constrained multi-objective optimization algorithm Generalized Differential Evolution 3 (GDE3), can assist with the practical sizing of mechatronic components used in e.g. digital displacement fluid power machinery. The studied bi- and tri-objectiv......This paper illustrates how the relatively simple constrained multi-objective optimization algorithm Generalized Differential Evolution 3 (GDE3), can assist with the practical sizing of mechatronic components used in e.g. digital displacement fluid power machinery. The studied bi- and tri...... different optimization control parameter settings and it is concluded that GDE3 is a reliable optimization tool that can assist mechatronic engineers in the design and decision making process....

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.

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...

Non-dominated sorting binary differential evolution for the multi-objective optimization of cascading failures protection in complex networks

International Nuclear Information System (INIS)

Li, Y.F.; Sansavini, G.; Zio, E.

2013-01-01

A number of research works have been devoted to the optimization of protection strategies (e.g. transmission line switch off) of critical infrastructures (e.g. power grids, telecommunication networks, computer networks, etc) to avoid cascading failures. This work aims at improving a previous optimization approach proposed by some of the authors [1], based on the modified binary differential evolution (MBDE) algorithm. The improvements are three-fold: (1) in the optimization problem formulation, we introduce a third objective function to minimize the impacts of the switching off operations onto the existing network topology; (2) in the optimization problem formulation, we use the final results of cascades, rather than only a short horizon of one step cascading, to evaluate the effects of the switching off strategies; (3) in the optimization algorithm, the fast non-dominated sorting mechanisms are incorporated into the MBDE algorithm: a new algorithm, namely non-dominated sorting binary differential evolution algorithm (NSBDE) is then proposed. The numerical application to the topological structure of the 380 kV Italian power transmission network proves the benefits of the improvements.

Application of enhanced discrete differential evolution approach to unit commitment problem

International Nuclear Information System (INIS)

Yuan Xiaohui; Su Anjun; Nie Hao; Yuan Yanbin; Wang Liang

2009-01-01

This paper proposes a discrete binary differential evolution (DBDE) approach to solve the unit commitment problem (UCP). The proposed method is enhanced by priority list based on the unit characteristics and heuristic search strategies to handle constraints effectively. The implementation of the proposed method for UCP consists of three stages. Firstly, the DBDE based on priority list is applied for unit scheduling when neglecting the minimum up/down time constraints. Secondly, repairing strategies are used to handle the minimum up/down time constraints and decommit excess spinning reserve units. Finally, heuristic unit substitution search and gray zone modification algorithm are used to improve optimal solution further. Furthermore, the effects of two crucial parameters on performance of the DBDE for solving UCP are studied as well. To verify the advantages of the method, the proposed method is tested and compared to the other methods on the systems with the number of units in the range of 10-100. Numerical results demonstrate that the proposed method is superior to other methods reported in the literature.

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.

Aerodynamic optimization of supersonic compressor cascade using differential evolution on GPU

Energy Technology Data Exchange (ETDEWEB)

Aissa, Mohamed Hasanine; Verstraete, Tom [Von Karman Institute for Fluid Dynamics (VKI) 1640 Sint-Genesius-Rode (Belgium); Vuik, Cornelis [Delft University of Technology 2628 CD Delft (Netherlands)

2016-06-08

Differential Evolution (DE) is a powerful stochastic optimization method. Compared to gradient-based algorithms, DE is able to avoid local minima but requires at the same time more function evaluations. In turbomachinery applications, function evaluations are performed with time-consuming CFD simulation, which results in a long, non affordable, design cycle. Modern High Performance Computing systems, especially Graphic Processing Units (GPUs), are able to alleviate this inconvenience by accelerating the design evaluation itself. In this work we present a validated CFD Solver running on GPUs, able to accelerate the design evaluation and thus the entire design process. An achieved speedup of 20x to 30x enabled the DE algorithm to run on a high-end computer instead of a costly large cluster. The GPU-enhanced DE was used to optimize the aerodynamics of a supersonic compressor cascade, achieving an aerodynamic loss minimization of 20%.

Global expression differences and tissue specific expression differences in rice evolution result in two contrasting types of differentially expressed genes

KAUST Repository

Horiuchi, Youko

2015-12-23

Background Since the development of transcriptome analysis systems, many expression evolution studies characterized evolutionary forces acting on gene expression, without explicit discrimination between global expression differences and tissue specific expression differences. However, different types of gene expression alteration should have different effects on an organism, the evolutionary forces that act on them might be different, and different types of genes might show different types of differential expression between species. To confirm this, we studied differentially expressed (DE) genes among closely related groups that have extensive gene expression atlases, and clarified characteristics of different types of DE genes including the identification of regulating loci for differential expression using expression quantitative loci (eQTL) analysis data. Results We detected differentially expressed (DE) genes between rice subspecies in five homologous tissues that were verified using japonica and indica transcriptome atlases in public databases. Using the transcriptome atlases, we classified DE genes into two types, global DE genes and changed-tissues DE genes. Global type DE genes were not expressed in any tissues in the atlas of one subspecies, however changed-tissues type DE genes were expressed in both subspecies with different tissue specificity. For the five tissues in the two japonica-indica combinations, 4.6 ± 0.8 and 5.9 ± 1.5 % of highly expressed genes were global and changed-tissues DE genes, respectively. Changed-tissues DE genes varied in number between tissues, increasing linearly with the abundance of tissue specifically expressed genes in the tissue. Molecular evolution of global DE genes was rapid, unlike that of changed-tissues DE genes. Based on gene ontology, global and changed-tissues DE genes were different, having no common GO terms. Expression differences of most global DE genes were regulated by cis-eQTLs. Expression

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.

Rolling Force Prediction in Heavy Plate Rolling Based on Uniform Differential Neural Network

Directory of Open Access Journals (Sweden)

Fei Zhang

2016-01-01

Full Text Available Accurate prediction of the rolling force is critical to assuring the quality of the final product in steel manufacturing. Exit thickness of plate for each pass is calculated from roll gap, mill spring, and predicted roll force. Ideal pass scheduling is dependent on a precise prediction of the roll force in each pass. This paper will introduce a concept that allows obtaining the material model parameters directly from the rolling process on an industrial scale by the uniform differential neural network. On the basis of the characteristics that the uniform distribution can fully characterize the solution space and enhance the diversity of the population, uniformity research on differential evolution operator is made to get improved crossover with uniform distribution. When its original function is transferred with a transfer function, the uniform differential evolution algorithms can quickly solve complex optimization problems. Neural network structure and weights threshold are optimized by uniform differential evolution algorithm, and a uniform differential neural network is formed to improve rolling force prediction accuracy in process control system.

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

Myeloma Cell Dynamics in Response to Treatment Supports a Model of Hierarchical Differentiation and Clonal Evolution.

Science.gov (United States)

Tang, Min; Zhao, Rui; van de Velde, Helgi; Tross, Jennifer G; Mitsiades, Constantine; Viselli, Suzanne; Neuwirth, Rachel; Esseltine, Dixie-Lee; Anderson, Kenneth; Ghobrial, Irene M; San Miguel, Jesús F; Richardson, Paul G; Tomasson, Michael H; Michor, Franziska

2016-08-15

Since the pioneering work of Salmon and Durie, quantitative measures of tumor burden in multiple myeloma have been used to make clinical predictions and model tumor growth. However, such quantitative analyses have not yet been performed on large datasets from trials using modern chemotherapy regimens. We analyzed a large set of tumor response data from three randomized controlled trials of bortezomib-based chemotherapy regimens (total sample size n = 1,469 patients) to establish and validate a novel mathematical model of multiple myeloma cell dynamics. Treatment dynamics in newly diagnosed patients were most consistent with a model postulating two tumor cell subpopulations, "progenitor cells" and "differentiated cells." Differential treatment responses were observed with significant tumoricidal effects on differentiated cells and less clear effects on progenitor cells. We validated this model using a second trial of newly diagnosed patients and a third trial of refractory patients. When applying our model to data of relapsed patients, we found that a hybrid model incorporating both a differentiation hierarchy and clonal evolution best explains the response patterns. The clinical data, together with mathematical modeling, suggest that bortezomib-based therapy exerts a selection pressure on myeloma cells that can shape the disease phenotype, thereby generating further inter-patient variability. This model may be a useful tool for improving our understanding of disease biology and the response to chemotherapy regimens. Clin Cancer Res; 22(16); 4206-14. ©2016 AACR. ©2016 American Association for Cancer Research.

Chaos Enhanced Differential Evolution in the Task of Evolutionary Control of Selected Set of Discrete Chaotic Systems

Directory of Open Access Journals (Sweden)

Roman Senkerik

2014-01-01

Full Text Available Evolutionary technique differential evolution (DE is used for the evolutionary tuning of controller parameters for the stabilization of set of different chaotic systems. The novelty of the approach is that the selected controlled discrete dissipative chaotic system is used also as the chaotic pseudorandom number generator to drive the mutation and crossover process in the DE. The idea was to utilize the hidden chaotic dynamics in pseudorandom sequences given by chaotic map to help differential evolution algorithm search for the best controller settings for the very same chaotic system. The optimizations were performed for three different chaotic systems, two types of case studies and developed cost functions.

Optimization of ultrasonic arrays design and setting using a differential evolution

International Nuclear Information System (INIS)

Puel, B.; Chatillon, S.; Calmon, P.; Lesselier, D.

2011-01-01

Optimization of both design and setting of phased arrays could be not so easy when they are performed manually via parametric studies. An optimization method based on an Evolutionary Algorithm and numerical simulation is proposed and evaluated. The Randomized Adaptive Differential Evolution has been adapted to meet the specificities of the non-destructive testing applications. In particular, the solution of multi-objective problems is aimed at with the implementation of the concept of pareto-optimal sets of solutions. The algorithm has been implemented and connected to the ultrasonic simulation modules of the CIVA software used as forward model. The efficiency of the method is illustrated on two realistic cases of application: optimization of the position and delay laws of a flexible array inspecting a nozzle, considered as a mono-objective problem; and optimization of the design of a surrounded array and its delay laws, considered as a constrained bi-objective problem. (authors)

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

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.

Differential rates of genic and chromosomal evolution in bats of the family Rhinolophidae.

Science.gov (United States)

Qumsiyeh, M B; Owen, R D; Chesser, R K

1988-06-01

Data for nondifferentially stained chromosomes from 10 species of Rhinolophus (Chiroptera: Rhinolophidae) suggest a conserved chromosomal evolution. G-banded chromosomes for three well differentiated species (Rhinolophus hipposideros, Rhinolophus blasii, and Rhinolophus acuminatus) corroborate a low level of gross chromosomal rearrangements. Additionally, a comparison between G-banded chromosomes of Rhinolophus (Rhinolophidae) and Hipposideros (Hipposideridae) suggests extreme conservatism in chromosomal arms between these two distantly related groups. On the other hand, we report extensive genic divergence as assayed by starch gel electrophoresis among these 10 species, and between Rhinolophus and two hipposiderid genera (Hipposideros and Aselliscus). The present chromosomal data are not sufficient for phylogenetic analysis. Phylogenies based on electrophoretic data are in many aspects discordant with those based on the classical morphological criteria. Different (and as yet not clearly understood) evolutionary forces affecting chromosomal, morphologic, and electrophoretic variation may be the reason for the apparent lack of concordance in these independent data sets.

Aerodynamic Shape Optimization Using Hybridized Differential Evolution

Science.gov (United States)

Madavan, Nateri K.

2003-01-01

An aerodynamic shape optimization method that uses an evolutionary algorithm known at Differential Evolution (DE) in conjunction with various hybridization strategies is described. DE is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Various hybridization strategies for DE are explored, including the use of neural networks as well as traditional local search methods. A Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the hybrid DE optimizer. The method is implemented on distributed parallel computers so that new designs can be obtained within reasonable turnaround times. Results are presented for the inverse design of a turbine airfoil from a modern jet engine. (The final paper will include at least one other aerodynamic design application). The capability of the method to search large design spaces and obtain the optimal airfoils in an automatic fashion is demonstrated.

Chaos Enhanced Differential Evolution in the Task of Evolutionary Control of Discrete Chaotic LOZI Map

Directory of Open Access Journals (Sweden)

Roman Senkerik

2016-01-01

Full Text Available In this paper, evolutionary technique Differential Evolution (DE is used for the evolutionary tuning of controller parameters for the stabilization of selected discrete chaotic system, which is the two-dimensional Lozi map. The novelty of the approach is that the selected controlled discrete dissipative chaotic system is used within Chaos enhanced heuristic concept as the chaotic pseudo-random number generator to drive the mutation and crossover process in the DE. The idea was to utilize the hidden chaotic dynamics in pseudo-random sequences given by chaotic map to help Differential evolution algorithm in searching for the best controller settings for the same chaotic system. The optimizations were performed for three different required final behavior of the chaotic system, and two types of developed cost function. To confirm the robustness of presented approach, comparisons with canonical DE strategy and PSO algorithm have been performed.

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.

An accurate modelling of the two-diode model of PV module using a hybrid solution based on differential evolution

International Nuclear Information System (INIS)

Chin, Vun Jack; Salam, Zainal; Ishaque, Kashif

2016-01-01

Highlights: • An accurate computational method for the two-diode model of PV module is proposed. • The hybrid method employs analytical equations and Differential Evolution (DE). • I PV , I o1 , and R p are computed analytically, while a 1 , a 2 , I o2 and R s are optimized. • This allows the model parameters to be computed without using costly assumptions. - Abstract: This paper proposes an accurate computational technique for the two-diode model of PV module. Unlike previous methods, it does not rely on assumptions that cause the accuracy to be compromised. The key to this improvement is the implementation of a hybrid solution, i.e. by incorporating the analytical method with the differential evolution (DE) optimization technique. Three parameters, i.e. I PV , I o1 , and R p are computed analytically, while the remaining, a 1 , a 2 , I o2 and R s are optimized using the DE. To validate its accuracy, the proposed method is tested on three PV modules of different technologies: mono-crystalline, poly-crystalline and thin film. Furthermore, its performance is evaluated against two popular computational methods for the two-diode model. The proposed method is found to exhibit superior accuracy for the variation in irradiance and temperature for all module types. In particular, the improvement in accuracy is evident at low irradiance conditions; the root-mean-square error is one order of magnitude lower than that of the other methods. In addition, the values of the model parameters are consistent with the physics of PV cell. It is envisaged that the method can be very useful for PV simulation, in which accuracy of the model is of prime concern.

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.

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

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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.

Micro-droplet based directed evolution outperforms conventional laboratory evolution

DEFF Research Database (Denmark)

Sjostrom, Staffan L.; Huang, Mingtao; Nielsen, Jens

2014-01-01

We present droplet adaptive laboratory evolution (DrALE), a directed evolution method used to improve industrial enzyme producing microorganisms for e.g. feedstock digestion. DrALE is based linking a desired phenotype to growth rate allowing only desired cells to proliferate. Single cells are con...... a whole-genome mutated library of yeast cells for α-amylase activity....

Multi-Objective Differential Evolution for Voltage Security Constrained Optimal Power Flow in Deregulated Power Systems

Science.gov (United States)

Roselyn, J. Preetha; Devaraj, D.; Dash, Subhransu Sekhar

2013-11-01

Voltage stability is an important issue in the planning and operation of deregulated power systems. The voltage stability problems is a most challenging one for the system operators in deregulated power systems because of the intense use of transmission line capabilities and poor regulation in market environment. This article addresses the congestion management problem avoiding offline transmission capacity limits related to voltage stability by considering Voltage Security Constrained Optimal Power Flow (VSCOPF) problem in deregulated environment. This article presents the application of Multi Objective Differential Evolution (MODE) algorithm to solve the VSCOPF problem in new competitive power systems. The maximum of L-index of the load buses is taken as the indicator of voltage stability and is incorporated in the Optimal Power Flow (OPF) problem. The proposed method in hybrid power market which also gives solutions to voltage stability problems by considering the generation rescheduling cost and load shedding cost which relieves the congestion problem in deregulated environment. The buses for load shedding are selected based on the minimum eigen value of Jacobian with respect to the load shed. In the proposed approach, real power settings of generators in base case and contingency cases, generator bus voltage magnitudes, real and reactive power demands of selected load buses using sensitivity analysis are taken as the control variables and are represented as the combination of floating point numbers and integers. DE/randSF/1/bin strategy scheme of differential evolution with self-tuned parameter which employs binomial crossover and difference vector based mutation is used for the VSCOPF problem. A fuzzy based mechanism is employed to get the best compromise solution from the pareto front to aid the decision maker. The proposed VSCOPF planning model is implemented on IEEE 30-bus system, IEEE 57 bus practical system and IEEE 118 bus system. The pareto optimal

Supplementary Material for: Global expression differences and tissue specific expression differences in rice evolution result in two contrasting types of differentially expressed genes

KAUST Repository

Horiuchi, Youko; Harushima, Yoshiaki; Fujisawa, Hironori; Mochizuki, Takako; Fujita, Masahiro; Ohyanagi, Hajime; Kurata, Nori

2015-01-01

Abstract Background Since the development of transcriptome analysis systems, many expression evolution studies characterized evolutionary forces acting on gene expression, without explicit discrimination between global expression differences and tissue specific expression differences. However, different types of gene expression alteration should have different effects on an organism, the evolutionary forces that act on them might be different, and different types of genes might show different types of differential expression between species. To confirm this, we studied differentially expressed (DE) genes among closely related groups that have extensive gene expression atlases, and clarified characteristics of different types of DE genes including the identification of regulating loci for differential expression using expression quantitative loci (eQTL) analysis data. Results We detected differentially expressed (DE) genes between rice subspecies in five homologous tissues that were verified using japonica and indica transcriptome atlases in public databases. Using the transcriptome atlases, we classified DE genes into two types, global DE genes and changed-tissues DE genes. Global type DE genes were not expressed in any tissues in the atlas of one subspecies, however changed-tissues type DE genes were expressed in both subspecies with different tissue specificity. For the five tissues in the two japonica-indica combinations, 4.6 ± 0.8 and 5.9 ± 1.5 % of highly expressed genes were global and changed-tissues DE genes, respectively. Changed-tissues DE genes varied in number between tissues, increasing linearly with the abundance of tissue specifically expressed genes in the tissue. Molecular evolution of global DE genes was rapid, unlike that of changed-tissues DE genes. Based on gene ontology, global and changed-tissues DE genes were different, having no common GO terms. Expression differences of most global DE genes were regulated by cis

Parsing parallel evolution: ecological divergence and differential gene expression in the adaptive radiations of thick-lipped Midas cichlid fishes from Nicaragua.

Science.gov (United States)

Manousaki, Tereza; Hull, Pincelli M; Kusche, Henrik; Machado-Schiaffino, Gonzalo; Franchini, Paolo; Harrod, Chris; Elmer, Kathryn R; Meyer, Axel

2013-02-01

The study of parallel evolution facilitates the discovery of common rules of diversification. Here, we examine the repeated evolution of thick lips in Midas cichlid fishes (the Amphilophus citrinellus species complex)-from two Great Lakes and two crater lakes in Nicaragua-to assess whether similar changes in ecology, phenotypic trophic traits and gene expression accompany parallel trait evolution. Using next-generation sequencing technology, we characterize transcriptome-wide differential gene expression in the lips of wild-caught sympatric thick- and thin-lipped cichlids from all four instances of repeated thick-lip evolution. Six genes (apolipoprotein D, myelin-associated glycoprotein precursor, four-and-a-half LIM domain protein 2, calpain-9, GTPase IMAP family member 8-like and one hypothetical protein) are significantly underexpressed in the thick-lipped morph across all four lakes. However, other aspects of lips' gene expression in sympatric morphs differ in a lake-specific pattern, including the magnitude of differentially expressed genes (97-510). Generally, fewer genes are differentially expressed among morphs in the younger crater lakes than in those from the older Great Lakes. Body shape, lower pharyngeal jaw size and shape, and stable isotopes (δ(13)C and δ(15)N) differ between all sympatric morphs, with the greatest differentiation in the Great Lake Nicaragua. Some ecological traits evolve in parallel (those related to foraging ecology; e.g. lip size, body and head shape) but others, somewhat surprisingly, do not (those related to diet and food processing; e.g. jaw size and shape, stable isotopes). Taken together, this case of parallelism among thick- and thin-lipped cichlids shows a mosaic pattern of parallel and nonparallel evolution. © 2012 Blackwell Publishing Ltd.

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.

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.

Differential Evolution between Monotocous and Polytocous Species

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Hyeonju Ahn

2014-04-01

Full Text Available One of the most important traits for both animal science and livestock production is the number of offspring for a species. This study was performed to identify differentially evolved genes and their distinct functions that influence the number of offspring at birth by comparative analysis of eight monotocous mammals and seven polytocous mammals in a number of scopes: specific amino acid substitution with site-wise adaptive evolution, gene expansion and specific orthologous group. The mutually exclusive amino acid substitution among the 16 mammalian species identified five candidate genes. These genes were both directly and indirectly related to ovulation. Furthermore, in monotocous mammals, the EPH gene family was found to have undergone expansion. Previously, the EPHA4 gene was found to positively affect litter size in pigs and supports the possibility of the EPH gene playing a role in determining the number of offspring per birth. The identified genes in this study offer a basis from which the differences between monotocous and polytocous species can be studied. Furthermore, these genes may harbor some clues to the underlying mechanism, which determines litter size and may prove useful for livestock breeding strategies.

Multi-objective optimization of coal-fired power plants using differential evolution

International Nuclear Information System (INIS)

Wang, Ligang; Yang, Yongping; Dong, Changqing; Morosuk, Tatiana; Tsatsaronis, George

2014-01-01

Highlights: • Multi-objective optimization of large-scale coal-fired power plants using differential evolution. • A newly-proposed algorithm for searching the fronts of decision space in a single run. • A reduction of cost of electricity by 2–4% with an optimal efficiency increase up to 2% points. • The uncertainty comes mainly from temperature- and reheat-related cost factors of steam generator. • An exergoeconomic analysis and comparison between optimal designs and one real industrial design. - Abstract: The design trade-offs between thermodynamics and economics for thermal systems can be studied with the aid of multi-objective optimization techniques. The investment costs usually increase with increasing thermodynamic performance of a system. In this paper, an enhanced differential evolution with diversity-preserving and density-adjusting mechanisms, and a newly-proposed algorithm for searching the decision space frontier in a single run were used, to conduct the multi-objective optimization of large-scale, supercritical coal-fired plants. The uncertainties associated with cost functions were discussed by analyzing the sensitivity of the decision space frontier to some significant parameters involved in cost functions. Comparisons made with the aid of an exergoeconomic analysis between the cost minimum designs and a real industrial design demonstrated how the plant improvement was achieved. It is concluded that the cost of electricity could be reduced by a 2–4%, whereas the efficiency could be increased by up to two percentage points. The largest uncertainty is introduced by the temperature-related and reheat-related cost coefficients of the steam generator. More reliable data on the price prediction of future advanced materials should be used to obtain more accurate fronts of the objective space

[The motive force of evolution based on the principle of organismal adjustment evolution.].

Science.gov (United States)

Cao, Jia-Shu

2010-08-01

From the analysis of the existing problems of the prevalent theories of evolution, this paper discussed the motive force of evolution based on the knowledge of the principle of organismal adjustment evolution to get a new understanding of the evolution mechanism. In the guide of Schrodinger's theory - "life feeds on negative entropy", the author proposed that "negative entropy flow" actually includes material flow, energy flow and information flow, and the "negative entropy flow" is the motive force for living and development. By modifying my own theory of principle of organismal adjustment evolution (not adaptation evolution), a new theory of "regulation system of organismal adjustment evolution involved in DNA, RNA and protein interacting with environment" is proposed. According to the view that phylogenetic development is the "integral" of individual development, the difference of negative entropy flow between organisms and environment is considered to be a motive force for evolution, which is a new understanding of the mechanism of evolution. Based on such understanding, evolution is regarded as "a changing process that one subsystem passes all or part of its genetic information to the next generation in a larger system, and during the adaptation process produces some new elements, stops some old ones, and thereby lasts in the larger system". Some other controversial questions related to evolution are also discussed.

Nonlinear evolution equations

CERN Document Server

Uraltseva, N N

1995-01-01

This collection focuses on nonlinear problems in partial differential equations. Most of the papers are based on lectures presented at the seminar on partial differential equations and mathematical physics at St. Petersburg University. Among the topics explored are the existence and properties of solutions of various classes of nonlinear evolution equations, nonlinear imbedding theorems, bifurcations of solutions, and equations of mathematical physics (Navier-Stokes type equations and the nonlinear Schrödinger equation). The book will be useful to researchers and graduate students working in p

Integrated model of multiple kernel learning and differential evolution for EUR/USD trading.

Science.gov (United States)

Deng, Shangkun; Sakurai, Akito

2014-01-01

Currency trading is an important area for individual investors, government policy decisions, and organization investments. In this study, we propose a hybrid approach referred to as MKL-DE, which combines multiple kernel learning (MKL) with differential evolution (DE) for trading a currency pair. MKL is used to learn a model that predicts changes in the target currency pair, whereas DE is used to generate the buy and sell signals for the target currency pair based on the relative strength index (RSI), while it is also combined with MKL as a trading signal. The new hybrid implementation is applied to EUR/USD trading, which is the most traded foreign exchange (FX) currency pair. MKL is essential for utilizing information from multiple information sources and DE is essential for formulating a trading rule based on a mixture of discrete structures and continuous parameters. Initially, the prediction model optimized by MKL predicts the returns based on a technical indicator called the moving average convergence and divergence. Next, a combined trading signal is optimized by DE using the inputs from the prediction model and technical indicator RSI obtained from multiple timeframes. The experimental results showed that trading using the prediction learned by MKL yielded consistent profits.

Integrated Model of Multiple Kernel Learning and Differential Evolution for EUR/USD Trading

Directory of Open Access Journals (Sweden)

Shangkun Deng

2014-01-01

Full Text Available Currency trading is an important area for individual investors, government policy decisions, and organization investments. In this study, we propose a hybrid approach referred to as MKL-DE, which combines multiple kernel learning (MKL with differential evolution (DE for trading a currency pair. MKL is used to learn a model that predicts changes in the target currency pair, whereas DE is used to generate the buy and sell signals for the target currency pair based on the relative strength index (RSI, while it is also combined with MKL as a trading signal. The new hybrid implementation is applied to EUR/USD trading, which is the most traded foreign exchange (FX currency pair. MKL is essential for utilizing information from multiple information sources and DE is essential for formulating a trading rule based on a mixture of discrete structures and continuous parameters. Initially, the prediction model optimized by MKL predicts the returns based on a technical indicator called the moving average convergence and divergence. Next, a combined trading signal is optimized by DE using the inputs from the prediction model and technical indicator RSI obtained from multiple timeframes. The experimental results showed that trading using the prediction learned by MKL yielded consistent profits.

Mantle differentiation and thermal evolution of Mars, Mercury, and Venus

International Nuclear Information System (INIS)

Spohn, T.

1991-01-01

In the present models for the thermal evolution of Mercury, Venus, and Mars encompass core and mantle chemical differentiation, lithospheric growth, and volcanic heat-transfer processes. Calculation results indicate that crust and lithosphere thicknesses are primarily dependent on planet size as well as the bulk concentration of planetary radiogenic elements and the lithosphere's thermal conductivity. The evidence for Martian volcanism for at least 3.5 Gyr, and in Mercury for up to 1 Gyr, in conjunction with the presence of a magnetic field on Mercury and its absence on Mars, suggest the dominance of a lithospheric conduction heat-transfer mechanism in these planets for most of their thermal history; by contrast, volcanic heat piping may have been an important heat-transfer mechanism on Venus. 50 refs

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

Gas-evolution oscillators. 10. A model based on a delay equation

Energy Technology Data Exchange (ETDEWEB)

Bar-Eli, K.; Noyes, R.M. [Univ. of Oregon, Eugene, OR (United States)

1992-09-17

This paper develops a simplified method to model the behavior of a gas-evolution oscillator with two differential delay equations in two unknowns consisting of the population of dissolved molecules in solution and the pressure of the gas.

Gas-evolution oscillators. 10. A model based on a delay equation

International Nuclear Information System (INIS)

Bar-Eli, K.; Noyes, R.M.

1992-01-01

This paper develops a simplified method to model the behavior of a gas-evolution oscillator with two differential delay equations in two unknowns consisting of the population of dissolved molecules in solution and the pressure of the gas

Iterative Splitting Methods for Differential Equations

CERN Document Server

Geiser, Juergen

2011-01-01

Iterative Splitting Methods for Differential Equations explains how to solve evolution equations via novel iterative-based splitting methods that efficiently use computational and memory resources. It focuses on systems of parabolic and hyperbolic equations, including convection-diffusion-reaction equations, heat equations, and wave equations. In the theoretical part of the book, the author discusses the main theorems and results of the stability and consistency analysis for ordinary differential equations. He then presents extensions of the iterative splitting methods to partial differential

Polygons of differential equations for finding exact solutions

International Nuclear Information System (INIS)

Kudryashov, Nikolai A.; Demina, Maria V.

2007-01-01

A method for finding exact solutions of nonlinear differential equations is presented. Our method is based on the application of polygons corresponding to nonlinear differential equations. It allows one to express exact solutions of the equation studied through solutions of another equation using properties of the basic equation itself. The ideas of power geometry are used and developed. Our approach has a pictorial interpretation, which is illustrative and effective. The method can be also applied for finding transformations between solutions of differential equations. To demonstrate the method application exact solutions of several equations are found. These equations are: the Korteveg-de Vries-Burgers equation, the generalized Kuramoto-Sivashinsky equation, the fourth-order nonlinear evolution equation, the fifth-order Korteveg-de Vries equation, the fifth-order modified Korteveg-de Vries equation and the sixth-order nonlinear evolution equation describing turbulent processes. Some new exact solutions of nonlinear evolution equations are given

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.

Evolution Inclusions and Variation Inequalities for Earth Data Processing II Differential-operator Inclusions and Evolution Variation Inequalities for Earth Data Processing

CERN Document Server

Zgurovsky, Mikhail Z; Kasyanov, Pavlo O

2011-01-01

Here, the authors present modern mathematical methods to solve problems of differential-operator inclusions and evolution variation inequalities which may occur in fields such as geophysics, aerohydrodynamics, or fluid dynamics. For the first time, they describe the detailed generalization of various approaches to the analysis of fundamentally nonlinear models and provide a toolbox of mathematical equations. These new mathematical methods can be applied to a broad spectrum of problems. Examples of these are phase changes, diffusion of electromagnetic, acoustic, vibro-, hydro- and seismoacousti

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.

A modified differential evolution approach for dynamic economic dispatch with valve-point effects

International Nuclear Information System (INIS)

Yuan Xiaohui; Wang Liang; Yuan Yanbin; Zhang Yongchuan; Cao Bo; Yang Bo

2008-01-01

Dynamic economic dispatch (DED) plays an important role in power system operation, which is a complicated non-linear constrained optimization problem. It has nonsmooth and nonconvex characteristic when generation unit valve-point effects are taken into account. This paper proposes a modified differential evolution approach (MDE) to solve DED problem with valve-point effects. In the proposed MDE method, feasibility-based selection comparison techniques and heuristic search rules are devised to handle constraints effectively. In contrast to the penalty function method, the constraints-handling method does not require penalty factors or any extra parameters and can guide the population to the feasible region quickly. Especially, it can be satisfied equality constraints of DED problem precisely. Moreover, the effects of two crucial parameters on the performance of the MDE for DED problem are studied as well. The feasibility and effectiveness of the proposed method is demonstrated for application example and the test results are compared with those of other methods reported in literature. It is shown that the proposed method is capable of yielding higher quality solutions

Evolution of magnetized, differentially rotating neutron stars: Simulations in full general relativity

International Nuclear Information System (INIS)

Duez, Matthew D.; Liu, Yuk Tung; Shapiro, Stuart L.; Stephens, Branson C.; Shibata, Masaru

2006-01-01

We study the effects of magnetic fields on the evolution of differentially rotating neutron stars, which can be formed in stellar core collapse or binary neutron star coalescence. Magnetic braking and the magnetorotational instability (MRI) both act on differentially rotating stars to redistribute angular momentum. Simulations of these stars are carried out in axisymmetry using our recently developed codes which integrate the coupled Einstein-Maxwell-MHD equations. We consider stars with two different equations of state (EOS), a gamma-law EOS with Γ=2, and a more realistic hybrid EOS, and we evolve them adiabatically. Our simulations show that the fate of the star depends on its mass and spin. For initial data, we consider three categories of differentially rotating, equilibrium configurations, which we label normal, hypermassive and ultraspinning. Normal configurations have rest masses below the maximum achievable with uniform rotation, and angular momentum below the maximum for uniform rotation at the same rest mass. Hypermassive stars have rest masses exceeding the mass limit for uniform rotation. Ultraspinning stars are not hypermassive, but have angular momentum exceeding the maximum for uniform rotation at the same rest mass. We show that a normal star will evolve to a uniformly rotating equilibrium configuration. An ultraspinning star evolves to an equilibrium state consisting of a nearly uniformly rotating central core, surrounded by a differentially rotating torus with constant angular velocity along magnetic field lines, so that differential rotation ceases to wind the magnetic field. In addition, the final state is stable against the MRI, although it has differential rotation. For a hypermassive neutron star, the MHD-driven angular momentum transport leads to catastrophic collapse of the core. The resulting rotating black hole is surrounded by a hot, massive, magnetized torus undergoing quasistationary accretion, and a magnetic field collimated along

Conical differentiability for evolution variational inequalities

Science.gov (United States)

Jarušek, Jiří; Krbec, Miroslav; Rao, Murali; Sokołowski, Jan

The conical differentiability of solutions to the parabolic variational inequality with respect to the right-hand side is proved in the paper. From one side the result is based on the Lipschitz continuity in H {1}/{2},1 (Q) of solutions to the variational inequality with respect to the right-hand side. On the other side, in view of the polyhedricity of the convex cone K={v∈ H;v |Σ c⩾0,v |Σ d=0}, we prove new results on sensitivity analysis of parabolic variational inequalities. Therefore, we have a positive answer to the question raised by Fulbert Mignot (J. Funct. Anal. 22 (1976) 25-32).

Efficient receiver tuning using differential evolution strategies

Science.gov (United States)

Wheeler, Caleb H.; Toland, Trevor G.

2016-08-01

Differential evolution (DE) is a powerful and computationally inexpensive optimization strategy that can be used to search an entire parameter space or to converge quickly on a solution. The Kilopixel Array Pathfinder Project (KAPPa) is a heterodyne receiver system delivering 5 GHz of instantaneous bandwidth in the tuning range of 645-695 GHz. The fully automated KAPPa receiver test system finds optimal receiver tuning using performance feedback and DE. We present an adaptation of DE for use in rapid receiver characterization. The KAPPa DE algorithm is written in Python 2.7 and is fully integrated with the KAPPa instrument control, data processing, and visualization code. KAPPa develops the technologies needed to realize heterodyne focal plane arrays containing 1000 pixels. Finding optimal receiver tuning by investigating large parameter spaces is one of many challenges facing the characterization phase of KAPPa. This is a difficult task via by-hand techniques. Characterizing or tuning in an automated fashion without need for human intervention is desirable for future large scale arrays. While many optimization strategies exist, DE is ideal for time and performance constraints because it can be set to converge to a solution rapidly with minimal computational overhead. We discuss how DE is utilized in the KAPPa system and discuss its performance and look toward the future of 1000 pixel array receivers and consider how the KAPPa DE system might be applied.

Simulating Chemical Kinetics Without Differential Equations: A Quantitative Theory Based on Chemical Pathways.

Science.gov (United States)

Bai, Shirong; Skodje, Rex T

2017-08-17

A new approach is presented for simulating the time-evolution of chemically reactive systems. This method provides an alternative to conventional modeling of mass-action kinetics that involves solving differential equations for the species concentrations. The method presented here avoids the need to solve the rate equations by switching to a representation based on chemical pathways. In the Sum Over Histories Representation (or SOHR) method, any time-dependent kinetic observable, such as concentration, is written as a linear combination of probabilities for chemical pathways leading to a desired outcome. In this work, an iterative method is introduced that allows the time-dependent pathway probabilities to be generated from a knowledge of the elementary rate coefficients, thus avoiding the pitfalls involved in solving the differential equations of kinetics. The method is successfully applied to the model Lotka-Volterra system and to a realistic H 2 combustion model.

Estimating reliability of degraded system based on the probability density evolution with multi-parameter

Directory of Open Access Journals (Sweden)

Jiang Ge

2017-01-01

Full Text Available System degradation was usually caused by multiple-parameter degradation. The assessment result of system reliability by universal generating function was low accurate when compared with the Monte Carlo simulation. And the probability density function of the system output performance cannot be got. So the reliability assessment method based on the probability density evolution with multi-parameter was presented for complexly degraded system. Firstly, the system output function was founded according to the transitive relation between component parameters and the system output performance. Then, the probability density evolution equation based on the probability conservation principle and the system output function was established. Furthermore, probability distribution characteristics of the system output performance was obtained by solving differential equation. Finally, the reliability of the degraded system was estimated. This method did not need to discrete the performance parameters and can establish continuous probability density function of the system output performance with high calculation efficiency and low cost. Numerical example shows that this method is applicable to evaluate the reliability of multi-parameter degraded system.

Reconcilable Differences: Standards-based Teaching and Differentiation.

Science.gov (United States)

Tomlinson, Carol Ann

2000-01-01

There is no contradiction between effective standards-based instruction and differentiation. Curriculum tells teachers what to teach; differentiation tells how. Teachers can challenge all learners by providing standards-based materials and tasks calling for varied difficulty levels, scaffolding, instructional styles, and learning times. (MLH)

On the adaptivity and complexity embedded into differential evolution

International Nuclear Information System (INIS)

Senkerik, Roman; Pluhacek, Michal; Jasek, Roman; Zelinka, Ivan

2016-01-01

This research deals with the comparison of the two modern approaches for evolutionary algorithms, which are the adaptivity and complex chaotic dynamics. This paper aims on the investigations on the chaos-driven Differential Evolution (DE) concept. This paper is aimed at the embedding of discrete dissipative chaotic systems in the form of chaotic pseudo random number generators for the DE and comparing the influence to the performance with the state of the art adaptive representative jDE. This research is focused mainly on the possible disadvantages and advantages of both compared approaches. Repeated simulations for Lozi map driving chaotic systems were performed on the simple benchmark functions set, which are more close to the real optimization problems. Obtained results are compared with the canonical not-chaotic and not adaptive DE. Results show that with used simple test functions, the performance of ChaosDE is better in the most cases than jDE and Canonical DE, furthermore due to the unique sequencing in CPRNG given by the hidden chaotic dynamics, thus better and faster selection of unique individuals from population, ChaosDE is faster.

On the adaptivity and complexity embedded into differential evolution

Energy Technology Data Exchange (ETDEWEB)

Senkerik, Roman; Pluhacek, Michal; Jasek, Roman [Tomas Bata University in Zlin, Faculty of Applied Informatics, Nam T.G. Masaryka 5555, 760 01 Zlin, Czech Republic, senkerik@fai.utb.cz,pluhacek@fai.utb.cz (Czech Republic); Zelinka, Ivan [Technical University of Ostrava, Faculty of Electrical Engineering and Computer Science, 17. listopadu 15,708 33 Ostrava-Poruba, Czech Republic, ivan.zelinka@vsb.cz (Czech Republic)

2016-06-08

This research deals with the comparison of the two modern approaches for evolutionary algorithms, which are the adaptivity and complex chaotic dynamics. This paper aims on the investigations on the chaos-driven Differential Evolution (DE) concept. This paper is aimed at the embedding of discrete dissipative chaotic systems in the form of chaotic pseudo random number generators for the DE and comparing the influence to the performance with the state of the art adaptive representative jDE. This research is focused mainly on the possible disadvantages and advantages of both compared approaches. Repeated simulations for Lozi map driving chaotic systems were performed on the simple benchmark functions set, which are more close to the real optimization problems. Obtained results are compared with the canonical not-chaotic and not adaptive DE. Results show that with used simple test functions, the performance of ChaosDE is better in the most cases than jDE and Canonical DE, furthermore due to the unique sequencing in CPRNG given by the hidden chaotic dynamics, thus better and faster selection of unique individuals from population, ChaosDE is faster.

On the adaptivity and complexity embedded into differential evolution

Science.gov (United States)

Senkerik, Roman; Pluhacek, Michal; Zelinka, Ivan; Jasek, Roman

2016-06-01

This research deals with the comparison of the two modern approaches for evolutionary algorithms, which are the adaptivity and complex chaotic dynamics. This paper aims on the investigations on the chaos-driven Differential Evolution (DE) concept. This paper is aimed at the embedding of discrete dissipative chaotic systems in the form of chaotic pseudo random number generators for the DE and comparing the influence to the performance with the state of the art adaptive representative jDE. This research is focused mainly on the possible disadvantages and advantages of both compared approaches. Repeated simulations for Lozi map driving chaotic systems were performed on the simple benchmark functions set, which are more close to the real optimization problems. Obtained results are compared with the canonical not-chaotic and not adaptive DE. Results show that with used simple test functions, the performance of ChaosDE is better in the most cases than jDE and Canonical DE, furthermore due to the unique sequencing in CPRNG given by the hidden chaotic dynamics, thus better and faster selection of unique individuals from population, ChaosDE is faster.

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.

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

Automatic Knowledge Base Evolution by Learning Instances

OpenAIRE

Kim, Sundong

2016-01-01

Knowledge base is the way to store structured and unstructured data throughout the web. Since the size of the web is increasing rapidly, there are huge needs to structure the knowledge in a fully automated way. However fully-automated knowledge-base evolution on the Semantic Web is a major challenges, although there are many ontology evolution techniques available. Therefore learning ontology automatically can contribute to the semantic web society significantly. In this paper, we propose ful...

Differential Equations as Actions

DEFF Research Database (Denmark)

Ronkko, Mauno; Ravn, Anders P.

1997-01-01

We extend a conventional action system with a primitive action consisting of a differential equation and an evolution invariant. The semantics is given by a predicate transformer. The weakest liberal precondition is chosen, because it is not always desirable that steps corresponding to differential...... actions shall terminate. It is shown that the proposed differential action has a semantics which corresponds to a discrete approximation when the discrete step size goes to zero. The extension gives action systems the power to model real-time clocks and continuous evolutions within hybrid systems....

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.

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.

Evolution of plant reproduction: from fusion and dispersal to interaction and communication

NARCIS (Netherlands)

Willemse, M.T.M.

2009-01-01

Based on the existing data concerning the evolution of the sexual reproduction, it is argued that the processes of sex differentiation and interactions play a key role in evolution. From the beginning environment and organism are unified. In a changing dynamic environment life originates and the

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.

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.

Solar-Based Boost Differential Single Phase Inverter | Eya | Nigerian ...

African Journals Online (AJOL)

Solar-Based Boost Differential Single Phase Inverter. ... Solar-based boost differential inverter is reduced down to 22.37% in closed loop system with the aid of Proportional –integral-Differential (PID) ... The dc power source is photovoltaic cell.

Decomposition of a hierarchy of nonlinear evolution equations

International Nuclear Information System (INIS)

Geng Xianguo

2003-01-01

The generalized Hamiltonian structures for a hierarchy of nonlinear evolution equations are established with the aid of the trace identity. Using the nonlinearization approach, the hierarchy of nonlinear evolution equations is decomposed into a class of new finite-dimensional Hamiltonian systems. The generating function of integrals and their generator are presented, based on which the finite-dimensional Hamiltonian systems are proved to be completely integrable in the Liouville sense. As an application, solutions for the hierarchy of nonlinear evolution equations are reduced to solving the compatible Hamiltonian systems of ordinary differential equations

Evidence of differential HLA class I-mediated viral evolution in functional and accessory/regulatory genes of HIV-1.

Directory of Open Access Journals (Sweden)

Zabrina L Brumme

2007-07-01

Full Text Available Despite the formidable mutational capacity and sequence diversity of HIV-1, evidence suggests that viral evolution in response to specific selective pressures follows generally predictable mutational pathways. Population-based analyses of clinically derived HIV sequences may be used to identify immune escape mutations in viral genes; however, prior attempts to identify such mutations have been complicated by the inability to discriminate active immune selection from virus founder effects. Furthermore, the association between mutations arising under in vivo immune selection and disease progression for highly variable pathogens such as HIV-1 remains incompletely understood. We applied a viral lineage-corrected analytical method to investigate HLA class I-associated sequence imprinting in HIV protease, reverse transcriptase (RT, Vpr, and Nef in a large cohort of chronically infected, antiretrovirally naïve individuals. A total of 478 unique HLA-associated polymorphisms were observed and organized into a series of "escape maps," which identify known and putative cytotoxic T lymphocyte (CTL epitopes under selection pressure in vivo. Our data indicate that pathways to immune escape are predictable based on host HLA class I profile, and that epitope anchor residues are not the preferred sites of CTL escape. Results reveal differential contributions of immune imprinting to viral gene diversity, with Nef exhibiting far greater evidence for HLA class I-mediated selection compared to other genes. Moreover, these data reveal a significant, dose-dependent inverse correlation between HLA-associated polymorphisms and HIV disease stage as estimated by CD4(+ T cell count. Identification of specific sites and patterns of HLA-associated polymorphisms across HIV protease, RT, Vpr, and Nef illuminates regions of the genes encoding these products under active immune selection pressure in vivo. The high density of HLA-associated polymorphisms in Nef compared to other

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.

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.

Partial Differential Equations

CERN Document Server

1988-01-01

The volume contains a selection of papers presented at the 7th Symposium on differential geometry and differential equations (DD7) held at the Nankai Institute of Mathematics, Tianjin, China, in 1986. Most of the contributions are original research papers on topics including elliptic equations, hyperbolic equations, evolution equations, non-linear equations from differential geometry and mechanics, micro-local analysis.

Coronary artery segmentation in X-ray angiogram using Gabor filters and differential evolution

International Nuclear Information System (INIS)

Cervantes S, F.; Hernandez A, A.; Cruz A, I.; Solorio M, S.; Cordova F, T.; Avina C, J. G.

2016-10-01

Segmentation of coronary arteries in X-ray angiograms represents an essential task for computer-aided diagnosis, since it can help cardiologists in diagnosing and monitoring vascular abnormalities. Due to the main disadvantages of the X-ray angiograms are the nonuniform illumination, and the weak contrast between blood vessels and image background, different vessel enhancement methods have been introduced. In this paper, a novel method for blood vessel enhancement based on Gabor filters tuned using the optimization strategy of Differential evolution (De) is proposed. Because the Gabor filters are governed by three different parameters, the optimal selection of those parameters is highly desirable in order to maximize the vessel detection rate while reducing the computational cost of the training stage. To obtain the optimal set of parameters for the Gabor filters, the area (Az) under the receiver operating characteristic curve is used as objective function. In the experimental results, the proposed method obtained the highest detection performance with Az = 0.956 using a test set of 60 angiograms, and Az = 0.934 with a training set of 20 angiograms compared with different state-of-the-art vessel detection methods. In addition, the experimental results in terms of computational time have also shown that the proposed method can be highly suitable for clinical decision support. (Author)

Coronary artery segmentation in X-ray angiogram using Gabor filters and differential evolution

Energy Technology Data Exchange (ETDEWEB)

Cervantes S, F.; Hernandez A, A.; Cruz A, I. [Centro de Investigacion en Matematicas, A. C., Jalisco s/n, Col. Valenciana, 36240 Guanajuato, Gto. (Mexico); Solorio M, S. [IMSS, Unidad de Investigacion, UMAE Hospital de Especialidades No. 1 del Centro Medico Nacional del Bajio, 37260 Leon, Guanajuato (Mexico); Cordova F, T. [Universidad de Guanajuato, Departamento de Ingenieria Fisica, 37150 Leon, Guanajuato (Mexico); Avina C, J. G., E-mail: ivan.cruz@cimat.mx [Universidad de Guanajuato, Departamento de Electronica, 36885 Salamanca, Guanajuato (Mexico)

2016-10-15

Segmentation of coronary arteries in X-ray angiograms represents an essential task for computer-aided diagnosis, since it can help cardiologists in diagnosing and monitoring vascular abnormalities. Due to the main disadvantages of the X-ray angiograms are the nonuniform illumination, and the weak contrast between blood vessels and image background, different vessel enhancement methods have been introduced. In this paper, a novel method for blood vessel enhancement based on Gabor filters tuned using the optimization strategy of Differential evolution (De) is proposed. Because the Gabor filters are governed by three different parameters, the optimal selection of those parameters is highly desirable in order to maximize the vessel detection rate while reducing the computational cost of the training stage. To obtain the optimal set of parameters for the Gabor filters, the area (Az) under the receiver operating characteristic curve is used as objective function. In the experimental results, the proposed method obtained the highest detection performance with Az = 0.956 using a test set of 60 angiograms, and Az = 0.934 with a training set of 20 angiograms compared with different state-of-the-art vessel detection methods. In addition, the experimental results in terms of computational time have also shown that the proposed method can be highly suitable for clinical decision support. (Author)

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.

Topological structure of the solution set for evolution inclusions

CERN Document Server

Zhou, Yong; Peng, Li

2017-01-01

This book systematically presents the topological structure of solution sets and attractability for nonlinear evolution inclusions, together with its relevant applications in control problems and partial differential equations. It provides readers the background material needed to delve deeper into the subject and explore the rich research literature.  In addition, the book addresses many of the basic techniques and results recently developed in connection with this theory, including the structure of solution sets for evolution inclusions with m-dissipative operators; quasi-autonomous and non-autonomous evolution inclusions and control systems;evolution inclusions with the Hille-Yosida operator; functional evolution inclusions; impulsive evolution inclusions; and stochastic evolution inclusions. Several applications of evolution inclusions and control systems are also discussed in detail.  Based on extensive research work conducted by the authors and other experts over the past four years, the information p...

Prolongation Structure of Semi-discrete Nonlinear Evolution Equations

International Nuclear Information System (INIS)

Bai Yongqiang; Wu Ke; Zhao Weizhong; Guo Hanying

2007-01-01

Based on noncommutative differential calculus, we present a theory of prolongation structure for semi-discrete nonlinear evolution equations. As an illustrative example, a semi-discrete model of the nonlinear Schroedinger equation is discussed in terms of this theory and the corresponding Lax pairs are also given.

Optical spatial differentiator based on subwavelength high-contrast gratings

Science.gov (United States)

Dong, Zhewei; Si, Jiangnan; Yu, Xuanyi; Deng, Xiaoxu

2018-04-01

An optical spatial differentiator based on subwavelength high-contrast gratings (HCGs) is proposed experimentally. The spatial differentiation property of the subwavelength HCG is analyzed by calculating its spatial spectral transfer function based on the periodic waveguide theory. By employing the FDTD solutions, the performance of the subwavelength HCG spatial differentiator was investigated numerically. The subwavelength HCG differentiator with the thickness at the nanoscale was fabricated on the quartz substrate by electron beam lithography and Bosch deep silicon etching. Observed under an optical microscope with a CCD camera, the spatial differentiation of the incident field profile was obtained by the subwavelength HCG differentiator in transmission without Fourier lens. By projecting the images of slits, letter "X," and a cross on the subwavelength HCG differentiator, edge detections of images were obtained in transmission. With the nanoscale HCG structure and simple optical implementation, the proposed optical spatial differentiator provides the prospects for applications in optical computing systems and parallel data processing.

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)

无

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.

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.

On convergence of differential evolution over a class of continuous functions with unique global optimum.

Science.gov (United States)

Ghosh, Sayan; Das, Swagatam; Vasilakos, Athanasios V; Suresh, Kaushik

2012-02-01

Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter optimization algorithms of current interest. Since its inception in the mid 1990s, DE has been finding many successful applications in real-world optimization problems from diverse domains of science and engineering. This paper takes a first significant step toward the convergence analysis of a canonical DE (DE/rand/1/bin) algorithm. It first deduces a time-recursive relationship for the probability density function (PDF) of the trial solutions, taking into consideration the DE-type mutation, crossover, and selection mechanisms. Then, by applying the concepts of Lyapunov stability theorems, it shows that as time approaches infinity, the PDF of the trial solutions concentrates narrowly around the global optimum of the objective function, assuming the shape of a Dirac delta distribution. Asymptotic convergence behavior of the population PDF is established by constructing a Lyapunov functional based on the PDF and showing that it monotonically decreases with time. The analysis is applicable to a class of continuous and real-valued objective functions that possesses a unique global optimum (but may have multiple local optima). Theoretical results have been substantiated with relevant computer simulations.

Comparative Analysis of Particle Swarm and Differential Evolution via Tuning on Ultrasmall Titanium Oxide Nanoclusters

Science.gov (United States)

Inclan, Eric; Lassester, Jack; Geohegan, David; Yoon, Mina

Optimization algorithms (OA) coupled with numerical methods enable researchers to identify and study (meta) stable nanoclusters without the control restrictions of empirical methods. An algorithm's performance is governed by two factors: (1) its compatibility with an objective function, (2) the dimension of a design space, which increases with cluster size. Although researchers often tune an algorithm's user-defined parameters (UDP), tuning is not guaranteed to improve performance. In this research, Particle Swarm (PSO) and Differential Evolution (DE), are compared by tuning their UDP in a multi-objective optimization environment (MOE). Combined with a Kolmogorov Smirnov test for statistical significance, the MOE enables the study of the Pareto Front (PF), made of the UDP settings that trade-off between best performance in energy minimization (``effectiveness'') based on force-field potential energy, and best convergence rate (``efficiency''). By studying the PF, this research finds that UDP values frequently suggested in the literature do not provide best effectiveness for these methods. Additionally, monotonic convergence is found to significantly improve efficiency without sacrificing effectiveness for very small systems, suggesting better compatibility. Work is supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division.

Differential pleiotropy and HOX functional organization.

Science.gov (United States)

Sivanantharajah, Lovesha; Percival-Smith, Anthony

2015-02-01

Key studies led to the idea that transcription factors are composed of defined modular protein motifs or domains, each with separable, unique function. During evolution, the recombination of these modular domains could give rise to transcription factors with new properties, as has been shown using recombinant molecules. This archetypic, modular view of transcription factor organization is based on the analyses of a few transcription factors such as GAL4, which may represent extreme exemplars rather than an archetype or the norm. Recent work with a set of Homeotic selector (HOX) proteins has revealed differential pleiotropy: the observation that highly-conserved HOX protein motifs and domains make small, additive, tissue specific contributions to HOX activity. Many of these differentially pleiotropic HOX motifs may represent plastic sequence elements called short linear motifs (SLiMs). The coupling of differential pleiotropy with SLiMs, suggests that protein sequence changes in HOX transcription factors may have had a greater impact on morphological diversity during evolution than previously believed. Furthermore, differential pleiotropy may be the genetic consequence of an ensemble nature of HOX transcription factor allostery, where HOX proteins exist as an ensemble of states with the capacity to integrate an extensive array of developmental information. Given a new structural model for HOX functional domain organization, the properties of the archetypic TF may require reassessment. Copyright © 2014 Elsevier Inc. All rights reserved.

Evolution of a Computer-Based Testing Laboratory

Science.gov (United States)

Moskal, Patrick; Caldwell, Richard; Ellis, Taylor

2009-01-01

In 2003, faced with increasing growth in technology-based and large-enrollment courses, the College of Business Administration at the University of Central Florida opened a computer-based testing lab to facilitate administration of course examinations. Patrick Moskal, Richard Caldwell, and Taylor Ellis describe the development and evolution of the…

A software for parameter optimization with Differential Evolution Entirely Parallel method

Directory of Open Access Journals (Sweden)

Konstantin Kozlov

2016-08-01

Full Text Available Summary. Differential Evolution Entirely Parallel (DEEP package is a software for finding unknown real and integer parameters in dynamical models of biological processes by minimizing one or even several objective functions that measure the deviation of model solution from data. Numerical solutions provided by the most efficient global optimization methods are often problem-specific and cannot be easily adapted to other tasks. In contrast, DEEP allows a user to describe both mathematical model and objective function in any programming language, such as R, Octave or Python and others. Being implemented in C, DEEP demonstrates as good performance as the top three methods from CEC-2014 (Competition on evolutionary computation benchmark and was successfully applied to several biological problems. Availability. DEEP method is an open source and free software distributed under the terms of GPL licence version 3. The sources are available at http://deepmethod.sourceforge.net/ and binary packages for Fedora GNU/Linux are provided for RPM package manager at https://build.opensuse.org/project/repositories/home:mackoel:compbio.

Ultrasound speckle reduction based on fractional order differentiation.

Science.gov (United States)

Shao, Dangguo; Zhou, Ting; Liu, Fan; Yi, Sanli; Xiang, Yan; Ma, Lei; Xiong, Xin; He, Jianfeng

2017-07-01

Ultrasound images show a granular pattern of noise known as speckle that diminishes their quality and results in difficulties in diagnosis. To preserve edges and features, this paper proposes a fractional differentiation-based image operator to reduce speckle in ultrasound. An image de-noising model based on fractional partial differential equations with balance relation between k (gradient modulus threshold that controls the conduction) and v (the order of fractional differentiation) was constructed by the effective combination of fractional calculus theory and a partial differential equation, and the numerical algorithm of it was achieved using a fractional differential mask operator. The proposed algorithm has better speckle reduction and structure preservation than the three existing methods [P-M model, the speckle reducing anisotropic diffusion (SRAD) technique, and the detail preserving anisotropic diffusion (DPAD) technique]. And it is significantly faster than bilateral filtering (BF) in producing virtually the same experimental results. Ultrasound phantom testing and in vivo imaging show that the proposed method can improve the quality of an ultrasound image in terms of tissue SNR, CNR, and FOM values.

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....

Many-Objective Optimization Using Adaptive Differential Evolution with a New Ranking Method

Directory of Open Access Journals (Sweden)

Xiaoguang He

2014-01-01

Full Text Available Pareto dominance is an important concept and is usually used in multiobjective evolutionary algorithms (MOEAs to determine the nondominated solutions. However, for many-objective problems, using Pareto dominance to rank the solutions even in the early generation, most obtained solutions are often the nondominated solutions, which results in a little selection pressure of MOEAs toward the optimal solutions. In this paper, a new ranking method is proposed for many-objective optimization problems to verify a relatively smaller number of representative nondominated solutions with a uniform and wide distribution and improve the selection pressure of MOEAs. After that, a many-objective differential evolution with the new ranking method (MODER for handling many-objective optimization problems is designed. At last, the experiments are conducted and the proposed algorithm is compared with several well-known algorithms. The experimental results show that the proposed algorithm can guide the search to converge to the true PF and maintain the diversity of solutions for many-objective problems.

Size evolution of ultrafine particles: Differential signatures of normal and episodic events.

Science.gov (United States)

Joshi, Manish; Khan, Arshad; Anand, S; Sapra, B K

2016-01-01

The effect of fireworks on the aerosol number characteristics of atmosphere was studied for an urban mega city. Measurements were made at 50 m height to assess the local changes around the festival days. Apart from the increase in total number concentration and characteristic accumulation mode, short-term increase of ultrafine particle concentration was noted. Total number concentration varies an order of magnitude during the measurement period in which peak occurs at a frequency of approximately one per day. On integral scale, it seems not possible to distinguish an episodic (e.g. firework bursting induced aerosol emission) and a normal (ambient atmospheric changes) event. However these events could be differentiated on the basis of size evolution analysis around number concentration peaks. The results are discussed relative to past studies and inferences are drawn towards aerosol signatures of firework bursting. The short-term burst in ultrafine particle concentration can pose an inhalation hazard. Copyright © 2015 Elsevier Ltd. All rights reserved.

Gene duplication and the evolution of hemoglobin isoform differentiation in birds.

Science.gov (United States)

Grispo, Michael T; Natarajan, Chandrasekhar; Projecto-Garcia, Joana; Moriyama, Hideaki; Weber, Roy E; Storz, Jay F

2012-11-02

The majority of bird species co-express two functionally distinct hemoglobin (Hb) isoforms in definitive erythrocytes as follows: HbA (the major adult Hb isoform, with α-chain subunits encoded by the α(A)-globin gene) and HbD (the minor adult Hb isoform, with α-chain subunits encoded by the α(D)-globin gene). The α(D)-globin gene originated via tandem duplication of an embryonic α-like globin gene in the stem lineage of tetrapod vertebrates, which suggests the possibility that functional differentiation between the HbA and HbD isoforms may be attributable to a retained ancestral character state in HbD that harkens back to a primordial, embryonic function. To investigate this possibility, we conducted a combined analysis of protein biochemistry and sequence evolution to characterize the structural and functional basis of Hb isoform differentiation in birds. Functional experiments involving purified HbA and HbD isoforms from 11 different bird species revealed that HbD is characterized by a consistently higher O(2) affinity in the presence of allosteric effectors such as organic phosphates and Cl(-) ions. In the case of both HbA and HbD, analyses of oxygenation properties under the two-state Monod-Wyman-Changeux allosteric model revealed that the pH dependence of Hb-O(2) affinity stems primarily from changes in the O(2) association constant of deoxy (T-state)-Hb. Ancestral sequence reconstructions revealed that the amino acid substitutions that distinguish the adult-expressed Hb isoforms are not attributable to the retention of an ancestral (pre-duplication) character state in the α(D)-globin gene that is shared with the embryonic α-like globin gene.

Gene Duplication and the Evolution of Hemoglobin Isoform Differentiation in Birds*

Science.gov (United States)

Grispo, Michael T.; Natarajan, Chandrasekhar; Projecto-Garcia, Joana; Moriyama, Hideaki; Weber, Roy E.; Storz, Jay F.

2012-01-01

The majority of bird species co-express two functionally distinct hemoglobin (Hb) isoforms in definitive erythrocytes as follows: HbA (the major adult Hb isoform, with α-chain subunits encoded by the αA-globin gene) and HbD (the minor adult Hb isoform, with α-chain subunits encoded by the αD-globin gene). The αD-globin gene originated via tandem duplication of an embryonic α-like globin gene in the stem lineage of tetrapod vertebrates, which suggests the possibility that functional differentiation between the HbA and HbD isoforms may be attributable to a retained ancestral character state in HbD that harkens back to a primordial, embryonic function. To investigate this possibility, we conducted a combined analysis of protein biochemistry and sequence evolution to characterize the structural and functional basis of Hb isoform differentiation in birds. Functional experiments involving purified HbA and HbD isoforms from 11 different bird species revealed that HbD is characterized by a consistently higher O2 affinity in the presence of allosteric effectors such as organic phosphates and Cl− ions. In the case of both HbA and HbD, analyses of oxygenation properties under the two-state Monod-Wyman-Changeux allosteric model revealed that the pH dependence of Hb-O2 affinity stems primarily from changes in the O2 association constant of deoxy (T-state)-Hb. Ancestral sequence reconstructions revealed that the amino acid substitutions that distinguish the adult-expressed Hb isoforms are not attributable to the retention of an ancestral (pre-duplication) character state in the αD-globin gene that is shared with the embryonic α-like globin gene. PMID:22962007

Dynamic Evolution Model Based on Social Network Services

Science.gov (United States)

Xiong, Xi; Gou, Zhi-Jian; Zhang, Shi-Bin; Zhao, Wen

2013-11-01

Based on the analysis of evolutionary characteristics of public opinion in social networking services (SNS), in the paper we propose a dynamic evolution model, in which opinions are coupled with topology. This model shows the clustering phenomenon of opinions in dynamic network evolution. The simulation results show that the model can fit the data from a social network site. The dynamic evolution of networks accelerates the opinion, separation and aggregation. The scale and the number of clusters are influenced by confidence limit and rewiring probability. Dynamic changes of the topology reduce the number of isolated nodes, while the increased confidence limit allows nodes to communicate more sufficiently. The two effects make the distribution of opinion more neutral. The dynamic evolution of networks generates central clusters with high connectivity and high betweenness, which make it difficult to control public opinions in SNS.

Designing manufacturable filters for a 16-band plenoptic camera using differential evolution

Science.gov (United States)

Doster, Timothy; Olson, Colin C.; Fleet, Erin; Yetzbacher, Michael; Kanaev, Andrey; Lebow, Paul; Leathers, Robert

2017-05-01

A 16-band plenoptic camera allows for the rapid exchange of filter sets via a 4x4 filter array on the lens's front aperture. This ability to change out filters allows for an operator to quickly adapt to different locales or threat intelligence. Typically, such a system incorporates a default set of 16 equally spaced at-topped filters. Knowing the operating theater or the likely targets of interest it becomes advantageous to tune the filters. We propose using a modified beta distribution to parameterize the different possible filters and differential evolution (DE) to search over the space of possible filter designs. The modified beta distribution allows us to jointly optimize the width, taper and wavelength center of each single- or multi-pass filter in the set over a number of evolutionary steps. Further, by constraining the function parameters we can develop solutions which are not just theoretical but manufacturable. We examine two independent tasks: general spectral sensing and target detection. In the general spectral sensing task we utilize the theory of compressive sensing (CS) and find filters that generate codings which minimize the CS reconstruction error based on a fixed spectral dictionary of endmembers. For the target detection task and a set of known targets, we train the filters to optimize the separation of the background and target signature. We compare our results to the default 16 at-topped non-overlapping filter set which comes with the plenoptic camera and full hyperspectral resolution data which was previously acquired.

Abstract methods in partial differential equations

CERN Document Server

Carroll, Robert W

2012-01-01

Detailed, self-contained treatment examines modern abstract methods in partial differential equations, especially abstract evolution equations. Suitable for graduate students with some previous exposure to classical partial differential equations. 1969 edition.

Evolution of clans in multiparticle production

International Nuclear Information System (INIS)

Zborovsky, I.

1994-01-01

An alternative interpretation of the development of the clan structure arising formally from the natural decomposition of the negative binomial multiplicity distribution is presented here. Our approach is based on stochastico-physical ideas of multiple production on the parton level. Specific differential-difference evolution equations have been proposed which besides the elementary processes involving the ingredients of QCD branching describe collective phenomena of clan's collapsing and clan's coherent disintegration. (orig.)

A Model Parameter Extraction Method for Dielectric Barrier Discharge Ozone Chamber using Differential Evolution

Science.gov (United States)

Amjad, M.; Salam, Z.; Ishaque, K.

2014-04-01

In order to design an efficient resonant power supply for ozone gas generator, it is necessary to accurately determine the parameters of the ozone chamber. In the conventional method, the information from Lissajous plot is used to estimate the values of these parameters. However, the experimental setup for this purpose can only predict the parameters at one operating frequency and there is no guarantee that it results in the highest ozone gas yield. This paper proposes a new approach to determine the parameters using a search and optimization technique known as Differential Evolution (DE). The desired objective function of DE is set at the resonance condition and the chamber parameter values can be searched regardless of experimental constraints. The chamber parameters obtained from the DE technique are validated by experiment.

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.

Advanced functional evolution equations and inclusions

CERN Document Server

Benchohra, Mouffak

2015-01-01

This book presents up-to-date results on abstract evolution equations and differential inclusions in infinite dimensional spaces. It covers equations with time delay and with impulses, and complements the existing literature in functional differential equations and inclusions. The exposition is devoted to both local and global mild solutions for some classes of functional differential evolution equations and inclusions, and other densely and non-densely defined functional differential equations and inclusions in separable Banach spaces or in Fréchet spaces. The tools used include classical fixed points theorems and the measure-of non-compactness, and each chapter concludes with a section devoted to notes and bibliographical remarks. This monograph is particularly useful for researchers and graduate students studying pure and applied mathematics, engineering, biology and all other applied sciences.

Adaptive Differential Evolution Approach for Constrained Economic Power Dispatch with Prohibited Operating Zones

Directory of Open Access Journals (Sweden)

Abdellatif HAMOUDA

2011-12-01

Full Text Available Economic power dispatch (EPD is one of the main tools for optimal operation and planning of modern power systems. To solve effectively the EPD problem, most of the conventional calculus methods rely on the assumption that the fuel cost characteristic of a generating unit is a continuous and convex function, resulting in inaccurate dispatch. This paper presents the design and application of efficient adaptive differential evolution (ADE algorithm for the solution of the economic power dispatch problem, where the non-convex characteristics of the generators, such us prohibited operating zones and ramp rate limits of the practical generator operation are considered. The 26 bus benchmark test system with 6 units having prohibited operating zones and ramp rate limits was used for testing and validation purposes. The results obtained demonstrate the effectiveness of the proposed method for solving the non-convex economic dispatch problem.

Differentiated protection services with failure probability guarantee for workflow-based applications

Science.gov (United States)

Zhong, Yaoquan; Guo, Wei; Jin, Yaohui; Sun, Weiqiang; Hu, Weisheng

2010-12-01

A cost-effective and service-differentiated provisioning strategy is very desirable to service providers so that they can offer users satisfactory services, while optimizing network resource allocation. Providing differentiated protection services to connections for surviving link failure has been extensively studied in recent years. However, the differentiated protection services for workflow-based applications, which consist of many interdependent tasks, have scarcely been studied. This paper investigates the problem of providing differentiated services for workflow-based applications in optical grid. In this paper, we develop three differentiated protection services provisioning strategies which can provide security level guarantee and network-resource optimization for workflow-based applications. The simulation demonstrates that these heuristic algorithms provide protection cost-effectively while satisfying the applications' failure probability requirements.

Tectono-sedimentary evolution of Erlian basin since late mesozoic and sandstone-hosted uranium metallogenesis

International Nuclear Information System (INIS)

Wei Sanyuan; Qin Mingkuan; Li Yuexiang; He Zhongbo; Chen Anping; Shen Kefeng; Cao Jianying

2006-01-01

Various mineral resources in a basin are associated with its tectono-sedimentary evolution. Based on the analysis of the tectono-sedimentary evolution of Erlian basin, three evolutional stages of Erlian basin are classified, they are: the continental extensional down-faulting stage, the transitional stage from down-faulting to down-warping in Early Cretaceous, and slightly compressional differentiated uplifting-subsidence since Late Cretaceous. According to the mechanism of sandstone-hosted uranium metallogenesis it is suggested that the grey clastic rock series deposited at the stage of down-faulting down-warping transition must be the important target for uranium prospecting, and the differentiated uplifting-subsidence offers necessary conditions for sandstone-hosted uranium ore-formation. Then, types of uranium mineralization that could occur in Erlian basin are discussed, and uranium metallogenic model has been preliminarily summarized. (authors)

Poorly Differentiated Thyroid Carcinoma.

Science.gov (United States)

Setia, Namrata; Barletta, Justine A

2014-12-01

Poorly differentiated thyroid carcinoma (PDTC) has been recognized for the past 30 years as an entity showing intermediate differentiation and clinical behavior between well-differentiated thyroid carcinomas (ie, papillary thyroid carcinoma and follicular thyroid carcinoma) and anaplastic thyroid carcinoma; however, there has been considerable controversy around the definition of PDTC. In this review, the evolution in the definition of PDTC, current diagnostic criteria, differential diagnoses, potentially helpful immunohistochemical studies, and molecular alterations are discussed with the aim of highlighting where the diagnosis of PDTC currently stands. Published by Elsevier Inc.

Fixation times in differentiation and evolution in the presence of bottlenecks, deserts, and oases.

Science.gov (United States)

Chou, Tom; Wang, Yu

2015-05-07

Cellular differentiation and evolution are stochastic processes that can involve multiple types (or states) of particles moving on a complex, high-dimensional state-space or "fitness" landscape. Cells of each specific type can thus be quantified by their population at a corresponding node within a network of states. Their dynamics across the state-space network involve genotypic or phenotypic transitions that can occur upon cell division, such as during symmetric or asymmetric cell differentiation, or upon spontaneous mutation. Here, we use a general multi-type branching processes to study first passage time statistics for a single cell to appear in a specific state. Our approach readily allows for nonexponentially distributed waiting times between transitions, reflecting, e.g., the cell cycle. For simplicity, we restrict most of our detailed analysis to exponentially distributed waiting times (Poisson processes). We present results for a sequential evolutionary process in which L successive transitions propel a population from a "wild-type" state to a given "terminally differentiated," "resistant," or "cancerous" state. Analytic and numeric results are also found for first passage times across an evolutionary chain containing a node with increased death or proliferation rate, representing a desert/bottleneck or an oasis. Processes involving cell proliferation are shown to be "nonlinear" (even though mean-field equations for the expected particle numbers are linear) resulting in first passage time statistics that depend on the position of the bottleneck or oasis. Our results highlight the sensitivity of stochastic measures to cell division fate and quantify the limitations of using certain approximations (such as the fixed-population and mean-field assumptions) in evaluating fixation times. Published by Elsevier Ltd.

SIGNUM: A Matlab, TIN-based landscape evolution model

Science.gov (United States)

Refice, A.; Giachetta, E.; Capolongo, D.

2012-08-01

Several numerical landscape evolution models (LEMs) have been developed to date, and many are available as open source codes. Most are written in efficient programming languages such as Fortran or C, but often require additional code efforts to plug in to more user-friendly data analysis and/or visualization tools to ease interpretation and scientific insight. In this paper, we present an effort to port a common core of accepted physical principles governing landscape evolution directly into a high-level language and data analysis environment such as Matlab. SIGNUM (acronym for Simple Integrated Geomorphological Numerical Model) is an independent and self-contained Matlab, TIN-based landscape evolution model, built to simulate topography development at various space and time scales. SIGNUM is presently capable of simulating hillslope processes such as linear and nonlinear diffusion, fluvial incision into bedrock, spatially varying surface uplift which can be used to simulate changes in base level, thrust and faulting, as well as effects of climate changes. Although based on accepted and well-known processes and algorithms in its present version, it is built with a modular structure, which allows to easily modify and upgrade the simulated physical processes to suite virtually any user needs. The code is conceived as an open-source project, and is thus an ideal tool for both research and didactic purposes, thanks to the high-level nature of the Matlab environment and its popularity among the scientific community. In this paper the simulation code is presented together with some simple examples of surface evolution, and guidelines for development of new modules and algorithms are proposed.

The degree of hydration assessment of blended cement pastes by differential thermal and thermogravimetric analysis. Morphological evolution of the solid phases

International Nuclear Information System (INIS)

Monteagudo, S.M.; Moragues, A.; Gálvez, J.C.; Casati, M.J.; Reyes, E.

2014-01-01

Highlights: • A proposal of hydration degree calculation for blended cement pastes is presented. • The method is based both on the contributions of various authors and on DTA–TG results. • Paste and mortar specimens with BFS, FA and SF mineral admixtures were used. • The evaluation of CH gives information on hydration and pozzolanic reactions. • The assessment of α provides an insight into future strength evolution. - Abstract: The degree of hydration assessment of cement paste from differential thermal and thermogravimetric analysis data has been performed by several authors that have offered a number of proposals for technical application to blended cements. In this paper, two calculation methods are studied in detail. Then, a proposal of the degree of hydration calculation for blended cements, based on the analysis of experimental results of DTA–TG, is presented. The proposed method combines the contributions of the authors and allows straightforward calculation of the degree of hydration from the experimental results. Validation of the methodology was performed by macroscopic and microstructural tests through paste and mortar specimens with blast furnace slag, flying ash and silica fume mineral admixtures bei(g)ng used. Tests of scanning electron microscopy with an energy dispersive analyser on paste specimens, and of mechanical strength on mortar specimens with the same percentages of substitution, were performed. They showed good agreement with the information derived from the differential thermal and thermogravimetric analysis data

Cognitive Function, Origin, and Evolution of Musical Emotions

Directory of Open Access Journals (Sweden)

Leonid Perlovsky

2013-12-01

Full Text Available Cognitive function of music, its origin, and evolution has been a mystery until recently. Here we discuss a theory of a fundamental function of music in cognition and culture. Music evolved in parallel with language. The evolution of language toward a semantically powerful tool required freeing from uncontrolled emotions. Knowledge evolved fast along with language. This created cognitive dissonances, contradictions among knowledge and instincts, which differentiated consciousness. To sustain evolution of language and culture, these contradictions had to be unified. Music was the mechanism of unification. Differentiated emotions are needed for resolving cognitive dissonances. As knowledge has been accumulated, contradictions multiplied and correspondingly more varied emotions had to evolve. While language differentiated psyche, music unified it. Thus the need for refined musical emotions in the process of cultural evolution is grounded in fundamental mechanisms of cognition. This is why today's human mind and cultures cannot exist without today's music.

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

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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.

Thermal evolution of magma reservoirs in the shallow crust and incidence on magma differentiation: the St-Jean-du-Doigt layered intrusion (Brittany, France)

Science.gov (United States)

Barboni, M.; Bussy, F.; Ovtcharova, M.; Schoene, B.

2009-12-01

Understanding the emplacement and growth of intrusive bodies in terms of mechanism, duration, thermal evolution and rates are fundamental aspects of crustal evolution. Recent studies show that many plutons grow in several Ma by in situ accretion of discrete magma pulses, which constitute small-scale magmatic reservoirs. The residence time of magmas, and hence their capacities to interact and differentiate, are controlled by the local thermal environment. The latter is highly dependant on 1) the emplacement depth, 2) the magmas and country rock composition, 3) the country rock thermal conductivity, 4) the rate of magma injection and 5) the geometry of the intrusion. In shallow level plutons, where magmas solidify quickly, evidence for magma mixing and/or differentiation processes is considered by many authors to be inherited from deeper levels. We show however that in-situ differentiation and magma interactions occurred within basaltic and felsic sills at shallow depth (0.3 GPa) in the St-Jean-du-Doigt bimodal intrusion, France. Field evidence coupled to high precision zircon U-Pb dating document progressive thermal maturation within the incrementally built laccolith. Early m-thick mafic sills are homogeneous and fine-grained with planar contacts with neighbouring felsic sills; within a minimal 0.5 Ma time span, the system gets warmer, adjacent sills interact and mingle, and mafic sills are differentiating in the top 40 cm of the layer. Rheological and thermal modelling show that observed in-situ differentiation-accumulation processes may be achieved in less than 10 years at shallow depth, provided that (1) the differentiating sills are injected beneath consolidated, yet still warm basalt sills, which act as low conductive insulating screens, (2) the early mafic sills accreted under the roof of the laccolith as a 100m thick top layer within 0.5 My, and (3) subsequent and sustained magmatic activity occurred on a short time scale (years) at an injection rate of ca. 0

Algebraic aspects of evolution partial differential equation arising in the study of constant elasticity of variance model from financial mathematics

Science.gov (United States)

Motsepa, Tanki; Aziz, Taha; Fatima, Aeeman; Khalique, Chaudry Masood

2018-03-01

The optimal investment-consumption problem under the constant elasticity of variance (CEV) model is investigated from the perspective of Lie group analysis. The Lie symmetry group of the evolution partial differential equation describing the CEV model is derived. The Lie point symmetries are then used to obtain an exact solution of the governing model satisfying a standard terminal condition. Finally, we construct conservation laws of the underlying equation using the general theorem on conservation laws.

Kernel Clustering with a Differential Harmony Search Algorithm for Scheme Classification

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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.

Using some results about the Lie evolution of differential operators to obtain the Fokker-Planck equation for non-Hamiltonian dynamical systems of interest

Science.gov (United States)

Bianucci, Marco

2018-05-01

Finding the generalized Fokker-Planck Equation (FPE) for the reduced probability density function of a subpart of a given complex system is a classical issue of statistical mechanics. Zwanzig projection perturbation approach to this issue leads to the trouble of resumming a series of commutators of differential operators that we show to correspond to solving the Lie evolution of first order differential operators along the unperturbed Liouvillian of the dynamical system of interest. In this paper, we develop in a systematic way the procedure to formally solve this problem. In particular, here we show which the basic assumptions are, concerning the dynamical system of interest, necessary for the Lie evolution to be a group on the space of first order differential operators, and we obtain the coefficients of the so-evolved operators. It is thus demonstrated that if the Liouvillian of the system of interest is not a first order differential operator, in general, the FPE structure breaks down and the master equation contains all the power of the partial derivatives, up to infinity. Therefore, this work shed some light on the trouble of the ubiquitous emergence of both thermodynamics from microscopic systems and regular regression laws at macroscopic scales. However these results are very general and can be applied also in other contexts that are non-Hamiltonian as, for example, geophysical fluid dynamics, where important events, like El Niño, can be considered as large time scale phenomena emerging from the observation of few ocean degrees of freedom of a more complex system, including the interaction with the atmosphere.

Differentiated instruction in a data-based decision-making context

NARCIS (Netherlands)

Faber, Janke M.; Glas, Cees A.W.; Visscher, Adrie J.

2018-01-01

In this study, the relationship between differentiated instruction, as an element of data-based decision making, and student achievement was examined. Classroom observations (n = 144) were used to measure teachers’ differentiated instruction practices and to predict the mathematical achievement of

Modulation of DNA base excision repair during neuronal differentiation

DEFF Research Database (Denmark)

Sykora, Peter; Yang, Jenq-Lin; Ferrarelli, Leslie K

2013-01-01

DNA damage susceptibility and base excision DNA repair (BER) capacity in undifferentiated and differentiated human neural cells. The results show that undifferentiated human SH-SY5Y neuroblastoma cells are less sensitive to oxidative damage than their differentiated counterparts, in part because...

Differential geometry based multiscale models.

Science.gov (United States)

Wei, Guo-Wei

2010-08-01

Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atomistic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier-Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson-Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson-Nernst-Planck equations that are

Differential Geometry Based Multiscale Models

Science.gov (United States)

Wei, Guo-Wei

2010-01-01

Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atom-istic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier–Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson–Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson–Nernst–Planck equations that

Optimal Control for Stochastic Delay Evolution Equations

Energy Technology Data Exchange (ETDEWEB)

Meng, Qingxin, E-mail: mqx@hutc.zj.cn [Huzhou University, Department of Mathematical Sciences (China); Shen, Yang, E-mail: skyshen87@gmail.com [York University, Department of Mathematics and Statistics (Canada)

2016-08-15

In this paper, we investigate a class of infinite-dimensional optimal control problems, where the state equation is given by a stochastic delay evolution equation with random coefficients, and the corresponding adjoint equation is given by an anticipated backward stochastic evolution equation. We first prove the continuous dependence theorems for stochastic delay evolution equations and anticipated backward stochastic evolution equations, and show the existence and uniqueness of solutions to anticipated backward stochastic evolution equations. Then we establish necessary and sufficient conditions for optimality of the control problem in the form of Pontryagin’s maximum principles. To illustrate the theoretical results, we apply stochastic maximum principles to study two examples, an infinite-dimensional linear-quadratic control problem with delay and an optimal control of a Dirichlet problem for a stochastic partial differential equation with delay. Further applications of the two examples to a Cauchy problem for a controlled linear stochastic partial differential equation and an optimal harvesting problem are also considered.

Density based pruning for identification of differentially expressed genes from microarray data

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Xu Jia

2010-11-01

Full Text Available Abstract Motivation Identification of differentially expressed genes from microarray datasets is one of the most important analyses for microarray data mining. Popular algorithms such as statistical t-test rank genes based on a single statistics. The false positive rate of these methods can be improved by considering other features of differentially expressed genes. Results We proposed a pattern recognition strategy for identifying differentially expressed genes. Genes are mapped to a two dimension feature space composed of average difference of gene expression and average expression levels. A density based pruning algorithm (DB Pruning is developed to screen out potential differentially expressed genes usually located in the sparse boundary region. Biases of popular algorithms for identifying differentially expressed genes are visually characterized. Experiments on 17 datasets from Gene Omnibus Database (GEO with experimentally verified differentially expressed genes showed that DB pruning can significantly improve the prediction accuracy of popular identification algorithms such as t-test, rank product, and fold change. Conclusions Density based pruning of non-differentially expressed genes is an effective method for enhancing statistical testing based algorithms for identifying differentially expressed genes. It improves t-test, rank product, and fold change by 11% to 50% in the numbers of identified true differentially expressed genes. The source code of DB pruning is freely available on our website http://mleg.cse.sc.edu/degprune

Fully Digital Chaotic Differential Equation-based Systems And Methods

KAUST Repository

Radwan, Ahmed Gomaa Ahmed; Zidan, Mohammed A.; Salama, Khaled N.

2012-01-01

Various embodiments are provided for fully digital chaotic differential equation-based systems and methods. In one embodiment, among others, a digital circuit includes digital state registers and one or more digital logic modules configured to obtain a first value from two or more of the digital state registers; determine a second value based upon the obtained first values and a chaotic differential equation; and provide the second value to set a state of one of the plurality of digital state registers. In another embodiment, a digital circuit includes digital state registers, digital logic modules configured to obtain outputs from a subset of the digital shift registers and to provide the input based upon a chaotic differential equation for setting a state of at least one of the subset of digital shift registers, and a digital clock configured to provide a clock signal for operating the digital shift registers.

Fully Digital Chaotic Differential Equation-based Systems And Methods

KAUST Repository

Radwan, Ahmed Gomaa Ahmed

2012-09-06

Various embodiments are provided for fully digital chaotic differential equation-based systems and methods. In one embodiment, among others, a digital circuit includes digital state registers and one or more digital logic modules configured to obtain a first value from two or more of the digital state registers; determine a second value based upon the obtained first values and a chaotic differential equation; and provide the second value to set a state of one of the plurality of digital state registers. In another embodiment, a digital circuit includes digital state registers, digital logic modules configured to obtain outputs from a subset of the digital shift registers and to provide the input based upon a chaotic differential equation for setting a state of at least one of the subset of digital shift registers, and a digital clock configured to provide a clock signal for operating the digital shift registers.

The early thermal evolution of Mars

Science.gov (United States)

Bhatia, G. K.; Sahijpal, S.

2016-01-01

Hf-W isotopic systematics of Martian meteorites have provided evidence for the early accretion and rapid core formation of Mars. We present the results of numerical simulations performed to study the early thermal evolution and planetary scale differentiation of Mars. The simulations are confined to the initial 50 Myr (Ma) of the formation of solar system. The accretion energy produced during the growth of Mars and the decay energy due to the short-lived radio-nuclides 26Al, 60Fe, and the long-lived nuclides, 40K, 235U, 238U, and 232Th are incorporated as the heat sources for the thermal evolution of Mars. During the core-mantle differentiation of Mars, the molten metallic blobs were numerically moved using Stoke's law toward the center with descent velocity that depends on the local acceleration due to gravity. Apart from the accretion and the radioactive heat energies, the gravitational energy produced during the differentiation of Mars and the associated heat transfer is also parametrically incorporated in the present work to make an assessment of its contribution to the early thermal evolution of Mars. We conclude that the accretion energy alone cannot produce widespread melting and differentiation of Mars even with an efficient consumption of the accretion energy. This makes 26Al the prime source for the heating and planetary scale differentiation of Mars. We demonstrate a rapid accretion and core-mantle differentiation of Mars within the initial ~1.5 Myr. This is consistent with the chronological records of Martian meteorites.

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.

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

Generalized frameworks for first-order evolution inclusions based on Yosida approximations

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Ram U. Verma

2011-04-01

Full Text Available First, general frameworks for the first-order evolution inclusions are developed based on the A-maximal relaxed monotonicity, and then using the Yosida approximation the solvability of a general class of first-order nonlinear evolution inclusions is investigated. The role the A-maximal relaxed monotonicity is significant in the sense that it not only empowers the first-order nonlinear evolution inclusions but also generalizes the existing Yosida approximations and its characterizations in the current literature.

Using Differential Evolution to Optimize Learning from Signals and Enhance Network Security

Energy Technology Data Exchange (ETDEWEB)

Harmer, Paul K [Air Force Institute of Technology; Temple, Michael A [Air Force Institute of Technology; Buckner, Mark A [ORNL; Farquhar, Ethan [ORNL

2011-01-01

Computer and communication network attacks are commonly orchestrated through Wireless Access Points (WAPs). This paper summarizes proof-of-concept research activity aimed at developing a physical layer Radio Frequency (RF) air monitoring capability to limit unauthorizedWAP access and mprove network security. This is done using Differential Evolution (DE) to optimize the performance of a Learning from Signals (LFS) classifier implemented with RF Distinct Native Attribute (RF-DNA) fingerprints. Performance of the resultant DE-optimized LFS classifier is demonstrated using 802.11a WiFi devices under the most challenging conditions of intra-manufacturer classification, i.e., using emissions of like-model devices that only differ in serial number. Using identical classifier input features, performance of the DE-optimized LFS classifier is assessed relative to a Multiple Discriminant Analysis / Maximum Likelihood (MDA/ML) classifier that has been used for previous demonstrations. The comparative assessment is made using both Time Domain (TD) and Spectral Domain (SD) fingerprint features. For all combinations of classifier type, feature type, and signal-to-noise ratio considered, results show that the DEoptimized LFS classifier with TD features is uperior and provides up to 20% improvement in classification accuracy with proper selection of DE parameters.

Constructing regional advantage: platform policies based on related variety and differentiated knowledge bases.

NARCIS (Netherlands)

Asheim, B.T.; Boschma, R.A.; Cooke, P.

2011-01-01

Constructing regional advantage: platform policies based on related variety and differentiated knowledge bases, Regional Studies. This paper presents a regional innovation policy model based on the idea of constructing regional advantage. This policy model brings together concepts like related

Neuron-Based Heredity and Human Evolution

Directory of Open Access Journals (Sweden)

Don Marshall Gash

2015-06-01

Full Text Available Abstract:Abstract: It is widely recognized that human evolution has been driven by two systems of heredity: one DNA-based and the other based on the transmission of behaviorally acquired information via nervous system functions. The genetic system is ancient, going back to the appearance of life on Earth. It is responsible for the evolutionary processes described by Darwin. By comparison, the nervous system is relatively newly minted and in its highest form, responsible for ideation and mind-to-mind transmission of information. Here the informational capabilities and functions of the two systems are compared. While employing quite different mechanisms for encoding, storing and transmission of information, both systems perform these generic hereditary functions. Three additional features of neuron-based heredity in humans are identified: the ability to transfer hereditary information to other members of their population, not just progeny; a selection process for the information being transferred; and a profoundly shorter time span for creation and dissemination of survival-enhancing information in a population. The mechanisms underlying neuron-based heredity involve hippocampal neurogenesis and memory and learning processes modifying and creating new neural assemblages changing brain structure and functions. A fundamental process in rewiring brain circuitry is through increased neural activity (use strengthening and increasing the number of synaptic connections. Decreased activity in circuitry (disuse leads to loss of synapses. Use and disuse modifying an organ to bring about new modes of living, habits and functions are processes are in line with Neolamarckian concepts of evolution (Packard, 1901. Evidence is presented of bipartite evolutionary processes – Darwinian and Neolamarckian – driving human descent from a common ancestor shared with the great apes.

Phenomenon in the Evolution of Voles (Mammalia, Rodentia, Arvicolidae

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Rekovets L. I.

2017-04-01

Full Text Available This paper presents analytical results of the study of adaptatiogenesis within the family Arvicolidae (Mammalia, Rodentia based of morphological changes of the most functional characters of their masticatory apparatus — dental system — through time. The main directions of the morphological differentiation in parallel evolution of the arvicolid tooth type within the Cricetidae and Arvicolidae during late Miocene and Pliocene were identified and substantiated. It is shown that such unique morphological structure as the arvicolid tooth type has provided a relatively high rate of evolution of voles and a wide range of their adaptive radiation, as well as has determined their taxonomic and ecological diversity. The optimality of the current state of this group and evaluation of evolutionary prospects of Arvicolidae were presented and substantiated here as a phenomenon in their evolution.

Digital differential confocal microscopy based on spatial shift transformation.

Science.gov (United States)

Liu, J; Wang, Y; Liu, C; Wilson, T; Wang, H; Tan, J

2014-11-01

Differential confocal microscopy is a particularly powerful surface profilometry technique in industrial metrology due to its high axial sensitivity and insensitivity to noise. However, the practical implementation of the technique requires the accurate positioning of point detectors in three-dimensions. We describe a simple alternative based on spatial transformation of a through-focus series of images obtained from a homemade beam scanning confocal microscope. This digital differential confocal microscopy approach is described and compared with the traditional Differential confocal microscopy approach. The ease of use of the digital differential confocal microscopy system is illustrated by performing measurements on a 3D standard specimen. © 2014 The Authors Journal of Microscopy © 2014 Royal Microscopical Society.

Design and Experiment of a Differential-Based Power Split Device

Directory of Open Access Journals (Sweden)

Xiaohua Zeng

2014-04-01

Full Text Available Hybrid electric vehicles have excellent energy efficiency and emission performance. Power split device (PSD is a key component that directly affects the control strategy of power systems, the economic consumption of fuel, and the dynamic performance of vehicles. A differential-based PSD was proposed in this paper. A traditional differential was taken as the prototype and a new design method is proposed to retrofit the differential into a PSD. First, a comprehensive approach that includes theoretical analysis and software simulation was used to analyze the possibility as well as the necessity of retrofitting the differential into PSD. Then the differential was retrofitted. Finally, finite element analysis and bench test were conducted. Results showed that applying the retrofitted differential as PSD is practicable.

Agent Based Simulation of Group Emotions Evolution and Strategy Intervention in Extreme Events

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Bo Li

2014-01-01

Full Text Available Agent based simulation method has become a prominent approach in computational modeling and analysis of public emergency management in social science research. The group emotions evolution, information diffusion, and collective behavior selection make extreme incidents studies a complex system problem, which requires new methods for incidents management and strategy evaluation. This paper studies the group emotion evolution and intervention strategy effectiveness using agent based simulation method. By employing a computational experimentation methodology, we construct the group emotion evolution as a complex system and test the effects of three strategies. In addition, the events-chain model is proposed to model the accumulation influence of the temporal successive events. Each strategy is examined through three simulation experiments, including two make-up scenarios and a real case study. We show how various strategies could impact the group emotion evolution in terms of the complex emergence and emotion accumulation influence in extreme events. This paper also provides an effective method of how to use agent-based simulation for the study of complex collective behavior evolution problem in extreme incidents, emergency, and security study domains.

Evolution of cooperation driven by social-welfare-based migration

Science.gov (United States)

Li, Yan; Ye, Hang; Zhang, Hong

2016-03-01

Individuals' migration behavior may play a significant role in the evolution of cooperation. In reality, individuals' migration behavior may depend on their perceptions of social welfare. To study the relationship between social-welfare-based migration and the evolution of cooperation, we consider an evolutionary prisoner's dilemma game (PDG) in which an individual's migration depends on social welfare but not on the individual's own payoff. By introducing three important social welfare functions (SWFs) that are commonly studied in social science, we find that social-welfare-based migration can promote cooperation under a wide range of parameter values. In addition, these three SWFs have different effects on cooperation, especially through the different spatial patterns formed by migration. Because the relative efficiency of the three SWFs will change if the parameter values are changed, we cannot determine which SWF is optimal for supporting cooperation. We also show that memory capacity, which is needed to evaluate individual welfare, may affect cooperation levels in opposite directions under different SWFs. Our work should be helpful for understanding the evolution of human cooperation and bridging the chasm between studies of social preferences and studies of social cooperation.

Evolution of Wireless Sensor Networks for Industrial Control

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Arthur Low

2013-05-01

Full Text Available Technologies evolve in a process of gradual scientific change, but the commercial application of technologies is discontinuous. Managers interested in technology evolution can integrate these contrasting ideas using a powerful theoretical framework, based on the concept of punctuated equilibrium from evolutionary biology. The framework, which enables the differentiation of the technical evolution of a technology from its market application, is used in this article to compare the two standards for wireless sensor networks (WSN for industrial instrumentation and control: WirelessHART and ISA100.11a. The two WSN standards are the product of two different market contexts, which have selected different minimum viable technologies for evolution in their respective niches. Network security issues present some important selection criteria. Both WSN standards implement security countermeasures against localized wireless network attacks based on the application of the AES encryption standard, but some specific security threats – some local, others remotely launched – are only well-defended by the adoption of public-key cryptographic (PKC protocols, which only ISA100.11a supports. This article concludes that the mainstream market potential of the Internet has influenced the evolution of ISA100.11a and will continue to demand that each WSN standard evolve in ways that are difficult to predict.

The Evolution of Reputation-Based Cooperation in Regular Networks

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Tatsuya Sasaki

2017-01-01

Full Text Available Despite recent advances in reputation technologies, it is not clear how reputation systems can affect human cooperation in social networks. Although it is known that two of the major mechanisms in the evolution of cooperation are spatial selection and reputation-based reciprocity, theoretical study of the interplay between both mechanisms remains almost uncharted. Here, we present a new individual-based model for the evolution of reciprocal cooperation between reputation and networks. We comparatively analyze four of the leading moral assessment rules—shunning, image scoring, stern judging, and simple standing—and base the model on the giving game in regular networks for Cooperators, Defectors, and Discriminators. Discriminators rely on a proper moral assessment rule. By using individual-based models, we show that the four assessment rules are differently characterized in terms of how cooperation evolves, depending on the benefit-to-cost ratio, the network-node degree, and the observation and error conditions. Our findings show that the most tolerant rule—simple standing—is the most robust among the four assessment rules in promoting cooperation in regular networks.

Link-based quantitative methods to identify differentially coexpressed genes and gene Pairs

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Ye Zhi-Qiang

2011-08-01

Full Text Available Abstract Background Differential coexpression analysis (DCEA is increasingly used for investigating the global transcriptional mechanisms underlying phenotypic changes. Current DCEA methods mostly adopt a gene connectivity-based strategy to estimate differential coexpression, which is characterized by comparing the numbers of gene neighbors in different coexpression networks. Although it simplifies the calculation, this strategy mixes up the identities of different coexpression neighbors of a gene, and fails to differentiate significant differential coexpression changes from those trivial ones. Especially, the correlation-reversal is easily missed although it probably indicates remarkable biological significance. Results We developed two link-based quantitative methods, DCp and DCe, to identify differentially coexpressed genes and gene pairs (links. Bearing the uniqueness of exploiting the quantitative coexpression change of each gene pair in the coexpression networks, both methods proved to be superior to currently popular methods in simulation studies. Re-mining of a publicly available type 2 diabetes (T2D expression dataset from the perspective of differential coexpression analysis led to additional discoveries than those from differential expression analysis. Conclusions This work pointed out the critical weakness of current popular DCEA methods, and proposed two link-based DCEA algorithms that will make contribution to the development of DCEA and help extend it to a broader spectrum.

Hybrid Differential Evolution Optimisation for Earth Observation Satellite Scheduling with Time-Dependent Earliness-Tardiness Penalties

Directory of Open Access Journals (Sweden)

Guoliang Li

2017-01-01

Full Text Available We study the order acceptance and scheduling (OAS problem with time-dependent earliness-tardiness penalties in a single agile earth observation satellite environment where orders are defined by their release dates, available processing time windows ranging from earliest start date to deadline, processing times, due dates, sequence-dependent setup times, and revenues. The objective is to maximise total revenue, where the revenue from an order is a piecewise linear function of its earliness and tardiness with reference to its due date. We formulate this problem as a mixed integer linear programming model and develop a novel hybrid differential evolution (DE algorithm under self-adaptation framework to solve this problem. Compared with classical DE, hybrid DE employs two mutation operations, scaling factor adaptation and crossover probability adaptation. Computational tests indicate that the proposed algorithm outperforms classical DE in addition to two other variants of DE.

Differential equations, mechanics, and computation

CERN Document Server

Palais, Richard S

2009-01-01

This book provides a conceptual introduction to the theory of ordinary differential equations, concentrating on the initial value problem for equations of evolution and with applications to the calculus of variations and classical mechanics, along with a discussion of chaos theory and ecological models. It has a unified and visual introduction to the theory of numerical methods and a novel approach to the analysis of errors and stability of various numerical solution algorithms based on carefully chosen model problems. While the book would be suitable as a textbook for an undergraduate or elementary graduate course in ordinary differential equations, the authors have designed the text also to be useful for motivated students wishing to learn the material on their own or desiring to supplement an ODE textbook being used in a course they are taking with a text offering a more conceptual approach to the subject.

Landscape evolution by subglacial quarrying

DEFF Research Database (Denmark)

Ugelvig, Sofie Vej; Egholm, D.L.; Iverson, Neal R.

In glacial landscape evolution models, subglacial erosion rates are often related to basal sliding or ice discharge by a power-law. This relation can be justified for bedrock abrasion because rock debris transported in the basal ice drives the erosion. However, a simple relation between rates of ...... evolution models. Geology, v. 40, no. 8, 679-682 (2012). Schoof, C. The effect of cavitation on glacier sliding. Proc. R. Soc. A , 461, 609-627 (2005). Jaeger, J.C., and Cook, N.G.W. Fundamentals of rock mechanics: New York, Chapman and Hall, 593 p. (1979)......In glacial landscape evolution models, subglacial erosion rates are often related to basal sliding or ice discharge by a power-law. This relation can be justified for bedrock abrasion because rock debris transported in the basal ice drives the erosion. However, a simple relation between rates...... of sliding and erosion is not well supported when considering models for quarrying of rock blocks from the bed. Iverson (2012) introduced a new subglacial quarrying model that operates from the theory of adhesive wear. The model is based on the fact that cavities, with a high level of bedrock differential...

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.

Niche evolution and adaptive radiation: Testing the order of trait divergence

Science.gov (United States)

Ackerly, D.D.; Schwilk, D.W.; Webb, C.O.

2006-01-01

In the course of an adaptive radiation, the evolution of niche parameters is of particular interest for understanding modes of speciation and the consequences for coexistence of related species within communities. We pose a general question: In the course of an evolutionary radiation, do traits related to within-community niche differences (?? niche) evolve before or after differentiation of macrohabitat affinity or climatic tolerances (?? niche)? Here we introduce a new test to address this question, based on a modification of the method of independent contrasts. The divergence order test (DOT) is based on the average age of the nodes on a tree, weighted by the absolute magnitude of the contrast at each node for a particular trait. The comparison of these weighted averages reveals whether large divergences for one trait have occurred earlier or later in the course of diversification, relative to a second trait; significance is determined by bootstrapping from maximum-likelihood ancestral state reconstructions. The method is applied to the evolution of Ceanothus, a woody plant group in California, in which co-occurring species exhibit significant differences in a key leaf trait (specific leaf area) associated with contrasting physiological and life history strategies. Co-occurring species differ more for this trait than expected under a null model of community assembly. This ?? niche difference evolved early in the divergence of two major subclades within Ceanothus, whereas climatic distributions (?? niche traits) diversified later within each of the subclades. However, rapid evolution of climate parameters makes inferences of early divergence events highly uncertain, and differentiation of the ?? niche might have taken place throughout the evolution of the group, without leaving a clear phylogenetic signal. Similar patterns observed in several plant and animal groups suggest that early divergence of ?? niche traits might be a common feature of niche evolution in

Semigroup methods for evolution equations on networks

CERN Document Server

Mugnolo, Delio

2014-01-01

This concise text is based on a series of lectures held only a few years ago and originally intended as an introduction to known results on linear hyperbolic and parabolic equations.  Yet the topic of differential equations on graphs, ramified spaces, and more general network-like objects has recently gained significant momentum and, well beyond the confines of mathematics, there is a lively interdisciplinary discourse on all aspects of so-called complex networks. Such network-like structures can be found in virtually all branches of science, engineering and the humanities, and future research thus calls for solid theoretical foundations.      This book is specifically devoted to the study of evolution equations – i.e., of time-dependent differential equations such as the heat equation, the wave equation, or the Schrödinger equation (quantum graphs) – bearing in mind that the majority of the literature in the last ten years on the subject of differential equations of graphs has been devoted to ellip...

The Evolution of ICT Markets: An Agent-Based Model on Complex Networks

Science.gov (United States)

Zhao, Liangjie; Wu, Bangtao; Chen, Zhong; Li, Li

Information and communication technology (ICT) products exhibit positive network effects.The dynamic process of ICT markets evolution has two intrinsic characteristics: (1) customers are influenced by each others’ purchasing decision; (2) customers are intelligent agents with bounded rationality.Guided by complex systems theory, we construct an agent-based model and simulate on complex networks to examine how the evolution can arise from the interaction of customers, which occur when they make expectations about the future installed base of a product by the fraction of neighbors who are using the same product in his personal network.We demonstrate that network effects play an important role in the evolution of markets share, which make even an inferior product can dominate the whole market.We also find that the intensity of customers’ communication can influence whether the best initial strategy for firms is to improve product quality or expand their installed base.

Genome differentiation of Drosophila melanogaster from a microclimate contrast in Evolution Canyon, Israel

Science.gov (United States)

Hübner, Sariel; Rashkovetsky, Eugenia; Kim, Young Bun; Oh, Jung Hun; Michalak, Katarzyna; Weiner, Dmitry; Korol, Abraham B.; Nevo, Eviatar; Michalak, Pawel

2013-01-01

The opposite slopes of “Evolution Canyon” in Israel have served as a natural model system of adaptation to a microclimate contrast. Long-term studies of Drosophila melanogaster populations inhabiting the canyon have exhibited significant interslope divergence in thermal and drought stress resistance, candidate genes, mobile elements, habitat choice, mating discrimination, and wing-shape variation, all despite close physical proximity of the contrasting habitats, as well as substantial interslope migration. To examine patterns of genetic differentiation at the genome-wide level, we used high coverage sequencing of the flies’ genomes. A total of 572 genes were significantly different in allele frequency between the slopes, 106 out of which were associated with 74 significantly overrepresented gene ontology (GO) terms, particularly so with response to stimulus and developmental and reproductive processes, thus corroborating previous observations of interslope divergence in stress response, life history, and mating functions. There were at least 37 chromosomal “islands” of interslope divergence and low sequence polymorphism, plausible signatures of selective sweeps, more abundant in flies derived from one (north-facing) of the slopes. Positive correlation between local recombination rate and the level of nucleotide polymorphism was also found. PMID:24324170

Epochs of radioactivity in historical evolution of the earth with reference to evolution of biosphere

International Nuclear Information System (INIS)

Neruchev, S.G.

1976-01-01

Periodic epochs of intense contamination of the medium by uranium in the course of the Earth's evolution and the biogene mechanism of uranium accumulation in sediments during the lifetime are established. Global differentiation of the radioactivity epochs and essential effect of periodic radiation on the evolution of biosphere are shown. Radiational-mutational mechanism in shown to be extremely nonuniform during the evolution of the organic kingdom. It has been found that the intermittency in radioactive epochs is responsible for peculiarities in the stratigraphic distribution of sedimentary uranium, sapropelic shales, phosphorites, oil-producing rocks and other minerals

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

Musical emotions: Functions, origins, evolution

Science.gov (United States)

Perlovsky, Leonid

2010-03-01

Theories of music origins and the role of musical emotions in the mind are reviewed. Most existing theories contradict each other, and cannot explain mechanisms or roles of musical emotions in workings of the mind, nor evolutionary reasons for music origins. Music seems to be an enigma. Nevertheless, a synthesis of cognitive science and mathematical models of the mind has been proposed describing a fundamental role of music in the functioning and evolution of the mind, consciousness, and cultures. The review considers ancient theories of music as well as contemporary theories advanced by leading authors in this field. It addresses one hypothesis that promises to unify the field and proposes a theory of musical origin based on a fundamental role of music in cognition and evolution of consciousness and culture. We consider a split in the vocalizations of proto-humans into two types: one less emotional and more concretely-semantic, evolving into language, and the other preserving emotional connections along with semantic ambiguity, evolving into music. The proposed hypothesis departs from other theories in considering specific mechanisms of the mind-brain, which required the evolution of music parallel with the evolution of cultures and languages. Arguments are reviewed that the evolution of language toward becoming the semantically powerful tool of today required emancipation from emotional encumbrances. The opposite, no less powerful mechanisms required a compensatory evolution of music toward more differentiated and refined emotionality. The need for refined music in the process of cultural evolution is grounded in fundamental mechanisms of the mind. This is why today's human mind and cultures cannot exist without today's music. The reviewed hypothesis gives a basis for future analysis of why different evolutionary paths of languages were paralleled by different evolutionary paths of music. Approaches toward experimental verification of this hypothesis in

Evolution, functional differentiation, and co-expression of the RLK gene family revealed in Jilin ginseng, Panax ginseng C.A. Meyer.

Science.gov (United States)

Lin, Yanping; Wang, Kangyu; Li, Xiangyu; Sun, Chunyu; Yin, Rui; Wang, Yanfang; Wang, Yi; Zhang, Meiping

2018-02-21

Most genes in a genome exist in the form of a gene family; therefore, it is necessary to have knowledge of how a gene family functions to comprehensively understand organismal biology. The receptor-like kinase (RLK)-encoding gene family is one of the most important gene families in plants. It plays important roles in biotic and abiotic stress tolerances, and growth and development. However, little is known about the functional differentiation and relationships among the gene members within a gene family in plants. This study has isolated 563 RLK genes (designated as PgRLK genes) expressed in Jilin ginseng (Panax ginseng C.A. Meyer), investigated their evolution, and deciphered their functional diversification and relationships. The PgRLK gene family is highly diverged and formed into eight types. The LRR type is the earliest and most prevalent, while only the Lec type originated after P. ginseng evolved. Furthermore, although the members of the PgRLK gene family all encode receptor-like protein kinases and share conservative domains, they are functionally very diverse, participating in numerous biological processes. The expressions of different members of the PgRLK gene family are extremely variable within a tissue, at a developmental stage and in the same cultivar, but most of the genes tend to express correlatively, forming a co-expression network. These results not only provide a deeper and comprehensive understanding of the evolution, functional differentiation and correlation of a gene family in plants, but also an RLK genic resource useful for enhanced ginseng genetic improvement.

NONLINEAR EVOLUTION OF GLOBAL HYDRODYNAMIC SHALLOW-WATER INSTABILITY IN THE SOLAR TACHOCLINE

International Nuclear Information System (INIS)

Dikpati, Mausumi

2012-01-01

We present a fully nonlinear hydrodynamic 'shallow-water' model of the solar tachocline. The model consists of a global spherical shell of differentially rotating fluid, which has a deformable top, thus allowing motions in radial directions along with latitudinal and longitudinal directions. When the system is perturbed, in the course of its nonlinear evolution it can generate unstable low-frequency shallow-water shear modes from the differential rotation, high-frequency gravity waves, and their interactions. Radiative and overshoot tachoclines are characterized in this model by high and low effective gravity values, respectively. Building a semi-implicit spectral scheme containing very low numerical diffusion, we perform nonlinear evolution of shallow-water modes. Our first results show that (1) high-latitude jets or polar spin-up occurs due to nonlinear evolution of unstable hydrodynamic shallow-water disturbances and differential rotation, (2) Reynolds stresses in the disturbances together with changing shell thickness and meridional flow are responsible for the evolution of differential rotation, (3) disturbance energy primarily remains concentrated in the lowest longitudinal wavenumbers, (4) an oscillation in energy between perturbed and unperturbed states occurs due to evolution of these modes in a nearly dissipation-free system, and (5) disturbances are geostrophic, but occasional nonadjustment in geostrophic balance can occur, particularly in the case of high effective gravity, leading to generation of gravity waves. We also find that a linearly stable differential rotation profile remains nonlinearly stable.

Maglev Train Signal Processing Architecture Based on Nonlinear Discrete Tracking Differentiator.

Science.gov (United States)

Wang, Zhiqiang; Li, Xiaolong; Xie, Yunde; Long, Zhiqiang

2018-05-24

In a maglev train levitation system, signal processing plays an important role for the reason that some sensor signals are prone to be corrupted by noise due to the harsh installation and operation environment of sensors and some signals cannot be acquired directly via sensors. Based on these concerns, an architecture based on a new type of nonlinear second-order discrete tracking differentiator is proposed. The function of this signal processing architecture includes filtering signal noise and acquiring needed signals for levitation purposes. The proposed tracking differentiator possesses the advantages of quick convergence, no fluttering, and simple calculation. Tracking differentiator's frequency characteristics at different parameter values are studied in this paper. The performance of this new type of tracking differentiator is tested in a MATLAB simulation and this tracking-differentiator is implemented in Very-High-Speed Integrated Circuit Hardware Description Language (VHDL). In the end, experiments are conducted separately on a test board and a maglev train model. Simulation and experiment results show that the performance of this novel signal processing architecture can fulfill the real system requirement.

Differential alkylation-based redox proteomics - Lessons learnt

DEFF Research Database (Denmark)

Wojdyla, Katarzyna; Rogowska-Wrzesinska, Adelina

2015-01-01

Cysteine is one of the most reactive amino acids. This is due to the electronegativity of sulphur atom in the side chain of thiolate group. It results in cysteine being present in several distinct redox forms inside the cell. Amongst these, reversible oxidations, S-nitrosylation and S-sulfenylati......Cysteine is one of the most reactive amino acids. This is due to the electronegativity of sulphur atom in the side chain of thiolate group. It results in cysteine being present in several distinct redox forms inside the cell. Amongst these, reversible oxidations, S-nitrosylation and S......-sulfenylation are crucial mediators of intracellular redox signalling, with known associations to health and disease. Study of their functionalities has intensified thanks to the development of various analytical strategies, with particular contribution from differential alkylation-based proteomics methods. Presented here...... is a critical evaluation of differential alkylation-based strategies for the analysis of S-nitrosylation and S-sulfenylation. The aim is to assess the current status and to provide insights for future directions in the dynamically evolving field of redox proteomics. To achieve that we collected 35 original...

Random number generation based on digital differential chaos

KAUST Repository

Zidan, Mohammed A.; Radwan, Ahmed G.; Salama, Khaled N.

2012-01-01

In this paper, we present a fully digital differential chaos based random number generator. The output of the digital circuit is proved to be chaotic by calculating the output time series maximum Lyapunov exponent. We introduce a new post processing

Lie symmetries for systems of evolution equations

Science.gov (United States)

Paliathanasis, Andronikos; Tsamparlis, Michael

2018-01-01

The Lie symmetries for a class of systems of evolution equations are studied. The evolution equations are defined in a bimetric space with two Riemannian metrics corresponding to the space of the independent and dependent variables of the differential equations. The exact relation of the Lie symmetries with the collineations of the bimetric space is determined.

Multi-objective differential evolution with adaptive Cauchy mutation for short-term multi-objective optimal hydro-thermal scheduling

Energy Technology Data Exchange (ETDEWEB)

Qin Hui [College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074 (China); Zhou Jianzhong, E-mail: jz.zhou@hust.edu.c [College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074 (China); Lu Youlin; Wang Ying; Zhang Yongchuan [College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074 (China)

2010-04-15

A new multi-objective optimization method based on differential evolution with adaptive Cauchy mutation (MODE-ACM) is presented to solve short-term multi-objective optimal hydro-thermal scheduling (MOOHS) problem. Besides fuel cost, the pollutant gas emission is also optimized as an objective. The water transport delay between connected reservoirs and the effect of valve-point loading of thermal units are also taken into account in the presented problem formulation. The proposed algorithm adopts an elitist archive to retain non-dominated solutions obtained during the evolutionary process. It modifies the DE's operators to make it suit for multi-objective optimization (MOO) problems and improve its performance. Furthermore, to avoid premature convergence, an adaptive Cauchy mutation is proposed to preserve the diversity of population. An effective constraints handling method is utilized to handle the complex equality and inequality constraints. The effectiveness of the proposed algorithm is tested on a hydro-thermal system consisting of four cascaded hydro plants and three thermal units. The results obtained by MODE-ACM are compared with several previous studies. It is found that the results obtained by MODE-ACM are superior in terms of fuel cost as well as emission output, consuming a shorter time. Thus it can be a viable alternative to generate optimal trade-offs for short-term MOOHS problem.

Development and evaluation of intelligent machine tools based on knowledge evolution in M2M environment

International Nuclear Information System (INIS)

Kim, Dong Hoon; Song, Jun Yeob; Lee, Jong Hyun; Cha, Suk Keun

2009-01-01

In the near future, the foreseen improvement in machine tools will be in the form of a knowledge evolution-based intelligent device. The goal of this study is to develop intelligent machine tools having knowledge-evolution capability in Machine to Machine (M2M) wired and wireless environment. The knowledge evolution-based intelligent machine tools are expected to be capable of gathering knowledge autonomously, producing knowledge, understanding knowledge, applying reasoning to knowledge, making new decisions, dialoguing with other machines, etc. The concept of the knowledge-evolution intelligent machine originated from the process of machine control operation by the sense, dialogue and decision of a human expert. The structure of knowledge evolution in M2M and the scheme for a dialogue agent among agent-based modules such as a sensory agent, a dialogue agent and an expert system (decision support agent) are presented in this paper, and work-offset compensation from thermal change and recommendation of cutting condition are performed on-line for knowledge-evolution verification

Proteinuria: The diagnostic strategy based on urine proteins differentiation

Directory of Open Access Journals (Sweden)

Stojimirović Biljana B.

2004-01-01

Full Text Available Basal glomerular membrane represents mechanical and electrical barrier for passing of the plasma proteins. Mechanical barrier is composed of cylindrical pores and filtration fissure, and negative layer charge in exterior and interior side of basal glomerular membrane, made of heparan sulphate and sialoglicoproteine, provides certain electrical barrier. Diagnostic strategy based on different serum and urine proteins enables the differentiation of various types of proteinuria. Depending on etiology of proteinuria it can be prerenal, renal and postrenal. By analyzing albumin, armicroglobulin, immunoglobulin G and armacroglobulin, together with total protein in urine, it is possible to detect and differentiate causes of prerenal, renal (glomerular, tubular, glomerulo-tubular and postrenal proteinuria. The adequate and early differentiation of proteinuria type is of an immense diagnostic and therapeutic importance.

Stability-based sorting: The forgotten process behind (not only) biological evolution.

Science.gov (United States)

Toman, Jan; Flegr, Jaroslav

2017-12-21

Natural selection is considered to be the main process that drives biological evolution. It requires selected entities to originate dependent upon one another by the means of reproduction or copying, and for the progeny to inherit the qualities of their ancestors. However, natural selection is a manifestation of a more general persistence principle, whose temporal consequences we propose to name "stability-based sorting" (SBS). Sorting based on static stability, i.e., SBS in its strict sense and usual conception, favours characters that increase the persistence of their holders and act on all material and immaterial entities. Sorted entities could originate independently from each other, are not required to propagate and need not exhibit heredity. Natural selection is a specific form of SBS-sorting based on dynamic stability. It requires some form of heredity and is based on competition for the largest difference between the speed of generating its own copies and their expiration. SBS in its strict sense and selection thus have markedly different evolutionary consequences that are stressed in this paper. In contrast to selection, which is opportunistic, SBS is able to accumulate even momentarily detrimental characters that are advantageous for the long-term persistence of sorted entities. However, it lacks the amplification effect based on the preferential propagation of holders of advantageous characters. Thus, it works slower than selection and normally is unable to create complex adaptations. From a long-term perspective, SBS is a decisive force in evolution-especially macroevolution. SBS offers a new explanation for numerous evolutionary phenomena, including broad distribution and persistence of sexuality, altruistic behaviour, horizontal gene transfer, patterns of evolutionary stasis, planetary homeostasis, increasing ecosystem resistance to disturbances, and the universal decline of disparity in the evolution of metazoan lineages. SBS acts on all levels in

The evolution of alliance capabilities

NARCIS (Netherlands)

Heimeriks, K.H.; Duysters, G.M.; Vanhaverbeke, W.P.M.

2004-01-01

This paper assesses the effectiveness and differential performance effects of learning mechanisms on the evolution of alliance capabilities. Relying on the concept of capability lifecycles, prior research has suggested that different capability levels could be identified in which different

Proliferation and osteoblastic differentiation of hMSCs on cellulose-based hydrogels.

Science.gov (United States)

Raucci, Maria Grazia; Alvarez-Perez, Marco Antonio; Demitri, Christian; Sannino, Alessandro; Ambrosio, Luigi

2012-01-01

The aim of this project was to study the proliferation and differentiation of human Mesenchymal Stem Cells (hMSCs) onto a cellulose-based hydrogel for bone tissue engineering. Modified-cellulose hydrogel was prepared via double esterification crosslinking using citric acid. The response of human Mesenchymal Stem Cells (hMSCs) in terms of cell proliferation and differentiation into osteoblastic phenotype was evaluated by using Alamar blue assay and Alkaline phosphatase activity. The results showed that CMCNa and CMCNa_CA have no negative effect on hMSC, adhesion and proliferation. Moreover, the increase of the ALP expression for CMCNa_CA confirms the ability of the hydrogels to support the osteoblastic differentiation. The cellulose-based hydrogels have a potential application as filler in bone tissue regeneration.

Does the oxytocin receptor polymorphism (rs2254298 confer 'vulnerability' for psychopathology or 'differential susceptibility'? insights from evolution

Directory of Open Access Journals (Sweden)

Brüne Martin

2012-04-01

Full Text Available Abstract The diathesis-stress model of psychiatric conditions has recently been challenged by the view that it might be more accurate to speak of 'differential susceptibility' or 'plasticity' genes, rather than one-sidedly focusing on individual vulnerability. That is, the same allelic variation that predisposes to a psychiatric disorder if associated with (developmentally early environmental adversity may lead to a better-than-average functional outcome in the same domain under thriving (or favourable environmental conditions. Studies of polymorphic variations of the serotonin transporter gene, the monoamino-oxidase-inhibitor A coding gene or the dopamine D4 receptor gene indicate that the early environment plays a crucial role in the development of favourable versus unfavourable outcomes. Current evidence is limited, however, to establishing a link between genetic variation and behavioural phenotypes. In contrast, little is known about how plasticity may be expressed at the neuroanatomical level as a 'hard-wired' correlate of observable behaviour. The present review article seeks to further strengthen the argument in favour of the differential susceptibility theory by incorporating findings from behavioural and neuroanatomical studies in relation to genetic variation of the oxytocin receptor gene. It is suggested that polymorphic variation at the oxytocin receptor gene (rs2254298 is associated with sociability, amygdala volume and differential risk for psychiatric conditions including autism, depression and anxiety disorder, depending on the quality of early environmental experiences. Seeing genetic variation at the core of developmental plasticity can explain, in contrast to the diathesis-stress perspective, why evolution by natural selection has maintained such 'risk' alleles in the gene pool of a population. Please see related manuscript: http://www.biomedcentral.com/1741-7015/10/37

Kinetic-Monte-Carlo-Based Parallel Evolution Simulation Algorithm of Dust Particles

Directory of Open Access Journals (Sweden)

Xiaomei Hu

2014-01-01

Full Text Available The evolution simulation of dust particles provides an important way to analyze the impact of dust on the environment. KMC-based parallel algorithm is proposed to simulate the evolution of dust particles. In the parallel evolution simulation algorithm of dust particles, data distribution way and communication optimizing strategy are raised to balance the load of every process and reduce the communication expense among processes. The experimental results show that the simulation of diffusion, sediment, and resuspension of dust particles in virtual campus is realized and the simulation time is shortened by parallel algorithm, which makes up for the shortage of serial computing and makes the simulation of large-scale virtual environment possible.

Global biogeography and evolution of Cuvierina pteropods.

Science.gov (United States)

Burridge, Alice K; Goetze, Erica; Raes, Niels; Huisman, Jef; Peijnenburg, Katja T C A

2015-03-12

Shelled pteropods are planktonic gastropods that are potentially good indicators of the effects of ocean acidification. They also have high potential for the study of zooplankton evolution because they are metazoan plankton with a good fossil record. We investigated phenotypic and genetic variation in pteropods belonging to the genus Cuvierina in relation to their biogeographic distribution across the world's oceans. We aimed to assess species boundaries and to reconstruct their evolutionary history. We distinguished six morphotypes based on geometric morphometric analyses of shells from 926 museum and 113 fresh specimens. These morphotypes have distinct geographic distributions across the Atlantic, Pacific and Indian oceans, and belong to three major genetic clades based on COI and 28S DNA sequence data. Using a fossil-calibrated phylogeny, we estimated that these clades separated in the Late Oligocene and Early to Middle Miocene. We found evidence for ecological differentiation among all morphotypes based on ecological niche modelling with sea surface temperature, salinity and phytoplankton biomass as primary determinants. Across all analyses, we found highly congruent patterns of differentiation suggesting species level divergences between morphotypes. However, we also found distinct morphotypes (e.g. in the Atlantic Ocean) that were ecologically, but not genetically differentiated. Given the distinct ecological and phenotypic specializations found among both described and undescribed Cuvierina taxa, they may not respond equally to future ocean changes and may not be equally sensitive to ocean acidification. Our findings support the view that ecological differentiation may be an important driving force in the speciation of zooplankton.

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

Improved stochastic approximation methods for discretized parabolic partial differential equations

Science.gov (United States)

Guiaş, Flavius

2016-12-01

We present improvements of the stochastic direct simulation method, a known numerical scheme based on Markov jump processes which is used for approximating solutions of ordinary differential equations. This scheme is suited especially for spatial discretizations of evolution partial differential equations (PDEs). By exploiting the full path simulation of the stochastic method, we use this first approximation as a predictor and construct improved approximations by Picard iterations, Runge-Kutta steps, or a combination. This has as consequence an increased order of convergence. We illustrate the features of the improved method at a standard benchmark problem, a reaction-diffusion equation modeling a combustion process in one space dimension (1D) and two space dimensions (2D).

Stochastic Differential Equation-Based Flexible Software Reliability Growth Model

Directory of Open Access Journals (Sweden)

P. K. Kapur

2009-01-01

Full Text Available Several software reliability growth models (SRGMs have been developed by software developers in tracking and measuring the growth of reliability. As the size of software system is large and the number of faults detected during the testing phase becomes large, so the change of the number of faults that are detected and removed through each debugging becomes sufficiently small compared with the initial fault content at the beginning of the testing phase. In such a situation, we can model the software fault detection process as a stochastic process with continuous state space. In this paper, we propose a new software reliability growth model based on Itô type of stochastic differential equation. We consider an SDE-based generalized Erlang model with logistic error detection function. The model is estimated and validated on real-life data sets cited in literature to show its flexibility. The proposed model integrated with the concept of stochastic differential equation performs comparatively better than the existing NHPP-based models.

Collage-based approaches for elliptic partial differential equations inverse problems

Science.gov (United States)

Yodzis, Michael; Kunze, Herb

2017-01-01

The collage method for inverse problems has become well-established in the literature in recent years. Initial work developed a collage theorem, based upon Banach's fixed point theorem, for treating inverse problems for ordinary differential equations (ODEs). Amongst the subsequent work was a generalized collage theorem, based upon the Lax-Milgram representation theorem, useful for treating inverse problems for elliptic partial differential equations (PDEs). Each of these two different approaches can be applied to elliptic PDEs in one space dimension. In this paper, we explore and compare how the two different approaches perform for the estimation of the diffusivity for a steady-state heat equation.

29 CFR 1620.20 - Pay differentials claimed to be based on extra duties.

Science.gov (United States)

2010-07-01

... 29 Labor 4 2010-07-01 2010-07-01 false Pay differentials claimed to be based on extra duties. 1620.20 Section 1620.20 Labor Regulations Relating to Labor (Continued) EQUAL EMPLOYMENT OPPORTUNITY COMMISSION THE EQUAL PAY ACT § 1620.20 Pay differentials claimed to be based on extra duties. Additional...

Clinical Study on the Visceral Differentiation-Based Acupuncture Therapy for Insomnia

Institute of Scientific and Technical Information of China (English)

LING Li; JIANG Xin-mei; XUE Jin-wei; WANG Miao; KE Rui

2008-01-01

objective;To investigate the clinical effects of acupuncture for insomnia on the basis of visceral differentiation.Methods;Seventy cases of insomnia were randomly divided into a treatment group and a control group,The former was treated by acupuncture based on visceral differentiation and the latter by the routine acupuncture therapy.Results;The clinical effcts were significantly better in the treatment group than that of the control group(P＜0.05).Conclusion;The visceral difrerentiation-based acupuncture therapy may enhance the therapeutic effects for insomnia patients.

Modeling evolution of the mind and cultures: emotional Sapir-Whorf hypothesis

Science.gov (United States)

Perlovsky, Leonid I.

2009-05-01

Evolution of cultures is ultimately determined by mechanisms of the human mind. The paper discusses the mechanisms of evolution of language from primordial undifferentiated animal cries to contemporary conceptual contents. In parallel with differentiation of conceptual contents, the conceptual contents were differentiated from emotional contents of languages. The paper suggests the neural brain mechanisms involved in these processes. Experimental evidence and theoretical arguments are discussed, including mathematical approaches to cognition and language: modeling fields theory, the knowledge instinct, and the dual model connecting language and cognition. Mathematical results are related to cognitive science, linguistics, and psychology. The paper gives an initial mathematical formulation and mean-field equations for the hierarchical dynamics of both the human mind and culture. In the mind heterarchy operation of the knowledge instinct manifests through mechanisms of differentiation and synthesis. The emotional contents of language are related to language grammar. The conclusion is an emotional version of Sapir-Whorf hypothesis. Cultural advantages of "conceptual" pragmatic cultures, in which emotionality of language is diminished and differentiation overtakes synthesis resulting in fast evolution at the price of self doubts and internal crises are compared to those of traditional cultures where differentiation lags behind synthesis, resulting in cultural stability at the price of stagnation. Multi-language, multi-ethnic society might combine the benefits of stability and fast differentiation. Unsolved problems and future theoretical and experimental directions are discussed.

Research on social communication network evolution based on topology potential distribution

Science.gov (United States)

Zhao, Dongjie; Jiang, Jian; Li, Deyi; Zhang, Haisu; Chen, Guisheng

2011-12-01

Aiming at the problem of social communication network evolution, first, topology potential is introduced to measure the local influence among nodes in networks. Second, from the perspective of topology potential distribution the method of network evolution description based on topology potential distribution is presented, which takes the artificial intelligence with uncertainty as basic theory and local influence among nodes as essentiality. Then, a social communication network is constructed by enron email dataset, the method presented is used to analyze the characteristic of the social communication network evolution and some useful conclusions are got, implying that the method is effective, which shows that topology potential distribution can effectively describe the characteristic of sociology and detect the local changes in social communication network.

An approach of community evolution based on gravitational relationship refactoring in dynamic networks

International Nuclear Information System (INIS)

Yin, Guisheng; Chi, Kuo; Dong, Yuxin; Dong, Hongbin

2017-01-01

In this paper, an approach of community evolution based on gravitational relationship refactoring between the nodes in a dynamic network is proposed, and it can be used to simulate the process of community evolution. A static community detection algorithm and a dynamic community evolution algorithm are included in the approach. At first, communities are initialized by constructing the core nodes chains, the nodes can be iteratively searched and divided into corresponding communities via the static community detection algorithm. For a dynamic network, an evolutionary process is divided into three phases, and behaviors of community evolution can be judged according to the changing situation of the core nodes chain in each community. Experiments show that the proposed approach can achieve accuracy and availability in the synthetic and real world networks. - Highlights: • The proposed approach considers both the static community detection and dynamic community evolution. • The approach of community evolution can identify the whole 6 common evolution events. • The proposed approach can judge the evolutionary events according to the variations of the core nodes chains.

Maglev Train Signal Processing Architecture Based on Nonlinear Discrete Tracking Differentiator

Directory of Open Access Journals (Sweden)

Zhiqiang Wang

2018-05-01

Full Text Available In a maglev train levitation system, signal processing plays an important role for the reason that some sensor signals are prone to be corrupted by noise due to the harsh installation and operation environment of sensors and some signals cannot be acquired directly via sensors. Based on these concerns, an architecture based on a new type of nonlinear second-order discrete tracking differentiator is proposed. The function of this signal processing architecture includes filtering signal noise and acquiring needed signals for levitation purposes. The proposed tracking differentiator possesses the advantages of quick convergence, no fluttering, and simple calculation. Tracking differentiator’s frequency characteristics at different parameter values are studied in this paper. The performance of this new type of tracking differentiator is tested in a MATLAB simulation and this tracking-differentiator is implemented in Very-High-Speed Integrated Circuit Hardware Description Language (VHDL. In the end, experiments are conducted separately on a test board and a maglev train model. Simulation and experiment results show that the performance of this novel signal processing architecture can fulfill the real system requirement.

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.

Direct approach for solving nonlinear evolution and two-point

Indian Academy of Sciences (India)

Time-delayed nonlinear evolution equations and boundary value problems have a wide range of applications in science and engineering. In this paper, we implement the differential transform method to solve the nonlinear delay differential equation and boundary value problems. Also, we present some numerical examples ...

Study of the evolution of nitrogen compounds during grape ripening. application to differentiate grape varieties and cultivated systems.

Science.gov (United States)

Garde-Cerdán, Teresa; Lorenzo, Cándida; Lara, José Félix; Pardo, Francisco; Ancín-Azpilicueta, Carmen; Salinas, M Rosario

2009-03-25

The aim of this work was to study the evolution of amino acids and ammonium during grape ripening and to evaluate its application to differentiate grape varieties and cultivated systems (organic and nonorganic). For this purpose, Monastrell, Syrah, Merlot, and Petit Verdot grapes produced using conventional agriculture and Monastrell grape cultivated using organic agriculture, collected during two consecutive harvests at different stages of ripening, were studied. These years of harvest were very different climatic years; even so, the grape varieties presented similar qualitative compositions. Therefore, the percentage of amino acids at harvest moment allowed differentiation of grapes according to variety and cultivated system, regardless of the year. The nitrogen composition could allow estimation of the fermentative aroma potential of grapes. Thus, Syrah was the grape with the greatest aroma potential at harvest. Monastrell nonorganic grape had a concentration of nitrogen compounds superior to that of Monastrell organic grape. In Monastrell, Syrah, and Merlot, traditional varieties in the area, the highest concentration of nitrogen compounds coincided with the highest degrees Baume/total acidity ratio and color index during 2007. Consequently, technological and phenolic maturity of these grape varieties coincided with the maximum composition of nitrogen compounds. However, in 2008, this did not happen because grape ripening was irregular as a consequence of different climatological conditions.

Nanoscale Morphology Evolution Under Ion Irradiation

Energy Technology Data Exchange (ETDEWEB)

Aziz, Michael J. [President & Fellows of Harvard College, Cambridge, MA (United States)

2014-11-10

We showed that the half-century-old paradigm of morphological instability under irradiation due to the curvature-dependence of the sputter yield, can account neither for the phase diagram nor the amplification or decay rates that we measure in the simplest possible experimental system -- an elemental semiconductor with an amorphous surface under noble-gas ion irradiation; We showed that a model of pattern formation based on the impact-induced redistribution of atoms that do not get sputtered away explains our experimental observations; We developed a first-principles, parameter-free approach for predicting morphology evolution, starting with molecular dynamics simulations of single ion impacts, lasting picoseconds, and upscaling through a rigorous crater-function formalism to develop a partial differential equation that predicts morphology evolution on time scales more than twelve orders of magnitude longer than can be covered by the molecular dynamics; We performed the first quantitative comparison of the contributions to morphological instability from sputter removal and from impact-induced redistribution of atoms that are removed, and showed that the former is negligible compared to the latter; We established a new paradigm for impact-induced morphology evolution based on crater functions that incorporate both redistribution and sputter effects; and We developed a model of nanopore closure by irradiation-induced stress and irradiationenhanced fluidity, for the near-surface irradiation regime in which nuclear stopping predominates, and showed that it explains many aspects of pore closure kinetics that we measure experimentally.

Strategy Dynamics through a Demand-Based Lens: The Evolution of Market Boundaries, Resource Rents and Competitive Positions

OpenAIRE

Adner, Ron; Zemsky, Peter

2003-01-01

We develop a novel approach to the dynamics of business strategy that is grounded in an explicit treatment of consumer choice when technologies improve over time. We address the evolution of market boundaries, resource rents and competitive positions by adapting models of competition with differentiated products. Our model is consistent with the central strategy assertion that competitive interactions are governed by superior value creation and competitive advantage. More importantly, it show...

Brightness temperature simulation of snow cover based on snow grain size evolution using in situ data

Science.gov (United States)

Wu, Lili; Li, Xiaofeng; Zhao, Kai; Zheng, Xingming; Jiang, Tao

2016-07-01

Snow depth parameter inversion from passive microwave remote sensing is of great significance to hydrological process and climate systems. The Helsinki University of Technology (HUT) model is a commonly used snow emission model. Snow grain size (SGS) is one of the important input parameters, but SGS is difficult to obtain in broad areas. The time series of SGS are first evolved by an SGS evolution model (Jordan 91) using in situ data. A good linear relationship between the effective SGS in HUT and the evolution SGS was found. Then brightness temperature simulations are performed based on the effective SGS and evolution SGS. The results showed that the biases of the simulated brightness temperatures based on the effective SGS and evolution SGS were -6.5 and -3.6 K, respectively, for 18.7 GHz and -4.2 and -4.0 K for 36.5 GHz. Furthermore, the model is performed in six pixels with different land use/cover type in other areas. The results showed that the simulated brightness temperatures based on the evolution SGS were consistent with those from the satellite. Consequently, evolution SGS appears to be a simple method to obtain an appropriate SGS for the HUT model.

A Bayesian Network Based Adaptability Design of Product Structures for Function Evolution

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Shaobo Li

2018-03-01

Full Text Available Structure adaptability design is critical for function evolution in product families, in which many structural and functional design factors are intertwined together with manufacturing cost, customer satisfaction, and final market sales. How to achieve a delicate balance among all of these factors to maximize the market performance of the product is too complicated to address based on traditional domain experts’ knowledge or some ad hoc heuristics. Here, we propose a quantitative product evolution design model that is based on Bayesian networks to model the dynamic relationship between customer needs and product structure design. In our model, all of the structural or functional features along with customer satisfaction, manufacturing cost, sale price, market sales, and indirect factors are modeled as random variables denoted as nodes in the Bayesian networks. The structure of the Bayesian model is then determined based on the historical data, which captures the dynamic sophisticated relationship of customer demands of a product, structural design, and market performance. Application of our approach to an electric toothbrush product family evolution design problem shows that our model allows for designers to interrogate with the model and obtain theoretical and decision support for dynamic product feature design process.

and O-based composite materials derived from differential ...

Indian Academy of Sciences (India)

Abstract. In this work, we have made an effort to determine whether the effective atomic numbers of H-, C-, N- and O-based composite materials would indeed remain a constant over the energy grid of 280–1200 keV wherein incoherent scattering dominates their interaction with photons. For this purpose, the differential ...

Efficient Power Scheduling in Smart Homes Using Hybrid Grey Wolf Differential Evolution Optimization Technique with Real Time and Critical Peak Pricing Schemes

Directory of Open Access Journals (Sweden)

Muqaddas Naz

2018-02-01

Full Text Available With the emergence of automated environments, energy demand by consumers is increasing rapidly. More than 80% of total electricity is being consumed in the residential sector. This brings a challenging task of maintaining the balance between demand and generation of electric power. In order to meet such challenges, a traditional grid is renovated by integrating two-way communication between the consumer and generation unit. To reduce electricity cost and peak load demand, demand side management (DSM is modeled as an optimization problem, and the solution is obtained by applying meta-heuristic techniques with different pricing schemes. In this paper, an optimization technique, the hybrid gray wolf differential evolution (HGWDE, is proposed by merging enhanced differential evolution (EDE and gray wolf optimization (GWO scheme using real-time pricing (RTP and critical peak pricing (CPP. Load shifting is performed from on-peak hours to off-peak hours depending on the electricity cost defined by the utility. However, there is a trade-off between user comfort and cost. To validate the performance of the proposed algorithm, simulations have been carried out in MATLAB. Results illustrate that using RTP, the peak to average ratio (PAR is reduced to 53.02%, 29.02% and 26.55%, while the electricity bill is reduced to 12.81%, 12.012% and 12.95%, respectively, for the 15-, 30- and 60-min operational time interval (OTI. On the other hand, the PAR and electricity bill are reduced to 47.27%, 22.91%, 22% and 13.04%, 12%, 11.11% using the CPP tariff.

Novel Design of Recursive Differentiator Based on Lattice Wave Digital Filter

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R. Barsainya

2017-04-01

Full Text Available In this paper, a novel design of third and fifth order differentiator based on lattice wave digital filter (LWDF, established on optimizing L_1-error approximation function using cuckoo search algorithm (CSA is proposed. We present a novel realization of minimum multiplier differentiator using LWD structure leading to requirement of optimizing only N coefficients for Nth order differentiator. The gamma coefficients of lattice wave digital differentiator (LWDD are computed by minimizing the L_1-norm fitness function leading to a flat response. The superiority of the proposed LWDD is evident by comparing it with other differentiators mentioned in the literature. The magnitude response of the designed LWDD is found to be of high accuracy with flat response in a wide frequency range. The simulation and statistical results validates that the designed minimum multiplier LWDD circumvents the existing one in terms of minimum absolute magnitude error, mean relative error (dB and efficient structural realization, thereby making the proposed LWDD a promising approach to digital differentiator design.

Saturation Detection-Based Blocking Scheme for Transformer Differential Protection

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Byung Eun Lee

2014-07-01

Full Text Available This paper describes a current differential relay for transformer protection that operates in conjunction with a core saturation detection-based blocking algorithm. The differential current for the magnetic inrush or over-excitation has a point of inflection at the start and end of each saturation period of the transformer core. At these instants, discontinuities arise in the first-difference function of the differential current. The second- and third-difference functions convert the points of inflection into pulses, the magnitudes of which are large enough to detect core saturation. The blocking signal is activated if the third-difference of the differential current is larger than the threshold and is maintained for one cycle. In addition, a method to discriminate between transformer saturation and current transformer (CT saturation is included. The performance of the proposed blocking scheme was compared with that of a conventional harmonic blocking method. The test results indicate that the proposed scheme successfully discriminates internal faults even with CT saturation from the magnetic inrush, over-excitation, and external faults with CT saturation, and can significantly reduce the operating time delay of the relay.

CIME course on Control of Partial Differential Equations

CERN Document Server

Alabau-Boussouira, Fatiha; Glass, Olivier; Le Rousseau, Jérôme; Zuazua, Enrique

2012-01-01

The term “control theory” refers to the body of results - theoretical, numerical and algorithmic - which have been developed to influence the evolution of the state of a given system in order to meet a prescribed performance criterion. Systems of interest to control theory may be of very different natures. This monograph is concerned with models that can be described by partial differential equations of evolution. It contains five major contributions and is connected to the CIME Course on Control of Partial Differential Equations that took place in Cetraro (CS, Italy), July 19 - 23, 2010.  Specifically, it covers the stabilization of evolution equations, control of the Liouville equation, control in fluid mechanics, control and numerics for the wave equation, and Carleman estimates for elliptic and parabolic equations with application to control. We are confident this work will provide an authoritative reference work for all scientists who are interested in this field, representing at the same time a fri...

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

Science.gov (United States)

Rai, Man Mohan

2006-01-01

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more

Turn-based evolution in a simplified model of artistic creative process

DEFF Research Database (Denmark)

Dahlstedt, Palle

2015-01-01

Evolutionary computation has often been presented as a possible model for creativity in computers. In this paper, evolution is discussed in the light of a theoretical model of human artistic process, recently presented by the author. Some crucial differences between human artistic creativity......, and the results of initial experiments are presented and discussed. Artistic creativity is here modeled as an iterated turn-based process, alternating between a conceptual representation and a material representation of the work-to-be. Evolutionary computation is proposed as a heuristic solution to the principal...... and natural evolution are observed and discussed, also in the light of other creative processes occurring in nature. As a tractable way to overcome these limitations, a new kind of evolutionary implementation of creativity is proposed, based on a simplified version of the previously presented model...

Opposition-Based Adaptive Fireworks Algorithm

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Chibing Gong

2016-07-01

Full Text Available A fireworks algorithm (FWA is a recent swarm intelligence algorithm that is inspired by observing fireworks explosions. An adaptive fireworks algorithm (AFWA proposes additional adaptive amplitudes to improve the performance of the enhanced fireworks algorithm (EFWA. The purpose of this paper is to add opposition-based learning (OBL to AFWA with the goal of further boosting performance and achieving global optimization. Twelve benchmark functions are tested in use of an opposition-based adaptive fireworks algorithm (OAFWA. The final results conclude that OAFWA significantly outperformed EFWA and AFWA in terms of solution accuracy. Additionally, OAFWA was compared with a bat algorithm (BA, differential evolution (DE, self-adapting control parameters in differential evolution (jDE, a firefly algorithm (FA, and a standard particle swarm optimization 2011 (SPSO2011 algorithm. The research results indicate that OAFWA ranks the highest of the six algorithms for both solution accuracy and runtime cost.

Differentiating case-based learning from problem-based learning after a twoday introductory workshop on case-based learning

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Aqil Mohammad Daher

2017-12-01

Full Text Available Background Considerable overlap exists between case-based learning (CBL and problem-based learning (PBL and differentiating between the two can be difficult for a lot of the academicians. Aims This study gauged the ability of members of medical school, familiar with a problem-based learning (PBL curriculum, to differentiate between case-based learning (CBL and PBL after a two-day workshop on CBL. Methods A questionnaire was distributed to all participants, attending the introductory course on CBL. It was designed to document the basic characteristics of the respondents, their preference for either CBL or PBL, their ability to recognize differences between CBL and PBL, and their overall perception of the course. Results Of the total workshop participants, 80.5 per cent returned the completed questionnaire. The mean age of the respondents was 44.12±12.31 years and women made up a slight majority. Majority favoured CBL over PBL and felt it was more clinical, emphasizes on self-directed learning, provides more opportunities for learning, permits in-depth exploration of cases, has structured environment and encourages the use of all learning resources. On the respondents’ ability to discriminate CBL from PBL, a weighted score of 39.9 per cent indicated a failure on the part of the respondents to correctly identify differences between CBL and PBL. Less than half opined that CBL was a worthwhile progression from PBL and about third would recommend CBL over PBL. Conclusion It seems that majority of the respondents failed to adequately differentiate between CBL and PBL and didn’t favour CBL over PBL.

The Brassica oleracea genome reveals the asymmetrical evolution of polyploid genomes

Science.gov (United States)

Liu, Shengyi; Liu, Yumei; Yang, Xinhua; Tong, Chaobo; Edwards, David; Parkin, Isobel A. P.; Zhao, Meixia; Ma, Jianxin; Yu, Jingyin; Huang, Shunmou; Wang, Xiyin; Wang, Junyi; Lu, Kun; Fang, Zhiyuan; Bancroft, Ian; Yang, Tae-Jin; Hu, Qiong; Wang, Xinfa; Yue, Zhen; Li, Haojie; Yang, Linfeng; Wu, Jian; Zhou, Qing; Wang, Wanxin; King, Graham J; Pires, J. Chris; Lu, Changxin; Wu, Zhangyan; Sampath, Perumal; Wang, Zhuo; Guo, Hui; Pan, Shengkai; Yang, Limei; Min, Jiumeng; Zhang, Dong; Jin, Dianchuan; Li, Wanshun; Belcram, Harry; Tu, Jinxing; Guan, Mei; Qi, Cunkou; Du, Dezhi; Li, Jiana; Jiang, Liangcai; Batley, Jacqueline; Sharpe, Andrew G; Park, Beom-Seok; Ruperao, Pradeep; Cheng, Feng; Waminal, Nomar Espinosa; Huang, Yin; Dong, Caihua; Wang, Li; Li, Jingping; Hu, Zhiyong; Zhuang, Mu; Huang, Yi; Huang, Junyan; Shi, Jiaqin; Mei, Desheng; Liu, Jing; Lee, Tae-Ho; Wang, Jinpeng; Jin, Huizhe; Li, Zaiyun; Li, Xun; Zhang, Jiefu; Xiao, Lu; Zhou, Yongming; Liu, Zhongsong; Liu, Xuequn; Qin, Rui; Tang, Xu; Liu, Wenbin; Wang, Yupeng; Zhang, Yangyong; Lee, Jonghoon; Kim, Hyun Hee; Denoeud, France; Xu, Xun; Liang, Xinming; Hua, Wei; Wang, Xiaowu; Wang, Jun; Chalhoub, Boulos; Paterson, Andrew H

2014-01-01

Polyploidization has provided much genetic variation for plant adaptive evolution, but the mechanisms by which the molecular evolution of polyploid genomes establishes genetic architecture underlying species differentiation are unclear. Brassica is an ideal model to increase knowledge of polyploid evolution. Here we describe a draft genome sequence of Brassica oleracea, comparing it with that of its sister species B. rapa to reveal numerous chromosome rearrangements and asymmetrical gene loss in duplicated genomic blocks, asymmetrical amplification of transposable elements, differential gene co-retention for specific pathways and variation in gene expression, including alternative splicing, among a large number of paralogous and orthologous genes. Genes related to the production of anticancer phytochemicals and morphological variations illustrate consequences of genome duplication and gene divergence, imparting biochemical and morphological variation to B. oleracea. This study provides insights into Brassica genome evolution and will underpin research into the many important crops in this genus. PMID:24852848

Quasi-Newton methods for parameter estimation in functional differential equations

Science.gov (United States)

Brewer, Dennis W.

1988-01-01

A state-space approach to parameter estimation in linear functional differential equations is developed using the theory of linear evolution equations. A locally convergent quasi-Newton type algorithm is applied to distributed systems with particular emphasis on parameters that induce unbounded perturbations of the state. The algorithm is computationally implemented on several functional differential equations, including coefficient and delay estimation in linear delay-differential equations.

Convergent evolution as natural experiment: the tape of life reconsidered.

Science.gov (United States)

Powell, Russell; Mariscal, Carlos

2015-12-06

Stephen Jay Gould argued that replaying the 'tape of life' would result in radically different evolutionary outcomes. Recently, biologists and philosophers of science have paid increasing attention to the theoretical importance of convergent evolution-the independent origination of similar biological forms and functions-which many interpret as evidence against Gould's thesis. In this paper, we examine the evidentiary relevance of convergent evolution for the radical contingency debate. We show that under the right conditions, episodes of convergent evolution can constitute valid natural experiments that support inferences regarding the deep counterfactual stability of macroevolutionary outcomes. However, we argue that proponents of convergence have problematically lumped causally heterogeneous phenomena into a single evidentiary basket, in effect treating all convergent events as if they are of equivalent theoretical import. As a result, the 'critique from convergent evolution' fails to engage with key claims of the radical contingency thesis. To remedy this, we develop ways to break down the heterogeneous set of convergent events based on the nature of the generalizations they support. Adopting this more nuanced approach to convergent evolution allows us to differentiate iterated evolutionary outcomes that are probably common among alternative evolutionary histories and subject to law-like generalizations, from those that do little to undermine and may even support, the Gouldian view of life.

Testing Differential Effects of Computer-Based, Web-Based and Paper-Based Administration of Questionnaire Research Instruments

Science.gov (United States)

Hardre, Patricia L.; Crowson, H. Michael; Xie, Kui; Ly, Cong

2007-01-01

Translation of questionnaire instruments to digital administration systems, both self-contained and web-based, is widespread and increasing daily. However, the literature is lean on controlled empirical studies investigating the potential for differential effects of administrative methods. In this study, two university student samples were…

Self-mixing differential vibrometer based on electronic channel subtraction

International Nuclear Information System (INIS)

Donati, Silvano; Norgia, Michele; Giuliani, Guido

2006-01-01

An instrument for noncontact measurement of differential vibrations is developed, based on the self-mixing interferometer. As no reference arm is available in the self-mixing configuration, the differential mode is obtained by electronic subtraction of signals from two (nominally equal) vibrometer channels, taking advantage that channels are servo stabilized and thus insensitive to speckle and other sources of amplitude fluctuation. We show that electronic subtraction is nearly as effective as field superposition. Common-mode suppression is 25-30 dB, the dynamic range (amplitude) is in excess of 100 μm, and the minimum measurable (differential) amplitude is 20 nm on aB=10 kHz bandwidth. The instrument has been used to measure vibrations of two metal samples kept in contact, revealing the hysteresis cycle in the microslip and gross-slip regimes, which are of interest in the study of friction induced vibration damping of gas turbine blades for aircraft applications

Fault Detection Based on Tracking Differentiator Applied on the Suspension System of Maglev Train

Directory of Open Access Journals (Sweden)

Hehong Zhang

2015-01-01

Full Text Available A fault detection method based on the optimized tracking differentiator is introduced. It is applied on the acceleration sensor of the suspension system of maglev train. It detects the fault of the acceleration sensor by comparing the acceleration integral signal with the speed signal obtained by the optimized tracking differentiator. This paper optimizes the control variable when the states locate within or beyond the two-step reachable region to improve the performance of the approximate linear discrete tracking differentiator. Fault-tolerant control has been conducted by feedback based on the speed signal acquired from the optimized tracking differentiator when the acceleration sensor fails. The simulation and experiment results show the practical usefulness of the presented method.

Using meta-differential evolution to enhance a calculation of a continuous blood glucose level.

Science.gov (United States)

Koutny, Tomas

2016-09-01

We developed a new model of glucose dynamics. The model calculates blood glucose level as a function of transcapillary glucose transport. In previous studies, we validated the model with animal experiments. We used analytical method to determine model parameters. In this study, we validate the model with subjects with type 1 diabetes. In addition, we combine the analytic method with meta-differential evolution. To validate the model with human patients, we obtained a data set of type 1 diabetes study that was coordinated by Jaeb Center for Health Research. We calculated a continuous blood glucose level from continuously measured interstitial fluid glucose level. We used 6 different scenarios to ensure robust validation of the calculation. Over 96% of calculated blood glucose levels fit A+B zones of the Clarke Error Grid. No data set required any correction of model parameters during the time course of measuring. We successfully verified the possibility of calculating a continuous blood glucose level of subjects with type 1 diabetes. This study signals a successful transition of our research from an animal experiment to a human patient. Researchers can test our model with their data on-line at https://diabetes.zcu.cz. Copyright © 2016 The Author. Published by Elsevier Ireland Ltd.. All rights reserved.

Differential alkylation-based redox proteomics--Lessons learnt.

Science.gov (United States)

Wojdyla, Katarzyna; Rogowska-Wrzesinska, Adelina

2015-12-01

Cysteine is one of the most reactive amino acids. This is due to the electronegativity of sulphur atom in the side chain of thiolate group. It results in cysteine being present in several distinct redox forms inside the cell. Amongst these, reversible oxidations, S-nitrosylation and S-sulfenylation are crucial mediators of intracellular redox signalling, with known associations to health and disease. Study of their functionalities has intensified thanks to the development of various analytical strategies, with particular contribution from differential alkylation-based proteomics methods. Presented here is a critical evaluation of differential alkylation-based strategies for the analysis of S-nitrosylation and S-sulfenylation. The aim is to assess the current status and to provide insights for future directions in the dynamically evolving field of redox proteomics. To achieve that we collected 35 original research articles published since 2010 and analysed them considering the following parameters, (i) resolution of modification site, (ii) quantitative information, including correction of modification levels by protein abundance changes and determination of modification site occupancy, (iii) throughput, including the amount of starting material required for analysis. The results of this meta-analysis are the core of this review, complemented by issues related to biological models and sample preparation in redox proteomics, including conditions for free thiol blocking and labelling of target cysteine oxoforms. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Critical spaces for quasilinear parabolic evolution equations and applications

Science.gov (United States)

Prüss, Jan; Simonett, Gieri; Wilke, Mathias

2018-02-01

We present a comprehensive theory of critical spaces for the broad class of quasilinear parabolic evolution equations. The approach is based on maximal Lp-regularity in time-weighted function spaces. It is shown that our notion of critical spaces coincides with the concept of scaling invariant spaces in case that the underlying partial differential equation enjoys a scaling invariance. Applications to the vorticity equations for the Navier-Stokes problem, convection-diffusion equations, the Nernst-Planck-Poisson equations in electro-chemistry, chemotaxis equations, the MHD equations, and some other well-known parabolic equations are given.

Molecular evolution and the latitudinal biodiversity gradient.

Science.gov (United States)

Dowle, E J; Morgan-Richards, M; Trewick, S A

2013-06-01

Species density is higher in the tropics (low latitude) than in temperate regions (high latitude) resulting in a latitudinal biodiversity gradient (LBG). The LBG must be generated by differential rates of speciation and/or extinction and/or immigration among regions, but the role of each of these processes is still unclear. Recent studies examining differences in rates of molecular evolution have inferred a direct link between rate of molecular evolution and rate of speciation, and postulated these as important drivers of the LBG. Here we review the molecular genetic evidence and examine the factors that might be responsible for differences in rates of molecular evolution. Critical to this is the directionality of the relationship between speciation rates and rates of molecular evolution.

Differential morphology and image processing.

Science.gov (United States)

Maragos, P

1996-01-01

Image processing via mathematical morphology has traditionally used geometry to intuitively understand morphological signal operators and set or lattice algebra to analyze them in the space domain. We provide a unified view and analytic tools for morphological image processing that is based on ideas from differential calculus and dynamical systems. This includes ideas on using partial differential or difference equations (PDEs) to model distance propagation or nonlinear multiscale processes in images. We briefly review some nonlinear difference equations that implement discrete distance transforms and relate them to numerical solutions of the eikonal equation of optics. We also review some nonlinear PDEs that model the evolution of multiscale morphological operators and use morphological derivatives. Among the new ideas presented, we develop some general 2-D max/min-sum difference equations that model the space dynamics of 2-D morphological systems (including the distance computations) and some nonlinear signal transforms, called slope transforms, that can analyze these systems in a transform domain in ways conceptually similar to the application of Fourier transforms to linear systems. Thus, distance transforms are shown to be bandpass slope filters. We view the analysis of the multiscale morphological PDEs and of the eikonal PDE solved via weighted distance transforms as a unified area in nonlinear image processing, which we call differential morphology, and briefly discuss its potential applications to image processing and computer vision.

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.

Problem-Based Service Learning: The Evolution of a Team Project

Science.gov (United States)

Connor-Greene, Patricia A.

2002-01-01

In this article, I describe the evolution of a problem-based service learning project in an undergraduate Abnormal Psychology course. Students worked in teams on a semester-long project to locate and evaluate information and treatment for specific psychiatric disorders. As part of the project, each team selected relevant bibliographic materials,…

Measure, Then Show: Grasping Human Evolution Through an Inquiry-Based, Data-driven Hominin Skulls Lab.

Science.gov (United States)

Bayer, Chris N; Luberda, Michael

2016-01-01

Incomprehension and denial of the theory of evolution among high school students has been observed to also occur when teachers are not equipped to deliver a compelling case also for human evolution based on fossil evidence. This paper assesses the outcomes of a novel inquiry-based paleoanthropology lab teaching human evolution to high-school students. The inquiry-based Be a Paleoanthropologist for a Day lab placed a dozen hominin skulls into the hands of high-school students. Upon measuring three variables of human evolution, students explain what they have observed and discuss findings. In the 2013/14 school year, 11 biology classes in 7 schools in the Greater New Orleans area participated in this lab. The interviewed teacher cohort unanimously agreed that the lab featuring hominin skull replicas and stimulating student inquiry was a pedagogically excellent method of delivering the subject of human evolution. First, the lab's learning path of transforming facts to data, information to knowledge, and knowledge to acceptance empowered students to themselves execute part of the science that underpins our understanding of deep time hominin evolution. Second, although challenging, the hands-on format of the lab was accessible to high-school students, most of whom were readily able to engage the lab's scientific process. Third, the lab's exciting and compelling pedagogy unlocked higher order thinking skills, effectively activating the cognitive, psychomotor and affected learning domains as defined in Bloom's taxonomy. Lastly, the lab afforded students a formative experience with a high degree of retention and epistemic depth. Further study is warranted to gauge the degree of these effects.

PCL-PDMS-PCL copolymer-based microspheres mediate cardiovascular differentiation from embryonic stem cells

Science.gov (United States)

Song, Liqing

Poly-epsilon-caprolactone (PCL) based copolymers have received much attention as drug or growth factor delivery carriers and tissue engineering scaffolds due to their biocompatibility, biodegradability, and tunable biophysical properties. Copolymers of PCL and polydimethylsiloxane (PDMS) also have shape memory behaviors and can be made into thermoresponsive shape memory polymers for various biomedical applications such as smart sutures and vascular stents. However, the influence of biophysical properties of PCL-PDMS-PCL copolymers on stem cell lineage commitment is not well understood. In this study, PDMS was used as soft segments of varying length to tailor the biophysical properties of PCL-based co-polymers. While low elastic modulus (affected cardiovascular differentiation of embryonic stem cells, the range of 60-100 MPa PCL-PDMS-PCL showed little influence on the differentiation. Then different size (30-140 mum) of microspheres were fabricated from PCL-PDMS-PCL copolymers and incorporated within embryoid bodies (EBs). Mesoderm differentiation was induced using bone morphogenetic protein (BMP)-4 for cardiovascular differentiation. Differential expressions of mesoderm progenitor marker KDR and vascular markers CD31 and VE-cadherin were observed for the cells differentiated from EBs incorporated with microspheres of different size, while little difference was observed for cardiac marker alpha-actinin expression. Small size of microspheres (30 mum) resulted in higher expression of KDR while medium size of microspheres (94 mum) resulted in higher CD31 and VE-cadherin expression. This study indicated that the biophysical properties of PCL-based copolymers impacted stem cell lineage commitment, which should be considered for drug delivery and tissue engineering applications.

Modelling the evolution and diversity of cumulative culture

Science.gov (United States)

Enquist, Magnus; Ghirlanda, Stefano; Eriksson, Kimmo

2011-01-01

Previous work on mathematical models of cultural evolution has mainly focused on the diffusion of simple cultural elements. However, a characteristic feature of human cultural evolution is the seemingly limitless appearance of new and increasingly complex cultural elements. Here, we develop a general modelling framework to study such cumulative processes, in which we assume that the appearance and disappearance of cultural elements are stochastic events that depend on the current state of culture. Five scenarios are explored: evolution of independent cultural elements, stepwise modification of elements, differentiation or combination of elements and systems of cultural elements. As one application of our framework, we study the evolution of cultural diversity (in time as well as between groups). PMID:21199845

CRPropa 3.1—a low energy extension based on stochastic differential equations

Energy Technology Data Exchange (ETDEWEB)

Merten, Lukas; Tjus, Julia Becker; Eichmann, Björn [Theoretische Physik IV: Plasma-Astroteilchenphysik, Ruhr-Universität Bochum, Universitätsstrasse 150, 44801 Bochum (Germany); Fichtner, Horst [Theoretische Physik IV: Weltraum- und Astrophysik, Ruhr-Universität Bochum, Universitätsstrasse 150, 44801 Bochum (Germany); Sigl, Günter, E-mail: lukas.merten@rub.de, E-mail: julia.tjus@rub.de, E-mail: hf@tp4.rub.de, E-mail: eiche@tp4.rub.de, E-mail: guenter.sigl@desy.de [II Institut für Theoretische Physik, Universität Hamburg, Luruper Chaussee 149, 22761 Hamburg (Germany)

2017-06-01

The propagation of charged cosmic rays through the Galactic environment influences all aspects of the observation at Earth. Energy spectrum, composition and arrival directions are changed due to deflections in magnetic fields and interactions with the interstellar medium. Today the transport is simulated with different simulation methods either based on the solution of a transport equation (multi-particle picture) or a solution of an equation of motion (single-particle picture). We developed a new module for the publicly available propagation software CRPropa 3.1, where we implemented an algorithm to solve the transport equation using stochastic differential equations. This technique allows us to use a diffusion tensor which is anisotropic with respect to an arbitrary magnetic background field. The source code of CRPropa is written in C++ with python steering via SWIG which makes it easy to use and computationally fast. In this paper, we present the new low-energy propagation code together with validation procedures that are developed to proof the accuracy of the new implementation. Furthermore, we show first examples of the cosmic ray density evolution, which depends strongly on the ratio of the parallel κ{sub ∥} and perpendicular κ{sub ⊥} diffusion coefficients. This dependency is systematically examined as well the influence of the particle rigidity on the diffusion process.

CRPropa 3.1—a low energy extension based on stochastic differential equations

International Nuclear Information System (INIS)

Merten, Lukas; Tjus, Julia Becker; Eichmann, Björn; Fichtner, Horst; Sigl, Günter

2017-01-01

The propagation of charged cosmic rays through the Galactic environment influences all aspects of the observation at Earth. Energy spectrum, composition and arrival directions are changed due to deflections in magnetic fields and interactions with the interstellar medium. Today the transport is simulated with different simulation methods either based on the solution of a transport equation (multi-particle picture) or a solution of an equation of motion (single-particle picture). We developed a new module for the publicly available propagation software CRPropa 3.1, where we implemented an algorithm to solve the transport equation using stochastic differential equations. This technique allows us to use a diffusion tensor which is anisotropic with respect to an arbitrary magnetic background field. The source code of CRPropa is written in C++ with python steering via SWIG which makes it easy to use and computationally fast. In this paper, we present the new low-energy propagation code together with validation procedures that are developed to proof the accuracy of the new implementation. Furthermore, we show first examples of the cosmic ray density evolution, which depends strongly on the ratio of the parallel κ ∥ and perpendicular κ ⊥ diffusion coefficients. This dependency is systematically examined as well the influence of the particle rigidity on the diffusion process.

CRPropa 3.1—a low energy extension based on stochastic differential equations

Science.gov (United States)

Merten, Lukas; Becker Tjus, Julia; Fichtner, Horst; Eichmann, Björn; Sigl, Günter

2017-06-01

The propagation of charged cosmic rays through the Galactic environment influences all aspects of the observation at Earth. Energy spectrum, composition and arrival directions are changed due to deflections in magnetic fields and interactions with the interstellar medium. Today the transport is simulated with different simulation methods either based on the solution of a transport equation (multi-particle picture) or a solution of an equation of motion (single-particle picture). We developed a new module for the publicly available propagation software CRPropa 3.1, where we implemented an algorithm to solve the transport equation using stochastic differential equations. This technique allows us to use a diffusion tensor which is anisotropic with respect to an arbitrary magnetic background field. The source code of CRPropa is written in C++ with python steering via SWIG which makes it easy to use and computationally fast. In this paper, we present the new low-energy propagation code together with validation procedures that are developed to proof the accuracy of the new implementation. Furthermore, we show first examples of the cosmic ray density evolution, which depends strongly on the ratio of the parallel κ∥ and perpendicular κ⊥ diffusion coefficients. This dependency is systematically examined as well the influence of the particle rigidity on the diffusion process.

Experimental Validation of a Differential Variational Inequality-Based Approach for Handling Friction and Contact in Vehicle

Science.gov (United States)

2015-11-20

terrain modeled using the discrete element method (DEM). Experimental Validation of a Differential Variational Inequality -Based Approach for Handling...COVERED 00-00-2015 to 00-00-2015 4. TITLE AND SUBTITLE Experimental Validation of a Differential Variational Inequality -Based Approach for...sinkage, and single wheel tests. 1.1. Modeling Frictional Contact Via Differential Variational Inequalities Consider a three dimensional (3D) system of

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

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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.

Genetic-evolution-based optimization methods for engineering design

Science.gov (United States)

Rao, S. S.; Pan, T. S.; Dhingra, A. K.; Venkayya, V. B.; Kumar, V.

1990-01-01

This paper presents the applicability of a biological model, based on genetic evolution, for engineering design optimization. Algorithms embodying the ideas of reproduction, crossover, and mutation are developed and applied to solve different types of structural optimization problems. Both continuous and discrete variable optimization problems are solved. A two-bay truss for maximum fundamental frequency is considered to demonstrate the continuous variable case. The selection of locations of actuators in an actively controlled structure, for minimum energy dissipation, is considered to illustrate the discrete variable case.

Combined Differential and Static Pressure Sensor based on a Double-Bridged Structure

DEFF Research Database (Denmark)

Pedersen, Casper; Jespersen, S.T.; Krog, J.P.

2005-01-01

A combined differential and static silicon microelectromechanical system pressure sensor based on a double piezoresistive Wheatstone bridge structure is presented. The developed sensor has a conventional (inner) bridge on a micromachined diaphragm and a secondary (outer) bridge on the chip...... substrate. A novel approach is demonstrated with a combined measurement of outputs from the two bridges, which results in a combined deduction of both differential and static media pressure. Also following this new approach, a significant improvement in differential pressure sensor accuracy is achieved....... Output from the two bridges depends linearly on both differential and absolute (relative to atmospheric pressure) media pressure. Furthermore, the sensor stress distributions involved are studied by three-dimensional finite-element (FE) stress analysis. Furthermore, the FE analysis evaluates current...

Average Gait Differential Image Based Human Recognition

Directory of Open Access Journals (Sweden)

Jinyan Chen

2014-01-01

Full Text Available The difference between adjacent frames of human walking contains useful information for human gait identification. Based on the previous idea a silhouettes difference based human gait recognition method named as average gait differential image (AGDI is proposed in this paper. The AGDI is generated by the accumulation of the silhouettes difference between adjacent frames. The advantage of this method lies in that as a feature image it can preserve both the kinetic and static information of walking. Comparing to gait energy image (GEI, AGDI is more fit to representation the variation of silhouettes during walking. Two-dimensional principal component analysis (2DPCA is used to extract features from the AGDI. Experiments on CASIA dataset show that AGDI has better identification and verification performance than GEI. Comparing to PCA, 2DPCA is a more efficient and less memory storage consumption feature extraction method in gait based recognition.

Personalized Medicine Based on Theranostic Radioiodine Molecular Imaging for Differentiated Thyroid Cancer.

Science.gov (United States)

Ahn, Byeong-Cheol

2016-01-01

Molecular imaging based personalized therapy has been a fascinating concept for individualized therapeutic strategy, which is able to attain the highest efficacy and reduce adverse effects in certain patients. Theranostics, which integrates diagnostic testing to detect molecular targets for particular therapeutic modalities, is one of the key technologies that contribute to the success of personalized medicine. Although the term "theranostics" was used after the second millennium, its basic principle was applied more than 70 years ago in the field of thyroidology with radioiodine molecular imaging. Differentiated thyroid cancer, which arises from follicular cells in the thyroid, is the most common endocrine malignancy, and theranostic radioiodine has been successfully applied to diagnose and treat differentiated thyroid cancer, the applications of which were included in the guidelines published by various thyroid or nuclear medicine societies. Through better pathophysiologic understanding of thyroid cancer and advancements in nuclear technologies, theranostic radioiodine contributes more to modern tailored personalized management by providing high therapeutic effect and by avoiding significant adverse effects in differentiated thyroid cancer. This review details the inception of theranostic radioiodine and recent radioiodine applications for differentiated thyroid cancer management as a prototype of personalized medicine based on molecular imaging.

Measure, Then Show: Grasping Human Evolution Through an Inquiry-Based, Data-driven Hominin Skulls Lab.

Directory of Open Access Journals (Sweden)

Chris N Bayer

Full Text Available Incomprehension and denial of the theory of evolution among high school students has been observed to also occur when teachers are not equipped to deliver a compelling case also for human evolution based on fossil evidence. This paper assesses the outcomes of a novel inquiry-based paleoanthropology lab teaching human evolution to high-school students. The inquiry-based Be a Paleoanthropologist for a Day lab placed a dozen hominin skulls into the hands of high-school students. Upon measuring three variables of human evolution, students explain what they have observed and discuss findings. In the 2013/14 school year, 11 biology classes in 7 schools in the Greater New Orleans area participated in this lab. The interviewed teacher cohort unanimously agreed that the lab featuring hominin skull replicas and stimulating student inquiry was a pedagogically excellent method of delivering the subject of human evolution. First, the lab's learning path of transforming facts to data, information to knowledge, and knowledge to acceptance empowered students to themselves execute part of the science that underpins our understanding of deep time hominin evolution. Second, although challenging, the hands-on format of the lab was accessible to high-school students, most of whom were readily able to engage the lab's scientific process. Third, the lab's exciting and compelling pedagogy unlocked higher order thinking skills, effectively activating the cognitive, psychomotor and affected learning domains as defined in Bloom's taxonomy. Lastly, the lab afforded students a formative experience with a high degree of retention and epistemic depth. Further study is warranted to gauge the degree of these effects.

Trait-based diversification shifts reflect differential extinction among fossil taxa.

Science.gov (United States)

Wagner, Peter J; Estabrook, George F

2014-11-18

Evolution provides many cases of apparent shifts in diversification associated with particular anatomical traits. Three general models connect these patterns to anatomical evolution: (i) elevated net extinction of taxa bearing particular traits, (ii) elevated net speciation of taxa bearing particular traits, and (iii) elevated evolvability expanding the range of anatomies available to some species. Trait-based diversification shifts predict elevated hierarchical stratigraphic compatibility (i.e., primitive→derived→highly derived sequences) among pairs of anatomical characters. The three specific models further predict (i) early loss of diversity for taxa retaining primitive conditions (elevated net extinction), (ii) increased diversification among later members of a clade (elevated net speciation), and (iii) increased disparity among later members in a clade (elevated evolvability). Analyses of 319 anatomical and stratigraphic datasets for fossil species and genera show that hierarchical stratigraphic compatibility exceeds the expectations of trait-independent diversification in the vast majority of cases, which was expected if trait-dependent diversification shifts are common. Excess hierarchical stratigraphic compatibility correlates with early loss of diversity for groups retaining primitive conditions rather than delayed bursts of diversity or disparity across entire clades. Cambrian clades (predominantly trilobites) alone fit null expectations well. However, it is not clear whether evolution was unusual among Cambrian taxa or only early trilobites. At least among post-Cambrian taxa, these results implicate models, such as competition and extinction selectivity/resistance, as major drivers of trait-based diversification shifts at the species and genus levels while contradicting the predictions of elevated net speciation and elevated evolvability models.

A prescription and fast code for the long-term evolution of star clusters

Science.gov (United States)

Alexander, Poul E. R.; Gieles, Mark

2012-06-01

We introduce the star cluster evolution code Evolve Me A Cluster of StarS (EMACSS), a simple yet physically motivated computational model that describes the evolution of some fundamental properties of star clusters in static tidal fields. We base our prescription upon the flow of energy within the cluster, which is a constant fraction of the total energy per half-mass relaxation time. According to Hénon's predictions, this flow is independent of the precise mechanisms for energy production within the core, and therefore does not require a complete description of the many-body interactions therein. For a cluster of equal-mass stars, we use dynamical theory and analytic descriptions of escape mechanisms to construct a series of coupled differential equations expressing the evolution of cluster mass and radius. These equations are numerically solved using a fourth-order Runge-Kutta integration kernel, and the results benchmarked against a data base of direct N-body simulations. We use simulations containing a modest initial number of stars (1024 ≤N≤ 65 536) and point-mass tidal fields of various strengths. Our prescription is publicly available and reproduces the N-body results to within ˜10 per cent accuracy for the entire post-collapse evolution of star clusters.

From stochastic processes to numerical methods: A new scheme for solving reaction subdiffusion fractional partial differential equations

Energy Technology Data Exchange (ETDEWEB)

Angstmann, C.N.; Donnelly, I.C. [School of Mathematics and Statistics, UNSW Australia, Sydney NSW 2052 (Australia); Henry, B.I., E-mail: B.Henry@unsw.edu.au [School of Mathematics and Statistics, UNSW Australia, Sydney NSW 2052 (Australia); Jacobs, B.A. [School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, Private Bag 3, Wits 2050 (South Africa); DST–NRF Centre of Excellence in Mathematical and Statistical Sciences (CoE-MaSS) (South Africa); Langlands, T.A.M. [Department of Mathematics and Computing, University of Southern Queensland, Toowoomba QLD 4350 (Australia); Nichols, J.A. [School of Mathematics and Statistics, UNSW Australia, Sydney NSW 2052 (Australia)

2016-02-15

We have introduced a new explicit numerical method, based on a discrete stochastic process, for solving a class of fractional partial differential equations that model reaction subdiffusion. The scheme is derived from the master equations for the evolution of the probability density of a sum of discrete time random walks. We show that the diffusion limit of the master equations recovers the fractional partial differential equation of interest. This limiting procedure guarantees the consistency of the numerical scheme. The positivity of the solution and stability results are simply obtained, provided that the underlying process is well posed. We also show that the method can be applied to standard reaction–diffusion equations. This work highlights the broader applicability of using discrete stochastic processes to provide numerical schemes for partial differential equations, including fractional partial differential equations.

Genome-wide analysis of the Solanum tuberosum (potato) trehalose-6-phosphate synthase (TPS) gene family: evolution and differential expression during development and stress.

Science.gov (United States)

Xu, Yingchun; Wang, Yanjie; Mattson, Neil; Yang, Liu; Jin, Qijiang

2017-12-01

Trehalose-6-phosphate synthase (TPS) serves important functions in plant desiccation tolerance and response to environmental stimuli. At present, a comprehensive analysis, i.e. functional classification, molecular evolution, and expression patterns of this gene family are still lacking in Solanum tuberosum (potato). In this study, a comprehensive analysis of the TPS gene family was conducted in potato. A total of eight putative potato TPS genes (StTPSs) were identified by searching the latest potato genome sequence. The amino acid identity among eight StTPSs varied from 59.91 to 89.54%. Analysis of d N /d S ratios suggested that regions in the TPP (trehalose-6-phosphate phosphatase) domains evolved faster than the TPS domains. Although the sequence of the eight StTPSs showed high similarity (2571-2796 bp), their gene length is highly differentiated (3189-8406 bp). Many of the regulatory elements possibly related to phytohormones, abiotic stress and development were identified in different TPS genes. Based on the phylogenetic tree constructed using TPS genes of potato, and four other Solanaceae plants, TPS genes could be categorized into 6 distinct groups. Analysis revealed that purifying selection most likely played a major role during the evolution of this family. Amino acid changes detected in specific branches of the phylogenetic tree suggests relaxed constraints might have contributed to functional divergence among groups. Moreover, StTPSs were found to exhibit tissue and treatment specific expression patterns upon analysis of transcriptome data, and performing qRT-PCR. This study provides a reference for genome-wide identification of the potato TPS gene family and sets a framework for further functional studies of this important gene family in development and stress response.

Fractal-Based Methods and Inverse Problems for Differential Equations: Current State of the Art

Directory of Open Access Journals (Sweden)

Herb E. Kunze

2014-01-01

Full Text Available We illustrate, in this short survey, the current state of the art of fractal-based techniques and their application to the solution of inverse problems for ordinary and partial differential equations. We review several methods based on the Collage Theorem and its extensions. We also discuss two innovative applications: the first one is related to a vibrating string model while the second one considers a collage-based approach for solving inverse problems for partial differential equations on a perforated domain.

HYPERDIRE HYPERgeometric functions DIfferential REduction. Mathematica-based packages for the differential reduction of generalized hypergeometric functions. Lauricella function FC of three variables

International Nuclear Information System (INIS)

Bytev, Vladimir V.; Kniehl, Bernd A.

2016-12-01

We present a further extension of the HYPERDIRE project, which is devoted to the creation of a set of Mathematica-based program packages for manipulations with Horn-type hypergeometric functions on the basis of differential equations. Specifically, we present the implementation of the differential reduction for the Lauricella function F C of three variables.

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.

Integration Processes of Delay Differential Equation Based on Modified Laguerre Functions

Directory of Open Access Journals (Sweden)

Yeguo Sun

2012-01-01

Full Text Available We propose long-time convergent numerical integration processes for delay differential equations. We first construct an integration process based on modified Laguerre functions. Then we establish its global convergence in certain weighted Sobolev space. The proposed numerical integration processes can also be used for systems of delay differential equations. We also developed a technique for refinement of modified Laguerre-Radau interpolations. Lastly, numerical results demonstrate the spectral accuracy of the proposed method and coincide well with analysis.

Power Transformer Differential Protection Based on Neural Network Principal Component Analysis, Harmonic Restraint and Park's Plots

OpenAIRE

Tripathy, Manoj

2012-01-01

This paper describes a new approach for power transformer differential protection which is based on the wave-shape recognition technique. An algorithm based on neural network principal component analysis (NNPCA) with back-propagation learning is proposed for digital differential protection of power transformer. The principal component analysis is used to preprocess the data from power system in order to eliminate redundant information and enhance hidden pattern of differential current to disc...

A Numerical Method for Partial Differential Algebraic Equations Based on Differential Transform Method

Directory of Open Access Journals (Sweden)

Murat Osmanoglu

2013-01-01

Full Text Available We have considered linear partial differential algebraic equations (LPDAEs of the form , which has at least one singular matrix of . We have first introduced a uniform differential time index and a differential space index. The initial conditions and boundary conditions of the given system cannot be prescribed for all components of the solution vector here. To overcome this, we introduced these indexes. Furthermore, differential transform method has been given to solve LPDAEs. We have applied this method to a test problem, and numerical solution of the problem has been compared with analytical solution.

Solution of partial differential equations by agent-based simulation

International Nuclear Information System (INIS)

Szilagyi, Miklos N

2014-01-01

The purpose of this short note is to demonstrate that partial differential equations can be quickly solved by agent-based simulation with high accuracy. There is no need for the solution of large systems of algebraic equations. This method is especially useful for quick determination of potential distributions and demonstration purposes in teaching electromagnetism. (letters and comments)

Differential Sarcomere and Electrophysiological Maturation of Human iPSC-Derived Cardiac Myocytes in Monolayer vs. Aggregation-Based Differentiation Protocols

Directory of Open Access Journals (Sweden)

Dorota Jeziorowska

2017-06-01

Full Text Available Human induced pluripotent stem cells (iPSCs represent a powerful human model to study cardiac disease in vitro, notably channelopathies and sarcomeric cardiomyopathies. Different protocols for cardiac differentiation of iPSCs have been proposed either based on embroid body formation (3D or, more recently, on monolayer culture (2D. We performed a direct comparison of the characteristics of the derived cardiomyocytes (iPSC-CMs on day 27 ± 2 of differentiation between 3D and 2D differentiation protocols with two different Wnt-inhibitors were compared: IWR1 (inhibitor of Wnt response or IWP2 (inhibitor of Wnt production. We firstly found that the level of Troponin T (TNNT2 expression measured by FACS was significantly higher for both 2D protocols as compared to the 3D protocol. In the three methods, iPSC-CM show sarcomeric structures. However, iPSC-CM generated in 2D protocols constantly displayed larger sarcomere lengths as compared to the 3D protocol. In addition, mRNA and protein analyses reveal higher cTNi to ssTNi ratios in the 2D protocol using IWP2 as compared to both other protocols, indicating a higher sarcomeric maturation. Differentiation of cardiac myocytes with 2D monolayer-based protocols and the use of IWP2 allows the production of higher yield of cardiac myocytes that have more suitable characteristics to study sarcomeric cardiomyopathies.

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

Adaptive differential correspondence imaging based on sorting technique

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Heng Wu

2017-04-01

Full Text Available We develop an adaptive differential correspondence imaging (CI method using a sorting technique. Different from the conventional CI schemes, the bucket detector signals (BDS are first processed by a differential technique, and then sorted in a descending (or ascending order. Subsequently, according to the front and last several frames of the sorted BDS, the positive and negative subsets (PNS are created by selecting the relative frames from the reference detector signals. Finally, the object image is recovered from the PNS. Besides, an adaptive method based on two-step iteration is designed to select the optimum number of frames. To verify the proposed method, a single-detector computational ghost imaging (GI setup is constructed. We experimentally and numerically compare the performance of the proposed method with different GI algorithms. The results show that our method can improve the reconstruction quality and reduce the computation cost by using fewer measurement data.

A hybrid approach to protein differential expression in mass spectrometry-based proteomics

KAUST Repository

Wang, X.

2012-04-19

MOTIVATION: Quantitative mass spectrometry-based proteomics involves statistical inference on protein abundance, based on the intensities of each protein\\'s associated spectral peaks. However, typical MS-based proteomics datasets have substantial proportions of missing observations, due at least in part to censoring of low intensities. This complicates intensity-based differential expression analysis. RESULTS: We outline a statistical method for protein differential expression, based on a simple Binomial likelihood. By modeling peak intensities as binary, in terms of \\'presence/absence,\\' we enable the selection of proteins not typically amenable to quantitative analysis; e.g. \\'one-state\\' proteins that are present in one condition but absent in another. In addition, we present an analysis protocol that combines quantitative and presence/absence analysis of a given dataset in a principled way, resulting in a single list of selected proteins with a single-associated false discovery rate. AVAILABILITY: All R code available here: http://www.stat.tamu.edu/~adabney/share/xuan_code.zip.

A random network based, node attraction facilitated network evolution method

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WenJun Zhang

2016-03-01

Full Text Available In present study, I present a method of network evolution that based on random network, and facilitated by node attraction. In this method, I assume that the initial network is a random network, or a given initial network. When a node is ready to connect, it tends to link to the node already owning the most connections, which coincides with the general rule (Barabasi and Albert, 1999 of node connecting. In addition, a node may randomly disconnect a connection i.e., the addition of connections in the network is accompanied by the pruning of some connections. The dynamics of network evolution is determined of the attraction factor Lamda of nodes, the probability of node connection, the probability of node disconnection, and the expected initial connectance. The attraction factor of nodes, the probability of node connection, and the probability of node disconnection are time and node varying. Various dynamics can be achieved by adjusting these parameters. Effects of simplified parameters on network evolution are analyzed. The changes of attraction factor Lamda can reflect various effects of the node degree on connection mechanism. Even the changes of Lamda only will generate various networks from the random to the complex. Therefore, the present algorithm can be treated as a general model for network evolution. Modeling results show that to generate a power-law type of network, the likelihood of a node attracting connections is dependent upon the power function of the node's degree with a higher-order power. Matlab codes for simplified version of the method are provided.

Trajectory data privacy protection based on differential privacy mechanism

Science.gov (United States)

Gu, Ke; Yang, Lihao; Liu, Yongzhi; Liao, Niandong

2018-05-01

In this paper, we propose a trajectory data privacy protection scheme based on differential privacy mechanism. In the proposed scheme, the algorithm first selects the protected points from the user’s trajectory data; secondly, the algorithm forms the polygon according to the protected points and the adjacent and high frequent accessed points that are selected from the accessing point database, then the algorithm calculates the polygon centroids; finally, the noises are added to the polygon centroids by the differential privacy method, and the polygon centroids replace the protected points, and then the algorithm constructs and issues the new trajectory data. The experiments show that the running time of the proposed algorithms is fast, the privacy protection of the scheme is effective and the data usability of the scheme is higher.

The evolution of the elements

International Nuclear Information System (INIS)

Williams, P.M.

1978-01-01

It is believed that only the lightest elements, hydrogen and helium, were created during the 'Big Bang' origin of the Universe and that all heavier elements were synthesized by nuclear reactions in stars, the interstellar medium and possibly in 'little bangs' in the nuclei of galaxies. The composition of the interstellar medium has evolved through enrichment by processed material shed by evolving stars and the composition of the Solar System reflects that of the interstellar medium at the time of its formation. Differentiation processes during the evolution of the Solar System and individual planets account for the different compositions of the Sun and the planets. The measurement of the abundance distribution of the elements has become a very powerful tool in the elucidation of the evolution of the Solar System, stars and the Galaxy. This review attempts to trace the formation of the elements in stars and their subsequent evolution. (author)

Universal pacemaker of genome evolution.

Science.gov (United States)

Snir, Sagi; Wolf, Yuri I; Koonin, Eugene V

2012-01-01

A fundamental observation of comparative genomics is that the distribution of evolution rates across the complete sets of orthologous genes in pairs of related genomes remains virtually unchanged throughout the evolution of life, from bacteria to mammals. The most straightforward explanation for the conservation of this distribution appears to be that the relative evolution rates of all genes remain nearly constant, or in other words, that evolutionary rates of different genes are strongly correlated within each evolving genome. This correlation could be explained by a model that we denoted Universal PaceMaker (UPM) of genome evolution. The UPM model posits that the rate of evolution changes synchronously across genome-wide sets of genes in all evolving lineages. Alternatively, however, the correlation between the evolutionary rates of genes could be a simple consequence of molecular clock (MC). We sought to differentiate between the MC and UPM models by fitting thousands of phylogenetic trees for bacterial and archaeal genes to supertrees that reflect the dominant trend of vertical descent in the evolution of archaea and bacteria and that were constrained according to the two models. The goodness of fit for the UPM model was better than the fit for the MC model, with overwhelming statistical significance, although similarly to the MC, the UPM is strongly overdispersed. Thus, the results of this analysis reveal a universal, genome-wide pacemaker of evolution that could have been in operation throughout the history of life.

Phase-field simulation of microstructure evolution in Ni-based superalloys

Energy Technology Data Exchange (ETDEWEB)

Tsukada, Yuhki; Murata, Yoshinori; Morinaga, Masahiko [Nagoya Univ. (Japan). Dept. of Materials, Physics and Energy Engineering; Koyama, Toshiyuki [National Institute for Materials Science, Tsukuba, Ibaraki (Japan)

2010-07-01

The morphological evolution of the ({gamma} + {gamma}') microstructure in Ni-based superalloys is investigated by a series of phase-field simulations. In the simulation for simple aging heat treatment, the effect of elastic constant inhomogeneity between the {gamma} and {gamma}' phases is investigated. The elastic anisotropy or the shear modulus is changed independently in the simulation. The variation of the anisotropy affects the morphology, particle size distribution and coarsening kinetics of the {gamma}' phase, whereas the variation of the shear modulus does not affect them. In the simulation for high temperature creep, formation and collapse of the rafted structure are reproduced under the assumption that the creep strain in the {gamma} matrix increases with creep time. This morphological evolution is related to the change in the energetically stable morphology of the {gamma}' phase with increasing the creep strain. (orig.)

Hyperbolicity and constrained evolution in linearized gravity

International Nuclear Information System (INIS)

Matzner, Richard A.

2005-01-01

Solving the 4-d Einstein equations as evolution in time requires solving equations of two types: the four elliptic initial data (constraint) equations, followed by the six second order evolution equations. Analytically the constraint equations remain solved under the action of the evolution, and one approach is to simply monitor them (unconstrained evolution). Since computational solution of differential equations introduces almost inevitable errors, it is clearly 'more correct' to introduce a scheme which actively maintains the constraints by solution (constrained evolution). This has shown promise in computational settings, but the analysis of the resulting mixed elliptic hyperbolic method has not been completely carried out. We present such an analysis for one method of constrained evolution, applied to a simple vacuum system, linearized gravitational waves. We begin with a study of the hyperbolicity of the unconstrained Einstein equations. (Because the study of hyperbolicity deals only with the highest derivative order in the equations, linearization loses no essential details.) We then give explicit analytical construction of the effect of initial data setting and constrained evolution for linearized gravitational waves. While this is clearly a toy model with regard to constrained evolution, certain interesting features are found which have relevance to the full nonlinear Einstein equations

Differential Search Coils Based Magnetometers: Conditioning, Magnetic Sensitivity, Spatial Resolution

Directory of Open Access Journals (Sweden)

Timofeeva Maria

2012-03-01

Full Text Available A theoretical and experimental comparison of optimized search coils based magnetometers, operating either in the Flux mode or in the classical Lenz-Faraday mode, is presented. The improvements provided by the Flux mode in terms of bandwidth and measuring range of the sensor are detailed. Theory, SPICE model and measurements are in good agreement. The spatial resolution of the sensor is studied which is an important parameter for applications in non destructive evaluation. A general expression of the magnetic sensitivity of search coils sensors is derived. Solutions are proposed to design magnetometers with reduced weight and volume without degrading the magnetic sensitivity. An original differential search coil based magnetometer, made of coupled coils, operating in flux mode and connected to a differential transimpedance amplifier is proposed. It is shown that this structure is better in terms of volume occupancy than magnetometers using two separated coils without any degradation in magnetic sensitivity. Experimental results are in good agreement with calculations.

Impulsive evolution inclusions with infinite delay and multivalued jumps

Directory of Open Access Journals (Sweden)

Mouffak Benchohra

2012-08-01

Full Text Available In this paper we prove the existence of a mild solution for a class of impulsive semilinear evolution differential inclusions with infinite delay and multivalued jumps in a Banach space.

MCPH1: a window into brain development and evolution

Directory of Open Access Journals (Sweden)

Jeannette eNardelli

2015-03-01

Full Text Available The development of the mammalian cerebral cortex involves a series of mechanisms: from patterning, progenitor cell proliferation and differentiation, to neuronal migration. Many factors influence the development of the cerebral cortex to its normal size and neuronal composition. Of these, the mechanisms that influence the proliferation and differentiation of neural progenitor cells are of particular interest, as they may have the greatest consequence on brain size, not only during development but also in evolution. In this context, causative genes of human autosomal recessive primary microcephaly, such as ASPM and MCPH1, are attractive candidates, as many of them show positive selection during primate evolution. MCPH1 causes microcephaly in mice and humans and is involved in a diverse array of molecular functions beyond brain development, including DNA repair and chromosome condensation. Positive selection of MCPH1 in the primate lineage has led to much insight and discussion of its role in brain size evolution. In this review, we will present an overview of MCPH1 from these multiple angles, and whilst its specific role in brain size regulation during development and evolution remain elusive, the pieces of the puzzle will be discussed with the aim of putting together the full picture of this fascinating gene.

Structure and evolution of the Y-chromosomal and mitochondrial DNA of cattle

NARCIS (Netherlands)

Verkaar, Edward Louis Christian

2003-01-01

The research described in this thesis is focused on the structure and evolution of the bovine Y-chromosome and the use of paternal markers in molecular diagnostics. The Y-chromosome has emerged together with the X-chromosome early during the evolution of the mammals by differentiation of a pair of

Evolution of Karyotypes in Chameleons

Directory of Open Access Journals (Sweden)

Michail Rovatsos

2017-12-01

Full Text Available The reconstruction of the evolutionary dynamics of karyotypes and sex determining systems in squamate reptiles is precluded by the lack of data in many groups including most chameleons (Squamata: Acrodonta: Chamaeleonidae. We performed cytogenetic analysis in 16 species of chameleons from 8 genera covering the phylogenetic diversity of the family and also phylogenetic reconstruction of karyotype evolution in this group. In comparison to other squamates, chameleons demonstrate rather variable karyotypes, differing in chromosome number, morphology and presence of interstitial telomeric signal (ITS. On the other hand, the location of rDNA is quite conserved among chameleon species. Phylogenetic analysis combining our new results and previously published data tentatively suggests that the ancestral chromosome number for chameleons is 2n = 36, which is the same as assumed for other lineages of the clade Iguania, i.e., agamids and iguanas. In general, we observed a tendency for the reduction of chromosome number during the evolution of chameleons, however, in Rieppeleon brevicaudatus, we uncovered a chromosome number of 2n = 62, very unusual among squamates, originating from a number of chromosome splits. Despite the presence of the highly differentiated ZZ/ZW sex chromosomes in the genus Furcifer, we did not detect any unequivocal sexual differences in the karyotypes of any other studied species of chameleons tested using differential staining and comparative genomic hybridization, suggesting that sex chromosomes in most chameleons are only poorly differentiated.

Differential geometry based solvation model II: Lagrangian formulation.

Science.gov (United States)

Chen, Zhan; Baker, Nathan A; Wei, G W

2011-12-01

Solvation is an elementary process in nature and is of paramount importance to more sophisticated chemical, biological and biomolecular processes. The understanding of solvation is an essential prerequisite for the quantitative description and analysis of biomolecular systems. This work presents a Lagrangian formulation of our differential geometry based solvation models. The Lagrangian representation of biomolecular surfaces has a few utilities/advantages. First, it provides an essential basis for biomolecular visualization, surface electrostatic potential map and visual perception of biomolecules. Additionally, it is consistent with the conventional setting of implicit solvent theories and thus, many existing theoretical algorithms and computational software packages can be directly employed. Finally, the Lagrangian representation does not need to resort to artificially enlarged van der Waals radii as often required by the Eulerian representation in solvation analysis. The main goal of the present work is to analyze the connection, similarity and difference between the Eulerian and Lagrangian formalisms of the solvation model. Such analysis is important to the understanding of the differential geometry based solvation model. The present model extends the scaled particle theory of nonpolar solvation model with a solvent-solute interaction potential. The nonpolar solvation model is completed with a Poisson-Boltzmann (PB) theory based polar solvation model. The differential geometry theory of surfaces is employed to provide a natural description of solvent-solute interfaces. The optimization of the total free energy functional, which encompasses the polar and nonpolar contributions, leads to coupled potential driven geometric flow and PB equations. Due to the development of singularities and nonsmooth manifolds in the Lagrangian representation, the resulting potential-driven geometric flow equation is embedded into the Eulerian representation for the purpose of

Differential alkylation-based redox proteomics – Lessons learnt

Science.gov (United States)

Wojdyla, Katarzyna; Rogowska-Wrzesinska, Adelina

2015-01-01

Cysteine is one of the most reactive amino acids. This is due to the electronegativity of sulphur atom in the side chain of thiolate group. It results in cysteine being present in several distinct redox forms inside the cell. Amongst these, reversible oxidations, S-nitrosylation and S-sulfenylation are crucial mediators of intracellular redox signalling, with known associations to health and disease. Study of their functionalities has intensified thanks to the development of various analytical strategies, with particular contribution from differential alkylation-based proteomics methods. Presented here is a critical evaluation of differential alkylation-based strategies for the analysis of S-nitrosylation and S-sulfenylation. The aim is to assess the current status and to provide insights for future directions in the dynamically evolving field of redox proteomics. To achieve that we collected 35 original research articles published since 2010 and analysed them considering the following parameters, (i) resolution of modification site, (ii) quantitative information, including correction of modification levels by protein abundance changes and determination of modification site occupancy, (iii) throughput, including the amount of starting material required for analysis. The results of this meta-analysis are the core of this review, complemented by issues related to biological models and sample preparation in redox proteomics, including conditions for free thiol blocking and labelling of target cysteine oxoforms. PMID:26282677

A paper-based scaffold for enhanced osteogenic differentiation of equine adipose-derived stem cells.

Science.gov (United States)

Petersen, Gayle F; Hilbert, Bryan J; Trope, Gareth D; Kalle, Wouter H J; Strappe, Padraig M

2015-11-01

We investigated the applicability of single layer paper-based scaffolds for the three-dimensional (3D) growth and osteogenic differentiation of equine adipose-derived stem cells (EADSC), with comparison against conventional two-dimensional (2D) culture on polystyrene tissue culture vessels. Viable culture of EADSC was achieved using paper-based scaffolds, with EADSC grown and differentiated in 3D culture retaining high cell viability (>94 %), similarly to EADSC in 2D culture. Osteogenic differentiation of EADSC was significantly enhanced in 3D culture, with Alizarin Red S staining and quantification demonstrating increased mineralisation (p < 0.0001), and an associated increase in expression of the osteogenic-specific markers alkaline phosphatase (p < 0.0001), osteopontin (p < 0.0001), and runx2 (p < 0.01). Furthermore, scanning electron microscopy revealed a spherical morphology of EADSC in 3D culture, compared to a flat morphology of EADSC in 2D culture. Single layer paper-based scaffolds provide an enhanced environment for the in vitro 3D growth and osteogenic differentiation of EADSC, with high cell viability, and a spherical morphology.

Web of Data Evolution by Exploiting Agent Based-Argumentation

OpenAIRE

Chamekh , Fatma; Boulanger , Danielle; Talens , Guilaine

2015-01-01

International audience; Sharing knowledge and data coming from different sources is one of the biggest advantage of linked data. Keeping this knowledge graph up to date may take in account both ontology vocabularies and data since they should be consistent. Our general problem is to deal with web of data evolution in particular: We aim at assisting user in a such complex process. In this research work, we propose an agent based-argumentation framework to help user linked data changes. We assi...

Physics, Formation and Evolution of Rotating Stars

CERN Document Server

Maeder, André

2009-01-01

Rotation is ubiquitous at each step of stellar evolution, from star formation to the final stages, and it affects the course of evolution, the timescales and nucleosynthesis. Stellar rotation is also an essential prerequisite for the occurrence of Gamma-Ray Bursts. In this book the author thoroughly examines the basic mechanical and thermal effects of rotation, their influence on mass loss by stellar winds, the effects of differential rotation and its associated instabilities, the relation with magnetic fields and the evolution of the internal and surface rotation. Further, he discusses the numerous observational signatures of rotational effects obtained from spectroscopy and interferometric observations, as well as from chemical abundance determinations, helioseismology and asteroseismology, etc. On an introductory level, this book presents in a didactical way the basic concepts of stellar structure and evolution in "track 1" chapters. The other more specialized chapters form an advanced course on the gradua...

Darwinian evolution

NARCIS (Netherlands)

Jagers op Akkerhuis, Gerard A.J.M.; Spijkerboer, Hendrik Pieter; Koelewijn, Hans Peter

2016-01-01

Darwinian evolution is a central tenet in biology. Conventionally, the defi nition of Darwinian evolution is linked to a population-based process that can be measured by focusing on changes in DNA/allele frequencies. However, in some publications it has been suggested that selection represents a

Origin and evolution of Petrocosmea (Gesneriaceae) inferred from both DNA sequence and novel findings in morphology with a test of morphology-based hypotheses.

Science.gov (United States)

Qiu, Zhi-Jing; Lu, Yuan-Xue; Li, Chao-Qun; Dong, Yang; Smith, James F; Wang, Yin-Zheng

2015-07-03

Petrocosmea Oliver (Gesneriaceae) currently comprises 38 species with four non-nominate varieties, nearly all of which have been described solely from herbarium specimens. However, the dried specimens have obscured the full range of extremely diverse morphological variation that exists in the genus and has resulted in a poor subgeneric classification system that does not reflect the evolutionary history of this group. It is important to develop innovative methods to find new morphological traits and reexamine and reevaluate the traditionally used morphological data based on new hypothesis. In addition, Petrocosmea is a mid-sized genus but exhibits extreme diverse floral variants. This makes the genus of particular interest in addressing the question whether there are any key factors that is specifically associated with their evolution and diversification. Here we present the first phylogenetic analyses of the genus based on dense taxonomic sampling and multiple genes combined with a comprehensive morphological investigation. Maximum-parsimony, maximum likelihood and Bayesian analyses of molecular data from two nuclear DNA and six cpDNA regions support the monophyly of Petrocosmea and recover five major clades within the genus, which is strongly corroborated by the reconstruction of ancestral states for twelve new morphological characters directly observed from living material. Ancestral area reconstruction shows that its most common ancestor was likely located east and southeast of the Himalaya-Tibetan plateau. The origin of Petrocosmea from a potentially Raphiocarpus-like ancestor might have involved a series of morphological modifications from caulescent to acaulescent habit as well as from a tetrandrous flower with a long corolla-tube to a diandrous flower with a short corolla-tube, also evident in the vestigial caulescent habit and transitional floral form in clade A that is sister to the remainder of the genus. Among the five clades in Petrocosmea, the

SGO: A fast engine for ab initio atomic structure global optimization by differential evolution

Science.gov (United States)

Chen, Zhanghui; Jia, Weile; Jiang, Xiangwei; Li, Shu-Shen; Wang, Lin-Wang

2017-10-01

As the high throughout calculations and material genome approaches become more and more popular in material science, the search for optimal ways to predict atomic global minimum structure is a high research priority. This paper presents a fast method for global search of atomic structures at ab initio level. The structures global optimization (SGO) engine consists of a high-efficiency differential evolution algorithm, accelerated local relaxation methods and a plane-wave density functional theory code running on GPU machines. The purpose is to show what can be achieved by combining the superior algorithms at the different levels of the searching scheme. SGO can search the global-minimum configurations of crystals, two-dimensional materials and quantum clusters without prior symmetry restriction in a relatively short time (half or several hours for systems with less than 25 atoms), thus making such a task a routine calculation. Comparisons with other existing methods such as minima hopping and genetic algorithm are provided. One motivation of our study is to investigate the properties of magnetic systems in different phases. The SGO engine is capable of surveying the local minima surrounding the global minimum, which provides the information for the overall energy landscape of a given system. Using this capability we have found several new configurations for testing systems, explored their energy landscape, and demonstrated that the magnetic moment of metal clusters fluctuates strongly in different local minima.

Graphene nanomesh-based devices exhibiting a strong negative differential conductance effect

International Nuclear Information System (INIS)

Hung Nguyen, V; Mazzamuto, F; Saint-Martin, J; Bournel, A; Dollfus, P

2012-01-01

Using atomistic quantum simulation based on a tight binding model, we have investigated the transport characteristics of graphene nanomesh-based devices and evaluated the possibilities of observing negative differential conductance. It is shown that by taking advantage of bandgap opening in the graphene nanomesh lattice, a strong negative differential conductance effect can be achieved at room temperature in pn junctions and n-doped structures. Remarkably, the effect is improved very significantly (with a peak-to-valley current ratio of a few hundred) and appears to be weakly sensitive to the transition length in graphene nanomesh pn hetero-junctions when inserting a pristine (gapless) graphene section in the transition region between n and p zones. The study therefore suggests new design strategies for graphene electronic devices which may offer strong advantages in terms of performance and processing over the devices studied previously. (paper)

Harnessing cellular differentiation to improve ALA-based photodynamic therapy in an artificial skin model

Science.gov (United States)

Maytin, Edward; Anand, Sanjay; Sato, Nobuyuki; Mack, Judith; Ortel, Bernhard

2005-04-01

During ALA-based photodynamic therapy (PDT), a pro-drug (aminolevulinic acid; ALA) is taken up by tumor cells and metabolically converted to a photosensitizing intermediate (protoporphyrin IX; PpIX). ALA-based PDT, while an emerging treatment modality, remains suboptimal for most cancers (e.g. squamous cell carcinoma of the skin). Many treatment failures may be largely due to insufficient conversion of ALA to PpIX within cells. We discovered a novel way to increase the conversion of ALA to PpIX, by administering agents that can drive terminal differentiation (i.e., accelerate cellular maturation). Terminally-differentiated epithelial cells show higher levels of intracellular PpIX, apparently via increased levels of a rate-limiting enzyme, coproporphyrinogen oxidase (CPO). To study these mechanisms in a three-dimensional tissue, we developed an organotypic model that mimics true epidermal physiology in a majority of respects. A line of rat epidermal keratinocytes (REKs), when grown in raft cultures, displays all the features of a fully-differentiated epidermis. Addition of ALA to the culture medium results in ALA uptake and PpIX synthesis, with subsequent death of keratinocytes upon exposure to blue light. Using this model, we can manipulate cellular differentiation via three different approaches. (1) Vitamin D, a hormone that enhances keratinocyte differentiation; (2) Hoxb13, a nuclear transcription factor that affects the genetically-controlled differentiation program of stratifying cells (3) Hyaluronan, an abundant extracellular matrix molecule that regulates epidermal differentiation. Because the raft cultures contain only a single cell type (no blood, fibroblasts, etc.) the effects of terminal differentiation upon CPO, PpIX, and keratinocyte cell death can be specifically defined.

Long Time Evolution of Populations under Selection and Vanishing Mutations

KAUST Repository

Raoul, Gaë l

2011-01-01

In this paper, we consider a long time and vanishing mutations limit of an integro-differential model describing the evolution of a population structured with respect to a continuous phenotypic trait. We show that the asymptotic population is a steady-state of the evolution equation without mutations, and satisfies an evolutionary stability condition. © 2011 Springer Science+Business Media B.V.

Long Time Evolution of Populations under Selection and Vanishing Mutations

KAUST Repository

Raoul, Gaël

2011-02-08

In this paper, we consider a long time and vanishing mutations limit of an integro-differential model describing the evolution of a population structured with respect to a continuous phenotypic trait. We show that the asymptotic population is a steady-state of the evolution equation without mutations, and satisfies an evolutionary stability condition. © 2011 Springer Science+Business Media B.V.

Differential BPFs with Multiple Transmission Zeros Based on Terminated Coupled Lines

Science.gov (United States)

Niu, Yiming; Yang, Guo; Wu, Wen

2018-04-01

Differential bandpass filters (BPFs) named Filter A and Filter B based on Terminated Coupled Lines (TCLs) are proposed in this letter. The TCLs contributes to not only three poles in differential-mode (DM) for wideband filtering response but also multiple zeros in both DM and common-mode (CM) offering wide DM out-of-band rejection and good CM suppression. Fabricated filters centred at 3.5 GHz with wide DM passband and wideband CM suppression have been designed and measured. The filters improved the noise suppression capability of the communication and radiometer systems. The simulated and measured results are in good agreement.

Gelatin-Based Hydrogels Promote Chondrogenic Differentiation of Human Adipose Tissue-Derived Mesenchymal Stem Cells In Vitro

Science.gov (United States)

Salamon, Achim; van Vlierberghe, Sandra; van Nieuwenhove, Ine; Baudisch, Frank; Graulus, Geert-Jan; Benecke, Verena; Alberti, Kristin; Neumann, Hans-Georg; Rychly, Joachim; Martins, José C.; Dubruel, Peter; Peters, Kirsten

2014-01-01

Due to the weak regeneration potential of cartilage, there is a high clinical incidence of articular joint disease, leading to a strong demand for cartilaginous tissue surrogates. The aim of this study was to evaluate a gelatin-based hydrogel for its suitability to support chondrogenic differentiation of human mesenchymal stem cells. Gelatin-based hydrogels are biodegradable, show high biocompatibility, and offer possibilities to introduce functional groups and/or ligands. In order to prove their chondrogenesis-supporting potential, a hydrogel film was developed and compared with standard cell culture polystyrene regarding the differentiation behavior of human mesenchymal stem cells. Cellular basis for this study were human adipose tissue-derived mesenchymal stem cells, which exhibit differentiation potential along the adipogenic, osteogenic and chondrogenic lineage. The results obtained show a promotive effect of gelatin-based hydrogels on chondrogenic differentiation of mesenchymal stem cells in vitro and therefore encourage subsequent in vivo studies. PMID:28788517

Symbolic Detection of Permutation and Parity Symmetries of Evolution Equations

KAUST Repository

Alghamdi, Moataz

2017-06-18

We introduce a symbolic computational approach to detecting all permutation and parity symmetries in any general evolution equation, and to generating associated invariant polynomials, from given monomials, under the action of these symmetries. Traditionally, discrete point symmetries of differential equations are systemically found by solving complicated nonlinear systems of partial differential equations; in the presence of Lie symmetries, the process can be simplified further. Here, we show how to find parity- and permutation-type discrete symmetries purely based on algebraic calculations. Furthermore, we show that such symmetries always form groups, thereby allowing for the generation of new group-invariant conserved quantities from known conserved quantities. This work also contains an implementation of the said results in Mathematica. In addition, it includes, as a motivation for this work, an investigation of the connection between variational symmetries, described by local Lie groups, and conserved quantities in Hamiltonian systems.

Phosphorene/rhenium disulfide heterojunction-based negative differential resistance device for multi-valued logic

Science.gov (United States)

Shim, Jaewoo; Oh, Seyong; Kang, Dong-Ho; Jo, Seo-Hyeon; Ali, Muhammad Hasnain; Choi, Woo-Young; Heo, Keun; Jeon, Jaeho; Lee, Sungjoo; Kim, Minwoo; Song, Young Jae; Park, Jin-Hong

2016-01-01

Recently, negative differential resistance devices have attracted considerable attention due to their folded current–voltage characteristic, which presents multiple threshold voltage values. Because of this remarkable property, studies associated with the negative differential resistance devices have been explored for realizing multi-valued logic applications. Here we demonstrate a negative differential resistance device based on a phosphorene/rhenium disulfide (BP/ReS2) heterojunction that is formed by type-III broken-gap band alignment, showing high peak-to-valley current ratio values of 4.2 and 6.9 at room temperature and 180 K, respectively. Also, the carrier transport mechanism of the BP/ReS2 negative differential resistance device is investigated in detail by analysing the tunnelling and diffusion currents at various temperatures with the proposed analytic negative differential resistance device model. Finally, we demonstrate a ternary inverter as a multi-valued logic application. This study of a two-dimensional material heterojunction is a step forward toward future multi-valued logic device research. PMID:27819264

Phosphorene/rhenium disulfide heterojunction-based negative differential resistance device for multi-valued logic

Science.gov (United States)

Shim, Jaewoo; Oh, Seyong; Kang, Dong-Ho; Jo, Seo-Hyeon; Ali, Muhammad Hasnain; Choi, Woo-Young; Heo, Keun; Jeon, Jaeho; Lee, Sungjoo; Kim, Minwoo; Song, Young Jae; Park, Jin-Hong

2016-11-01

Recently, negative differential resistance devices have attracted considerable attention due to their folded current-voltage characteristic, which presents multiple threshold voltage values. Because of this remarkable property, studies associated with the negative differential resistance devices have been explored for realizing multi-valued logic applications. Here we demonstrate a negative differential resistance device based on a phosphorene/rhenium disulfide (BP/ReS2) heterojunction that is formed by type-III broken-gap band alignment, showing high peak-to-valley current ratio values of 4.2 and 6.9 at room temperature and 180 K, respectively. Also, the carrier transport mechanism of the BP/ReS2 negative differential resistance device is investigated in detail by analysing the tunnelling and diffusion currents at various temperatures with the proposed analytic negative differential resistance device model. Finally, we demonstrate a ternary inverter as a multi-valued logic application. This study of a two-dimensional material heterojunction is a step forward toward future multi-valued logic device research.

Evolution families of conformal mappings with fixed points and the Löwner-Kufarev equation

International Nuclear Information System (INIS)

Goryainov, V V

2015-01-01

The paper is concerned with evolution families of conformal mappings of the unit disc to itself that fix an interior point and a boundary point. Conditions are obtained for the evolution families to be differentiable, and an existence and uniqueness theorem for an evolution equation is proved. A convergence theorem is established which describes the topology of locally uniform convergence of evolution families in terms of infinitesimal generating functions. The main result in this paper is the embedding theorem which shows that any conformal mapping of the unit disc to itself with two fixed points can be embedded into a differentiable evolution family of such mappings. This result extends the range of the parametric method in the theory of univalent functions. In this way the problem of the mutual change of the derivative at an interior point and the angular derivative at a fixed point on the boundary is solved for a class of mappings of the unit disc to itself. In particular, the rotation theorem is established for this class of mappings. Bibliography: 27 titles

MVMO-based approach for optimal placement and tuning of ...

African Journals Online (AJOL)

DR OKE

differential evolution DE algorithm with adaptive crossover operator, .... x are assigned by using a sequential scheme which accounts for mean and ... the representative scenarios from probabilistic model based Monte Carlo ... Comparison of average convergence of MVMO-S with other metaheuristic optimization methods.

Existence of solutions for second-order evolution inclusions

Directory of Open Access Journals (Sweden)

Nikolaos S. Papageorgiou

1994-01-01

Full Text Available In this paper we examine second-order nonlinear evolution inclusions and prove two existence theorems; one with a convex-valued orientor field and the other with a nonconvex-valued field. An example of a hyperbolic partial differential inclusion is also presented.

HYPERDIRE HYPERgeometric functions DIfferential REduction. Mathematica-based packages for the differential reduction of generalized hypergeometric functions. Lauricella function F{sub C} of three variables

Energy Technology Data Exchange (ETDEWEB)

Bytev, Vladimir V. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Joint Institute for Nuclear Research, Dubna (Russian Federation); Kniehl, Bernd A. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik

2016-12-15

We present a further extension of the HYPERDIRE project, which is devoted to the creation of a set of Mathematica-based program packages for manipulations with Horn-type hypergeometric functions on the basis of differential equations. Specifically, we present the implementation of the differential reduction for the Lauricella function F{sub C} of three variables.

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.

Constraints on the evolution of phenotypic plasticity

DEFF Research Database (Denmark)

Murren, Courtney J; Auld, Josh R.; Callahan, Hilary S

2015-01-01

Phenotypic plasticity is ubiquitous and generally regarded as a key mechanism for enabling organisms to survive in the face of environmental change. Because no organism is infinitely or ideally plastic, theory suggests that there must be limits (for example, the lack of ability to produce...... an optimal trait) to the evolution of phenotypic plasticity, or that plasticity may have inherent significant costs. Yet numerous experimental studies have not detected widespread costs. Explicitly differentiating plasticity costs from phenotype costs, we re-evaluate fundamental questions of the limits...... to the evolution of plasticity and of generalists vs specialists. We advocate for the view that relaxed selection and variable selection intensities are likely more important constraints to the evolution of plasticity than the costs of plasticity. Some forms of plasticity, such as learning, may be inherently...

MnFe(PGe) compounds: Preparation, structural evolution, and magnetocaloric effects

International Nuclear Information System (INIS)

Yue Ming; Zhang Hong-Guo; Zhang Jiu-Xing; Liu Dan-Min

2015-01-01

The interdependences of preparation conditions, magnetic and crystal structures, and magnetocaloric effects (MCE) of the MnFePGe-based compounds are reviewed. Based upon those findings, a new method for the evaluation of the MCE in these compounds, based on differential scanning calorimetry (DSC), is proposed. The MnFePGe-based compounds are a group of magnetic refrigerants with giant magnetocaloric effect (GMCE), and as such, have drawn tremendous attention, especially due to their many advantages for practical applications. Structural evolution and phase transformation in the compounds as functions of temperature, pressure, and magnetic field are reported. Influences of preparation conditions upon the homogeneity of the compounds’ chemical composition and microstructure, both of which play a key role in the MCE and thermal hysteresis of the compounds, are introduced. Lastly, the origin of the “virgin effect” in the MnFePGe-based compounds is discussed. (paper)

Gelatin-Based Hydrogels Promote Chondrogenic Differentiation of Human Adipose Tissue-Derived Mesenchymal Stem Cells In Vitro

Directory of Open Access Journals (Sweden)

Achim Salamon

2014-02-01

Full Text Available Due to the weak regeneration potential of cartilage, there is a high clinical incidence of articular joint disease, leading to a strong demand for cartilaginous tissue surrogates. The aim of this study was to evaluate a gelatin-based hydrogel for its suitability to support chondrogenic differentiation of human mesenchymal stem cells. Gelatin-based hydrogels are biodegradable, show high biocompatibility, and offer possibilities to introduce functional groups and/or ligands. In order to prove their chondrogenesis-supporting potential, a hydrogel film was developed and compared with standard cell culture polystyrene regarding the differentiation behavior of human mesenchymal stem cells. Cellular basis for this study were human adipose tissue-derived mesenchymal stem cells, which exhibit differentiation potential along the adipogenic, osteogenic and chondrogenic lineage. The results obtained show a promotive effect of gelatin-based hydrogels on chondrogenic differentiation of mesenchymal stem cells in vitro and therefore encourage subsequent in vivo studies.

Lack of Evolution Acceptance Inhibits Students' Negotiation of Biology-Based Socioscientific Issues

Science.gov (United States)

Fowler, S. R.; Zeidler, D. L.

2016-01-01

The purpose of this study was to explore science content used during college students' negotiation of biology-based socioscientific issues (SSI) and examine how it related to students' conceptual understanding and acceptance of biological evolution. The Socioscientific Issues Questionnaire (SSI-Q) was developed to measure depth of evolutionary…

Evolution of Project-Based Learning in Small Groups in Environmental Engineering Courses

Science.gov (United States)

Requies, Jesús M.; Agirre, Ion; Barrio, V. Laura; Graells, Moisès

2018-01-01

This work presents the assessment of the development and evolution of an active methodology (Project-Based Learning--PBL) implemented on the course "Unit Operations in Environmental Engineering", within the bachelor's degree in Environmental Engineering, with the purpose of decreasing the dropout rate in this course. After the initial…

Genetic diversity and molecular evolution of Ornithogalum mosaic virus based on the coat protein gene sequence

Directory of Open Access Journals (Sweden)

Fangluan Gao

2018-03-01

Full Text Available Ornithogalum mosaic virus (OrMV has a wide host range and affects the production of a variety of ornamentals. In this study, the coat protein (CP gene of OrMVwas used to investigate the molecular mechanisms underlying the evolution of this virus. The 36 OrMV isolates fell into two groups which have significant subpopulation differentiation with an FST value of 0.470. One isolate was identified as a recombinant and the other 35 recombination-free isolates could be divided into two major clades under different evolutionary constraints with dN/dS values of 0.055 and 0.028, respectively, indicating a role of purifying selection in the differentiation of OrMV. In addition, the results from analysis of molecular variance (AMOVA indicated that the effect of host species on the genetic divergence of OrMV is greater than that of geography. Furthermore, OrMV isolates from the genera Ornithogalum, Lachenalia and Diuri tended to group together, indicating that OrMV diversification was maintained, in part, by host-driven adaptation.

Multi-objective trajectory optimization of Space Manoeuvre Vehicle using adaptive differential evolution and modified game theory

Science.gov (United States)

Chai, Runqi; Savvaris, Al; Tsourdos, Antonios; Chai, Senchun

2017-07-01

Highly constrained trajectory optimization for Space Manoeuvre Vehicles (SMV) is a challenging problem. In practice, this problem becomes more difficult when multiple mission requirements are taken into account. Because of the nonlinearity in the dynamic model and even the objectives, it is usually hard for designers to generate a compromised trajectory without violating strict path and box constraints. In this paper, a new multi-objective SMV optimal control model is formulated and parameterized using combined shooting-collocation technique. A modified game theory approach, coupled with an adaptive differential evolution algorithm, is designed in order to generate the pareto front of the multi-objective trajectory optimization problem. In addition, to improve the quality of obtained solutions, a control logic is embedded in the framework of the proposed approach. Several existing multi-objective evolutionary algorithms are studied and compared with the proposed method. Simulation results indicate that without driving the solution out of the feasible region, the proposed method can perform better in terms of convergence ability and convergence speed than its counterparts. Moreover, the quality of the pareto set generated using the proposed method is higher than other multi-objective evolutionary algorithms, which means the newly proposed algorithm is more attractive for solving multi-criteria SMV trajectory planning problem.

Schramm–Loewner evolution

CERN Document Server

Kemppainen, Antti

2017-01-01

This book is a short, but complete, introduction to the Loewner equation and the SLEs, which are a family of random fractal curves, as well as the relevant background in probability and complex analysis. The connection to statistical physics is also developed in the text in an example case. The book is based on a course (with the same title) lectured by the author. First three chapters are devoted to the background material, but at the same time, give the reader a good understanding on the overview on the subject and on some aspects of conformal invariance. The chapter on the Loewner equation develops in detail the connection of growing hulls and the differential equation satisfied by families of conformal maps. The Schramm–Loewner evolutions are defined and their basic properties are studied in the following chapter, and the regularity properties of random curves as well as scaling limits of discrete random curves are investigated in the final chapter. The book is aimed at graduate students or researcher...

Geochronological synthesis of Bahia state and the crustal evolution, based in evolution diagram of Sr and initial rate of Sr87/Sr86

International Nuclear Information System (INIS)

Sato, K.

1986-01-01

The crustal evolution of the ancient terrains of the State of Bahia, Brazil, is attempted with the aid of Sr isotopic results as natural tracers. Some Nd and Pb isotopic data are also available, and support the main conclusions based on Sr evolution diagrams. The analysis of the Sr evolution diagrams shows that the Archean Terrains are mainly formed by accretion from mantle-derived material, but crustal reworking is indicated by the high initial 87 Sr/ 86 Sr value of the Jequie Complex. The Transamazonian mobile belt include both types of materials, but the 87 Sr/ 86 Sr value, generally lower than those of the Jequie Complex, markes improbable a direct derivation. During Middle and Late Proterozoic, the continental crust was already well consolidated, and reworking of crustal material predominated within the Espinhaco and Brasiliano folded systems [pt

Characteristics of the evolution of cooperation by the probabilistic peer-punishment based on the difference of payoff

International Nuclear Information System (INIS)

Ohdaira, Tetsushi

2017-01-01

Highlights: • The probabilistic peer-punishment based on the difference of payoff is introduced. • The characteristics of the evolution of cooperation are studied. • Those characteristics present the significant contribution to knowledge. - Abstract: Regarding costly punishment of two types, especially peer-punishment is considered to decrease the average payoff of all players as well as pool-punishment does, and to facilitate the antisocial punishment as a result of natural selection. To solve those problems, the author has proposed the probabilistic peer-punishment based on the difference of payoff. In the limited condition, the proposed peer-punishment has shown the positive effects on the evolution of cooperation, and increased the average payoff of all players. Based on those findings, this study exhibits the characteristics of the evolution of cooperation by the proposed peer-punishment. Those characteristics present the significant contribution to knowledge that for the evolution of cooperation, a limited number of players should cause severe damage to defectors at the large expense of their payoff when connections between them are sparse, whereas a greater number of players should share the responsibility to punish defectors at the relatively small expense of their payoff when connections between them are dense.

The fast debris evolution model

Science.gov (United States)

Lewis, H. G.; Swinerd, G. G.; Newland, R. J.; Saunders, A.

2009-09-01

The 'particles-in-a-box' (PIB) model introduced by Talent [Talent, D.L. Analytic model for orbital debris environmental management. J. Spacecraft Rocket, 29 (4), 508-513, 1992.] removed the need for computer-intensive Monte Carlo simulation to predict the gross characteristics of an evolving debris environment. The PIB model was described using a differential equation that allows the stability of the low Earth orbit (LEO) environment to be tested by a straightforward analysis of the equation's coefficients. As part of an ongoing research effort to investigate more efficient approaches to evolutionary modelling and to develop a suite of educational tools, a new PIB model has been developed. The model, entitled Fast Debris Evolution (FADE), employs a first-order differential equation to describe the rate at which new objects ⩾10 cm are added and removed from the environment. Whilst Talent [Talent, D.L. Analytic model for orbital debris environmental management. J. Spacecraft Rocket, 29 (4), 508-513, 1992.] based the collision theory for the PIB approach on collisions between gas particles and adopted specific values for the parameters of the model from a number of references, the form and coefficients of the FADE model equations can be inferred from the outputs of future projections produced by high-fidelity models, such as the DAMAGE model. The FADE model has been implemented as a client-side, web-based service using JavaScript embedded within a HTML document. Due to the simple nature of the algorithm, FADE can deliver the results of future projections immediately in a graphical format, with complete user-control over key simulation parameters. Historical and future projections for the ⩾10 cm LEO debris environment under a variety of different scenarios are possible, including business as usual, no future launches, post-mission disposal and remediation. A selection of results is presented with comparisons with predictions made using the DAMAGE environment model

Morphology-based prediction of osteogenic differentiation potential of human mesenchymal stem cells.

Directory of Open Access Journals (Sweden)

Fumiko Matsuoka

Full Text Available Human bone marrow mesenchymal stem cells (hBMSCs are widely used cell source for clinical bone regeneration. Achieving the greatest therapeutic effect is dependent on the osteogenic differentiation potential of the stem cells to be implanted. However, there are still no practical methods to characterize such potential non-invasively or previously. Monitoring cellular morphology is a practical and non-invasive approach for evaluating osteogenic potential. Unfortunately, such image-based approaches had been historically qualitative and requiring experienced interpretation. By combining the non-invasive attributes of microscopy with the latest technology allowing higher throughput and quantitative imaging metrics, we studied the applicability of morphometric features to quantitatively predict cellular osteogenic potential. We applied computational machine learning, combining cell morphology features with their corresponding biochemical osteogenic assay results, to develop prediction model of osteogenic differentiation. Using a dataset of 9,990 images automatically acquired by BioStation CT during osteogenic differentiation culture of hBMSCs, 666 morphometric features were extracted as parameters. Two commonly used osteogenic markers, alkaline phosphatase (ALP activity and calcium deposition were measured experimentally, and used as the true biological differentiation status to validate the prediction accuracy. Using time-course morphological features throughout differentiation culture, the prediction results highly correlated with the experimentally defined differentiation marker values (R>0.89 for both marker predictions. The clinical applicability of our morphology-based prediction was further examined with two scenarios: one using only historical cell images and the other using both historical images together with the patient's own cell images to predict a new patient's cellular potential. The prediction accuracy was found to be greatly enhanced

Material inhomogeneities and their evolution a geometric approach

CERN Document Server

Epstein, Marcelo

2007-01-01

Presents a unified treatment of the inhomogeneity theory using some of the tools of modern differential geometry. This book deals with the geometrical description of uniform bodies and their homogeneity conditions. It also develops a theory of material evolution and discusses its relevance in various applied contexts.

Transcriptomics-based identification of developmental toxicants through their interference with cardiomyocyte differentiation of embryonic stem cells

International Nuclear Information System (INIS)

Dartel, Dorien A.M. van; Pennings, Jeroen L.A.; Schooten, Frederik J. van; Piersma, Aldert H.

2010-01-01

The embryonic stem cell test (EST) predicts developmental toxicity based on the inhibition of cardiomyocyte differentiation of embryonic stem cells (ESC). The subjective endpoint, the long culture duration together with the undefined applicability domain and related predictivity need further improvement to facilitate implementation of the EST into regulatory strategies. These aspects may be improved by studying gene expression changes in the ESC differentiation cultures and their modulation by compound exposure using transcriptomics. Here, we tested the developmental toxicants monobutyl phthalate and 6-aminonicotinamide. ESC were allowed to differentiated, and cardiomyocyte differentiation was assessed after 10 days of culture. RNA of solvent controls was collected after 0, 24, 48, 72 and 96 h of exposure, and RNA of developmental-toxicant-exposed cultures was collected after 24 and 96 h. Samples were hybridized to DNA microarrays, and 1355 genes were found differentially expressed among the unexposed experimental groups. These regulated genes were involved in differentiation-related processes, and Principal Component Analysis (PCA) based on these genes showed that the unexposed experimental groups appeared in chronological order in the PCA, which can therefore be regarded as a continuous representation of the differentiation track. The developmental-toxicant-exposed cultures appeared to deviate significantly from this differentiation track, which confirms the compound-modulating effects on the differentiation process. The incorporation of transcriptomics in the EST is expected to provide a more informative and improved endpoint in the EST as compared with morphology, allowing early detection of differentiation modulation. Furthermore, this approach may improve the definition of the applicability domain and predictivity of the EST.

Molecular Phylogenetic: Organism Taxonomy Method Based on Evolution History

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N.L.P Indi Dharmayanti

2011-03-01

Full Text Available Phylogenetic is described as taxonomy classification of an organism based on its evolution history namely its phylogeny and as a part of systematic science that has objective to determine phylogeny of organism according to its characteristic. Phylogenetic analysis from amino acid and protein usually became important area in sequence analysis. Phylogenetic analysis can be used to follow the rapid change of a species such as virus. The phylogenetic evolution tree is a two dimensional of a species graphic that shows relationship among organisms or particularly among their gene sequences. The sequence separation are referred as taxa (singular taxon that is defined as phylogenetically distinct units on the tree. The tree consists of outer branches or leaves that represents taxa and nodes and branch represent correlation among taxa. When the nucleotide sequence from two different organism are similar, they were inferred to be descended from common ancestor. There were three methods which were used in phylogenetic, namely (1 Maximum parsimony, (2 Distance, and (3 Maximum likehoood. Those methods generally are applied to construct the evolutionary tree or the best tree for determine sequence variation in group. Every method is usually used for different analysis and data.

Comparative Genomics Identifies Epidermal Proteins Associated with the Evolution of the Turtle Shell.

Science.gov (United States)

Holthaus, Karin Brigit; Strasser, Bettina; Sipos, Wolfgang; Schmidt, Heiko A; Mlitz, Veronika; Sukseree, Supawadee; Weissenbacher, Anton; Tschachler, Erwin; Alibardi, Lorenzo; Eckhart, Leopold

2016-03-01

The evolution of reptiles, birds, and mammals was associated with the origin of unique integumentary structures. Studies on lizards, chicken, and humans have suggested that the evolution of major structural proteins of the outermost, cornified layers of the epidermis was driven by the diversification of a gene cluster called Epidermal Differentiation Complex (EDC). Turtles have evolved unique defense mechanisms that depend on mechanically resilient modifications of the epidermis. To investigate whether the evolution of the integument in these reptiles was associated with specific adaptations of the sequences and expression patterns of EDC-related genes, we utilized newly available genome sequences to determine the epidermal differentiation gene complement of turtles. The EDC of the western painted turtle (Chrysemys picta bellii) comprises more than 100 genes, including at least 48 genes that encode proteins referred to as beta-keratins or corneous beta-proteins. Several EDC proteins have evolved cysteine/proline contents beyond 50% of total amino acid residues. Comparative genomics suggests that distinct subfamilies of EDC genes have been expanded and partly translocated to loci outside of the EDC in turtles. Gene expression analysis in the European pond turtle (Emys orbicularis) showed that EDC genes are differentially expressed in the skin of the various body sites and that a subset of beta-keratin genes within the EDC as well as those located outside of the EDC are expressed predominantly in the shell. Our findings give strong support to the hypothesis that the evolutionary innovation of the turtle shell involved specific molecular adaptations of epidermal differentiation. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Evolution-based Virtual Content Insertion with Visually Virtual Interactions in Videos

Science.gov (United States)

Chang, Chia-Hu; Wu, Ja-Ling

With the development of content-based multimedia analysis, virtual content insertion has been widely used and studied for video enrichment and multimedia advertising. However, how to automatically insert a user-selected virtual content into personal videos in a less-intrusive manner, with an attractive representation, is a challenging problem. In this chapter, we present an evolution-based virtual content insertion system which can insert virtual contents into videos with evolved animations according to predefined behaviors emulating the characteristics of evolutionary biology. The videos are considered not only as carriers of message conveyed by the virtual content but also as the environment in which the lifelike virtual contents live. Thus, the inserted virtual content will be affected by the videos to trigger a series of artificial evolutions and evolve its appearances and behaviors while interacting with video contents. By inserting virtual contents into videos through the system, users can easily create entertaining storylines and turn their personal videos into visually appealing ones. In addition, it would bring a new opportunity to increase the advertising revenue for video assets of the media industry and online video-sharing websites.

Design of Novel FBG-Based Sensor of Differential Pressure with Magnetic Transfer

Directory of Open Access Journals (Sweden)

Guohui Lyu

2017-02-01

Full Text Available In this paper, a differential pressure sensor with magnetic transfer is proposed, in which the non-electric measurement based on the fiber Bragg grating (FBG with the position limiting mechanism is implemented without the direct contact of the sensing unit with the measuring fluid. The test shows that the designed sensor is effective for measuring differential pressure in the range of 0~10 kPa with a sensitivity of 0.0112 nm/kPa, which can be used in environments with high temperature, strong corrosion and high overload measurements.

Design of Novel FBG-Based Sensor of Differential Pressure with Magnetic Transfer.

Science.gov (United States)

Lyu, Guohui; Che, Guohang; Li, Junqing; Jiang, Xu; Wang, Keda; Han, Yueqiang; Gao, Laixu

2017-02-15

In this paper, a differential pressure sensor with magnetic transfer is proposed, in which the non-electric measurement based on the fiber Bragg grating (FBG) with the position limiting mechanism is implemented without the direct contact of the sensing unit with the measuring fluid. The test shows that the designed sensor is effective for measuring differential pressure in the range of 0~10 kPa with a sensitivity of 0.0112 nm/kPa, which can be used in environments with high temperature, strong corrosion and high overload measurements.

High degree of sex chromosome differentiation in stickleback fishes

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Shimada Yukinori

2011-09-01

Full Text Available Abstract Background Studies of closely related species with different sex chromosome systems can provide insights into the processes of sex chromosome differentiation and evolution. To investigate the potential utility of molecular markers in studying sex chromosome differentiation at early stages of their divergence, we examined the levels and patterns of genetic differentiation between sex chromosomes in nine-spined (Pungitius pungitius and three-spined sticklebacks (Gasterosteus aculeatus using microsatellite markers. Results A set of novel microsatellite markers spanning the entire length of the sex chromosomes were developed for nine-spined sticklebacks using the sequenced genomes of other fish species. Sex-specific patterns of genetic variability and male-specific alleles were identified at most of these loci, indicating a high degree of differentiation between the X and Y chromosomes in nine-spined sticklebacks. In three-spined sticklebacks, male-specific alleles were detected at some loci confined to two chromosomal regions. In addition, male-specific null alleles were identified at several other loci, implying the absence of Y chromosomal alleles at these loci. Overall, male-specific alleles and null alleles were found over a region spanning 81% of the sex chromosomes in three-spined sticklebacks. Conclusions High levels but distinct patterns of sex chromosome differentiation were uncovered in the stickleback species that diverged 13 million years ago. Our results suggest that the Y chromosome is highly degenerate in three-spined sticklebacks, but not in nine-spined sticklebacks. In general, the results demonstrate that microsatellites can be useful in identifying the degree and patterns of sex chromosome differentiation in species at initial stages of sex chromosome evolution.

The geotectonic evolution of southern part of Sao Francisco Craton, based in geochronologic interpretation

International Nuclear Information System (INIS)

Teixeira, W.

1985-01-01

Interpretation of available radiometric data from poly metamorphic terranes of southern part of the Sao Francisco Craton demonstrates the importance of geochronology as a tool in the study of ancient crustal evolution. In addition, radiometric study of basic intrusive magmatism helps define the most important epochs of crustal rifting during the Proterozoic. The definition of the southern border of the cratonic area based on distinctive age patterns of the geochronological provinces is also discussed. Finally, the geochronologic evolution of the Bambui platform cover is presented. Approximately 250 radiometric age determinations (Rb-Sr, K-Ar and Pb-Pb methods) were interpreted principally through the use of iso chronic diagrams. The geologic history tectonomagnetic events identified in this study is compared to the crustal evolution of similar segments of the Sao Francisco Craton and elsewhere. (author)

Evolution based on domain combinations: the case of glutaredoxins

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Herrero Enrique

2009-03-01

Full Text Available Abstract Background Protein domains represent the basic units in the evolution of proteins. Domain duplication and shuffling by recombination and fusion, followed by divergence are the most common mechanisms in this process. Such domain fusion and recombination events are predicted to occur only once for a given multidomain architecture. However, other scenarios may be relevant in the evolution of specific proteins, such as convergent evolution of multidomain architectures. With this in mind, we study glutaredoxin (GRX domains, because these domains of approximately one hundred amino acids are widespread in archaea, bacteria and eukaryotes and participate in fusion proteins. GRXs are responsible for the reduction of protein disulfides or glutathione-protein mixed disulfides and are involved in cellular redox regulation, although their specific roles and targets are often unclear. Results In this work we analyze the distribution and evolution of GRX proteins in archaea, bacteria and eukaryotes. We study over one thousand GRX proteins, each containing at least one GRX domain, from hundreds of different organisms and trace the origin and evolution of the GRX domain within the tree of life. Conclusion Our results suggest that single domain GRX proteins of the CGFS and CPYC classes have, each, evolved through duplication and divergence from one initial gene that was present in the last common ancestor of all organisms. Remarkably, we identify a case of convergent evolution in domain architecture that involves the GRX domain. Two independent recombination events of a TRX domain to a GRX domain are likely to have occurred, which is an exception to the dominant mechanism of domain architecture evolution.

Gradient Evolution-based Support Vector Machine Algorithm for Classification

Science.gov (United States)

Zulvia, Ferani E.; Kuo, R. J.

2018-03-01

This paper proposes a classification algorithm based on a support vector machine (SVM) and gradient evolution (GE) algorithms. SVM algorithm has been widely used in classification. However, its result is significantly influenced by the parameters. Therefore, this paper aims to propose an improvement of SVM algorithm which can find the best SVMs’ parameters automatically. The proposed algorithm employs a GE algorithm to automatically determine the SVMs’ parameters. The GE algorithm takes a role as a global optimizer in finding the best parameter which will be used by SVM algorithm. The proposed GE-SVM algorithm is verified using some benchmark datasets and compared with other metaheuristic-based SVM algorithms. The experimental results show that the proposed GE-SVM algorithm obtains better results than other algorithms tested in this paper.

Disorders of sexual differentiation as seen at Kenyatta National ...

African Journals Online (AJOL)

Background: Disorders of sexual differentiation (DSD) are a group of congenital anomalies characterised by discordance between genetic, gonadal and phenotypic sex. There has been remarkable evolution in management over the last decade, including nomenclature, diagnosis and management. There has also been ...

How to discretize differential systems in a systematic way

International Nuclear Information System (INIS)

Murata, M; Satsuma, J; Ramani, A; Grammaticos, B

2010-01-01

We present a systematic approach to the construction of discrete analogues for differential systems. Our method is tailored to first-order differential equations and relies on a formal linearization, followed by a Pade-like rational approximation of an exponential evolution operator. We apply our method to a host of systems for which there exist discretization results obtained by what we call the 'intuitive' method and compare the discretizations obtained. A discussion of our method as compared to one of the Mickens is also presented. Finally we apply our method to a system of coupled Riccati equations with emphasis on the preservation of the integrable character of the differential system.

Transcriptome-based differentiation of closely-related Miscanthus lines.

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Philippe Chouvarine

Full Text Available BACKGROUND: Distinguishing between individuals is critical to those conducting animal/plant breeding, food safety/quality research, diagnostic and clinical testing, and evolutionary biology studies. Classical genetic identification studies are based on marker polymorphisms, but polymorphism-based techniques are time and labor intensive and often cannot distinguish between closely related individuals. Illumina sequencing technologies provide the detailed sequence data required for rapid and efficient differentiation of related species, lines/cultivars, and individuals in a cost-effective manner. Here we describe the use of Illumina high-throughput exome sequencing, coupled with SNP mapping, as a rapid means of distinguishing between related cultivars of the lignocellulosic bioenergy crop giant miscanthus (Miscanthus × giganteus. We provide the first exome sequence database for Miscanthus species complete with Gene Ontology (GO functional annotations. RESULTS: A SNP comparative analysis of rhizome-derived cDNA sequences was successfully utilized to distinguish three Miscanthus × giganteus cultivars from each other and from other Miscanthus species. Moreover, the resulting phylogenetic tree generated from SNP frequency data parallels the known breeding history of the plants examined. Some of the giant miscanthus plants exhibit considerable sequence divergence. CONCLUSIONS: Here we describe an analysis of Miscanthus in which high-throughput exome sequencing was utilized to differentiate between closely related genotypes despite the current lack of a reference genome sequence. We functionally annotated the exome sequences and provide resources to support Miscanthus systems biology. In addition, we demonstrate the use of the commercial high-performance cloud computing to do computational GO annotation.

The spectral transform as a tool for solving nonlinear discrete evolution equations

International Nuclear Information System (INIS)

Levi, D.

1979-01-01

In this contribution we study nonlinear differential difference equations which became important to the description of an increasing number of problems in natural science. Difference equations arise for instance in the study of electrical networks, in statistical problems, in queueing problems, in ecological problems, as computer models for differential equations and as models for wave excitation in plasma or vibrations of particles in an anharmonic lattice. We shall first review the passages necessary to solve linear discrete evolution equations by the discrete Fourier transfrom, then, starting from the Zakharov-Shabat discretized eigenvalue, problem, we shall introduce the spectral transform. In the following part we obtain the correlation between the evolution of the potentials and scattering data through the Wronskian technique, giving at the same time many other properties as, for example, the Baecklund transformations. Finally we recover some of the important equations belonging to this class of nonlinear discrete evolution equations and extend the method to equations with n-dependent coefficients. (HJ)

Constraint Differentiation

DEFF Research Database (Denmark)

Mödersheim, Sebastian Alexander; Basin, David; Viganò, Luca

2010-01-01

We introduce constraint differentiation, a powerful technique for reducing search when model-checking security protocols using constraint-based methods. Constraint differentiation works by eliminating certain kinds of redundancies that arise in the search space when using constraints to represent...... results show that constraint differentiation substantially reduces search and considerably improves the performance of OFMC, enabling its application to a wider class of problems....

Random number generation based on digital differential chaos

KAUST Repository

Zidan, Mohammed A.

2012-07-29

In this paper, we present a fully digital differential chaos based random number generator. The output of the digital circuit is proved to be chaotic by calculating the output time series maximum Lyapunov exponent. We introduce a new post processing technique to improve the distribution and statistical properties of the generated data. The post-processed output passes the NIST Sp. 800-22 statistical tests. The system is written in Verilog VHDL and realized on Xilinx Virtex® FPGA. The generator can fit into a very small area and have a maximum throughput of 2.1 Gb/s.

Curve Evolution in Subspaces and Exploring the Metameric Class of Histogram of Gradient Orientation based Features using Nonlinear Projection Methods

DEFF Research Database (Denmark)

Tatu, Aditya Jayant

This thesis deals with two unrelated issues, restricting curve evolution to subspaces and computing image patches in the equivalence class of Histogram of Gradient orientation based features using nonlinear projection methods. Curve evolution is a well known method used in various applications like...... tracking interfaces, active contour based segmentation methods and others. It can also be used to study shape spaces, as deforming a shape can be thought of as evolving its boundary curve. During curve evolution a curve traces out a path in the infinite dimensional space of curves. Due to application...... specific requirements like shape priors or a given data model, and due to limitations of the computer, the computed curve evolution forms a path in some finite dimensional subspace of the space of curves. We give methods to restrict the curve evolution to a finite dimensional linear or implicitly defined...

Decoupling of the Leading Order DGLAP Evolution Equation with Spin Dependent Structure Functions

Science.gov (United States)

Azadbakht, F. Teimoury; Boroun, G. R.

2018-02-01

We propose an analytical solution for DGLAP evolution equations with polarized splitting functions at the Leading Order (LO) approximation based on the Laplace transform method. It is shown that the DGLAP evolution equations can be decoupled completely into two second order differential equations which then are solved analytically by using the initial conditions δ FS(x,Q2)=F[partial δ FS0(x), δ FS0(x)] and {δ G}(x,Q2)=G[partial δ G0(x), δ G0(x)]. We used this method to obtain the polarized structure function of the proton as well as the polarized gluon distribution function inside the proton and compared the numerical results with experimental data of COMPASS, HERMES, and AAC'08 Collaborations. It was found that there is a good agreement between our predictions and the experiments.

Are there laws of genome evolution?

Directory of Open Access Journals (Sweden)

Eugene V Koonin

2011-08-01

Full Text Available Research in quantitative evolutionary genomics and systems biology led to the discovery of several universal regularities connecting genomic and molecular phenomic variables. These universals include the log-normal distribution of the evolutionary rates of orthologous genes; the power law-like distributions of paralogous family size and node degree in various biological networks; the negative correlation between a gene's sequence evolution rate and expression level; and differential scaling of functional classes of genes with genome size. The universals of genome evolution can be accounted for by simple mathematical models similar to those used in statistical physics, such as the birth-death-innovation model. These models do not explicitly incorporate selection; therefore, the observed universal regularities do not appear to be shaped by selection but rather are emergent properties of gene ensembles. Although a complete physical theory of evolutionary biology is inconceivable, the universals of genome evolution might qualify as "laws of evolutionary genomics" in the same sense "law" is understood in modern physics.

SOME IMPORTANT FACTORS AFFECTING EVOLUTION OF ACTIVITY BASED COSTING (ABC) SYSTEM IN EGYPTIAN MANUFACTURING FIRMS

OpenAIRE

Karim MAMDOUH ABBAS

2014-01-01

The present investigation aims to determine the factors affecting evolution of Activity Based Costing (ABC) system in Egyptian case. The study used the survey method to describe and analyze these factors in some Egyptian firms. The population of the study is Egyptian manufacturing firms. Accordingly, the number of received questionnaires was 392 (23 Egyptian manufacturing firms) in the first half of 2013. Finally, the study stated some influencing factors for evolution this system (ABC) in Eg...

Evolution in fluctuating environments: decomposing selection into additive components of the Robertson-Price equation.

Science.gov (United States)

Engen, Steinar; Saether, Bernt-Erik

2014-03-01

We analyze the stochastic components of the Robertson-Price equation for the evolution of quantitative characters that enables decomposition of the selection differential into components due to demographic and environmental stochasticity. We show how these two types of stochasticity affect the evolution of multivariate quantitative characters by defining demographic and environmental variances as components of individual fitness. The exact covariance formula for selection is decomposed into three components, the deterministic mean value, as well as stochastic demographic and environmental components. We show that demographic and environmental stochasticity generate random genetic drift and fluctuating selection, respectively. This provides a common theoretical framework for linking ecological and evolutionary processes. Demographic stochasticity can cause random variation in selection differentials independent of fluctuating selection caused by environmental variation. We use this model of selection to illustrate that the effect on the expected selection differential of random variation in individual fitness is dependent on population size, and that the strength of fluctuating selection is affected by how environmental variation affects the covariance in Malthusian fitness between individuals with different phenotypes. Thus, our approach enables us to partition out the effects of fluctuating selection from the effects of selection due to random variation in individual fitness caused by demographic stochasticity. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Unusual metastatic localizations of differentiated thyroid carcinoma

International Nuclear Information System (INIS)

Ben Rais, N.; Ghfir, I.

2007-01-01

Full text: Introduction: The majority of thyroid cancers have a slow evolution, a more often loco-regional extension, and a good forecast. Remote metastases, when they exist, generally touch the osseous skeleton and/or pulmonary tissue. However, unusual metastatic localizations much more exceptional are possible. The authors report through these work five cases of atypical metastasis of differentiated thyroid carcinoma followed in Nuclear Medicine department of Ibn Sina hospital in Rabat under the directives of Professor N Ben Rais. Materials and methods: Our five patients had initially undergone a total thyroidectomy for differentiated thyroid carcinoma histologically confirmed. They had profited 4 weeks after the surgical gesture from a reference isotopic exploration (131 Iodine whole body scan and thyroglobulin dosage). The paraclinic assessment was supplemented by a computed tomography (CT). Results: Revealing symptomatology in the first 69 year old patient was dominated by blindness associated with an elective up-take of radioactive 131-Iodine on the level of hypophyseal gland extending to the sphenoid bone. The second 55 year old patient reported right basithoracic pains resisting to the usual antalgic treatment with a bulky mass driving back the kidney right to the bottom at CT with and important up-take 131-Iodine at whole body scan; a surrenalectomy was thus carried out with conservation of the kidney. The three other patients presented at the clinical examination dermohypodermic nodular lesions of various localizations whose anatomopathologic study had confirmed their thyroid metastatic origin. In the 5 patients the rate of thyroglobulin was considerably high. An activity of 3,7 GBq 131-Iodine was managed with the 5 patients. The evolution was marked, in the short run, at the first patient by a recovery partial of the sight, the disappearance of pain in the second patient and a remarkable reduction of thyroglobulin level for all our patients. Conclusion

Investigating Island Evolution: A Galapagos-Based Lesson Using the 5E Instructional Model.

Science.gov (United States)

DeFina, Anthony V.

2002-01-01

Introduces an inquiry-based lesson plan on evolution and the Galapagos Islands. Uses the 5E instructional model which includes phases of engagement, exploration, explanation, elaboration, and evaluation. Includes information on species for exploration and elaboration purposes, and a general rubric for student evaluation. (YDS)

Introduction of the Notion of Differential Equations by Modelling Based Teaching

Science.gov (United States)

Budinski, Natalija; Takaci, Djurdjica

2011-01-01

This paper proposes modelling based learning as a tool for learning and teaching mathematics. The example of modelling real world problems leading to the exponential function as the solution of differential equations is described, as well as the observations about students' activities during the process. The students were acquainted with the…

The problem of evolution of toroidal plasma equilibrium

International Nuclear Information System (INIS)

Kostomarov, D.; Zaitsev, F.; Shishkin, A.

1999-03-01

This paper is devoted to an advanced mathematical model for a self-consistent description of the evolution of free boundary toroidal plasmas, with a description of numerical algorithms for the solution of the appropriate non-linear system of integro-differential equations, and discussion of some results from the model. (author)

Symmetry Reduction and Cauchy Problems for a Class of Fourth-Order Evolution Equations

International Nuclear Information System (INIS)

Li Jina; Zhang Shunli

2008-01-01

We exploit higher-order conditional symmetry to reduce initial-value problems for evolution equations to Cauchy problems for systems of ordinary differential equations (ODEs). We classify a class of fourth-order evolution equations which admit certain higher-order generalized conditional symmetries (GCSs) and give some examples to show the main reduction procedure. These reductions cannot be derived within the framework of the standard Lie approach, which hints that the technique presented here is something essential for the dimensional reduction of evolution equations

Heavy Quark Production at HERA in KT Factorization Supplemented With CCFM Evolution

International Nuclear Information System (INIS)

Jung, H.

2001-01-01

The application of k t - factorization, supplemented with the CCFM small-x evolution equation, to heavy quark production is discussed. Differential cross sections of bb production and also inelastic J/ψ production as measured at HERA are compared to the hadron level CCFM Monte Carlo generator Cascade, using the unintegrated gluon density obtained within the CCFM evolution approach from a fit to HERA F 2 data. (author)

Incorporating information on predicted solvent accessibility to the co-evolution-based study of protein interactions.

Science.gov (United States)

Ochoa, David; García-Gutiérrez, Ponciano; Juan, David; Valencia, Alfonso; Pazos, Florencio

2013-01-27

A widespread family of methods for studying and predicting protein interactions using sequence information is based on co-evolution, quantified as similarity of phylogenetic trees. Part of the co-evolution observed between interacting proteins could be due to co-adaptation caused by inter-protein contacts. In this case, the co-evolution is expected to be more evident when evaluated on the surface of the proteins or the internal layers close to it. In this work we study the effect of incorporating information on predicted solvent accessibility to three methods for predicting protein interactions based on similarity of phylogenetic trees. We evaluate the performance of these methods in predicting different types of protein associations when trees based on positions with different characteristics of predicted accessibility are used as input. We found that predicted accessibility improves the results of two recent versions of the mirrortree methodology in predicting direct binary physical interactions, while it neither improves these methods, nor the original mirrortree method, in predicting other types of interactions. That improvement comes at no cost in terms of applicability since accessibility can be predicted for any sequence. We also found that predictions of protein-protein interactions are improved when multiple sequence alignments with a richer representation of sequences (including paralogs) are incorporated in the accessibility prediction.

MEVTV Workshop on Early Tectonic and Volcanic Evolution of Mars

International Nuclear Information System (INIS)

Frey, H.

1988-01-01

Although not ignored, the problems of the early tectonic and volcanic evolution of Mars have generally received less attention than those later in the evolution of the planet. Specifically, much attention was devoted to the evolution of the Tharsis region of Mars and to the planet itself at the time following the establishment of this major tectonic and volcanic province. By contrast, little attention was directed at fundamental questions, such as the conditions that led to the development of Tharsis and the cause of the basic fundamental dichotomy of the Martian crust. It was to address these and related questions of the earliest evolution of Mars that a workshop was organized under the auspices of the Mars: Evolution of Volcanism, Tectonism, and Volatiles (MEVTV) Program. Four sessions were held: crustal dichotomy; crustal differentiation/volcanism; Tharsis, Elysium, and Valles Marineris; and ridges and fault tectonics

Repetitive sequences and epigenetic modification: inseparable partners play important roles in the evolution of plant sex chromosomes.

Science.gov (United States)

Li, Shu-Fen; Zhang, Guo-Jun; Yuan, Jin-Hong; Deng, Chuan-Liang; Gao, Wu-Jun

2016-05-01

The present review discusses the roles of repetitive sequences played in plant sex chromosome evolution, and highlights epigenetic modification as potential mechanism of repetitive sequences involved in sex chromosome evolution. Sex determination in plants is mostly based on sex chromosomes. Classic theory proposes that sex chromosomes evolve from a specific pair of autosomes with emergence of a sex-determining gene(s). Subsequently, the newly formed sex chromosomes stop recombination in a small region around the sex-determining locus, and over time, the non-recombining region expands to almost all parts of the sex chromosomes. Accumulation of repetitive sequences, mostly transposable elements and tandem repeats, is a conspicuous feature of the non-recombining region of the Y chromosome, even in primitive one. Repetitive sequences may play multiple roles in sex chromosome evolution, such as triggering heterochromatization and causing recombination suppression, leading to structural and morphological differentiation of sex chromosomes, and promoting Y chromosome degeneration and X chromosome dosage compensation. In this article, we review the current status of this field, and based on preliminary evidence, we posit that repetitive sequences are involved in sex chromosome evolution probably via epigenetic modification, such as DNA and histone methylation, with small interfering RNAs as the mediator.

A high-throughput surface plasmon resonance biosensor based on differential interferometric imaging

International Nuclear Information System (INIS)

Wang, Daqian; Ding, Lili; Zhang, Wei; Zhang, Enyao; Yu, Xinglong; Luo, Zhaofeng; Ou, Huichao

2012-01-01

A new high-throughput surface plasmon resonance (SPR) biosensor based on differential interferometric imaging is reported. The two SPR interferograms of the sensing surface are imaged on two CCD cameras. The phase difference between the two interferograms is 180°. The refractive index related factor (RIRF) of the sensing surface is calculated from the two simultaneously acquired interferograms. The simulation results indicate that the RIRF exhibits a linear relationship with the refractive index of the sensing surface and is unaffected by the noise, drift and intensity distribution of the light source. The affinity and kinetic information can be extracted in real time from continuously acquired RIRF distributions. The results of refractometry experiments show that the dynamic detection range of SPR differential interferometric imaging system can be over 0.015 refractive index unit (RIU). High refractive index resolution is down to 0.45 RU (1 RU = 1 × 10 −6 RIU). Imaging and protein microarray experiments demonstrate the ability of high-throughput detection. The aptamer experiments demonstrate that the SPR sensor based on differential interferometric imaging has a great capability to be implemented for high-throughput aptamer kinetic evaluation. These results suggest that this biosensor has the potential to be utilized in proteomics and drug discovery after further improvement. (paper)

Reaction Mechanism of Tar Evolution in Biomass Steam Gasification for Hydrogen Production

International Nuclear Information System (INIS)

Shingo Katayama; Masahiro Suzuki; Atsushi Tsutsumi

2006-01-01

Reaction mechanism of tar evolution in steam gasification of biomass was investigated with a continuous cross-flow moving bed type differential reactor, in which tar and gases can be fractionated according to reaction time. We estimated that time profile of tar and gas evolution in the gasification of cellulose, xylan, and lignin, and compared it with experimental product time profile of real biomass gasification. The experimental tar evolution rate is different from estimated tar evolution rate. The estimated tar evolution rate has a peak at 20 s. On the other hand, the experimental tar evolution rate at 20 s is little, and tar at initial stage includes more water-soluble and water-insoluble compounds. It can be concluded that in the real biomass steam gasification the evolution of tar from cellulose and lignin component was found to be precipitated by that from hemi-cellulose component. (authors)

Confronting uncertainty in model-based geostatistics using Markov Chain Monte Carlo simulation

NARCIS (Netherlands)

Minasny, B.; Vrugt, J.A.; McBratney, A.B.

2011-01-01

This paper demonstrates for the first time the use of Markov Chain Monte Carlo (MCMC) simulation for parameter inference in model-based soil geostatistics. We implemented the recently developed DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm to jointly summarize the posterior

Data Analytics Based Dual-Optimized Adaptive Model Predictive Control for the Power Plant Boiler

Directory of Open Access Journals (Sweden)

Zhenhao Tang

2017-01-01

Full Text Available To control the furnace temperature of a power plant boiler precisely, a dual-optimized adaptive model predictive control (DoAMPC method is designed based on the data analytics. In the proposed DoAMPC, an accurate predictive model is constructed adaptively by the hybrid algorithm of the least squares support vector machine and differential evolution method. Then, an optimization problem is constructed based on the predictive model and many constraint conditions. To control the boiler furnace temperature, the differential evolution method is utilized to decide the control variables by solving the optimization problem. The proposed method can adapt to the time-varying situation by updating the sample data. The experimental results based on practical data illustrate that the DoAMPC can control the boiler furnace temperature with errors of less than 1.5% which can meet the requirements of the real production process.

Development of efficient time-evolution method based on three-term recurrence relation

International Nuclear Information System (INIS)

Akama, Tomoko; Kobayashi, Osamu; Nanbu, Shinkoh

2015-01-01

The advantage of the real-time (RT) propagation method is a direct solution of the time-dependent Schrödinger equation which describes frequency properties as well as all dynamics of a molecular system composed of electrons and nuclei in quantum physics and chemistry. Its applications have been limited by computational feasibility, as the evaluation of the time-evolution operator is computationally demanding. In this article, a new efficient time-evolution method based on the three-term recurrence relation (3TRR) was proposed to reduce the time-consuming numerical procedure. The basic formula of this approach was derived by introducing a transformation of the operator using the arcsine function. Since this operator transformation causes transformation of time, we derived the relation between original and transformed time. The formula was adapted to assess the performance of the RT time-dependent Hartree-Fock (RT-TDHF) method and the time-dependent density functional theory. Compared to the commonly used fourth-order Runge-Kutta method, our new approach decreased computational time of the RT-TDHF calculation by about factor of four, showing the 3TRR formula to be an efficient time-evolution method for reducing computational cost

SOME IMPORTANT FACTORS AFFECTING EVOLUTION OF ACTIVITY BASED COSTING (ABC SYSTEM IN EGYPTIAN MANUFACTURING FIRMS

Directory of Open Access Journals (Sweden)

Karim MAMDOUH ABBAS

2014-04-01

Full Text Available The present investigation aims to determine the factors affecting evolution of Activity Based Costing (ABC system in Egyptian case. The study used the survey method to describe and analyze these factors in some Egyptian firms. The population of the study is Egyptian manufacturing firms. Accordingly, the number of received questionnaires was 392 (23 Egyptian manufacturing firms in the first half of 2013. Finally, the study stated some influencing factors for evolution this system (ABC in Egyptian manufacturing firms.

Absolute Position Sensing Based on a Robust Differential Capacitive Sensor with a Grounded Shield Window

Directory of Open Access Journals (Sweden)

Yang Bai

2016-05-01

Full Text Available A simple differential capacitive sensor is provided in this paper to measure the absolute positions of length measuring systems. By utilizing a shield window inside the differential capacitor, the measurement range and linearity range of the sensor can reach several millimeters. What is more interesting is that this differential capacitive sensor is only sensitive to one translational degree of freedom (DOF movement, and immune to the vibration along the other two translational DOFs. In the experiment, we used a novel circuit based on an AC capacitance bridge to directly measure the differential capacitance value. The experimental result shows that this differential capacitive sensor has a sensitivity of 2 × 10−4 pF/μm with 0.08 μm resolution. The measurement range of this differential capacitive sensor is 6 mm, and the linearity error are less than 0.01% over the whole absolute position measurement range.

From determinism and probability to chaos: chaotic evolution towards philosophy and methodology of chaotic optimization.

Science.gov (United States)

Pei, Yan

2015-01-01

We present and discuss philosophy and methodology of chaotic evolution that is theoretically supported by chaos theory. We introduce four chaotic systems, that is, logistic map, tent map, Gaussian map, and Hénon map, in a well-designed chaotic evolution algorithm framework to implement several chaotic evolution (CE) algorithms. By comparing our previous proposed CE algorithm with logistic map and two canonical differential evolution (DE) algorithms, we analyse and discuss optimization performance of CE algorithm. An investigation on the relationship between optimization capability of CE algorithm and distribution characteristic of chaotic system is conducted and analysed. From evaluation result, we find that distribution of chaotic system is an essential factor to influence optimization performance of CE algorithm. We propose a new interactive EC (IEC) algorithm, interactive chaotic evolution (ICE) that replaces fitness function with a real human in CE algorithm framework. There is a paired comparison-based mechanism behind CE search scheme in nature. A simulation experimental evaluation is conducted with a pseudo-IEC user to evaluate our proposed ICE algorithm. The evaluation result indicates that ICE algorithm can obtain a significant better performance than or the same performance as interactive DE. Some open topics on CE, ICE, fusion of these optimization techniques, algorithmic notation, and others are presented and discussed.

From Determinism and Probability to Chaos: Chaotic Evolution towards Philosophy and Methodology of Chaotic Optimization

Science.gov (United States)

2015-01-01

We present and discuss philosophy and methodology of chaotic evolution that is theoretically supported by chaos theory. We introduce four chaotic systems, that is, logistic map, tent map, Gaussian map, and Hénon map, in a well-designed chaotic evolution algorithm framework to implement several chaotic evolution (CE) algorithms. By comparing our previous proposed CE algorithm with logistic map and two canonical differential evolution (DE) algorithms, we analyse and discuss optimization performance of CE algorithm. An investigation on the relationship between optimization capability of CE algorithm and distribution characteristic of chaotic system is conducted and analysed. From evaluation result, we find that distribution of chaotic system is an essential factor to influence optimization performance of CE algorithm. We propose a new interactive EC (IEC) algorithm, interactive chaotic evolution (ICE) that replaces fitness function with a real human in CE algorithm framework. There is a paired comparison-based mechanism behind CE search scheme in nature. A simulation experimental evaluation is conducted with a pseudo-IEC user to evaluate our proposed ICE algorithm. The evaluation result indicates that ICE algorithm can obtain a significant better performance than or the same performance as interactive DE. Some open topics on CE, ICE, fusion of these optimization techniques, algorithmic notation, and others are presented and discussed. PMID:25879067

From Determinism and Probability to Chaos: Chaotic Evolution towards Philosophy and Methodology of Chaotic Optimization

Directory of Open Access Journals (Sweden)

Yan Pei

2015-01-01

Full Text Available We present and discuss philosophy and methodology of chaotic evolution that is theoretically supported by chaos theory. We introduce four chaotic systems, that is, logistic map, tent map, Gaussian map, and Hénon map, in a well-designed chaotic evolution algorithm framework to implement several chaotic evolution (CE algorithms. By comparing our previous proposed CE algorithm with logistic map and two canonical differential evolution (DE algorithms, we analyse and discuss optimization performance of CE algorithm. An investigation on the relationship between optimization capability of CE algorithm and distribution characteristic of chaotic system is conducted and analysed. From evaluation result, we find that distribution of chaotic system is an essential factor to influence optimization performance of CE algorithm. We propose a new interactive EC (IEC algorithm, interactive chaotic evolution (ICE that replaces fitness function with a real human in CE algorithm framework. There is a paired comparison-based mechanism behind CE search scheme in nature. A simulation experimental evaluation is conducted with a pseudo-IEC user to evaluate our proposed ICE algorithm. The evaluation result indicates that ICE algorithm can obtain a significant better performance than or the same performance as interactive DE. Some open topics on CE, ICE, fusion of these optimization techniques, algorithmic notation, and others are presented and discussed.

Comparative genomic analysis of Helicobacter pylori from Malaysia identifies three distinct lineages suggestive of differential evolution.

Science.gov (United States)

Kumar, Narender; Mariappan, Vanitha; Baddam, Ramani; Lankapalli, Aditya K; Shaik, Sabiha; Goh, Khean-Lee; Loke, Mun Fai; Perkins, Tim; Benghezal, Mohammed; Hasnain, Seyed E; Vadivelu, Jamuna; Marshall, Barry J; Ahmed, Niyaz

2015-01-01

The discordant prevalence of Helicobacter pylori and its related diseases, for a long time, fostered certain enigmatic situations observed in the countries of the southern world. Variation in H. pylori infection rates and disease outcomes among different populations in multi-ethnic Malaysia provides a unique opportunity to understand dynamics of host-pathogen interaction and genome evolution. In this study, we extensively analyzed and compared genomes of 27 Malaysian H. pylori isolates and identified three major phylogeographic lineages: hspEastAsia, hpEurope and hpSouthIndia. The analysis of the virulence genes within the core genome, however, revealed a comparable pathogenic potential of the strains. In addition, we identified four genes limited to strains of East-Asian lineage. Our analyses identified a few strain-specific genes encoding restriction modification systems and outlined 311 core genes possibly under differential evolutionary constraints, among the strains representing different ethnic groups. The cagA and vacA genes also showed variations in accordance with the host genetic background of the strains. Moreover, restriction modification genes were found to be significantly enriched in East-Asian strains. An understanding of these variations in the genome content would provide significant insights into various adaptive and host modulation strategies harnessed by H. pylori to effectively persist in a host-specific manner. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

A Pattern Language for the Evolution of Component-based Software Architectures

DEFF Research Database (Denmark)

Ahmad, Aakash; Jamshidi, Pooyan; Pahl, Claus

2013-01-01

Modern software systems are prone to a continuous evolution under frequently varying requirements. Architecture-centric software evolution enables change in system’s structure and behavior while maintaining a global view of the software to address evolution-centric tradeoffs. Lehman’s law...... evolution problems. We propose that architectural evolution process requires an explicit evolution-centric knowledge – that can be discovered, shared, and reused – to anticipate and guide change management. Therefore, we present a pattern language as a collection of interconnected change patterns......) as a complementary and integrated phase to facilitate reuse-driven architecture change execution (pattern language application). Reuse-knowledge in the proposed pattern language is expressed as a formalised collection of interconnected-patterns. Individual patterns in the language build on each other to facilitate...

The symbiotic intestinal ciliates and the evolution of their hosts

NARCIS (Netherlands)

Moon-van der Staay, S.Y.; Staay, G.W. van der; Michalowski, T.; Jouany, J.P.; Pristas, P.; Javorsky, P.; Kisidayova, S.; Varadyova, Z.; McEwan, N.R.; Newbold, C.J.; Alen, T. van; Graaf, R. de; Schmid, M.; Huynen, M.A.; Hackstein, J.H.

2014-01-01

The evolution of sophisticated differentiations of the gastro-intestinal tract enabled herbivorous mammals to digest dietary cellulose and hemicellulose with the aid of a complex anaerobic microbiota. Distinctive symbiotic ciliates, which are unique to this habitat, are the largest representatives

The lie-algebraic structures and integrability of differential and differential-difference nonlinear dynamical systems

International Nuclear Information System (INIS)

Prykarpatsky, A.K.; Blackmore, D.L.; Bogolubov, N.N. Jr.

2007-05-01

The infinite-dimensional operator Lie algebras of the related integrable nonlocal differential-difference dynamical systems are treated as their hidden symmetries. As a result of their dimerization the Lax type representations for both local differential-difference equations and nonlocal ones are obtained. An alternative approach to the Lie-algebraic interpretation of the integrable local differential-difference systems is also proposed. The Hamiltonian representation for a hierarchy of Lax type equations on a dual space to the centrally extended Lie algebra of integro-differential operators with matrix-valued coefficients coupled with suitable eigenfunctions and adjoint eigenfunctions evolutions of associated spectral problems is obtained by means of a specially constructed Baecklund transformation. The Hamiltonian description for the corresponding set of additional symmetry hierarchies is represented. The relation of these hierarchies with Lax type integrable (3+1)-dimensional nonlinear dynamical systems and their triple Lax type linearizations is analyzed. The Lie-algebraic structures, related with centrally extended current operator Lie algebras are discussed with respect to constructing new nonlinear integrable dynamical systems on functional manifolds and super-manifolds. Special Poisson structures and related with them factorized integrable operator dynamical systems having interesting applications in modern mathematical physics, quantum computing mathematics and other fields are constructed. The previous purely computational results are explained within the approach developed. (author)

Local Orientation and the Evolution of Foraging: Changes in Decision Making Can Eliminate Evolutionary Trade-offs

Science.gov (United States)

van der Post, Daniel J.; Semmann, Dirk

2011-01-01

Information processing is a major aspect of the evolution of animal behavior. In foraging, responsiveness to local feeding opportunities can generate patterns of behavior which reflect or “recognize patterns” in the environment beyond the perception of individuals. Theory on the evolution of behavior generally neglects such opportunity-based adaptation. Using a spatial individual-based model we study the role of opportunity-based adaptation in the evolution of foraging, and how it depends on local decision making. We compare two model variants which differ in the individual decision making that can evolve (restricted and extended model), and study the evolution of simple foraging behavior in environments where food is distributed either uniformly or in patches. We find that opportunity-based adaptation and the pattern recognition it generates, plays an important role in foraging success, particularly in patchy environments where one of the main challenges is “staying in patches”. In the restricted model this is achieved by genetic adaptation of move and search behavior, in light of a trade-off on within- and between-patch behavior. In the extended model this trade-off does not arise because decision making capabilities allow for differentiated behavioral patterns. As a consequence, it becomes possible for properties of movement to be specialized for detection of patches with more food, a larger scale information processing not present in the restricted model. Our results show that changes in decision making abilities can alter what kinds of pattern recognition are possible, eliminate an evolutionary trade-off and change the adaptive landscape. PMID:21998571

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.

Karyological characterization of the endemic Iberian rock lizard, Iberolacerta monticola (Squamata, Lacertidae): insights into sex chromosome evolution.

Science.gov (United States)

Rojo, V; Giovannotti, M; Naveira, H; Nisi Cerioni, P; González-Tizón, A M; Caputo Barucchi, V; Galán, P; Olmo, E; Martínez-Lage, A

2014-01-01

Rock lizards of the genus Iberolacerta constitute a promising model to examine the process of sex chromosome evolution, as these closely related taxa exhibit remarkable diversity in the degree of sex chromosome differentiation with no clear phylogenetic segregation, ranging from cryptic to highly heteromorphic ZW chromosomes and even multiple chromosome systems (Z1Z1Z2Z2/Z1Z2W). To gain a deeper insight into the patterns of karyotype and sex chromosome evolution, we performed a cytogenetic analysis based on conventional staining, banding techniques and fluorescence in situ hybridization in the species I. monticola, for which previous cytogenetic investigations did not detect differentiated sex chromosomes. The karyotype is composed of 2n = 36 acrocentric chromosomes. NORs and the major ribosomal genes were located in the subtelomeric region of chromosome pair 6. Hybridization signals of the telomeric sequences (TTAGGG)n were visualized at the telomeres of all chromosomes and interstitially in 5 chromosome pairs. C-banding showed constitutive heterochromatin at the centromeres of all chromosomes, as well as clear pericentromeric and light telomeric C-bands in several chromosome pairs. These results highlight some chromosomal markers which can be useful to identify species-specific diagnostic characters, although they may not accurately reflect the phylogenetic relationships among the taxa. In addition, C-banding revealed the presence of a heteromorphic ZW sex chromosome pair, where W is smaller than Z and almost completely heterochromatic. This finding sheds light on sex chromosome evolution in the genus Iberolacerta and suggests that further comparative cytogenetic analyses are needed to understand the processes underlying the origin, differentiation and plasticity of sex chromosome systems in lacertid lizards. © 2013 S. Karger AG, Basel.

Design of an ultrafast all-optical differentiator based on a fiber Bragg grating in transmission.

Science.gov (United States)

Preciado, Miguel A; Muriel, Miguel A

2008-11-01

We propose and analyze a first-order optical differentiator based on a fiber Bragg grating (FBG) in transmission. It is shown in the examples that a simple uniform-period FBG in a very strong coupling regime (maximum reflectivity very close to 100%) can perform close to ideal temporal differentiation of the complex envelope of an arbitrary-input optical signal.

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)

Pb evolution in the Martian mantle

Science.gov (United States)

Bellucci, J. J.; Nemchin, A. A.; Whitehouse, M. J.; Snape, J. F.; Bland, P.; Benedix, G. K.; Roszjar, J.

2018-03-01

The initial Pb compositions of one enriched shergottite, one intermediate shergottite, two depleted shergottites, and Nakhla have been measured by Secondary Ion Mass Spectrometry (SIMS). These values, in addition to data from previous studies using an identical analytical method performed on three enriched shergottites, ALH 84001, and Chassigny, are used to construct a unified and internally consistent model for the differentiation history of the Martian mantle and crystallization ages for Martian meteorites. The differentiation history of the shergottites and Nakhla/Chassigny are fundamentally different, which is in agreement with short-lived radiogenic isotope systematics. The initial Pb compositions of Nakhla/Chassigny are best explained by the late addition of a Pb-enriched component with a primitive, non-radiogenic composition. In contrast, the Pb isotopic compositions of the shergottite group indicate a relatively simple evolutionary history of the Martian mantle that can be modeled based on recent results from the Sm-Nd system. The shergottites have been linked to a single mantle differentiation event at 4504 Ma. Thus, the shergottite Pb isotopic model here reflects a two-stage history 1) pre-silicate differentiation (4504 Ma) and 2) post-silicate differentiation to the age of eruption (as determined by concordant radiogenic isochron ages). The μ-values (238U/204Pb) obtained for these two different stages of Pb growth are μ1 of 1.8 and a range of μ2 from 1.4-4.7, respectively. The μ1-value of 1.8 is in broad agreement with enstatite and ordinary chondrites and that proposed for proto Earth, suggesting this is the initial μ-value for inner Solar System bodies. When plotted against other source radiogenic isotopic variables (Sri, γ187Os, ε143Nd, and ε176Hf), the second stage mantle evolution range in observed mantle μ-values display excellent linear correlations (r2 > 0.85) and represent a spectrum of Martian mantle mixing-end members (depleted

Dip-in Indicators for Visual Differentiation of Fuel Mixtures Based on Wettability of Fluoroalkylchlorosilane-Coated Inverse Opal Films.

Science.gov (United States)

Sedighi, Abootaleb; Qiu, Shuang; Wong, Michael C K; Li, Paul C H

2015-12-30

We have developed the dip-in indicator based on the inverse opal film (IOF) for visual differentiation of organic liquid mixtures, such as oil/gasoline or ethanol/gasoline fuel mixtures. The IOF consists of a three-dimensional porous structure with a highly ordered periodic arrangement of nanopores. The specularly reflected light at the interface of the nanopores and silica walls contributes to the structural color of the IOF film. This color disappears when the nanopores are infiltrated by a liquid with a similar refractive index to silica. The disappearance of the structural color provides a means to differentiate various liquid fuel mixtures based on their wettability of the nanopores in the IOF-based indicators. For differentiation of various liquid mixtures, we tune the wettability threshold of the indicator in such a way that it is wetted (color disappears) by one liquid but is not wetted by the other (color remains). Although colorimetric differentiation of liquids based on IOF wettability has been reported, differentiation of highly similar liquid mixtures require complicated readout approaches. It is known that the IOF wettability is controlled by multiple surface properties (e.g., oleophobicity) and structural properties (e.g., neck angle and film thickness) of the nanostructure. Therefore, we aim to exploit the combined tuning of these properties for differentiation of fuel mixtures with close compositions. In this study, we have demonstrated that, for the first time, the IOF-based dip-in indicator is able to detect a slight difference in the fuel mixture composition (i.e., 0.4% of oil content). Moreover, the color/no-color differentiation platform is simple, powerful, and easy-to-read. This platform makes the dip-in indicator a promising tool for authentication and determination of fuel composition at the point-of-purchase or point-of-use.

Dynamic and quantitative method of analyzing service consistency evolution based on extended hierarchical finite state automata.

Science.gov (United States)

Fan, Linjun; Tang, Jun; Ling, Yunxiang; Li, Benxian

2014-01-01

This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service's evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version's confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA.

Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata

Directory of Open Access Journals (Sweden)

Linjun Fan

2014-01-01

Full Text Available This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA. Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service’s evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA is constructed based on finite state automata (FSA, which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average is the biggest influential factor, the noncomposition of atomic services (13.12% is the second biggest one, and the service version’s confusion (1.2% is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA.

Software evolution with XVCL

DEFF Research Database (Denmark)

Zhang, Weishan; Jarzabek, Stan; Zhang, Hongyu

2004-01-01

This chapter introduces software evolution with XVCL (XML-based Variant Configuration Language), which is an XML-based metaprogramming technique. As the software evolves, a large number of variants may arise, especially whtn such kinds of evolutions are related to multiple platforms as shown in our...... case study. Handling variants and tracing the impact of variants across the development lifecycle is a challenge. This chapter shows how we can maintain different versions of software in a reuse-based way....

The early evolution of the atmospheres of terrestrial planets

CERN Document Server

Raulin, François; Muller, Christian; Nixon, Conor; Astrophysics and Space Science Proceedings : Volume 35

2013-01-01

“The Early Evolution of the Atmospheres of Terrestrial Planets” presents the main processes participating in the atmospheric evolution of terrestrial planets. A group of experts in the different fields provide an update of our current knowledge on this topic. Several papers in this book discuss the key role of nitrogen in the atmospheric evolution of terrestrial planets. The earliest setting and evolution of planetary atmospheres of terrestrial planets is directly associated with accretion, chemical differentiation, outgassing, stochastic impacts, and extremely high energy fluxes from their host stars. This book provides an overview of the present knowledge of the initial atmospheric composition of the terrestrial planets. Additionally it includes some papers about the current exoplanet discoveries and provides additional clues to our understanding of Earth’s transition from a hot accretionary phase into a habitable world. All papers included were reviewed by experts in their respective fields. We are ...

Fast and quantitative differentiation of single-base mismatched DNA by initial reaction rate of catalytic hairpin assembly.

Science.gov (United States)

Li, Chenxi; Li, Yixin; Xu, Xiao; Wang, Xinyi; Chen, Yang; Yang, Xiaoda; Liu, Feng; Li, Na

2014-10-15

The widely used catalytic hairpin assembly (CHA) amplification strategy generally needs several hours to accomplish one measurement based on the prevailingly used maximum intensity detection mode, making it less practical for assays where high throughput or speed is desired. To make the best use of the kinetic specificity of toehold domain for circuit reaction initiation, we developed a mathematical model and proposed an initial reaction rate detection mode to quantitatively differentiate the single-base mismatch. Using the kinetic mode, assay time can be reduced substantially to 10 min for one measurement with the comparable sensitivity and single-base mismatch differentiating ability as were obtained by the maximum intensity detection mode. This initial reaction rate based approach not only provided a fast and quantitative differentiation of single-base mismatch, but also helped in-depth understanding of the CHA system, which will be beneficial to the design of highly sensitive and specific toehold-mediated hybridization reactions. Copyright © 2014 Elsevier B.V. All rights reserved.

Lectures on differential Galois theory

CERN Document Server

Magid, Andy R

1994-01-01

Differential Galois theory studies solutions of differential equations over a differential base field. In much the same way that ordinary Galois theory is the theory of field extensions generated by solutions of (one variable) polynomial equations, differential Galois theory looks at the nature of the differential field extension generated by the solutions of differential equations. An additional feature is that the corresponding differential Galois groups (of automorphisms of the extension fixing the base and commuting with the derivation) are algebraic groups. This book deals with the differential Galois theory of linear homogeneous differential equations, whose differential Galois groups are algebraic matrix groups. In addition to providing a convenient path to Galois theory, this approach also leads to the constructive solution of the inverse problem of differential Galois theory for various classes of algebraic groups. Providing a self-contained development and many explicit examples, this book provides ...

A stochastic differential equation framework for the turbulent velocity field

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Schmiegel, Jürgen

We discuss a stochastic differential equation, as a modelling framework for the turbulent velocity field, that is capable of capturing basic stylized facts of the statistics of velocity increments. In particular, we focus on the evolution of the probability density of velocity increments...

Study of a sol–gel precursor and its evolution towards ZnO

Energy Technology Data Exchange (ETDEWEB)

Gómez-Núñez, Alberto [University of Barcelona, Department of Electronics, Martí i Franquès 1, E08028 Barcelona (Spain); López, Concepción [University of Barcelona, Department of Inorganic Chemistry, Martí i Franquès 1, E08028 Barcelona (Spain); Alonso-Gil, Santiago [University of Barcelona, Department of Organic Chemistry, Martí i Franquès 1, E08028 Barcelona (Spain); Roura, Pere [University of Girona, Department of Physics, Campus Montilivi, Edif. PII, E17071 Girona (Spain); Vilà, Anna, E-mail: anna.vila@ub.edu [University of Barcelona, Department of Electronics, Martí i Franquès 1, E08028 Barcelona (Spain)

2015-07-15

The processes involved in the assembly of zinc acetate dihydrate {Zn(CH_3COO)_2·2H_2O} and ethanolamine (H{sub 2}NCH{sub 2}CH{sub 2}OH), with or without 2-methoxyethanol as solvent, have been analysed by infrared spectra, mass spectrometry, nuclear magnetic resonance, powder X-ray diffraction and computational studies. Thermal evolution of the mixtures was characterized by thermoanalytical and structural techniques (thermogravimetry, differential thermal analysis, differential scanning calorimetry, X-ray diffraction and X-Ray photoelectron spectroscopy). Computational studies together with experiments served to thoroughly describe the precursor and its decomposition. The thermal decomposition of the mixture and its transformation into crystalline ZnO take place in a temperature range between 50 and 450 °C through different processes. With solvent, the processes need temperatures 90 °C higher with respect to the mixture without solvent, and ZnO arises at 250 °C. - Graphical abstract: Display Omitted - Highlights: • Tetramer structure of the zinc-acetate plus ethanolamine precursor confirmed by IR, MS and theoretical calculations. • Precursor crystal structure determined to be of the monoclinic P2{sub 1}/m system. • High influence of the metoxyethanol solvent on the formation temperature of ZnO. • Detailed description of the thermal evolution from the zinc-based precursor to ZnO.

Differentiating the evolution of female song and male-female duets in the New World blackbirds: can tropical natural history traits explain duet evolution?

Science.gov (United States)

Odom, Karan J; Omland, Kevin E; Price, J Jordan

2015-03-01

Female bird song and combined vocal duets of mated pairs are both frequently associated with tropical, monogamous, sedentary natural histories. Little is known, however, about what selects for duetting behavior versus female song. Female song likely preceded duet evolution and could drive apparent relationships between duets and these natural histories. We compared the evolution of female song and male-female duets in the New World blackbirds (Icteridae) by investigating patterns of gains and losses of both traits and their relationships with breeding latitude, mating system, nesting pattern, and migratory behavior. We found that duets evolved only in lineages in which female song was likely ancestral. Both female song and duets were correlated with tropical breeding, social monogamy, territorial nesting, and sedentary behavior when all taxa were included; however, correlations between duets and these natural history traits disappeared when comparisons were limited to taxa with female song. Also, likelihood values supported stronger relationships between the natural history traits and female song than between these traits and duets. Our results suggest that the natural histories thought to favor the evolution of duetting may in fact be associated with female song and that additional selection pressures are responsible for the evolution of duets. © 2015 The Author(s).

Reconstructing human evolution

CERN Multimedia

AUTHOR|(CDS)2074069

1999-01-01

One can reconstruct human evolution using modern genetic data and models based on the mathematical theory of evolution and its four major factors : mutation, natural selection, statistical fluctuations in finite populations (random genetic drift), and migration. Archaeology gives some help on the major dates and events of the process. Chances of studying ancient DNA are very limited but there have been a few successful results. Studying DNA instead of proteins, as was done until a few years ago, and in particular the DNA of mitochondria and of the Y chromosome which are transmitted, respectively, by the maternal line and the paternal line, has greatly simplified the analysis. It is now possible to carry the analysis on individuals, while earlier studies were of necessity based on populations. Also the evolution of ÒcultureÓ (i.e. what we learn from others), in particular that of languages, gives some help and can be greatly enlightened by genetic studies. Even though it is largely based on mechanisms of mut...

Evolution of Web-based International Marketing

DEFF Research Database (Denmark)

Rask, Morten

2002-01-01

Companies that have been doing international business do not usually make the transition from traditional marketers to full-blown Web marketers in one sharp step. In our study of Danish firms, we found that in terms of the evolution of their Web strategies, these Danish companies went through three...

Lie symmetry analysis and conservation laws for the time fractional fourth-order evolution equation

Directory of Open Access Journals (Sweden)

Wang Li

2017-06-01

Full Text Available In this paper, we study Lie symmetry analysis and conservation laws for the time fractional nonlinear fourth-order evolution equation. Using the method of Lie point symmetry, we provide the associated vector fields, and derive the similarity reductions of the equation, respectively. The method can be applied wisely and efficiently to get the reduced fractional ordinary differential equations based on the similarity reductions. Finally, by using the nonlinear self-adjointness method and Riemann-Liouville time-fractional derivative operator as well as Euler-Lagrange operator, the conservation laws of the equation are obtained.

Agent-Based Model of Price Competition and Product Differentiation on Congested Networks

OpenAIRE

Lei Zhang; David Levinson; Shanjiang Zhu

2007-01-01

Using consistent agent-based techniques, this research models the decision-making processes of users and infrastructure owner/operators to explore the welfare consequence of price competition, capacity choice, and product differentiation on congested transportation networks. Component models include: (1) An agent-based travel demand model wherein each traveler has learning capabilities and unique characteristics (e.g. value of time); (2) Econometric facility provision cost models; and (3) Rep...

Black hole thermodynamics based on unitary evolutions

International Nuclear Information System (INIS)

Feng, Yu-Lei; Chen, Yi-Xin

2015-01-01

In this paper, we try to construct black hole thermodynamics based on the fact that the formation and evaporation of a black hole can be described by quantum unitary evolutions. First, we show that the Bekenstein–Hawking entropy S BH may not be a Boltzmann or thermal entropy. To confirm this statement, we show that the original black hole's ‘first law’ may not simply be treated as the first law of thermodynamics formally, due to some missing metric perturbations caused by matter. Then, by including those (quantum) metric perturbations, we show that the black hole formation and evaporation can be described effectively in a unitary manner, through a quantum channel between the exterior and interior of the event horizon. In this way, the paradoxes of information loss and firewall can be resolved effectively. Finally, we show that black hole thermodynamics can be constructed in an ordinary way, by constructing statistical mechanics. (paper)

Trait-specific processes of convergence and conservatism shape ecomorphological evolution in ground-dwelling squirrels.

Science.gov (United States)

McLean, Bryan S; Helgen, Kristofer M; Goodwin, H Thomas; Cook, Joseph A

2018-03-01

Our understanding of mechanisms operating over deep timescales to shape phenotypic diversity often hinges on linking variation in one or few trait(s) to specific evolutionary processes. When distinct processes are capable of similar phenotypic signatures, however, identifying these drivers is difficult. We explored ecomorphological evolution across a radiation of ground-dwelling squirrels whose history includes convergence and constraint, two processes that can yield similar signatures of standing phenotypic diversity. Using four ecologically relevant trait datasets (body size, cranial, mandibular, and molariform tooth shape), we compared and contrasted variation, covariation, and disparity patterns in a new phylogenetic framework. Strong correlations existed between body size and two skull traits (allometry) and among skull traits themselves (integration). Inferred evolutionary modes were also concordant across traits (Ornstein-Uhlenbeck with two adaptive regimes). However, despite these broad similarities, we found divergent dynamics on the macroevolutionary landscape, with phenotypic disparity being differentially shaped by convergence and conservatism. Such among-trait heterogeneity in process (but not always pattern) reiterates the mosaic nature of morphological evolution, and suggests ground squirrel evolution is poorly captured by single process descriptors. Our results also highlight how use of single traits can bias macroevolutionary inference, affirming the importance of broader trait-bases in understanding phenotypic evolutionary dynamics. © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.

The effect of numerical techniques on differential equation based chaotic generators

KAUST Repository

Zidan, Mohammed A.

2012-07-29

In this paper, we study the effect of the numerical solution accuracy on the digital implementation of differential chaos generators. Four systems are built on a Xilinx Virtex 4 FPGA using Euler, mid-point, and Runge-Kutta fourth order techniques. The twelve implementations are compared based on the FPGA used area, maximum throughput, maximum Lyapunov exponent, and autocorrelation confidence region. Based on circuit performance and the chaotic response of the different implementations, it was found that less complicated numerical solution has better chaotic response and higher throughput.

The Evolution of Facultative Conformity Based on Similarity.

Science.gov (United States)

Efferson, Charles; Lalive, Rafael; Cacault, Maria Paula; Kistler, Deborah

2016-01-01

Conformist social learning can have a pronounced impact on the cultural evolution of human societies, and it can shape both the genetic and cultural evolution of human social behavior more broadly. Conformist social learning is beneficial when the social learner and the demonstrators from whom she learns are similar in the sense that the same behavior is optimal for both. Otherwise, the social learner's optimum is likely to be rare among demonstrators, and conformity is costly. The trade-off between these two situations has figured prominently in the longstanding debate about the evolution of conformity, but the importance of the trade-off can depend critically on the flexibility of one's social learning strategy. We developed a gene-culture coevolutionary model that allows cognition to encode and process information about the similarity between naive learners and experienced demonstrators. Facultative social learning strategies that condition on perceived similarity evolve under certain circumstances. When this happens, facultative adjustments are often asymmetric. Asymmetric adjustments mean that the tendency to follow the majority when learners perceive demonstrators as similar is stronger than the tendency to follow the minority when learners perceive demonstrators as different. In an associated incentivized experiment, we found that social learners adjusted how they used social information based on perceived similarity, but adjustments were symmetric. The symmetry of adjustments completely eliminated the commonly assumed trade-off between cases in which learners and demonstrators share an optimum versus cases in which they do not. In a second experiment that maximized the potential for social learners to follow their preferred strategies, a few social learners exhibited an inclination to follow the majority. Most, however, did not respond systematically to social information. Additionally, in the complete absence of information about their similarity to

The Evolution of Facultative Conformity Based on Similarity.

Directory of Open Access Journals (Sweden)

Charles Efferson

Full Text Available Conformist social learning can have a pronounced impact on the cultural evolution of human societies, and it can shape both the genetic and cultural evolution of human social behavior more broadly. Conformist social learning is beneficial when the social learner and the demonstrators from whom she learns are similar in the sense that the same behavior is optimal for both. Otherwise, the social learner's optimum is likely to be rare among demonstrators, and conformity is costly. The trade-off between these two situations has figured prominently in the longstanding debate about the evolution of conformity, but the importance of the trade-off can depend critically on the flexibility of one's social learning strategy. We developed a gene-culture coevolutionary model that allows cognition to encode and process information about the similarity between naive learners and experienced demonstrators. Facultative social learning strategies that condition on perceived similarity evolve under certain circumstances. When this happens, facultative adjustments are often asymmetric. Asymmetric adjustments mean that the tendency to follow the majority when learners perceive demonstrators as similar is stronger than the tendency to follow the minority when learners perceive demonstrators as different. In an associated incentivized experiment, we found that social learners adjusted how they used social information based on perceived similarity, but adjustments were symmetric. The symmetry of adjustments completely eliminated the commonly assumed trade-off between cases in which learners and demonstrators share an optimum versus cases in which they do not. In a second experiment that maximized the potential for social learners to follow their preferred strategies, a few social learners exhibited an inclination to follow the majority. Most, however, did not respond systematically to social information. Additionally, in the complete absence of information about their

The Evolution of Facultative Conformity Based on Similarity

Science.gov (United States)

Efferson, Charles; Lalive, Rafael; Cacault, Maria Paula; Kistler, Deborah

2016-01-01

Conformist social learning can have a pronounced impact on the cultural evolution of human societies, and it can shape both the genetic and cultural evolution of human social behavior more broadly. Conformist social learning is beneficial when the social learner and the demonstrators from whom she learns are similar in the sense that the same behavior is optimal for both. Otherwise, the social learner’s optimum is likely to be rare among demonstrators, and conformity is costly. The trade-off between these two situations has figured prominently in the longstanding debate about the evolution of conformity, but the importance of the trade-off can depend critically on the flexibility of one’s social learning strategy. We developed a gene-culture coevolutionary model that allows cognition to encode and process information about the similarity between naive learners and experienced demonstrators. Facultative social learning strategies that condition on perceived similarity evolve under certain circumstances. When this happens, facultative adjustments are often asymmetric. Asymmetric adjustments mean that the tendency to follow the majority when learners perceive demonstrators as similar is stronger than the tendency to follow the minority when learners perceive demonstrators as different. In an associated incentivized experiment, we found that social learners adjusted how they used social information based on perceived similarity, but adjustments were symmetric. The symmetry of adjustments completely eliminated the commonly assumed trade-off between cases in which learners and demonstrators share an optimum versus cases in which they do not. In a second experiment that maximized the potential for social learners to follow their preferred strategies, a few social learners exhibited an inclination to follow the majority. Most, however, did not respond systematically to social information. Additionally, in the complete absence of information about their similarity to

Variation, differential reproduction and oscillation: the evolution of nucleic acid hybridization.

Science.gov (United States)

Suárez-Díaz, Edna

2013-01-01

This paper builds upon Hans-Jörg Rheinberger ideas on the oscillation and intercalation of epistemic things and technical objects in experimental systems, to give a fine-grained analysis of what here is called the problems of "adaptation" between our material and cognitive tools and the phenomena of the material world. To do so, it relies on the case-study of the evolution of nucleic acid hybridization and the stabilization of satellite DNA.

Differential standard deviation of log-scale intensity based optical coherence tomography angiography.

Science.gov (United States)

Shi, Weisong; Gao, Wanrong; Chen, Chaoliang; Yang, Victor X D

2017-12-01

In this paper, a differential standard deviation of log-scale intensity (DSDLI) based optical coherence tomography angiography (OCTA) is presented for calculating microvascular images of human skin. The DSDLI algorithm calculates the variance in difference images of two consecutive log-scale intensity based structural images from the same position along depth direction to contrast blood flow. The en face microvascular images were then generated by calculating the standard deviation of the differential log-scale intensities within the specific depth range, resulting in an improvement in spatial resolution and SNR in microvascular images compared to speckle variance OCT and power intensity differential method. The performance of DSDLI was testified by both phantom and in vivo experiments. In in vivo experiments, a self-adaptive sub-pixel image registration algorithm was performed to remove the bulk motion noise, where 2D Fourier transform was utilized to generate new images with spatial interval equal to half of the distance between two pixels in both fast-scanning and depth directions. The SNRs of signals of flowing particles are improved by 7.3 dB and 6.8 dB on average in phantom and in vivo experiments, respectively, while the average spatial resolution of images of in vivo blood vessels is increased by 21%. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparative Sex Chromosome Genomics in Snakes: Differentiation, Evolutionary Strata, and Lack of Global Dosage Compensation

Science.gov (United States)

Zektser, Yulia; Mahajan, Shivani; Bachtrog, Doris

2013-01-01

Snakes exhibit genetic sex determination, with female heterogametic sex chromosomes (ZZ males, ZW females). Extensive cytogenetic work has suggested that the level of sex chromosome heteromorphism varies among species, with Boidae having entirely homomorphic sex chromosomes, Viperidae having completely heteromorphic sex chromosomes, and Colubridae showing partial differentiation. Here, we take a genomic approach to compare sex chromosome differentiation in these three snake families. We identify homomorphic sex chromosomes in boas (Boidae), but completely heteromorphic sex chromosomes in both garter snakes (Colubridae) and pygmy rattlesnake (Viperidae). Detection of W-linked gametologs enables us to establish the presence of evolutionary strata on garter and pygmy rattlesnake sex chromosomes where recombination was abolished at different time points. Sequence analysis shows that all strata are shared between pygmy rattlesnake and garter snake, i.e., recombination was abolished between the sex chromosomes before the two lineages diverged. The sex-biased transmission of the Z and its hemizygosity in females can impact patterns of molecular evolution, and we show that rates of evolution for Z-linked genes are increased relative to their pseudoautosomal homologs, both at synonymous and amino acid sites (even after controlling for mutational biases). This demonstrates that mutation rates are male-biased in snakes (male-driven evolution), but also supports faster-Z evolution due to differential selective effects on the Z. Finally, we perform a transcriptome analysis in boa and pygmy rattlesnake to establish baseline levels of sex-biased expression in homomorphic sex chromosomes, and show that heteromorphic ZW chromosomes in rattlesnakes lack chromosome-wide dosage compensation. Our study provides the first full scale overview of the evolution of snake sex chromosomes at the genomic level, thus greatly expanding our knowledge of reptilian and vertebrate sex chromosomes

An Analysis on a Negotiation Model Based on Multiagent Systems with Symbiotic Learning and Evolution

Science.gov (United States)

Hossain, Md. Tofazzal

This study explores an evolutionary analysis on a negotiation model based on Masbiole (Multiagent Systems with Symbiotic Learning and Evolution) which has been proposed as a new methodology of Multiagent Systems (MAS) based on symbiosis in the ecosystem. In Masbiole, agents evolve in consideration of not only their own benefits and losses, but also the benefits and losses of opponent agents. To aid effective application of Masbiole, we develop a competitive negotiation model where rigorous and advanced intelligent decision-making mechanisms are required for agents to achieve solutions. A Negotiation Protocol is devised aiming at developing a set of rules for agents' behavior during evolution. Simulations use a newly developed evolutionary computing technique, called Genetic Network Programming (GNP) which has the directed graph-type gene structure that can develop and design the required intelligent mechanisms for agents. In a typical scenario, competitive negotiation solutions are reached by concessions that are usually predetermined in the conventional MAS. In this model, however, not only concession is determined automatically by symbiotic evolution (making the system intelligent, automated, and efficient) but the solution also achieves Pareto optimal automatically.

The Effect of Using Evolution Textbook Based on ICT and Metacognitive on Cognitive Competence of Biology Students at State University of Padang

Science.gov (United States)

Helendra, H.; Fadilah, M.; Arsih, F.

2018-04-01

Implementation of evolution lectures at Biology Department Faculty of Mathematics and Natural Sciences State University of Padang has been considered not optimal. The reasons are the limited availability of textbooks and students' learning attitudes. Because currently the students are very familiar with the internet and even has become a necessity, it has developed textbooks of evolution based on ICT and metacognitive. Selection of ICT based is in order to optimize the utilization of multimedia, and this is very compatible with the development of learning technology. While metacognitive based is in order to train students' learning attitudes to be able to think analysis, creative and evaluative. The aim of this study is to determine the effect of the use of evolution textbooks based on ICT and metacognitive to the cognitive competence of students of Biology Department State University of Padang. The data of this research is students' cognitive competence obtained from the implementation of effectiveness test of evolution textbook in the form of student learning outcomes. The research instrument is a learning result test designed to determine students’ cognitive competence. The subject of the study is a group of students in evolution course consisting of 33 students. Lectures are conducted through face-to-face and online lectures on Edmodo’s platform. The result of data analysis shows that there is an increase of cognitive competence of biology students after learning using ICT and metacognitive based evolution textbook, where average achievement is 77.72 with Percentage of achievement of criteria mastery is 81.25%. Therefore, it can be concluded that the evolution textbook based on ICT and metacognitive is effective in improving cognitive competence of students of Biology Department, Universitas Negeri Padang.

The Characterization Tool: A knowledge-based stem cell, differentiated cell, and tissue database with a web-based analysis front-end.

NARCIS (Netherlands)

I. Wohlers (Inken); H. Stachelscheid; J. Borstlap; K. Zeilinger; J.C. Gerlach

2009-01-01

htmlabstractIn the rapidly growing field of stem cell research, there is a need for universal databases and web-based applications that provide a common knowledge base on the characteristics of stem cells, differentiated cells, and tissues by collecting, processing, and making available diverse

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.

Epigenetic differentiation and relationship to adaptive genetic divergence in discrete populations of the violet Viola cazorlensis.

Science.gov (United States)

Herrera, Carlos M; Bazaga, Pilar

2010-08-01

*In plants, epigenetic variations based on DNA methylation are often heritable and could influence the course of evolution. Before this hypothesis can be assessed, fundamental questions about epigenetic variation remain to be addressed in a real-world context, including its magnitude, structuring within and among natural populations, and autonomy in relation to the genetic context. *Extent and patterns of cytosine methylation, and the relationship to adaptive genetic divergence between populations, were investigated for wild populations of the southern Spanish violet Viola cazorlensis (Violaceae) using the methylation-sensitive amplified polymorphism (MSAP) technique, a modification of the amplified fragment length polymorphism method (AFLP) based on the differential sensitivity of isoschizomeric restriction enzymes to site-specific cytosine methylation. *The genome of V. cazorlensis plants exhibited extensive levels of methylation, and methylation-based epigenetic variation was structured into distinct between- and within- population components. Epigenetic differentiation of populations was correlated with adaptive genetic divergence revealed by a Bayesian population-genomic analysis of AFLP data. Significant associations existed at the individual genome level between adaptive AFLP loci and the methylation state of methylation-susceptible MSAP loci. *Population-specific, divergent patterns of correlated selection on epigenetic and genetic individual variation could account for the coordinated epigenetic-genetic adaptive population differentiation revealed by this study.

The role of rotation in the evolution of massive stars losing mass

International Nuclear Information System (INIS)

Sreenivasan, S.R.; Wilson, W.J.F.

1979-01-01

The role of differential and solid body rotation in the evolution of massive stars undergoing mass loss is discussed. The implications for Of, WR, β Cephei stars and shell stars are brought out. (Auth.)

Quantum theory of open systems based on stochastic differential equations of generalized Langevin (non-Wiener) type

International Nuclear Information System (INIS)

Basharov, A. M.

2012-01-01

It is shown that the effective Hamiltonian representation, as it is formulated in author’s papers, serves as a basis for distinguishing, in a broadband environment of an open quantum system, independent noise sources that determine, in terms of the stationary quantum Wiener and Poisson processes in the Markov approximation, the effective Hamiltonian and the equation for the evolution operator of the open system and its environment. General stochastic differential equations of generalized Langevin (non-Wiener) type for the evolution operator and the kinetic equation for the density matrix of an open system are obtained, which allow one to analyze the dynamics of a wide class of localized open systems in the Markov approximation. The main distinctive features of the dynamics of open quantum systems described in this way are the stabilization of excited states with respect to collective processes and an additional frequency shift of the spectrum of the open system. As an illustration of the general approach developed, the photon dynamics in a single-mode cavity without losses on the mirrors is considered, which contains identical intracavity atoms coupled to the external vacuum electromagnetic field. For some atomic densities, the photons of the cavity mode are “locked” inside the cavity, thus exhibiting a new phenomenon of radiation trapping and non-Wiener dynamics.

Evolution of networks for body plan patterning; interplay of modularity, robustness and evolvability.

Directory of Open Access Journals (Sweden)

Kirsten H Ten Tusscher

2011-10-01

Full Text Available A major goal of evolutionary developmental biology (evo-devo is to understand how multicellular body plans of increasing complexity have evolved, and how the corresponding developmental programs are genetically encoded. It has been repeatedly argued that key to the evolution of increased body plan complexity is the modularity of the underlying developmental gene regulatory networks (GRNs. This modularity is considered essential for network robustness and evolvability. In our opinion, these ideas, appealing as they may sound, have not been sufficiently tested. Here we use computer simulations to study the evolution of GRNs' underlying body plan patterning. We select for body plan segmentation and differentiation, as these are considered to be major innovations in metazoan evolution. To allow modular networks to evolve, we independently select for segmentation and differentiation. We study both the occurrence and relation of robustness, evolvability and modularity of evolved networks. Interestingly, we observed two distinct evolutionary strategies to evolve a segmented, differentiated body plan. In the first strategy, first segments and then differentiation domains evolve (SF strategy. In the second scenario segments and domains evolve simultaneously (SS strategy. We demonstrate that under indirect selection for robustness the SF strategy becomes dominant. In addition, as a byproduct of this larger robustness, the SF strategy is also more evolvable. Finally, using a combined functional and architectural approach, we determine network modularity. We find that while SS networks generate segments and domains in an integrated manner, SF networks use largely independent modules to produce segments and domains. Surprisingly, we find that widely used, purely architectural methods for determining network modularity completely fail to establish this higher modularity of SF networks. Finally, we observe that, as a free side effect of evolving segmentation

Geometrical nuclear diagnosis and total paths of cervical cell evolution from normality to cancer

Directory of Open Access Journals (Sweden)

Javier Oswaldo Rodríguez Velásquez

2015-01-01

Full Text Available Background: The diagnosis of cervix cytology has problems of inter-observer reproducibility. Methodologies based on fractal geometry objectively differentiated normal, low-grade squamous intraepithelial lesion (L-SIL and high-grade squamous intraepithelial lesion (H-SIL states. Aims: The aim was to develop a mathematical-physical diagnosis and a theoretical generalization of the evolution paths of cervical cells from normal to carcinoma based on their occupation in the box-counting space. Subjects and Methods: Overlaying a grid of 8x8 pixels, the a number of squares occupying the nucleus surface and cytoplasm of 5 normal cells, 5 ASCUS, 5 L-SIL and 5 H-SIL were evaluated, as well as the ratio C/N, establishing differences between states. Sensitivity, specificity, negative likelihood ratio, and Kappa coefficient over the gold standard were calculated. Also was developed a generalization of all possible paths from normality to carcinoma. Results: The occupancy spaces of the nuclear surface allow differentiating normal L-SIL and H-SIL thus avoiding the indeterminacy of ASCUS cells. Compared to the Gold Standard, this method has sensitivity and specificity of 100%, negative likelihood ratio of 0, and Kappa coefficient of 1. 62,900 possible routes of evolution were determined between normal and H-SIL, states, based on the structural basis of the cells. Conclusions: it was obtained an objective and reproducible diagnostic methodology of the development of preneoplastic and neoplastic cervical cells for clinical application. Additionally were developed all possible paths of preneoplastic cellular alteration to carcinoma which facilitates the tracking of patients over time to clinical level, warning of alterations that lead to malignancy, based on the spatial occupation measurements of the nucleus in fractal space regardless of causes or risk factors.

A Topology Evolution Model Based on Revised PageRank Algorithm and Node Importance for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Xiaogang Qi

2015-01-01

Full Text Available Wireless sensor network (WSN is a classical self-organizing communication network, and its topology evolution currently becomes one of the attractive issues in this research field. Accordingly, the problem is divided into two subproblems: one is to design a new preferential attachment method and the other is to analyze the dynamics of the network topology evolution. To solve the first subproblem, a revised PageRank algorithm, called Con-rank, is proposed to evaluate the node importance upon the existing node contraction, and then a novel preferential attachment is designed based on the node importance calculated by the proposed Con-rank algorithm. To solve the second one, we firstly analyze the network topology evolution dynamics in a theoretical way and then simulate the evolution process. Theoretical analysis proves that the network topology evolution of our model agrees with power-law distribution, and simulation results are well consistent with our conclusions obtained from the theoretical analysis and simultaneously show that our topology evolution model is superior to the classic BA model in the average path length and the clustering coefficient, and the network topology is more robust and can tolerate the random attacks.

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.

Repeated evolution of soldier sub-castes suggests parasitism drives social complexity in stingless bees.

Science.gov (United States)

Grüter, Christoph; Segers, Francisca H I D; Menezes, Cristiano; Vollet-Neto, Ayrton; Falcón, Tiago; von Zuben, Lucas; Bitondi, Márcia M G; Nascimento, Fabio S; Almeida, Eduardo A B

2017-02-23

The differentiation of workers into morphological castes represents an important evolutionary innovation that is thought to improve division of labor in insect societies. Given the potential benefits of task-related worker differentiation, it is puzzling that physical worker castes, such as soldiers, are extremely rare in social bees and absent in wasps. Following the recent discovery of soldiers in a stingless bee, we studied the occurrence of worker differentiation in 28 stingless bee species from Brazil and found that several species have specialized soldiers for colony defence. Our results reveal that worker differentiation evolved repeatedly during the last ~ 25 million years and coincided with the emergence of parasitic robber bees, a major threat to many stingless bee species. Furthermore, our data suggest that these robbers are a driving force behind the evolution of worker differentiation as targets of robber bees are four times more likely to have nest guards of increased size than non-targets. These findings reveal unexpected diversity in the social organization of stingless bees.Although common in ants and termites, worker differentiation into physical castes is rare in social bees and unknown in wasps. Here, Grüter and colleagues find a guard caste in ten species of stingless bees and show that the evolution of the guard caste is associated with parasitization by robber bees.

A stochastic differential equation analysis of cerebrospinal fluid dynamics.