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.

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.

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.

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

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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.

Application of differential evolution algorithm on self-potential data.

Science.gov (United States)

Li, Xiangtao; Yin, Minghao

2012-01-01

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

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.

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.

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.

Solving SAT Problem Based on Hybrid Differential Evolution Algorithm

Science.gov (United States)

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

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

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

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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.

Battery parameterisation based on differential evolution via a boundary evolution strategy

DEFF Research Database (Denmark)

Yang, Guangya

2013-01-01

the advances of evolutionary algorithms (EAs). Differential evolution (DE) is selected and modified to parameterise an equivalent circuit model of lithium-ion batteries. A boundary evolution strategy (BES) is developed and incorporated into the DE to update the parameter boundaries during the parameterisation......, as the equivalent circuit model is an abstract map of the battery electric characteristics, the determination of the possible ranges of parameters can be a challenging task. In this paper, an efficient yet easy to implement method is proposed to parameterise the equivalent circuit model of batteries utilising...

The Cellular Differential Evolution Based on Chaotic Local Search

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Qingfeng Ding

2015-01-01

Full Text Available To avoid immature convergence and tune the selection pressure in the differential evolution (DE algorithm, a new differential evolution algorithm based on cellular automata and chaotic local search (CLS or ccDE is proposed. To balance the exploration and exploitation tradeoff of differential evolution, the interaction among individuals is limited in cellular neighbors instead of controlling parameters in the canonical DE. To improve the optimizing performance of DE, the CLS helps by exploring a large region to avoid immature convergence in the early evolutionary stage and exploiting a small region to refine the final solutions in the later evolutionary stage. What is more, to improve the convergence characteristics and maintain the population diversity, the binomial crossover operator in the canonical DE may be instead by the orthogonal crossover operator without crossover rate. The performance of ccDE is widely evaluated on a set of 14 bound constrained numerical optimization problems compared with the canonical DE and several DE variants. The simulation results show that ccDE has better performances in terms of convergence rate and solution accuracy than other optimizers.

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.

Harmony Search Based Parameter Ensemble Adaptation for Differential Evolution

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Rammohan Mallipeddi

2013-01-01

Full Text Available In differential evolution (DE algorithm, depending on the characteristics of the problem at hand and the available computational resources, different strategies combined with a different set of parameters may be effective. In addition, a single, well-tuned combination of strategies and parameters may not guarantee optimal performance because different strategies combined with different parameter settings can be appropriate during different stages of the evolution. Therefore, various adaptive/self-adaptive techniques have been proposed to adapt the DE strategies and parameters during the course of evolution. In this paper, we propose a new parameter adaptation technique for DE based on ensemble approach and harmony search algorithm (HS. In the proposed method, an ensemble of parameters is randomly sampled which form the initial harmony memory. The parameter ensemble evolves during the course of the optimization process by HS algorithm. Each parameter combination in the harmony memory is evaluated by testing them on the DE population. The performance of the proposed adaptation method is evaluated using two recently proposed strategies (DE/current-to-pbest/bin and DE/current-to-gr_best/bin as basic DE frameworks. Numerical results demonstrate the effectiveness of the proposed adaptation technique compared to the state-of-the-art DE based algorithms on a set of challenging test problems (CEC 2005.

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.

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

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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.

An Enhanced Differential Evolution with Elite Chaotic Local Search

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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.

Cloud computing task scheduling strategy based on improved differential evolution algorithm

Science.gov (United States)

Ge, Junwei; He, Qian; Fang, Yiqiu

2017-04-01

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

Hybridizing Differential Evolution with a Genetic Algorithm for Color Image Segmentation

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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.

Student Teachers' Approaches to Teaching Biological Evolution

Science.gov (United States)

Borgerding, Lisa A.; Klein, Vanessa A.; Ghosh, Rajlakshmi; Eibel, Albert

2015-06-01

Evolution is fundamental to biology and scientific literacy, but teaching high school evolution is often difficult. Evolution teachers face several challenges including limited content knowledge, personal conflicts with evolution, expectations of resistance, concerns about students' conflicts with religion, and curricular constraints. Evolution teaching can be particularly challenging for student teachers who are just beginning to gain pedagogical knowledge and pedagogical content knowledge related to evolution teaching and who seek approval from university supervisors and cooperating teachers. Science teacher educators need to know how to best support student teachers as they broach the sometimes daunting task of teaching evolution within student teaching placements. This multiple case study report documents how three student teachers approached evolution instruction and what influenced their approaches. Data sources included student teacher interviews, field note observations for 4-5 days of evolution instruction, and evolution instructional artifacts. Data were analyzed using grounded theory approaches to develop individual cases and a cross-case analysis. Seven influences (state exams and standards, cooperating teacher, ideas about teaching and learning, concerns about evolution controversy, personal commitment to evolution, knowledge and preparation for teaching evolution, and own evolution learning experiences) were identified and compared across cases. Implications for science teacher preparation and future research are provided.

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.

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

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.

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.

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

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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.

An Orthogonal Learning Differential Evolution Algorithm for Remote Sensing Image Registration

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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.

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

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

International Nuclear Information System (INIS)

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

2015-01-01

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

Differential evolution based method for total transfer capability ...

African Journals Online (AJOL)

The application of Differential Evolution (DE) to compute the Total Transfer Capability (TTC) in deregulated market is proposed in this paper. The objective is to maximize a specific point-to-point power transaction without violating system constraints using DE. This algorithm is based on full ac optimal power flow solution to ...

Parameter Estimation of Damped Compound Pendulum Differential Evolution Algorithm

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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.

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.

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.

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

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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.

A stochastic approach to chemical evolution

International Nuclear Information System (INIS)

Copi, C.J.

1997-01-01

Observations of elemental abundances in the Galaxy have repeatedly shown an intrinsic scatter as a function of time and metallicity. The standard approach to chemical evolution does not attempt to address this scatter in abundances since only the mean evolution is followed. In this work, the scatter is addressed via a stochastic approach to solving chemical evolution models. Three simple chemical evolution scenarios are studied using this stochastic approach: a closed box model, an infall model, and an outflow model. These models are solved for the solar neighborhood in a Monte Carlo fashion. The evolutionary history of one particular region is determined randomly based on the star formation rate and the initial mass function. Following the evolution in an ensemble of such regions leads to the predicted spread in abundances expected, based solely on different evolutionary histories of otherwise identical regions. In this work, 13 isotopes are followed, including the light elements, the CNO elements, a few α-elements, and iron. It is found that the predicted spread in abundances for a 10 5 M circle-dot region is in good agreement with observations for the α-elements. For CN, the agreement is not as good, perhaps indicating the need for more physics input for low-mass stellar evolution. Similarly for the light elements, the predicted scatter is quite small, which is in contradiction to the observations of 3 He in HII regions. The models are tuned for the solar neighborhood so that good agreement with HII regions is not expected. This has important implications for low-mass stellar evolution and on using chemical evolution to determine the primordial light-element abundances in order to test big bang nucleosynthesis. copyright 1997 The American Astronomical Society

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 ...

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-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.

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.

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.

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.

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.

On geometric approach to Lie symmetries of differential-difference equations

International Nuclear Information System (INIS)

Li Hongjing; Wang Dengshan; Wang Shikun; Wu Ke; Zhao Weizhong

2008-01-01

Based upon Cartan's geometric formulation of differential equations, Harrison and Estabrook proposed a geometric approach for the symmetries of differential equations. In this Letter, we extend Harrison and Estabrook's approach to analyze the symmetries of differential-difference equations. The discrete exterior differential technique is applied in our approach. The Lie symmetry of (2+1)-dimensional Toda equation is investigated by means of our approach

Differential equations a dynamical systems approach ordinary differential equations

CERN Document Server

Hubbard, John H

1991-01-01

This is a corrected third printing of the first part of the text Differential Equations: A Dynamical Systems Approach written by John Hubbard and Beverly West. The authors' main emphasis in this book is on ordinary differential equations. The book is most appropriate for upper level undergraduate and graduate students in the fields of mathematics, engineering, and applied mathematics, as well as the life sciences, physics and economics. Traditional courses on differential equations focus on techniques leading to solutions. Yet most differential equations do not admit solutions which can be written in elementary terms. The authors have taken the view that a differential equations defines functions; the object of the theory is to understand the behavior of these functions. The tools the authors use include qualitative and numerical methods besides the traditional analytic methods. The companion software, MacMath, is designed to bring these notions to life.

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.

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.

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

Science.gov (United States)

Hyyti, Janne; Escoto, Esmerando; Steinmeyer, Günter

2017-10-01

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

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.

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.

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.

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.

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

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...

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.

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...

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.

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.

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

Science.gov (United States)

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

2018-01-01

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

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 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.

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

Science.gov (United States)

Gao, Xiaohui; Liu, Yongguang

2018-01-01

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

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...

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

Differentiating Performance Approach Goals and Their Unique Effects

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Edwards, Ordene V.

2014-01-01

The study differentiates between two types of performance approach goals (competence demonstration performance approach goal and normative performance approach goal) by examining their unique effects on self-efficacy, interest, and fear of failure. Seventy-nine students completed questionnaires that measure performance approach goals,…

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

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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.

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.

Teaching Modeling with Partial Differential Equations: Several Successful Approaches

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Myers, Joseph; Trubatch, David; Winkel, Brian

2008-01-01

We discuss the introduction and teaching of partial differential equations (heat and wave equations) via modeling physical phenomena, using a new approach that encompasses constructing difference equations and implementing these in a spreadsheet, numerically solving the partial differential equations using the numerical differential equation…

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

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

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.

Perturbative evolution: a different approach at small x

Energy Technology Data Exchange (ETDEWEB)

Donnachie, A. [University of Manchester, School of Physics and Astromony, Manchester (United Kingdom); Landshoff, P.V. [DAMTP, Cambridge University, Cambridge (United Kingdom)

2017-08-15

We propose an approach to DGLAP evolution at small x that circumvents the usual problem that a perturbation expansion is not valid there. The data for the charm structure function are important to motivate the method, and it describes them much more successfully than the conventional approach. (orig.)

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

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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

Optimasi Peletakan Base Transceiver Station Di Kabupaten Mojokerto Menggunakan Algoritma Differential Evolution

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Ahadi Arif Nugraha

2015-03-01

Full Text Available Salah satu aspek penting dalam perencanaan infrastruktur jaringan seluler adalah Base Transceiver Station (BTS yang merupakan sebuah pemancar dan penerima sinyal telephone seluler. Di satu sisi, peningkatan jumlah menara memang akan mendukung tercapainya pemenuhan kebutuhan masyarakat terhadap layanan telekomunikasi. Namun di sisi lain, penempatan menara yang  tanpa perencanaan serta koordinasi yang tepat akan menimbulkan jumlah menara yang berlebih sehingga dapat mengganggu estetika lingkungan, tata ruang suatu wilayah, dan radiasi gelombang radio yang tidak terkontrol sehingga sangat mengganggu. Berdasarkan permasalahan diatas, maka dapat diselesaikan dengan cara menyusun suatu master plan yang lengkap dan rinci tentang penataan lokasi menara di Kabupaten Mojokerto untuk lima tahun mendatang. Penataan lokasi menara dilakukan dengan menggunakan algoritma Differential Evolution (DE untuk menemukan solusi penataan menara yang baik berdasarkan luas cakupan area sel yang dihasilkan, kemudian menggunakan software MapInfo sebagai media visualisasi peta lokasi penempatan menara telekomunikasi. Dalam perancangan menara BTS tahun 2019, Kabupaten Mojokerto membutuhkan 106 menara BTS 2G dan 36 menara BTS 3G. Penempatan menara BTS 2G dan 3G menggunakan algoritma differential evolution mampu mengoptimalkan 2,94% dari luas wilayah Kabupaten Mojokerto

Numerical approaches to time evolution of complex quantum systems

International Nuclear Information System (INIS)

Fehske, Holger; Schleede, Jens; Schubert, Gerald; Wellein, Gerhard; Filinov, Vladimir S.; Bishop, Alan R.

2009-01-01

We examine several numerical techniques for the calculation of the dynamics of quantum systems. In particular, we single out an iterative method which is based on expanding the time evolution operator into a finite series of Chebyshev polynomials. The Chebyshev approach benefits from two advantages over the standard time-integration Crank-Nicholson scheme: speedup and efficiency. Potential competitors are semiclassical methods such as the Wigner-Moyal or quantum tomographic approaches. We outline the basic concepts of these techniques and benchmark their performance against the Chebyshev approach by monitoring the time evolution of a Gaussian wave packet in restricted one-dimensional (1D) geometries. Thereby the focus is on tunnelling processes and the motion in anharmonic potentials. Finally we apply the prominent Chebyshev technique to two highly non-trivial problems of current interest: (i) the injection of a particle in a disordered 2D graphene nanoribbon and (ii) the spatiotemporal evolution of polaron states in finite quantum systems. Here, depending on the disorder/electron-phonon coupling strength and the device dimensions, we observe transmission or localisation of the matter wave.

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.

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

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.

Structural Approaches to Sequence Evolution Molecules, Networks, Populations

CERN Document Server

Bastolla, Ugo; Roman, H. Eduardo; Vendruscolo, Michele

2007-01-01

Structural requirements constrain the evolution of biological entities at all levels, from macromolecules to their networks, right up to populations of biological organisms. Classical models of molecular evolution, however, are focused at the level of the symbols - the biological sequence - rather than that of their resulting structure. Now recent advances in understanding the thermodynamics of macromolecules, the topological properties of gene networks, the organization and mutation capabilities of genomes, and the structure of populations make it possible to incorporate these key elements into a broader and deeply interdisciplinary view of molecular evolution. This book gives an account of such a new approach, through clear tutorial contributions by leading scientists specializing in the different fields involved.

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.

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.

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

Enhanced lipase recovery through RSM integrated differential evolutionary approach from the fermented biomass

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Vijay Kumar Garlapati

2013-10-01

Full Text Available The aim of this work was to apply a modeling integrated optimisation approach for a complex, highly nonlinear system for an extracellular lipase extraction process. The model was developed using mutation, crossover and selection variables of Differential Evolution (DE based on central composite design of Response Surface Methodology. The experimentally validated model was optimized by DE, a robust evolutionary optimization tool. A maximum lipase activity of 134.13 U/gds (more than 36.28 U/gds compared to one variable at a time approach was observed with the DE-stated optimum values of 25.01% dimethyl sulfoxide concentration, 40 mM buffer, 128.52 min soaking time and 35ºC with the DE control parameters, namely number of population, generations, crossover operator and scaling factor as 20, 50, 0.5 and 0.25, respectively. The use of DE approach improved the optimization capability and decision speed, resulting in an improved yield of 36.28 U/gds compared to the one variable at a time approach for the extracellular lipase activity under the non-optimized conditions. The developed mathematical model and optimization were generic in nature, which seemed to be useful for the scale-up studies of maximum recovery of lipase from the fermented biomass.

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.

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.

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.

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.

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.

Design of Test Wrapper Scan Chain Based on Differential Evolution

Directory of Open Access Journals (Sweden)

Aijun Zhu

2013-08-01

Full Text Available Integrated Circuit has entered the era of design of the IP-based SoC (System on Chip, which makes the IP core reuse become a key issue. SoC test wrapper design for scan chain is a NP Hard problem, we propose an algorithm based on Differential Evolution (DE to design wrapper scan chain. Through group’s mutation, crossover and selection operations, the design of test wrapper scan chain is achieved. Experimental verification is carried out according to the international standard benchmark ITC’02. The results show that the algorithm can obtain shorter longest wrapper scan chains, compared with other algorithms.

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.

A differential transformation approach for solving functional differential equations with multiple delays

Science.gov (United States)

Rebenda, Josef; Šmarda, Zdeněk

2017-07-01

In the paper an efficient semi-analytical approach based on the method of steps and the differential transformation is proposed for numerical approximation of solutions of functional differential models of delayed and neutral type on a finite interval of arbitrary length, including models with several constant delays. Algorithms for both commensurate and non-commensurate delays are described, applications are shown in examples. Validity and efficiency of the presented algorithms is compared with the variational iteration method, the Adomian decomposition method and the polynomial least squares method numerically. Matlab package DDE23 is used to produce reference numerical values.

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)

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

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.

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.

Spatial Economics: The Evolution of Approaches and Methodology

Directory of Open Access Journals (Sweden)

Minakir P. A.

2010-06-01

Full Text Available The evolution of theoretical principles and approaches to the study of spatial organization of the economy is set forth. The changes in the content of the category «economic region» are analyzed. A comparative assessment is given of theoretical approaches to studying spatial aspects of the economy. The limited character of theoretical and applied regional economic tools in studying spatial organization and spatial interactions between economic agents of the modern economy is shown

Toward Analytic Solution of Nonlinear Differential Difference Equations via Extended Sensitivity Approach

International Nuclear Information System (INIS)

Darmani, G.; Setayeshi, S.; Ramezanpour, H.

2012-01-01

In this paper an efficient computational method based on extending the sensitivity approach (SA) is proposed to find an analytic exact solution of nonlinear differential difference equations. In this manner we avoid solving the nonlinear problem directly. By extension of sensitivity approach for differential difference equations (DDEs), the nonlinear original problem is transformed into infinite linear differential difference equations, which should be solved in a recursive manner. Then the exact solution is determined in the form of infinite terms series and by intercepting series an approximate solution is obtained. Numerical examples are employed to show the effectiveness of the proposed approach. (general)

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.

Symmetries of stochastic differential equations: A geometric approach

Energy Technology Data Exchange (ETDEWEB)

De Vecchi, Francesco C., E-mail: francesco.devecchi@unimi.it; Ugolini, Stefania, E-mail: stefania.ugolini@unimi.it [Dipartimento di Matematica, Università degli Studi di Milano, via Saldini 50, Milano (Italy); Morando, Paola, E-mail: paola.morando@unimi.it [DISAA, Università degli Studi di Milano, via Celoria 2, Milano (Italy)

2016-06-15

A new notion of stochastic transformation is proposed and applied to the study of both weak and strong symmetries of stochastic differential equations (SDEs). The correspondence between an algebra of weak symmetries for a given SDE and an algebra of strong symmetries for a modified SDE is proved under suitable regularity assumptions. This general approach is applied to a stochastic version of a two dimensional symmetric ordinary differential equation and to the case of two dimensional Brownian motion.

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.

Differential Evolution between Monotocous and Polytocous Species

Directory of Open Access Journals (Sweden)

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.

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

OpenAIRE

Hyyti, Janne; Escoto, Esmerando; Steinmeyer, Günter

2017-01-01

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

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

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

An ensemble approach to the evolution of complex systems

Indian Academy of Sciences (India)

2014-03-15

Mar 15, 2014 ... [Arpağ G and Erzan A 2014 An ensemble approach to the evolution of complex systems. J. Biosci. ... almost nothing about all the different ways in which your ...... energy cost to the organism of the maintenance, replication,.

SEAS: A simulated evolution approach for analog circuit synthesis

NARCIS (Netherlands)

Ning, Zhen-Qiu; Ning, Zhen-Qiu; Mouthaan, A.J.; Wallinga, Hans

1991-01-01

The authors present a simulated evolution approach for analog circuit synthesis based on an analogy with the natural selection process in biological environments and on the iterative improvements in solving engineering problems. A prototype framework based on this idea, called SEAS, has been

Modification of species-based differential evolution for multimodal optimization

Science.gov (United States)

Idrus, Said Iskandar Al; Syahputra, Hermawan; Firdaus, Muliawan

2015-12-01

At this time optimization has an important role in various fields as well as between other operational research, industry, finance and management. Optimization problem is the problem of maximizing or minimizing a function of one variable or many variables, which include unimodal and multimodal functions. Differential Evolution (DE), is a random search technique using vectors as an alternative solution in the search for the optimum. To localize all local maximum and minimum on multimodal function, this function can be divided into several domain of fitness using niching method. Species-based niching method is one of method that build sub-populations or species in the domain functions. This paper describes the modification of species-based previously to reduce the computational complexity and run more efficiently. The results of the test functions show species-based modifications able to locate all the local optima in once run the program.

EVOLUTION OF THEORETICAL APPROACHES TO THE DEFINITION OF THE CATEGORY “PERSONNEL POTENTIAL”

Directory of Open Access Journals (Sweden)

Аlexandra Deshchenko

2016-02-01

Full Text Available The article describes the evolution of theoretical approaches to definition of the category «personnel potential» based on the analysis of approaches to definition of the conceptual apparatus of labor Economics, including such categories as: labor force, labor resources, labor potential, human resources, human capital, human capital different authors. The analysis of the evolution of the terms in accordance with the stages of development of a society.

Integro-differential equation approach extended to larger nuclei

International Nuclear Information System (INIS)

Adam, R.M.; Sofianos, S.A.; Fiedeldey, H.; Fabre de la Ripelle, M.

1992-01-01

We extend the integro-differential equation approach (IDEA) from few-nucleon to closed-shell and closed-subshell nuclei and outline the analytical methods required for the calculation of the density functions, which enter into the integro-differential equations. These contain all the physics for a system of fermions associated with the Pauli principle. In order to test the accuracy of the IDEA comparisons are made of the binding energies of 4 He, 12 C and 16 O obtained with effective potentials using the hypercentral approximation (HCA) providing a variational solution without correlations, the IDEA which fully includes the two-body correlations, the S-states integro-differential equation (SIDE) valid for potentials operating only on pairs in the S-state and those calculated by several variational or perturbative methods in the literature. (author)

A neuro approach to solve fuzzy Riccati differential equations

Energy Technology Data Exchange (ETDEWEB)

Shahrir, Mohammad Shazri, E-mail: mshazri@gmail.com [InstitutSainsMatematik, Universiti Malaya 50603 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur (Malaysia); Telekom Malaysia, R& D TM Innovation Centre, LingkaranTeknokrat Timur, 63000 Cyberjaya, Selangor (Malaysia); Kumaresan, N., E-mail: drnk2008@gmail.com; Kamali, M. Z. M.; Ratnavelu, Kurunathan [InstitutSainsMatematik, Universiti Malaya 50603 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur (Malaysia)

2015-10-22

There are many applications of optimal control theory especially in the area of control systems in engineering. In this paper, fuzzy quadratic Riccati differential equation is estimated using neural networks (NN). Previous works have shown reliable results using Runge-Kutta 4th order (RK4). The solution can be achieved by solving the 1st Order Non-linear Differential Equation (ODE) that is found commonly in Riccati differential equation. Research has shown improved results relatively to the RK4 method. It can be said that NN approach shows promising results with the advantage of continuous estimation and improved accuracy that can be produced over RK4.

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.

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.

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.

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.

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

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.

Reconsidering harmonic and anharmonic coherent states: Partial differential equations approach

Energy Technology Data Exchange (ETDEWEB)

Toutounji, Mohamad, E-mail: Mtoutounji@uaeu.ac.ae

2015-02-15

This article presents a new approach to dealing with time dependent quantities such as autocorrelation function of harmonic and anharmonic systems using coherent states and partial differential equations. The approach that is normally used to evaluate dynamical quantities involves formidable operator algebra. That operator algebra becomes insurmountable when employing Morse oscillator coherent states. This problem becomes even more complicated in case of Morse oscillator as it tends to exhibit divergent dynamics. This approach employs linear partial differential equations, some of which may be solved exactly and analytically, thereby avoiding the cumbersome noncommutative algebra required to manipulate coherent states of Morse oscillator. Additionally, the arising integrals while using the herein presented method feature stability and high numerical efficiency. The correctness, applicability, and utility of the above approach are tested by reproducing the partition and optical autocorrelation function of the harmonic oscillator. A closed-form expression for the equilibrium canonical partition function of the Morse oscillator is derived using its coherent states and partial differential equations. Also, a nonequilibrium autocorrelation function expression for weak electron–phonon coupling in condensed systems is derived for displaced Morse oscillator in electronic state. Finally, the utility of the method is demonstrated through further simplifying the Morse oscillator partition function or autocorrelation function expressions reported by other researchers in unevaluated form of second-order derivative exponential. Comparison with exact dynamics shows identical results.

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)

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.

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.

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

Stochastic Computational Approach for Complex Nonlinear Ordinary Differential Equations

International Nuclear Information System (INIS)

Khan, Junaid Ali; Raja, Muhammad Asif Zahoor; Qureshi, Ijaz Mansoor

2011-01-01

We present an evolutionary computational approach for the solution of nonlinear ordinary differential equations (NLODEs). The mathematical modeling is performed by a feed-forward artificial neural network that defines an unsupervised error. The training of these networks is achieved by a hybrid intelligent algorithm, a combination of global search with genetic algorithm and local search by pattern search technique. The applicability of this approach ranges from single order NLODEs, to systems of coupled differential equations. We illustrate the method by solving a variety of model problems and present comparisons with solutions obtained by exact methods and classical numerical methods. The solution is provided on a continuous finite time interval unlike the other numerical techniques with comparable accuracy. With the advent of neuroprocessors and digital signal processors the method becomes particularly interesting due to the expected essential gains in the execution speed. (general)

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.

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)

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.)

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.

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

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.

Influence of bone marrow-derived mesenchymal stem cells pre-implantation differentiation approach on periodontal regeneration in vivo.

Science.gov (United States)

Cai, Xinjie; Yang, Fang; Yan, Xiangzhen; Yang, Wanxun; Yu, Na; Oortgiesen, Daniel A W; Wang, Yining; Jansen, John A; Walboomers, X Frank

2015-04-01

The implantation of bone marrow-derived mesenchymal stem cells (MSCs) has previously been shown successful to achieve periodontal regeneration. However, the preferred pre-implantation differentiation strategy (e.g. maintenance of stemness, osteogenic or chondrogenic induction) to obtain optimal periodontal regeneration is still unknown. This in vivo study explored which differentiation approach is most suitable for periodontal regeneration. Mesenchymal stem cells were obtained from Fischer rats and seeded onto poly(lactic-co-glycolic acid)/poly(ɛ-caprolactone) electrospun scaffolds, and then pre-cultured under different in vitro conditions: (i) retention of multilineage differentiation potential; (ii) osteogenic differentiation approach; and (iii) chondrogenic differentiation approach. Subsequently, the cell-scaffold constructs were implanted into experimental periodontal defects of Fischer rats, with empty scaffolds as controls. After 6 weeks of implantation, histomorphometrical analyses were applied to evaluate the regenerated periodontal tissues. The chondrogenic differentiation approach showed regeneration of alveolar bone and ligament tissues. The retention of multilineage differentiation potential supported only ligament regeneration, while the osteogenic differentiation approach boosted alveolar bone regeneration. Chondrogenic differentiation of MSCs before implantation is a useful strategy for regeneration of alveolar bone and periodontal ligament, in the currently used rat model. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

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.

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....

A structuralist approach in the study of evolution and classification

NARCIS (Netherlands)

Hammen, van der L.

1985-01-01

A survey is given of structuralism as a method that can be applied in the study of evolution and classification. The results of a structuralist approach are illustrated by examples from the laws underlying numerical changes, from the laws underlying changes in the chelicerate life-cycle, and from

Review of differentiated approaches to antiretroviral therapy distribution.

Science.gov (United States)

Davis, Nicole; Kanagat, Natasha; Sharer, Melissa; Eagan, Sabrina; Pearson, Jennifer; Amanyeiwe, Ugochukwu Ugo

2018-02-22

In response to global trends of maximizing the number of patients receiving antiretroviral therapy (ART), this review summarizes literature describing differentiated models of ART distribution at facility and community levels in order to highlight promising strategies and identify evidence gaps. Databases and gray literature were searched, yielding thirteen final articles on differentiated ART distribution models supporting stable adult patients. Of these, seven articles focused on distribution at facility level and six at community level. Findings suggest that differentiated models of ART distribution contribute to higher retention, lower attrition, and less loss to follow-up (LTFU). These models also reduced patient wait time, travel costs, and time lost from work for drug pick-up. Facility- and community-level ART distribution models have the potential to extend treatment availability, enable improved access and adherence among people living with HIV (PLHIV), and facilitate retention in treatment and care. Gaps remain in understanding the desirability of these models for PLHIV, and the need for more information the negative and positive impacts of stigma, and identifying models to reach traditionally marginalized groups such as key populations and youth. Replicating differentiated care so efforts can reach more PLHIV will be critical to scaling these approaches across varying contexts.

Constructing HVS-Based Optimal Substitution Matrix Using Enhanced Differential Evolution

Directory of Open Access Journals (Sweden)

Shu-Fen Tu

2013-01-01

Full Text Available Least significant bit (LSB substitution is a method of information hiding. The secret message is embedded into the last k bits of a cover-image in order to evade the notice of hackers. The security and stego-image quality are two main limitations of the LSB substitution method. Therefore, some researchers have proposed an LSB substitution matrix to address these two issues. Finding the optimal LSB substitution matrix can be conceptualized as a problem of combinatorial optimization. In this paper, we adopt a different heuristic method based on other researchers’ method, called enhanced differential evolution (EDE, to construct an optimal LSB substitution matrix. Differing from other researchers, we adopt an HVS-based measurement as a fitness function and embed the secret by modifying the pixel to a closest value rather than simply substituting the LSBs. Our scheme extracts the secret by modular operations as simple LSB substitution does. The experimental results show that the proposed embedding algorithm indeed improves imperceptibility of stego-images substantially.

Analytical approach for the Floquet theory of delay differential equations.

Science.gov (United States)

Simmendinger, C; Wunderlin, A; Pelster, A

1999-05-01

We present an analytical approach to deal with nonlinear delay differential equations close to instabilities of time periodic reference states. To this end we start with approximately determining such reference states by extending the Poincaré-Lindstedt and the Shohat expansions, which were originally developed for ordinary differential equations. Then we systematically elaborate a linear stability analysis around a time periodic reference state. This allows us to approximately calculate the Floquet eigenvalues and their corresponding eigensolutions by using matrix valued continued fractions.

An enhanced reliability-oriented workforce planning model for process industry using combined fuzzy goal programming and differential evolution approach

Science.gov (United States)

Ighravwe, D. E.; Oke, S. A.; Adebiyi, K. A.

2018-03-01

This paper draws on the "human reliability" concept as a structure for gaining insight into the maintenance workforce assessment in a process industry. Human reliability hinges on developing the reliability of humans to a threshold that guides the maintenance workforce to execute accurate decisions within the limits of resources and time allocations. This concept offers a worthwhile point of deviation to encompass three elegant adjustments to literature model in terms of maintenance time, workforce performance and return-on-workforce investments. These fully explain the results of our influence. The presented structure breaks new grounds in maintenance workforce theory and practice from a number of perspectives. First, we have successfully implemented fuzzy goal programming (FGP) and differential evolution (DE) techniques for the solution of optimisation problem in maintenance of a process plant for the first time. The results obtained in this work showed better quality of solution from the DE algorithm compared with those of genetic algorithm and particle swarm optimisation algorithm, thus expressing superiority of the proposed procedure over them. Second, the analytical discourse, which was framed on stochastic theory, focusing on specific application to a process plant in Nigeria is a novelty. The work provides more insights into maintenance workforce planning during overhaul rework and overtime maintenance activities in manufacturing systems and demonstrated capacity in generating substantially helpful information for practice.

Piecewise-linear and bilinear approaches to nonlinear differential equations approximation problem of computational structural mechanics

OpenAIRE

Leibov Roman

2017-01-01

This paper presents a bilinear approach to nonlinear differential equations system approximation problem. Sometimes the nonlinear differential equations right-hand sides linearization is extremely difficult or even impossible. Then piecewise-linear approximation of nonlinear differential equations can be used. The bilinear differential equations allow to improve piecewise-linear differential equations behavior and reduce errors on the border of different linear differential equations systems ...

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.

Emotional and Spiritual Quotient Approach Improve Biology Education Students’ Acceptance of Evolution Theory

Science.gov (United States)

Darussyamsu, R.; Fadilah, M.; Putri, D. H.

2018-04-01

Emotional and spiritual aspect is one of main factors that influence students’ acceptance of a theory. This study aim to measure university students’ acceptance of evolution by learns evolution using emotional and spiritual quotient (ESQ) approach. This is a quasi-experimental research using one shot case study design with the subject 36 biology educational students at Biology Department, Faculty of Mathematics and Natural Science, Universitas Negeri Padang. Data collected using the MATE instrument by Rutledge and Warden (2000) after the students learn evolution for eight meetings since January until March 2017. The result showed that by learning evolution theory combine with ESQ aspects increase students acceptance from very low become moderate acceptance. It concluded that ESQ aspects can improve students’ acceptance of evolution. Any criteria depend on it are discussed.

R&D, patents and innovation: a differential game approach

NARCIS (Netherlands)

Wang, H.-M.

2016-01-01

A patent race is a technological competition among firms and the firm making a first-hand innovation takes advantages of patenting. Firms strategically invest in R&D and produce knowledge in order to innovate. Instead of growing model of R&D, I use a differential game approach to investigate firms

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 ...

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

Pointing and the Evolution of Language: An Applied Evolutionary Epistemological Approach

Directory of Open Access Journals (Sweden)

Nathalie Gontier

2013-07-01

Full Text Available Numerous evolutionary linguists have indicated that human pointing behaviour might be associated with the evolution of language. At an ontogenetic level, and in normal individuals, pointing develops spontaneously and the onset of human pointing precedes as well as facilitates phases in speech and language development. Phylogenetically, pointing behaviour might have preceded and facilitated the evolutionary origin of both gestural and vocal language. Contrary to wild non-human primates, captive and human-reared nonhuman primates also demonstrate pointing behaviour. In this article, we analyse the debates on pointing and its role it might have played in language evolution from a meta-level. From within an Applied Evolutionary Epistemological approach, we examine how exactly we can determine whether pointing has been a unit, a level or a mechanism in language evolution.

Group Dynamics and Individual Roles: A Differentiated Approach to Social-Emotional Learning

Science.gov (United States)

Dugas, Daryl

2017-01-01

Differentiated instruction is a set of strategies to help teachers meet each child where he or she is in order to improve students' engagement, lead them to do their best work, and maximize their success. This article describes a differentiated classroom management approach based in group dynamics which focuses on the development of group norms…

Evolution of the mirror approach to fusion: some conjectures

International Nuclear Information System (INIS)

Post, R.E.

1984-01-01

Some possible directions for the future evolution of the mirror approach to fusion are outlined, in the context of economically-motivated criteria. Speculations are given as to the potential advantages, economic and otherwise, of the use of axially-symmetric systems, operated in semi-collisional regimes of lower Q (fusion power balance ratio) than that projected for present-day tandem mirror designs. These regims include barely tandem modes, and ion-heated modes, in association with higher efficiency direct conversion. Another possible economically advantageous approach mentioned is the use of a tandem mirror plasma to stabilize a FRM (field-reversed mirror) plasma, with potential synergistic advantages

A Differential Geometric Approach to Nonlinear Filtering: The Projection Filter

NARCIS (Netherlands)

Brigo, D.; Hanzon, B.; LeGland, F.

1998-01-01

This paper presents a new and systematic method of approximating exact nonlinear filters with finite dimensional filters, using the differential geometric approach to statistics. The projection filter is defined rigorously in the case of exponential families. A convenient exponential family is

NATURAL SCIENCE AT SCHOOL: MODERN APPROACHES TO THE DIFFERENTIATED STUDY

Directory of Open Access Journals (Sweden)

Dechtyarenko S.G.

2015-08-01

Full Text Available The article analyzes the possibility of differentiated study natural science at school on the basis of ecological educational process. Natural science is the science about nature as a single unity or totality of the natural sciences, which constituting a single unit. The main aim of the course is to develop student’s natural science competence through integrated mastering system knowledge about nature and man, the basics of environmental knowledge, ways of improving teaching and learning activities, development of value orientations in relation to the nature. There is strong need to review approaches to teaching nature science at schools, taking into account the general trend of greening of the educational process. The aim of the work is to analyze the possibility of practical application of modern approaches to differentiated teaching of the nature science at school greening within the educational process. In our view, the environmental component may be a basis to the formation and differentiated teaching in general. The environmental component of the educational sector has been aimed to the student’s environmental consciousness and compliance with rules of environmentally safe behavior in the environment. The learning of the integrated knowledge about nature and man can be submitted through the prism of action of the environmental factors according classic approach to their classification: abiotic, biotic and anthropogenic factors. In parallel, it is reasonable to raise the issues of practical importance as some natural objects and actions of each of these factors. The new degree of the studying of the environment has been provided by the beginning of the systematization of knowledge about natural objects and structure of the universe, by the formation of primary concepts about the relationship between the world of the living and inanimate nature, between organisms and between human activities and changes that has been occurred in the

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.

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

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%.

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

APPROACHED DECISION OF THE DIFFERENTIAL EQUATIONS

Directory of Open Access Journals (Sweden)

Oleksii B. Krasnozhon

2011-02-01

Full Text Available The urgency of the material stated in the article is caused by necessity of development, updating and improvements of methodical operating time on subject matters of issue "Calculus mathematics" which teaching is carried out in conditions of use of information-communication technologies. In the article the program realizations in Mathcad environment of Adams and Runge-Kutt methods of the approached decision of the differential equations are offered; examples on application of the specified methods are brought; the expediency of application of Mathcad environment during mathematical preparation of experts is proved. Perspective directions of the further scientific researches are methodical, mathematical and algorithmic aspects of creation of effective program realizations of numerical methods in Mathcad environment.

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.

Engineering-derived approaches for iPSC preparation, expansion, differentiation and applications.

Science.gov (United States)

Li, Yang; Li, Ling; Chen, Zhi-Nan; Gao, Ge; Yao, Rui; Sun, Wei

2017-07-31

Remarkable achievements have been made since induced pluripotent stem cells (iPSCs) were first introduced in 2006. Compared with non-pluripotent stem cells, iPSC research faces several additional complexities, such as the choice of extracellular matrix proteins, growth and differentiation factors, as well as technical challenges related to self-renewal and directed differentiation. Overcoming these challenges requires the integration of knowledge and technologies from multiple fields including cell biology, biomaterial science, engineering, physics and medicine. Here, engineering-derived iPSC approaches are reviewed according to three aspects of iPSC studies: preparation, expansion, differentiation and applications. Engineering strategies, such as 3D systems establishment, cell-matrix mechanics and the regulation of biophysical and biochemical cues, together with engineering techniques, such as 3D scaffolds, cell microspheres and bioreactors, have been applied to iPSC studies and have generated insightful results and even mini-organs such as retinas, livers and intestines. Specific results are given to demonstrate how these approaches impact iPSC behavior, and related mechanisms are discussed. In addition, cell printing technologies are presented as an advanced engineering-derived approach since they have been applied in both iPSC studies and the construction of diverse tissues and organs. Further development and possible innovations of cell printing technologies are presented in terms of creating complex and functional iPSC-derived living tissues and organs.

Student Teachers' Approaches to Teaching Biological Evolution

Science.gov (United States)

Borgerding, Lisa A.; Klein, Vanessa A.; Ghosh, Rajlakshmi; Eibel, Albert

2015-01-01

Evolution is fundamental to biology and scientific literacy, but teaching high school evolution is often difficult. Evolution teachers face several challenges including limited content knowledge, personal conflicts with evolution, expectations of resistance, concerns about students' conflicts with religion, and curricular constraints. Evolution…

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

Groups of integral transforms generated by Lie algebras of second-and higher-order differential operators

International Nuclear Information System (INIS)

Steinberg, S.; Wolf, K.B.

1979-01-01

The authors study the construction and action of certain Lie algebras of second- and higher-order differential operators on spaces of solutions of well-known parabolic, hyperbolic and elliptic linear differential equations. The latter include the N-dimensional quadratic quantum Hamiltonian Schroedinger equations, the one-dimensional heat and wave equations and the two-dimensional Helmholtz equation. In one approach, the usual similarity first-order differential operator algebra of the equation is embedded in the larger one, which appears as a quantum-mechanical dynamic algebra. In a second approach, the new algebra is built as the time evolution of a finite-transformation algebra on the initial conditions. In a third approach, the algebra to inhomogeneous similarity algebra is deformed to a noncompact classical one. In every case, we can integrate the algebra to a Lie group of integral transforms acting effectively on the solution space of the differential equation. (author)

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.

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.

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)

The evolution model of Uppsala in light of the complex adaptive systems approach

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Rennaly Alves da Silva

2013-11-01

Full Text Available The behavioral approach to the internationalization of companies explains that the movements toward external markets occur in accordance with the increasing commitment of resources to mitigate the effects of uncertainty and reduce the perception of risk. Evidence indicates that the theories and practices developed in the domestic market may not be able to explain the reality of companies that operate in international markets. Thus, the Paradigm of Complexity presents itself as a comprehensive alternative to realize the relationships within organizations and markets. Accordingly, the aim of this theoretical paper is to analyze the evolution of the Uppsala Model between years 1975 and 2010 with the understanding of the companies in the process of internationalization as Complex Adaptive Systems, in accordance with the Model Kelly and Allison (1998. Four propositions are presented that show the links between the approaches. The most surprising is the perception that the conceptual evolution of the Uppsala Model seems to accompany the evolution of complexity levels, presented in Model Kelly and Allison.

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.

Morphofunctional and Biochemical Approaches for Studying Mitochondrial Changes during Myoblasts Differentiation

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Elena Barbieri

2011-01-01

Full Text Available This study describes mitochondrial behaviour during the C2C12 myoblast differentiation program and proposes a proteomic approach to mitochondria integrated with classical morphofunctional and biochemical analyses. Mitochondrial ultrastructure variations were determined by transmission electron microscopy; mitochondrial mass and membrane potential were analysed by Mitotracker Green and JC-1 stains and by epifluorescence microscope. Expression of PGC1 , NRF1 , and Tfam genes controlling mitochondrial biogenesis was studied by real-time PCR. The mitochondrial functionality was tested by cytochrome c oxidase activity and COXII expression. Mitochondrial proteomic profile was also performed. These assays showed that mitochondrial biogenesis and activity significantly increase in differentiating myotubes. The proteomic profile identifies 32 differentially expressed proteins, mostly involved in oxidative metabolism, typical of myotubes formation. Other notable proteins, such as superoxide dismutase (MnSOD, a cell protection molecule, and voltage-dependent anion-selective channel protein (VDAC1 involved in the mitochondria-mediated apoptosis, were found to be regulated by the myogenic process. The integration of these approaches represents a helpful tool for studying mitochondrial dynamics, biogenesis, and functionality in comparative surveys on mitochondrial pathogenic or senescent satellite cells.

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.

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.

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

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Zabrina L Brumme

2007-07-01

genes investigated indicates differential HLA class I-driven evolution in different viral genes. The relationship between HLA class I-associated polymorphisms and lower CD4(+ cell count suggests that immune escape correlates with disease status, supporting an essential role of maintenance of effective CTL responses in immune control of HIV-1. The design of preventative and therapeutic CTL-based vaccine approaches could incorporate information on predictable escape pathways.

Helicopter Approach Capability Using the Differential Global Positioning System

Science.gov (United States)

Kaufmann, David N.

1994-01-01

The results of flight tests to determine the feasibility of using the Global Positioning System (GPS) in the Differential mode (DGPS) to provide high accuracy, precision navigation and guidance for helicopter approaches to landing are presented. The airborne DGPS receiver and associated equipment is installed in a NASA UH-60 Black Hawk helicopter. The ground-based DGPS reference receiver is located at a surveyed test site and is equipped with a real-time VHF data link to transmit correction information to the airborne DGPS receiver. The corrected airborne DGPS information, together with the preset approach geometry, is used to calculate guidance commands which are sent to the aircraft's approach guidance instruments. The use of DGPS derived guidance for helicopter approaches to landing is evaluated by comparing the DGPS data with the laser tracker truth data. The errors indicate that the helicopter position based on DGPS guidance satisfies the International Civil Aviation Organization (ICAO) Category 1 (CAT 1) lateral and vertical navigational accuracy requirements.

A pertinent approach to solve nonlinear fuzzy integro-differential equations.

Science.gov (United States)

Narayanamoorthy, S; Sathiyapriya, S P

2016-01-01

Fuzzy integro-differential equations is one of the important parts of fuzzy analysis theory that holds theoretical as well as applicable values in analytical dynamics and so an appropriate computational algorithm to solve them is in essence. In this article, we use parametric forms of fuzzy numbers and suggest an applicable approach for solving nonlinear fuzzy integro-differential equations using homotopy perturbation method. A clear and detailed description of the proposed method is provided. Our main objective is to illustrate that the construction of appropriate convex homotopy in a proper way leads to highly accurate solutions with less computational work. The efficiency of the approximation technique is expressed via stability and convergence analysis so as to guarantee the efficiency and performance of the methodology. Numerical examples are demonstrated to verify the convergence and it reveals the validity of the presented numerical technique. Numerical results are tabulated and examined by comparing the obtained approximate solutions with the known exact solutions. Graphical representations of the exact and acquired approximate fuzzy solutions clarify the accuracy of the approach.

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.

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

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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.

Conceptual Challenges of the Systemic Approach in Understanding Cell Differentiation.

Science.gov (United States)

Paldi, Andras

2018-01-01

The cells of a multicellular organism are derived from a single zygote and genetically identical. Yet, they are phenotypically very different. This difference is the result of a process commonly called cell differentiation. How the phenotypic diversity emerges during ontogenesis or regeneration is a central and intensely studied but still unresolved issue in biology. Cell biology is facing conceptual challenges that are frequently confused with methodological difficulties. How to define a cell type? What stability or change means in the context of cell differentiation and how to deal with the ubiquitous molecular variations seen in the living cells? What are the driving forces of the change? We propose to reframe the problem of cell differentiation in a systemic way by incorporating different theoretical approaches. The new conceptual framework is able to capture the insights made at different levels of cellular organization and considered previously as contradictory. It also provides a formal strategy for further experimental studies.

Impact of a Differential Learning Approach on Practical Exam Performance: A Controlled Study in a Preclinical Dental Course.

Science.gov (United States)

Pabel, Sven-Olav; Pabel, Anne-Kathrin; Schmickler, Jan; Schulz, Xenia; Wiegand, Annette

2017-09-01

The aim of this study was to evaluate if differential learning in a preclinical dental course impacted the performance of dental students in a practical exam (preparation of a gold partial crown) immediately after the training session and 20 weeks later compared to conventional learning. This controlled study was performed in a preclinical course in operative dentistry at a dental school in Germany. Third-year students were trained in preparing gold partial crowns by using either the conventional learning (n=41) or the differential learning approach (n=32). The differential learning approach consisted of 20 movement exercises with a continuous change of movement execution during the learning session, while the conventional learning approach was mainly based on repetition, a methodological series of exercises, and correction of preparations during the training phase. Practical exams were performed immediately after the training session (T1) and 20 weeks later (T2, retention test). Preparations were rated by four independent and blinded examiners. At T1, no significant difference between the performance (exam passed) of the two groups was detected (conventional learning: 54.3%, differential learning: 68.0%). At T2, significantly more students passed the exam when trained by the differential learning approach (68.8%) than by the conventional learning approach (18.9%). Interrater reliability was moderate (Kappa: 0.57, T1) or substantial (Kappa: 0.67, T2), respectively. These results suggest that a differential learning approach can increase the manual skills of dental students.

A Constructive Approach To Software Evolution

NARCIS (Netherlands)

Ciraci, S.; van den Broek, P.M.; Aksit, Mehmet

2007-01-01

In many software design and evaluation techniques, either the software evolution problem is not systematically elaborated, or only the impact of evolution is considered. Thus, most of the time software is changed by editing the components of the software system, i.e. breaking down the software

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.

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.

Gene selection for the reconstruction of stem cell differentiation trees: a linear programming approach.

Science.gov (United States)

Ghadie, Mohamed A; Japkowicz, Nathalie; Perkins, Theodore J

2015-08-15

Stem cell differentiation is largely guided by master transcriptional regulators, but it also depends on the expression of other types of genes, such as cell cycle genes, signaling genes, metabolic genes, trafficking genes, etc. Traditional approaches to understanding gene expression patterns across multiple conditions, such as principal components analysis or K-means clustering, can group cell types based on gene expression, but they do so without knowledge of the differentiation hierarchy. Hierarchical clustering can organize cell types into a tree, but in general this tree is different from the differentiation hierarchy itself. Given the differentiation hierarchy and gene expression data at each node, we construct a weighted Euclidean distance metric such that the minimum spanning tree with respect to that metric is precisely the given differentiation hierarchy. We provide a set of linear constraints that are provably sufficient for the desired construction and a linear programming approach to identify sparse sets of weights, effectively identifying genes that are most relevant for discriminating different parts of the tree. We apply our method to microarray gene expression data describing 38 cell types in the hematopoiesis hierarchy, constructing a weighted Euclidean metric that uses just 175 genes. However, we find that there are many alternative sets of weights that satisfy the linear constraints. Thus, in the style of random-forest training, we also construct metrics based on random subsets of the genes and compare them to the metric of 175 genes. We then report on the selected genes and their biological functions. Our approach offers a new way to identify genes that may have important roles in stem cell differentiation. tperkins@ohri.ca Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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.

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....

A phenomenological approach to simulating the evolution of radioactive-waste container damage due to pitting corrosion

International Nuclear Information System (INIS)

Henshall, G.A.

1995-01-01

The damage to high-level radioactive-waste containers by pitting corrosion is an important design and performance assessment consideration. It is desirable to calculate the evolution of the pit depth distribution, not just the time required for initial penetration of the containers, so that the area available for advective of diffusive release of radionuclides through the container can be estimated. A phenomenological approach for computing the time evolution of these distributions is presented which combines elements of the deterministic and stochastic aspects of pit growth. The consistency of this approach with the mechanisms believed to control the evolution of the pit depth distribution is discussed. Qualitative comparisons of preliminary model predictions with a variety of experimental data from the literature are shown to be generally favorable. The sensitivity of the simulated distributions to changes in the input parameters is discussed. Finally, the results of the current model are compared to those of existing approaches based on extreme-value statistics, particularly regarding the extrapolation of laboratory data to large exposed surface areas

One size does not fit all : An approach for differentiated supply chain management

OpenAIRE

Beck, Patrick; Hofmann, Erik; Stölzle, Wolfgang

2012-01-01

Supply chain management (SCM) has developed from an object of operational optimization into a strategic weapon for distinction from competitors. Dynamically changing and strongly varying customer needs demand a differentiated SCM approach. Supply chain differentiation (SCD) plans and designs supply chains based on customer needs, as increasingly demanded by SCM researchers. Therefore SCD offers a possibility to increase SCM effectiveness. While practitioners are highly interested in SCD, acad...

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

Laughter as an approach to vocal evolution: The bipedal theory.

Science.gov (United States)

Provine, Robert R

2017-02-01

Laughter is a simple, stereotyped, innate, human play vocalization that is ideal for the study of vocal evolution. The basic approach of describing the act of laughter and when we do it has revealed a variety of phenomena of social, linguistic, and neurological significance. Findings include the acoustic structure of laughter, the minimal voluntary control of laughter, the punctuation effect (which describes the placement of laughter in conversation and indicates the dominance of speech over laughter), and the role of laughter in human matching and mating. Especially notable is the use of laughter to discover why humans can speak and other apes cannot. Quadrupeds, including our primate ancestors, have a 1:1 relation between breathing and stride because their thorax must absorb forelimb impacts during running. The direct link between breathing and locomotion limits vocalizations to short, simple utterances, such as the characteristic panting chimpanzee laugh (one sound per inward or outward breath). The evolution of bipedal locomotion freed the respiration system of its support function during running, permitting greater breath control and the selection for human-type laughter (a parsed exhalation), and subsequently the virtuosic, sustained, expiratory vocalization of speech. This is the basis of the bipedal theory of speech evolution.

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.

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.

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.

R&D, patents and innovation: a differential game approach

OpenAIRE

Wang, H.-M.

2016-01-01

A patent race is a technological competition among firms and the firm making a first-hand innovation takes advantages of patenting. Firms strategically invest in R&D and produce knowledge in order to innovate. Instead of growing model of R&D, I use a differential game approach to investigate firms interaction of R&D behavior in a patent race. In general, knowledge is an intangible good that gives a special feature of a patent race. Whether knowledge is substitutable to the existing knowledge ...

Integro-differential transport approaches

International Nuclear Information System (INIS)

Stepanek, J.; Arkuszewski, J.; Boffi, V.; Matausek, M.V.

1981-01-01

This chapter summarizes the work done in Italy, Poland, Switzerland and Yugoslavia in the field of integro-differential neutron transport theory. It reflects different viewpoints in the handling of the subject. Some of the methods are based only on the solution of the integro-differential equation, others use only the integral form of the transport equation. Use of the characteristic solution closely related to the integral equation (ARKUSZEWSKI et al.,(1979)) seems to be a rather effective way to accelerate the 2 dimensional discrete ordinates (Ssub(n)) transport methods and supress one of the main disadvantages, the ray effect. The advanced ''Surface Currents'' (MAEDER (1975)) and ''Surface Flux'' (STEPANEK (1979)) methods are based on the solution of both the integro-differential and integral form of the transport equation. As long as the spatial fluxes were considered to be flat in each region only the integral form of the transport equation was considered. The solution seems to be the best method of simple handling the higher order Legendre polynomials used to approximate spatial and angular flux distribution. The coupling of the Bsub(n) integral transport equations with the related Psub(n) equations removes the greatest disadvantage of the Psub(n) theory and closes the system of the Psub(n) equations (LIGOU, STEPANEK (1974))

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.

A call for differentiated approaches to delivering HIV services to key populations.

Science.gov (United States)

Macdonald, Virginia; Verster, Annette; Baggaley, Rachel

2017-07-21

Key populations (KPs) are disproportionally affected by HIV and have low rates of access to HIV testing and treatment services compared to the broader population. WHO promotes the use of differentiated approaches for reaching and recruiting KP into the HIV services continuum. These approaches may help increase access to KPs who are often criminalized or stigmatized. By catering to the specific needs of each KP individual, differentiated approaches may increase service acceptability, quality and coverage, reduce costs and support KP members in leading the HIV response among their communities. WHO recommends the implementation of community-based and lay provider administered HIV testing services. Together, these approaches reduce barriers and costs associated with other testing strategies, allow greater ownership in HIV programmes for KP members and reach more people than do facility-based services. Despite this evidence availability and support for them is limited. Peer-driven interventions have been shown to be effective in engaging, recruiting and supporting clients. Some programmes employ HIV-positive or non-PLHIV "peer navigators" and other staff to provide case management, enrolment and/or re-enrolment in care and treatment services. However, a better understanding of the impact, cost effectiveness and potential burden on peer volunteers is required. Task shifting and non-facility-based service locations for antiretroviral therapy (ART) initiation and maintenance and antiretroviral (ARV) distribution are recommended in both the consolidated HIV treatment and KP guidelines of WHO. These approaches are accepted in generalized epidemics and for the general population where successful models exist; however, few organizations provide or initiate ART at KP community-based services. The application of a differentiated service approach for KP could increase the number of people who know their status and receive effective and sustained prevention and treatment for HIV

SaLEM (v1.0) - the Soil and Landscape Evolution Model (SaLEM) for simulation of regolith depth in periglacial environments

Science.gov (United States)

Bock, Michael; Conrad, Olaf; Günther, Andreas; Gehrt, Ernst; Baritz, Rainer; Böhner, Jürgen

2018-04-01

We propose the implementation of the Soil and Landscape Evolution Model (SaLEM) for the spatiotemporal investigation of soil parent material evolution following a lithologically differentiated approach. Relevant parts of the established Geomorphic/Orogenic Landscape Evolution Model (GOLEM) have been adapted for an operational Geographical Information System (GIS) tool within the open-source software framework System for Automated Geoscientific Analyses (SAGA), thus taking advantage of SAGA's capabilities for geomorphometric analyses. The model is driven by palaeoclimatic data (temperature, precipitation) representative of periglacial areas in northern Germany over the last 50 000 years. The initial conditions have been determined for a test site by a digital terrain model and a geological model. Weathering, erosion and transport functions are calibrated using extrinsic (climatic) and intrinsic (lithologic) parameter data. First results indicate that our differentiated SaLEM approach shows some evidence for the spatiotemporal prediction of important soil parental material properties (particularly its depth). Future research will focus on the validation of the results against field data, and the influence of discrete events (mass movements, floods) on soil parent material formation has to be evaluated.

Evolution of the Theoretical Approaches to Disclosing the Economic Substance of Accumulation of Capital

Directory of Open Access Journals (Sweden)

Yemets Vadym V.

2016-05-01

Full Text Available The article proposes a classification for periods of evolution of theoretical approaches to disclosing the economic substance of accumulation of capital, taking into account the civilizational approach to the development of society. The author has proposed five stages in the evolution of theoretical approaches, which are closely related to the development of economy and stipulate dominance of a certain form of accumulation of capital. So, the first stage (time period B.C. – the 5th Century is referred to as Individual-social significance of accumulation of capital; the second stage (from the 6th century to the 16th century – Accumulation of monetary capitals; the third stage (from the mid-17th century until the end of the 18th century – Industrialproduction accumulation of capital; the fourth stage (from the mid-19th century until the 70s of the 20th century – Investment-oriented accumulation of capital; the fifth stage (from the 70s of the 20th century up to the current period – Globally-intensive accumulation of capital.

Constructive Approaches for Understanding the Origin of Self-Replication and Evolution

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Norikazu Ichihashi

2016-07-01

Full Text Available The mystery of the origin of life can be divided into two parts. The first part is the origin of biomolecules: under what physicochemical conditions did biomolecules such as amino acids, nucleotides, and their polymers arise? The second part of the mystery is the origin of life-specific functions such as the replication of genetic information, the reproduction of cellular structures, metabolism, and evolution. These functions require the coordination of many different kinds of biological molecules. A direct strategy to approach the second part of the mystery is the constructive approach, in which life-specific functions are recreated in a test tube from specific biological molecules. Using this approach, we are able to employ design principles to reproduce life-specific functions, and the knowledge gained through the reproduction process provides clues as to their origins. In this mini-review, we introduce recent insights gained using this approach, and propose important future directions for advancing our understanding of the origins of life.

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.

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

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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.

A variational approach to parameter estimation in ordinary differential equations

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Kaschek Daniel

2012-08-01

Full Text Available Abstract Background Ordinary differential equations are widely-used in the field of systems biology and chemical engineering to model chemical reaction networks. Numerous techniques have been developed to estimate parameters like rate constants, initial conditions or steady state concentrations from time-resolved data. In contrast to this countable set of parameters, the estimation of entire courses of network components corresponds to an innumerable set of parameters. Results The approach presented in this work is able to deal with course estimation for extrinsic system inputs or intrinsic reactants, both not being constrained by the reaction network itself. Our method is based on variational calculus which is carried out analytically to derive an augmented system of differential equations including the unconstrained components as ordinary state variables. Finally, conventional parameter estimation is applied to the augmented system resulting in a combined estimation of courses and parameters. Conclusions The combined estimation approach takes the uncertainty in input courses correctly into account. This leads to precise parameter estimates and correct confidence intervals. In particular this implies that small motifs of large reaction networks can be analysed independently of the rest. By the use of variational methods, elements from control theory and statistics are combined allowing for future transfer of methods between the two fields.

A variational approach to parameter estimation in ordinary differential equations.

Science.gov (United States)

Kaschek, Daniel; Timmer, Jens

2012-08-14

Ordinary differential equations are widely-used in the field of systems biology and chemical engineering to model chemical reaction networks. Numerous techniques have been developed to estimate parameters like rate constants, initial conditions or steady state concentrations from time-resolved data. In contrast to this countable set of parameters, the estimation of entire courses of network components corresponds to an innumerable set of parameters. The approach presented in this work is able to deal with course estimation for extrinsic system inputs or intrinsic reactants, both not being constrained by the reaction network itself. Our method is based on variational calculus which is carried out analytically to derive an augmented system of differential equations including the unconstrained components as ordinary state variables. Finally, conventional parameter estimation is applied to the augmented system resulting in a combined estimation of courses and parameters. The combined estimation approach takes the uncertainty in input courses correctly into account. This leads to precise parameter estimates and correct confidence intervals. In particular this implies that small motifs of large reaction networks can be analysed independently of the rest. By the use of variational methods, elements from control theory and statistics are combined allowing for future transfer of methods between the two fields.

A novel algebraic procedure for solving non-linear evolution equations of higher order

International Nuclear Information System (INIS)

Huber, Alfred

2007-01-01

We report here a systematic approach that can easily be used for solving non-linear partial differential equations (nPDE), especially of higher order. We restrict the analysis to the so called evolution equations describing any wave propagation. The proposed new algebraic approach leads us to traveling wave solutions and moreover, new class of solution can be obtained. The crucial step of our method is the basic assumption that the solutions satisfy an ordinary differential equation (ODE) of first order that can be easily integrated. The validity and reliability of the method is tested by its application to some non-linear evolution equations. The important aspect of this paper however is the fact that we are able to calculate distinctive class of solutions which cannot be found in the current literature. In other words, using this new algebraic method the solution manifold is augmented to new class of solution functions. Simultaneously we would like to stress the necessity of such sophisticated methods since a general theory of nPDE does not exist. Otherwise, for practical use the algebraic construction of new class of solutions is of fundamental interest

[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.

Multiple wall-reflection effect in adaptive-array differential-phase reflectometry on QUEST

International Nuclear Information System (INIS)

Idei, H.; Fujisawa, A.; Nagashima, Y.; Onchi, T.; Hanada, K.; Zushi, H.; Mishra, K.; Hamasaki, M.; Hayashi, Y.; Yamamoto, M.K.

2016-01-01

A phased array antenna and Software-Defined Radio (SDR) heterodyne-detection systems have been developed for adaptive array approaches in reflectometry on the QUEST. In the QUEST device considered as a large oversized cavity, standing wave (multiple wall-reflection) effect was significantly observed with distorted amplitude and phase evolution even if the adaptive array analyses were applied. The distorted fields were analyzed by Fast Fourier Transform (FFT) in wavenumber domain to treat separately the components with and without wall reflections. The differential phase evolution was properly obtained from the distorted field evolution by the FFT procedures. A frequency derivative method has been proposed to overcome the multiple-wall reflection effect, and SDR super-heterodyned components with small frequency difference for the derivative method were correctly obtained using the FFT analysis

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

Directory of Open Access Journals (Sweden)

Akbar Swandaru

2012-09-01

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

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

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

Redox Evolution via Gravitational Differentiation on Low-mass Planets: Implications for Abiotic Oxygen, Water Loss, and Habitability

Science.gov (United States)

Wordsworth, R. D.; Schaefer, L. K.; Fischer, R. A.

2018-05-01

The oxidation of rocky planet surfaces and atmospheres, which arises from the twin forces of stellar nucleosynthesis and gravitational differentiation, is a universal process of key importance to habitability and exoplanet biosignature detection. Here we take a generalized approach to this phenomenon. Using a single parameter to describe the redox state, we model the evolution of terrestrial planets around nearby M stars and the Sun. Our model includes atmospheric photochemistry, diffusion and escape, line-by-line climate calculations, and interior thermodynamics and chemistry. In most cases, we find abiotic atmospheric {{{O}}}2 buildup around M stars during the pre-main-sequence phase to be much less than calculated previously, because the planet’s magma ocean absorbs most oxygen liberated from {{{H}}}2{{O}} photolysis. However, loss of noncondensing atmospheric gases after the mantle solidifies remains a significant potential route to abiotic atmospheric {{{O}}}2 subsequently. In all cases, we predict that exoplanets that receive lower stellar fluxes, such as LHS1140b and TRAPPIST-1f and g, have the lowest probability of abiotic {{{O}}}2 buildup and hence may be the most interesting targets for future searches for biogenic {{{O}}}2. Key remaining uncertainties can be minimized in future by comparing our predictions for the atmospheres of hot, sterile exoplanets such as GJ1132b and TRAPPIST-1b and c with observations.

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.

Quantifying uncertainty, variability and likelihood for ordinary differential equation models

LENUS (Irish Health Repository)

Weisse, Andrea Y

2010-10-28

Abstract Background In many applications, ordinary differential equation (ODE) models are subject to uncertainty or variability in initial conditions and parameters. Both, uncertainty and variability can be quantified in terms of a probability density function on the state and parameter space. Results The partial differential equation that describes the evolution of this probability density function has a form that is particularly amenable to application of the well-known method of characteristics. The value of the density at some point in time is directly accessible by the solution of the original ODE extended by a single extra dimension (for the value of the density). This leads to simple methods for studying uncertainty, variability and likelihood, with significant advantages over more traditional Monte Carlo and related approaches especially when studying regions with low probability. Conclusions While such approaches based on the method of characteristics are common practice in other disciplines, their advantages for the study of biological systems have so far remained unrecognized. Several examples illustrate performance and accuracy of the approach and its limitations.

Remarks on the differential algebraic approach to particle beam optics by M. Berz

International Nuclear Information System (INIS)

Garczynski, V.

1992-01-01

The underlying mathematical structure of the differential algebraic approach of M. Berz to particle beam optics is isomorphic to the familiar truncated polynomial algebra. Concrete examples of derivations in this algebra, consistent with the truncation operation, are given

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.

The Approach to Equilibrium: Detailed Balance and the Master Equation

Science.gov (United States)

Alexander, Millard H.; Hall, Gregory E.; Dagdigian, Paul J.

2011-01-01

The approach to the equilibrium (Boltzmann) distribution of populations of internal states of a molecule is governed by inelastic collisions in the gas phase and with surfaces. The set of differential equations governing the time evolution of the internal state populations is commonly called the master equation. An analytic solution to the master…

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

International Nuclear Information System (INIS)

Hudson, S.R.

2010-01-01

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

A Differential Approach to Choosing Extracorporeal Detoxification Methods for Abdominal Sepsis

Directory of Open Access Journals (Sweden)

L. Ye Shukevich

2005-01-01

Full Text Available A differential approach to choosing the methods of extracorporeal detoxification in the complex treatment of abdominal sepsis in the context of endogenous intoxication in order to enhance the efficiency of medical measures was pathogeneti-cally substantiated. In 51 patients diagnosed as having abdominal sepsis, the latter was characterized as the endogenous intoxication syndrome in relation to the accumulation of low and medium molecular-weight substances (plasma and red blood cells in the body and their physiological elimination with urine. An original formula was used to calculate the integral marker – the endogenous intoxication index correlating with the routine severity rating scales APACHE II and SOFA and reflecting the severity of endotoxicosis. According to the values of the endogenous intoxication index and to the sum of scores by the APACHE II and SOFA scales, the patients were divided into 3 groups of the clinicopathogenetic types of endogenous intoxication. According to the type of endogenous intoxication, the authors proposed a differential approach to choosing the modes of efferent therapy for abdominal sepsis: high-volume plasmapheresis in the subcompensated type and prolonged venovenous hemofiltration, which improved the results of treatment and reduced mortality rates.

Orbiting binary black hole evolutions with a multipatch high order finite-difference approach

International Nuclear Information System (INIS)

Pazos, Enrique; Tiglio, Manuel; Duez, Matthew D.; Kidder, Lawrence E.; Teukolsky, Saul A.

2009-01-01

We present numerical simulations of orbiting black holes for around 12 cycles, using a high order multipatch approach. Unlike some other approaches, the computational speed scales almost perfectly for thousands of processors. Multipatch methods are an alternative to adaptive mesh refinement, with benefits of simplicity and better scaling for improving the resolution in the wave zone. The results presented here pave the way for multipatch evolutions of black hole-neutron star and neutron star-neutron star binaries, where high resolution grids are needed to resolve details of the matter flow.

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

Directory of Open Access Journals (Sweden)

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.

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.

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

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 semi-analytical approach for solving of nonlinear systems of functional differential equations with delay

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Rebenda, Josef; Šmarda, Zdeněk

2017-07-01

In the paper, we propose a correct and efficient semi-analytical approach to solve initial value problem for systems of functional differential equations with delay. The idea is to combine the method of steps and differential transformation method (DTM). In the latter, formulas for proportional arguments and nonlinear terms are used. An example of using this technique for a system with constant and proportional delays is presented.

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

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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

Critical spaces for quasilinear parabolic evolution equations and applications

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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.

Modeling of delays in PKPD: classical approaches and a tutorial for delay differential equations.

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Koch, Gilbert; Krzyzanski, Wojciech; Pérez-Ruixo, Juan Jose; Schropp, Johannes

2014-08-01

In pharmacokinetics/pharmacodynamics (PKPD) the measured response is often delayed relative to drug administration, individuals in a population have a certain lifespan until they maturate or the change of biomarkers does not immediately affects the primary endpoint. The classical approach in PKPD is to apply transit compartment models (TCM) based on ordinary differential equations to handle such delays. However, an alternative approach to deal with delays are delay differential equations (DDE). DDEs feature additional flexibility and properties, realize more complex dynamics and can complementary be used together with TCMs. We introduce several delay based PKPD models and investigate mathematical properties of general DDE based models, which serve as subunits in order to build larger PKPD models. Finally, we review current PKPD software with respect to the implementation of DDEs for PKPD analysis.

Synchronization of integral and fractional order chaotic systems a differential algebraic and differential geometric approach with selected applications in real-time

CERN Document Server

Martínez-Guerra, Rafael; Gómez-Cortés, Gian Carlo

2015-01-01

This book provides a general overview of several concepts of synchronization and brings together related approaches to secure communication in chaotic systems. This is achieved using a combination of analytic, algebraic, geometrical and asymptotical methods to tackle the dynamical feedback stabilization problem. In particular, differential-geometric and algebraic differential concepts reveal important structural properties of chaotic systems and serve as guide for the construction of design procedures for a wide variety of chaotic systems. The basic differential algebraic and geometric concepts are presented in the first few chapters in a novel way as design tools, together with selected experimental studies demonstrating their importance. The subsequent chapters treat recent applications. Written for graduate students in applied physical sciences, systems engineers, and applied mathematicians interested in synchronization of chaotic systems and in secure communications, this self-contained text requires only...

Building bridges connections and challenges in modern approaches to numerical partial differential equations

CERN Document Server

Brezzi, Franco; Cangiani, Andrea; Georgoulis, Emmanuil

2016-01-01

This volume contains contributed survey papers from the main speakers at the LMS/EPSRC Symposium “Building bridges: connections and challenges in modern approaches to numerical partial differential equations”. This meeting took place in July 8-16, 2014, and its main purpose was to gather specialists in emerging areas of numerical PDEs, and explore the connections between the different approaches. The type of contributions ranges from the theoretical foundations of these new techniques, to the applications of them, to new general frameworks and unified approaches that can cover one, or more than one, of these emerging techniques.

A HYBRID APPROACH FOR RURAL FEEDER DESIGN

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DAMANJEET KAUR

2012-08-01

Full Text Available In this paper, a population based approach for conductor size selection in rural radial distribution system is presented. The proposed hybrid approach implies a particle swarm optimization (PSO approach in combination with mutant property of differential evolution (DE for conductor size selection in radial distribution system. The conductor size for each feeder segment is selected such that the total cost of capital investment and capitalized cost of energy losses is minimized while constraints of voltage at each node and current carrying capacity of conductor is within the limits. The applicability and effectiveness of the proposed method is demonstrated with the help of 32-node test system.

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

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.

Detection of Differential Item Functioning with Nonlinear Regression: A Non-IRT Approach Accounting for Guessing

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Drabinová, Adéla; Martinková, Patrícia

2017-01-01

In this article we present a general approach not relying on item response theory models (non-IRT) to detect differential item functioning (DIF) in dichotomous items with presence of guessing. The proposed nonlinear regression (NLR) procedure for DIF detection is an extension of method based on logistic regression. As a non-IRT approach, NLR can…

When Differential Privacy Meets Randomized Perturbation: A Hybrid Approach for Privacy-Preserving Recommender System

KAUST Repository

Liu, Xiao; Liu, An; Zhang, Xiangliang; Li, Zhixu; Liu, Guanfeng; Zhao, Lei; Zhou, Xiaofang

2017-01-01

result. However, none is designed for both hiding users’ private data and preventing privacy inference. To achieve this goal, we propose in this paper a hybrid approach for privacy-preserving recommender systems by combining differential privacy (DP

Stable Numerical Approach for Fractional Delay Differential Equations

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Singh, Harendra; Pandey, Rajesh K.; Baleanu, D.

2017-12-01

In this paper, we present a new stable numerical approach based on the operational matrix of integration of Jacobi polynomials for solving fractional delay differential equations (FDDEs). The operational matrix approach converts the FDDE into a system of linear equations, and hence the numerical solution is obtained by solving the linear system. The error analysis of the proposed method is also established. Further, a comparative study of the approximate solutions is provided for the test examples of the FDDE by varying the values of the parameters in the Jacobi polynomials. As in special case, the Jacobi polynomials reduce to the well-known polynomials such as (1) Legendre polynomial, (2) Chebyshev polynomial of second kind, (3) Chebyshev polynomial of third and (4) Chebyshev polynomial of fourth kind respectively. Maximum absolute error and root mean square error are calculated for the illustrated examples and presented in form of tables for the comparison purpose. Numerical stability of the presented method with respect to all four kind of polynomials are discussed. Further, the obtained numerical results are compared with some known methods from the literature and it is observed that obtained results from the proposed method is better than these methods.

SaLEM (v1.0 – the Soil and Landscape Evolution Model (SaLEM for simulation of regolith depth in periglacial environments

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M. Bock

2018-04-01

Full Text Available We propose the implementation of the Soil and Landscape Evolution Model (SaLEM for the spatiotemporal investigation of soil parent material evolution following a lithologically differentiated approach. Relevant parts of the established Geomorphic/Orogenic Landscape Evolution Model (GOLEM have been adapted for an operational Geographical Information System (GIS tool within the open-source software framework System for Automated Geoscientific Analyses (SAGA, thus taking advantage of SAGA's capabilities for geomorphometric analyses. The model is driven by palaeoclimatic data (temperature, precipitation representative of periglacial areas in northern Germany over the last 50 000 years. The initial conditions have been determined for a test site by a digital terrain model and a geological model. Weathering, erosion and transport functions are calibrated using extrinsic (climatic and intrinsic (lithologic parameter data. First results indicate that our differentiated SaLEM approach shows some evidence for the spatiotemporal prediction of important soil parental material properties (particularly its depth. Future research will focus on the validation of the results against field data, and the influence of discrete events (mass movements, floods on soil parent material formation has to be evaluated.

Wave-packet continuum-discretization approach to ion-atom collisions including rearrangement: Application to differential ionization in proton-hydrogen scattering

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Abdurakhmanov, I. B.; Bailey, J. J.; Kadyrov, A. S.; Bray, I.

2018-03-01

In this work, we develop a wave-packet continuum-discretization approach to ion-atom collisions that includes rearrangement processes. The total scattering wave function is expanded using a two-center basis built from wave-packet pseudostates. The exact three-body Schrödinger equation is converted into coupled-channel differential equations for time-dependent expansion coefficients. In the asymptotic region these time-dependent coefficients represent transition amplitudes for all processes including elastic scattering, excitation, ionization, and electron capture. The wave-packet continuum-discretization approach is ideal for differential ionization studies as it allows one to generate pseudostates with arbitrary energies and distribution. The approach is used to calculate the double differential cross section for ionization in proton collisions with atomic hydrogen. Overall good agreement with experiment is obtained for all considered cases.

Impulsive differential inclusions a fixed point approach

CERN Document Server

Ouahab, Abdelghani; Henderson, Johnny

2013-01-01

Impulsive differential equations have been developed in modeling impulsive problems in physics, population dynamics, ecology, biotechnology, industrial robotics, pharmacokinetics, optimal control, etc. The questions of existence and stability of solutions for different classes of initial values problems for impulsive differential equations and inclusions with fixed and variable moments are considered in detail. Attention is also given to boundary value problems and relative questions concerning differential equations. This monograph addresses a variety of side issues that arise from its simple

Developmental evolution in social insects: regulatory networks from genes to societies.

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Linksvayer, Timothy A; Fewell, Jennifer H; Gadau, Jürgen; Laubichler, Manfred D

2012-05-01

The evolution and development of complex phenotypes in social insect colonies, such as queen-worker dimorphism or division of labor, can, in our opinion, only be fully understood within an expanded mechanistic framework of Developmental Evolution. Conversely, social insects offer a fertile research area in which fundamental questions of Developmental Evolution can be addressed empirically. We review the concept of gene regulatory networks (GRNs) that aims to fully describe the battery of interacting genomic modules that are differentially expressed during the development of individual organisms. We discuss how distinct types of network models have been used to study different levels of biological organization in social insects, from GRNs to social networks. We propose that these hierarchical networks spanning different organizational levels from genes to societies should be integrated and incorporated into full GRN models to elucidate the evolutionary and developmental mechanisms underlying social insect phenotypes. Finally, we discuss prospects and approaches to achieve such an integration. © 2012 WILEY PERIODICALS, INC.

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

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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.

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

Alloimmunization in autoimmune hemolytic anemia patient: The differential adsorption approach

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Ravi C Dara

2017-01-01

Full Text Available Patients of β-thalassemia major are dependent on regular blood transfusions for their entire lifetime. Development of antibodies against red blood cell (RBC antigen which may be alloantibody or autoantibody, several times as a result of frequent red cell component transfusions, further complicates the subsequent transfusion therapy. Among the autoantibodies, warm-reactive autoantibodies are commoner and interfere in the pretransfusion testing. These RBC autoantibodies present in patient's serum potentially react with all the cells of antibody identification panel giving “pan-reactive” picture and making alloantibody identification complex. In this report, we present our approach in a thalassemia patient who presented with warm-type autoimmune hemolytic anemia, low hemoglobin of 5.8 g/dl, and three significant alloantibodies (anti-D, anti-S, and anti-Jk b which were masked by pan-reactive warm autoantibody(s. Differential adsorption was used to unmask underlying alloantibodies. We suggest that differential adsorption procedure is an effective and efficient method for autoantibody adsorption, detection, and identification of masked alloantibody(s, especially in patients with low hemoglobin and history of recent blood transfusion.

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.

Bias due to differential participation in case-control studies and review of available approaches for adjustment.

Science.gov (United States)

Aigner, Annette; Grittner, Ulrike; Becher, Heiko

2018-01-01

Low response rates in epidemiologic research potentially lead to the recruitment of a non-representative sample of controls in case-control studies. Problems in the unbiased estimation of odds ratios arise when characteristics causing the probability of participation are associated with exposure and outcome. This is a specific setting of selection bias and a realistic hazard in many case-control studies. This paper formally describes the problem and shows its potential extent, reviews existing approaches for bias adjustment applicable under certain conditions, compares and applies them. We focus on two scenarios: a characteristic C causing differential participation of controls is linked to the outcome through its association with risk factor E (scenario I), and C is additionally a genuine risk factor itself (scenario II). We further assume external data sources are available which provide an unbiased estimate of C in the underlying population. Given these scenarios, we (i) review available approaches and their performance in the setting of bias due to differential participation; (ii) describe two existing approaches to correct for the bias in both scenarios in more detail; (iii) present the magnitude of the resulting bias by simulation if the selection of a non-representative sample is ignored; and (iv) demonstrate the approaches' application via data from a case-control study on stroke. The bias of the effect measure for variable E in scenario I and C in scenario II can be large and should therefore be adjusted for in any analysis. It is positively associated with the difference in response rates between groups of the characteristic causing differential participation, and inversely associated with the total response rate in the controls. Adjustment in a standard logistic regression framework is possible in both scenarios if the population distribution of the characteristic causing differential participation is known or can be approximated well.

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

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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.

An investigation of changes in element distribution and chemical states during differentiation of embryonic stem cells

International Nuclear Information System (INIS)

Sugimoto, T.; Ide-Ektessabi, A.; Ishihara, R.; Tanigaki, M.

2004-01-01

Metallic elements and their organic compounds have dynamic regulatory functions in cells. In this study, we implemented a new approach to investigate the mechanism of differentiation of embryonic stem cells, by measuring and analyzing the change in distribution and chemical states of intracellular trace elements. We anticipate that trace metal elements and metalloproteins play important roles in the direction of differentiation, both as active centers, and as factors in the death of neural cells in neurodegenerative disorders. The aim of this study is to analyze the distribution and chemical states of trace elements during the process of differentiation of mouse embryonic stem cells, and to understand how these factors relate to the differentiation process. Using the experimental results, some previously unexplained points are considered, namely (1) how the intracellular elements change during the process of neuronal differentiation, and (2) what the optimal conditions of such elements are for neuronal differentiation. The information obtained during this study is relevant to nervous system development and evolution

An investigation of changes in element distribution and chemical states during differentiation of embryonic stem cells

Energy Technology Data Exchange (ETDEWEB)

Sugimoto, T.; Ide-Ektessabi, A. E-mail: h51167@sakura.kudpc.kyoto-u.ac.jp; Ishihara, R.; Tanigaki, M

2004-07-01

Metallic elements and their organic compounds have dynamic regulatory functions in cells. In this study, we implemented a new approach to investigate the mechanism of differentiation of embryonic stem cells, by measuring and analyzing the change in distribution and chemical states of intracellular trace elements. We anticipate that trace metal elements and metalloproteins play important roles in the direction of differentiation, both as active centers, and as factors in the death of neural cells in neurodegenerative disorders. The aim of this study is to analyze the distribution and chemical states of trace elements during the process of differentiation of mouse embryonic stem cells, and to understand how these factors relate to the differentiation process. Using the experimental results, some previously unexplained points are considered, namely (1) how the intracellular elements change during the process of neuronal differentiation, and (2) what the optimal conditions of such elements are for neuronal differentiation. The information obtained during this study is relevant to nervous system development and evolution.

[Historic and functional biology: the inadequacy of a system theory of evolution].

Science.gov (United States)

Regelmann, J P

1982-01-01

In the first half of the 20th century neo-Kantianism in a broad sense proved itself the main conceptual and methodological background of the central European biology. As such it contributed much to the victory on the typological, idealistic-morphological and psycho-vitalistic interpretations of life. On the other hand it could not give tools to the biologists for working out a strictly darwinian evolution theory. Kant's theory of organism was conceived without evolution as a theory of the internal functionality of the organism. There was only some 'play' with the evolutionary differentiation of the species. Since then the disputes around the work of August Weismann, a synthetical evolution theory which is now behind time, arose. This theory developed from coinciding claims, elaborated by geneticists, mathematicians, and by biologists studying development, natural history and systematics. This was done under a strong influence of marxist ideas. Through the interweaving of such different approaches it was possible for this evolutionary synthesis to influence successfully the development of evolution research during more than 40 years. Philosophically speaking modern evolution theory means therefore an aversion, even a positive abolition of Kantian positions. A number of biologists however--as L. von Bertalanffy--refused to adhere to a misinterpreted Kantian methodology and oriented themselves to an approach via system theory, which obtained a place in evolution research. In fact this is a Kantian approach as well. They only repeated the Kantian dilemma of the evolution which can also be found in Lamarck and Hegel. The system theory of the functionality of the organism never reaches to the level of the evolving species, but remains always on the level of epigenetic thinking, because of its philosophical origin. This paper points out the consequences of this still current dilemma. At the same time an all-enclosing reflection on the methodological, epistemological and

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

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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.

Redox environment in stem and differentiated cells: A quantitative approach

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O.G. Lyublinskaya

2017-08-01

Full Text Available Stem cells are believed to maintain a specific intracellular redox status through a combination of enhanced removal capacity and limited production of ROS. In the present study, we challenge this assumption by developing a quantitative approach for the analysis of the pro- and antioxidant ability of human embryonic stem cells in comparison with their differentiated descendants, as well as adult stem and non-stem cells. Our measurements showed that embryonic stem cells are characterized by low ROS level, low rate of extracellular hydrogen peroxide removal and low threshold for peroxide-induced cytotoxicity. However, biochemical normalization of these parameters to cell volume/protein leads to matching of normalized values in stem and differentiated cells and shows that tested in the present study cells (human embryonic stem cells and their fibroblast-like progenies, adult mesenchymal stem cells, lymphocytes, HeLa maintain similar intracellular redox status. Based on these observations, we propose to use ROS concentration averaged over the cell volume instead of ROS level as a measure of intracellular redox balance. We show that attempts to use ROS level for comparative analysis of redox status of morphologically different cells could lead to false conclusions. Methods for the assessment of ROS concentration based on flow cytometry analysis with the use of H2DCFDA dye and HyPer, genetically encoded probe for hydrogen peroxide, are discussed. Keywords: Embryonic stem cells, Differentiated cells, ROS, Redox status, H2DCFDA, HyPer, Flow cytometry, Quantitative redox biology

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.

A boundary value approach for solving three-dimensional elliptic and hyperbolic partial differential equations.

Science.gov (United States)

Biala, T A; Jator, S N

2015-01-01

In this article, the boundary value method is applied to solve three dimensional elliptic and hyperbolic partial differential equations. The partial derivatives with respect to two of the spatial variables (y, z) are discretized using finite difference approximations to obtain a large system of ordinary differential equations (ODEs) in the third spatial variable (x). Using interpolation and collocation techniques, a continuous scheme is developed and used to obtain discrete methods which are applied via the Block unification approach to obtain approximations to the resulting large system of ODEs. Several test problems are investigated to elucidate the solution process.

A Dynamic BI–Orthogonal Field Equation Approach to Efficient Bayesian Inversion

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Tagade Piyush M.

2017-06-01

Full Text Available This paper proposes a novel computationally efficient stochastic spectral projection based approach to Bayesian inversion of a computer simulator with high dimensional parametric and model structure uncertainty. The proposed method is based on the decomposition of the solution into its mean and a random field using a generic Karhunen-Loève expansion. The random field is represented as a convolution of separable Hilbert spaces in stochastic and spatial dimensions that are spectrally represented using respective orthogonal bases. In particular, the present paper investigates generalized polynomial chaos bases for the stochastic dimension and eigenfunction bases for the spatial dimension. Dynamic orthogonality is used to derive closed-form equations for the time evolution of mean, spatial and the stochastic fields. The resultant system of equations consists of a partial differential equation (PDE that defines the dynamic evolution of the mean, a set of PDEs to define the time evolution of eigenfunction bases, while a set of ordinary differential equations (ODEs define dynamics of the stochastic field. This system of dynamic evolution equations efficiently propagates the prior parametric uncertainty to the system response. The resulting bi-orthogonal expansion of the system response is used to reformulate the Bayesian inference for efficient exploration of the posterior distribution. The efficacy of the proposed method is investigated for calibration of a 2D transient diffusion simulator with an uncertain source location and diffusivity. The computational efficiency of the method is demonstrated against a Monte Carlo method and a generalized polynomial chaos approach.

Pricing derivatives under Lévy models modern finite-difference and pseudo-differential operators approach

CERN Document Server

Itkin, Andrey

2017-01-01

This monograph presents a novel numerical approach to solving partial integro-differential equations arising in asset pricing models with jumps, which greatly exceeds the efficiency of existing approaches. The method, based on pseudo-differential operators and several original contributions to the theory of finite-difference schemes, is new as applied to the Lévy processes in finance, and is herein presented for the first time in a single volume. The results within, developed in a series of research papers, are collected and arranged together with the necessary background material from Lévy processes, the modern theory of finite-difference schemes, the theory of M-matrices and EM-matrices, etc., thus forming a self-contained work that gives the reader a smooth introduction to the subject. For readers with no knowledge of finance, a short explanation of the main financial terms and notions used in the book is given in the glossary. The latter part of the book demonstrates the efficacy of the method by solvin...

Quasi-Steady Evolution of Hillslopes in Layered Landscapes: An Analytic Approach

Science.gov (United States)

Glade, R. C.; Anderson, R. S.

2018-01-01

Landscapes developed in layered sedimentary or igneous rocks are common on Earth, as well as on other planets. Features such as hogbacks, exposed dikes, escarpments, and mesas exhibit resistant rock layers adjoining more erodible rock in tilted, vertical, or horizontal orientations. Hillslopes developed in the erodible rock are typically characterized by steep, linear-to-concave slopes or "ramps" mantled with material derived from the resistant layers, often in the form of large blocks. Previous work on hogbacks has shown that feedbacks between weathering and transport of the blocks and underlying soft rock can create relief over time and lead to the development of concave-up slope profiles in the absence of rilling processes. Here we employ an analytic approach, informed by numerical modeling and field data, to describe the quasi-steady state behavior of such rocky hillslopes for the full spectrum of resistant layer dip angles. We begin with a simple geometric analysis that relates structural dip to erosion rates. We then explore the mechanisms by which our numerical model of hogback evolution self-organizes to meet these geometric expectations, including adjustment of soil depth, erosion rates, and block velocities along the ramp. Analytical solutions relate easily measurable field quantities such as ramp length, slope, block size, and resistant layer dip angle to local incision rate, block velocity, and block weathering rate. These equations provide a framework for exploring the evolution of layered landscapes and pinpoint the processes for which we require a more thorough understanding to predict their evolution over time.

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

Directory of Open Access Journals (Sweden)

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.

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

An abstract approach to some spectral problems of direct sum differential operators

Directory of Open Access Journals (Sweden)

Maksim S. Sokolov

2003-07-01

Full Text Available In this paper, we study the common spectral properties of abstract self-adjoint direct sum operators, considered in a direct sum Hilbert space. Applications of such operators arise in the modelling of processes of multi-particle quantum mechanics, quantum field theory and, specifically, in multi-interval boundary problems of differential equations. We show that a direct sum operator does not depend in a straightforward manner on the separate operators involved. That is, on having a set of self-adjoint operators giving a direct sum operator, we show how the spectral representation for this operator depends on the spectral representations for the individual operators (the coordinate operators involved in forming this sum operator. In particular it is shown that this problem is not immediately solved by taking a direct sum of the spectral properties of the coordinate operators. Primarily, these results are to be applied to operators generated by a multi-interval quasi-differential system studied, in the earlier works of Ashurov, Everitt, Gesztezy, Kirsch, Markus and Zettl. The abstract approach in this paper indicates the need for further development of spectral theory for direct sum differential operators.

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

A quantitative approach to evolution of music and philosophy

International Nuclear Information System (INIS)

Vieira, Vilson; Fabbri, Renato; Travieso, Gonzalo; Oliveira Jr, Osvaldo N; Costa, Luciano da Fontoura

2012-01-01

The development of new statistical and computational methods is increasingly making it possible to bridge the gap between hard sciences and humanities. In this study, we propose an approach based on a quantitative evaluation of attributes of objects in fields of humanities, from which concepts such as dialectics and opposition are formally defined mathematically. As case studies, we analyzed the temporal evolution of classical music and philosophy by obtaining data for 8 features characterizing the corresponding fields for 7 well-known composers and philosophers, which were treated with multivariate statistics and pattern recognition methods. A bootstrap method was applied to avoid statistical bias caused by the small sample data set, with which hundreds of artificial composers and philosophers were generated, influenced by the 7 names originally chosen. Upon defining indices for opposition, skewness and counter-dialectics, we confirmed the intuitive analysis of historians in that classical music evolved according to a master–apprentice tradition, while in philosophy changes were driven by opposition. Though these case studies were meant only to show the possibility of treating phenomena in humanities quantitatively, including a quantitative measure of concepts such as dialectics and opposition, the results are encouraging for further application of the approach presented here to many other areas, since it is entirely generic. (paper)

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.

Paul Baillon presents the book "Differential manifolds: a basic approach for experimental physicists" | 25 March

CERN Multimedia

CERN Library

2014-01-01

Tuesday 25 March 2014 at 4 p.m. in the Library, bldg. 52-1-052 "Differential manifolds: a basic approach for experimental physicists" by Paul Baillon,  World Scientific, 2013, ISBN 978-981-4449-56-4. Differential manifold is the framework of particle physics and astrophysics nowadays. It is important for all research physicists to be accustomed to it, and even experimental physicists should be able to manipulate equations and expressions in this framework. This book gives a comprehensive description of the basics of differential manifold with a full proof of elements. A large part of the book is devoted to the basic mathematical concepts, which are all necessary for the development of the differential manifold. This book is self-consistent; it starts from first principles. The mathematical framework is the set theory with its axioms and its formal logic. No special knowledge is needed. Coffee will be served from 3.30 p.m.

The geoforecasting approach and long-term prediction of evolutive nuclide migration

International Nuclear Information System (INIS)

Peaudecerf, P.; D'Alessandro, M.; Canceill, M.; Fourniquet, J.; Godefroy, P.

1985-01-01

Safety analysis of long-lived radioactive waste repositories is dependent on natural site evolution scenarios. This is a complex problem given that there may be a large number of interdependent factors whose occurrence probability is usually very difficult to quantify. A major methodological effort has therefore been undertaken in this field under the terms of the Community's R and D programme. Research teams from the JRC and the BRGM tackled the problems by way of two complementary approaches; A critical analysis of existing methods was also undertaken at the request of the Commission. This paper sets out to summarize the work and, as far as possible, make a methodological evaluation

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.

Molecular polymorphism as a tool for differentiating ground beetles (Carabus species): application of ubiquitin PCR/SSCP analysis.

Science.gov (United States)

Boge, A; Gerstmeier, R; Einspanier, R

1994-11-01

Differentiation between Carabus species (ground beetle) and subspecies is difficult, although there have been extensive studies. To address this problem we have applied PCR in combination with SSCP analysis focussing on the evolutionally conservative ubiquitin gene to elaborate a new approach to molecular differentiation between species. We report that Carabidae possess an ubiquitin gene and that its gene has a multimeric structure. Differential SSCP analysis was performed with the monomeric form of the gene to generate a clear SSCP pattern. Such PCR/SSCP resulted in reproducible patterns throughout our experiments. Comparing different Carabus species (Carabus granulatus, C. irregularis, C. violaceus and C. auronitens) we could observe clear interspecies differences but no differences between genders. Some species showed some remarkable differences between the individuals. We suggest that the ubiquitin PCR-SSCP technique might be an additional tool for the differentiation of ground beetles.

The evolution of green jobs in Scotland: A hybrid approach

International Nuclear Information System (INIS)

Connolly, Kevin; Allan, Grant J; McIntyre, Stuart G

2016-01-01

In support of its ambitious target to reduce CO_2 emissions the Scottish Government is aiming to have the equivalent of 100% of Scottish electricity consumption generated from renewable sources by 2020. This is, at least in part, motivated by an expectation of subsequent employment growth in low carbon and renewable energy technologies; however there is no official data source to track employment in these areas. This has led to a variety of definitions, methodologies and alternative estimates being produced. Building on a recent study (Bishop and Brand, 2013) we develop a “hybrid” approach which combines the detail of “bottom-up” surveys with “top-down” trend data to produce estimates on employment in Low Carbon Environmental Goods and Services (LCEGS). We demonstrate this methodology to produce estimates for such employment in Scotland between 2004 and 2012. Our approach shows how survey and official sources can combine to produce a more timely measure of employment in LCEGS activities, assisting policymakers in tracking, consistently, developments. Applying our approach, we find that over this period employment in LCEGS in Scotland grew, but that this was more volatile than aggregate employment, and in particular that employment in this sector was particularly badly hit during the great recession. - Highlights: • A “hybrid” approach estimates green jobs from bottom-up detail and top-down data. • Illustrative results show the evolution of such jobs in Scotland from 2004 to 2012. • Method provides policymakers a timely measure of the jobs success of energy policy.

Integrated management system - management standards evolution and the IAEA new approach

International Nuclear Information System (INIS)

Oliveira, Dirceu Paulo de; Zouain, Desiree Moraes

2007-01-01

The management standards application began in military and nuclear areas towards the end of Second World War, when some westerns countries developed quality standards to improve their means to assess suppliers' conditions to assure their products conformance, which was increasingly complex and required a higher degree of reliability. Afterwards, the quality standards application was extended to the consumer market focused on consumers' requirements satisfaction. Coming along the society crescent concern about quality of life, other management standards were developed, such as those dealing with environmental and sustainable development, occupational health and safety, social accountability and so on. As a consequence, the management process became complex. The management system integrated form approach makes possible the compatibility of distinct and complementary interests from several functions and disciplines involved and supply the absence of the organizations' holistic approach. According to this integrated management approach, the Agency - 'International Atomic Energy Agency' (IAEA) - decided to review the structure of the 50-C-Q standard - 'Quality Assurance for Safety in Nuclear Power Plants and Other Nuclear Installations', from 1996, publishing in 2006 the new GS-R-3 standard - 'The Management System for Facilities and Activities - Safety Requirements'. This work presents a brief evolution of management standards and integrated management approach, showing the Agency's new vision concerning this issue with the GS-R-3 standard publication. (author)

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).

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...

Computational Experiment Approach to Controlled Evolution of Procurement Pattern in Cluster Supply Chain

Directory of Open Access Journals (Sweden)

Xiao Xue

2015-01-01

Full Text Available Companies have been aware of the benefits of developing Cluster Supply Chains (CSCs, and they are spending a great deal of time and money attempting to develop the new business pattern. Yet, the traditional techniques for identifying CSCs have strong theoretical antecedents, but seem to have little traction in the field. We believe this is because the standard techniques fail to capture evolution over time, nor provide useful intervention measures to reach goals. To address these problems, we introduce an agent-based modeling approach to evaluate CSCs. Taking collaborative procurement as research object, our approach is composed of three parts: model construction, model instantiation, and computational experiment. We use the approach to explore the service charging policy problem in collaborative procurement. Three kinds of service charging polices are compared in the same experiment environment. Finally, “Fixed Cost” is identified as the optimal policy under the stable market environment. The case study can help us to understand the workflow of applying the approach, and provide valuable decision support applications to industry.

An evolution of image source camera attribution approaches.

Science.gov (United States)

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

2016-05-01

researchers, are also critically analysed and further categorised into four different classes, namely, optical aberrations based, sensor camera fingerprints based, processing statistics based and processing regularities based, to present a classification. Furthermore, this paper aims to investigate the challenging problems, and the proposed strategies of such schemes based on the suggested taxonomy to plot an evolution of the source camera attribution approaches with respect to the subjective optimisation criteria over the last decade. The optimisation criteria were determined based on the strategies proposed to increase the detection accuracy, robustness and computational efficiency of source camera brand, model or device attribution. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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%.

Variational Approaches for the Existence of Multiple Periodic Solutions of Differential Delay Equations

Directory of Open Access Journals (Sweden)

Rong Cheng

2010-01-01

Full Text Available The existence of multiple periodic solutions of the following differential delay equation (=−((− is established by applying variational approaches directly, where ∈ℝ, ∈(ℝ,ℝ and >0 is a given constant. This means that we do not need to use Kaplan and Yorke's reduction technique to reduce the existence problem of the above equation to an existence problem for a related coupled system. Such a reduction method introduced first by Kaplan and Yorke in (1974 is often employed in previous papers to study the existence of periodic solutions for the above equation and its similar ones by variational approaches.

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

Modeling tree crown dynamics with 3D partial differential equations.

Science.gov (United States)

Beyer, Robert; Letort, Véronique; Cournède, Paul-Henry

2014-01-01

We characterize a tree's spatial foliage distribution by the local leaf area density. Considering this spatially continuous variable allows to describe the spatiotemporal evolution of the tree crown by means of 3D partial differential equations. These offer a framework to rigorously take locally and adaptively acting effects into account, notably the growth toward light. Biomass production through photosynthesis and the allocation to foliage and wood are readily included in this model framework. The system of equations stands out due to its inherent dynamic property of self-organization and spontaneous adaptation, generating complex behavior from even only a few parameters. The density-based approach yields spatially structured tree crowns without relying on detailed geometry. We present the methodological fundamentals of such a modeling approach and discuss further prospects and applications.

Differential diagnosis of nongap metabolic acidosis: value of a systematic approach.

Science.gov (United States)

Kraut, Jeffrey A; Madias, Nicolaos E

2012-04-01

Nongap metabolic acidosis is a common form of both acute and chronic metabolic acidosis. Because derangements in renal acid-base regulation are a common cause of nongap metabolic acidosis, studies to evaluate renal acidification often serve as the mainstay of differential diagnosis. However, in many cases, information obtained from the history and physical examination, evaluation of the electrolyte pattern (to determine if a nongap acidosis alone or a combined nongap and high anion gap metabolic acidosis is present), and examination of the serum potassium concentration (to characterize the disorder as hyperkalemic or hypokalemic in nature) is sufficient to make a presumptive diagnosis without more sophisticated studies. If this information proves insufficient, indirect estimates or direct measurement of urinary NH(4)(+) concentration, measurement of urine pH, and assessment of urinary HCO(3)(-) excretion can help in establishing the diagnosis. This review summarizes current information concerning the pathophysiology of this electrolyte pattern and the value and limitations of all of the diagnostic studies available. It also provides a systematic and cost-effective approach to the differential diagnosis of nongap metabolic acidosis.

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.

Modelling the optical turbulence boiling and its effect on finite-exposure differential image motion

Science.gov (United States)

Berdja, A.; Borgnino, J.

2007-07-01

It is usually accepted that whenever dealing with astronomical observation through the atmosphere, the optical turbulence temporal evolution can be sufficiently described with the so-called frozen turbulence hypothesis. In this model, turbulence is supposed to be equivalent to a series of solid phase screens that slide horizontally in front of the observation field of view. Experimental evidence shows, however, that an additional physical process must be taken into account when describing the temporal behaviour of the optical turbulence. In fact, while translating above the observer, turbulence undergoes a proper temporal evolution and affects differently the astronomical and, more specifically, the astrometric observations. The proper temporal evolution of the turbulence-induced optical turbulence observable quantities is here called the optical turbulence boiling. We are proposing through this paper a theoretical approach to the modelling of the optical turbulence temporal evolution when the turbulent layer horizontal translation and the optical turbulence boiling are both involved. The model we propose, as a working hypothesis though, has a direct relevance to differential astrometry because of its explicit dependence upon the optical turbulence temporal evolution. It can also be generalized to other techniques of high angular resolution astronomical observation through the atmospheric turbulence.

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

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 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.

A fixed point approach towards stability of delay differential equations with applications to neural networks

NARCIS (Netherlands)

Chen, Guiling

2013-01-01

This thesis studies asymptotic behavior and stability of determinsitic and stochastic delay differential equations. The approach used in this thesis is based on fixed point theory, which does not resort to any Liapunov function or Liapunov functional. The main contribution of this thesis is to study

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.

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)

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.

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.

Approaches for modeling within subject variability in pharmacometric count data analysis: dynamic inter-occasion variability and stochastic differential equations.

Science.gov (United States)

Deng, Chenhui; Plan, Elodie L; Karlsson, Mats O

2016-06-01

Parameter variation in pharmacometric analysis studies can be characterized as within subject parameter variability (WSV) in pharmacometric models. WSV has previously been successfully modeled using inter-occasion variability (IOV), but also stochastic differential equations (SDEs). In this study, two approaches, dynamic inter-occasion variability (dIOV) and adapted stochastic differential equations, were proposed to investigate WSV in pharmacometric count data analysis. These approaches were applied to published count models for seizure counts and Likert pain scores. Both approaches improved the model fits significantly. In addition, stochastic simulation and estimation were used to explore further the capability of the two approaches to diagnose and improve models where existing WSV is not recognized. The results of simulations confirmed the gain in introducing WSV as dIOV and SDEs when parameters vary randomly over time. Further, the approaches were also informative as diagnostics of model misspecification, when parameters changed systematically over time but this was not recognized in the structural model. The proposed approaches in this study offer strategies to characterize WSV and are not restricted to count data.

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.

A Comparison of Two-Stage Approaches for Fitting Nonlinear Ordinary Differential Equation Models with Mixed Effects.

Science.gov (United States)

Chow, Sy-Miin; Bendezú, Jason J; Cole, Pamela M; Ram, Nilam

2016-01-01

Several approaches exist for estimating the derivatives of observed data for model exploration purposes, including functional data analysis (FDA; Ramsay & Silverman, 2005 ), generalized local linear approximation (GLLA; Boker, Deboeck, Edler, & Peel, 2010 ), and generalized orthogonal local derivative approximation (GOLD; Deboeck, 2010 ). These derivative estimation procedures can be used in a two-stage process to fit mixed effects ordinary differential equation (ODE) models. While the performance and utility of these routines for estimating linear ODEs have been established, they have not yet been evaluated in the context of nonlinear ODEs with mixed effects. We compared properties of the GLLA and GOLD to an FDA-based two-stage approach denoted herein as functional ordinary differential equation with mixed effects (FODEmixed) in a Monte Carlo (MC) study using a nonlinear coupled oscillators model with mixed effects. Simulation results showed that overall, the FODEmixed outperformed both the GLLA and GOLD across all the embedding dimensions considered, but a novel use of a fourth-order GLLA approach combined with very high embedding dimensions yielded estimation results that almost paralleled those from the FODEmixed. We discuss the strengths and limitations of each approach and demonstrate how output from each stage of FODEmixed may be used to inform empirical modeling of young children's self-regulation.

Mass Media as Actor in Political Process: Evolution of the Western Approaches since the 1950s. (Part 1)

OpenAIRE

Гуторов, Владимир Александрович

2013-01-01

The author analyses evolution of western political science’s approaches to mass media and mass media’s role in political process in liberal democracies. The author focuses on theories of “Minimal Effect,” “Mediocracy,” “Effects Research,” “Tеxt Analysis,” “Use and Gratification Approach.” The author discusses A. Giddens’s structuration theory as the most elaborate approach to interpreting the role of mass media in the western political and social science.Key words: mass and political communic...

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

Does rapid evolution matter? Measuring the rate of contemporary evolution and its impacts on ecological dynamics.

Science.gov (United States)

Ellner, Stephen P; Geber, Monica A; Hairston, Nelson G

2011-06-01

Rapid contemporary evolution due to natural selection is common in the wild, but it remains uncertain whether its effects are an essential component of community and ecosystem structure and function. Previously we showed how to partition change in a population, community or ecosystem property into contributions from environmental and trait change, when trait change is entirely caused by evolution (Hairston et al. 2005). However, when substantial non-heritable trait change occurs (e.g. due to phenotypic plasticity or change in population structure) that approach can mis-estimate both contributions. Here, we demonstrate how to disentangle ecological impacts of evolution vs. non-heritable trait change by combining our previous approach with the Price Equation. This yields a three-way partitioning into effects of evolution, non-heritable phenotypic change and environment. We extend the approach to cases where ecological consequences of trait change are mediated through interspecific interactions. We analyse empirical examples involving fish, birds and zooplankton, finding that the proportional contribution of rapid evolution varies widely (even among different ecological properties affected by the same trait), and that rapid evolution can be important when it acts to oppose and mitigate phenotypic effects of environmental change. Paradoxically, rapid evolution may be most important when it is least evident. © 2011 Blackwell Publishing Ltd/CNRS.

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.

Differential manifolds

CERN Document Server

Kosinski, Antoni A

2007-01-01

The concepts of differential topology form the center of many mathematical disciplines such as differential geometry and Lie group theory. Differential Manifolds presents to advanced undergraduates and graduate students the systematic study of the topological structure of smooth manifolds. Author Antoni A. Kosinski, Professor Emeritus of Mathematics at Rutgers University, offers an accessible approach to both the h-cobordism theorem and the classification of differential structures on spheres.""How useful it is,"" noted the Bulletin of the American Mathematical Society, ""to have a single, sho

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.

Evolution of plant growth and defense in a continental introduction.

Science.gov (United States)

Agrawal, Anurag A; Hastings, Amy P; Bradburd, Gideon S; Woods, Ellen C; Züst, Tobias; Harvey, Jeffrey A; Bukovinszky, Tibor

2015-07-01

Substantial research has addressed adaptation of nonnative biota to novel environments, yet surprisingly little work has integrated population genetic structure and the mechanisms underlying phenotypic differentiation in ecologically important traits. We report on studies of the common milkweed Asclepias syriaca, which was introduced from North America to Europe over the past 400 years and which lacks most of its specialized herbivores in the introduced range. Using 10 populations from each continent grown in a common environment, we identified several growth and defense traits that have diverged, despite low neutral genetic differentiation between continents. We next developed a Bayesian modeling approach to account for relationships between molecular and phenotypic differences, confirming that continental trait differentiation was greater than expected from neutral genetic differentiation. We found evidence that growth-related traits adaptively diverged within and between continents. Inducible defenses triggered by monarch butterfly herbivory were substantially reduced in European populations, and this reduction in inducibility was concordant with altered phytohormonal dynamics, reduced plant growth, and a trade-off with constitutive investment. Freedom from the community of native and specialized herbivores may have favored constitutive over induced defense. Our replicated analysis of plant growth and defense, including phenotypically plastic traits, suggests adaptive evolution following a continental introduction.

Rethinking pedagogy for second-order differential equations: a simplified approach to understanding well-posed problems

Science.gov (United States)

Tisdell, Christopher C.

2017-07-01

Knowing an equation has a unique solution is important from both a modelling and theoretical point of view. For over 70 years, the approach to learning and teaching 'well posedness' of initial value problems (IVPs) for second- and higher-order ordinary differential equations has involved transforming the problem and its analysis to a first-order system of equations. We show that this excursion is unnecessary and present a direct approach regarding second- and higher-order problems that does not require an understanding of systems.

Dhat syndrome: Evolution of concept, current understanding, and need of an integrated approach

Directory of Open Access Journals (Sweden)

Sujita Kumar Kar

2015-01-01

Full Text Available Dhat syndrome has often been construed as a culture-bound sexual neurosis of the Indian subcontinent. Symptoms similar to that of Dhat syndrome has been described in other cultures across different time periods. The present paper looks at the evolution of the concept of Dhat syndrome in India. The review also takes an overview of the current understanding of this syndrome in terms of nosological status as a distinct entity and its "culture-bound" status. The narrative finally attempts to discuss the integrated approach for the treatment of this disorder.

Effects of extrinsic mortality on the evolution of aging: a stochastic modeling approach.

Directory of Open Access Journals (Sweden)

Maxim Nikolaievich Shokhirev

Full Text Available The evolutionary theories of aging are useful for gaining insights into the complex mechanisms underlying senescence. Classical theories argue that high levels of extrinsic mortality should select for the evolution of shorter lifespans and earlier peak fertility. Non-classical theories, in contrast, posit that an increase in extrinsic mortality could select for the evolution of longer lifespans. Although numerous studies support the classical paradigm, recent data challenge classical predictions, finding that high extrinsic mortality can select for the evolution of longer lifespans. To further elucidate the role of extrinsic mortality in the evolution of aging, we implemented a stochastic, agent-based, computational model. We used a simulated annealing optimization approach to predict which model parameters predispose populations to evolve longer or shorter lifespans in response to increased levels of predation. We report that longer lifespans evolved in the presence of rising predation if the cost of mating is relatively high and if energy is available in excess. Conversely, we found that dramatically shorter lifespans evolved when mating costs were relatively low and food was relatively scarce. We also analyzed the effects of increased predation on various parameters related to density dependence and energy allocation. Longer and shorter lifespans were accompanied by increased and decreased investments of energy into somatic maintenance, respectively. Similarly, earlier and later maturation ages were accompanied by increased and decreased energetic investments into early fecundity, respectively. Higher predation significantly decreased the total population size, enlarged the shared resource pool, and redistributed energy reserves for mature individuals. These results both corroborate and refine classical predictions, demonstrating a population-level trade-off between longevity and fecundity and identifying conditions that produce both

Rethinking Pedagogy for Second-Order Differential Equations: A Simplified Approach to Understanding Well-Posed Problems

Science.gov (United States)

Tisdell, Christopher C.

2017-01-01

Knowing an equation has a unique solution is important from both a modelling and theoretical point of view. For over 70 years, the approach to learning and teaching "well posedness" of initial value problems (IVPs) for second- and higher-order ordinary differential equations has involved transforming the problem and its analysis to a…

Ordinary differential equations with applications in molecular biology.

Science.gov (United States)

Ilea, M; Turnea, M; Rotariu, M

2012-01-01

Differential equations are of basic importance in molecular biology mathematics because many biological laws and relations appear mathematically in the form of a differential equation. In this article we presented some applications of mathematical models represented by ordinary differential equations in molecular biology. The vast majority of quantitative models in cell and molecular biology are formulated in terms of ordinary differential equations for the time evolution of concentrations of molecular species. Assuming that the diffusion in the cell is high enough to make the spatial distribution of molecules homogenous, these equations describe systems with many participating molecules of each kind. We propose an original mathematical model with small parameter for biological phospholipid pathway. All the equations system includes small parameter epsilon. The smallness of epsilon is relative to the size of the solution domain. If we reduce the size of the solution region the same small epsilon will result in a different condition number. It is clear that the solution for a smaller region is less difficult. We introduce the mathematical technique known as boundary function method for singular perturbation system. In this system, the small parameter is an asymptotic variable, different from the independent variable. In general, the solutions of such equations exhibit multiscale phenomena. Singularly perturbed problems form a special class of problems containing a small parameter which may tend to zero. Many molecular biology processes can be quantitatively characterized by ordinary differential equations. Mathematical cell biology is a very active and fast growing interdisciplinary area in which mathematical concepts, techniques, and models are applied to a variety of problems in developmental medicine and bioengineering. Among the different modeling approaches, ordinary differential equations (ODE) are particularly important and have led to significant advances

Teaching differential diagnosis in primary care using an inverted classroom approach: student satisfaction and gain in skills and knowledge.

Science.gov (United States)

Bösner, Stefan; Pickert, Julia; Stibane, Tina

2015-04-01

Differential diagnosis is a crucial skill for primary care physicians. General practice plays an increasing important role in undergraduate medical education. Via general practice, students may be presented with an overview of the whole spectrum of differential diagnosis in regard to common symptoms encountered in primary care. This project evaluated the impact of a blended learning program (using the inverted classroom approach) on student satisfaction and development of skills and knowledge. An elective seminar in differential diagnosis in primary care, which utilized an inverted classroom design, was offered to students. Evaluation followed a mixed methods design: participants completed a pre- and post-test, a questionnaire, and a focus group discussion. Interviews were transcribed verbatim and answers were grouped according to different themes. Test results were analysed using the Wilcoxon matched-pairs signed-ranks test. Participants (n = 17) rated the course concept very positively. Especially the inverted classroom approach was appreciated by all students, as it allowed for more time during the seminar to concentrate on interactive and practice based learning. Students (n = 16) showed a post-test significant overall gain in skills and knowledge of 33%. This study showed a positive effect of the inverted classroom approach on students' satisfaction and skills and knowledge. Further research is necessary in order to explore the potentials of this approach, especially the impact on development of clinical skills.

Perturbative evolution of particle orbits around Kerr black holes: time-domain calculation

Energy Technology Data Exchange (ETDEWEB)

Lopez-Aleman, Ramon [Physical Sciences Department, University of Puerto Rico-Rio Piedras, San Juan, PR 00931 (Puerto Rico); Khanna, Gaurav [Natural Science Division, Long Island University, Southampton, NY 11968 (United States); Pullin, Jorge [Department of Physics and Astronomy, Louisiana State University, 202 Nicholson Hall, Baton Rouge, LA 70803-4001 (United States)

2003-07-21

We consider the problem of the gravitational waves produced by a particle of negligible mass orbiting a Kerr black hole. We treat the Teukolsky perturbation equation in the time domain numerically as a 2 + 1 partial differential equation. We model the particle by smearing the singularities in the source term by the use of narrow Gaussian distributions. We have been able to reproduce earlier results for equatorial circular orbits that were computed using the frequency-domain formalism. The time-domain approach is however geared for a more general evolution, for instance of nearly geodesic orbits under the effects of radiation reaction.

Perturbative evolution of particle orbits around Kerr black holes: time-domain calculation

International Nuclear Information System (INIS)

Lopez-Aleman, Ramon; Khanna, Gaurav; Pullin, Jorge

2003-01-01

We consider the problem of the gravitational waves produced by a particle of negligible mass orbiting a Kerr black hole. We treat the Teukolsky perturbation equation in the time domain numerically as a 2 + 1 partial differential equation. We model the particle by smearing the singularities in the source term by the use of narrow Gaussian distributions. We have been able to reproduce earlier results for equatorial circular orbits that were computed using the frequency-domain formalism. The time-domain approach is however geared for a more general evolution, for instance of nearly geodesic orbits under the effects of radiation reaction

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.

Differential Learning as a Key Training Approach to Improve Creative and Tactical Behavior in Soccer.

Science.gov (United States)

Santos, Sara; Coutinho, Diogo; Gonçalves, Bruno; Schöllhorn, Wolfgang; Sampaio, Jaime; Leite, Nuno

2018-03-01

The aim of this study was to identify the effects of a differential-learning program, embedded in small-sided games, on the creative and tactical behavior of youth soccer players. Forty players from under-13 (U13) and under-15 (U15) were allocated into control and experimental groups and were tested using a randomized pretest to posttest design using small-sided games situations. The experimental group participated in a 5-month differential-learning program embodied in small-sided games situations, while the control group participated in a typical small-sided games training program. In-game creativity was assessed through notational analyses of the creative components, and the players' positional data were used to compute tactical-derived variables. The findings suggested that differential learning facilitated the development of creative components, mainly concerning attempts (U13, small; U15, small), versatility (U13, moderate; U15, small), and originality (U13, unclear; U15, small) of players' actions. Likewise, the differential-learning approach provided a decrease in fails during the game in both experimental groups (moderate). Moreover, differential learning seemed to favor regularity in pitch-positioning behavior for the distance between players' dyads (U13, small; U15, small), the distance to the team target (U13, moderate; U15, small), and the distance to the opponent target (U13, moderate; U15, small). The differential-learning program stressed creative and positional behavior in both age groups with a distinct magnitude of effects, with the U13 players demonstrating higher improvements over the U15 players. Overall, these findings confirmed that the technical variability promoted by differential learning nurtures regularity of positioning behavior.

A Cultural Evolution Approach to Digital Media.

Science.gov (United States)

Acerbi, Alberto

2016-01-01

Digital media have today an enormous diffusion, and their influence on the behavior of a vast part of the human population can hardly be underestimated. In this review I propose that cultural evolution theory, including both a sophisticated view of human behavior and a methodological attitude to modeling and quantitative analysis, provides a useful framework to study the effects and the developments of media in the digital age. I will first give a general presentation of the cultural evolution framework, and I will then introduce this more specific research program with two illustrative topics. The first topic concerns how cultural transmission biases, that is, simple heuristics such as "copy prestigious individuals" or "copy the majority," operate in the novel context of digital media. The existence of transmission biases is generally justified with their adaptivity in small-scale societies. How do they operate in an environment where, for example, prestigious individuals possess not-relevant skills, or popularity is explicitly quantified and advertised? The second aspect relates to fidelity of cultural transmission. Digitally-mediated interactions support cheap and immediate high-fidelity transmission, in opposition, for example, to oral traditions. How does this change the content that is more likely to spread? Overall, I suggest the usefulness of a "long view" to our contemporary digital environment, contextualized in cognitive science and cultural evolution theory, and I discuss how this perspective could help us to understand what is genuinely new and what is not.

A cultural evolution approach to digital media

Directory of Open Access Journals (Sweden)

Alberto Acerbi

2016-12-01

Full Text Available Digital media have today an enormous diffusion, and their influence on the behaviour of a vast part of the human population can hardly be underestimated. In this review I propose that cultural evolution theory, including both a sophisticated view of human behaviour and a methodological attitude to modelling and quantitative analysis, provides a useful framework to study the effects and the developments of media in the digital age. I will first give a general presentation of the cultural evolution framework, and I will then introduce this more specific research program with two illustrative topics.The first topic concerns how cultural transmission biases, that is, simple heuristics such as copy prestigious individuals or copy the majority, operate in the novel context of digital media. The existence of transmission biases is generally justified with their adaptivity in small-scale societies. How do they operate in an environment where, for example, prestigious individuals possess not-relevant skills, or popularity is explicitly quantified and advertised?The second aspect relates to fidelity of cultural transmission. Digitally-mediated interactions support cheap and immediate high-fidelity transmission, in opposition, for example, to oral traditions. How does this change the content that is more likely to spread? Overall, I suggest the usefulness of a long view to our contemporary digital environment, contextualised in cognitive science and cultural evolution theory, and I discuss how this perspective could help us to understand what is genuinely new and what is not.

A Cultural Evolution Approach to Digital Media

Science.gov (United States)

Acerbi, Alberto

2016-01-01

Digital media have today an enormous diffusion, and their influence on the behavior of a vast part of the human population can hardly be underestimated. In this review I propose that cultural evolution theory, including both a sophisticated view of human behavior and a methodological attitude to modeling and quantitative analysis, provides a useful framework to study the effects and the developments of media in the digital age. I will first give a general presentation of the cultural evolution framework, and I will then introduce this more specific research program with two illustrative topics. The first topic concerns how cultural transmission biases, that is, simple heuristics such as “copy prestigious individuals” or “copy the majority,” operate in the novel context of digital media. The existence of transmission biases is generally justified with their adaptivity in small-scale societies. How do they operate in an environment where, for example, prestigious individuals possess not-relevant skills, or popularity is explicitly quantified and advertised? The second aspect relates to fidelity of cultural transmission. Digitally-mediated interactions support cheap and immediate high-fidelity transmission, in opposition, for example, to oral traditions. How does this change the content that is more likely to spread? Overall, I suggest the usefulness of a “long view” to our contemporary digital environment, contextualized in cognitive science and cultural evolution theory, and I discuss how this perspective could help us to understand what is genuinely new and what is not. PMID:28018200

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...

Epidemiology of differentiated thyroid carcinoma in Morocco

International Nuclear Information System (INIS)

Ben Rais, N.; Ghfir, I.

2007-01-01

Full text: The incidence of thyroid cancer has been in linear increase for several decades because of the evolution and the generalization of the means of diagnosis. The objective of our work is to carry out an epidemiologic approach of differentiated thyroid carcinoma in our country, with an evaluation of the recent review of literature. Materials and methods: Our work consists of a retrospective analysis of 3144 cases of differentiated thyroid carcinoma, followed in nuclear medicine department of Ibn Sina hospital in Rabat for a period of 12 years. Our evaluation parameters related to the incidence of thyroid carcinoma are age of onset, sex, size of tumor, histological type, evolution and risk factors. Results: The incidence of differentiated thyroid carcinoma was estimated in our country at 0,8 by 100000 inhabitants per year. The sex ratio was evaluated at 3,5/1 whereas the average age was 42,5 years. Papillary carcinoma represented 65,58 %, well differentiated follicular carcinoma 21,92 % and moderately differentiated carcinoma to 12,5%. The microcarcinomas were estimated at 8,1 %. The size of tumor at the time of diagnosis was higher than 2 cm in 70% of cases. The lymphatic extension was objectified in 47,6 % of papillary forms and 3,5 % of follicular carcinoma. Remote metastasis was found in 0,8 % of cases between 30 and 40 years and 4,71 % after the age of 40 years. Discussion: The cancer of thyroid is not very frequent. Indeed, its annual incidence throughout the world is 0,5 to 10 by 100.000 inhabitants with a clear female prevalence. The majority of cases occur between 15 and 50 years. This cancer is very rare in children less than 15 years. In Morocco, the incidence has increased these last decades like many countries in the world (0,8 by 100.000 inhabitants per year). We note, in addition, an increase in the prevalence of papillary microcarcinoma seeing the improvement of early tracking methods (echography, fine needle aspiration biopsy). The risk

Sociohistorical evolution of judo: introductory approaches

Directory of Open Access Journals (Sweden)

Orozimbo Cordeiro Júnior

2008-06-01

Full Text Available The sociohistorical evolution of judo provided by the research project Methodology for teaching judo from the critical–excelling stance is discussed in this article. The aim of the project was to establish a plan for systematizing judo as body culture constituent and scholastic knowledge of physical education. The ancillary pedagogical material is constituted by an introduction, objectives, contents, teaching methodology and evaluation system.

A new approach to Catalan numbers using differential equations

Science.gov (United States)

Kim, D. S.; Kim, T.

2017-10-01

In this paper, we introduce two differential equations arising from the generating function of the Catalan numbers which are `inverses' to each other in a certain sense. From these differential equations, we obtain some new and explicit identities for Catalan and higher-order Catalan numbers. In addition, by other means than differential equations, we also derive some interesting identities involving Catalan numbers which are of arithmetic and combinatorial nature.

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

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.

Explaining the Evolution of Poverty

DEFF Research Database (Denmark)

Arndt, Channing; Hussain, Azhar; Jones, Edward Samuel

2012-01-01

We provide a comprehensive approach for analyzing the evolution of poverty using Mozambique as a case study. Bringing together data from disparate sources, we develop a novel “back-casting” framework that links a dynamic computable general equilibrium model to a micro-simulation poverty module....... This framework provides a new approach to explaining and decomposing the evolution of poverty, as well as to examining rigorously the coherence between poverty, economic growth, and inequality outcomes. Finally, various simple but useful and rarely-applied approaches to considering regional changes in poverty...

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...

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.

Modeling spatial navigation in the presence of dynamic obstacles: a differential games approach.

Science.gov (United States)

Darekar, Anuja; Goussev, Valery; McFadyen, Bradford J; Lamontagne, Anouk; Fung, Joyce

2018-03-01

Obstacle circumvention strategies can be shaped by the dynamic interaction of an individual (evader) and an obstacle (pursuer). We have developed a mathematical model with predictive and emergent components, using experimental data from seven healthy young adults walking toward a target while avoiding collision with a stationary or moving obstacle (approaching head-on, or diagonally 30° left or right) in a virtual environment. Two linear properties from the predictive component enable the evader to predict the minimum distance between itself and the obstacle at all times, including the future intersection of trajectories. The emergent component uses the classical differential games model to solve for an optimal circumvention while reaching the target, wherein the locomotor strategy is influenced by the obstacle, target, and the evader velocity. Both model components were fitted to a different set of experimental data obtained from five poststroke and healthy participants to derive the minimum predicted distance (predictive component) and obstacle influence dimensions (emergent component) during circumvention. Minimum predicted distance between evader and pursuer was kept constant when the evader was closest to the obstacle in all participants. Obstacle influence dimensions varied depending on obstacle approach condition and preferred side of circumvention, reflecting differences in locomotor strategies between poststroke and healthy individuals. Additionally, important associations between model outputs and observed experimental outcomes were found. The model, supported by experimental data, suggests that both predictive and emergent processes can shape obstacle circumvention strategies in healthy and poststroke individuals. NEW & NOTEWORTHY Obstacle circumvention during goal-directed locomotion is modeled with a new mathematical approach comprising both predictive and emergent elements. The major novelty is using differential games solutions to illustrate the

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.

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.

Fitting Analysis using Differential evolution Optimization (FADO):. Spectral population synthesis through genetic optimization under self-consistency boundary conditions

Science.gov (United States)

Gomes, J. M.; Papaderos, P.

2017-07-01

The goal of population spectral synthesis (pss; also referred to as inverse, semi-empirical evolutionary- or fossil record approach) is to decipher from the spectrum of a galaxy the mass, age and metallicity of its constituent stellar populations. This technique, which is the reverse of but complementary to evolutionary synthesis, has been established as fundamental tool in extragalactic research. It has been extensively applied to large spectroscopic data sets, notably the SDSS, leading to important insights into the galaxy assembly history. However, despite significant improvements over the past decade, all current pss codes suffer from two major deficiencies that inhibit us from gaining sharp insights into the star-formation history (SFH) of galaxies and potentially introduce substantial biases in studies of their physical properties (e.g., stellar mass, mass-weighted stellar age and specific star formation rate). These are I) the neglect of nebular emission in spectral fits, consequently; II) the lack of a mechanism that ensures consistency between the best-fitting SFH and the observed nebular emission characteristics of a star-forming (SF) galaxy (e.g., hydrogen Balmer-line luminosities and equivalent widths-EWs, shape of the continuum in the region around the Balmer and Paschen jump). In this article, we present fado (Fitting Analysis using Differential evolution Optimization) - a conceptually novel, publicly available pss tool with the distinctive capability of permitting identification of the SFH that reproduces the observed nebular characteristics of a SF galaxy. This so-far unique self-consistency concept allows us to significantly alleviate degeneracies in current spectral synthesis, thereby opening a new avenue to the exploration of the assembly history of galaxies. The innovative character of fado is further augmented by its mathematical foundation: fado is the first pss code employing genetic differential evolution optimization. This, in conjunction

Toward Documentation of Program Evolution

DEFF Research Database (Denmark)

Vestdam, Thomas; Nørmark, Kurt

2005-01-01

The documentation of a program often falls behind the evolution of the program source files. When this happens it may be attractive to shift the documentation mode from updating the documentation to documenting the evolution of the program. This paper describes tools that support the documentatio....... It is concluded that our approach can help revitalize older documentation, and that discovery of the fine grained program evolution steps help the programmer in documenting the evolution of the program....

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.

A cultural evolution approach to digital media

NARCIS (Netherlands)

Acerbi, A.

2016-01-01

Digital media have today an enormous diffusion, and their influence on the behaviour of a vast part of the human population can hardly be underestimated. In this review I propose that cultural evolution theory, including both a sophisticated view of human behaviour and a methodological attitude to

Differential DNA Methylation Analysis without a Reference Genome

Directory of Open Access Journals (Sweden)

Johanna Klughammer

2015-12-01

Full Text Available Genome-wide DNA methylation mapping uncovers epigenetic changes associated with animal development, environmental adaptation, and species evolution. To address the lack of high-throughput methods for DNA methylation analysis in non-model organisms, we developed an integrated approach for studying DNA methylation differences independent of a reference genome. Experimentally, our method relies on an optimized 96-well protocol for reduced representation bisulfite sequencing (RRBS, which we have validated in nine species (human, mouse, rat, cow, dog, chicken, carp, sea bass, and zebrafish. Bioinformatically, we developed the RefFreeDMA software to deduce ad hoc genomes directly from RRBS reads and to pinpoint differentially methylated regions between samples or groups of individuals (http://RefFreeDMA.computational-epigenetics.org. The identified regions are interpreted using motif enrichment analysis and/or cross-mapping to annotated genomes. We validated our method by reference-free analysis of cell-type-specific DNA methylation in the blood of human, cow, and carp. In summary, we present a cost-effective method for epigenome analysis in ecology and evolution, which enables epigenome-wide association studies in natural populations and species without a reference genome.

Redox environment in stem and differentiated cells: A quantitative approach.

Science.gov (United States)

Lyublinskaya, O G; Ivanova, Ju S; Pugovkina, N A; Kozhukharova, I V; Kovaleva, Z V; Shatrova, A N; Aksenov, N D; Zenin, V V; Kaulin, Yu A; Gamaley, I A; Nikolsky, N N

2017-08-01

Stem cells are believed to maintain a specific intracellular redox status through a combination of enhanced removal capacity and limited production of ROS. In the present study, we challenge this assumption by developing a quantitative approach for the analysis of the pro- and antioxidant ability of human embryonic stem cells in comparison with their differentiated descendants, as well as adult stem and non-stem cells. Our measurements showed that embryonic stem cells are characterized by low ROS level, low rate of extracellular hydrogen peroxide removal and low threshold for peroxide-induced cytotoxicity. However, biochemical normalization of these parameters to cell volume/protein leads to matching of normalized values in stem and differentiated cells and shows that tested in the present study cells (human embryonic stem cells and their fibroblast-like progenies, adult mesenchymal stem cells, lymphocytes, HeLa) maintain similar intracellular redox status. Based on these observations, we propose to use ROS concentration averaged over the cell volume instead of ROS level as a measure of intracellular redox balance. We show that attempts to use ROS level for comparative analysis of redox status of morphologically different cells could lead to false conclusions. Methods for the assessment of ROS concentration based on flow cytometry analysis with the use of H 2 DCFDA dye and HyPer, genetically encoded probe for hydrogen peroxide, are discussed. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Modeling of microstructure evolution in direct metal laser sintering: A phase field approach

Science.gov (United States)

Nandy, Jyotirmoy; Sarangi, Hrushikesh; Sahoo, Seshadev

2017-02-01

Direct Metal Laser Sintering (DMLS) is a new technology in the field of additive manufacturing, which builds metal parts in a layer by layer fashion directly from the powder bed. The process occurs within a very short time period with rapid solidification rate. Slight variations in the process parameters may cause enormous change in the final build parts. The physical and mechanical properties of the final build parts are dependent on the solidification rate which directly affects the microstructure of the material. Thus, the evolving of microstructure plays a vital role in the process parameters optimization. Nowadays, the increase in computational power allows for direct simulations of microstructures during materials processing for specific manufacturing conditions. In this study, modeling of microstructure evolution of Al-Si-10Mg powder in DMLS process was carried out by using a phase field approach. A MATLAB code was developed to solve the set of phase field equations, where simulation parameters include temperature gradient, laser scan speed and laser power. The effects of temperature gradient on microstructure evolution were studied and found that with increase in temperature gradient, the dendritic tip grows at a faster rate.

Nonlinear Evolution of Alfvenic Wave Packets

Science.gov (United States)

Buti, B.; Jayanti, V.; Vinas, A. F.; Ghosh, S.; Goldstein, M. L.; Roberts, D. A.; Lakhina, G. S.; Tsurutani, B. T.

1998-01-01

Alfven waves are a ubiquitous feature of the solar wind. One approach to studying the evolution of such waves has been to study exact solutions to approximate evolution equations. Here we compare soliton solutions of the Derivative Nonlinear Schrodinger evolution equation (DNLS) to solutions of the compressible MHD equations.

A Simple Approach to Derive a Novel N-Soliton Solution for a (3+1)-Dimensional Nonlinear Evolution Equation

International Nuclear Information System (INIS)

Wu Jianping

2010-01-01

Based on the Hirota bilinear form, a simple approach without employing the standard perturbation technique, is presented for constructing a novel N-soliton solution for a (3+1)-dimensional nonlinear evolution equation. Moreover, the novel N-soliton solution is shown to have resonant behavior with the aid of Mathematica. (general)

Linear differential equations to solve nonlinear mechanical problems: A novel approach

OpenAIRE

Nair, C. Radhakrishnan

2004-01-01

Often a non-linear mechanical problem is formulated as a non-linear differential equation. A new method is introduced to find out new solutions of non-linear differential equations if one of the solutions of a given non-linear differential equation is known. Using the known solution of the non-linear differential equation, linear differential equations are set up. The solutions of these linear differential equations are found using standard techniques. Then the solutions of the linear differe...

A Hybrid Genetic Algorithm Approach for Optimal Power Flow

Directory of Open Access Journals (Sweden)

Sydulu Maheswarapu

2011-08-01

Full Text Available This paper puts forward a reformed hybrid genetic algorithm (GA based approach to the optimal power flow. In the approach followed here, continuous variables are designed using real-coded GA and discrete variables are processed as binary strings. The outcomes are compared with many other methods like simple genetic algorithm (GA, adaptive genetic algorithm (AGA, differential evolution (DE, particle swarm optimization (PSO and music based harmony search (MBHS on a IEEE30 bus test bed, with a total load of 283.4 MW. Its found that the proposed algorithm is found to offer lowest fuel cost. The proposed method is found to be computationally faster, robust, superior and promising form its convergence characteristics.

A stochastic differential equations approach for the description of helium bubble size distributions in irradiated metals

Energy Technology Data Exchange (ETDEWEB)

Seif, Dariush, E-mail: dariush.seif@iwm-extern.fraunhofer.de [Fraunhofer Institut für Werkstoffmechanik, Freiburg 79108 (Germany); Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, CA 90095-1597 (United States); Ghoniem, Nasr M. [Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, CA 90095-1597 (United States)

2014-12-15

A rate theory model based on the theory of nonlinear stochastic differential equations (SDEs) is developed to estimate the time-dependent size distribution of helium bubbles in metals under irradiation. Using approaches derived from Itô’s calculus, rate equations for the first five moments of the size distribution in helium–vacancy space are derived, accounting for the stochastic nature of the atomic processes involved. In the first iteration of the model, the distribution is represented as a bivariate Gaussian distribution. The spread of the distribution about the mean is obtained by white-noise terms in the second-order moments, driven by fluctuations in the general absorption and emission of point defects by bubbles, and fluctuations stemming from collision cascades. This statistical model for the reconstruction of the distribution by its moments is coupled to a previously developed reduced-set, mean-field, rate theory model. As an illustrative case study, the model is applied to a tungsten plasma facing component under irradiation. Our findings highlight the important role of stochastic atomic fluctuations on the evolution of helium–vacancy cluster size distributions. It is found that when the average bubble size is small (at low dpa levels), the relative spread of the distribution is large and average bubble pressures may be very large. As bubbles begin to grow in size, average bubble pressures decrease, and stochastic fluctuations have a lessened effect. The distribution becomes tighter as it evolves in time, corresponding to a more uniform bubble population. The model is formulated in a general way, capable of including point defect drift due to internal temperature and/or stress gradients. These arise during pulsed irradiation, and also during steady irradiation as a result of externally applied or internally generated non-homogeneous stress fields. Discussion is given into how the model can be extended to include full spatial resolution and how the

A stochastic differential equations approach for the description of helium bubble size distributions in irradiated metals

Science.gov (United States)

Seif, Dariush; Ghoniem, Nasr M.

2014-12-01

A rate theory model based on the theory of nonlinear stochastic differential equations (SDEs) is developed to estimate the time-dependent size distribution of helium bubbles in metals under irradiation. Using approaches derived from Itô's calculus, rate equations for the first five moments of the size distribution in helium-vacancy space are derived, accounting for the stochastic nature of the atomic processes involved. In the first iteration of the model, the distribution is represented as a bivariate Gaussian distribution. The spread of the distribution about the mean is obtained by white-noise terms in the second-order moments, driven by fluctuations in the general absorption and emission of point defects by bubbles, and fluctuations stemming from collision cascades. This statistical model for the reconstruction of the distribution by its moments is coupled to a previously developed reduced-set, mean-field, rate theory model. As an illustrative case study, the model is applied to a tungsten plasma facing component under irradiation. Our findings highlight the important role of stochastic atomic fluctuations on the evolution of helium-vacancy cluster size distributions. It is found that when the average bubble size is small (at low dpa levels), the relative spread of the distribution is large and average bubble pressures may be very large. As bubbles begin to grow in size, average bubble pressures decrease, and stochastic fluctuations have a lessened effect. The distribution becomes tighter as it evolves in time, corresponding to a more uniform bubble population. The model is formulated in a general way, capable of including point defect drift due to internal temperature and/or stress gradients. These arise during pulsed irradiation, and also during steady irradiation as a result of externally applied or internally generated non-homogeneous stress fields. Discussion is given into how the model can be extended to include full spatial resolution and how the

A stochastic differential equations approach for the description of helium bubble size distributions in irradiated metals

International Nuclear Information System (INIS)

Seif, Dariush; Ghoniem, Nasr M.

2014-01-01

A rate theory model based on the theory of nonlinear stochastic differential equations (SDEs) is developed to estimate the time-dependent size distribution of helium bubbles in metals under irradiation. Using approaches derived from Itô’s calculus, rate equations for the first five moments of the size distribution in helium–vacancy space are derived, accounting for the stochastic nature of the atomic processes involved. In the first iteration of the model, the distribution is represented as a bivariate Gaussian distribution. The spread of the distribution about the mean is obtained by white-noise terms in the second-order moments, driven by fluctuations in the general absorption and emission of point defects by bubbles, and fluctuations stemming from collision cascades. This statistical model for the reconstruction of the distribution by its moments is coupled to a previously developed reduced-set, mean-field, rate theory model. As an illustrative case study, the model is applied to a tungsten plasma facing component under irradiation. Our findings highlight the important role of stochastic atomic fluctuations on the evolution of helium–vacancy cluster size distributions. It is found that when the average bubble size is small (at low dpa levels), the relative spread of the distribution is large and average bubble pressures may be very large. As bubbles begin to grow in size, average bubble pressures decrease, and stochastic fluctuations have a lessened effect. The distribution becomes tighter as it evolves in time, corresponding to a more uniform bubble population. The model is formulated in a general way, capable of including point defect drift due to internal temperature and/or stress gradients. These arise during pulsed irradiation, and also during steady irradiation as a result of externally applied or internally generated non-homogeneous stress fields. Discussion is given into how the model can be extended to include full spatial resolution and how the

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

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

Directory of Open Access Journals (Sweden)

B Vinoth Kumar

2017-07-01

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

Differential structures in C*-algebras

Indian Academy of Sciences (India)

Second and higher order differential structure defined by a closed symmetric operator. Differential ... (1) General theory – differential seminorm approach and growth conditions ...... S is dual of a Banach space, and the weak ∗-topology on A2.

Genetic characterization, species differentiation and detection of Fasciola spp. by molecular approaches.

Science.gov (United States)

Ai, Lin; Chen, Mu-Xin; Alasaad, Samer; Elsheikha, Hany M; Li, Juan; Li, Hai-Long; Lin, Rui-Qing; Zou, Feng-Cai; Zhu, Xing-Quan; Chen, Jia-Xu

2011-06-10

Liver flukes belonging to the genus Fasciola are among the causes of foodborne diseases of parasitic etiology. These parasites cause significant public health problems and substantial economic losses to the livestock industry. Therefore, it is important to definitively characterize the Fasciola species. Current phenotypic techniques fail to reflect the full extent of the diversity of Fasciola spp. In this respect, the use of molecular techniques to identify and differentiate Fasciola spp. offer considerable advantages. The advent of a variety of molecular genetic techniques also provides a powerful method to elucidate many aspects of Fasciola biology, epidemiology, and genetics. However, the discriminatory power of these molecular methods varies, as does the speed and ease of performance and cost. There is a need for the development of new methods to identify the mechanisms underpinning the origin and maintenance of genetic variation within and among Fasciola populations. The increasing application of the current and new methods will yield a much improved understanding of Fasciola epidemiology and evolution as well as more effective means of parasite control. Herein, we provide an overview of the molecular techniques that are being used for the genetic characterization, detection and genotyping of Fasciola spp..

Helicopter approach capability using the differential global positioning system. M.S. Thesis

Science.gov (United States)

Kaufmann, David N.

1993-01-01

The results of flight tests to determine the feasibility of using the Global Positioning System (GPS) in the differential mode (DGPS) to provide high accuracy, precision navigation, and guidance for helicopter approaches to landing are presented. The airborne DGPS receiver and associated equipment is installed in a NASA UH-60 Black Hawk helicopter. The ground-based DGPS reference receiver is located at a surveyed test site and is equipped with a real-time VHF data link to transmit correction information to the airborne DGPS receiver. The corrected airborne DGPS information, together with the preset approach geometry, is used to calculate guidance commands which are sent to the aircraft's approach guidance instruments. The use of DGPS derived guidance for helicopter approaches to landing is evaluated by comparing the DGPS data with the laser tracker truth data. Both standard (3 deg) and steep (6 deg and 9 deg) glideslope straight-in approaches were flown. DGPS positioning accuracy based on a time history analysis of the entire approach was 0.2 m (mean) +/- 1.8 m (2 sigma) laterally and -2.0 m (mean) +/- 3.5 m (2 sigma) vertically for 3 deg glideslope approaches, -0.1 m (mean) +/- 1.5 m (2 sigma) laterally and -1.1 m (mean) +/- 3.5 m (2 sigma) vertically for 6 deg glideslope approaches and 0.2 m (mean) +/- 1.3 m (2 sigma) laterally and -1.0 m (mean) +/- 2.8 m (2 sigma) vertically for 9 deg glideslope approaches. DGPS positioning accuracy at the 200 ft decision height (DH) on a standard 3 deg slideslope approach was 0.3 m (mean) +/- 1.5 m (2 sigma) laterally and -2.3 m (mean) +/- 1.6 m (2 sigma) vertically. These errors indicate that the helicopter position based on DGPS guidance satisfies the International Civil Aviation Organization (ICAO) Category 1 (CAT 1) lateral and vertical navigational accuracy requirements.

Mialgias: Approaches to differential diagnosis, treatment

Directory of Open Access Journals (Sweden)

Nadezhda Aleksandrovna Shostak

2013-01-01

Full Text Available Differential diagnosis in muscle pains often presents great difficulties so all existing signs of the disease should be carefully considered to make its diagnosis and to prescribe adequate therapy. The paper considers the causes of muscle pains, laboratory and instrumental studies (immunological tests, determination of the level of specific muscular enzymes, primarily creatine phosphokinase – CPK, etc., and the main reasons for enhanced plasma CPK activity. It also describes acute and chronic mialgias associated with enhanced plasma CPK activity, as well as diseases in which mialgias are related to the normal level of CPK, myofascial syndrome (MFS and fibromyalgia (FM in particular. The characteristic features of MFS are given in its diagnostic criteria. It is stated that a differential diagnosis should be made between MFS and major muscle pain-associated abnormalities, such as polymyalgia rheumatica, FM, etc. Diagnosticcriteria for polymyalgia rheumatica are given. A MFS treatment algorithm is presented. Local exposure methods applied to altered musculoligamentous structures in combination with myorelaxants and non-steroidal anti-inflammatory drugs assume paramount importance in MFS.

Trickle-down evolution: an approach to getting major evolutionary adaptive changes into textbooks and curricula.

Science.gov (United States)

Padian, Kevin

2008-08-01

Although contemporary high school and college textbooks of biology generally cover the principles and data of microevolution (genetic and populational change) and speciation rather well, coverage of what is known of the major changes in evolution (macroevolution), and how the evidence is understood is generally poor to nonexistent. It is critical to improve this because acceptance of evolution by the American public rests on the understanding of how we know what we know about the emergence of major new taxonomic groups, and about their adaptations, behaviors, and ecologies in geologic time. An efficient approach to this problem is to improve the illustrations in college textbooks to show the consilience of different lines of fossil, morphological, and molecular evidence mapped on phylogenies. Such "evograms" will markedly improve traditional illustrations of phylogenies, "menageries," and "companatomies." If "evograms" are installed at the college level, the basic principles and evidence of macroevolution will be more likely taught in K-12, thus providing an essential missing piece in biological education.

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.

Equilibrium approach in the derivation of differential equations for ...

African Journals Online (AJOL)

In this paper, the differential equations of Mindlin plates are derived from basic principles by simultaneous satisfaction of the differential equations of equilibrium, the stress-strain laws and the strain-displacement relations for isotropic, homogenous linear elastic materials. Equilibrium method was adopted in the derivation.

An Efficient Numerical Approach for Solving Nonlinear Coupled Hyperbolic Partial Differential Equations with Nonlocal Conditions

Directory of Open Access Journals (Sweden)

A. H. Bhrawy

2014-01-01

Full Text Available One of the most important advantages of collocation method is the possibility of dealing with nonlinear partial differential equations (PDEs as well as PDEs with variable coefficients. A numerical solution based on a Jacobi collocation method is extended to solve nonlinear coupled hyperbolic PDEs with variable coefficients subject to initial-boundary nonlocal conservation conditions. This approach, based on Jacobi polynomials and Gauss-Lobatto quadrature integration, reduces solving the nonlinear coupled hyperbolic PDEs with variable coefficients to a system of nonlinear ordinary differential equation which is far easier to solve. In fact, we deal with initial-boundary coupled hyperbolic PDEs with variable coefficients as well as initial-nonlocal conditions. Using triangular, soliton, and exponential-triangular solutions as exact solutions, the obtained results show that the proposed numerical algorithm is efficient and very accurate.

Two-dimensional gel human protein databases offer a systematic approach to the study of cell proliferation and differentiation

DEFF Research Database (Denmark)

Celis, julio E.; Gesser, Borbala; Dejgaard, Kurt

1989-01-01

Human cellular protein databases have been established using computer-analyzed 2D gel electrophoresis. These databases, which include information on various properties of proteins, offer a global approach to the study of regulation of cell proliferation and differentiation. Furthermore, thanks...

Two dimensional gel human protein databases offer a systematic approach to the study of cell proliferation and differentiation

DEFF Research Database (Denmark)

Celis, J E; Gesser, B; Dejgaard, K

1989-01-01

Human cellular protein databases have been established using computer-analyzed 2D gel electrophoresis. These databases, which include information on various properties of proteins, offer a global approach to the study of regulation of cell proliferation and differentiation. Furthermore, thanks to...

Respiratory consequences of prematurity: evolution of a diagnosis and development of a comprehensive approach.

Science.gov (United States)

Maitre, Nathalie L; Ballard, Roberta A; Ellenberg, Jonas H; Davis, Stephanie D; Greenberg, James M; Hamvas, Aaron; Pryhuber, Gloria S

2015-05-01

Bronchopulmonary dysplasia (BPD) is the most common respiratory consequence of premature birth and contributes to significant short- and long-term morbidity, mortality and resource utilization. Initially defined as a radiographic, clinical and histopathological entity, the chronic lung disease known as BPD has evolved as obstetrical and neonatal care have improved the survival of lower gestational age infants. Now, definitions based on the need for supplementary oxygen at 28 days and/or 36 weeks provide a useful reference point in the neonatal intensive-care unit (NICU), but are no longer based on histopathological findings, and are neither designed to predict longer term respiratory consequences nor to study the evolution of a multifactorial disease. The aims of this review are to critically examine the evolution of the diagnosis of BPD and the challenges inherent to current classifications. We found that the increasing use of respiratory support strategies that administer ambient air without supplementary oxygen confounds oxygen-based definitions of BPD. Furthermore, lack of reproducible, genetic, biochemical and physiological biomarkers limits the ability to identify an impending BPD for early intervention, quantify disease severity for standardized classification and approaches and reliably predict the long-term outcomes. More comprehensive, multidisciplinary approaches to overcome these challenges involve longitudinal observation of extremely preterm infants, not only those with BPD, using genetic, environmental, physiological and clinical data as well as large databases of patient samples. The Prematurity and Respiratory Outcomes Program (PROP) will provide such a framework to address these challenges through high-resolution characterization of both NICU and post-NICU discharge outcomes.

Online evolution of robot behaviour

OpenAIRE

Silva, Fernando Goulart da

2012-01-01

Tese de mestrado em Engenharia Informática (Interação e Conhecimento), apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2012 In this dissertation, we propose and evaluate two novel approaches to the online synthesis of neural controllers for autonomous robots. The first approach is odNEAT, an online, distributed, and decentralized version of NeuroEvolution of Augmenting Topologies (NEAT). odNEAT is an algorithm for online evolution in groups of embodied agents such a...

equilibrium approach in thederivation of differential equations

African Journals Online (AJOL)

user

DEPT OF CIVIL ENGINEERING, ENUGU STATE UNIVERSITY OF SCIENCE & TECHNOLOGY ... In this paper, the differential equations of Mindlin plates are derived from basic principles by ..... Journal of Applied Mechanics, pages 31-38.

A Self-Adaptive Evolutionary Approach to the Evolution of Aesthetic Maps for a RTS Game

OpenAIRE

Lara-Cabrera, Raúl; Cotta, Carlos; Fernández-Leiva, Antonio J.

2014-01-01

Procedural content generation (PCG) is a research eld on the rise,with numerous papers devoted to this topic. This paper presents a PCG method based on a self-adaptive evolution strategy for the automatic generation of maps for the real-time strategy (RTS) game PlanetWars. These maps are generated in order to ful ll the aesthetic preferences of the user, as implied by her assessment of a collection of maps used as training set. A topological approach is used for the characterization of th...

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

Statistical approach to thermal evolution of neutron stars

International Nuclear Information System (INIS)

Beznogov, M V; Yakovlev, D G

2015-01-01

Studying thermal evolution of neutron stars (NSs) is one of a few ways to investigate the properties of superdense matter in their cores. We study the cooling of isolated NSs (INSs) and deep crustal heating of transiently accreting NSs in X-ray transients (XRTs, binary systems with low-mass companions). Currently, nearly 50 of such NSs are observed, and one can apply statistical methods to analyze the whole dataset. We propose a method for such analysis based on thermal evolution theory for individual stars and on averaging the results over NS mass distributions. We calculate the distributions of INSs and accreting NSs (ANSs) in XRTs over cooling and heating diagrams respectively. Comparing theoretical and observational distributions one can infer information on physical properties of superdense matter and on mass distributions of INSs and ANSs. (paper)

Evolution of transoral approaches, endoscopic endonasal approaches, and reduction strategies for treatment of craniovertebral junction pathology: a treatment algorithm update.

Science.gov (United States)

Dlouhy, Brian J; Dahdaleh, Nader S; Menezes, Arnold H

2015-04-01

The craniovertebral junction (CVJ), or the craniocervical junction (CCJ) as it is otherwise known, houses the crossroads of the CNS and is composed of the occipital bone that surrounds the foramen magnum, the atlas vertebrae, the axis vertebrae, and their associated ligaments and musculature. The musculoskeletal organization of the CVJ is unique and complex, resulting in a wide range of congenital, developmental, and acquired pathology. The refinements of the transoral approach to the CVJ by the senior author (A.H.M.) in the late 1970s revolutionized the treatment of CVJ pathology. At the same time, a physiological approach to CVJ management was adopted at the University of Iowa Hospitals and Clinics in 1977 based on the stability and motion dynamics of the CVJ and the site of encroachment, incorporating the transoral approach for irreducible ventral CVJ pathology. Since then, approaches and techniques to treat ventral CVJ lesions have evolved. In the last 40 years at University of Iowa Hospitals and Clinics, multiple approaches to the CVJ have evolved and a better understanding of CVJ pathology has been established. In addition, new reduction strategies that have diminished the need to perform ventral decompressive approaches have been developed and implemented. In this era of surgical subspecialization, to properly treat complex CVJ pathology, the CVJ specialist must be trained in skull base transoral and endoscopic endonasal approaches, pediatric and adult CVJ spine surgery, and must understand and be able to treat the complex CSF dynamics present in CVJ pathology to provide the appropriate, optimal, and tailored treatment strategy for each individual patient, both child and adult. This is a comprehensive review of the history and evolution of the transoral approaches, extended transoral approaches, endoscopie assisted transoral approaches, endoscopie endonasal approaches, and CVJ reduction strategies. Incorporating these advancements, the authors update the

The evolution of Lean organizations

OpenAIRE

Serafinas, Dalius; Ruželė, Darius

2014-01-01

Remiantis evoliucijos tyrimų modeliais bei autorių sudarytu evoliucionuojančios organizacijos modeliu,straipsnyje analizuojama Lean vadybos metodologija ir tiriama, kaip evoliucionuoja ją įgyvendinančios Lietuvosgamybinės organizacijos. The purpose of this paper is to examine the evolution of Lean organizations.Design/methodology/approach: a conceptual literature on the evolution of species, organisms and organizations was reviewed and an original model (framework) of the evolution of orga...

On the Legal Issues of Teaching Evolution in Public Schools

Science.gov (United States)

Hermann, Ronald S.

2013-01-01

In order to effectively teach evolution to all students, even those resistant to learning evolution, science teachers may question the extent to which religion can legally be discussed in the public high school science classroom. Evolution is taught from a variety of approaches, each of which has legal implications. Four approaches to teaching…

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.

Intelligent Resource Management for Local Area Networks: Approach and Evolution

Science.gov (United States)

Meike, Roger

1988-01-01

The Data Management System network is a complex and important part of manned space platforms. Its efficient operation is vital to crew, subsystems and experiments. AI is being considered to aid in the initial design of the network and to augment the management of its operation. The Intelligent Resource Management for Local Area Networks (IRMA-LAN) project is concerned with the application of AI techniques to network configuration and management. A network simulation was constructed employing real time process scheduling for realistic loads, and utilizing the IEEE 802.4 token passing scheme. This simulation is an integral part of the construction of the IRMA-LAN system. From it, a causal model is being constructed for use in prediction and deep reasoning about the system configuration. An AI network design advisor is being added to help in the design of an efficient network. The AI portion of the system is planned to evolve into a dynamic network management aid. The approach, the integrated simulation, project evolution, and some initial results are described.

Identifying Country-Specific Cultures of Physics Education: A differential item functioning approach

Science.gov (United States)

Mesic, Vanes

2012-11-01

In international large-scale assessments of educational outcomes, student achievement is often represented by unidimensional constructs. This approach allows for drawing general conclusions about country rankings with respect to the given achievement measure, but it typically does not provide specific diagnostic information which is necessary for systematic comparisons and improvements of educational systems. Useful information could be obtained by exploring the differences in national profiles of student achievement between low-achieving and high-achieving countries. In this study, we aimed to identify the relative weaknesses and strengths of eighth graders' physics achievement in Bosnia and Herzegovina in comparison to the achievement of their peers from Slovenia. For this purpose, we ran a secondary analysis of Trends in International Mathematics and Science Study (TIMSS) 2007 data. The student sample consisted of 4,220 students from Bosnia and Herzegovina and 4,043 students from Slovenia. After analysing the cognitive demands of TIMSS 2007 physics items, the correspondent differential item functioning (DIF)/differential group functioning contrasts were estimated. Approximately 40% of items exhibited large DIF contrasts, indicating significant differences between cultures of physics education in Bosnia and Herzegovina and Slovenia. The relative strength of students from Bosnia and Herzegovina showed to be mainly associated with the topic area 'Electricity and magnetism'. Classes of items which required the knowledge of experimental method, counterintuitive thinking, proportional reasoning and/or the use of complex knowledge structures proved to be differentially easier for students from Slovenia. In the light of the presented results, the common practice of ranking countries with respect to universally established cognitive categories seems to be potentially misleading.

Computationally efficient statistical differential equation modeling using homogenization

Science.gov (United States)

Hooten, Mevin B.; Garlick, Martha J.; Powell, James A.

2013-01-01

Statistical models using partial differential equations (PDEs) to describe dynamically evolving natural systems are appearing in the scientific literature with some regularity in recent years. Often such studies seek to characterize the dynamics of temporal or spatio-temporal phenomena such as invasive species, consumer-resource interactions, community evolution, and resource selection. Specifically, in the spatial setting, data are often available at varying spatial and temporal scales. Additionally, the necessary numerical integration of a PDE may be computationally infeasible over the spatial support of interest. We present an approach to impose computationally advantageous changes of support in statistical implementations of PDE models and demonstrate its utility through simulation using a form of PDE known as “ecological diffusion.” We also apply a statistical ecological diffusion model to a data set involving the spread of mountain pine beetle (Dendroctonus ponderosae) in Idaho, USA.

Coastal Foredune Evolution, Part 2: Modeling Approaches for Meso-Scale Morphologic Evolution

Science.gov (United States)

2017-03-01

for Meso-Scale Morphologic Evolution by Margaret L. Palmsten1, Katherine L. Brodie2, and Nicholas J. Spore2 PURPOSE: This Coastal and Hydraulics ...managers because foredunes provide ecosystem services and can reduce storm damages to coastal infrastructure, both of which increase the resiliency...MS 2 U.S. Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, Duck, NC ERDC/CHL CHETN-II-57 March 2017 2 models of

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.

Mapping the evolution of scientific fields.

Science.gov (United States)

Herrera, Mark; Roberts, David C; Gulbahce, Natali

2010-05-04

Despite the apparent cross-disciplinary interactions among scientific fields, a formal description of their evolution is lacking. Here we describe a novel approach to study the dynamics and evolution of scientific fields using a network-based analysis. We build an idea network consisting of American Physical Society Physics and Astronomy Classification Scheme (PACS) numbers as nodes representing scientific concepts. Two PACS numbers are linked if there exist publications that reference them simultaneously. We locate scientific fields using a community finding algorithm, and describe the time evolution of these fields over the course of 1985-2006. The communities we identify map to known scientific fields, and their age depends on their size and activity. We expect our approach to quantifying the evolution of ideas to be relevant for making predictions about the future of science and thus help to guide its development.

Biochemical approaches to C4 photosynthesis evolution studies: the case of malic enzymes decarboxylases.

Science.gov (United States)

Saigo, Mariana; Tronconi, Marcos A; Gerrard Wheeler, Mariel C; Alvarez, Clarisa E; Drincovich, María F; Andreo, Carlos S

2013-11-01

C4 photosynthesis enables the capture of atmospheric CO2 and its concentration at the site of RuBisCO, thus counteracting the negative effects of low atmospheric levels of CO2 and high atmospheric levels of O2 (21 %) on photosynthesis. The evolution of this complex syndrome was a multistep process. It did not occur by simply recruiting pre-exiting components of the pathway from C3 ancestors which were already optimized for C4 function. Rather it involved modifications in the kinetics and regulatory properties of pre-existing isoforms of non-photosynthetic enzymes in C3 plants. Thus, biochemical studies aimed at elucidating the functional adaptations of these enzymes are central to the development of an integrative view of the C4 mechanism. In the present review, the most important biochemical approaches that we currently use to understand the evolution of the C4 isoforms of malic enzyme are summarized. It is expected that this information will help in the rational design of the best decarboxylation processes to provide CO2 for RuBisCO in engineering C3 species to perform C4 photosynthesis.

Backward-stochastic-differential-equation approach to modeling of gene expression.

Science.gov (United States)

Shamarova, Evelina; Chertovskih, Roman; Ramos, Alexandre F; Aguiar, Paulo

2017-03-01

In this article, we introduce a backward method to model stochastic gene expression and protein-level dynamics. The protein amount is regarded as a diffusion process and is described by a backward stochastic differential equation (BSDE). Unlike many other SDE techniques proposed in the literature, the BSDE method is backward in time; that is, instead of initial conditions it requires the specification of end-point ("final") conditions, in addition to the model parametrization. To validate our approach we employ Gillespie's stochastic simulation algorithm (SSA) to generate (forward) benchmark data, according to predefined gene network models. Numerical simulations show that the BSDE method is able to correctly infer the protein-level distributions that preceded a known final condition, obtained originally from the forward SSA. This makes the BSDE method a powerful systems biology tool for time-reversed simulations, allowing, for example, the assessment of the biological conditions (e.g., protein concentrations) that preceded an experimentally measured event of interest (e.g., mitosis, apoptosis, etc.).

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.

Interplay between chaperones and protein disorder promotes the evolution of protein networks.

Directory of Open Access Journals (Sweden)

Sebastian Pechmann

2014-06-01

Full Text Available Evolution is driven by mutations, which lead to new protein functions but come at a cost to protein stability. Non-conservative substitutions are of interest in this regard because they may most profoundly affect both function and stability. Accordingly, organisms must balance the benefit of accepting advantageous substitutions with the possible cost of deleterious effects on protein folding and stability. We here examine factors that systematically promote non-conservative mutations at the proteome level. Intrinsically disordered regions in proteins play pivotal roles in protein interactions, but many questions regarding their evolution remain unanswered. Similarly, whether and how molecular chaperones, which have been shown to buffer destabilizing mutations in individual proteins, generally provide robustness during proteome evolution remains unclear. To this end, we introduce an evolutionary parameter λ that directly estimates the rate of non-conservative substitutions. Our analysis of λ in Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens sequences reveals how co- and post-translationally acting chaperones differentially promote non-conservative substitutions in their substrates, likely through buffering of their destabilizing effects. We further find that λ serves well to quantify the evolution of intrinsically disordered proteins even though the unstructured, thus generally variable regions in proteins are often flanked by very conserved sequences. Crucially, we show that both intrinsically disordered proteins and highly re-wired proteins in protein interaction networks, which have evolved new interactions and functions, exhibit a higher λ at the expense of enhanced chaperone assistance. Our findings thus highlight an intricate interplay of molecular chaperones and protein disorder in the evolvability of protein networks. Our results illuminate the role of chaperones in enabling protein evolution, and underline the

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

A Bayesian approach to the evolution of metabolic networks on a phylogeny.

Directory of Open Access Journals (Sweden)

Aziz Mithani

2010-08-01

Full Text Available The availability of genomes of many closely related bacteria with diverse metabolic capabilities offers the possibility of tracing metabolic evolution on a phylogeny relating the genomes to understand the evolutionary processes and constraints that affect the evolution of metabolic networks. Using simple (independent loss/gain of reactions or complex (incorporating dependencies among reactions stochastic models of metabolic evolution, it is possible to study how metabolic networks evolve over time. Here, we describe a model that takes the reaction neighborhood into account when modeling metabolic evolution. The model also allows estimation of the strength of the neighborhood effect during the course of evolution. We present Gibbs samplers for sampling networks at the internal node of a phylogeny and for estimating the parameters of evolution over a phylogeny without exploring the whole search space by iteratively sampling from the conditional distributions of the internal networks and parameters. The samplers are used to estimate the parameters of evolution of metabolic networks of bacteria in the genus Pseudomonas and to infer the metabolic networks of the ancestral pseudomonads. The results suggest that pathway maps that are conserved across the Pseudomonas phylogeny have a stronger neighborhood structure than those which have a variable distribution of reactions across the phylogeny, and that some Pseudomonas lineages are going through genome reduction resulting in the loss of a number of reactions from their metabolic networks.

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.

Differentiating Approaches to Diabetes Self-Management of Multi-Ethnic Rural Older Adults at the Extremes of Glycemic Control

Science.gov (United States)

Brewer-Lowry, Aleshia Nichol; Arcury, Thomas A.; Bell, Ronny A.; Quandt, Sara A.

2010-01-01

Purpose of the Study: This study identified approaches to diabetes self-management that differentiate persons with well-controlled from poorly controlled diabetes. Previous research has focused largely on persons participating in self-management interventions. Design and Methods: In-depth qualitative interviews were conducted with 48 adults, drawn…

Partial differential equation-based approach for empirical mode decomposition: application on image analysis.

Science.gov (United States)

Niang, Oumar; Thioune, Abdoulaye; El Gueirea, Mouhamed Cheikh; Deléchelle, Eric; Lemoine, Jacques

2012-09-01

The major problem with the empirical mode decomposition (EMD) algorithm is its lack of a theoretical framework. So, it is difficult to characterize and evaluate this approach. In this paper, we propose, in the 2-D case, the use of an alternative implementation to the algorithmic definition of the so-called "sifting process" used in the original Huang's EMD method. This approach, especially based on partial differential equations (PDEs), was presented by Niang in previous works, in 2005 and 2007, and relies on a nonlinear diffusion-based filtering process to solve the mean envelope estimation problem. In the 1-D case, the efficiency of the PDE-based method, compared to the original EMD algorithmic version, was also illustrated in a recent paper. Recently, several 2-D extensions of the EMD method have been proposed. Despite some effort, 2-D versions for EMD appear poorly performing and are very time consuming. So in this paper, an extension to the 2-D space of the PDE-based approach is extensively described. This approach has been applied in cases of both signal and image decomposition. The obtained results confirm the usefulness of the new PDE-based sifting process for the decomposition of various kinds of data. Some results have been provided in the case of image decomposition. The effectiveness of the approach encourages its use in a number of signal and image applications such as denoising, detrending, or texture analysis.

Genetic characterization, species differentiation and detection of Fasciola spp. by molecular approaches

Directory of Open Access Journals (Sweden)

Li Hai-Long

2011-06-01

Full Text Available Abstract Liver flukes belonging to the genus Fasciola are among the causes of foodborne diseases of parasitic etiology. These parasites cause significant public health problems and substantial economic losses to the livestock industry. Therefore, it is important to definitively characterize the Fasciola species. Current phenotypic techniques fail to reflect the full extent of the diversity of Fasciola spp. In this respect, the use of molecular techniques to identify and differentiate Fasciola spp. offer considerable advantages. The advent of a variety of molecular genetic techniques also provides a powerful method to elucidate many aspects of Fasciola biology, epidemiology, and genetics. However, the discriminatory power of these molecular methods varies, as does the speed and ease of performance and cost. There is a need for the development of new methods to identify the mechanisms underpinning the origin and maintenance of genetic variation within and among Fasciola populations. The increasing application of the current and new methods will yield a much improved understanding of Fasciola epidemiology and evolution as well as more effective means of parasite control. Herein, we provide an overview of the molecular techniques that are being used for the genetic characterization, detection and genotyping of Fasciola spp..

FUNCTIONAL FECAL INCONTINENCE IN CHILDREN (DIFFERENTIAL DIAGNOSTICS AND TREATMENT APPROACHES

Directory of Open Access Journals (Sweden)

V.N. Kopeikin

2009-01-01

Full Text Available Impairment of the intestinal content continence, a common clinical situation with various pathogenetic mechanisms. Disease proceeds with the child’s maladjustment events. 33 cases of encopresis have been analyzed. This condition has various clinical and instrumental diagnostic criteria depending on the origin which simplifies differential diagnostics. Using a differential diagnostics table helps expedite the process of making a diagnosis and hence start an adequate treatment in a timely manner.Key words: encopresis, differential diagnostics, treatment, children.

An alternative approach for modeling strength differential effect in sheet metals with symmetric yield functions

Science.gov (United States)

Kurukuri, Srihari; Worswick, Michael J.

2013-12-01

An alternative approach is proposed to utilize symmetric yield functions for modeling the tension-compression asymmetry commonly observed in hcp materials. In this work, the strength differential (SD) effect is modeled by choosing separate symmetric plane stress yield functions (for example, Barlat Yld 2000-2d) for the tension i.e., in the first quadrant of principal stress space, and compression i.e., third quadrant of principal stress space. In the second and fourth quadrants, the yield locus is constructed by adopting interpolating functions between uniaxial tensile and compressive stress states. In this work, different interpolating functions are chosen and the predictive capability of each approach is discussed. The main advantage of this proposed approach is that the yield locus parameters are deterministic and relatively easy to identify when compared to the Cazacu family of yield functions commonly used for modeling SD effect observed in hcp materials.

Income differential of female labor in Southern Brazil: dual approach

Directory of Open Access Journals (Sweden)

Rita de Cassia Garcia Margonato

2014-06-01

Full Text Available This study analyzes the formation and income differential of female labor in Southern Brazil in 2002 and 2009 based on microdata from the National Sample Survey (PNAD.The methodology is to estimate the selection and wages equations using the Heckman's Sample Selection Model (1979. For the measurement of the female income differential in commerce, industry and domestic service, compared to income of women in the service sector it is applied an adaptation of the Oaxaca-Blinder Decomposition (1973 adapted by Jann (2008. It was confirmed the hypothesis that segmentation occurs in the female labor market in Southern Brazil because the income differential cannot be explained only by personal attributes (productive or not and by formal work. There are specificities in the sectors (sector effect determining the income differential of women´s income in the labor market, moreover the sector effect explained 33% of the wage differential observed in industry, also explained 29% in the commerce and 35% of the female income gaps when compared to the service sector, which is considered as in advantage.

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...

Introduction to differentiable manifolds

CERN Document Server

Auslander, Louis

2009-01-01

The first book to treat manifold theory at an introductory level, this text surveys basic concepts in the modern approach to differential geometry. The first six chapters define and illustrate differentiable manifolds, and the final four chapters investigate the roles of differential structures in a variety of situations.Starting with an introduction to differentiable manifolds and their tangent spaces, the text examines Euclidean spaces, their submanifolds, and abstract manifolds. Succeeding chapters explore the tangent bundle and vector fields and discuss their association with ordinary diff

A topological approach to the existence of solutions for nonlinear differential equations with piecewise constant argument

International Nuclear Information System (INIS)

Huang Zhenkun; Wang Xinghua; Xia Yonghui

2009-01-01

In this paper, we investigate qualitative behavior of nonlinear differential equations with piecewise constant argument (PCA). A topological approach of Wazewski-type which gives sufficient conditions to guarantee that the graph of at least one solution stays in a given domain is formulated. Moreover, our results are also suitable for a class of general system of discrete equations. By using a regular polyfacial set, we apply our developed topological approach to cellular neural networks (CNNs) with PCA. Some new results are attained to reveal dynamic behavior of CNNs with PCA and discrete-time CNNs. Finally, an illustrative example of CNNs with PCA shows usefulness and effectiveness of our results.

Mapping the evolution of scientific ideas

Energy Technology Data Exchange (ETDEWEB)

Roberts, David C [Los Alamos National Laboratory; Herrera, Mark [UNIV OF MARYLAND; Gulbahce, Natali [NORTHEASTERN UNIV

2008-01-01

The importance of interdisciplinary research is ever increasing as challenging world problems require expertise across diverse fields. Despite the apparent conceptual boundaries of scientific fields, a formal description for their evolution is lacking. Here we describe a novel approach to study the dynamics and evolution of scientific ideas and fields using a network-based analysis. We build a idea network consisting of American Physical Society Pacs numbers as nodes representing scientific concepts. Two Pacs numbers are linked in the network if there exist publications that reference them simultaneously. We locate scientific fields using an overlapping community finding algorithm and describe the time evolution of these fields using a community evolution method over the course of 1985-2006. We find that the communities we find map to scientific fields, the lifetime of these fields strongly depends on their size, impact and activity, and longest living communities are least volatile. The described approach to quantify the evolution of ideas is expected to be relevant in making predictions about the future of science and how to guide its development.

Differentiation in Online Retailing from a Consumer’s Perspective – A Repertory Grid Approach

DEFF Research Database (Denmark)

Kellner, Julian; Wagner, Gerhard; Zielke, Stephan

2014-01-01

Due to the highly competitive nature of the online retail environment, differentiation strategies are import for online retailers to gain competitive advantages and achieve a unique positioning on the market. However, little is known about perceptual dimensions used by consumers to make...... a distinction between online retailers. The present study addresses this research gap by using a repertory grid approach to identify points of difference between online retailers from a consumer’s perspective. The results have important implications for positioning strategies of online retailers and research...... on online store formats....

Mega-phylogeny approach for comparative biology: an alternative to supertree and supermatrix approaches

OpenAIRE

Smith, Stephen A; Beaulieu, Jeremy M; Donoghue, Michael J

2009-01-01

Abstract Background Biology has increasingly recognized the necessity to build and utilize larger phylogenies to address broad evolutionary questions. Large phylogenies have facilitated the discovery of differential rates of molecular evolution between trees and herbs. They have helped us understand the diversification patterns of mammals as well as the patterns of seed evolution. In addition to these broad evolutionary questions there is increasing awareness of the importance of large phylog...

Coastline evolution of Portuguese low-lying sandy coast in the last 50 years: an integrated approach

Science.gov (United States)

Ponte Lira, Cristina; Nobre Silva, Ana; Taborda, Rui; Freire de Andrade, Cesar

2016-06-01

Regional/national-scale information on coastline rates of change and trends is extremely valuable, but these studies are scarce. A widely accepted standardized methodology for analysing long-term coastline change has been difficult to achieve, but it is essential to conduct an integrated and holistic approach to coastline evolution and hence support coastal management actions. Additionally, databases providing knowledge on coastline evolution are of key importance to support both coastal management experts and users.The main objective of this work is to present the first systematic, national-scale and consistent long-term coastline evolution data of Portuguese mainland low-lying sandy coasts.The methodology used quantifies coastline evolution using a unique and robust coastline indicator (the foredune toe), which is independent of short-term changes.The dataset presented comprises (1) two polyline sets, mapping the 1958 and 2010 sandy beach-dune system coastline, both optimized for working at 1 : 50 000 scale or smaller; (2) one polyline set representing long-term change rates between 1958 and 2010, each estimated at 250 m; and (3) a table with minimum, maximum and mean of evolution rates for sandy beach-dune system coastline. All science data produced here are openly accessible at https://doi.pangaea.de/10.1594/PANGAEA.859136 and can be used in other studies.Results show beach erosion as the dominant trend, with a mean change rate of -0.24 ± 0.01 m year-1 for all mainland Portuguese beach-dune systems. Although erosion is dominant, this evolution is variable in signal and magnitude in different coastal sediment cells and also within each cell. The most relevant beach erosion issues were found in the coastal stretches of Espinho-Torreira and Costa Nova-Praia de Mira, Cova da Gala-Leirosa, and Cova do Vapor-Costa da Caparica. The coastal segments Minho River-Nazaré and Costa da Caparica adjacent to the coast exhibit a history of major human interventions

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.

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

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

Software architecture evolution

DEFF Research Database (Denmark)

Barais, Olivier; Le Meur, Anne-Francoise; Duchien, Laurence

2008-01-01

Software architectures must frequently evolve to cope with changing requirements, and this evolution often implies integrating new concerns. Unfortunately, when the new concerns are crosscutting, existing architecture description languages provide little or no support for this kind of evolution....... The software architect must modify multiple elements of the architecture manually, which risks introducing inconsistencies. This chapter provides an overview, comparison and detailed treatment of the various state-of-the-art approaches to describing and evolving software architectures. Furthermore, we discuss...... one particular framework named Tran SAT, which addresses the above problems of software architecture evolution. Tran SAT provides a new element in the software architecture descriptions language, called an architectural aspect, for describing new concerns and their integration into an existing...

Artificial boundary conditions for certain evolution PDEs with cubic nonlinearity for non-compactly supported initial data

Science.gov (United States)

Vaibhav, V.

2011-04-01

The paper addresses the problem of constructing non-reflecting boundary conditions for two types of one dimensional evolution equations, namely, the cubic nonlinear Schrödinger (NLS) equation, ∂tu+Lu-iχ|u|2u=0 with L≡-i∂x2, and the equation obtained by letting L≡∂x3. The usual restriction of compact support of the initial data is relaxed by allowing it to have a constant amplitude along with a linear phase variation outside a compact domain. We adapt the pseudo-differential approach developed by Antoine et al. (2006) [5] for the NLS equation to the second type of evolution equation, and further, extend the scheme to the aforementioned class of initial data for both of the equations. In addition, we discuss efficient numerical implementation of our scheme and produce the results of several numerical experiments demonstrating its effectiveness.

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.

A non-deterministic approach to forecasting the trophic evolution of lakes

Directory of Open Access Journals (Sweden)

Roberto Bertoni

2016-03-01

Full Text Available Limnologists have long recognized that one of the goals of their discipline is to increase its predictive capability. In recent years, the role of prediction in applied ecology escalated, mainly due to man’s increased ability to change the biosphere. Such alterations often came with unplanned and noticeably negative side effects mushrooming from lack of proper attention to long-term consequences. Regression analysis of common limnological parameters has been successfully applied to develop predictive models relating the variability of limnological parameters to specific key causes. These approaches, though, are biased by the requirement of a priori cause-relation assumption, oftentimes difficult to find in the complex, nonlinear relationships entangling ecological data. A set of quantitative tools that can help addressing current environmental challenges avoiding such restrictions is currently being researched and developed within the framework of ecological informatics. One of these approaches attempting to model the relationship between a set of inputs and known outputs, is based on genetic algorithms and programming (GP. This stochastic optimization tool is based on the process of evolution in natural systems and was inspired by a direct analogy to sexual reproduction and Charles Darwin’s principle of natural selection. GP works through genetic algorithms that use selection and recombination operators to generate a population of equations. Thanks to a 25-years long time-series of regular limnological data, the deep, large, oligotrophic Lake Maggiore (Northern Italy is the ideal case study to test the predictive ability of GP. Testing of GP on the multi-year data series of this lake has allowed us to verify the forecasting efficacy of the models emerging from GP application. In addition, this non-deterministic approach leads to the discovery of non-obvious relationships between variables and enabled the formulation of new stochastic models.

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.

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...

A population memetics approach to cultural evolution in chaffinch song: meme diversity within populations.

Science.gov (United States)

Lynch, A; Baker, A J

1993-04-01

We investigated cultural evolution in populations of common chaffinches (Fringilla coelebs) in the Atlantic islands (Azores, Madeira, Canaries) and neighboring continental regions (Morocco, Iberia) by employing a population memetics approach. To quantify variability within populations, we used the concept of a song meme, defined as a single syllable or a series of linked syllables capable of being transmitted. The frequency distribution of memes within populations generally fit a neutral model in which there is an equilibrium between mutation, migration, and drift, which suggests that memes are functionally equivalent. The diversity of memes of single syllables is significantly greater in the Azores compared to all other regions, consistent with higher population densities of chaffinches there. On the other hand, memes of two to five syllables have greater diversity in Atlantic island and Moroccan populations compared to their Iberian counterparts. This higher diversity emanates from a looser syntax and increased recombination in songs, presumably because of relaxed selection for distinctive songs in these peripheral and depauperate avifaunas. We urge comparative population memetic studies of other species of songbirds and predict that they will lead to a formulation of a general theory for the cultural evolution of bird song analogous to population genetics theory for biological traits.

Regional approaches to the management of patients with advanced, radioactive iodine-refractory differentiated thyroid carcinoma.

Science.gov (United States)

Brose, Marcia S; Smit, Johannes; Capdevila, Jaume; Elisei, Rossella; Nutting, Christopher; Pitoia, Fabian; Robinson, Bruce; Schlumberger, Martin; Shong, Young Kee; Takami, Hiroshi

2012-09-01

For patients with advanced, radioactive iodine-refractory differentiated thyroid cancer, current treatment guidelines recommend clinical trial enrollment or small-molecule kinase inhibitor therapy. However, details of patient management vary between countries depending on trial availability and national regulatory policies. Insufficient clinical trial data and variable disease characteristics challenge the creation of universal guidelines, and treatment plans often reflect regional influences. A multidisciplinary, multiregional panel of experts met to discuss regional approaches to managing patients with advanced, radioactive iodine-refractory differentiated thyroid cancer and the potential impact of emerging therapies on current treatment strategies. Despite process-oriented regional differences, the decision-making strategies were similar. Multidisciplinary teams used to manage high-risk patients varied in composition across regions, particularly regarding the responsible physician's specialty. Cytotoxic chemotherapy was viewed as limited in clinical benefit, and targeted agents as attractive, based on promising data. Panel members support clinical trial enrollment as the preferred treatment strategy for managing these patients.

Selective phosphorylation during early macrophage differentiation

KAUST Repository

Zhang, Huoming

2015-08-26

The differentiation of macrophages from monocytes is a tightly controlled and complex biological process. Although numerous studies have been conducted using biochemical approaches or global gene/gene profiling, the mechanisms of the early stages of differentiation remain unclear. Here we used SILAC-based quantitative proteomics approach to perform temporal phosphoproteome profiling of early macrophage differentiation. We identified a large set of phosphoproteins and grouped them as PMA-regulated and non-regulated phosphoproteins in the early stages of differentiation. Further analysis of the PMA-regulated phosphoproteins revealed that transcriptional suppression, cytoskeletal reorganization and cell adhesion were among the most significantly activated pathways. Some key involved regulators of these pathways are mTOR, MYB, STAT1 and CTNNB. Moreover, we were able to classify the roles and activities of several transcriptional factors during different differentiation stages and found that E2F is likely to be an important regulator during the relatively late stages of differentiation. This study provides the first comprehensive picture of the dynamic phosphoproteome during myeloid cells differentiation, and identifies potential molecular targets in leukemic cells.

Chemical evolution of galaxies

CERN Document Server

Matteucci, Francesca

2012-01-01

The term “chemical evolution of galaxies” refers to the evolution of abundances of chemical species in galaxies, which is due to nuclear processes occurring in stars and to gas flows into and out of galaxies. This book deals with the chemical evolution of galaxies of all morphological types (ellipticals, spirals and irregulars) and stresses the importance of the star formation histories in determining the properties of stellar populations in different galaxies. The topic is approached in a didactical and logical manner via galaxy evolution models which are compared with observational results obtained in the last two decades: The reader is given an introduction to the concept of chemical abundances and learns about the main stellar populations in our Galaxy as well as about the classification of galaxy types and their main observables. In the core of the book, the construction and solution of chemical evolution models are discussed in detail, followed by descriptions and interpretations of observations of ...

Mapping the evolution of scientific ideas

Energy Technology Data Exchange (ETDEWEB)

Roberts, David [Los Alamos National Laboratory; Herrera, Mark [UNIV OF MARYLAND; Gulbahce, Natali [UNIV OF BOSTON

2009-01-01

Despite the apparent conceptual boundaries of scientific fields, a formal description for their evolution is lacking. Here we describe a novel approach to study the dynamics and evolution of scientific fields using a network-based analysis. We build an idea network consisting of American Physical Society PACS numbers as nodes representing scientific concepts. Two PACS numbers are linked if there exist publications that reference them simultaneously. We locate scientific fields using Cfinder, an overlapping community finding algorithm, and describe the time evolution of these fields using a community evolution method over the course of 1985-2006. The communities we identify map to known scientific fields, and their age strongly depends on t.heir size, impact and activity. Our analysis further suggests that communities that redefine themselves by merging and creating new groups of ideas tend to have more fitness as measured by the impact per paper, and hence communities with a higher fitness tend to be short-lived. The described approach to quantify the evolution of ideas may be relevant in making predictions about the future of science and how to guide its development.

Study of lattice strain evolution during biaxial deformation of stainless steel using a finite element and fast Fourier transform based multi-scale approach

International Nuclear Information System (INIS)

Upadhyay, M.V.; Van Petegem, S.; Panzner, T.; Lebensohn, R.A.; Van Swygenhoven, H.

2016-01-01

A multi-scale elastic-plastic finite element and fast Fourier transform based approach is proposed to study lattice strain evolution during uniaxial and biaxial loading of stainless steel cruciform shaped samples. At the macroscale, finite element simulations capture the complex coupling between applied forces in the arms and gauge stresses induced by the cruciform geometry. The predicted gauge stresses are used as macroscopic boundary conditions to drive a mesoscale elasto-viscoplastic fast Fourier transform model, from which lattice strains are calculated for particular grain families. The calculated lattice strain evolution matches well with experimental values from in-situ neutron diffraction measurements and demonstrates that the spread in lattice strain evolution between different grain families decreases with increasing biaxial stress ratio. During equibiaxial loading, the model reveals that the lattice strain evolution in all grain families, and not just the 311 grain family, is representative of the polycrystalline response. A detailed quantitative analysis of the 200 and 220 grain family reveals that the contribution of elastic and plastic anisotropy to the lattice strain evolution significantly depends on the applied stress ratio.

Biological evolution of replicator systems: towards a quantitative approach.

Science.gov (United States)

Martin, Osmel; Horvath, J E

2013-04-01

The aim of this work is to study the features of a simple replicator chemical model of the relation between kinetic stability and entropy production under the action of external perturbations. We quantitatively explore the different paths leading to evolution in a toy model where two independent replicators compete for the same substrate. To do that, the same scenario described originally by Pross (J Phys Org Chem 17:312-316, 2004) is revised and new criteria to define the kinetic stability are proposed. Our results suggest that fast replicator populations are continually favored by the effects of strong stochastic environmental fluctuations capable to determine the global population, the former assumed to be the only acting evolution force. We demonstrate that the process is continually driven by strong perturbations only, and that population crashes may be useful proxies for these catastrophic environmental fluctuations. As expected, such behavior is particularly enhanced under very large scale perturbations, suggesting a likely dynamical footprint in the recovery patterns of new species after mass extinction events in the Earth's geological past. Furthermore, the hypothesis that natural selection always favors the faster processes may give theoretical support to different studies that claim the applicability of maximum principles like the Maximum Metabolic Flux (MMF) or Maximum Entropy Productions Principle (MEPP), seen as the main goal of biological evolution.

The evolution of "Life": A Metadarwinian integrative approach.

Science.gov (United States)

De Loof, Arnold

2017-01-01

It is undeniably very logical to first formulate an unambiguous definition of "Life" before engaging in defining the parameters instrumental to Life's evolution. Because nearly everybody assumes, erroneously in my opinion, that catching Life's essence in a single sentence is impossible, this way of thinking remained largely unexplored in evolutionary theory. Upon analyzing what exactly happens at the transition from "still alive" to "just dead," the following definition emerged. What we call "Life" (L) is an activity . It is nothing other than the total sum (∑) of all communication acts (C) executed, at moment t, by entities organized as sender-receiver compartments: L = ∑C Such "living" entities are self-electrifying and talking ( = communicating) aggregates of fossil stardust operating in an environment heavily polluted by toxic calcium. Communication is a multifaceted, complex process that is seldom well explained in introductory textbooks of biology. Communication is instrumental to adaptation because, at the cellular level, any act of communication is in fact a problem-solving act. It can be logically deduced that not Natural Selection itself but communication/problem-solving activity preceding selection is the universal driving force of evolution. This is against what textbooks usually claim, although doubt on the status of Natural Selection as driving force has been around for long. Finally, adopting the sender-receiver with its 2 memory systems (genetic and cognitive, both with their own rules) and 2 types of progeny ("physical children" and "pupils") as the universal unit of architecture and function of all living entities, also enables the seamless integration of cultural and organic evolution, another long-standing tough problem in evolutionary theory. Paraphrasing Theodosius Dobzhansky, the very essence of biology is: "Nothing in biology and evolutionary theory makes sense except in the light of the ability of living matter to communicate, and by

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.

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)

Rapid evolution leads to differential population dynamics and top-down control in resurrected Daphnia populations.

Science.gov (United States)

Goitom, Eyerusalem; Kilsdonk, Laurens J; Brans, Kristien; Jansen, Mieke; Lemmens, Pieter; De Meester, Luc

2018-01-01

There is growing evidence of rapid genetic adaptation of natural populations to environmental change, opening the perspective that evolutionary trait change may subsequently impact ecological processes such as population dynamics, community composition, and ecosystem functioning. To study such eco-evolutionary feedbacks in natural populations, however, requires samples across time. Here, we capitalize on a resurrection ecology study that documented rapid and adaptive evolution in a natural population of the water flea Daphnia magna in response to strong changes in predation pressure by fish, and carry out a follow-up mesocosm experiment to test whether the observed genetic changes influence population dynamics and top-down control of phytoplankton. We inoculated populations of the water flea D. magna derived from three time periods of the same natural population known to have genetically adapted to changes in predation pressure in replicate mesocosms and monitored both Daphnia population densities and phytoplankton biomass in the presence and absence of fish. Our results revealed differences in population dynamics and top-down control of algae between mesocosms harboring populations from the time period before, during, and after a peak in fish predation pressure caused by human fish stocking. The differences, however, deviated from our a priori expectations. An S-map approach on time series revealed that the interactions between adults and juveniles strongly impacted the dynamics of populations and their top-down control on algae in the mesocosms, and that the strength of these interactions was modulated by rapid evolution as it occurred in nature. Our study provides an example of an evolutionary response that fundamentally alters the processes structuring population dynamics and impacts ecosystem features.

Cell–cell signaling drives the evolution of complex traits: introduction—lung evo-devo

Science.gov (United States)

Torday, John S.; Rehan, V. K.

2009-01-01

Physiology integrates biology with the environment through cell–cell interactions at multiple levels. The evolution of the respiratory system has been “deconvoluted” (Torday and Rehan in Am J Respir Cell Mol Biol 31:8–12, 2004) through Gene Regulatory Networks (GRNs) applied to cell–cell communication for all aspects of lung biology development, homeostasis, regeneration, and aging. Using this approach, we have predicted the phenotypic consequences of failed signaling for lung development, homeostasis, and regeneration based on evolutionary principles. This cell–cell communication model predicts other aspects of vertebrate physiology as adaptational responses. For example, the oxygen-induced differentiation of alveolar myocytes into alveolar adipocytes was critical for the evolution of the lung in land dwelling animals adapting to fluctuating Phanarezoic oxygen levels over the past 500 million years. Adipocytes prevent lung injury due to oxygen radicals and facilitate the rise of endothermy. In addition, they produce the class I cytokine leptin, which augments pulmonary surfactant activity and alveolar surface area, increasing selection pressure for both respiratory oxygenation and metabolic demand initially constrained by high-systemic vascular pressure, but subsequently compensated by the evolution of the adrenomedullary beta-adrenergic receptor mechanism. Conserted positive selection for the lung and adrenals created further selection pressure for the heart, which becomes progressively more complex phylogenetically in tandem with the lung. Developmentally, increasing heart complexity and size impinges precociously on the gut mesoderm to induce the liver. That evolutionary-developmental interaction is significant because the liver provides regulated sources of glucose and glycogen to the evolving physiologic system, which is necessary for the evolution of the neocortex. Evolution of neocortical control furthers integration of physiologic systems. Such

The interplay between differential geometry and differential equations

CERN Document Server

Lychagin, V V

1995-01-01

This work applies symplectic methods and discusses quantization problems to emphasize the advantage of an algebraic geometry approach to nonlinear differential equations. One common feature in most of the presentations in this book is the systematic use of the geometry of jet spaces.

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.

High degree of sex chromosome differentiation in stickleback fishes

Directory of Open Access Journals (Sweden)

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.

An Engineering-Oriented Approach to the Introductory Differential Equations Course

Science.gov (United States)

Pennell, S.; Avitabile, P.; White, J.

2009-01-01

The introductory differential equations course can be made more relevant to engineering students by including more of the engineering viewpoint, in which differential equations are regarded as systems with inputs and outputs. This can be done without sacrificing any of the usual topical coverage. This point of view is conducive to student…

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 ...

Developing theology for evolution

Directory of Open Access Journals (Sweden)

Chris Wiltsher

2013-07-01

Full Text Available This speculative paper explores one idea for approaching some of the problems which arise when the doctrines of Christian theology meet the current scientific understanding of evolution through natural selection. The main suggestion is that Christian theology should relax the requirement that God controls everything. Some implications of this move are explored, with a brief look at how similar ideas might be of use for non-Christian religions entering into dialogue with the theory of evolution

On Degenerate Partial Differential Equations

OpenAIRE

Chen, Gui-Qiang G.

2010-01-01

Some of recent developments, including recent results, ideas, techniques, and approaches, in the study of degenerate partial differential equations are surveyed and analyzed. Several examples of nonlinear degenerate, even mixed, partial differential equations, are presented, which arise naturally in some longstanding, fundamental problems in fluid mechanics and differential geometry. The solution to these fundamental problems greatly requires a deep understanding of nonlinear degenerate parti...

When Differential Privacy Meets Randomized Perturbation: A Hybrid Approach for Privacy-Preserving Recommender System

KAUST Repository

Liu, Xiao

2017-03-21

Privacy risks of recommender systems have caused increasing attention. Users’ private data is often collected by probably untrusted recommender system in order to provide high-quality recommendation. Meanwhile, malicious attackers may utilize recommendation results to make inferences about other users’ private data. Existing approaches focus either on keeping users’ private data protected during recommendation computation or on preventing the inference of any single user’s data from the recommendation result. However, none is designed for both hiding users’ private data and preventing privacy inference. To achieve this goal, we propose in this paper a hybrid approach for privacy-preserving recommender systems by combining differential privacy (DP) with randomized perturbation (RP). We theoretically show the noise added by RP has limited effect on recommendation accuracy and the noise added by DP can be well controlled based on the sensitivity analysis of functions on the perturbed data. Extensive experiments on three large-scale real world datasets show that the hybrid approach generally provides more privacy protection with acceptable recommendation accuracy loss, and surprisingly sometimes achieves better privacy without sacrificing accuracy, thus validating its feasibility in practice.

Beginning partial differential equations

CERN Document Server

O'Neil, Peter V

2011-01-01

A rigorous, yet accessible, introduction to partial differential equations-updated in a valuable new edition Beginning Partial Differential Equations, Second Edition provides a comprehensive introduction to partial differential equations (PDEs) with a special focus on the significance of characteristics, solutions by Fourier series, integrals and transforms, properties and physical interpretations of solutions, and a transition to the modern function space approach to PDEs. With its breadth of coverage, this new edition continues to present a broad introduction to the field, while also addres

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 ...

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)

Competition and quality in health care markets: a differential-game approach.

Science.gov (United States)

Brekke, Kurt R; Cellini, Roberto; Siciliani, Luigi; Straume, Odd Rune

2010-07-01

We investigate the effect of competition on quality in health care markets with regulated prices taking a differential game approach, in which quality is a stock variable. Using a Hotelling framework, we derive the open-loop solution (health care providers set the optimal investment plan at the initial period) and the feedback closed-loop solution (providers move investments in response to the dynamics of the states). Under the closed-loop solution competition is more intense in the sense that providers observe quality in each period and base their investment on this information. If the marginal provision cost is constant, the open-loop and closed-loop solutions coincide, and the results are similar to the ones obtained by static models. If the marginal provision cost is increasing, investment and quality are lower in the closed-loop solution (when competition is more intense). In this case, static models tend to exaggerate the positive effect of competition on quality.

Differential equations and finite groups

NARCIS (Netherlands)

Put, Marius van der; Ulmer, Felix

2000-01-01

The classical solution of the Riemann-Hilbert problem attaches to a given representation of the fundamental group a regular singular linear differential equation. We present a method to compute this differential equation in the case of a representation with finite image. The approach uses Galois

A general nonlinear evolution equation for irreversible conservative approach to stable equilibrium

International Nuclear Information System (INIS)

Beretta, G.P.

1986-01-01

This paper addresses a mathematical problem relevant to the question of nonequilibrium and irreversibility, namely, that of ''designing'' a general evolution equation capable of describing irreversible but conservative relaxtion towards equilibrium. The objective is to present an interesting mathematical solution to this design problem, namely, a new nonlinear evolution equation that satisfies a set of very stringent relevant requirements. Three different frameworks are defined from which the new equation could be adopted, with entirely different interpretations. Some useful well-known mathematics involving Gram determinants are presented and a nonlinear evolution equation is given which meets the stringent design specifications

A Multilevel Network Study of the Effects of Delinquent Behavior on Friendship Evolution

NARCIS (Netherlands)

Snijders, T.A.B.; Baerveldt, Chris

2003-01-01

A multilevel approach is proposed to the study of the evolution of multiple networks. In this approach, the basic evolution process is assumed to be the same, while parameter values may differ between different networks. For the network evolution process, stochastic actor-oriented models are used,

Time-dependent evolution of rock slopes by a multi-modelling approach

Science.gov (United States)

Bozzano, F.; Della Seta, M.; Martino, S.

2016-06-01

This paper presents a multi-modelling approach that incorporates contributions from morpho-evolutionary modelling, detailed engineering-geological modelling and time-dependent stress-strain numerical modelling to analyse the rheological evolution of a river valley slope over approximately 102 kyr. The slope is located in a transient, tectonically active landscape in southwestern Tyrrhenian Calabria (Italy), where gravitational processes drive failures in rock slopes. Constraints on the valley profile development were provided by a morpho-evolutionary model based on the correlation of marine and river strath terraces. Rock mass classes were identified through geomechanical parameters that were derived from engineering-geological surveys and outputs of a multi-sensor slope monitoring system. The rock mass classes were associated to lithotechnical units to obtain a high-resolution engineering-geological model along a cross section of the valley. Time-dependent stress-strain numerical modelling reproduced the main morpho-evolutionary stages of the valley slopes. The findings demonstrate that a complex combination of eustatism, uplift and Mass Rock Creep (MRC) deformations can lead to first-time failures of rock slopes when unstable conditions are encountered up to the generation of stress-controlled shear zones. The multi-modelling approach enabled us to determine that such complex combinations may have been sufficient for the first-time failure of the S. Giovanni slope at approximately 140 ka (MIS 7), even without invoking any trigger. Conversely, further reactivations of the landslide must be related to triggers such as earthquakes, rainfall and anthropogenic activities. This failure involved a portion of the slope where a plasticity zone resulted from mass rock creep that evolved with a maximum strain rate of 40% per thousand years, after the formation of a river strath terrace. This study demonstrates that the multi-modelling approach presented herein is a useful

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

On Theories of Superalgebras of Differentiable Functions

NARCIS (Netherlands)

Carchedi, D.J.; Roytenberg, D.

2013-01-01

This is the first in a series of papers laying the foundations for a differential graded approach to derived differential geometry (and other geometries in characteristic zero). In this paper, we study theories of supercommutative algebras for which infinitely differentiable functions can be

Experimental evolution in budding yeast

Science.gov (United States)

Murray, Andrew

2012-02-01

I will discuss our progress in analyzing evolution in the budding yeast, Saccharomyces cerevisiae. We take two basic approaches. The first is to try and examine quantitative aspects of evolution, for example by determining how the rate of evolution depends on the mutation rate and the population size or asking whether the rate of mutation is uniform throughout the genome. The second is to try to evolve qualitatively novel, cell biologically interesting phenotypes and track the mutations that are responsible for the phenotype. Our efforts include trying to alter cell morphology, evolve multicellularity, and produce a biological oscillator.

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.

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

Evolution of flexibility and rigidity in retaliatory punishment.

Science.gov (United States)

Morris, Adam; MacGlashan, James; Littman, Michael L; Cushman, Fiery

2017-09-26

Natural selection designs some social behaviors to depend on flexible learning processes, whereas others are relatively rigid or reflexive. What determines the balance between these two approaches? We offer a detailed case study in the context of a two-player game with antisocial behavior and retaliatory punishment. We show that each player in this game-a "thief" and a "victim"-must balance two competing strategic interests. Flexibility is valuable because it allows adaptive differentiation in the face of diverse opponents. However, it is also risky because, in competitive games, it can produce systematically suboptimal behaviors. Using a combination of evolutionary analysis, reinforcement learning simulations, and behavioral experimentation, we show that the resolution to this tension-and the adaptation of social behavior in this game-hinges on the game's learning dynamics. Our findings clarify punishment's adaptive basis, offer a case study of the evolution of social preferences, and highlight an important connection between natural selection and learning in the resolution of social conflicts.

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)

The Institutional Approach for Modeling the Evolution of Human Societies.

Science.gov (United States)

Powers, Simon T

2018-01-01

Artificial life is concerned with understanding the dynamics of human societies. A defining feature of any society is its institutions. However, defining exactly what an institution is has proven difficult, with authors often talking past each other. This article presents a dynamic model of institutions, which views them as political game forms that generate the rules of a group's economic interactions. Unlike most prior work, the framework presented here allows for the construction of explicit models of the evolution of institutional rules. It takes account of the fact that group members are likely to try to create rules that benefit themselves. Following from this, it allows us to determine the conditions under which self-interested individuals will create institutional rules that support cooperation-for example, that prevent a tragedy of the commons. The article finishes with an example of how a model of the evolution of institutional rewards and punishments for promoting cooperation can be created. It is intended that this framework will allow artificial life researchers to examine how human groups can themselves create conditions for cooperation. This will help provide a better understanding of historical human social evolution, and facilitate the resolution of pressing societal social dilemmas.

Natural differential operations on manifolds: an algebraic approach

International Nuclear Information System (INIS)

Katsylo, P I; Timashev, D A

2008-01-01

Natural algebraic differential operations on geometric quantities on smooth manifolds are considered. A method for the investigation and classification of such operations is described, the method of IT-reduction. With it the investigation of natural operations reduces to the analysis of rational maps between k-jet spaces, which are equivariant with respect to certain algebraic groups. On the basis of the method of IT-reduction a finite generation theorem is proved: for tensor bundles V,W→M all the natural differential operations D:Γ(V)→Γ(W) of degree at most d can be algebraically constructed from some finite set of such operations. Conceptual proofs of known results on the classification of natural linear operations on arbitrary and symplectic manifolds are presented. A non-existence theorem is proved for natural deformation quantizations on Poisson manifolds and symplectic manifolds. Bibliography: 21 titles.

New evolution equations for the joint response-excitation probability density function of stochastic solutions to first-order nonlinear PDEs

Science.gov (United States)

Venturi, D.; Karniadakis, G. E.

2012-08-01

By using functional integral methods we determine new evolution equations satisfied by the joint response-excitation probability density function (PDF) associated with the stochastic solution to first-order nonlinear partial differential equations (PDEs). The theory is presented for both fully nonlinear and for quasilinear scalar PDEs subject to random boundary conditions, random initial conditions or random forcing terms. Particular applications are discussed for the classical linear and nonlinear advection equations and for the advection-reaction equation. By using a Fourier-Galerkin spectral method we obtain numerical solutions of the proposed response-excitation PDF equations. These numerical solutions are compared against those obtained by using more conventional statistical approaches such as probabilistic collocation and multi-element probabilistic collocation methods. It is found that the response-excitation approach yields accurate predictions of the statistical properties of the system. In addition, it allows to directly ascertain the tails of probabilistic distributions, thus facilitating the assessment of rare events and associated risks. The computational cost of the response-excitation method is order magnitudes smaller than the one of more conventional statistical approaches if the PDE is subject to high-dimensional random boundary or initial conditions. The question of high-dimensionality for evolution equations involving multidimensional joint response-excitation PDFs is also addressed.

Sclerosing cholangitis: Clinicopathologic features, imaging spectrum, and systemic approach to differential diagnosis

Energy Technology Data Exchange (ETDEWEB)

Seo, Ni Eun [Dept. of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul (Korea, Republic of); Kim, So Yeon; Lee, Seung Soo; Byun, Jae Ho; Kim, Hyoung Jung; Kim, Jin Hee; Lee, Moon Gyu [Dept. of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul (Korea, Republic of)

2016-02-15

Sclerosing cholangitis is a spectrum of chronic progressive cholestatic liver disease characterized by inflammation, fibrosis, and stricture of the bile ducts, which can be classified as primary and secondary sclerosing cholangitis. Primary sclerosing cholangitis is a chronic progressive liver disease of unknown cause. On the other hand, secondary sclerosing cholangitis has identifiable causes that include immunoglobulin G4-related sclerosing disease, recurrent pyogenic cholangitis, ischemic cholangitis, acquired immunodeficiency syndrome-related cholangitis, and eosinophilic cholangitis. In this review, we suggest a systemic approach to the differential diagnosis of sclerosing cholangitis based on the clinical and laboratory findings, as well as the typical imaging features on computed tomography and magnetic resonance (MR) imaging with MR cholangiography. Familiarity with various etiologies of sclerosing cholangitis and awareness of their typical clinical and imaging findings are essential for an accurate diagnosis and appropriate management.

Sclerosing Cholangitis: Clinicopathologic Features, Imaging Spectrum, and Systemic Approach to Differential Diagnosis.

Science.gov (United States)

Seo, Nieun; Kim, So Yeon; Lee, Seung Soo; Byun, Jae Ho; Kim, Jin Hee; Kim, Hyoung Jung; Lee, Moon-Gyu

2016-01-01

Sclerosing cholangitis is a spectrum of chronic progressive cholestatic liver disease characterized by inflammation, fibrosis, and stricture of the bile ducts, which can be classified as primary and secondary sclerosing cholangitis. Primary sclerosing cholangitis is a chronic progressive liver disease of unknown cause. On the other hand, secondary sclerosing cholangitis has identifiable causes that include immunoglobulin G4-related sclerosing disease, recurrent pyogenic cholangitis, ischemic cholangitis, acquired immunodeficiency syndrome-related cholangitis, and eosinophilic cholangitis. In this review, we suggest a systemic approach to the differential diagnosis of sclerosing cholangitis based on the clinical and laboratory findings, as well as the typical imaging features on computed tomography and magnetic resonance (MR) imaging with MR cholangiography. Familiarity with various etiologies of sclerosing cholangitis and awareness of their typical clinical and imaging findings are essential for an accurate diagnosis and appropriate management.

Linear determining equations for differential constraints

International Nuclear Information System (INIS)

Kaptsov, O V

1998-01-01

A construction of differential constraints compatible with partial differential equations is considered. Certain linear determining equations with parameters are used to find such differential constraints. They generalize the classical determining equations used in the search for admissible Lie operators. As applications of this approach equations of an ideal incompressible fluid and non-linear heat equations are discussed

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

Stochastic Loewner evolution as an approach to conformal field theory

International Nuclear Information System (INIS)