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Sample records for differential evolution based

  1. 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.

  2. 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 ...

  3. Market-based transmission expansion planning by improved differential evolution

    International Nuclear Information System (INIS)

    Georgilakis, Pavlos S.

    2010-01-01

    The restructuring and deregulation has exposed the transmission planner to new objectives and uncertainties. As a result, new criteria and approaches are needed for transmission expansion planning (TEP) in deregulated electricity markets. This paper proposes a new market-based approach for TEP. An improved differential evolution (IDE) model is proposed for the solution of this new market-based TEP problem. The modifications of IDE in comparison to the simple differential evolution method are: (1) the scaling factor F is varied randomly within some range, (2) an auxiliary set is employed to enhance the diversity of the population, (3) the newly generated trial vector is compared with the nearest parent, and (4) the simple feasibility rule is used to treat the constraints. Results from the application of the proposed method on the IEEE 30-bus test system demonstrate the feasibility and practicality of the proposed IDE for the solution of TEP problem. (author)

  4. The Cellular Differential Evolution Based on Chaotic Local Search

    Directory of Open Access Journals (Sweden)

    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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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...

  10. Battery parameterisation based on differential evolution via a boundary evolution strategy

    Science.gov (United States)

    Yang, Guangya

    2014-01-01

    Attention has been given to the battery modelling in the electric engineering field following the current development of renewable energy and electrification of transportation. The establishment of the equivalent circuit model of the battery requires data preparation and parameterisation. Besides, 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 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. The method can parameterise the model without extensive data preparation. In addition, the approach can also estimate the initial SOC and the available capacity. The efficiency of the approach is verified through two battery packs, one is an 8-cell battery module and one from an electrical vehicle.

  11. 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.

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    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

  18. 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

  19. 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.

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

    International Nuclear Information System (INIS)

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

    2011-01-01

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

  1. 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.

  2. 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.

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

    Directory of Open Access Journals (Sweden)

    Banaja Mohanty

    2014-09-01

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

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    R. Balamurugan

    2007-09-01

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

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

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    Kok Soon Tey

    2014-01-01

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

  7. 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.

  8. 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.

  9. [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.

  10. 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%.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

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

    Directory of Open Access Journals (Sweden)

    Jin-Yu Zhang

    2014-01-01

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

  1. 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.

  2. Solving Bi-Objective Optimal Power Flow using Hybrid method of Biogeography-Based Optimization and Differential Evolution Algorithm: A case study of the Algerian Electrical Network

    Directory of Open Access Journals (Sweden)

    Ouafa Herbadji

    2016-03-01

    Full Text Available This paper proposes a new hybrid metaheuristique algorithm based on the hybridization of Biogeography-based optimization with the Differential Evolution for solving the optimal power flow problem with emission control. The biogeography-based optimization (BBO algorithm is strongly influenced by equilibrium theory of island biogeography, mainly through two steps: Migration and Mutation. Differential Evolution (DE is one of the best Evolutionary Algorithms for global optimization. The hybridization of these two methods is used to overcome traps of local optimal solutions and problems of time consumption. The objective of this paper is to minimize the total fuel cost of generation, total emission, total real power loss and also maintain an acceptable system performance in terms of limits on generator real power, bus voltages and power flow of transmission lines. In the present work, BBO/DE has been applied to solve the optimal power flow problems on IEEE 30-bus test system and the Algerian electrical network 114 bus. The results obtained from this method show better performances compared with DE, BBO and other well known metaheuristique and evolutionary optimization methods.

  3. Differential Evolution for Many-Particle Adaptive Quantum Metrology

    NARCIS (Netherlands)

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

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Yanfei Zhong

    2017-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Natee Panagant

    2014-01-01

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

  6. Differential Evolution and Particle Swarm Optimization for Partitional Clustering

    DEFF Research Database (Denmark)

    Krink, Thiemo; Paterlini, Sandra

    2006-01-01

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

  7. 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.

  8. 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.

  9. Parameter Estimation of Damped Compound Pendulum Differential Evolution Algorithm

    Directory of Open Access Journals (Sweden)

    Saad Mohd Sazli

    2016-01-01

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

  10. An Enhanced Differential Evolution with Elite Chaotic Local Search

    Directory of Open Access Journals (Sweden)

    Zhaolu Guo

    2015-01-01

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

  11. 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.

  12. 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.

  13. Real parameter optimization by an effective differential evolution algorithm

    Directory of Open Access Journals (Sweden)

    Ali Wagdy Mohamed

    2013-03-01

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

  14. 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.

  15. 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.

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

    Directory of Open Access Journals (Sweden)

    Shuyu Dai

    2018-04-01

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

  17. 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).

  18. 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.

  19. 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...

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

    Directory of Open Access Journals (Sweden)

    Shahnazari-Shahrezaei, P.

    2012-11-01

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

  1. A Unified Differential Evolution Algorithm for Global Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Qiang, Ji; Mitchell, Chad

    2014-06-24

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

  2. 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.

  3. Differential evolution optimization combined with chaotic sequences for image contrast enhancement

    Energy Technology Data Exchange (ETDEWEB)

    Santos Coelho, Leandro dos [Industrial and Systems Engineering Graduate Program, LAS/PPGEPS, Pontifical Catholic University of Parana, PUCPR Imaculada Conceicao, 1155, 80215-901 Curitiba, Parana (Brazil)], E-mail: leandro.coelho@pucpr.br; Sauer, Joao Guilherme [Industrial and Systems Engineering Graduate Program, LAS/PPGEPS, Pontifical Catholic University of Parana, PUCPR Imaculada Conceicao, 1155, 80215-901 Curitiba, Parana (Brazil)], E-mail: joao.sauer@gmail.com; Rudek, Marcelo [Industrial and Systems Engineering Graduate Program, LAS/PPGEPS, Pontifical Catholic University of Parana, PUCPR Imaculada Conceicao, 1155, 80215-901 Curitiba, Parana (Brazil)], E-mail: marcelo.rudek@pucpr.br

    2009-10-15

    Evolutionary Algorithms (EAs) are stochastic and robust meta-heuristics of evolutionary computation field useful to solve optimization problems in image processing applications. Recently, as special mechanism to avoid being trapped in local minimum, the ergodicity property of chaotic sequences has been used in various designs of EAs. Three differential evolution approaches based on chaotic sequences using logistic equation for image enhancement process are proposed in this paper. Differential evolution is a simple yet powerful evolutionary optimization algorithm that has been successfully used in solving continuous problems. The proposed chaotic differential evolution schemes have fast convergence rate but also maintain the diversity of the population so as to escape from local optima. In this paper, the image contrast enhancement is approached as a constrained nonlinear optimization problem. The objective of the proposed chaotic differential evolution schemes is to maximize the fitness criterion in order to enhance the contrast and detail in the image by adapting the parameters using a contrast enhancement technique. The proposed chaotic differential evolution schemes are compared with classical differential evolution to two testing images. Simulation results on three images show that the application of chaotic sequences instead of random sequences is a possible strategy to improve the performance of classical differential evolution optimization algorithm.

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

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Ahmed R. Abdelaziz

    2015-08-01

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

  6. 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.

  7. 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.

  8. 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.

  9. Geometric differential evolution for combinatorial and programs spaces.

    Science.gov (United States)

    Moraglio, A; Togelius, J; Silva, S

    2013-01-01

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

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    R. V. V. Krishna

    2016-10-01

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

  12. An Efficient Binary Differential Evolution with Parameter Adaptation

    Directory of Open Access Journals (Sweden)

    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.

  13. A Hybrid Backtracking Search Optimization Algorithm with Differential Evolution

    Directory of Open Access Journals (Sweden)

    Lijin Wang

    2015-01-01

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

  14. 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.

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

    Science.gov (United States)

    Guo, Zhan; Yan, Xuefeng

    2018-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Ali Wagdy Mohamed

    2014-11-01

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

  17. 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.

  18. Differential Evolution algorithm applied to FSW model calibration

    Science.gov (United States)

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

    2014-03-01

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

  19. Many-Objective Distinct Candidates Optimization using Differential Evolution

    DEFF Research Database (Denmark)

    Justesen, Peter; Ursem, Rasmus Kjær

    2010-01-01

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

  20. 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...

  1. 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.

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

    International Nuclear Information System (INIS)

    Coelho, Leandro dos Santos

    2009-01-01

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

  3. Micro-droplet based directed evolution outperforms conventional laboratory evolution

    DEFF Research Database (Denmark)

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

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Yu-xin Zhao

    2014-01-01

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

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    Xinli Xu

    2013-01-01

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

  12. Differential Geometry Based Multiscale Models

    Science.gov (United States)

    Wei, Guo-Wei

    2010-01-01

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

  13. Differential geometry based multiscale models.

    Science.gov (United States)

    Wei, Guo-Wei

    2010-08-01

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

  14. 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.

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

    Directory of Open Access Journals (Sweden)

    Wenping Ma

    2014-01-01

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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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

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

    Directory of Open Access Journals (Sweden)

    Xiaohao Wen

    2018-03-01

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

  3. 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

  4. 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.

  5. 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

  6. Automatic Knowledge Base Evolution by Learning Instances

    OpenAIRE

    Kim, Sundong

    2016-01-01

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

  7. Optimal Operation of Wind Turbines Based on Support Vector Machine and Differential Evolution Algorithm%基于支持向量机和微分进化算法的风电机优化运行

    Institute of Scientific and Technical Information of China (English)

    彭春华; 相龙阳; 刘刚; 易洪京

    2012-01-01

    Output control of wind turbines is the key item in the operation of wind farm. In view of complicated relations among wind turbine output, wind speed and blade pitch angle, it is hard to establish a versatile and accurate mathematical model. For this reason, a new mode to optimize wind turbine output is proposed: firstly a model for nonlinear fitting between wind turbine output and operational parameters is built; then based on the built model and the variation of wind speed and adopting the high-efficient differential evolution algorithm, the blade pitch angle of wind turbine is optimized fast and dynamically. Using the proposed method, the dynamic relation between wind speed and optimal blade pitch angle can be established. Simulation results of the proposed method show that the output of wind turbine can be effectively uprated, thus the feasibility of the proposed method is verified.%风电机出力控制是风电场运行过程中的一个关键问题。针对风电机出力与风速和桨距角之间存在非常复杂的关系,很难建立通用准确的数学模型,提出了一种新的风电机出力优化模式,即首先通过支持向量机算法建立风电机出力与运行参数之间的非线性拟合模型,并基于此模型和风速的变化,采用高效的微分进化算法对风力机桨距角进行快速动态优化,从而实现风电机出力最大化。以鄱阳湖长岭风电场风电机组实际运行数据进行了仿真应用与分析。结果表明通过优化风力机桨距角可有效地提高风电机出力,验证了文中方法的可行性和优越性。采用文中方法可准确建立风速与最优桨距角的动态对应关系,为风电机的优化运行提供了科学的指导。

  8. 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.

  9. 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.

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    Yalin Wang

    2013-01-01

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

  13. 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.

  14. 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)

  15. 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.

  16. 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.

  17. 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%.

  18. 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 ...

  19. 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.

  20. Differential evolution and neofunctionalization of snake venom metalloprotease domains.

    Science.gov (United States)

    Brust, Andreas; Sunagar, Kartik; Undheim, Eivind A B; Vetter, Irina; Yang, Daryl C; Yang, Dary C; Casewell, Nicholas R; Jackson, Timothy N W; Koludarov, Ivan; Alewood, Paul F; Hodgson, Wayne C; Lewis, Richard J; King, Glenn F; Antunes, Agostinho; Hendrikx, Iwan; Fry, Bryan G

    2013-03-01

    Snake venom metalloproteases (SVMP) are composed of five domains: signal peptide, propeptide, metalloprotease, disintegrin, and cysteine-rich. Secreted toxins are typically combinatorial variations of the latter three domains. The SVMP-encoding genes of Psammophis mossambicus venom are unique in containing only the signal and propeptide domains. We show that the Psammophis SVMP propeptide evolves rapidly and is subject to a high degree of positive selection. Unlike Psammophis, some species of Echis express both the typical multidomain and the unusual monodomain (propeptide only) SVMP, with the result that a lower level of variation is exerted upon the latter. We showed that most mutations in the multidomain Echis SVMP occurred in the protease domain responsible for proteolytic and hemorrhagic activities. The cysteine-rich and disintegrin-like domains, which are putatively responsible for making the P-III SVMPs more potent than the P-I and P-II forms, accumulate the remaining variation. Thus, the binding sites on the molecule's surface are evolving rapidly whereas the core remains relatively conserved. Bioassays conducted on two post-translationally cleaved novel proline-rich peptides from the P. mossambicus propeptide domain showed them to have been neofunctionalized for specific inhibition of mammalian a7 neuronal nicotinic acetylcholine receptors. We show that the proline rich postsynaptic specific neurotoxic peptides from Azemiops feae are the result of convergent evolution within the precursor region of the C-type natriuretic peptide instead of the SVMP. The results of this study reinforce the value of studying obscure venoms for biodiscovery of novel investigational ligands.

  1. Existence of solutions for quasilinear random impulsive neutral differential evolution equation

    Directory of Open Access Journals (Sweden)

    B. Radhakrishnan

    2018-07-01

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

  2. 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.

  3. 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

  4. 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.

  5. 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.

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

    Science.gov (United States)

    Colautti, Robert I; Lau, Jennifer A

    2015-05-01

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

  7. Application of enhanced discrete differential evolution approach to unit commitment problem

    International Nuclear Information System (INIS)

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

    2009-01-01

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

  8. 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

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

    Science.gov (United States)

    Lynch, Alejandro; Baker, Allan J

    1994-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Roman Senkerik

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Chuii Khim Chong

    2012-06-01

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

  12. 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....

  13. 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.

  14. 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)

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

    International Nuclear Information System (INIS)

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

    2008-01-01

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

  16. 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)

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Average Gait Differential Image Based Human Recognition

    Directory of Open Access Journals (Sweden)

    Jinyan Chen

    2014-01-01

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

  2. Neuron-Based Heredity and Human Evolution

    Directory of Open Access Journals (Sweden)

    Don Marshall Gash

    2015-06-01

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

  3. 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)

  4. Black hole thermodynamics based on unitary evolutions

    International Nuclear Information System (INIS)

    Feng, Yu-Lei; Chen, Yi-Xin

    2015-01-01

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

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

    Science.gov (United States)

    Cao, Jia-Shu

    2010-08-01

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

  6. 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

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

    African Journals Online (AJOL)

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

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

    Science.gov (United States)

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

    2017-12-01

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

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

    Science.gov (United States)

    Koshak, William; Solakiewicz, Richard

    2012-01-01

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

  10. A 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....

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  12. 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.

  13. 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

  14. Adaptive CGFs Based on Grammatical Evolution

    Directory of Open Access Journals (Sweden)

    Jian Yao

    2015-01-01

    Full Text Available Computer generated forces (CGFs play blue or red units in military simulations for personnel training and weapon systems evaluation. Traditionally, CGFs are controlled through rule-based scripts, despite the doctrine-driven behavior of CGFs being rigid and predictable. Furthermore, CGFs are often tricked by trainees or fail to adapt to new situations (e.g., changes in battle field or update in weapon systems, and, in most cases, the subject matter experts (SMEs review and redesign a large amount of CGF scripts for new scenarios or training tasks, which is both challenging and time-consuming. In an effort to overcome these limitations and move toward more true-to-life scenarios, a study using grammatical evolution (GE to generate adaptive CGFs for air combat simulations has been conducted. Expert knowledge is encoded with modular behavior trees (BTs for compatibility with the operators in genetic algorithm (GA. GE maps CGFs, represented with BTs to binary strings, and uses GA to evolve CGFs with performance feedback from the simulation. Beyond-visual-range air combat experiments between adaptive CGFs and nonadaptive baseline CGFs have been conducted to observe and study this evolutionary process. The experimental results show that the GE is an efficient framework to generate CGFs in BTs formalism and evolve CGFs via GA.

  15. Optical spatial differentiator based on subwavelength high-contrast gratings

    Science.gov (United States)

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

    2018-04-01

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

  16. 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.

  17. 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.

  18. 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.

  19. A File Based Visualization of Software Evolution

    NARCIS (Netherlands)

    Voinea, S.L.; Telea, A.

    2006-01-01

    Software Configuration Management systems are important instruments for supporting development of large software projects. They accumulate large amounts of evolution data that can be used for process accounting and auditing. We study how visualization can help developers and managers to get insight

  20. Evolution of Web-based International Marketing

    DEFF Research Database (Denmark)

    Rask, Morten

    2002-01-01

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

  1. 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

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

    Directory of Open Access Journals (Sweden)

    Zhongbo Hu

    2014-01-01

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

  3. 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.

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

    Directory of Open Access Journals (Sweden)

    Lianghong Wu

    2011-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Abdellatif HAMOUDA

    2011-12-01

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

  6. 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.

  7. 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.

  8. Reconcilable Differences: Standards-based Teaching and Differentiation.

    Science.gov (United States)

    Tomlinson, Carol Ann

    2000-01-01

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

  9. 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

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

    Directory of Open Access Journals (Sweden)

    Roman Senkerik

    2014-01-01

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

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

    Science.gov (United States)

    Rai, Man Mohan

    2006-01-01

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

  12. 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.

  13. 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.

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

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  15. 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

  16. Modulation of DNA base excision repair during neuronal differentiation

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  17. 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.

  18. 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

  19. Random number generation based on digital differential chaos

    KAUST Repository

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

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Zabrina L Brumme

    2007-07-01

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

  1. Evolution of the european data base

    International Nuclear Information System (INIS)

    Bonnefous, S.; Despres, A.

    1991-01-01

    Works connected with the data base on the European grid are carried on following several ways: 1. Enrichment of the data base, with the inclusion of new data (milk products, agricultural products). Progress along this line is depending on the progress made within EUROSTAT. 2. Elaboration of the data base on a finer grid (10 km * 10 km), for the meshes that are estimated more critical (because they include important potential sources of pollution), or for very non-homogeneous meshes (costal areas). 3. Development and/or acquisition of softwares allowing an exploitation and an easy consultation of the data base. At the present state, installation of the data base with 10 000 km 2 meshes on the PARADOX system is in progress. (PARADOX is a software for data base maintenance). A graphical representation software (cartography) completes the system, allowing the visualization of the data. The paper presents the current state of development of this work

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

    Science.gov (United States)

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

    2015-01-01

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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. Dynamic Evolution Model Based on Social Network Services

    Science.gov (United States)

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

    2013-11-01

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

  11. Evolution of a Computer-Based Testing Laboratory

    Science.gov (United States)

    Moskal, Patrick; Caldwell, Richard; Ellis, Taylor

    2009-01-01

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

  12. 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

  13. 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.

  14. 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.

  15. Digital differential confocal microscopy based on spatial shift transformation.

    Science.gov (United States)

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

    2014-11-01

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

  16. 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

  17. Fully Digital Chaotic Differential Equation-based Systems And Methods

    KAUST Repository

    Radwan, Ahmed Gomaa Ahmed

    2012-09-06

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

  18. Fully Digital Chaotic Differential Equation-based Systems And Methods

    KAUST Repository

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

    2012-01-01

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

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

    Science.gov (United States)

    Ebtehaj, Isa; Bonakdari, Hossein

    2017-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Longquan Yong

    2012-01-01

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

  1. Ultrasound speckle reduction based on fractional order differentiation.

    Science.gov (United States)

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

    2017-07-01

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

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

    Indian Academy of Sciences (India)

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

  3. Solution of partial differential equations by agent-based simulation

    International Nuclear Information System (INIS)

    Szilagyi, Miklos N

    2014-01-01

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

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

    NARCIS (Netherlands)

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

    2011-01-01

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

  5. 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.

  6. Proteinuria: The diagnostic strategy based on urine proteins differentiation

    Directory of Open Access Journals (Sweden)

    Stojimirović Biljana B.

    2004-01-01

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

  7. Self-mixing differential vibrometer based on electronic channel subtraction

    International Nuclear Information System (INIS)

    Donati, Silvano; Norgia, Michele; Giuliani, Guido

    2006-01-01

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

  8. 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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1992-09-17

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

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

    International Nuclear Information System (INIS)

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

    1992-01-01

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

  11. SIGNUM: A Matlab, TIN-based landscape evolution model

    Science.gov (United States)

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

    2012-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Akbar Swandaru

    2012-09-01

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

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

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

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

  14. Evolution of cooperation driven by social-welfare-based migration

    Science.gov (United States)

    Li, Yan; Ye, Hang; Zhang, Hong

    2016-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Timofeeva Maria

    2012-03-01

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

  16. Saturation Detection-Based Blocking Scheme for Transformer Differential Protection

    Directory of Open Access Journals (Sweden)

    Byung Eun Lee

    2014-07-01

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

  17. The Evolution of Reputation-Based Cooperation in Regular Networks

    Directory of Open Access Journals (Sweden)

    Tatsuya Sasaki

    2017-01-01

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

  18. A random network based, node attraction facilitated network evolution method

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2016-03-01

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

  19. Adaptive differential correspondence imaging based on sorting technique

    Directory of Open Access Journals (Sweden)

    Heng Wu

    2017-04-01

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

  20. Trajectory data privacy protection based on differential privacy mechanism

    Science.gov (United States)

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

    2018-05-01

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

  1. Genetic-evolution-based optimization methods for engineering design

    Science.gov (United States)

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

    1990-01-01

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

  2. Web of Data Evolution by Exploiting Agent Based-Argumentation

    OpenAIRE

    Chamekh , Fatma; Boulanger , Danielle; Talens , Guilaine

    2015-01-01

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

  3. The evolution of a company based on technological innovation. Gamesa

    International Nuclear Information System (INIS)

    Lopez Mielgo, N.

    2007-01-01

    This paper reviews the evolution of a company that has based its competitive strategy on technological innovation. Gamesa was established in 1976 and it has been continuously transforming its portfolio of businesses until it has become one of the main global operators in the field of wind turbine manufacturing. The firm was able to apply its technological capital in the emerging phase of the domestic wind energy industry. Once leadership in Spain was consolidated, Gamesa has developed an ambitious programme of sales and operational internationalisation, which has converted it in the number two producer of wind turbines worldwide. (Author)

  4. Case-Base Maintenance for CCBR-Based Process Evolution

    NARCIS (Netherlands)

    Weber, B.; Reichert, M.U.; Wild, W.; Roth-Berghofer, T.; Göker, M.H.; Güvenir, H.A.

    2006-01-01

    The success of a company more and more depends on its ability to flexibly and quickly react to changes. Combining process management techniques and conversational case-based reasoning (CCBR) allows for flexibly aligning the business processes to new requirements by providing integrated process life

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

    Science.gov (United States)

    Suárez-Díaz, Edna

    2013-01-01

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

  6. Differential scaling patterns of vertebrae and the evolution of neck length in mammals.

    Science.gov (United States)

    Arnold, Patrick; Amson, Eli; Fischer, Martin S

    2017-06-01

    Almost all mammals have seven vertebrae in their cervical spines. This consistency represents one of the most prominent examples of morphological stasis in vertebrae evolution. Hence, the requirements associated with evolutionary modifications of neck length have to be met with a fixed number of vertebrae. It has not been clear whether body size influences the overall length of the cervical spine and its inner organization (i.e., if the mammalian neck is subject to allometry). Here, we provide the first large-scale analysis of the scaling patterns of the cervical spine and its constituting cervical vertebrae. Our findings reveal that the opposite allometric scaling of C1 and C2-C7 accommodate the increase of neck bending moment with body size. The internal organization of the neck skeleton exhibits surprisingly uniformity in the vast majority of mammals. Deviations from this general pattern only occur under extreme loading regimes associated with particular functional and allometric demands. Our results indicate that the main source of variation in the mammalian neck stems from the disparity of overall cervical spine length. The mammalian neck reveals how evolutionary disparity manifests itself in a structure that is otherwise highly restricted by meristic constraints. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

  7. Random number generation based on digital differential chaos

    KAUST Repository

    Zidan, Mohammed A.

    2012-07-29

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

  8. Stochastic Differential Equation-Based Flexible Software Reliability Growth Model

    Directory of Open Access Journals (Sweden)

    P. K. Kapur

    2009-01-01

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

  9. 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.

  10. Gradient Evolution-based Support Vector Machine Algorithm for Classification

    Science.gov (United States)

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

    2018-03-01

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

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    Guoliang Li

    2017-01-01

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

  13. 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.

  14. Molecular Phylogenetic: Organism Taxonomy Method Based on Evolution History

    Directory of Open Access Journals (Sweden)

    N.L.P Indi Dharmayanti

    2011-03-01

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

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  16. Differential alkylation-based redox proteomics – Lessons learnt

    Science.gov (United States)

    Wojdyla, Katarzyna; Rogowska-Wrzesinska, Adelina

    2015-01-01

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

  17. Differential alkylation-based redox proteomics--Lessons learnt.

    Science.gov (United States)

    Wojdyla, Katarzyna; Rogowska-Wrzesinska, Adelina

    2015-12-01

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

  18. Differential alkylation-based redox proteomics - Lessons learnt

    DEFF Research Database (Denmark)

    Wojdyla, Katarzyna; Rogowska-Wrzesinska, Adelina

    2015-01-01

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

  19. Dietary differentiation and the evolution of population genetic structure in a highly mobile carnivore.

    Directory of Open Access Journals (Sweden)

    Małgorzata Pilot

    Full Text Available Recent studies on highly mobile carnivores revealed cryptic population genetic structures correlated to transitions in habitat types and prey species composition. This led to the hypothesis that natal-habitat-biased dispersal may be responsible for generating population genetic structure. However, direct evidence for the concordant ecological and genetic differentiation between populations of highly mobile mammals is rare. To address this we analyzed stable isotope profiles (δ(13C and δ(15N values for Eastern European wolves (Canis lupus as a quantifiable proxy measure of diet for individuals that had been genotyped in an earlier study (showing cryptic genetic structure, to provide a quantitative assessment of the relationship between individual foraging behavior and genotype. We found a significant correlation between genetic distances and dietary differentiation (explaining 46% of the variation in both the marginal test and crucially, when geographic distance was accounted for as a co-variable. These results, interpreted in the context of other possible mechanisms such as allopatry and isolation by distance, reinforce earlier studies suggesting that diet and associated habitat choice are influencing the structuring of populations in highly mobile carnivores.

  20. 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.

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

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    Murat Osmanoglu

    2013-01-01

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

  2. 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.

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

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    Jiang Ge

    2017-01-01

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

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

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    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

  5. Tie Points Extraction for SAR Images Based on Differential Constraints

    Science.gov (United States)

    Xiong, X.; Jin, G.; Xu, Q.; Zhang, H.

    2018-04-01

    Automatically extracting tie points (TPs) on large-size synthetic aperture radar (SAR) images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC) algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC) algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

  6. TIE POINTS EXTRACTION FOR SAR IMAGES BASED ON DIFFERENTIAL CONSTRAINTS

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    X. Xiong

    2018-04-01

    Full Text Available Automatically extracting tie points (TPs on large-size synthetic aperture radar (SAR images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

  7. Differential evolution of members of the rhomboid gene family with conservative and divergent patterns.

    Science.gov (United States)

    Li, Qi; Zhang, Ning; Zhang, Liangsheng; Ma, Hong

    2015-04-01

    Rhomboid proteins are intramembrane serine proteases that are involved in a plethora of biological functions, but the evolutionary history of the rhomboid gene family is not clear. We performed a comprehensive molecular evolutionary analysis of the rhomboid gene family and also investigated the organization and sequence features of plant rhomboids in different subfamilies. Our results showed that eukaryotic rhomboids could be divided into five subfamilies (RhoA-RhoD and PARL). Most orthology groups appeared to be conserved only as single or low-copy genes in all lineages in RhoB-RhoD and PARL, whereas RhoA genes underwent several duplication events, resulting in multiple gene copies. These duplication events were due to whole genome duplications in plants and animals and the duplicates might have experienced functional divergence. We also identified a novel group of plant rhomboid (RhoB1) that might have lost their enzymatic activity; their existence suggests that they might have evolved new mechanisms. Plant and animal rhomboids have similar evolutionary patterns. In addition, there are mutations affecting key active sites in RBL8, RBL9 and one of the Brassicaceae PARL duplicates. This study delineates a possible evolutionary scheme for intramembrane proteins and illustrates distinct fates and a mechanism of evolution of gene duplicates. © 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.

  8. Differential Evolutionary Constraints in the Evolution of Chemoreceptors: A Murine and Human Case Study

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    Ricardo D’Oliveira Albanus

    2014-01-01

    Full Text Available Chemoreception is among the most important sensory modalities in animals. Organisms use the ability to perceive chemical compounds in all major ecological activities. Recent studies have allowed the characterization of chemoreceptor gene families. These genes present strikingly high variability in copy numbers and pseudogenization degrees among different species, but the mechanisms underlying their evolution are not fully understood. We have analyzed the functional networks of these genes, their orthologs distribution, and performed phylogenetic analyses in order to investigate their evolutionary dynamics. We have modeled the chemosensory networks and compared the evolutionary constraints of their genes in Mus musculus, Homo sapiens, and Rattus norvegicus. We have observed significant differences regarding the constraints on the orthologous groups and network topologies of chemoreceptors and signal transduction machinery. Our findings suggest that chemosensory receptor genes are less constrained than their signal transducing machinery, resulting in greater receptor diversity and conservation of information processing pathways. More importantly, we have observed significant differences among the receptors themselves, suggesting that olfactory and bitter taste receptors are more conserved than vomeronasal receptors.

  9. Ardipithecus ramidus and the evolution of the human cranial base.

    Science.gov (United States)

    Kimbel, William H; Suwa, Gen; Asfaw, Berhane; Rak, Yoel; White, Tim D

    2014-01-21

    The early Pliocene African hominoid Ardipithecus ramidus was diagnosed as a having a unique phylogenetic relationship with the Australopithecus + Homo clade based on nonhoning canine teeth, a foreshortened cranial base, and postcranial characters related to facultative bipedality. However, pedal and pelvic traits indicating substantial arboreality have raised arguments that this taxon may instead be an example of parallel evolution of human-like traits among apes around the time of the chimpanzee-human split. Here we investigated the basicranial morphology of Ar. ramidus for additional clues to its phylogenetic position with reference to African apes, humans, and Australopithecus. Besides a relatively anterior foramen magnum, humans differ from apes in the lateral shift of the carotid foramina, mediolateral abbreviation of the lateral tympanic, and a shortened, trapezoidal basioccipital element. These traits reflect a relative broadening of the central basicranium, a derived condition associated with changes in tympanic shape and the extent of its contact with the petrous. Ar. ramidus shares with Australopithecus each of these human-like modifications. We used the preserved morphology of ARA-VP 1/500 to estimate the missing basicranial length, drawing on consistent proportional relationships in apes and humans. Ar. ramidus is confirmed to have a relatively short basicranium, as in Australopithecus and Homo. Reorganization of the central cranial base is among the earliest morphological markers of the Ardipithecus + Australopithecus + Homo clade.

  10. The Evolution of Facultative Conformity Based on Similarity.

    Science.gov (United States)

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

    2016-01-01

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

  11. The Evolution of Facultative Conformity Based on Similarity.

    Directory of Open Access Journals (Sweden)

    Charles Efferson

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

  12. The Evolution of Facultative Conformity Based on Similarity

    Science.gov (United States)

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

    2016-01-01

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

  13. Evolution is a cooperative process: the biodiversity-related niches differentiation theory (BNDT) can explain why.

    Science.gov (United States)

    Gatti, Roberto Cazzolla

    2011-01-01

    A. McFayden and G.E. Hutchinson defined a niche as a multidimensional space or hypervolume within the environment that allows an individual or a species to survive, we consider niches as a fundamental ecological variable that regulate species' composition and relation in ecosystems. Successively the niche concept has been associated to the genetic term "phenotype" by MacArthurstressing the importance on what a species or a genome can show outside, either in the environmental functions or in body characteristics. Several indexes have been developed to evaluate the grade of overlapping and similarities of species' niches, even utilizing the theory of information. However, which are the factors that determine the number of species that can coexist in a determinate environment and why a generalist species do not compete until the exclusion of the remaining species to maximize its fitness, is still quite unknown. Moreover, there are few studies and theories that clearly explain why the number of niches is so variable through ecosystems and how can several species live in the same basal niche, intended in a comprehensive sense as the range of basic conditions (temperature, humidity, food-guild, etc.). Here I show that the number of niches in an ecosystem depends on the number of species present in a particular moment and that the species themselves allow the enhancement of niches in terms of space and number. I found that using a three-dimensional model as hypervolume and testing the theory on a Mediterranean, temperate and tropical forest ecosystem it is possible to demonstrate that each species plays a fundamental role in facilitating the colonization by other species by simply modifying the environment and exponentially increasing the available niches' space and number. I resumed these hypothesis, after some preliminary empiric tests, in the Biodiversity-related Niches Differentiation Theory (BNDT), stressing with these definition that the process of niches

  14. Reward-based spatial crowdsourcing with differential privacy preservation

    Science.gov (United States)

    Xiong, Ping; Zhang, Lefeng; Zhu, Tianqing

    2017-11-01

    In recent years, the popularity of mobile devices has transformed spatial crowdsourcing (SC) into a novel mode for performing complicated projects. Workers can perform tasks at specified locations in return for rewards offered by employers. Existing methods ensure the efficiency of their systems by submitting the workers' exact locations to a centralised server for task assignment, which can lead to privacy violations. Thus, implementing crowsourcing applications while preserving the privacy of workers' location is a key issue that needs to be tackled. We propose a reward-based SC method that achieves acceptable utility as measured by task assignment success rates, while efficiently preserving privacy. A differential privacy model ensures rigorous privacy guarantee, and Laplace noise is introduced to protect workers' exact locations. We then present a reward allocation mechanism that adjusts each piece of the reward for a task using the distribution of the workers' locations. Through experimental results, we demonstrate that this optimised-reward method is efficient for SC applications.

  15. Viscoelastic Plate Analysis Based on Gâteaux Differential

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    Kadıoğlu Fethi

    2016-01-01

    Full Text Available In this study, it is aimed to analyze the quasi-static response of viscoelastic Kirchhoff plates with mixed finite element formulation based on the Gâteaux differential. Although the static response of elastic plate, beam and shell structures is a widely studied topic, there are few studies that exist in the literature pertaining to the analysis of the viscoelastic structural elements especially with complex geometries, loading conditions and constitutive relations. The developed mixed finite element model in transformed Laplace-Carson space has four unknowns as displacement, bending and twisting moments in addition to the dynamic and geometric boundary condition terms. Four-parameter solid model is employed for modelling the viscoelastic behaviour. For transformation of the solutions obtained in the Laplace-Carson domain to the time domain, different numerical inverse transform techniques are employed. The developed solution technique is applied to several quasi-static example problems for the verification of the suggested numerical procedure.

  16. Transcriptome-based differentiation of closely-related Miscanthus lines.

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    Philippe Chouvarine

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

  17. Numerical solution of modified differential equations based on symmetry preservation.

    Science.gov (United States)

    Ozbenli, Ersin; Vedula, Prakash

    2017-12-01

    In this paper, we propose a method to construct invariant finite-difference schemes for solution of partial differential equations (PDEs) via consideration of modified forms of the underlying PDEs. The invariant schemes, which preserve Lie symmetries, are obtained based on the method of equivariant moving frames. While it is often difficult to construct invariant numerical schemes for PDEs due to complicated symmetry groups associated with cumbersome discrete variable transformations, we note that symmetries associated with more convenient transformations can often be obtained by appropriately modifying the original PDEs. In some cases, modifications to the original PDEs are also found to be useful in order to avoid trivial solutions that might arise from particular selections of moving frames. In our proposed method, modified forms of PDEs can be obtained either by addition of perturbation terms to the original PDEs or through defect correction procedures. These additional terms, whose primary purpose is to enable symmetries with more convenient transformations, are then removed from the system by considering moving frames for which these specific terms go to zero. Further, we explore selection of appropriate moving frames that result in improvement in accuracy of invariant numerical schemes based on modified PDEs. The proposed method is tested using the linear advection equation (in one- and two-dimensions) and the inviscid Burgers' equation. Results obtained for these tests cases indicate that numerical schemes derived from the proposed method perform significantly better than existing schemes not only by virtue of improvement in numerical accuracy but also due to preservation of qualitative properties or symmetries of the underlying differential equations.

  18. pSum-SaDE: A Modified p-Median Problem and Self-Adaptive Differential Evolution Algorithm for Text Summarization

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    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.

  19. Differential geometry based solvation model II: Lagrangian formulation.

    Science.gov (United States)

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

    2011-12-01

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

  20. Re-Os Isotopic Constraints on the Chemical Evolution and Differentiation of the Martian Mantle

    Science.gov (United States)

    Brandon, Alan D.; Walker, Richard J.

    2002-01-01

    The (187)Re-187Os isotopic systematics of SNC meteorites, thought to be from Mars, provide valuable information regarding the chemical processes that affected the Martian mantle, particularly with regard to the relative abundances of highly siderophile elements (HSE). Previously published data (Birck and Allegre 1994, Brandon et al. 2000), and new data obtained since these studies, indicate that the HSE and Os isotopic composition of the Martian mantle was primarily set in its earliest differentiation history. If so, then these meteorites provide key constraints on the processes that lead to variation in HSE observed in not only Mars, but also Earth, the Moon and other rocky bodies in the Solar System. Processes that likely have an effect on the HSE budgets of terrestrial mantles include core formation, magma ocean crystallization, development of juvenile crust, and the addition of a late veneer. Each of these processes will result in different HSE variation and the isotopic composition of mantle materials and mantle derived lavas. Two observations on the SNC data to present provide a framework for which to test the importance of each of these processes. First, the concentrations of Re and Os in SNC meteorites indicate that they are derived from a mantle that has similar concentrations to the Earth's mantle. Such an observation is consistent with a model where a chondritic late veneer replenished the Earth and Martian mantles subsequent to core formation on each planet. Alternative models to explain this observation do exist, but will require additional data to test the limitations of each. Second, Re-Os isotopic results from Brandon et al. (2000) and new data presented here, show that initial yos correlates with variations in the short-lived systems of (182)Hf- (182)W and (142)Sm-142Nd in the SNC meteorites (epsilon(sub W) and epsilon(sub 142Nd)). These systematics require an isolation of mantle reservoirs during the earliest differentiation history of Mars, and

  1. Biological information systems: Evolution as cognition-based information management.

    Science.gov (United States)

    Miller, William B

    2018-05-01

    An alternative biological synthesis is presented that conceptualizes evolutionary biology as an epiphenomenon of integrated self-referential information management. Since all biological information has inherent ambiguity, the systematic assessment of information is required by living organisms to maintain self-identity and homeostatic equipoise in confrontation with environmental challenges. Through their self-referential attachment to information space, cells are the cornerstone of biological action. That individualized assessment of information space permits self-referential, self-organizing niche construction. That deployment of information and its subsequent selection enacted the dominant stable unicellular informational architectures whose biological expressions are the prokaryotic, archaeal, and eukaryotic unicellular forms. Multicellularity represents the collective appraisal of equivocal environmental information through a shared information space. This concerted action can be viewed as systematized information management to improve information quality for the maintenance of preferred homeostatic boundaries among the varied participants. When reiterated in successive scales, this same collaborative exchange of information yields macroscopic organisms as obligatory multicellular holobionts. Cognition-Based Evolution (CBE) upholds that assessment of information precedes biological action, and the deployment of information through integrative self-referential niche construction and natural cellular engineering antecedes selection. Therefore, evolutionary biology can be framed as a complex reciprocating interactome that consists of the assessment, communication, deployment and management of information by self-referential organisms at multiple scales in continuous confrontation with environmental stresses. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Western classical music development: a statistical analysis of composers similarity, differentiation and evolution.

    Science.gov (United States)

    Georges, Patrick

    2017-01-01

    This paper proposes a statistical analysis that captures similarities and differences between classical music composers with the eventual aim to understand why particular composers 'sound' different even if their 'lineages' (influences network) are similar or why they 'sound' alike if their 'lineages' are different. In order to do this we use statistical methods and measures of association or similarity (based on presence/absence of traits such as specific 'ecological' characteristics and personal musical influences) that have been developed in biosystematics, scientometrics, and bibliographic coupling. This paper also represents a first step towards a more ambitious goal of developing an evolutionary model of Western classical music.

  3. Indirect Inference for Stochastic Differential Equations Based on Moment Expansions

    KAUST Repository

    Ballesio, Marco; Tempone, Raul; Vilanova, Pedro

    2016-01-01

    We provide an indirect inference method to estimate the parameters of timehomogeneous scalar diffusion and jump diffusion processes. We obtain a system of ODEs that approximate the time evolution of the first two moments of the process

  4. 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.

  5. 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.

  6. 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.

  7. Evolution of PHWR fuel transfer system based on operating experience

    International Nuclear Information System (INIS)

    Parvatikar, R.S.; Singh, Jaipal; Chaturvedi, P.C.; Bhambra, H.S.

    2006-01-01

    Fuel Transfer System facilitates loading of new fuel into Fuelling Machine, receipt of spent fuel from Fuelling Machine and its further transportation to Storage Bay. To overcome the limitations of transferring a pair of bundles in the single tube Airlock and Transfer Arm in RAPS-1 and 2/MAPS, a new concept of six tube Transfer Magazine was introduced in NAPS. This resulted in simultaneous loading of new fuel from Transfer Magazine into the Fuelling Machine and unloading of spent fuel from the Fuelling Machine through the exchange mode. It further facilitated the parallel/simultaneous operation of refuelling by Fuelling Machines on the reactor and transferring of spent fuel bundles from the Transfer Magazine to the bay. This new design of Fuel Transfer System was adopted for all standardised 220 MWe PHWRs. Based on the experience gained in 220 MWe PHWRs in the area of operation and maintenance, a number of improvements have been carried out over the years. These aspects have been further strengthened and refined in the Fuel Transfer System of 540 MWe units. The operating experience of the system indicates that the presence of heavy water in the Transfer Magazine poses limitations in its maintenance in the Fuel Transfer room. Further, Surveillance and maintenance of large number of under water equipment and associated valves, rams and underwater sensors is putting extra burden on the O and M efforts. A new concept of mobile light water filled Transfer Machine has been evolved for proposed 700 MWe PHWR units to simplify Fuel Transfer System. This has been made possible by adopting snout level control in the Fuelling Machine, elimination of Shuttle Transport System and locating the Storage Bay adjacent to the Reactor Building. This paper describes the evolution of Fuel Transfer System concepts and various improvements based on the experience gained in the operation and maintenance of the system. (author)

  8. The development and evolution of landform based on neotectonic ...

    Indian Academy of Sciences (India)

    Lingmin Zhong

    2018-02-14

    Feb 14, 2018 ... involving integration of data from the aspects of structural geology ... regions is very sensitive to crustal movement such as folding and faulting ...... drainage network evolution in the upper Narmada Valley: Implication to ...

  9. Geomorphological evolution of badlands based on the dynamics of ...

    Indian Academy of Sciences (India)

    In the light of the evidences, a modified schematic geomorphic evolution of badlands ... Chambal River follows an anti-formal up-warp. Agarwal et al. (2002) ..... Aging of sediments from .... Makaske B 2001 Anastomosing rivers: A review of their.

  10. 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.

  11. 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.

  12. Evolution based on domain combinations: the case of glutaredoxins

    Directory of Open Access Journals (Sweden)

    Herrero Enrique

    2009-03-01

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

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

    Science.gov (United States)

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

    2017-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Ram U. Verma

    2011-04-01

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

  15. 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

  16. Evolution of Black-Box Models Based on Volterra Series

    Directory of Open Access Journals (Sweden)

    Daniel D. Silveira

    2015-01-01

    Full Text Available This paper presents a historical review of the many behavioral models actually used to model radio frequency power amplifiers and a new classification of these behavioral models. It also discusses the evolution of these models, from a single polynomial to multirate Volterra models, presenting equations and estimation methods. New trends in RF power amplifier behavioral modeling are suggested.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-04-15

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

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

    OpenAIRE

    Tripathy, Manoj

    2012-01-01

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

  19. 29 CFR 1620.20 - Pay differentials claimed to be based on extra duties.

    Science.gov (United States)

    2010-07-01

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

  20. Gender-Based Differential Item Performance in Mathematics Achievement Items.

    Science.gov (United States)

    Doolittle, Allen E.; Cleary, T. Anne

    1987-01-01

    Eight randomly equivalent samples of high school seniors were each given a unique form of the ACT Assessment Mathematics Usage Test (ACTM). Signed measures of differential item performance (DIP) were obtained for each item in the eight ACTM forms. DIP estimates were analyzed and a significant item category effect was found. (Author/LMO)

  1. Evolution strategy based optimal chiller loading for saving energy

    International Nuclear Information System (INIS)

    Chang, Y.-C.; Lee, C.-Y.; Chen, C.-R.; Chou, C.-J.; Chen, W.-H.; Chen, W.-H.

    2009-01-01

    This study employs evolution strategy (ES) to solve optimal chiller loading (OCL) problem. ES overcomes the flaw that Lagrangian method is not adaptable for solving OCL as the power consumption models or the kW-PLR (partial load ratio) curves include convex functions and concave functions simultaneously. The complicated process of evolution by the genetic algorithm (GA) method for solving OCL can also be simplified by the ES method. This study uses the PLR of chiller as the variable to be solved for the decoupled air conditioning system. After analysis and comparison of the case study, it has been concluded that this method not only solves the problems of Lagrangian method and GA method, but also produces results with high accuracy within a rapid timeframe. It can be perfectly applied to the operation of air conditioning systems

  2. Neurosphere based differentiation of human iPSC improves astrocyte differentiation

    DEFF Research Database (Denmark)

    Zhou, Shuling; Szczesna, Karolina; Ochalek, Anna

    2016-01-01

    Neural progenitor cells (NPCs) derived from human induced pluripotent stem cells (iPSCs) are traditionally maintained and proliferated utilizing two-dimensional (2D) adherent monolayer culture systems. However, NPCs cultured using this system hardly reflect the intrinsic spatial development...... of brain tissue. In this study, we determined that culturing iPSC-derived NPCs as three-dimensional (3D) floating neurospheres resulted in increased expression of the neural progenitor cell (NPC) markers, PAX6 and NESTIN. Expansion of NPCs in 3D culture methods also resulted in a more homogenous PAX6...... expression when compared to 2D culture methods. Furthermore, the 3D propagation method for NPCs resulted in a significant higher expression of the astrocyte markers  GFAP and aquaporin 4 (AQP4) in the differentiated cells. Thus, our 3D propagation method could constitute a useful tool to promote NPC...

  3. Simulation Study of Swarm Intelligence Based on Life Evolution Behavior

    OpenAIRE

    Yanmin Liu; Ying Bi; Changling Sui; Yuanfeng Luo; Zhuanzhou Zhang; Rui Liu

    2015-01-01

    Swarm intelligence (SI) is a new evolutionary computation technology, and its performance efficacy is usually affected by each individual behavior in the swarm. According to the genetic and sociological theory, the life evolution behavior process is influenced by the external and internal factors, so the mechanisms of external and internal environment change must be analyzed and explored. Therefore, in this paper, we used the thought of the famous American genetic biologist Morgan, “life = DN...

  4. 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

    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

  5. Investigation of de novo unique differentially expressed genes related to evolution in exercise response during domestication in Thoroughbred race horses.

    Directory of Open Access Journals (Sweden)

    Woncheoul Park

    Full Text Available Previous studies of horse RNA-seq were performed by mapping sequence reads to the reference genome during transcriptome analysis. However in this study, we focused on two main ideas. First, differentially expressed genes (DEGs were identified by de novo-based analysis (DBA in RNA-seq data from six Thoroughbreds before and after exercise, here-after referred to as "de novo unique differentially expressed genes" (DUDEG. Second, by integrating both conventional DEGs and genes identified as being selected for during domestication of Thoroughbred and Jeju pony from whole genome re-sequencing (WGS data, we give a new concept to the definition of DEG. We identified 1,034 and 567 DUDEGs in skeletal muscle and blood, respectively. DUDEGs in skeletal muscle were significantly related to exercise-induced stress biological process gene ontology (BP-GO terms: 'immune system process'; 'response to stimulus'; and, 'death' and a KEGG pathways: 'JAK-STAT signaling pathway'; 'MAPK signaling pathway'; 'regulation of actin cytoskeleton'; and, 'p53 signaling pathway'. In addition, we found TIMELESS, EIF4A3 and ZNF592 in blood and CHMP4C and FOXO3 in skeletal muscle, to be in common between DUDEGs and selected genes identified by evolutionary statistics such as FST and Cross Population Extended Haplotype Homozygosity (XP-EHH. Moreover, in Thoroughbreds, three out of five genes (CHMP4C, EIF4A3 and FOXO3 related to exercise response showed relatively low nucleotide diversity compared to the Jeju pony. DUDEGs are not only conceptually new DEGs that cannot be attained from reference-based analysis (RBA but also supports previous RBA results related to exercise in Thoroughbred. In summary, three exercise related genes which were selected for during domestication in the evolutionary history of Thoroughbred were identified as conceptually new DEGs in this study.

  6. Investigation of de novo unique differentially expressed genes related to evolution in exercise response during domestication in Thoroughbred race horses.

    Science.gov (United States)

    Park, Woncheoul; Kim, Jaemin; Kim, Hyeon Jeong; Choi, JaeYoung; Park, Jeong-Woong; Cho, Hyun-Woo; Kim, Byeong-Woo; Park, Myung Hum; Shin, Teak-Soon; Cho, Seong-Keun; Park, Jun-Kyu; Kim, Heebal; Hwang, Jae Yeon; Lee, Chang-Kyu; Lee, Hak-Kyo; Cho, Seoae; Cho, Byung-Wook

    2014-01-01

    Previous studies of horse RNA-seq were performed by mapping sequence reads to the reference genome during transcriptome analysis. However in this study, we focused on two main ideas. First, differentially expressed genes (DEGs) were identified by de novo-based analysis (DBA) in RNA-seq data from six Thoroughbreds before and after exercise, here-after referred to as "de novo unique differentially expressed genes" (DUDEG). Second, by integrating both conventional DEGs and genes identified as being selected for during domestication of Thoroughbred and Jeju pony from whole genome re-sequencing (WGS) data, we give a new concept to the definition of DEG. We identified 1,034 and 567 DUDEGs in skeletal muscle and blood, respectively. DUDEGs in skeletal muscle were significantly related to exercise-induced stress biological process gene ontology (BP-GO) terms: 'immune system process'; 'response to stimulus'; and, 'death' and a KEGG pathways: 'JAK-STAT signaling pathway'; 'MAPK signaling pathway'; 'regulation of actin cytoskeleton'; and, 'p53 signaling pathway'. In addition, we found TIMELESS, EIF4A3 and ZNF592 in blood and CHMP4C and FOXO3 in skeletal muscle, to be in common between DUDEGs and selected genes identified by evolutionary statistics such as FST and Cross Population Extended Haplotype Homozygosity (XP-EHH). Moreover, in Thoroughbreds, three out of five genes (CHMP4C, EIF4A3 and FOXO3) related to exercise response showed relatively low nucleotide diversity compared to the Jeju pony. DUDEGs are not only conceptually new DEGs that cannot be attained from reference-based analysis (RBA) but also supports previous RBA results related to exercise in Thoroughbred. In summary, three exercise related genes which were selected for during domestication in the evolutionary history of Thoroughbred were identified as conceptually new DEGs in this study.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-06-01

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

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

    International Nuclear Information System (INIS)

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2017-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Xu Jia

    2010-11-01

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

  11. Targeted mass spektrometry based assay for monitoring neuronal differentiation

    Czech Academy of Sciences Publication Activity Database

    Žižková, Martina; Suchá, Rita; Rákocyová, Michaela; Doležalová, D.; Červenka, Jakub; Kovářová, Hana

    2015-01-01

    Roč. 78, Suppl 2 (2015), s. 26-27 ISSN 1210-7859. [Conference on Animal Models for neurodegenerative Diseases /3./. 08.11.2015-10.11.2015, Liblice] R&D Projects: GA TA ČR(CZ) TA01011466; GA MŠk ED2.1.00/03.0124; GA MŠk(CZ) 7F14308 Institutional support: RVO:67985904 Keywords : pluripotent cells * neural differentiation * neurons

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

    Directory of Open Access Journals (Sweden)

    Zhengzheng Xian

    2017-01-01

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

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

    Science.gov (United States)

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

    2015-03-01

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

  14. Indirect Inference for Stochastic Differential Equations Based on Moment Expansions

    KAUST Repository

    Ballesio, Marco

    2016-01-06

    We provide an indirect inference method to estimate the parameters of timehomogeneous scalar diffusion and jump diffusion processes. We obtain a system of ODEs that approximate the time evolution of the first two moments of the process by the approximation of the stochastic model applying a second order Taylor expansion of the SDE s infinitesimal generator in the Dynkin s formula. This method allows a simple and efficient procedure to infer the parameters of such stochastic processes given the data by the maximization of the likelihood of an approximating Gaussian process described by the two moments equations. Finally, we perform numerical experiments for two datasets arising from organic and inorganic fouling deposition phenomena.

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

    Science.gov (United States)

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

    2007-01-01

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

  16. Quantifying Mosaic Development: Towards an Evo-Devo Postmodern Synthesis of the Evolution of Development via Differentiation Trees of Embryos

    Directory of Open Access Journals (Sweden)

    Bradly Alicea

    2016-08-01

    Full Text Available Embryonic development proceeds through a series of differentiation events. The mosaic version of this process (binary cell divisions can be analyzed by comparing early development of Ciona intestinalis and Caenorhabditis elegans. To do this, we reorganize lineage trees into differentiation trees using the graph theory ordering of relative cell volume. Lineage and differentiation trees provide us with means to classify each cell using binary codes. Extracting data characterizing lineage tree position, cell volume, and nucleus position for each cell during early embryogenesis, we conduct several statistical analyses, both within and between taxa. We compare both cell volume distributions and cell volume across developmental time within and between single species and assess differences between lineage tree and differentiation tree orderings. This enhances our understanding of the differentiation events in a model of pure mosaic embryogenesis and its relationship to evolutionary conservation. We also contribute several new techniques for assessing both differences between lineage trees and differentiation trees, and differences between differentiation trees of different species. The results suggest that at the level of differentiation trees, there are broad similarities between distantly related mosaic embryos that might be essential to understanding evolutionary change and phylogeny reconstruction. Differentiation trees may therefore provide a basis for an Evo-Devo Postmodern Synthesis.

  17. Monitoring inter-channel nonlinearity based on differential pilot

    Science.gov (United States)

    Wang, Wanli; Yang, Aiying; Guo, Peng; Lu, Yueming; Qiao, Yaojun

    2018-06-01

    We modify and simplify the inter-channel nonlinearity (NL) estimation method by using differential pilot. Compared to previous works, the inter-channel NL estimation method we propose has much lower complexity and does not need modification of the transmitter. The performance of inter-channel NL monitoring with different launch power is tested. For both QPSK and 16QAM systems with 9 channels, the estimation error of inter-channel NL is lower than 1 dB when the total launch power is bigger than 12 dBm after 1000 km optical transmission. At last, we compare our inter-channel NL estimation method with other methods.

  18. Sensing line effects on PWR-based differential pressure measurements

    International Nuclear Information System (INIS)

    Evans, R.P.; Neff, G.G.

    1982-01-01

    An incorrrect configuration of the fluid-filled pressure sensing lines connecting differential pressure transducers to the pressure taps in a pressurized water reactor system can cause errors in the measurement and, during rapid pressure transients, could cause the transducer to fail. Testing was performed in both static and dynamic modes to experimentally determine the effects of sensing lines of various lengths, diameters, and materials. Testing was performed at ambient temperature with absolute line pressures at about 17 MPa using water as the pressure transmission fluid

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

    Science.gov (United States)

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

    2010-12-01

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

  20. Differentiated instruction in a data-based decision-making context

    NARCIS (Netherlands)

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

    2018-01-01

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

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

    Science.gov (United States)

    Preciado, Miguel A; Muriel, Miguel A

    2008-11-01

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

  2. Starvation Based Differential Chemotherapy: A Novel Approach for Cancer Treatment

    Directory of Open Access Journals (Sweden)

    Sidra Naveed

    2014-11-01

    Full Text Available Cancer patients undergoing chemotherapy treatment are advised to increase food intake to overcome the therapy-induced side effects, and weight loss. Dietary restriction is known to slow down the aging process and hence reduce age-related diseases such as cancer. Fasting or short-term starvation is more effective than dietary restriction to prevent cancer growth since starved cells switch off signals for growth and reproduction and enter a protective mode, while cancer cells, being mutated, are not sensitized by any external growth signals and are not protected against any stress. This phenomenon is known as differential stress resistance (DSR. Nutrient signaling pathways involving growth hormone/insulin-like growth factor-1 axis and its downstream effectors, play a key role in DSR in response to starvation controlling the other cell maintenance systems, such as autophagy and apoptosis, that are related to the tumorigenesis. Yeast cells lacking these effectors are better protected against oxidative stress compared to normal cells. In the same way, starvation protects many cell lines and mice against high-dose chemotherapeutic drugs. According to a series of studies, fasting results in overall reduction in chemotherapy side effects in cancer patients. Data shows that starvation-dependent differential chemotherapy is safe, feasible and effective in cancer treatment, but the possible side effects of starvation limit its efficacy. However, further studies and clinical trials may result in its implementation in cancer treatment.

  3. 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

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

    Directory of Open Access Journals (Sweden)

    Yang Bai

    2016-05-01

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

  5. Design and Experiment of a Differential-Based Power Split Device

    Directory of Open Access Journals (Sweden)

    Xiaohua Zeng

    2014-04-01

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

  6. Using 2-Opt based evolution strategy for travelling salesman problem

    Directory of Open Access Journals (Sweden)

    Kenan Karagul

    2016-03-01

    Full Text Available Harmony search algorithm that matches the (µ+1 evolution strategy, is a heuristic method simulated by the process of music improvisation. In this paper, a harmony search algorithm is directly used for the travelling salesman problem. Instead of conventional selection operators such as roulette wheel, the transformation of real number values of harmony search algorithm to order index of vertex representation and improvement of solutions are obtained by using the 2-Opt local search algorithm. Then, the obtained algorithm is tested on two different parameter groups of TSPLIB. The proposed method is compared with classical 2-Opt which randomly started at each step and best known solutions of test instances from TSPLIB. It is seen that the proposed algorithm offers valuable solutions.

  7. An evolution-based strategy for engineering allosteric regulation

    Science.gov (United States)

    Pincus, David; Resnekov, Orna; Reynolds, Kimberly A.

    2017-04-01

    Allosteric regulation provides a way to control protein activity at the time scale of milliseconds to seconds inside the cell. An ability to engineer synthetic allosteric systems would be of practical utility for the development of novel biosensors, creation of synthetic cell signaling pathways, and design of small molecule pharmaceuticals with regulatory impact. To this end, we outline a general approach—termed rational engineering of allostery at conserved hotspots (REACH)—to introduce novel regulation into a protein of interest by exploiting latent allostery that has been hard-wired by evolution into its structure. REACH entails the use of statistical coupling analysis (SCA) to identify ‘allosteric hotspots’ on protein surfaces, the development and implementation of experimental assays to test hotspots for functionality, and a toolkit of allosteric modulators to impinge on endogenous cellular circuitry. REACH can be broadly applied to rewire cellular processes to respond to novel inputs.

  8. Evidence of genetic differentiation and karyotype evolution of the sedges Cyperus ligularis L. and C. odoratus L. (Cyperaceae

    Directory of Open Access Journals (Sweden)

    Geyner Alves dos Santos Cruz

    2018-01-01

    Full Text Available ABSTRACT The taxonomy of Cyperaceae is complex, with genera like Cyperus harboring species complexes. We analyzed the genetic similarity between Cyperus ligularis L. and C. odoratus L. based on DNA fingerprinting and cytogenetics. Significative genetic differentiation (G ST = 0.363 and low gene flow (N m = 0.877 indicated a clear genetic distinction between the two species. Moreover, the clustering analysis showed two distinct genetic groups, suggesting a lack of evidence for hybridization. The phenogram revealed two different lineages, and although all individuals of C. odoratus were collected from plots close to each other, they possessed greater genetic diversity than that observed among individuals of C. ligularis, which were sampled over a wider geographic range. Variation in chromosome number within the two species exhibited the opposite pattern, indicating greater karyotype stability in C. odoratus with 2n = 72 and 2n = 76, while the diploid number for C. ligularis varied from 2n = 66 to 88. The lower genetic variation in C. ligularis may be a result of the founder effect associated with seed dispersion and clonal reproduction. Field observations and analysis of reproductive biology should enrich the understanding of the genetic structure of the investigated populations and their role in successional processes.

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

    OpenAIRE

    Karim MAMDOUH ABBAS

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Karim MAMDOUH ABBAS

    2014-04-01

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

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

    International Nuclear Information System (INIS)

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

    2009-01-01

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

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

    Science.gov (United States)

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

    2016-07-01

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

  13. Simulation Study of Swarm Intelligence Based on Life Evolution Behavior

    Directory of Open Access Journals (Sweden)

    Yanmin Liu

    2015-01-01

    Full Text Available Swarm intelligence (SI is a new evolutionary computation technology, and its performance efficacy is usually affected by each individual behavior in the swarm. According to the genetic and sociological theory, the life evolution behavior process is influenced by the external and internal factors, so the mechanisms of external and internal environment change must be analyzed and explored. Therefore, in this paper, we used the thought of the famous American genetic biologist Morgan, “life = DNA + environment + interaction of environment + gene,” to propose the mutation and crossover operation of DNA fragments by the environmental change to improve the performance efficiency of intelligence algorithms. Additionally, PSO is a random swarm intelligence algorithm with the genetic and sociological property, so we embed the improved mutation and crossover operation to particle swarm optimization (PSO and designed DNA-PSO algorithm to optimize single and multiobjective optimization problems. Simulation experiments in single and multiobjective optimization problems show that the proposed strategies can effectively improve the performance of swarm intelligence.

  14. 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.

  15. 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.

  16. Computations of Wall Distances Based on Differential Equations

    Science.gov (United States)

    Tucker, Paul G.; Rumsey, Chris L.; Spalart, Philippe R.; Bartels, Robert E.; Biedron, Robert T.

    2004-01-01

    The use of differential equations such as Eikonal, Hamilton-Jacobi and Poisson for the economical calculation of the nearest wall distance d, which is needed by some turbulence models, is explored. Modifications that could palliate some turbulence-modeling anomalies are also discussed. Economy is of especial value for deforming/adaptive grid problems. For these, ideally, d is repeatedly computed. It is shown that the Eikonal and Hamilton-Jacobi equations can be easy to implement when written in implicit (or iterated) advection and advection-diffusion equation analogous forms, respectively. These, like the Poisson Laplacian term, are commonly occurring in CFD solvers, allowing the re-use of efficient algorithms and code components. The use of the NASA CFL3D CFD program to solve the implicit Eikonal and Hamilton-Jacobi equations is explored. The re-formulated d equations are easy to implement, and are found to have robust convergence. For accurate Eikonal solutions, upwind metric differences are required. The Poisson approach is also found effective, and easiest to implement. Modified distances are not found to affect global outputs such as lift and drag significantly, at least in common situations such as airfoil flows.

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

    Directory of Open Access Journals (Sweden)

    Ye Zhi-Qiang

    2011-08-01

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

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

    Science.gov (United States)

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

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

  19. Differential blood-based biomarkers of psychopathological dimensions of schizophrenia.

    Science.gov (United States)

    Garcia-Alvarez, Leticia; Garcia-Portilla, Maria Paz; Gonzalez-Blanco, Leticia; Saiz Martinez, Pilar Alejandra; de la Fuente-Tomas, Lorena; Menendez-Miranda, Isabel; Iglesias, Celso; Bobes, Julio

    Symptomatology of schizophrenia is heterogeneous, there is not any pathognomonic symptom. Moreover, the diagnosis is difficult, since it is based on subjective information, instead of markers. The purpose of this study is to provide a review of the current status of blood-based biomarkers of psychopathological dimensions of schizophrenia. Inflammatory, hormonal or metabolic dysfunctions have been identified in patients with schizophrenia and it has attempted to establish biomarkers responsible for these dysfunctions. The identification of these biomarkers could contribute to the diagnosis and treatment of schizophrenia. Copyright © 2016 SEP y SEPB. Publicado por Elsevier España, S.L.U. All rights reserved.

  20. Activity-based differentiation of pathologists' workload in surgical pathology.

    Science.gov (United States)

    Meijer, G A; Oudejans, J J; Koevoets, J J M; Meijer, C J L M

    2009-06-01

    Adequate budget control in pathology practice requires accurate allocation of resources. Any changes in types and numbers of specimens handled or protocols used will directly affect the pathologists' workload and consequently the allocation of resources. The aim of the present study was to develop a model for measuring the pathologists' workload that can take into account the changes mentioned above. The diagnostic process was analyzed and broken up into separate activities. The time needed to perform these activities was measured. Based on linear regression analysis, for each activity, the time needed was calculated as a function of the number of slides or blocks involved. The total pathologists' time required for a range of specimens was calculated based on standard protocols and validated by comparing to actually measured workload. Cutting up, microscopic procedures and dictating turned out to be highly correlated to number of blocks and/or slides per specimen. Calculated workload per type of specimen was significantly correlated to the actually measured workload. Modeling pathologists' workload based on formulas that calculate workload per type of specimen as a function of the number of blocks and slides provides a basis for a comprehensive, yet flexible, activity-based costing system for pathology.

  1. Adaptive Game Level Creation through Rank-based Interactive Evolution

    DEFF Research Database (Denmark)

    Liapis, Antonios; Martínez, Héctor Pérez; Togelius, Julian

    2013-01-01

    as fitness functions for the optimization of the generated content. The preference models are built via ranking-based preference learning, while the content is generated via evolutionary search. The proposed method is evaluated on the creation of strategy game maps, and its performance is tested using...

  2. The evolution of process-based hydrologic models

    NARCIS (Netherlands)

    Clark, Martyn P.; Bierkens, Marc F.P.; Samaniego, Luis; Woods, Ross A.; Uijlenhoet, Remko; Bennett, Katrina E.; Pauwels, Valentijn R.N.; Cai, Xitian; Wood, Andrew W.; Peters-Lidard, Christa D.

    2017-01-01

    The diversity in hydrologic models has historically led to great controversy on the "correct" approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. In this

  3. Controlling Tensegrity Robots through Evolution using Friction based Actuation

    Science.gov (United States)

    Kothapalli, Tejasvi; Agogino, Adrian K.

    2017-01-01

    Traditional robotic structures have limitations in planetary exploration as their rigid structural joints are prone to damage in new and rough terrains. In contrast, robots based on tensegrity structures, composed of rods and tensile cables, offer a highly robust, lightweight, and energy efficient solution over traditional robots. In addition tensegrity robots can be highly configurable by rearranging their topology of rods, cables and motors. However, these highly configurable tensegrity robots pose a significant challenge for locomotion due to their complexity. This study investigates a control pattern for successful locomotion in tensegrity robots through an evolutionary algorithm. A twelve-rod hardware model is rapidly prototyped to utilize a new actuation method based on friction. A web-based physics simulation is created to model the twelve-rod tensegrity ball structure. Square-waves are used as control policies for the actuators of the tensegrity structure. Monte Carlo trials are run to find the most successful number of amplitudes for the square-wave control policy. From the results, an evolutionary algorithm is implemented to find the most optimized solution for locomotion of the twelve-rod tensegrity structure. The software pattern coupled with the new friction based actuation method can serve as the basis for highly efficient tensegrity robots in space exploration.

  4. Evolution of IT Architecture: based on Taxonomy perspective

    NARCIS (Netherlands)

    Suh, Hanjun; van Hillegersberg, Jos

    2013-01-01

    This research aims to explore how latest IT architecture is evolving in real world. We reviewed historical IT structure and classified five IT architecture typology based on various dimensions of IT architectures such as processing decentralization, network connectivity, data and program

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

    Directory of Open Access Journals (Sweden)

    Bo Li

    2014-01-01

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

  6. Regulation, cell differentiation and protein-based inheritance.

    Science.gov (United States)

    Malagnac, Fabienne; Silar, Philippe

    2006-11-01

    Recent research using fungi as models provide new insight into the ability of regulatory networks to generate cellular states that are sufficiently stable to be faithfully transmitted to daughter cells, thereby generating epigenetic inheritance. Such protein-based inheritance is driven by infectious factors endowed with properties usually displayed by prions. We emphasize the contribution of regulatory networks to the emerging properties displayed by cells.

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

    Science.gov (United States)

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

    2015-04-20

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

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

    Directory of Open Access Journals (Sweden)

    Hehong Zhang

    2015-01-01

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

  9. Integration Processes of Delay Differential Equation Based on Modified Laguerre Functions

    Directory of Open Access Journals (Sweden)

    Yeguo Sun

    2012-01-01

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

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

    International Nuclear Information System (INIS)

    Bytev, Vladimir V.; Kniehl, Bernd A.

    2016-12-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-12-15

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

  12. EVOLUTION OF SOUTHERN AFRICAN CRATONS BASED ON SEISMIC IMAGING

    DEFF Research Database (Denmark)

    Thybo, Hans; Soliman, Mohammad Youssof Ahmad; Artemieva, Irina

    2014-01-01

    present a new seismic model for the structure of the crust and lithospheric mantle of the Kalahari Craton, constrained by seismic receiver functions and finite-frequency tomography based on the seismological data from the South Africa Seismic Experiment (SASE). The combination of these two methods...... since formation of the craton, and (3) seismically fast lithospheric keels are imaged in the Kaapvaal and Zimabwe cratons to depths of 300-350 km. Relatively low velocity anomalies are imaged beneath both the paleo-orogenic Limpopo Belt and the Bushveld Complex down to depths of ~250 km and ~150 km...

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

    Directory of Open Access Journals (Sweden)

    Aqil Mohammad Daher

    2017-12-01

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

  14. Estimation of Supercapacitor Energy Storage Based on Fractional Differential Equations.

    Science.gov (United States)

    Kopka, Ryszard

    2017-12-22

    In this paper, new results on using only voltage measurements on supercapacitor terminals for estimation of accumulated energy are presented. For this purpose, a study based on application of fractional-order models of supercapacitor charging/discharging circuits is undertaken. Parameter estimates of the models are then used to assess the amount of the energy accumulated in supercapacitor. The obtained results are compared with energy determined experimentally by measuring voltage and current on supercapacitor terminals. All the tests are repeated for various input signal shapes and parameters. Very high consistency between estimated and experimental results fully confirm suitability of the proposed approach and thus applicability of the fractional calculus to modelling of supercapacitor energy storage.

  15. Progress in molecular-based management of differentiated thyroid cancer

    Science.gov (United States)

    Xing, Mingzhao; Haugen, Bryan R; Schlumberger, Martin

    2014-01-01

    Substantial developments have occurred in the past 5–10 years in clinical translational research of thyroid cancer. Diagnostic molecular markers, such as RET-PTC, RAS, and BRAFV600E mutations; galectin 3; and a new gene expression classifier, are outstanding examples that have improved diagnosis of thyroid nodules. BRAF mutation is a prognostic genetic marker that has improved risk stratification and hence tailored management of patients with thyroid cancer, including those with conventionally low risks. Novel molecular-targeted treatments hold great promise for radioiodine-refractory and surgically inoperable thyroid cancers as shown in clinical trials; such treatments are likely to become a component of the standard treatment regimen for patients with thyroid cancer in the near future. These novel molecular-based management strategies for thyroid nodules and thyroid cancer are the most exciting developments in this unprecedented era of molecular thyroid-cancer medicine. PMID:23668556

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

    Directory of Open Access Journals (Sweden)

    Herb E. Kunze

    2014-01-01

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

  17. Base Realignment and Closure: An Evolution for Harvesting Efficiencies

    Science.gov (United States)

    2012-06-15

    JIOI .1 I’\\ ( a~~:c ...... cu t\\ pnl 17. 20 1::!!. 16 The Commiss ion’s review of the military force strucrure and basing requi rements wa~ geared...II I II,JII __ (lt_ ( )iloltll~_ ( <o• l t.\\tl __ [,q tllt<’ll\\ (’dl !<t~<.: C’-’- t.: d t\\ pnl :!(l. 21!1 :2). ’i U.S. Ctt~,·rnutt: lll At... pnl 2.\\. 2012 ). I ’ . - ll11ll. 6 1 Durin~ the BRJ\\C 2005 i nau~ural hcmi nu in IVlav nf 2005. G;\\0 ’"’"" a"ked w addre:-.s: .... .._ ..... - ( I

  18. Gender-based wage differentials among registered dietitians.

    Science.gov (United States)

    Pollard, Prudence; Taylor, Maxine; Daher, Noha

    2007-01-01

    The debate on compensation equity is broad-based, addressing many organizational, personal, and outcome factors. Central to compensation philosophy is the issue of gender equity. Health care, like many other industries, remains fraught with gender inequity in compensation. This inequity is partially explained by choice of practice area. However, much remains unexplained. Health care is a female-dominated industry with most of the women working in the allied health professions (eg, nurses, dietitians, etc). Registered dietitians (RD) may experience wage discrimination, similar to registered nurses, but prior to the present study, the assumption was not tested. Using data from the first comprehensive study of RD compensation, we examined gender equity in total cash compensation to RDs. Data were collected on total cash compensation, and questions focused on career progression and work outcomes. For purposes of our study, we analyzed data on 5,477 full-time RDs. Ninety-six percent were women, the median age was 43, and median total cash compensation for RDs employed in the position for at least 1 year was $45,500.00. Women earned $45,285.00 and men earned $50,250.00. A median wage gap of $4,965.00 between women and men was observed. Variability in total cash compensation to women was best explained by size of budget, years of experience, work setting, and educational level. Variability for men was explained by size of budget, years of experience, educational level, and employer status. Conclusions suggest that given the wage discrimination that female RDs experience, work organizations should evaluate their pay plans to monitor pay equity. Factors that women can manage to receive compensation that is equal to that of the men include size of budgets they manage, years of experience in the field, employer status, work setting, and educational level attained. Findings are useful for career advisers, human resource specialists, compensation specialists, supervisors, RDs

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

    Science.gov (United States)

    DeFina, Anthony V.

    2002-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

    Connor-Greene, Patricia A.

    2002-01-01

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

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

    Science.gov (United States)

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

    2018-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Qiang Yu

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

  4. Developing Marketing Higher Education Strategies Based on Students’ Satisfaction Evolution

    Directory of Open Access Journals (Sweden)

    Andreea Orîndaru

    2015-09-01

    Full Text Available The educational system worldwide is currently under the spotlight as it shows significant signs of an ongoing crisis in its search for resources, visibility in the crowded market and significance to the ever-changing society. Within this framework, higher education institutions (HEIs are taking significant actions for maintaining students as clients of their educational services. As competition on this market is becoming stronger, HEIs face difficulties in keeping students, leading them to a continuous evaluation of student satisfaction indicators. Beyond HEIs’ managers, researchers in marketing higher education have contributed to the development of a comprehensive literature where still very few have forwarded a longitudinal research model for student satisfaction evaluation despite the need for such approaches. Given this context, the current paper presents a first step towards a longitudinal study as it displays, in a compare and contrast vision, the results of two different quantitative research projects developed in the same student community, with the same objective, but conducted in two different years. Among the most significant results of this research refer to an important decline in students’ satisfaction with a significant increase in the number of students that have a neutral perception. This is highly expected to determine a major impact on university’s overall performance and, therefore, it constitutes a strong argument for determining underlying causes, and especially developing the appropriate marketing strategies to tackle with these issues. Based on this result and other similar research outcomes, strategic and tactic recommendations are granted in the final part of this paper.

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

    DEFF Research Database (Denmark)

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

    2005-01-01

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

  6. Testing a model of codependency for college students in Taiwan based on Bowen's concept of differentiation.

    Science.gov (United States)

    Chang, Shih-Hua

    2018-04-01

    The purpose of this study was to test a model of codependency based on Bowen's concept of differentiation for college students in Taiwan. The relations between family-of-origin dysfunction, differentiation of self, codependency traits and related symptoms including low self-esteem, relationship distress and psychological adjustment problems were examined. Data were collected from 567 college students from 2 large, urban universities in northern Taiwan. Results indicated a significantly negative relationship between levels of codependency and self-differentiation and that self-differentiation partially mediated the relationship between family-of-origin dysfunction and codependency. The implications of these findings for counselling Taiwanese college students who experience codependency traits and related symptoms as well as suggestions for future research are discussed. © 2016 International Union of Psychological Science.

  7. Mesoscale modeling and simulation of microstructure evolution during dynamic recrystallization of a Ni-based superalloy

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Fei [University of Nottingham, Department of Mechanical, Materials and Manufacturing Engineering, Nottingham (United Kingdom); Shanghai Jiao Tong University, Institute of Forming Technology and Equipment, Shanghai (China); Cui, Zhenshan [Shanghai Jiao Tong University, Institute of Forming Technology and Equipment, Shanghai (China); Ou, Hengan [University of Nottingham, Department of Mechanical, Materials and Manufacturing Engineering, Nottingham (United Kingdom); Long, Hui [University of Sheffield, Department of Mechanical Engineering, Sheffield (United Kingdom)

    2016-10-15

    Microstructural evolution and plastic flow characteristics of a Ni-based superalloy were investigated using a simulative model that couples the basic metallurgical principle of dynamic recrystallization (DRX) with the two-dimensional (2D) cellular automaton (CA). Variation of dislocation density with local strain of deformation is considered for accurate determination of the microstructural evolution during DRX. The grain topography, the grain size and the recrystallized fraction can be well predicted by using the developed CA model, which enables to the establishment of the relationship between the flow stress, dislocation density, recrystallized fraction volume, recrystallized grain size and the thermomechanical parameters. (orig.)

  8. 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

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

    Science.gov (United States)

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

    2005-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Ning Dong

    2014-01-01

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

  11. Differential Temporal Evolution Patterns in Brain Temperature in Different Ischemic Tissues in a Monkey Model of Middle Cerebral Artery Occlusion

    Directory of Open Access Journals (Sweden)

    Zhihua Sun

    2012-01-01

    Full Text Available Brain temperature is elevated in acute ischemic stroke, especially in the ischemic penumbra (IP. We attempted to investigate the dynamic evolution of brain temperature in different ischemic regions in a monkey model of middle cerebral artery occlusion. The brain temperature of different ischemic regions was measured with proton magnetic resonance spectroscopy (1H MRS, and the evolution processes of brain temperature were compared among different ischemic regions. We found that the normal (baseline brain temperature of the monkey brain was 37.16°C. In the artery occlusion stage, the mean brain temperature of ischemic tissue was 1.16°C higher than the baseline; however, this increase was region dependent, with 1.72°C in the IP, 1.08°C in the infarct core, and 0.62°C in the oligemic region. After recanalization, the brain temperature of the infarct core showed a pattern of an initial decrease accompanied by a subsequent increase. However, the brain temperature of the IP and oligemic region showed a monotonously and slowly decreased pattern. Our study suggests that in vivo measurement of brain temperature could help to identify whether ischemic tissue survives.

  12. 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

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

    Directory of Open Access Journals (Sweden)

    Xiaomei Hu

    2014-01-01

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

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

    International Nuclear Information System (INIS)

    Teixeira, W.

    1985-01-01

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

  15. Research on social communication network evolution based on topology potential distribution

    Science.gov (United States)

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

    2011-12-01

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

  16. 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.

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

    Institute of Scientific and Technical Information of China (English)

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

    2008-01-01

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

  18. A differential evolution algorithm for tooth profile optimization with respect to balancing specific sliding coefficients of involute cylindrical spur and helical gears

    Directory of Open Access Journals (Sweden)

    Hammoudi Abderazek

    2015-09-01

    Full Text Available Profile shift has an immense effect on the sliding, load capacity, and stability of involute cylindrical gears. Available standards such as ISO/DIS 6336 and BS 436 DIN/3990 currently give the recommendation for the selection of profile shift coefficients. It is, however, very approximate and usually given in the form of implicit graphs or charts. In this article, the optimal selection values of profile shift coefficients for cylindrical involute spur and helical gears are described, using a differential evolution algorithm. The optimization procedure is developed specifically for exact balancing specific sliding coefficients at extremes of contact path and account for gear design constraints. The obtained results are compared with those of standards and research of other authors. They demonstrate the effectiveness and robustness of the applied method. A substantial improvement in balancing specific sliding coefficients is found in this work.

  19. 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.

  20. 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.

  1. Novel Design of Recursive Differentiator Based on Lattice Wave Digital Filter

    Directory of Open Access Journals (Sweden)

    R. Barsainya

    2017-04-01

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

  2. Effect Of Superfluidity And Differential Rotation Of Quark Matter On Magetic Field Evolution in Neutron Star And Black Hole

    Science.gov (United States)

    Aurongzeb, Deeder

    2010-11-01

    Anomalous X-ray pulsars and soft gamma-ray repeaters reveal that existence of very strong magnetic field(> 10e15G) from neutron stars. It has been estimated that at the core the magnitude can be even higher at the center. Apart from dynamo mechanism it has been shown that color locked ferromagnetic phase [ Phys. Rev. D. 72,114003(2005)] can be a possible origin of magnetic field. In this study, we explore electric charge of strange quark matter and its effect on forming chirality in the quark-gluon plasma. We show that electromagnetic current induced by chiral magnetic effect [(Phys. Rev. D. 78.07033(2008)] can induce differential rotation in super fluid quark-gluon plasma giving additional boost to the magnetic field. The internal phase and current has no effect from external magnetic field originating from active galactic nuclei due to superconducting phase formation which screens the fields due to Meissner effect. We show that differential motion can create high radial electric field at the surface making all radiation highly polarized and directional including thermal radiation. As the electric field strength can be even stronger for a collapsing neutron star, the implication of this study to detect radiation from black holes will also be discussed. The work was partly completed at the University of Texas at austin

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Linjun Fan

    2014-01-01

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

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

    Science.gov (United States)

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

    2018-05-24

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

  7. Hybrid sterility and evolution in Hawaiian Drosophila: differential gene and allele-specific expression analysis of backcross males.

    Science.gov (United States)

    Brill, E; Kang, L; Michalak, K; Michalak, P; Price, D K

    2016-08-01

    The Hawaiian Drosophila are an iconic example of sequential colonization, adaptive radiation and speciation on islands. Genetic and phenotypic analysis of closely related species pairs that exhibit incomplete reproductive isolation can provide insights into the mechanisms of speciation. Drosophila silvestris from Hawai'i Island and Drosophila planitibia from Maui are two closely related allopatric Hawaiian picture-winged Drosophila that produce sterile F1 males but fertile F1 females, a pattern consistent with Haldane's rule. Backcrossing F1 hybrid females between these two species to parental species gives rise to recombinant males with three distinct sperm phenotypes despite a similar genomic background: motile sperm, no sperm (sterile), and immotile sperm. We found that these three reproductive morphologies of backcross hybrid males produce divergent gene expression profiles in testes, as measured with RNA sequencing. There were a total of 71 genes significantly differentially expressed between backcross males with no sperm compared with those backcross males with motile sperm and immotile sperm, but no significant differential gene expression between backcross males with motile sperm and backcross males with immotile sperm. All of these genes were underexpressed in males with no sperm, including a number of genes with previously known activities in adult testis. An allele-specific expression analysis showed overwhelmingly more cis-divergent than trans-divergent genes, with no significant difference in the ratio of cis- and trans-divergent genes among the sperm phenotypes. Overall, the results indicate that the regulation of gene expression involved in sperm production likely diverged relatively rapidly between these two closely related species.

  8. Introduction of the Notion of Differential Equations by Modelling Based Teaching

    Science.gov (United States)

    Budinski, Natalija; Takaci, Djurdjica

    2011-01-01

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

  9. Construction of Interval Wavelet Based on Restricted Variational Principle and Its Application for Solving Differential Equations

    OpenAIRE

    Mei, Shu-Li; Lv, Hong-Liang; Ma, Qin

    2008-01-01

    Based on restricted variational principle, a novel method for interval wavelet construction is proposed. For the excellent local property of quasi-Shannon wavelet, its interval wavelet is constructed, and then applied to solve ordinary differential equations. Parameter choices for the interval wavelet method are discussed and its numerical performance is demonstrated.

  10. Image denoising using new pixon representation based on fuzzy filtering and partial differential equations

    DEFF Research Database (Denmark)

    Nadernejad, Ehsan; Nikpour, Mohsen

    2012-01-01

    In this paper, we have proposed two extensions to pixon-based image modeling. The first one is using bicubic interpolation instead of bilinear interpolation and the second one is using fuzzy filtering method, aiming to improve the quality of the pixonal image. Finally, partial differential...

  11. Stepwise Analysis of Differential Item Functioning Based on Multiple-Group Partial Credit Model.

    Science.gov (United States)

    Muraki, Eiji

    1999-01-01

    Extended an Item Response Theory (IRT) method for detection of differential item functioning to the partial credit model and applied the method to simulated data using a stepwise procedure. Then applied the stepwise DIF analysis based on the multiple-group partial credit model to writing trend data from the National Assessment of Educational…

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

    Science.gov (United States)

    Song, Liqing

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

  13. Genome-Wide Analysis of the Musa WRKY Gene Family: Evolution and Differential Expression during Development and Stress.

    Science.gov (United States)

    Goel, Ridhi; Pandey, Ashutosh; Trivedi, Prabodh K; Asif, Mehar H

    2016-01-01

    The WRKY gene family plays an important role in the development and stress responses in plants. As information is not available on the WRKY gene family in Musa species, genome-wide analysis has been carried out in this study using available genomic information from two species, Musa acuminata and Musa balbisiana. Analysis identified 147 and 132 members of the WRKY gene family in M. acuminata and M. balbisiana, respectively. Evolutionary analysis suggests that the WRKY gene family expanded much before the speciation in both the species. Most of the orthologs retained in two species were from the γ duplication event which occurred prior to α and β genome-wide duplication (GWD) events. Analysis also suggests that subtle changes in nucleotide sequences during the course of evolution have led to the development of new motifs which might be involved in neo-functionalization of different WRKY members in two species. Expression and cis-regulatory motif analysis suggest possible involvement of Group II and Group III WRKY members during various stresses and growth/development including fruit ripening process respectively.

  14. Differential susceptibility to plasticity: a 'missing link' between gene-culture co-evolution and neuropsychiatric spectrum disorders?

    Directory of Open Access Journals (Sweden)

    Wurzman Rachel

    2012-04-01

    Full Text Available Abstract Brüne's proposal that erstwhile 'vulnerability' genes need to be reconsidered as 'plasticity' genes, given the potential for certain environments to yield increased positive function in the same domain as potential dysfunction, has implications for psychiatric nosology as well as a more dynamic understanding of the relationship between genes and culture. In addition to validating neuropsychiatric spectrum disorder nosologies by calling for similar methodological shifts in gene-environment-interaction studies, Brüne's position elevates the importance of environmental contexts - inclusive of socio-cultural variables - as mechanisms that contribute to clinical presentation. We assert that when models of susceptibility to plasticity and neuropsychiatric spectrum disorders are concomitantly considered, a new line of inquiry emerges into the co-evolution and co-determination of socio-cultural contexts and endophenotypes. This presents potentially unique opportunities, benefits, challenges, and responsibilities for research and practice in psychiatry. Please see related manuscript: http://www.biomedcentral.com/1741-7015/10/38

  15. Genome-wide analysis of the Musa WRKY gene family: evolution and differential expression during development and stress

    Directory of Open Access Journals (Sweden)

    Ridhi eGoel

    2016-03-01

    Full Text Available The WRKY gene family plays an important role in the development and stress responses in plants. As information is not available on the WRKY gene family in Musa species, genome-wide analysis has been carried out in this study using available genomic information from two species, Musa acuminata and Musa balbisiana. Analysis identified 147 and 132 members of the WRKY gene family in M. acuminata and M. balbisiana respectively. Evolutionary analysis suggests that the WRKY gene family expanded much before the speciation in both the species. Most of the orthologs retained in two species were from the γ duplication event which occurred prior to α and β genome-wide duplication (GWD events. Analysis also suggests that subtle changes in nucleotide sequences during the course of evolution have led to the development of new motifs which might be involved in neo-functionalization of different WRKY members in two species. Expression and cis-regulatory motif analysis suggest possible involvement of Group II and Group III WRKY members during various stresses and growth/ development including fruit ripening process respectively.

  16. Differential BPFs with Multiple Transmission Zeros Based on Terminated Coupled Lines

    Science.gov (United States)

    Niu, Yiming; Yang, Guo; Wu, Wen

    2018-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Guohui Lyu

    2017-02-01

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

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

    Science.gov (United States)

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

    2017-02-15

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

  19. Expressions of pathologic markers in PRP based chondrogenic differentiation of human adipose derived stem cells.

    Science.gov (United States)

    Pakfar, Arezou; Irani, Shiva; Hanaee-Ahvaz, Hana

    2017-02-01

    Optimization of the differentiation medium through using autologous factors such as PRP is of great consideration, but due to the complex, variable and undefined composition of PRP on one hand and lack of control over the absolute regulatory mechanisms in in vitro conditions or disrupted and different mechanisms in diseased tissue microenvironments in in vivo conditions on the other hand, it is complicated and rather unpredictable to get the desired effects of PRP making it inevitable to monitor the possible pathologic or undesired differentiation pathways and therapeutic effects of PRP. Therefore, in this study the probable potential of PRP on inducing calcification, inflammation and angiogenesis in chondrogenically-differentiated cells was investigated. The expressions of chondrogenic, inflammatory, osteogenic and angiogenic markers from TGFβ or PRP-treated cells during chondrogenic differentiation of human adipose-derived stem cells (ADSCs) was evaluated. Expressions of Collagen II (Col II), Aggrecan, Sox9 and Runx2 were quantified using q-RT PCR. Expression of Col II and X was investigated by immunocytochemistry as well. Glycosaminoglycans (GAGs) production was also determined by GAG assay. Possible angiogenic/inflammatory potential was determined by quantitatively measuring the secreted VEGF, TNFα and phosphorylated VEGFR2 via ELISA. In addition, the calcification of the construct was monitored by measuring ALP activity and calcium deposition. Our data showed that PRP positively induced chondrogenesis; meanwhile the secretion of angiogenic and inflammatory markers was decreased. VEGFR2 phosphorylation and ALP activity had a decreasing trend, but tissue mineralization was enhanced upon treating with PRP. Although reduction in inflammatory/angiogenic potential of the chondrogenically differentiated constructs highlights the superior effectiveness of PRP in comparison to TGFβ for chondrogenic differentiation, yet further improvement of the PRP-based

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

    OpenAIRE

    Lei Zhang; David Levinson; Shanjiang Zhu

    2007-01-01

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

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

    Science.gov (United States)

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

    2015-11-01

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

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

    DEFF Research Database (Denmark)

    Dahlstedt, Palle

    2015-01-01

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

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

    Science.gov (United States)

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

    2016-11-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Fumiko Matsuoka

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

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

    Science.gov (United States)

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

    2013-01-27

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

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

    Directory of Open Access Journals (Sweden)

    Shaobo Li

    2018-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Fangluan Gao

    2018-03-01

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

  9. Detection of Individual Molecules and Ions by Carbon Nanotube-Based Differential Resistive Pulse Sensor.

    Science.gov (United States)

    Peng, Ran; Tang, Xiaowu Shirley; Li, Dongqing

    2018-04-01

    This paper presents a new method of sensing single molecules and cations by a carbon nanotube (CNT)-based differential resistive pulse sensing (RPS) technique on a nanofluidic chip. A mathematical model for multichannel RPS systems is developed to evaluate the CNT-based RPS signals. Individual cations, rhodamine B dye molecules, and ssDNAs are detected successfully with high resolution and high signal-to-noise ratio. Differentiating ssDNAs with 15 and 30 nucleotides are achieved. The experimental results also show that translocation of negatively charged ssDNAs through a CNT decreases the electrical resistance of the CNT channel, while translocation of positively charged cations and rhodamine B molecules increases the electrical resistance of the CNT. The CNT-based nanofluidic device developed in this work provides a new avenue for single-molecule/ion detection and offers a potential strategy for DNA sequencing. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Alignment and prediction of cis-regulatory modules based on a probabilistic model of evolution.

    Directory of Open Access Journals (Sweden)

    Xin He

    2009-03-01

    Full Text Available Cross-species comparison has emerged as a powerful paradigm for predicting cis-regulatory modules (CRMs and understanding their evolution. The comparison requires reliable sequence alignment, which remains a challenging task for less conserved noncoding sequences. Furthermore, the existing models of DNA sequence evolution generally do not explicitly treat the special properties of CRM sequences. To address these limitations, we propose a model of CRM evolution that captures different modes of evolution of functional transcription factor binding sites (TFBSs and the background sequences. A particularly novel aspect of our work is a probabilistic model of gains and losses of TFBSs, a process being recognized as an important part of regulatory sequence evolution. We present a computational framework that uses this model to solve the problems of CRM alignment and prediction. Our alignment method is similar to existing methods of statistical alignment but uses the conserved binding sites to improve alignment. Our CRM prediction method deals with the inherent uncertainties of binding site annotations and sequence alignment in a probabilistic framework. In simulated as well as real data, we demonstrate that our program is able to improve both alignment and prediction of CRM sequences over several state-of-the-art methods. Finally, we used alignments produced by our program to study binding site conservation in genome-wide binding data of key transcription factors in the Drosophila blastoderm, with two intriguing results: (i the factor-bound sequences are under strong evolutionary constraints even if their neighboring genes are not expressed in the blastoderm and (ii binding sites in distal bound sequences (relative to transcription start sites tend to be more conserved than those in proximal regions. Our approach is implemented as software, EMMA (Evolutionary Model-based cis-regulatory Module Analysis, ready to be applied in a broad biological context.

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

    Directory of Open Access Journals (Sweden)

    Zhiqiang Wang

    2018-05-01

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

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

    Science.gov (United States)

    Ahn, Byeong-Cheol

    2016-01-01

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

  13. 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

  14. Regulation of human mesenchymal stem cells differentiation into chondrocytes in extracellular matrix-based hydrogel scaffolds.

    Science.gov (United States)

    Du, Mingchun; Liang, Hui; Mou, Chenchen; Li, Xiaoran; Sun, Jie; Zhuang, Yan; Xiao, Zhifeng; Chen, Bing; Dai, Jianwu

    2014-02-01

    To induce human mesenchymal stem cells (hMSCs) to differentiate into chondrocytes in three-dimensional (3D) microenvironments, we developed porous hydrogel scaffolds using the cartilage extracellular matrix (ECM) components of chondroitin sulfate (CS) and collagen (COL). The turbidity and viscosity experiments indicated hydrogel could form through pH-triggered co-precipitation when pH=2-3. Enzyme-linked immunosorbent assay (ELISA) confirmed the hydrogel scaffolds could controllably release growth factors as envisaged. Transforming growth factor-β (TGF-β) was released to stimulate hMSCs differentiation into chondrocytes; and then collagen binding domain-basic fibroblast growth factor (CBD-bFGF) was released to improve the differentiation and preserve the chondrocyte phenotype. In in vitro cell culture experiments, the differentiation processes were compared in different microenvironments: 2D culture in culture plate as control, 3D culture in the fabricated scaffolds without growth factors (CC), the samples with CBD-bFGF (CC-C), the samples with TGF-β (CC-T), the samples with CBD-bFGF/TGF-β (CC-CT). Real-time polymerase chain reaction (RT-PCR) revealed the hMSC marker genes of CD44 and CD105 decreased; at the same time the chondrocyte marker genes of collagen type II and aggrecan increased, especially in the CC-CT sample. Immunostaining results further confirmed the hMSC marker protein of CD 44 disappeared and the chondrocyte marker protein of collagen type II emerged over time in the CC-CT sample. These results imply the ECM-based hydrogel scaffolds with growth factors can supply suitable 3D cell niches for hMSCs differentiation into chondrocytes and the differentiation process can be regulated by the controllably released growth factors. Copyright © 2013 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

    Hossain, Md. Tofazzal

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

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

    International Nuclear Information System (INIS)

    Sato, K.

    1986-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-07-01

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

  18. Toward Agent-Based Models of the Development And Evolution of Business Relations and Networks

    Science.gov (United States)

    Wilkinson, Ian F.; Marks, Robert E.; Young, Louise

    Firms achieve competitive advantage in part through the development of cooperative relations with other firms and organisations. We describe a program of research designed to map and model the development of cooperative inter-firm relations, including the processes and paths by which firms may evolve from adversarial to more cooperative relations. Narrative-event-history methods will be used to develop stylised histories of the emergence of business relations in various contexts and to identify relevant causal mechanisms to be included in the agent-based models of relationship and network evolution. The relationship histories will provide the means of assuring the agent-based models developed.

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

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

    DEFF Research Database (Denmark)

    Tatu, Aditya Jayant

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

  1. Investigating market efficiency through a forecasting model based on differential equations

    Science.gov (United States)

    de Resende, Charlene C.; Pereira, Adriano C. M.; Cardoso, Rodrigo T. N.; de Magalhães, A. R. Bosco

    2017-05-01

    A new differential equation based model for stock price trend forecast is proposed as a tool to investigate efficiency in an emerging market. Its predictive power showed statistically to be higher than the one of a completely random model, signaling towards the presence of arbitrage opportunities. Conditions for accuracy to be enhanced are investigated, and application of the model as part of a trading strategy is discussed.

  2. Systems-based decomposition schemes for the approximate solution of multi-term fractional differential equations

    Science.gov (United States)

    Ford, Neville J.; Connolly, Joseph A.

    2009-07-01

    We give a comparison of the efficiency of three alternative decomposition schemes for the approximate solution of multi-term fractional differential equations using the Caputo form of the fractional derivative. The schemes we compare are based on conversion of the original problem into a system of equations. We review alternative approaches and consider how the most appropriate numerical scheme may be chosen to solve a particular equation.

  3. Agent-Based Modelling of the Evolution of the Russian Party System Based on Pareto and Hotelling Distributions. Part II

    Directory of Open Access Journals (Sweden)

    Владимир Геннадьевич Иванов

    2015-12-01

    Full Text Available The given article presents research of the evolution of the Russian party system. The chosen methodology is based on the heuristic potential of agent-based modelling. The author analyzes various scenarios of parties’ competition (applying Pareto distribution in connection with recent increase of the number of political parties. In addition, the author predicts the level of ideological diversity of the parties’ platforms (applying the principles of Hotelling distribution in order to evaluate their potential competitiveness in the struggle for voters.

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

    Science.gov (United States)

    Toman, Jan; Flegr, Jaroslav

    2017-12-21

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

  5. Clinicopathological and Molecular Histochemical Review of Skull Base Metastasis from Differentiated Thyroid Carcinoma

    International Nuclear Information System (INIS)

    Matsuno, Akira; Murakami, Mineko; Hoya, Katsumi; Yamada, Shoko M.; Miyamoto, Shinya; Yamada, So; Son, Jae-Hyun; Nishido, Hajime; Ide, Fuyuaki; Nagashima, Hiroshi; Sugaya, Mutsumi; Hirohata, Toshio; Mizutani, Akiko; Okinaga, Hiroko; Ishii, Yudo; Tahara, Shigeyuki; Teramoto, Akira; Osamura, R. Yoshiyuki; Yamazaki, Kazuto; Ishida, Yasuo

    2013-01-01

    Skull base metastasis from differentiated thyroid carcinoma including follicular thyroid carcinoma (FTC) and papillary thyroid carcinoma (PTC) is a rare clinical entity. Eighteen FTC cases and 10 PTC cases showing skull base metastasis have been reported. The most common symptom of skull base metastasis from FTC and PTC is cranial nerve dysfunction. Bone destruction and local invasion to the surrounding soft tissues are common on radiological imaging. Skull base metastases can be the initial clinical presentation of FTC and PTC in the presence of silent primary sites. The possibility of skull base metastasis from FTC and PTC should be considered in patients with the clinical symptoms of cranial nerve dysfunction and radiological findings of bone destruction. A variety of genetic alterations in thyroid tumors have been identified to have a fundamental role in their tumorigenesis. Molecular histochemical studies are useful for elucidating the histopathological features of thyroid carcinoma. Recent molecular findings may provide novel molecular-based treatment strategies for thyroid carcinoma

  6. 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...

  7. Improving thermal efficiency and increasing production rate in the double moving beds thermally coupled reactors by using differential evolution (DE) technique

    International Nuclear Information System (INIS)

    Karimi, Mohsen; Rahimpour, Mohammad Reza; Rafiei, Razieh; Shariati, Alireza; Iranshahi, Davood

    2016-01-01

    Highlights: • Double moving bed thermally coupled reactor is modeled in two dimensions. • The required heat of naphtha process is attained with nitrobenzene hydrogenation. • DE optimization method is applied to optimize operating conditions. • Hydrogen, aromatic and aniline productions increase in the proposed configuration. - Abstract: According to the global requirements for energy saving and the control of global warming, multifunctional auto-thermal reactors as a novel concept in the process integration (PI) have risen up in the recent years. In the novel modification presented in this study, the required heat of endothermic naphtha reforming process has been supplied by nitrobenzene hydrogenation reaction. In addition, the enhancement of reactor performance, such as the increase of production rate, has become a key issue in the diverse industries. Thus, Differential Evolution (DE) technique is applied to optimize the operating conditions (temperature and pressure) and designing parameters of a thermally coupled reactor with double moving beds. Ultimately, the obtained results of the proposed model are compared with non-optimized and conventional model. This model results in noticeable reduction in the operational costs as well as enhancement of the net profit of the plant. The increase in the hydrogen and aromatic production shows the superiority of the proposed model.

  8. Classification of breast masses in ultrasound images using self-adaptive differential evolution extreme learning machine and rough set feature selection.

    Science.gov (United States)

    Prabusankarlal, Kadayanallur Mahadevan; Thirumoorthy, Palanisamy; Manavalan, Radhakrishnan

    2017-04-01

    A method using rough set feature selection and extreme learning machine (ELM) whose learning strategy and hidden node parameters are optimized by self-adaptive differential evolution (SaDE) algorithm for classification of breast masses is investigated. A pathologically proven database of 140 breast ultrasound images, including 80 benign and 60 malignant, is used for this study. A fast nonlocal means algorithm is applied for speckle noise removal, and multiresolution analysis of undecimated discrete wavelet transform is used for accurate segmentation of breast lesions. A total of 34 features, including 29 textural and five morphological, are applied to a [Formula: see text]-fold cross-validation scheme, in which more relevant features are selected by quick-reduct algorithm, and the breast masses are discriminated into benign or malignant using SaDE-ELM classifier. The diagnosis accuracy of the system is assessed using parameters, such as accuracy (Ac), sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), Matthew's correlation coefficient (MCC), and area ([Formula: see text]) under receiver operating characteristics curve. The performance of the proposed system is also compared with other classifiers, such as support vector machine and ELM. The results indicated that the proposed SaDE algorithm has superior performance with [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] compared to other classifiers.

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

    International Nuclear Information System (INIS)

    Akama, Tomoko; Kobayashi, Osamu; Nanbu, Shinkoh

    2015-01-01

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

  10. Damage evolution analysis of coal samples under cyclic loading based on single-link cluster method

    Science.gov (United States)

    Zhang, Zhibo; Wang, Enyuan; Li, Nan; Li, Xuelong; Wang, Xiaoran; Li, Zhonghui

    2018-05-01

    In this paper, the acoustic emission (AE) response of coal samples under cyclic loading is measured. The results show that there is good positive relation between AE parameters and stress. The AE signal of coal samples under cyclic loading exhibits an obvious Kaiser Effect. The single-link cluster (SLC) method is applied to analyze the spatial evolution characteristics of AE events and the damage evolution process of coal samples. It is found that a subset scale of the SLC structure becomes smaller and smaller when the number of cyclic loading increases, and there is a negative linear relationship between the subset scale and the degree of damage. The spatial correlation length ξ of an SLC structure is calculated. The results show that ξ fluctuates around a certain value from the second cyclic loading process to the fifth cyclic loading process, but spatial correlation length ξ clearly increases in the sixth loading process. Based on the criterion of microcrack density, the coal sample failure process is the transformation from small-scale damage to large-scale damage, which is the reason for changes in the spatial correlation length. Through a systematic analysis, the SLC method is an effective method to research the damage evolution process of coal samples under cyclic loading, and will provide important reference values for studying coal bursts.

  11. A physically based 3-D model of ice cliff evolution over debris-covered glaciers

    Science.gov (United States)

    Buri, Pascal; Miles, Evan S.; Steiner, Jakob F.; Immerzeel, Walter W.; Wagnon, Patrick; Pellicciotti, Francesca

    2016-12-01

    We use high-resolution digital elevation models (DEMs) from unmanned aerial vehicle (UAV) surveys to document the evolution of four ice cliffs on the debris-covered tongue of Lirung Glacier, Nepal, over one ablation season. Observations show that out of four cliffs, three different patterns of evolution emerge: (i) reclining cliffs that flatten during the ablation season; (ii) stable cliffs that maintain a self-similar geometry; and (iii) growing cliffs, expanding laterally. We use the insights from this unique data set to develop a 3-D model of cliff backwasting and evolution that is validated against observations and an independent data set of volume losses. The model includes ablation at the cliff surface driven by energy exchange with the atmosphere, reburial of cliff cells by surrounding debris, and the effect of adjacent ponds. The cliff geometry is updated monthly to account for the modifications induced by each of those processes. Model results indicate that a major factor affecting the survival of steep cliffs is the coupling with ponded water at its base, which prevents progressive flattening and possible disappearance of a cliff. The radial growth observed at one cliff is explained by higher receipts of longwave and shortwave radiation, calculated taking into account atmospheric fluxes, shading, and the emission of longwave radiation from debris surfaces. The model is a clear step forward compared to existing static approaches that calculate atmospheric melt over an invariant cliff geometry and can be used for long-term simulations of cliff evolution and to test existing hypotheses about cliffs' survival.

  12. Subtype differentiation of renal tumors using voxel-based histogram analysis of intravoxel incoherent motion parameters.

    Science.gov (United States)

    Gaing, Byron; Sigmund, Eric E; Huang, William C; Babb, James S; Parikh, Nainesh S; Stoffel, David; Chandarana, Hersh

    2015-03-01

    The aim of this study was to determine if voxel-based histogram analysis of intravoxel incoherent motion imaging (IVIM) parameters can differentiate various subtypes of renal tumors, including benign and malignant lesions. A total of 44 patients with renal tumors who underwent surgery and had histopathology available were included in this Health Insurance Portability and Accountability Act-compliant, institutional review board-approved, single-institution prospective study. In addition to routine renal magnetic resonance imaging examination performed on a 1.5-T system, all patients were imaged with axial diffusion-weighted imaging using 8 b values (range, 0-800 s/mm). A biexponential model was fitted to the diffusion signal data using a segmented algorithm to extract the IVIM parameters perfusion fraction (fp), tissue diffusivity (Dt), and pseudodiffusivity (Dp) for each voxel. Mean and histogram measures of heterogeneity (standard deviation, skewness, and kurtosis) of IVIM parameters were correlated with pathology results of tumor subtype using unequal variance t tests to compare subtypes in terms of each measure. Correction for multiple comparisons was accomplished using the Tukey honestly significant difference procedure. A total of 44 renal tumors including 23 clear cell (ccRCC), 4 papillary (pRCC), 5 chromophobe, and 5 cystic renal cell carcinomas, as well as benign lesions, 4 oncocytomas (Onc) and 3 angiomyolipomas (AMLs), were included in our analysis. Mean IVIM parameters fp and Dt differentiated 8 of 15 pairs of renal tumors. Histogram analysis of IVIM parameters differentiated 9 of 15 subtype pairs. One subtype pair (ccRCC vs pRCC) was differentiated by mean analysis but not by histogram analysis. However, 2 other subtype pairs (AML vs Onc and ccRCC vs Onc) were differentiated by histogram distribution parameters exclusively. The standard deviation of Dt [σ(Dt)] differentiated ccRCC (0.362 ± 0.136 × 10 mm/s) from AML (0.199 ± 0.043 × 10 mm/s) (P = 0

  13. Measurement-based perturbation theory and differential equation parameter estimation with applications to satellite gravimetry

    Science.gov (United States)

    Xu, Peiliang

    2018-06-01

    The numerical integration method has been routinely used by major institutions worldwide, for example, NASA Goddard Space Flight Center and German Research Center for Geosciences (GFZ), to produce global gravitational models from satellite tracking measurements of CHAMP and/or GRACE types. Such Earth's gravitational products have found widest possible multidisciplinary applications in Earth Sciences. The method is essentially implemented by solving the differential equations of the partial derivatives of the orbit of a satellite with respect to the unknown harmonic coefficients under the conditions of zero initial values. From the mathematical and statistical point of view, satellite gravimetry from satellite tracking is essentially the problem of estimating unknown parameters in the Newton's nonlinear differential equations from satellite tracking measurements. We prove that zero initial values for the partial derivatives are incorrect mathematically and not permitted physically. The numerical integration method, as currently implemented and used in mathematics and statistics, chemistry and physics, and satellite gravimetry, is groundless, mathematically and physically. Given the Newton's nonlinear governing differential equations of satellite motion with unknown equation parameters and unknown initial conditions, we develop three methods to derive new local solutions around a nominal reference orbit, which are linked to measurements to estimate the unknown corrections to approximate values of the unknown parameters and the unknown initial conditions. Bearing in mind that satellite orbits can now be tracked almost continuously at unprecedented accuracy, we propose the measurement-based perturbation theory and derive global uniformly convergent solutions to the Newton's nonlinear governing differential equations of satellite motion for the next generation of global gravitational models. Since the solutions are global uniformly convergent, theoretically speaking

  14. Interrogation of weak Bragg grating sensors based on dual-wavelength differential detection.

    Science.gov (United States)

    Cheng, Rui; Xia, Li

    2016-11-15

    It is shown that for weak Bragg gratings the logarithmic ratio of reflected intensities at any two wavelengths within the spectrum follows a linear relationship with the Bragg wavelength shift, with a slope proportional to their wavelength spacing. This finding is exploited to develop a flexible, efficient, and cheap interrogation solution of weak fiber Bragg grating (FBGs), especially ultra-short FBGs, in distributed sensing based on dual-wavelength differential detection. The concept is experimentally studied in both single and distributed sensing systems with ultra-short FBG sensors. The work may form the basis of new and promising FBG interrogation techniques based on detecting discrete rather than continuous spectra.

  15. The effect of numerical techniques on differential equation based chaotic generators

    KAUST Repository

    Zidan, Mohammed A.

    2012-07-29

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

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  17. A novel method to identify hub pathways of rheumatoid arthritis based on differential pathway networks.

    Science.gov (United States)

    Wei, Shi-Tong; Sun, Yong-Hua; Zong, Shi-Hua

    2017-09-01

    The aim of the current study was to identify hub pathways of rheumatoid arthritis (RA) using a novel method based on differential pathway network (DPN) analysis. The present study proposed a DPN where protein‑protein interaction (PPI) network was integrated with pathway‑pathway interactions. Pathway data was obtained from background PPI network and the Reactome pathway database. Subsequently, pathway interactions were extracted from the pathway data by building randomized gene‑gene interactions and a weight value was assigned to each pathway interaction using Spearman correlation coefficient (SCC) to identify differential pathway interactions. Differential pathway interactions were visualized using Cytoscape to construct a DPN. Topological analysis was conducted to identify hub pathways that possessed the top 5% degree distribution of DPN. Modules of DPN were mined according to ClusterONE. A total of 855 pathways were selected to build pathway interactions. By filtrating pathway interactions of weight values >0.7, a DPN with 312 nodes and 791 edges was obtained. Topological degree analysis revealed 15 hub pathways, such as heparan sulfate/heparin‑glycosaminoglycan (HS‑GAG) degradation, HS‑GAG metabolism and keratan sulfate degradation for RA based on DPN. Furthermore, hub pathways were also important in modules, which validated the significance of hub pathways. In conclusion, the proposed method is a computationally efficient way to identify hub pathways of RA, which identified 15 hub pathways that may be potential biomarkers and provide insight to future investigation and treatment of RA.

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

    Science.gov (United States)

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

    2017-12-01

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

  19. Crustal evolution of South American Platform based on Sm-Nd isotope geochemistry

    International Nuclear Information System (INIS)

    Sato, Kei

    1998-01-01

    Sm-Nd isotopic systematics is relevant to the topics of origin and evolution the of continental crust, where model ages refer to the time when crustal material was differentiated from the upper mantle. Alternative interpretations are due to a lack of adequate information on crustal processes and the variable composition of the mantle sources. The Sm-Nd methods are presented, and applied on rock materials from the South American Platform. The main conclusions indicate juvenile accretion with higher growth rates (peaks), around 3.7-3.5 Ga (∼ 0.5% in volume), 3.1 - 2.9 Ga (∼16%), 2.7 - 2.6 (∼ 9%), 2.2 - 1.9 (35%) and 1.3-1.0 (7%). The continental growth curve indicates that about 35 % of the crust was formed by 2.5 Ga, 88% by 1.8 Ga and 99% by 1.0 Ga, and the remaining ∼ 1 % was added in the Phanerozoic. Rapid crustal growth occurred between 2.2 and 1.9 Ga. The main period of continental crust formation occurred during the Paleoproterozoic, corresponding to 54 % in volume. Sm-Nd model ages, when compared with the crystallisation ages of granitoid rocks, furnish a rough estimate of juvenile vs. reworked material. Within the South American Platform about 45% of juvenile continental crust is still preserved within tectonic provinces of different ages. The remainder represents continental crust reworked in younger tectono-thermal events. In particular crustal reworking was predominating over juvenile accretion during Meso-Neoproterozoic. The Transbrasiliano Lineament is a megasuture, active in the Neoproterozoic, which separates a large northwestern mass, including the Amazonian and Sao Luis Cratons, from a southeastern mass, formed by a collage of cratonic fragments, of which the Sao Francisco and Rio de La Plata are the largest. The crustal evolutions of these two large continental masses are considered individually, and can be resumed following form: I - Old Archean rocks (>3.4 Ga) are found only within the south-eastern part (Gaviao Block, Contendas

  20. Freestanding eggshell membrane-based electrodes for high-performance supercapacitors and oxygen evolution reaction

    Science.gov (United States)

    Geng, Jing; Wu, Hao; Al-Enizi, Abdullah M.; Elzatahry, Ahmed A.; Zheng, Gengfeng

    2015-08-01

    A type of freestanding, light-weight eggshell membrane-based electrode is demonstrated for supercapacitors and for oxygen evolution reaction (OER) catalysis. As a widely available daily waste, eggshell membranes have unique porous three-dimensional grid-like fibrous structures with relatively high surface area and abundant macropores, allowing for effective conjugation of carbon nanotubes and growth of NiCo2O4 nanowire arrays, an effective supercapacitor material and OER catalyst. The three-dimensional fibrous eggshell membrane frameworks with carbon nanotubes offer efficient pathways for charge transport, and the macropores between adjacent fibers are fully accessible for electrolytes and bubble evolution. As a supercapacitor, the eggshell membrane/carbon nanotube/NiCo2O4 electrode shows high specific capacitances at current densities from 1 to 20 A g-1, with excellent capacitance retention (>90%) at 10 A g-1 for over 10 000 cycles. When employed as an OER catalyst, this eggshell membrane-based electrode exhibits an OER onset potential of 1.53 V vs. the reversible hydrogen electrode (RHE), and a stable catalytic current density of 20 mA cm-2 at 1.65 V vs. the RHE.A type of freestanding, light-weight eggshell membrane-based electrode is demonstrated for supercapacitors and for oxygen evolution reaction (OER) catalysis. As a widely available daily waste, eggshell membranes have unique porous three-dimensional grid-like fibrous structures with relatively high surface area and abundant macropores, allowing for effective conjugation of carbon nanotubes and growth of NiCo2O4 nanowire arrays, an effective supercapacitor material and OER catalyst. The three-dimensional fibrous eggshell membrane frameworks with carbon nanotubes offer efficient pathways for charge transport, and the macropores between adjacent fibers are fully accessible for electrolytes and bubble evolution. As a supercapacitor, the eggshell membrane/carbon nanotube/NiCo2O4 electrode shows high specific

  1. Evolution of precipitate in nickel-base alloy 718 irradiated with argon ions at elevated temperature

    International Nuclear Information System (INIS)

    Jin, Shuoxue; Luo, Fengfeng; Ma, Shuli; Chen, Jihong; Li, Tiecheng; Tang, Rui; Guo, Liping

    2013-01-01

    Alloy 718 is a nickel-base superalloy whose strength derives from γ′(Ni 3 (Al,Ti)) and γ″(Ni 3 Nb) precipitates. The evolution of the precipitates in alloy 718 irradiated with argon ions at elevated temperature were examined via transmission electron microscopy. Selected-area electron diffraction indicated superlattice spots disappeared after argon ion irradiation, which showing that the ordered structure of the γ′ and γ″ precipitates became disordered. The size of the precipitates became smaller with the irradiation dose increasing at 290 °C

  2. Differential barometric-based positioning technique for indoor elevation measurement in IoT medical applications.

    Science.gov (United States)

    Wang, Hua; Wen, Yingyou; Zhao, Dazhe

    2017-07-20

    Medical applications have begun to benefit from Internet of Things (IoT) technology through the introduction of wearable devices. Several medical applications require accurate patient location as various changes affect pressure parameters inside the body. This study aims to develop a system to measure indoor altitude for IoT medical applications. We propose a differential barometric-based positioning system to estimate the altitude between a reference sensor and a localizing sensor connected to the human body. The differential barometric altimetry model is introduced to estimate indoor elevations and eliminate environmental artifacts. In addition, a Gaussian filter processing is adopted to remove noise from the elevation measurements. The proposed system is then investigated through extensive experiments, using various evaluation criteria. The results indicate that the proposed system yielded good accuracy with reduced implementation complexity and fewer costs. The proposed system is resilient compared to other indoor localization approaches, even when numerous environmental artifacts in indoor environments are present.

  3. Partial differential equation-based localization of a monopole source from a circular array.

    Science.gov (United States)

    Ando, Shigeru; Nara, Takaaki; Levy, Tsukassa

    2013-10-01

    Wave source localization from a sensor array has long been the most active research topics in both theory and application. In this paper, an explicit and time-domain inversion method for the direction and distance of a monopole source from a circular array is proposed. The approach is based on a mathematical technique, the weighted integral method, for signal/source parameter estimation. It begins with an exact form of the source-constraint partial differential equation that describes the unilateral propagation of wide-band waves from a single source, and leads to exact algebraic equations that include circular Fourier coefficients (phase mode measurements) as their coefficients. From them, nearly closed-form, single-shot and multishot algorithms are obtained that is suitable for use with band-pass/differential filter banks. Numerical evaluation and several experimental results obtained using a 16-element circular microphone array are presented to verify the validity of the proposed method.

  4. A robust random number generator based on differential comparison of chaotic laser signals.

    Science.gov (United States)

    Zhang, Jianzhong; Wang, Yuncai; Liu, Ming; Xue, Lugang; Li, Pu; Wang, Anbang; Zhang, Mingjiang

    2012-03-26

    We experimentally realize a robust real-time random number generator by differentially comparing the signal from a chaotic semiconductor laser and its delayed signal through a 1-bit analog-to-digital converter. The probability density distribution of the output chaotic signal based on the differential comparison method possesses an extremely small coefficient of Pearson's median skewness (1.5 × 10⁻⁶), which can yield a balanced random sequence much easily than the previously reported method that compares the signal from the chaotic laser with a certain threshold value. Moveover, we experimently demonstrate that our method can stably generate good random numbers at rates of 1.44 Gbit/s with excellent immunity from external perturbations while the previously reported method fails.

  5. An Energy Efficient Hydraulic Winch Drive Concept Based on a Speed-variable Switched Differential Pump

    DEFF Research Database (Denmark)

    Schmidt, Lasse; Andersen, Torben O.; Pedersen, Henrik Clemmensen

    2017-01-01

    controls. Such solutions are typically constituted by many and rather expensive components, and are furthermore often suffering from low frequency dynamics. In this paper an alternative solution is proposed for winch drive operation, which is based on the so-called speed-variable switched differential pump......, originally designed for direct drive of hydraulic differential cylinders. This concept utilizes three pumps, driven by a single electric servo drive. The concept is redesigned for usage in winch drives, driven by flow symmetric hydraulic motors and single directional loads as commonly seen in e.g. active...... heave compensation applications. A general drive configuration approach is presented, along with a proper control strategy and design. The resulting concept is evaluated when applied for active heave compensation. Results demonstrate control performance on level with conventional valve solutions...

  6. Quartz crystal microbalance-based system for high-sensitivity differential sputter yield measurements

    International Nuclear Information System (INIS)

    Rubin, B.; Topper, J. L.; Farnell, C. C.; Yalin, A. P.

    2009-01-01

    We present a quartz crystal microbalance-based system for high sensitivity differential sputter yield measurements of different target materials due to ion bombardment. The differential sputter yields can be integrated to find total yields. Possible ion beam conditions include ion energies in the range of 30-350 eV and incidence angles of 0 deg. - 70 deg. from normal. A four-grid ion optics system is used to achieve a collimated ion beam at low energy (<100 eV) and a two-grid ion optics is used for higher energies (up to 750 eV). A complementary weight loss approach is also used to measure total sputter yields. Validation experiments are presented that confirm high sensitivity and accuracy of sputter yield measurements.

  7. Living biointerfaces based on non-pathogenic bacteria to direct cell differentiation

    Science.gov (United States)

    Rodrigo-Navarro, Aleixandre; Rico, Patricia; Saadeddin, Anas; Garcia, Andres J.; Salmeron-Sanchez, Manuel

    2014-07-01

    Genetically modified Lactococcus lactis, non-pathogenic bacteria expressing the FNIII7-10 fibronectin fragment as a protein membrane have been used to create a living biointerface between synthetic materials and mammalian cells. This FNIII7-10 fragment comprises the RGD and PHSRN sequences of fibronectin to bind α5β1 integrins and triggers signalling for cell adhesion, spreading and differentiation. We used L. lactis strain to colonize material surfaces and produce stable biofilms presenting the FNIII7-10 fragment readily available to cells. Biofilm density is easily tunable and remains stable for several days. Murine C2C12 myoblasts seeded over mature biofilms undergo bipolar alignment and form differentiated myotubes, a process triggered by the FNIII7-10 fragment. This biointerface based on living bacteria can be further modified to express any desired biochemical signal, establishing a new paradigm in biomaterial surface functionalisation for biomedical applications.

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

    KAUST Repository

    Wang, X.

    2012-04-19

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

  9. A Simulation Model for Tensile Fracture Procedure Analysis of Graphite Material based on Damage Evolution

    International Nuclear Information System (INIS)

    Zhao Erqiang; Ma Shaopeng; Wang Hongtao

    2014-01-01

    Graphite material is generally easy to be damaged by the widely distributed micro-cracks when subjects to load. For numerically analyzing of the structure made of graphite material, the influences of the degradation of the material in damaged areas need to be considered. In this paper, an axial tension test method is proposed to obtain the dynamic damage evolution rule of the material. Using the degradation rule (variation of elastic modulus), the finite element model is then constructed to analyze the tensile fracture process of the L-shaped graphite specimen. An axial tension test of graphite is performed to obtain the stress-strain curve. Based on the variation of the measured curve, the damage evolution rule of the material are fitted out. A simulation model based on the above measured results is then constructed on ABAQUS by user subroutine. Using this simulation model, the tension failure process of L-shaped graphite specimen with fillet are simulated. The calculated and experimental results on fracture load are in good agreement. The damage simulation model based on the stress-strain curve of axial tensile test can be used in other tensile fracture analysis. (author)

  10. Darwinian evolution

    NARCIS (Netherlands)

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

    2016-01-01

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

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

    Science.gov (United States)

    Wagner, Peter J; Estabrook, George F

    2014-11-18

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

  12. Mechanism for microstructural evolution induced by high temperature deformation in Zr-based bulk metallic glasses

    International Nuclear Information System (INIS)

    Cheng, Sirui; Wang, Chunju; Ma, Mingzhen; Shan, Debin; Guo, Bin

    2016-01-01

    In the Zr_4_1_._2Ti_1_3_._8Cu_1_2_._5Ni_1_0Be_2_2_._5 (Vit1) alloy undergoing high temperature deformation, its thermal properties and microstructure are quite different from those in the annealing alloy. In order to research the coupled effect of temperature and plastic strain on microstructural evolution of Zr-based amorphous, uniaxial compression test of Vit1 alloy with good amorphous nature has been performed, and then the structural state and thermal properties of Vit1 alloy after thermal deformation and isothermal annealing in the supercooled liquid region were investigated. It is revealed that the deformed specimens possess higher characteristic temperature and lower enthalpy change of microstructural relaxation. In addition, the smaller inter-atomic distance and higher order degree of atomic arrangement can be observed in those deformed Vit1 alloy. That can be deduced that thermal deformation is in favor of the microstructural evolution from a metastable amorphous state to stable crystallization state, because plastic strain promotes the annihilation of free volume and provide excess driving force of atomic diffusion. However, upon increasing the ambient temperature, the influence of plastic deformation on microstructure gradually decreased owing to the decreasing proportion of the plastic deformation-induced annihilation of free volume during the whole thermal deformation process. - Highlights: • The deformed specimens possess closer microstructure and higher characteristic temperatures. • The order degree of microstructures in deformed specimens is higher than that in annealed specimens. • Thermal deformation accelerates the microstructural evolution of Zr-based BMGs. • The influence of thermal deformation on microstructure decreases with the temperature increasing.

  13. Accurate detection of hierarchical communities in complex networks based on nonlinear dynamical evolution

    Science.gov (United States)

    Zhuo, Zhao; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng

    2018-04-01

    One of the most challenging problems in network science is to accurately detect communities at distinct hierarchical scales. Most existing methods are based on structural analysis and manipulation, which are NP-hard. We articulate an alternative, dynamical evolution-based approach to the problem. The basic principle is to computationally implement a nonlinear dynamical process on all nodes in the network with a general coupling scheme, creating a networked dynamical system. Under a proper system setting and with an adjustable control parameter, the community structure of the network would "come out" or emerge naturally from the dynamical evolution of the system. As the control parameter is systematically varied, the community hierarchies at different scales can be revealed. As a concrete example of this general principle, we exploit clustered synchronization as a dynamical mechanism through which the hierarchical community structure can be uncovered. In particular, for quite arbitrary choices of the nonlinear nodal dynamics and coupling scheme, decreasing the coupling parameter from the global synchronization regime, in which the dynamical states of all nodes are perfectly synchronized, can lead to a weaker type of synchronization organized as clusters. We demonstrate the existence of optimal choices of the coupling parameter for which the synchronization clusters encode accurate information about the hierarchical community structure of the network. We test and validate our method using a standard class of benchmark modular networks with two distinct hierarchies of communities and a number of empirical networks arising from the real world. Our method is computationally extremely efficient, eliminating completely the NP-hard difficulty associated with previous methods. The basic principle of exploiting dynamical evolution to uncover hidden community organizations at different scales represents a "game-change" type of approach to addressing the problem of community

  14. Mechanism for microstructural evolution induced by high temperature deformation in Zr-based bulk metallic glasses

    Energy Technology Data Exchange (ETDEWEB)

    Cheng, Sirui [School of Materials Science and Engineering, Harbin Institute of Technology, Harbin 150001 (China); Wang, Chunju [Key Laboratory of Micro-Systems and Micro-Structures Manufacturing, Ministry of Education, Harbin Institute of Technology, Harbin 150080 (China); School of Materials Science and Engineering, Harbin Institute of Technology, Harbin 150001 (China); Ma, Mingzhen [State Key Laboratory of Metastable Materials Science and Technology, Yanshan University, Qinhuangdao 066004 (China); Shan, Debin, E-mail: shandebin@hit.edu.cn [State Key Laboratory of Advanced Welding and Joining, Harbin Institute of Technology, Harbin 150001 (China); Key Laboratory of Micro-Systems and Micro-Structures Manufacturing, Ministry of Education, Harbin Institute of Technology, Harbin 150080 (China); School of Materials Science and Engineering, Harbin Institute of Technology, Harbin 150001 (China); Guo, Bin [School of Materials Science and Engineering, Harbin Institute of Technology, Harbin 150001 (China)

    2016-08-15

    In the Zr{sub 41.2}Ti{sub 13.8}Cu{sub 12.5}Ni{sub 10}Be{sub 22.5} (Vit1) alloy undergoing high temperature deformation, its thermal properties and microstructure are quite different from those in the annealing alloy. In order to research the coupled effect of temperature and plastic strain on microstructural evolution of Zr-based amorphous, uniaxial compression test of Vit1 alloy with good amorphous nature has been performed, and then the structural state and thermal properties of Vit1 alloy after thermal deformation and isothermal annealing in the supercooled liquid region were investigated. It is revealed that the deformed specimens possess higher characteristic temperature and lower enthalpy change of microstructural relaxation. In addition, the smaller inter-atomic distance and higher order degree of atomic arrangement can be observed in those deformed Vit1 alloy. That can be deduced that thermal deformation is in favor of the microstructural evolution from a metastable amorphous state to stable crystallization state, because plastic strain promotes the annihilation of free volume and provide excess driving force of atomic diffusion. However, upon increasing the ambient temperature, the influence of plastic deformation on microstructure gradually decreased owing to the decreasing proportion of the plastic deformation-induced annihilation of free volume during the whole thermal deformation process. - Highlights: • The deformed specimens possess closer microstructure and higher characteristic temperatures. • The order degree of microstructures in deformed specimens is higher than that in annealed specimens. • Thermal deformation accelerates the microstructural evolution of Zr-based BMGs. • The influence of thermal deformation on microstructure decreases with the temperature increasing.

  15. Effect of migration based on strategy and cost on the evolution of cooperation

    International Nuclear Information System (INIS)

    Li, Yan; Ye, Hang

    2015-01-01

    Highlights: •Propose a migration based on strategy and cost in the Prisoner’s Dilemma Game. •The level of cooperation without mutation is higher than that with mutation. •Increased costs have no effect on the level of cooperation without mutation. •The level of cooperation decreases with the increase in cost with mutation. •An optimal density value ρ resulting in the maximum level of cooperation exists. -- Abstract: Humans consider not only their own ability but also the environment around them during the process of migration. Based on this fact, we introduce migration based on strategy and cost into the Spatial Prisoner’s Dilemma Game on a two-dimensional grid. The migration means that agents cannot move when all of the neighbors are cooperators; otherwise, agents move with a probability related to payoff and cost. The result obtained by the computer simulation shows that the moving mechanism based on strategy and cost improves the level of cooperation in a wide parameter space. This occurs because movement based on strategy effectively keeps the cooperative clusters and because movement based on cost effectively regulates the rate of movement. Both types of movement provide a favorable guarantee for the evolution of stable cooperation under the mutation rate q = 0.0. In addition, we discuss the effectiveness of the migration mechanism in the evolution of cooperation under the mutation rate q = 0.001. The result indicates that a higher level of cooperation is obtained at a lower migration cost, whereas cooperation is suppressed at a higher migration cost. Our work may provide an effective method for understanding the emergence of cooperation in our society

  16. 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.

  17. A sandwich-like differential B-dot based on EACVD polycrystalline diamond slice

    Science.gov (United States)

    Xu, P.; Yu, Y.; Xu, L.; Zhou, H. Y.; Qiu, C. J.

    2018-06-01

    In this article, we present a method of mass production of a standardized high-performance differential B-dot magnetic probe together with the magnetic field measurement in a pulsed current device with the current up to hundreds of kilo-Amperes. A polycrystalline diamond slice produced in an Electron Assisted Chemical Vapor Deposition device is used as the base and insulating material to imprint two symmetric differential loops for the magnetic field measurement. The SP3 carbon bond in the cubic lattice structure of diamond is confirmed by Raman spectra. The thickness of this slice is 20 μm. A gold loop is imprinted onto each surface of the slice by using the photolithography technique. The inner diameter, width, and thickness of each loop are 0.8 mm, 50 μm, and 1 μm, respectively. It provides a way of measuring the pulsed magnetic field with a high spatial and temporal resolution, especially in limited space. This differential magnetic probe has demonstrated a very good common-mode rejection rate through the pulsed magnetic field measurement.

  18. Investigation into the Influence of Physician for Treatment Based on Syndrome Differentiation

    Directory of Open Access Journals (Sweden)

    Lijie Jiang

    2013-01-01

    Full Text Available Background. The characteristics of treatment based on syndrome differentiation (TBSD cause great challenges to evaluate the effectiveness of the clinical methods. Objectives. This paper aims to evaluate the influence of physician to personalized medicine in the process of TBSD. Methods. We performed a randomized, triple-blind trial involving patients of primary insomnia treated by 3 physicians individually and independently. The patients (n=30 were randomly assigned to receive treatments by the 3 physicians for every visit. However, they always received the treatment, respectively, prescribed by the physician at the first visit. The primary outcome was evaluated, respectively, by the Pittsburgh Sleep Quality Index (PSQI and the TCM symptoms measuring scale. The clinical practices of the physicians were recorded at every visit including diagnostic information, syndrome differentiation, treating principles, and prescriptions. Results. All patients in the 3 groups (30 patients showed significant improvements (>66% according to the PSQI and TCM symptoms measuring scale. Conclusion. The results indicate that although with comparable effectiveness, there exist significant differences in syndrome differentiation, the treating principles, and the prescriptions of the approaches used by the 3 physicians. This means that the physician should be considered as an important factor for individualized medicine and the related TCM clinical research.

  19. The reliability of differentiating neurogenic claudication from vascular claudication based on symptomatic presentation.

    Science.gov (United States)

    Nadeau, Mélissa; Rosas-Arellano, M Patricia; Gurr, Kevin R; Bailey, Stewart I; Taylor, David C; Grewal, Ruby; Lawlor, D Kirk; Bailey, Chris S

    2013-12-01

    Intermittent claudication can be neurogenic or vascular. Physicians use a profile based on symptom attributes to differentiate the 2 types of claudication, and this guides their investigations for diagnosis of the underlying pathology. We evaluated the validity of these symptom attributes in differentiating neurogenic from vascular claudication. Patients with a diagnosis of lumbar spinal stenosis (LSS) or peripheral vascular disease (PVD) who reported claudication answered 14 questions characterizing their symptoms. We determined the sensitivity, specificity and positive and negative likelihood ratios (PLR and NLR) for neurogenic and vascular claudication for each symptom attribute. We studied 53 patients. The most sensitive symptom attribute to rule out LSS was the absence of "triggering of pain with standing alone" (sensitivity 0.97, NLR 0.050). Pain alleviators and symptom location data showed a weak clinical significance for LSS and PVD. Constellation of symptoms yielded the strongest associations: patients with a positive shopping cart sign whose symptoms were located above the knees, triggered with standing alone and relieved with sitting had a strong likelihood of neurogenic claudication (PLR 13). Patients with symptoms in the calf that were relieved with standing alone had a strong likelihood of vascular claudication (PLR 20.0). The classic symptom attributes used to differentiate neurogenic from vascular claudication are at best weakly valid independently. However, certain constellation of symptoms are much more indicative of etiology. These results can guide general practitioners in their evaluation of and investigation for claudication.

  20. Freestanding eggshell membrane-based electrodes for high-performance supercapacitors and oxygen evolution reaction.

    Science.gov (United States)

    Geng, Jing; Wu, Hao; Al-Enizi, Abdullah M; Elzatahry, Ahmed A; Zheng, Gengfeng

    2015-09-14

    A type of freestanding, light-weight eggshell membrane-based electrode is demonstrated for supercapacitors and for oxygen evolution reaction (OER) catalysis. As a widely available daily waste, eggshell membranes have unique porous three-dimensional grid-like fibrous structures with relatively high surface area and abundant macropores, allowing for effective conjugation of carbon nanotubes and growth of NiCo2O4 nanowire arrays, an effective supercapacitor material and OER catalyst. The three-dimensional fibrous eggshell membrane frameworks with carbon nanotubes offer efficient pathways for charge transport, and the macropores between adjacent fibers are fully accessible for electrolytes and bubble evolution. As a supercapacitor, the eggshell membrane/carbon nanotube/NiCo2O4 electrode shows high specific capacitances at current densities from 1 to 20 A g(-1), with excellent capacitance retention (>90%) at 10 A g(-1) for over 10,000 cycles. When employed as an OER catalyst, this eggshell membrane-based electrode exhibits an OER onset potential of 1.53 V vs. the reversible hydrogen electrode (RHE), and a stable catalytic current density of 20 mA cm(-2) at 1.65 V vs. the RHE.

  1. A contribution to the study of plant development evolution based on gene co-expression networks

    Directory of Open Access Journals (Sweden)

    Francisco J. Romero-Campero

    2013-08-01

    Full Text Available Phototrophic eukaryotes are among the most successful organisms on Earth due to their unparalleled efficiency at capturing light energy and fixing carbon dioxide to produce organic molecules. A conserved and efficient network of light-dependent regulatory modules could be at the bases of this success. This regulatory system conferred early advantages to phototrophic eukaryotes that allowed for specialization, complex developmental processes and modern plant characteristics. We have studied light-dependent gene regulatory modules from algae to plants employing integrative-omics approaches based on gene co-expression networks. Our study reveals some remarkably conserved ways in which eukaryotic phototrophs deal with day length and light signaling. Here we describe how a family of Arabidopsis transcription factors involved in photoperiod response has evolved from a single algal gene according to the innovation, amplification and divergence theory of gene evolution by duplication. These modifications of the gene co-expression networks from the ancient unicellular green algae Chlamydomonas reinhardtii to the modern brassica Arabidopsis thaliana may hint on the evolution and specialization of plants and other organisms.

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

    Science.gov (United States)

    Chang, Chia-Hu; Wu, Ja-Ling

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

  3. 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...

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

    Directory of Open Access Journals (Sweden)

    Dorota Jeziorowska

    2017-06-01

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

  5. Differentiation of Enhancing Glioma and Primary Central Nervous System Lymphoma by Texture-Based Machine Learning.

    Science.gov (United States)

    Alcaide-Leon, P; Dufort, P; Geraldo, A F; Alshafai, L; Maralani, P J; Spears, J; Bharatha, A

    2017-06-01

    Accurate preoperative differentiation of primary central nervous system lymphoma and enhancing glioma is essential to avoid unnecessary neurosurgical resection in patients with primary central nervous system lymphoma. The purpose of the study was to evaluate the diagnostic performance of a machine-learning algorithm by using texture analysis of contrast-enhanced T1-weighted images for differentiation of primary central nervous system lymphoma and enhancing glioma. Seventy-one adult patients with enhancing gliomas and 35 adult patients with primary central nervous system lymphomas were included. The tumors were manually contoured on contrast-enhanced T1WI, and the resulting volumes of interest were mined for textural features and subjected to a support vector machine-based machine-learning protocol. Three readers classified the tumors independently on contrast-enhanced T1WI. Areas under the receiver operating characteristic curves were estimated for each reader and for the support vector machine classifier. A noninferiority test for diagnostic accuracy based on paired areas under the receiver operating characteristic curve was performed with a noninferiority margin of 0.15. The mean areas under the receiver operating characteristic curve were 0.877 (95% CI, 0.798-0.955) for the support vector machine classifier; 0.878 (95% CI, 0.807-0.949) for reader 1; 0.899 (95% CI, 0.833-0.966) for reader 2; and 0.845 (95% CI, 0.757-0.933) for reader 3. The mean area under the receiver operating characteristic curve of the support vector machine classifier was significantly noninferior to the mean area under the curve of reader 1 ( P = .021), reader 2 ( P = .035), and reader 3 ( P = .007). Support vector machine classification based on textural features of contrast-enhanced T1WI is noninferior to expert human evaluation in the differentiation of primary central nervous system lymphoma and enhancing glioma. © 2017 by American Journal of Neuroradiology.

  6. A genome-wide analysis of the flax (Linum usitatissimum L.) dirigent protein family: from gene identification and evolution to differential regulation.

    Science.gov (United States)

    Corbin, Cyrielle; Drouet, Samantha; Markulin, Lucija; Auguin, Daniel; Lainé, Éric; Davin, Laurence B; Cort, John R; Lewis, Norman G; Hano, Christophe

    2018-05-01

    Identification of DIR encoding genes in flax genome. Analysis of phylogeny, gene/protein structures and evolution. Identification of new conserved motifs linked to biochemical functions. Investigation of spatio-temporal gene expression and response to stress. Dirigent proteins (DIRs) were discovered during 8-8' lignan biosynthesis studies, through identification of stereoselective coupling to afford either (+)- or (-)-pinoresinols from E-coniferyl alcohol. DIRs are also involved or potentially involved in terpenoid, allyl/propenyl phenol lignan, pterocarpan and lignin biosynthesis. DIRs have very large multigene families in different vascular plants including flax, with most still of unknown function. DIR studies typically focus on a small subset of genes and identification of biochemical/physiological functions. Herein, a genome-wide analysis and characterization of the predicted flax DIR 44-membered multigene family was performed, this species being a rich natural grain source of 8-8' linked secoisolariciresinol-derived lignan oligomers. All predicted DIR sequences, including their promoters, were analyzed together with their public gene expression datasets. Expression patterns of selected DIRs were examined using qPCR, as well as through clustering analysis of DIR gene expression. These analyses further implicated roles for specific DIRs in (-)-pinoresinol formation in seed-coats, as well as (+)-pinoresinol in vegetative organs and/or specific responses to stress. Phylogeny and gene expression analysis segregated flax DIRs into six distinct clusters with new cluster-specific motifs identified. We propose that these findings can serve as a foundation to further systematically determine functions of DIRs, i.e. other than those already known in lignan biosynthesis in flax and other species. Given the differential expression profiles and inducibility of the flax DIR family, we provisionally propose that some DIR genes of unknown function could be involved in

  7. A genome-wide analysis of the flax (Linum usitatissimum L.) dirigent protein family: from gene identification and evolution to differential regulation.

    Energy Technology Data Exchange (ETDEWEB)

    Corbin, Cyrielle; Drouet, Samantha; Markulin, Lucija; Auguin, Daniel; Laine, Eric; Davin, Laurence B.; Cort, John R.; Lewis, Norman G.; Hano, Christophe

    2018-04-30

    Identification of DIR encoding genes in flax genome. Analysis of phylogeny, gene/protein structures and evolution. Identification of new conserved motifs linked to biochemical functions. Investigation of spatio-temporal gene expression and response to stress. Dirigent proteins (DIRs) were discovered during 8-8' lignan biosynthesis studies, through identification of stereoselective coupling to afford either (+)- or (-)-pinoresinols from E-coniferyl alcohol. DIRs are also involved or potentially involved in terpenoid, allyl/propenyl phenol lignan, pterocarpan and lignin biosynthesis. DIRs have very large multigene families in different vascular plants including flax, with most still of unknown function. DIR studies typically focus on a small subset of genes and identification of biochemical/physiological functions. Herein, a genome-wide analysis and characterization of the predicted flax DIR 44-membered multigene family was performed, this species being a rich natural grain source of 8-8' linked secoisolariciresinol-derived lignan oligomers. All predicted DIR sequences, including their promoters, were analyzed together with their public gene expression datasets. Expression patterns of selected DIRs were examined using qPCR, as well as through clustering analysis of DIR gene expression. These analyses further implicated roles for specific DIRs in (-)-pinoresinol formation in seed-coats, as well as (+)-pinoresinol in vegetative organs and/or specific responses to stress. Phylogeny and gene expression analysis segregated flax DIRs into six distinct clusters with new cluster-specific motifs identified. We propose that these findings can serve as a foundation to further systematically determine functions of DIRs, i.e. other than those already known in lignan biosynthesis in flax and other species. Given the differential expression profiles and inducibility of the flax DIR family, we provisionally propose that some DIR genes of unknown function could be involved

  8. Differential Laser Doppler based Non-Contact Sensor for Dimensional Inspection with Error Propagation Evaluation

    Directory of Open Access Journals (Sweden)

    Ketsaya Vacharanukul

    2006-06-01

    Full Text Available To achieve dynamic error compensation in CNC machine tools, a non-contactlaser probe capable of dimensional measurement of a workpiece while it is being machinedhas been developed and presented in this paper. The measurements are automatically fedback to the machine controller for intelligent error compensations. Based on a well resolvedlaser Doppler technique and real time data acquisition, the probe delivers a very promisingdimensional accuracy at few microns over a range of 100 mm. The developed opticalmeasuring apparatus employs a differential laser Doppler arrangement allowing acquisitionof information from the workpiece surface. In addition, the measurements are traceable tostandards of frequency allowing higher precision.

  9. Finding differentially expressed genes in high dimensional data: Rank based test statistic via a distance measure.

    Science.gov (United States)

    Mathur, Sunil; Sadana, Ajit

    2015-12-01

    We present a rank-based test statistic for the identification of differentially expressed genes using a distance measure. The proposed test statistic is highly robust against extreme values and does not assume the distribution of parent population. Simulation studies show that the proposed test is more powerful than some of the commonly used methods, such as paired t-test, Wilcoxon signed rank test, and significance analysis of microarray (SAM) under certain non-normal distributions. The asymptotic distribution of the test statistic, and the p-value function are discussed. The application of proposed method is shown using a real-life data set. © The Author(s) 2011.

  10. Low cost, microcontroller based heating device for multi-wavelength differential scanning fluorimetry.

    Science.gov (United States)

    Hoeser, Jo; Gnandt, Emmanuel; Friedrich, Thorsten

    2018-01-23

    Differential scanning fluorimetry is a popular method to estimate the stability of a protein in distinct buffer conditions by determining its 'melting point'. The method requires a temperature controlled fluorescence spectrometer or a RT-PCR machine. Here, we introduce a low-budget version of a microcontroller based heating device implemented into a 96-well plate reader that is connected to a standard fluorescence spectrometer. We demonstrate its potential to determine the 'melting point' of soluble and membranous proteins at various buffer conditions.

  11. A Lateral Differential Resonant Pressure Microsensor Based on SOI-Glass Wafer-Level Vacuum Packaging

    Directory of Open Access Journals (Sweden)

    Bo Xie

    2015-09-01

    Full Text Available This paper presents the fabrication and characterization of a resonant pressure microsensor based on SOI-glass wafer-level vacuum packaging. The SOI-based pressure microsensor consists of a pressure-sensitive diaphragm at the handle layer and two lateral resonators (electrostatic excitation and capacitive detection on the device layer as a differential setup. The resonators were vacuum packaged with a glass cap using anodic bonding and the wire interconnection was realized using a mask-free electrochemical etching approach by selectively patterning an Au film on highly topographic surfaces. The fabricated resonant pressure microsensor with dual resonators was characterized in a systematic manner, producing a quality factor higher than 10,000 (~6 months, a sensitivity of about 166 Hz/kPa and a reduced nonlinear error of 0.033% F.S. Based on the differential output, the sensitivity was increased to two times and the temperature-caused frequency drift was decreased to 25%.

  12. Investigation of the microcrack evolution in a Ti-based bulk metallic glass matrix composite

    Directory of Open Access Journals (Sweden)

    Yongsheng Wang

    2014-04-01

    Full Text Available The initiation and evolution behavior of the shear-bands and microcracks in a Ti-based metallic-glass–matrix composite (MGMC were investigated by using an in-situ tensile test under transmission electron microscopy (TEM. It was found that the plastic deformation of the Ti-based MGMC related with the generation of the plastic deformation zone in crystalline and shear deformation zone in glass phase near the crack tip. The dendrites can suppress the propagation of the shear band effectively. Before the rapid propagation of cracks, the extending of plastic deformation zone and shear deformation zone ahead of crack tip is the main pattern in the composite.

  13. REDSHIFT EVOLUTION IN BLACK HOLE-BULGE RELATIONS: TESTING C IV-BASED BLACK HOLE MASSES

    International Nuclear Information System (INIS)

    Greene, Jenny E.; Peng, Chien Y.; Ludwig, Randi R.

    2010-01-01

    We re-examine claims for redshift evolution in black hole-bulge scaling relations based on lensed quasars. In particular, we refine the black hole (BH) mass estimates using measurements of Balmer lines from near-infrared spectroscopy obtained with Triplespec at Apache Point Observatory. In support of previous work, we find a large scatter between Balmer and UV line widths, both Mg IIλλ2796, 2803 and C IVλλ1548, 1550. There is tentative evidence that C III]λ1909, despite being a blend of multiple transitions, may correlate well with Mg II, although a larger sample is needed for a real calibration. Most importantly, we find no systematic changes in the estimated BH masses for the lensed sample based on Balmer lines, providing additional support to the interpretation that black holes were overly massive compared to their host galaxies at high redshift.

  14. Opinion evolution based on cellular automata rules in small world networks

    Science.gov (United States)

    Shi, Xiao-Ming; Shi, Lun; Zhang, Jie-Fang

    2010-03-01

    In this paper, we apply cellular automata rules, which can be given by a truth table, to human memory. We design each memory as a tracking survey mode that keeps the most recent three opinions. Each cellular automata rule, as a personal mechanism, gives the final ruling in one time period based on the data stored in one's memory. The key focus of the paper is to research the evolution of people's attitudes to the same question. Based on a great deal of empirical observations from computer simulations, all the rules can be classified into 20 groups. We highlight the fact that the phenomenon shown by some rules belonging to the same group will be altered within several steps by other rules in different groups. It is truly amazing that, compared with the last hundreds of presidential voting in America, the eras of important events in America's history coincide with the simulation results obtained by our model.

  15. Enthalpy-Based Thermal Evolution of Loops: II. Improvements to the Model

    Science.gov (United States)

    Cargill, P. J.; Bradshaw, S. J.; Klimchuk, J. A.

    2011-01-01

    This paper further develops the zero-dimensional (0D) hydrodynamic coronal loop model "Enthalpy-based Thermal Evolution of Loops" (EBTEL) originally proposed by Klimchuk et al (2008), which studies the plasma response to evolving coronal heating. It has typically been applied to impulsive heating events. The basis of EBTEL is the modelling of mass exchange between the corona and transition region and chromosphere in response to heating variations, with the key parameter being the ratio of transition region to coronal radiation. We develop new models for this parameter that now include gravitational stratification and a physically motivated approach to radiative cooling. A number of examples are presented, including nanoflares in short and long loops, and a small flare. It is found that while the evolution of the loop temperature is rather insensitive to the details of the model, accurate tracking of the density requires the inclusion of our new features. In particular, we are able to now obtain highly over-dense loops in the late cooling phase and decreases to the coronal density arising due to stratification. The 0D results are compared to a 1D hydro code (Hydrad). The agreement is acceptable, with the exception of the flare case where some versions of Hydrad can give significantly lower densities. This is attributed to the method used to model the chromosphere in a flare. EBTEL is suitable for general use as a tool for (a) quick-look results of loop evolution in response to a given heating function and (b) situations where the modelling of hundreds or thousands of elemental loops is needed. A single run takes a few seconds on a contemporary laptop.

  16. Redox switching and oxygen evolution at oxidized metal and metal oxide electrodes: iron in base.

    Science.gov (United States)

    Lyons, Michael E G; Doyle, Richard L; Brandon, Michael P

    2011-12-28

    Outstanding issues regarding the film formation, redox switching characteristics and the oxygen evolution reaction (OER) electrocatalytic behaviour of multicycled iron oxyhydroxide films in aqueous alkaline solution have been revisited. The oxide is grown using a repetitive potential multicycling technique, and the mechanism of the latter hydrous oxide formation process has been discussed. A duplex layer model of the oxide/solution interphase region is proposed. The acid/base behaviour of the hydrous oxide and the microdispersed nature of the latter material has been emphasised. The hydrous oxide is considered as a porous assembly of interlinked octahedrally coordinated anionic metal oxyhydroxide surfaquo complexes which form an open network structure. The latter contains considerable quantities of water molecules which facilitate hydroxide ion discharge at the metal site during active oxygen evolution, and also charge compensating cations. The dynamics of redox switching has been quantified via analysis of the cyclic voltammetry response as a function of potential sweep rate using the Laviron-Aoki electron hopping diffusion model by analogy with redox polymer modified electrodes. Steady state Tafel plot analysis has been used to elucidate the kinetics and mechanism of oxygen evolution. Tafel slope values of ca. 60 mV dec(-1) and ca. 120 mV dec(-1) are found at low and high overpotentials respectively, whereas the reaction order with respect to hydroxide ion activity changes from ca. 3/2 to ca. 1 as the potential is increased. These observations are rationalised in terms of a kinetic scheme involving Temkin adsorption and the rate determining formation of a physisorbed hydrogen peroxide intermediate on the oxide surface. The dual Tafel slope behaviour is ascribed to the potential dependence of the surface coverage of adsorbed intermediates.

  17. Structural Evolution of the R-T Phase Boundary in KNN-Based Ceramics

    KAUST Repository

    Lv, Xiang

    2017-10-04

    Although a rhombohedral-tetragonal (R-T) phase boundary is known to substantially enhance the piezoelectric properties of potassium-sodium niobate ceramics, the structural evolution of the R-T phase boundary itself is still unclear. In this work, the structural evolution of R-T phase boundary from -150 °C to 200 °C is investigated in (0.99-x)K0.5Na0.5Nb1-ySbyO3-0.01CaSnO3-xBi0.5K0.5HfO3 (where x=0~0.05 with y=0.035, and y=0~0.07 with x=0.03) ceramics. Through temperature-dependent powder X-ray diffraction (XRD) patterns and Raman spectra, the structural evolution was determined to be Rhombohedral (R, <-125 °C) → Rhombohedral+Orthorhombic (R+O, -125 °C to 0 °C) → Rhombohedral+Tetragonal (R+T, 0 °C to 150 °C) → dominating Tetragonal (T, 200 °C to Curie temperature (TC)) → Cubic (C, >TC). In addition, the enhanced electrical properties (e.g., a direct piezoelectric coefficient (d33) of ~450±5 pC/N, a conversion piezoelectric coefficient (d33*) of ~580±5 pm/V, an electromechanical coupling factor (kp) of ~0.50±0.02, and TC~250 °C), fatigue-free behavior, and good thermal stability were exhibited by the ceramics possessing the R-T phase boundary. This work improves understanding of the physical mechanism behind the R-T phase boundary in KNN-based ceramics and is an important step towards their adoption in practical applications. This article is protected by copyright. All rights reserved.

  18. Magneto-motive detection of tissue-based macrophages by differential phase optical coherence tomography.

    Science.gov (United States)

    Oh, Junghwan; Feldman, Marc D; Kim, Jihoon; Kang, Hyun Wook; Sanghi, Pramod; Milner, Thomas E

    2007-03-01

    A novel method to detect tissue-based macrophages using a combination of superparamagnetic iron oxide (SPIO) nanoparticles and differential phase optical coherence tomography (DP-OCT) with an external oscillating magnetic field is reported. Magnetic force acting on iron-laden tissue-based macrophages was varied by applying a sinusoidal current to a solenoid containing a conical iron core that substantially focused and increased magnetic flux density. Nanoparticle motion was detected with DP-OCT, which can detect tissue movement with nanometer resolution. Frequency response of iron-laden tissue movement was twice the modulation frequency since the magnetic force is proportional to the product of magnetic flux density and gradient. Results of our experiments indicate that DP-OCT can be used to identify tissue-based macrophage when excited by an external focused oscillating magnetic field. (c) 2007 Wiley-Liss, Inc

  19. 3D facial expression recognition based on histograms of surface differential quantities

    KAUST Repository

    Li, Huibin

    2011-01-01

    3D face models accurately capture facial surfaces, making it possible for precise description of facial activities. In this paper, we present a novel mesh-based method for 3D facial expression recognition using two local shape descriptors. To characterize shape information of the local neighborhood of facial landmarks, we calculate the weighted statistical distributions of surface differential quantities, including histogram of mesh gradient (HoG) and histogram of shape index (HoS). Normal cycle theory based curvature estimation method is employed on 3D face models along with the common cubic fitting curvature estimation method for the purpose of comparison. Based on the basic fact that different expressions involve different local shape deformations, the SVM classifier with both linear and RBF kernels outperforms the state of the art results on the subset of the BU-3DFE database with the same experimental setting. © 2011 Springer-Verlag.

  20. Density-based Monte Carlo filter and its applications in nonlinear stochastic differential equation models.

    Science.gov (United States)

    Huang, Guanghui; Wan, Jianping; Chen, Hui

    2013-02-01

    Nonlinear stochastic differential equation models with unobservable state variables are now widely used in analysis of PK/PD data. Unobservable state variables are usually estimated with extended Kalman filter (EKF), and the unknown pharmacokinetic parameters are usually estimated by maximum likelihood estimator. However, EKF is inadequate for nonlinear PK/PD models, and MLE is known to be biased downwards. A density-based Monte Carlo filter (DMF) is proposed to estimate the unobservable state variables, and a simulation-based M estimator is proposed to estimate the unknown parameters in this paper, where a genetic algorithm is designed to search the optimal values of pharmacokinetic parameters. The performances of EKF and DMF are compared through simulations for discrete time and continuous time systems respectively, and it is found that the results based on DMF are more accurate than those given by EKF with respect to mean absolute error. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. On cooperative and efficient overlay network evolution based on a group selection pattern.

    Science.gov (United States)

    Nakao, Akihiro; Wang, Yufeng

    2010-04-01

    In overlay networks, the interplay between network structure and dynamics remains largely unexplored. In this paper, we study dynamic coevolution between individual rational strategies (cooperative or defect) and the overlay network structure, that is, the interaction between peer's local rational behaviors and the emergence of the whole network structure. We propose an evolutionary game theory (EGT)-based overlay topology evolution scheme to drive a given overlay into the small-world structure (high global network efficiency and average clustering coefficient). Our contributions are the following threefold: From the viewpoint of peers' local interactions, we explicitly consider the peer's rational behavior and introduce a link-formation game to characterize the social dilemma of forming links in an overlay network. Furthermore, in the evolutionary link-formation phase, we adopt a simple economic process: Each peer keeps one link to a cooperative neighbor in its neighborhood, which can slightly speed up the convergence of cooperation and increase network efficiency; from the viewpoint of the whole network structure, our simulation results show that the EGT-based scheme can drive an arbitrary overlay network into a fully cooperative and efficient small-world structure. Moreover, we compare our scheme with a search-based economic model of network formation and illustrate that our scheme can achieve the experimental and analytical results in the latter model. In addition, we also graphically illustrate the final overlay network structure; finally, based on the group selection model and evolutionary set theory, we theoretically obtain the approximate threshold of cost and draw the conclusion that the small value of the average degree and the large number of the total peers in an overlay network facilitate the evolution of cooperation.

  2. On the nature and evolution of the neural bases of human language

    Science.gov (United States)

    Lieberman, Philip

    2002-01-01

    The traditional theory equating the brain bases of language with Broca's and Wernicke's neocortical areas is wrong. Neural circuits linking activity in anatomically segregated populations of neurons in subcortical structures and the neocortex throughout the human brain regulate complex behaviors such as walking, talking, and comprehending the meaning of sentences. When we hear or read a word, neural structures involved in the perception or real-world associations of the word are activated as well as posterior cortical regions adjacent to Wernicke's area. Many areas of the neocortex and subcortical structures support the cortical-striatal-cortical circuits that confer complex syntactic ability, speech production, and a large vocabulary. However, many of these structures also form part of the neural circuits regulating other aspects of behavior. For example, the basal ganglia, which regulate motor control, are also crucial elements in the circuits that confer human linguistic ability and abstract reasoning. The cerebellum, traditionally associated with motor control, is active in motor learning. The basal ganglia are also key elements in reward-based learning. Data from studies of Broca's aphasia, Parkinson's disease, hypoxia, focal brain damage, and a genetically transmitted brain anomaly (the putative "language gene," family KE), and from comparative studies of the brains and behavior of other species, demonstrate that the basal ganglia sequence the discrete elements that constitute a complete motor act, syntactic process, or thought process. Imaging studies of intact human subjects and electrophysiologic and tracer studies of the brains and behavior of other species confirm these findings. As Dobzansky put it, "Nothing in biology makes sense except in the light of evolution" (cited in Mayr, 1982). That applies with as much force to the human brain and the neural bases of language as it does to the human foot or jaw. The converse follows: the mark of evolution on

  3. Modulating functions-based method for parameters and source estimation in one-dimensional partial differential equations

    KAUST Repository

    Asiri, Sharefa M.; Laleg-Kirati, Taous-Meriem

    2016-01-01

    In this paper, modulating functions-based method is proposed for estimating space–time-dependent unknowns in one-dimensional partial differential equations. The proposed method simplifies the problem into a system of algebraic equations linear

  4. Education based thinking and behaving? Towards an identity perspective for studying education differentials in public opinion and political participation

    NARCIS (Netherlands)

    Spruyt, Bram; Kuppens, Toon

    2015-01-01

    Education based thinking and behaving? Towards and identity perspective for studying education differentials in public opinion and political participation Abstract Ever since scholars started studying public opinion and political behaviour, they have reported substantial educational differences.

  5. Method of Monitoring Urban Area Deformation Based on Differential TomoSAR

    Directory of Open Access Journals (Sweden)

    WANG Aichun

    2016-12-01

    Full Text Available While the use of differential TomoSAR based on compressive sensing (CS makes it possible to solve the layover problem and reconstruct the deformation information of an observed urban area scene acquired by moderate-high resolution SAR satellite, the performance of the reconstruction decreases for a sparse and structural observed scene due to ignoring the structural characteristics of the observed scene. To deal with this issue, the method for differential SAR tomography based on Khatri-Rao subspace and block compressive sensing (KRS-BCS is proposed. The proposed method changes the reconstruction of the sparse and structural observed scene into a BCS problem under Khatri-Rao subspace, using the structure information of the observed scene and Khatri-Rao product property of the reconstructed observation matrix for differential TomoSAR, such that the KRS-BCS problem is efficiently solved with a block sparse l1/l2 norm optimization signal model, and the performance of resolution capability and reconstruction estimation is compared and analyzed qualitatively and quantitatively by the theoretical analysis and the simulation experiments, all of the results show the propose KRS-BCS method practicably overcomes the problems of CS method, as well as, quite maintains the high resolution characteristics, effectively reduces the probability of false scattering target and greatly improves the reconstruction accurate of scattering point. Finally, the application is taking the urban area of the Mobara(in Chiba, Japan as the test area and using 34 ENVISAT-ASAR images, the accuracy is verifying with the reference deformations derived from first level point data and GPS tracking data, the results show the trend is consistent and the overall deviation is small between reconstruction deformations of the propose KRS-BCS method and the reference deformations, and the accuracy is high in the estimation of the urban area deformation.

  6. Microstructure evolution of Fe-based nanostructured bainite coating by laser cladding

    International Nuclear Information System (INIS)

    Guo, Yanbing; Li, Zhuguo; Yao, Chengwu; Zhang, Ke; Lu, Fenggui; Feng, Kai; Huang, Jian; Wang, Min; Wu, Yixiong

    2014-01-01

    Highlights: • The laser cladding and isothermal holding are used to fabricate nanobainite coating. • Fine prior austenite is obtained to accelerate the bainite transformation. • Low transformation temperature results in fine bainite ferrite and film austenite. • Retained austenite volume fraction in bainite coating is determined by XRD. • Evolution of carbon content in austenite and ferrite is analyzed. - Abstract: A Fe-based coating with nano-scale bainitic microstructure was fabricated using laser cladding and subsequent isothermal heat treatment. The microstructure of the coating was observed and analyzed using optical microscope (OM), field-emission scanning electron microscope (FE-SEM), transmission electron microscope (TEM) and X-ray diffraction (XRD). The results showed that nanostructured bainitic ferrite and carbon-enriched retained austenite distributed uniformly in the coating. Blocky retained austenite was confined to the prior austenite grain boundaries resulting from the elements segregation. The bainitic microstructure obtained at 250 °C had a finer scale compared with that obtained at 300 °C. The volume fraction of austenite increased with increasing transformation temperature for the fully transformed bainitic coating. The bainitic transformation was accelerated as a result of the fine prior austenite generated during the laser cladding. The evolution of the carbon contents in bainitic ferrite and retained austenite revealed the diffusionless mechanism of the bainitic transformation

  7. FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants.

    Science.gov (United States)

    Bednar, David; Beerens, Koen; Sebestova, Eva; Bendl, Jaroslav; Khare, Sagar; Chaloupkova, Radka; Prokop, Zbynek; Brezovsky, Jan; Baker, David; Damborsky, Jiri

    2015-11-01

    There is great interest in increasing proteins' stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt's reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔTm = 24°C and 21°C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.

  8. FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants.

    Directory of Open Access Journals (Sweden)

    David Bednar

    2015-11-01

    Full Text Available There is great interest in increasing proteins' stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt's reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔTm = 24°C and 21°C by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.

  9. The Formation and Evolution of Shear Bands in Plane Strain Compressed Nickel-Base Superalloy

    Directory of Open Access Journals (Sweden)

    Bin Tang

    2018-02-01

    Full Text Available The formation and evolution of shear bands in Inconel 718 nickel-base superalloy under plane strain compression was investigated in the present work. It is found that the propagation of shear bands under plane strain compression is more intense in comparison with conventional uniaxial compression. The morphology of shear bands was identified to generally fall into two categories: in “S” shape at severe conditions (low temperatures and high strain rates and “X” shape at mild conditions (high temperatures and low strain rates. However, uniform deformation at the mesoscale without shear bands was also obtained by compressing at 1050 °C/0.001 s−1. By using the finite element method (FEM, the formation mechanism of the shear bands in the present study was explored for the special deformation mode of plane strain compression. Furthermore, the effect of processing parameters, i.e., strain rate and temperature, on the morphology and evolution of shear bands was discussed following a phenomenological approach. The plane strain compression attempt in the present work yields important information for processing parameters optimization and failure prediction under plane strain loading conditions of the Inconel 718 superalloy.

  10. Constraint Differentiation

    DEFF Research Database (Denmark)

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

    2010-01-01

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

  11. HYPERDIRE. HYPERgeometric functions DIfferential REduction. MATEMATICA based packages for differential reduction of generalized hypergeometric functions. FD and FS Horn-type hypergeometric functions of three variables

    International Nuclear Information System (INIS)

    Bytev, Vladimir V.; Kalmykov, Mikhail Yu.; Moch, Sven-Olaf; Hamburg Univ.

    2013-12-01

    HYPERDIRE is a project devoted to the creation of a set of Mathematica based programs for the differential reduction of hypergeometric functions. The current version includes two parts: the first one, FdFunction, for manipulations with Appell hypergeometric functions F D of r variables; and the second one, FsFunction, for manipulations with Lauricella-Saran hypergeometric functions F S of three variables. Both functions are related with one-loop Feynman diagrams.

  12. HYPERDIRE. HYPERgeometric functions DIfferential REduction. MATHEMATICA based packages for differential reduction of generalized hypergeometric functions pFp-1, F1, F2, F3, F4

    International Nuclear Information System (INIS)

    Bytev, Vladimir V.; Kalmykov, Mikhail Yu.; Kniehl, Bernd A.

    2013-05-01

    HYPERDIRE is a project devoted to the creation of a set of Mathematica based programs for the differential reduction of hypergeometric functions. The current version includes two parts: one, pfq, is relevant for manipulations of hypergeometric functions p+1 F p , and the second one, AppellF1F4, for manipulations with Appell hypergeometric functions F 1 , F 2 , F 3 , F 4 of two variables.

  13. High-brightness electron beam evolution following laser-based cleaning of a photocathode

    Directory of Open Access Journals (Sweden)

    F. Zhou

    2012-09-01

    Full Text Available Laser-based techniques have been widely used for cleaning metal photocathodes to increase quantum efficiency (QE. However, the impact of laser cleaning on cathode uniformity and thereby on electron beam quality are less understood. We are evaluating whether this technique can be applied to revive photocathodes used for high-brightness electron sources in advanced x-ray free-electron laser (FEL facilities, such as the Linac Coherent Light Source (LCLS at the SLAC National Accelerator Laboratory. The laser-based cleaning was applied to two separate areas of the current LCLS photocathode on July 4 and July 26, 2011, respectively. The QE was increased by 8–10 times upon the laser cleaning. Since the cleaning, routine operation has exhibited a slow evolution of the QE improvement and comparatively rapid improvement of transverse emittance, with a factor of 3 QE enhancement over five months, and a significant emittance improvement over the initial 2–3 weeks following the cleaning. Currently, the QE of the LCLS photocathode is holding constant at about 1.2×10^{-4}, with a normalized injector emittance of about 0.3  μm for a 150-pC bunch charge. With the proper procedures, the laser-cleaning technique appears to be a viable tool to revive the LCLS photocathode. We present observations and analyses for the QE and emittance evolution in time following the laser-based cleaning of the LCLS photocathode, and comparison to the previous studies, the measured thermal emittance versus the QE and comparison to the theoretical model.

  14. Generalized query-based active learning to identify differentially methylated regions in DNA.

    Science.gov (United States)

    Haque, Md Muksitul; Holder, Lawrence B; Skinner, Michael K; Cook, Diane J

    2013-01-01

    Active learning is a supervised learning technique that reduces the number of examples required for building a successful classifier, because it can choose the data it learns from. This technique holds promise for many biological domains in which classified examples are expensive and time-consuming to obtain. Most traditional active learning methods ask very specific queries to the Oracle (e.g., a human expert) to label an unlabeled example. The example may consist of numerous features, many of which are irrelevant. Removing such features will create a shorter query with only relevant features, and it will be easier for the Oracle to answer. We propose a generalized query-based active learning (GQAL) approach that constructs generalized queries based on multiple instances. By constructing appropriately generalized queries, we can achieve higher accuracy compared to traditional active learning methods. We apply our active learning method to find differentially DNA methylated regions (DMRs). DMRs are DNA locations in the genome that are known to be involved in tissue differentiation, epigenetic regulation, and disease. We also apply our method on 13 other data sets and show that our method is better than another popular active learning technique.

  15. A test of the California competency-based differentiated role model.

    Science.gov (United States)

    Keating, Sarah B; Rutledge, Dana N; Sargent, Arlene; Walker, Polly

    2003-01-01

    To address the incongruence between the expectations of nursing service and education in California, the Education Industry Interface Task Force of the California Strategic Planning Committee for Nursing developed descriptions to assist employers and educators in clearly differentiating practice and educational competencies. The completion of the Competency-Based Role Differentiation Model resulted in the need to test the model for its utility in the service setting, in education, and for career planning for nurses. Three alpha demonstration sites were selected based on representative geographical regions of California. The sites were composed of tri-partnerships consisting of a medical center, an associate degree in nursing program, and a baccalaureate nursing program. Observers rated senior students and new graduates in medical-surgical units on their behaviors in teacher and leadership care provider and care coordinator roles. The alpha demonstration study results were as expected. That is, senior students practice predominantly at a novice level in teacher and management/leadership care provider functions and new graduates practice predominately at the competent level. New graduates are more likely to take on novice and competent care coordinator roles. The CBRDM may be useful for practice and education settings to evaluate student and nurse performance, to define role expectations, and to identify the preparation necessary for the roles. It is useful for all of nursing as it continues to define its levels of practice and their relationship to on-the-job performance, curriculum development, and carrier planning.

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

    Directory of Open Access Journals (Sweden)

    Pandu Sandi Pratama

    2012-12-01

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

  17. Monitoring Bone Tissue Engineered (BTE) Constructs Based on the Shifting Metabolism of Differentiating Stem Cells.

    Science.gov (United States)

    Simmons, Aaron D; Sikavitsas, Vassilios I

    2018-01-01

    Ever-increasing demand for bone grafts necessitates the realization of clinical implementation of bone tissue engineered constructs. The predominant hurdle to implementation remains to be securing FDA approval, based on the lack of viable methods for the rigorous monitoring of said constructs. The study presented herein details a method for such monitoring based on the shifting metabolism of mesenchymal stem cells (MSCs) as they differentiate into osteoblasts. To that end, rat MSCs seeded on 85% porous spunbonded poly(L-lactic acid) scaffolds were cultured in flow perfusion bioreactors with baseline or osteoinductive media, and levels of key physio-metabolic markers (oxygen, glucose, osteoprotegerin, and osteocalcin) were monitored throughout culture. Comparison of these non-destructively obtained values and current standard destructive analyses demonstrated key trends useful for the concurrent real-time monitoring of construct cellularity and maturation. Principle among these is the elucidation of the ratio of the rates of oxygen uptake to glucose consumption as a powerful quality marker. This ratio, supported on a physiological basis, has been shown herein to be reliable in the determination of both construct maturation (defined as osteoblastic differentiation and accompanying mineralization) and construct cellularity. Supplementary monitoring of OPG and OCN are shown to provide further validation of such metrics.

  18. The evolution of cranial base and face in Cercopithecoidea and Hominoidea: Modularity and morphological integration.

    Science.gov (United States)

    Profico, Antonio; Piras, Paolo; Buzi, Costantino; Di Vincenzo, Fabio; Lattarini, Flavio; Melchionna, Marina; Veneziano, Alessio; Raia, Pasquale; Manzi, Giorgio

    2017-12-01

    The evolutionary relationship between the base and face of the cranium is a major topic of interest in primatology. Such areas of the skull possibly respond to different selective pressures. Yet, they are often said to be tightly integrated. In this paper, we analyzed shape variability in the cranial base and the facial complex in Cercopithecoidea and Hominoidea. We used a landmark-based approach to single out the effects of size (evolutionary allometry), morphological integration, modularity, and phylogeny (under Brownian motion) on skull shape variability. Our results demonstrate that the cranial base and the facial complex exhibit different responses to different factors, which produces a little degree of morphological integration between them. Facial shape variation appears primarily influenced by body size and sexual dimorphism, whereas the cranial base is mostly influenced by functional factors. The different adaptations affecting the two modules suggest they are best studied as separate and independent units, and that-at least when dealing with Catarrhines-caution must be posed with the notion of strong cranial integration that is commonly invoked for the evolution of their skull shape. © 2017 Wiley Periodicals, Inc.

  19. Evolution of the DeNOC-based dynamic modelling for multibody systems

    Directory of Open Access Journals (Sweden)

    S. K. Saha

    2013-01-01

    Full Text Available Dynamic modelling of a multibody system plays very essential role in its analyses. As a result, several methods for dynamic modelling have evolved over the years that allow one to analyse multibody systems in a very efficient manner. One such method of dynamic modelling is based on the concept of the Decoupled Natural Orthogonal Complement (DeNOC matrices. The DeNOC-based methodology for dynamics modelling, since its introduction in 1995, has been applied to a variety of multibody systems such as serial, parallel, general closed-loop, flexible, legged, cam-follower, and space robots. The methodology has also proven useful for modelling of proteins and hyper-degree-of-freedom systems like ropes, chains, etc. This paper captures the evolution of the DeNOC-based dynamic modelling applied to different type of systems, and its benefits over other existing methodologies. It is shown that the DeNOC-based modelling provides deeper understanding of the dynamics of a multibody system. The power of the DeNOC-based modelling has been illustrated using several numerical examples.

  20. Spinocerebellar ataxia type 2 neurodegeneration differentially affects error-based and strategic-based visuomotor learning.

    Science.gov (United States)

    Vaca-Palomares, Israel; Díaz, Rosalinda; Rodríguez-Labrada, Roberto; Medrano-Montero, Jacqeline; Vázquez-Mojena, Yaimé; Velázquez-Pérez, Luis; Fernandez-Ruiz, Juan

    2013-12-01

    There are different types of visuomotor learning. Among the most studied is motor error-based learning where the sign and magnitude of the error are used to update motor commands. However, there are other instances where individuals show visuomotor learning even if the sign or magnitude of the error is precluded. Studies with patients suggest that the former learning is impaired after cerebellar lesions, while basal ganglia lesions disrupt the latter. Nevertheless, the cerebellar role is not restricted only to error-based learning, but it also contributes to several cognitive processes. Therefore, here, we tested if cerebellar ataxia patients are affected in two tasks, one that depends on error-based learning and the other that prevents the use of error-based learning. Our results showed that cerebellar patients have deficits in both visuomotor tasks; however, while error-based learning tasks deficits correlated with the motor impairments, the motor error-dependent task did not correlate with any motor measure.

  1. X-Ray Pulsar Profile Recovery Based on Tracking-Differentiator

    Directory of Open Access Journals (Sweden)

    Dapeng Zhang

    2016-01-01

    Full Text Available The profile recovery is an important work in X-ray pulsar-based navigation. It is a key step for the analysis on the pulsar signal’s characteristic and the computing of time of arrival (TOA. This paper makes an argument for an algorithm based on the tracking-differentiator (TD to recover the profile from the low Signal-to-Noise Ratio (SNR signals. In the method, a TD filter with cascade structure is designed which has very low phase delay and amplitude distortion. In the simulation experiment, two typical pulsars (PSR B0531+21 and PSR B1937+21 are used to verify the algorithm’s performance. The simulation results show that the method satisfies the application requirements in the aspects of SNR and profile fidelity. By processing the data collected by the Rossi X-Ray Timing Explorer (RXTE satellite in space, similar results can also be achieved.

  2. Diagnostic of the temperature and differential emission measure (DEM based on Hinode/XRT data

    Directory of Open Access Journals (Sweden)

    P. Rudawy

    2008-10-01

    Full Text Available We discuss here various methodologies and an optimal strategy of the temperature and emission measure diagnostics based on Hinode X-Ray Telescope data. As an example of our results we present the determination of the temperature distribution of the X-rays emitting plasma using a filters ratio method and three various methods of the calculation of the differential emission measure (DEM. We have found that all these methods give results similar to the two filters ratio method. Additionally, all methods of the DEM calculation gave similar solutions. We can state that the majority of the pairs of the Hinode filters allows one to derive the temperature and emission measure in the isothermal plasma approximation using standard diagnostics based on the two filters ratio method. In cases of strong flares one can also expect good conformity of the results obtained using a Withbroe – Sylwester, genetic algorithm and least-squares methods of the DEM evaluation.

  3. Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

    Science.gov (United States)

    Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B

    2013-03-23

    Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.

  4. Resolving glass transition in Te-based phase-change materials by modulated differential scanning calorimetry

    Science.gov (United States)

    Chen, Yimin; Mu, Sen; Wang, Guoxiang; Shen, Xiang; Wang, Junqiang; Dai, Shixun; Xu, Tiefeng; Nie, Qiuhua; Wang, Rongping

    2017-10-01

    Glass transitions of Te-based phase-change materials (PCMs) were studied by modulated differential scanning calorimetry. It was found that both Ge2Sb2Te5 and GeTe are marginal glass formers with ΔT (= T x - T g) less than 2.1 °C when the heating rate is below 3 °C min-1. The fragilities of Ge2Sb2Te5 and GeTe can be estimated as 46.0 and 39.7, respectively, around the glass transition temperature, implying that a fragile-to-strong transition would be presented in such Te-based PCMs. The above results provide direct experimental evidence to support the investigation of crystallization kinetics in supercooled liquid PCMs.

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

    Directory of Open Access Journals (Sweden)

    Achim Salamon

    2014-02-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  7. Effects of sintering temperature on the microstructural evolution and wear behavior of WCp reinforced Ni-based coatings

    Science.gov (United States)

    Chen, Chuan-hui; Bai, Yang; Ye, Xu-chu

    2014-12-01

    This article focuses on the microstructural evolution and wear behavior of 50wt%WC reinforced Ni-based composites prepared onto 304 stainless steel substrates by vacuum sintering at different sintering temperatures. The microstructure and chemical composition of the coatings were investigated by X-ray diffraction (XRD), differential thermal analysis (DTA), scanning and transmission electron microscopy (SEM and TEM) equipped with energy-dispersive X-ray spectroscopy (EDS). The wear resistance of the coatings was tested by thrust washer testing. The mechanisms of the decomposition, dissolution, and precipitation of primary carbides, and their influences on the wear resistance have been discussed. The results indicate that the coating sintered at 1175°C is composed of fine WC particles, coarse M6C (M=Ni, Fe, Co, etc.) carbides, and discrete borides dispersed in solid solution. Upon increasing the sintering temperature to 1225°C, the microstructure reveals few incompletely dissolved WC particles trapped in larger M6C, Cr-rich lamellar M23C6, and M3C2 in the austenite matrix. M23C6 and M3C2 precipitates are formed in both the γ/M6C grain boundary and the matrix. These large-sized and lamellar brittle phases tend to weaken the wear resistance of the composite coatings. The wear behavior is controlled simultaneously by both abrasive wear and adhesive wear. Among them, abrasive wear plays a major role in the wear process of the coating sintered at 1175°C, while the effect of adhesive wear is predominant in the coating sintered at 1225°C.

  8. Geotectonic evolution of lunar LQ-4 region based on multisource data

    Directory of Open Access Journals (Sweden)

    Jianping Chen

    2014-03-01

    Full Text Available The Sinus Iridum region, the first choice for China's “Lunar Exploration Project” is located at the center of the lunar LQ-4 area and is the site of Chang'e-3 (CE-3's soft landing. To make the scientific exploration of Chang'e-3 more targeted and scientific, and to obtain a better macro-level understanding of the geotectonic environment of the Sinus Iridum region, the tectonic elements in LQ-4 region have been studied and the typical structures were analyzed statistically using data from CE-1, Clementine, LRO and Lunar Prospector missions. Also, the mineral components and periods of mare basalt activities in the study area have been ascertained. The present study divides the tectonic units and establishes the major tectonic events and sequence of evolution in the study area based on morphology, mineral constituents, and tectonic element distribution.

  9. Agent-Based Model to Study and Quantify the Evolution Dynamics of Android Malware Infection

    Directory of Open Access Journals (Sweden)

    Juan Alegre-Sanahuja

    2014-01-01

    Full Text Available In the last years the number of malware Apps that the users download to their devices has risen. In this paper, we propose an agent-based model to quantify the Android malware infection evolution, modeling the behavior of the users and the different markets where the users may download Apps. The model predicts the number of infected smartphones depending on the type of malware. Additionally, we will estimate the cost that the users should afford when the malware is in their devices. We will be able to analyze which part is more critical: the users, giving indiscriminate permissions to the Apps or not protecting their devices with antivirus software, or the Android platform, due to the vulnerabilities of the Android devices that permit their rooted. We focus on the community of Valencia, Spain, although the obtained results can be extrapolated to other places where the number of Android smartphones remains fairly stable.

  10. Phase-field modelling of as-cast microstructure evolution in nickel-based superalloys

    Energy Technology Data Exchange (ETDEWEB)

    Warnken, N., E-mail: n.warnken@bham.ac.uk [University of Birmingham, Department of Metallurgy and Materials, Edgbaston, Birmingham B15 2TT (United Kingdom); Ma, D. [Foundry Institute of the RWTH-Aachen, Intzestr. 5, 52072 Aachen (Germany); Drevermann, A. [ACCESS e.V., Intzestr. 5, 52072 Aachen (Germany); Reed, R.C. [University of Birmingham, Department of Metallurgy and Materials, Edgbaston, Birmingham B15 2TT (United Kingdom); Fries, S.G. [SGF Consultancy, 52064 Aachen (Germany)] [ICAMS, Ruhr University Bochum, Stiepeler Strasse 129, D-44780 Bochum (Germany); Steinbach, I. [ICAMS, Ruhr University Bochum, Stiepeler Strasse 129, D-44780 Bochum (Germany)

    2009-11-15

    A modelling approach is presented for the prediction of microstructure evolution during directional solidification of nickel-based superalloys. A phase-field model is coupled to CALPHAD thermodynamic and kinetic (diffusion) databases, so that a multicomponent alloy representative of those used in industrial practice can be handled. Dendritic growth and the formation of interdendritic phases in an isothermal (2-D) cross-section are simulated for a range of solidification parameters. The sensitivity of the model to changes in the solidification input parameters is investigated. It is demonstrated that the predicted patterns of microsegregation obtained from the simulations compare well to the experimental ones; moreover, an experimentally observed change in the solidification sequence is correctly predicted. The extension of the model to 3-D simulations is demonstrated. Simulations of the homogenization of the as-cast structure during heat treatment are presented.

  11. Phase-field modelling of as-cast microstructure evolution in nickel-based superalloys

    International Nuclear Information System (INIS)

    Warnken, N.; Ma, D.; Drevermann, A.; Reed, R.C.; Fries, S.G.; Steinbach, I.

    2009-01-01

    A modelling approach is presented for the prediction of microstructure evolution during directional solidification of nickel-based superalloys. A phase-field model is coupled to CALPHAD thermodynamic and kinetic (diffusion) databases, so that a multicomponent alloy representative of those used in industrial practice can be handled. Dendritic growth and the formation of interdendritic phases in an isothermal (2-D) cross-section are simulated for a range of solidification parameters. The sensitivity of the model to changes in the solidification input parameters is investigated. It is demonstrated that the predicted patterns of microsegregation obtained from the simulations compare well to the experimental ones; moreover, an experimentally observed change in the solidification sequence is correctly predicted. The extension of the model to 3-D simulations is demonstrated. Simulations of the homogenization of the as-cast structure during heat treatment are presented.

  12. The evolution of human mobility based on the public goods game

    Science.gov (United States)

    Yan, Shiqing

    2017-07-01

    We explore the evolution of human mobility behavior based on public goods game. By using mean field method, the population distribution in different regions is theoretical calculated. Numerical simulation results show that the correlation between the region's degree and its final population is not significant under a larger human migration rate. Human mobility could effectively promote cooperative behavior and the population balance of different regions. Therefore, encouraging individuals to migrate may increase the total benefits of the whole society. Moreover, increasing the cooperation cost could reduce the number of cooperators, and that would happen to the correlation between the region's degree and its final population. The results indicate the total population could not dramatically rise with the region's degree under an unfair society.

  13. Titanium-Phosphonate-Based Metal-Organic Frameworks with Hierarchical Porosity for Enhanced Photocatalytic Hydrogen Evolution

    KAUST Repository

    Li, Hui

    2018-02-01

    Photocatalytic hydrogen production is crucial for solar-to-chemical conversion process, wherein high-efficiency photocatalysts lie in the heart of this area. Herein a new photocatalyst of hierarchically mesoporous titanium-phosphonate-based metal-organic frameworks, featuring well-structured spheres, periodic mesostructure and large secondary mesoporosity, are rationally designed with the complex of polyelectrolyte and cathodic surfactant serving as the template. The well-structured hierarchical porosity and homogeneously incorporated phosphonate groups can favor the mass transfer and strong optical absorption during the photocatalytic reactions. Correspondingly, the titanium phosphonates exhibit significantly improved photocatalytic hydrogen evolution rate along with impressive stability. This work can provide more insights into designing advanced photocatalysts for energy conversion and render a tunable platform in photoelectrochemical field.

  14. Titanium-Phosphonate-Based Metal-Organic Frameworks with Hierarchical Porosity for Enhanced Photocatalytic Hydrogen Evolution

    KAUST Repository

    Li, Hui; Sun, Ying; Yuan, Zhong-Yong; Zhu, Yun-Pei; Ma, Tianyi

    2018-01-01

    Photocatalytic hydrogen production is crucial for solar-to-chemical conversion process, wherein high-efficiency photocatalysts lie in the heart of this area. Herein a new photocatalyst of hierarchically mesoporous titanium-phosphonate-based metal-organic frameworks, featuring well-structured spheres, periodic mesostructure and large secondary mesoporosity, are rationally designed with the complex of polyelectrolyte and cathodic surfactant serving as the template. The well-structured hierarchical porosity and homogeneously incorporated phosphonate groups can favor the mass transfer and strong optical absorption during the photocatalytic reactions. Correspondingly, the titanium phosphonates exhibit significantly improved photocatalytic hydrogen evolution rate along with impressive stability. This work can provide more insights into designing advanced photocatalysts for energy conversion and render a tunable platform in photoelectrochemical field.

  15. On Religion and Language Evolutions Seen Through Mathematical and Agent Based Models

    Science.gov (United States)

    Ausloos, M.

    Religions and languages are social variables, like age, sex, wealth or political opinions, to be studied like any other organizational parameter. In fact, religiosity is one of the most important sociological aspects of populations. Languages are also obvious characteristics of the human species. Religions, languages appear though also disappear. All religions and languages evolve and survive when they adapt to the society developments. On the other hand, the number of adherents of a given religion, or the number of persons speaking a language is not fixed in time, - nor space. Several questions can be raised. E.g. from a oscopic point of view : How many religions/languages exist at a given time? What is their distribution? What is their life time? How do they evolve? From a "microscopic" view point: can one invent agent based models to describe oscopic aspects? Do simple evolution equations exist? How complicated must be a model? These aspects are considered in the present note. Basic evolution equations are outlined and critically, though briefly, discussed. Similarities and differences between religions and languages are summarized. Cases can be illustrated with historical facts and data. It is stressed that characteristic time scales are different. It is emphasized that "external fields" are historically very relevant in the case of religions, rending the study more " interesting" within a mechanistic approach based on parity and symmetry of clusters concepts. Yet the modern description of human societies through networks in reported simulations is still lacking some mandatory ingredients, i.e. the non scalar nature of the nodes, and the non binary aspects of nodes and links, though for the latter this is already often taken into account, including directions. From an analytical point of view one can consider a population independently of the others. It is intuitively accepted, but also found from the statistical analysis of the frequency distribution that an

  16. Microstructure evolution and texture development in thermomechanically processed Mg-Li-Al based alloys

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Vinod [Department of Materials Science and Engineering, IIT Kanpur (India); Govind [Vikram Sarabhai Space Center, Trivandrum (India); Shekhar, Rajiv; Balasubramaniam, R. [Department of Materials Science and Engineering, IIT Kanpur (India); Balani, Kantesh, E-mail: kbalani@iitk.ac.in [Department of Materials Science and Engineering, IIT Kanpur (India)

    2012-06-15

    Highlights: Black-Right-Pointing-Pointer Thermomechanical processing of novel LAT 971 and LATZ 9531 Mg-Al-Li based alloys. Black-Right-Pointing-Pointer Microstructural deviation from the equilibrium phase diagram. Black-Right-Pointing-Pointer Disparity in texture of these alloys after hot-rolling (recrystallization and grain growth). Black-Right-Pointing-Pointer Role of alloying and phase distribution in affecting the texture/interplaner spacing. - Abstract: In the present study, the influence of alloying and thermomechanical processing on the microstructure and texture evolution on the two Mg-Li-Al based alloys, namely Mg-9 wt% Li-7 wt% Al-1 wt% Sn (LAT971) and Mg-9 wt% Li-5 wt% Al-3 wt% Sn-1 wt% Zn (LATZ9531) has been elicited. Novel Mg-Li-Al based alloys were cast (induction melting under protective atmosphere) followed by hot rolling at {approx}573 K with a cumulative reduction of five. A contrary dual phase dendritic microstructure rich in {alpha}-Mg, instead of {beta}-Li phase predicted by equilibrium phase diagram of Mg-Li binary alloy was observed. Preferential presence of Mg-Li-Sn primary precipitates (size 4-10 {mu}m) within {alpha}-Mg phase and Mg-Li-Al secondary precipitates (<3 {mu}m) interspersed in {beta}-Li indicated their degree of dissolution during hot-rolling and homogenization in the dual phase matrix. Presence of Al, Sn and Zn alloying elements in the Mg-Li based alloy has resulted an unusual dual-phase microstructure, change in the lattice parameter, and intriguing texture evolution after hot-rolling of cast LAT 971 and LATZ9531 alloy. Strong texture was absent in the as-cast samples whereas texture development after hot-rolling revealed an increased activity of the non-basal (101{sup Macron }0) slip planes. The quantification of the grain average misorientation (less than 2 Degree-Sign ) using electron backscattered diffraction confirmed the presence of strain free grains in majority of the grains (fraction >0.75) after hot-rolling of Mg

  17. CSP electricity cost evolution and grid parities based on the IEA roadmaps

    International Nuclear Information System (INIS)

    Hernández-Moro, J.; Martínez-Duart, J.M.

    2012-01-01

    The main object of this paper consists in the development of a mathematical closed-form expression for the evaluation, in the period 2010–2050, of the levelized costs of energy (LCOE) of concentrating solar power (CSP) electricity. For this purpose, the LCOE is calculated using a life-cycle cost method, based on the net present value, the discounted cash flow technique and the technology learning curve approach. By this procedure, the LCOE corresponding to CSP electricity is calculated as a function of ten independent variables. Among these parameters, special attention has been put on the evaluation of the available solar resource, the analysis of the IEA predicted values for the cumulative installed capacity, the initial (2010) cost of the system, the discount and learning rates, etc. One significant contribution of our work is that the predicted evolution of the LCOEs strongly depend, not only on the particular values of the cumulative installed capacity function in the targeted years, but mainly on the specific curved time-paths which are followed by this function. The results obtained in this work are shown both graphically and numerically. Finally, the implications that the results could have in energy planning policies and grid parity calculations are discussed. - Highlights: ► A mathematical closed expression has been developed for calculating the evolution of CSP electricity costs. ► Our technique for the prediction of CSP electricity costs and grid parities is based on IEA Roadmaps. ► The time-table (2010–2050) of cumulative installed CSP capacity is key to electricity cost predictions. ► CSP grid parities can occur within next decade for sites with proper solar resources.

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

    International Nuclear Information System (INIS)

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

    2010-01-01

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

  19. 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.

  20. Differentiating between light and deep sleep stages using an ambulatory device based on peripheral arterial tonometry

    International Nuclear Information System (INIS)

    Bresler, Ma'ayan; Sheffy, Koby; Preiszler, Meir; Herscovici, Sarah; Pillar, Giora

    2008-01-01

    The objective of this study is to develop and assess an automatic algorithm based on the peripheral arterial tone (PAT) signal to differentiate between light and deep sleep stages. The PAT signal is a measure of the pulsatile arterial volume changes at the finger tip reflecting sympathetic tone variations and is recorded by an ambulatory unattended device, the Watch-PAT100, which has been shown to be capable of detecting wake, NREM and REM sleep. An algorithm to differentiate light from deep sleep was developed using a training set of 49 patients and was validated using a separate set of 44 patients. In both patient sets, Watch-PAT100 data were recorded simultaneously with polysomnography during a full night sleep study. The algorithm is based on 14 features extracted from two time series of PAT amplitudes and inter-pulse periods (IPP). Those features were then further processed to yield a prediction function that determines the likelihood of detecting a deep sleep stage epoch during NREM sleep periods. Overall sensitivity, specificity and agreement of the automatic algorithm to identify standard 30 s epochs of light and deep sleep stages were 66%, 89%, 82% and 65%, 87%, 80% for the training and validation sets, respectively. Together with the already existing algorithms for REM and wake detection we propose a close to full stage detection method based solely on the PAT and actigraphy signals. The automatic sleep stages detection algorithm could be very useful for unattended ambulatory sleep monitoring assessing sleep stages when EEG recordings are not available