Data inversion immune to cycle-skipping using AWI

NASA Astrophysics Data System (ADS)

Guasch, L.; Warner, M.; Umpleby, A.; Yao, G.; Morgan, J. V.

2014-12-01

Over the last decade, 3D Full Waveform Inversion (FWI) has become a standard model-building tool in exploration seismology, especially in oil and gas applications -thanks to the high quality (spatial density of sources and receivers) datasets acquired by the industry. FWI provides superior quantitative images than its travel-time counterparts (travel-time based inversion methods) because it aims to match all the information in the observations instead of a severely restricted subset of them, namely picked arrivals.The downside is that the solution space explored by FWI has a high number of local minima, and since the solution is restricted to local optimization methods (due to the objective function evaluation cost), the success of the inversion is subject to starting within the basin of attraction of the global minimum.Local minima can exist for a wide variety of reasons, and it seems unlikely that a formulation of the problem that can eliminate all of them -by defining the optimization problem in a form that results in a monotonic objective function- exist. However, a significant amount of local minima are created by the definition of data misfit. In its standard formulation FWI compares observed data (field data) with predicted data (generated with a synthetic model) by subtracting one from the other, and the objective function is defined as some norm of this difference. The combination of this criteria and the fact that seismic data is oscillatory produces the well-known phenomenon of cycle-skipping, where model updates try to match nearest cycles from one dataset to the other.In order to avoid cycle-skipping we propose a different comparison between observed and predicted data, based on Wiener filters, which exploits the fact that the "identity" Wiener filter is a spike at zero lag. This gives rise to a new objective function without cycle-skipped related local minima, and therefore suppress the need of accurate starting models or low frequencies in the data. This new technique, called Adaptive Waveform Inversion (AWI) appears always superior to conventional FWI.

An annealed chaotic maximum neural network for bipartite subgraph problem.

PubMed

Wang, Jiahai; Tang, Zheng; Wang, Ronglong

2004-04-01

In this paper, based on maximum neural network, we propose a new parallel algorithm that can help the maximum neural network escape from local minima by including a transient chaotic neurodynamics for bipartite subgraph problem. The goal of the bipartite subgraph problem, which is an NP- complete problem, is to remove the minimum number of edges in a given graph such that the remaining graph is a bipartite graph. Lee et al. presented a parallel algorithm using the maximum neural model (winner-take-all neuron model) for this NP- complete problem. The maximum neural model always guarantees a valid solution and greatly reduces the search space without a burden on the parameter-tuning. However, the model has a tendency to converge to a local minimum easily because it is based on the steepest descent method. By adding a negative self-feedback to the maximum neural network, we proposed a new parallel algorithm that introduces richer and more flexible chaotic dynamics and can prevent the network from getting stuck at local minima. After the chaotic dynamics vanishes, the proposed algorithm is then fundamentally reined by the gradient descent dynamics and usually converges to a stable equilibrium point. The proposed algorithm has the advantages of both the maximum neural network and the chaotic neurodynamics. A large number of instances have been simulated to verify the proposed algorithm. The simulation results show that our algorithm finds the optimum or near-optimum solution for the bipartite subgraph problem superior to that of the best existing parallel algorithms.

A combinatorial framework to quantify peak/pit asymmetries in complex dynamics.

PubMed

Hasson, Uri; Iacovacci, Jacopo; Davis, Ben; Flanagan, Ryan; Tagliazucchi, Enzo; Laufs, Helmut; Lacasa, Lucas

2018-02-23

We explore a combinatorial framework which efficiently quantifies the asymmetries between minima and maxima in local fluctuations of time series. We first showcase its performance by applying it to a battery of synthetic cases. We find rigorous results on some canonical dynamical models (stochastic processes with and without correlations, chaotic processes) complemented by extensive numerical simulations for a range of processes which indicate that the methodology correctly distinguishes different complex dynamics and outperforms state of the art metrics in several cases. Subsequently, we apply this methodology to real-world problems emerging across several disciplines including cases in neurobiology, finance and climate science. We conclude that differences between the statistics of local maxima and local minima in time series are highly informative of the complex underlying dynamics and a graph-theoretic extraction procedure allows to use these features for statistical learning purposes.

Real-time obstacle avoidance using harmonic potential functions

NASA Technical Reports Server (NTRS)

Kim, Jin-Oh; Khosla, Pradeep K.

1992-01-01

This paper presents a new formulation of the artificial potential approach to the obstacle avoidance problem for a mobile robot or a manipulator in a known environment. Previous formulations of artificial potentials for obstacle avoidance have exhibited local minima in a cluttered environment. To build an artificial potential field, harmonic functions that completely eliminate local minima even for a cluttered environment are used. The panel method is employed to represent arbitrarily shaped obstacles and to derive the potential over the whole space. Based on this potential function, an elegant control strategy is proposed for the real-time control of a robot. The harmonic potential, the panel method, and the control strategy are tested with a bar-shaped mobile robot and a three-degree-of-freedom planar redundant manipulator.

Simulated annealing in orbital flight planning

NASA Technical Reports Server (NTRS)

Soller, Jeffrey

1990-01-01

Simulated annealing is used to solve a minimum fuel trajectory problem in the space station environment. The environment is unique because the space station will define the first true multivehicle environment in space. The optimization yields surfaces which are potentially complex, with multiple local minima. Because of the likelihood of these local minima, descent techniques are unable to offer robust solutions. Other deterministic optimization techniques were explored without success. The simulated annealing optimization is capable of identifying a minimum-fuel, two-burn trajectory subject to four constraints. Furthermore, the computational efforts involved in the optimization are such that missions could be planned on board the space station. Potential applications could include the on-site planning of rendezvous with a target craft of the emergency rescue of an astronaut. Future research will include multiwaypoint maneuvers, using a knowledge base to guide the optimization.

A strategy to find minimal energy nanocluster structures.

PubMed

Rogan, José; Varas, Alejandro; Valdivia, Juan Alejandro; Kiwi, Miguel

2013-11-05

An unbiased strategy to search for the global and local minimal energy structures of free standing nanoclusters is presented. Our objectives are twofold: to find a diverse set of low lying local minima, as well as the global minimum. To do so, we use massively the fast inertial relaxation engine algorithm as an efficient local minimizer. This procedure turns out to be quite efficient to reach the global minimum, and also most of the local minima. We test the method with the Lennard-Jones (LJ) potential, for which an abundant literature does exist, and obtain novel results, which include a new local minimum for LJ13 , 10 new local minima for LJ14 , and thousands of new local minima for 15≤N≤65. Insights on how to choose the initial configurations, analyzing the effectiveness of the method in reaching low-energy structures, including the global minimum, are developed as a function of the number of atoms of the cluster. Also, a novel characterization of the potential energy surface, analyzing properties of the local minima basins, is provided. The procedure constitutes a promising tool to generate a diverse set of cluster conformations, both two- and three-dimensional, that can be used as an input for refinement by means of ab initio methods. Copyright © 2013 Wiley Periodicals, Inc.

Exploratory Bifactor Analysis: The Schmid-Leiman Orthogonalization and Jennrich-Bentler Analytic Rotations

PubMed Central

Mansolf, Maxwell; Reise, Steven P.

2017-01-01

Analytic bifactor rotations (Jennrich & Bentler, 2011, 2012) have been recently developed and made generally available, but are not well understood. The Jennrich-Bentler analytic bifactor rotations (bi-quartimin and bi-geomin) are an alternative to, and arguably an improvement upon, the less technically sophisticated Schmid-Leiman orthogonalization (Schmid & Leiman, 1957). We review the technical details that underlie the Schmid-Leiman and Jennrich-Bentler bifactor rotations, using simulated data structures to illustrate important features and limitations. For the Schmid-Leiman, we review the problem of inaccurate parameter estimates caused by the linear dependencies, sometimes called “proportionality constraints,” that are required to expand a p correlated factors solution into a (p+1) (bi)factor space. We also review the complexities involved when the data depart from perfect cluster structure (e.g., item cross-loading on group factors). For the Jennrich-Bentler rotations, we describe problems in parameter estimation caused by departures from perfect cluster structure. In addition, we illustrate the related problems of: (a) solutions that are not invariant under different starting values (i.e., local minima problems); and, (b) group factors collapsing onto the general factor. Recommendations are made for substantive researchers including examining all local minima and applying multiple exploratory techniques in an effort to identify an accurate model. PMID:27612521

Iterative repair for scheduling and rescheduling

NASA Technical Reports Server (NTRS)

Zweben, Monte; Davis, Eugene; Deale, Michael

1991-01-01

An iterative repair search method is described called constraint based simulated annealing. Simulated annealing is a hill climbing search technique capable of escaping local minima. The utility of the constraint based framework is shown by comparing search performance with and without the constraint framework on a suite of randomly generated problems. Results are also shown of applying the technique to the NASA Space Shuttle ground processing problem. These experiments show that the search methods scales to complex, real world problems and reflects interesting anytime behavior.

Convex central configurations for the n-body problem

NASA Astrophysics Data System (ADS)

Xia, Zhihong

We give a simple proof of a classical result of MacMillan and Bartky (Trans. Amer. Math. Soc. 34 (1932) 838) which states that, for any four positive masses and any assigned order, there is a convex planar central configuration. Moreover, we show that the central configurations we find correspond to local minima of the potential function with fixed moment of inertia. This allows us to show that there are at least six local minimum central configurations for the planar four-body problem. We also show that for any assigned order of five masses, there is at least one convex spatial central configuration of local minimum type. Our method also applies to some other cases.

The Local Minima Problem in Hierarchical Classes Analysis: An Evaluation of a Simulated Annealing Algorithm and Various Multistart Procedures

ERIC Educational Resources Information Center

Ceulemans, Eva; Van Mechelen, Iven; Leenen, Iwin

2007-01-01

Hierarchical classes models are quasi-order retaining Boolean decomposition models for N-way N-mode binary data. To fit these models to data, rationally started alternating least squares (or, equivalently, alternating least absolute deviations) algorithms have been proposed. Extensive simulation studies showed that these algorithms succeed quite…

A hybrid neural learning algorithm using evolutionary learning and derivative free local search method.

PubMed

Ghosh, Ranadhir; Yearwood, John; Ghosh, Moumita; Bagirov, Adil

2006-06-01

In this paper we investigate a hybrid model based on the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. Also we discuss different variants for hybrid models using the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. The Discrete Gradient method has the advantage of being able to jump over many local minima and find very deep local minima. However, earlier research has shown that a good starting point for the discrete gradient method can improve the quality of the solution point. Evolutionary algorithms are best suited for global optimisation problems. Nevertheless they are cursed with longer training times and often unsuitable for real world application. For optimisation problems such as weight optimisation for ANNs in real world applications the dimensions are large and time complexity is critical. Hence the idea of a hybrid model can be a suitable option. In this paper we propose different fusion strategies for hybrid models combining the evolutionary strategy with the discrete gradient method to obtain an optimal solution much quicker. Three different fusion strategies are discussed: a linear hybrid model, an iterative hybrid model and a restricted local search hybrid model. Comparative results on a range of standard datasets are provided for different fusion hybrid models.

Optimizer convergence and local minima errors and their clinical importance

NASA Astrophysics Data System (ADS)

Jeraj, Robert; Wu, Chuan; Mackie, Thomas R.

2003-09-01

Two of the errors common in the inverse treatment planning optimization have been investigated. The first error is the optimizer convergence error, which appears because of non-perfect convergence to the global or local solution, usually caused by a non-zero stopping criterion. The second error is the local minima error, which occurs when the objective function is not convex and/or the feasible solution space is not convex. The magnitude of the errors, their relative importance in comparison to other errors as well as their clinical significance in terms of tumour control probability (TCP) and normal tissue complication probability (NTCP) were investigated. Two inherently different optimizers, a stochastic simulated annealing and deterministic gradient method were compared on a clinical example. It was found that for typical optimization the optimizer convergence errors are rather small, especially compared to other convergence errors, e.g., convergence errors due to inaccuracy of the current dose calculation algorithms. This indicates that stopping criteria could often be relaxed leading into optimization speed-ups. The local minima errors were also found to be relatively small and typically in the range of the dose calculation convergence errors. Even for the cases where significantly higher objective function scores were obtained the local minima errors were not significantly higher. Clinical evaluation of the optimizer convergence error showed good correlation between the convergence of the clinical TCP or NTCP measures and convergence of the physical dose distribution. On the other hand, the local minima errors resulted in significantly different TCP or NTCP values (up to a factor of 2) indicating clinical importance of the local minima produced by physical optimization.

Optimizer convergence and local minima errors and their clinical importance.

PubMed

Jeraj, Robert; Wu, Chuan; Mackie, Thomas R

2003-09-07

Two of the errors common in the inverse treatment planning optimization have been investigated. The first error is the optimizer convergence error, which appears because of non-perfect convergence to the global or local solution, usually caused by a non-zero stopping criterion. The second error is the local minima error, which occurs when the objective function is not convex and/or the feasible solution space is not convex. The magnitude of the errors, their relative importance in comparison to other errors as well as their clinical significance in terms of tumour control probability (TCP) and normal tissue complication probability (NTCP) were investigated. Two inherently different optimizers, a stochastic simulated annealing and deterministic gradient method were compared on a clinical example. It was found that for typical optimization the optimizer convergence errors are rather small, especially compared to other convergence errors, e.g., convergence errors due to inaccuracy of the current dose calculation algorithms. This indicates that stopping criteria could often be relaxed leading into optimization speed-ups. The local minima errors were also found to be relatively small and typically in the range of the dose calculation convergence errors. Even for the cases where significantly higher objective function scores were obtained the local minima errors were not significantly higher. Clinical evaluation of the optimizer convergence error showed good correlation between the convergence of the clinical TCP or NTCP measures and convergence of the physical dose distribution. On the other hand, the local minima errors resulted in significantly different TCP or NTCP values (up to a factor of 2) indicating clinical importance of the local minima produced by physical optimization.

A continuum theory of edge dislocations

NASA Astrophysics Data System (ADS)

Berdichevsky, V. L.

2017-09-01

Continuum theory of dislocation aims to describe the behavior of large ensembles of dislocations. This task is far from completion, and, most likely, does not have a "universal solution", which is applicable to any dislocation ensemble. In this regards it is important to have guiding lines set by benchmark cases, where the transition from a discrete set of dislocations to a continuum description is made rigorously. Two such cases have been considered recently: equilibrium of dislocation walls and screw dislocations in beams. In this paper one more case is studied, equilibrium of a large set of 2D edge dislocations placed randomly in a 2D bounded region. The major characteristic of interest is energy of dislocation ensemble, because it determines the structure of continuum equations. The homogenized energy functional is obtained for the periodic dislocation ensembles with a random contents of the periodic cell. Parameters of the periodic structure can change slowly on distances of order of the size of periodic cells. The energy functional is obtained by the variational-asymptotic method. Equilibrium positions are local minima of energy. It is confirmed the earlier assertion that energy density of the system is the sum of elastic energy of averaged elastic strains and microstructure energy, which is elastic energy of the neutralized dislocation system, i.e. the dislocation system placed in a constant dislocation density field making the averaged dislocation density zero. The computation of energy is reduced to solution of a variational cell problem. This problem is solved analytically. The solution is used to investigate stability of simple dislocation arrays, i.e. arrays with one dislocation in the periodic cell. The relations obtained yield two outcomes: First, there is a state parameter of the system, dislocation polarization; averaged stresses affect only dislocation polarization and cannot change other characteristics of the system. Second, the structure of dislocation phase space is strikingly simple. Dislocation phase space is split in a family of subspaces corresponding to constant values of dislocation polarizations; in each equipolarization subspace there are many local minima of energy; for zero external stresses the system is stuck in a local minimum of energy; for non-zero slowly changing external stress, dislocation polarization evolves, while the system moves over local energy minima of equipolarization subspaces. Such a simple picture of dislocation dynamics is due to the presence of two time scales, slow evolution of dislocation polarization and fast motion of the system over local minima of energy. The existence of two time scales is justified for a neutral system of edge dislocations.

Weevils versus no weevils: a comparison of Salvinia minima populations in Florida and Louisiana

USDA-ARS?s Scientific Manuscript database

Cyrtobagous salviniae Calder and Sands (Coleoptera: Curculionidae) is a successful biological control agents of aquatic weeds including common salvinia, Salvinia minima. Although S. minima has caused significant problems in Louisiana, it rarely forms persistent mats in Florida, perhaps because of t...

Maxima and Minima Without Calculus.

ERIC Educational Resources Information Center

Birnbaum, Ian

1982-01-01

Approaches to extrema that do not require calculus are presented to help free maxima/minima problems from the confines of calculus. Many students falsely suppose that these types of problems can only be dealt with through calculus, since few, if any, noncalculus examples are usually presented. (MP)

Segmentation in cohesive systems constrained by elastic environments

NASA Astrophysics Data System (ADS)

Novak, I.; Truskinovsky, L.

2017-04-01

The complexity of fracture-induced segmentation in elastically constrained cohesive (fragile) systems originates from the presence of competing interactions. The role of discreteness in such phenomena is of interest in a variety of fields, from hierarchical self-assembly to developmental morphogenesis. In this paper, we study the analytically solvable example of segmentation in a breakable mass-spring chain elastically linked to a deformable lattice structure. We explicitly construct the complete set of local minima of the energy in this prototypical problem and identify among them the states corresponding to the global energy minima. We show that, even in the continuum limit, the dependence of the segmentation topology on the stretching/pre-stress parameter in this problem takes the form of a devil's type staircase. The peculiar nature of this staircase, characterized by locking in rational microstructures, is of particular importance for biological applications, where its structure may serve as an explanation of the robustness of stress-driven segmentation. This article is part of the themed issue 'Patterning through instabilities in complex media: theory and applications.'

Fast Recall for Complex-Valued Hopfield Neural Networks with Projection Rules.

PubMed

Kobayashi, Masaki

2017-01-01

Many models of neural networks have been extended to complex-valued neural networks. A complex-valued Hopfield neural network (CHNN) is a complex-valued version of a Hopfield neural network. Complex-valued neurons can represent multistates, and CHNNs are available for the storage of multilevel data, such as gray-scale images. The CHNNs are often trapped into the local minima, and their noise tolerance is low. Lee improved the noise tolerance of the CHNNs by detecting and exiting the local minima. In the present work, we propose a new recall algorithm that eliminates the local minima. We show that our proposed recall algorithm not only accelerated the recall but also improved the noise tolerance through computer simulations.

Inherent structures of crystalline pentacene

NASA Astrophysics Data System (ADS)

Della Valle, Raffaele Guido; Venuti, Elisabetta; Brillante, Aldo; Girlando, Alberto

2003-01-01

Using a quasi-Monte Carlo scheme, we search the potential energy surface of crystalline pentacene to sample its local minima, which represent the "inherent" structures, i.e., the possible configurations of mechanical equilibrium. The system is described in terms of rigid molecules interacting through a standard atom-atom potential model. Several hundreds of distinct minima are encountered, with a surprising variety of structural arrangements. We find that deep minima are easily accessible because they exhibit a favorable energy distribution and their attraction basins tend to be wide. Thanks to these features of the potential surface, the localization the global minimum becomes entirely feasible, allowing reliable a priori predictions of the crystallographic structures. The results for pentacene are very satisfactory. In fact, the two deepest minima correspond to the structures of the two known experimental polymorphs, which are described correctly. Further polymorphs are also likely to exist.

A frozen Gaussian approximation-based multi-level particle swarm optimization for seismic inversion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Jinglai, E-mail: jinglaili@sjtu.edu.cn; Lin, Guang, E-mail: lin491@purdue.edu; Computational Sciences and Mathematics Division, Pacific Northwest National Laboratory, Richland, WA 99352

2015-09-01

In this paper, we propose a frozen Gaussian approximation (FGA)-based multi-level particle swarm optimization (MLPSO) method for seismic inversion of high-frequency wave data. The method addresses two challenges in it: First, the optimization problem is highly non-convex, which makes hard for gradient-based methods to reach global minima. This is tackled by MLPSO which can escape from undesired local minima. Second, the character of high-frequency of seismic waves requires a large number of grid points in direct computational methods, and thus renders an extremely high computational demand on the simulation of each sample in MLPSO. We overcome this difficulty by threemore » steps: First, we use FGA to compute high-frequency wave propagation based on asymptotic analysis on phase plane; Then we design a constrained full waveform inversion problem to prevent the optimization search getting into regions of velocity where FGA is not accurate; Last, we solve the constrained optimization problem by MLPSO that employs FGA solvers with different fidelity. The performance of the proposed method is demonstrated by a two-dimensional full-waveform inversion example of the smoothed Marmousi model.« less

Piecewise convexity of artificial neural networks.

PubMed

Rister, Blaine; Rubin, Daniel L

2017-10-01

Although artificial neural networks have shown great promise in applications including computer vision and speech recognition, there remains considerable practical and theoretical difficulty in optimizing their parameters. The seemingly unreasonable success of gradient descent methods in minimizing these non-convex functions remains poorly understood. In this work we offer some theoretical guarantees for networks with piecewise affine activation functions, which have in recent years become the norm. We prove three main results. First, that the network is piecewise convex as a function of the input data. Second, that the network, considered as a function of the parameters in a single layer, all others held constant, is again piecewise convex. Third, that the network as a function of all its parameters is piecewise multi-convex, a generalization of biconvexity. From here we characterize the local minima and stationary points of the training objective, showing that they minimize the objective on certain subsets of the parameter space. We then analyze the performance of two optimization algorithms on multi-convex problems: gradient descent, and a method which repeatedly solves a number of convex sub-problems. We prove necessary convergence conditions for the first algorithm and both necessary and sufficient conditions for the second, after introducing regularization to the objective. Finally, we remark on the remaining difficulty of the global optimization problem. Under the squared error objective, we show that by varying the training data, a single rectifier neuron admits local minima arbitrarily far apart, both in objective value and parameter space. Copyright © 2017 Elsevier Ltd. All rights reserved.

Energy landscapes and properties of biomolecules.

PubMed

Wales, David J

2005-11-09

Thermodynamic and dynamic properties of biomolecules can be calculated using a coarse-grained approach based upon sampling stationary points of the underlying potential energy surface. The superposition approximation provides an overall partition function as a sum of contributions from the local minima, and hence functions such as internal energy, entropy, free energy and the heat capacity. To obtain rates we must also sample transition states that link the local minima, and the discrete path sampling method provides a systematic means to achieve this goal. A coarse-grained picture is also helpful in locating the global minimum using the basin-hopping approach. Here we can exploit a fictitious dynamics between the basins of attraction of local minima, since the objective is to find the lowest minimum, rather than to reproduce the thermodynamics or dynamics.

A Possible Physiological Basis for the Discontinuity of Consciousness

PubMed Central

Pockett, Susan; Brennan, Barry J.; Bold, Gary E. J.; Holmes, Mark D.

2011-01-01

A comparison is made between the frequency of local minima in the analytic power (AP) of intracranial EEG (ECoG) from waking and unconscious human subjects and the frequency of putative frames of consciousness reported in earlier psychological literature. In ECoG from unconscious subjects, the frequency of deep minima in AP is found to be a linear function of bandwidth. In contrast, in ECoG from conscious subjects, the bandwidth/minima-frequency curve saturates or plateaus at minima frequencies similar to the frequencies of previously reported frames of consciousness. This result is consistent with the hypothesis that local minima in AP may act as the shutter in a cinematographic model of consciousness. The fact that artificially generated samples of black noise with power spectra similar to ECoG data give similar results in the analyses above suggests that the discontinuous nature of consciousness is not due to some specifically biological factor, but is simply a consequence of the physical properties of the 1/f (aka power law) oscillations that are widely found in nature. PMID:22203811

[Cognitive advantages of the third age: a neural network model of brain aging].

PubMed

Karpenko, M P; Kachalova, L M; Budilova, E V; Terekhin, A T

2009-01-01

We consider a neural network model of age-related cognitive changes in aging brain based on Hopfield network with a sigmoid function of neuron activation. Age is included in the activation function as a parameter in the form of exponential rate denominator, which makes it possible to take into account the weakening of interneuronal links really observed in the aging brain. Analysis of properties of the Lyapunov function associated with the network shows that, with increasing parameter of age, its relief becomes smoother and the number of local minima (network attractors) decreases. As a result, the network gets less frequently stuck in the nearest local minima of the Lyapunov function and reaches a global minimum corresponding to the most effective solution of the cognitive task. It is reasonable to assume that similar changes really occur in the aging brain. Phenomenologically, these changes can be manifested as emergence in aged people of a cognitive quality such as wisdom i.e. ability to find optimal decisions in difficult controversial situations, to distract from secondary aspects and to see the problem as a whole.

Segmentation in cohesive systems constrained by elastic environments

PubMed Central

Novak, I.

2017-01-01

The complexity of fracture-induced segmentation in elastically constrained cohesive (fragile) systems originates from the presence of competing interactions. The role of discreteness in such phenomena is of interest in a variety of fields, from hierarchical self-assembly to developmental morphogenesis. In this paper, we study the analytically solvable example of segmentation in a breakable mass–spring chain elastically linked to a deformable lattice structure. We explicitly construct the complete set of local minima of the energy in this prototypical problem and identify among them the states corresponding to the global energy minima. We show that, even in the continuum limit, the dependence of the segmentation topology on the stretching/pre-stress parameter in this problem takes the form of a devil's type staircase. The peculiar nature of this staircase, characterized by locking in rational microstructures, is of particular importance for biological applications, where its structure may serve as an explanation of the robustness of stress-driven segmentation. This article is part of the themed issue ‘Patterning through instabilities in complex media: theory and applications.’ PMID:28373383

Restricted random search method based on taboo search in the multiple minima problem

NASA Astrophysics Data System (ADS)

Hong, Seung Do; Jhon, Mu Shik

1997-03-01

The restricted random search method is proposed as a simple Monte Carlo sampling method to search minima fast in the multiple minima problem. This method is based on taboo search applied recently to continuous test functions. The concept of the taboo region instead of the taboo list is used and therefore the sampling of a region near an old configuration is restricted in this method. This method is applied to 2-dimensional test functions and the argon clusters. This method is found to be a practical and efficient method to search near-global configurations of test functions and the argon clusters.

Virtual local target method for avoiding local minimum in potential field based robot navigation.

PubMed

Zou, Xi-Yong; Zhu, Jing

2003-01-01

A novel robot navigation algorithm with global path generation capability is presented. Local minimum is a most intractable but is an encountered frequently problem in potential field based robot navigation. Through appointing appropriately some virtual local targets on the journey, it can be solved effectively. The key concept employed in this algorithm are the rules that govern when and how to appoint these virtual local targets. When the robot finds itself in danger of local minimum, a virtual local target is appointed to replace the global goal temporarily according to the rules. After the virtual target is reached, the robot continues on its journey by heading towards the global goal. The algorithm prevents the robot from running into local minima anymore. Simulation results showed that it is very effective in complex obstacle environments.

Speed and convergence properties of gradient algorithms for optimization of IMRT.

PubMed

Zhang, Xiaodong; Liu, Helen; Wang, Xiaochun; Dong, Lei; Wu, Qiuwen; Mohan, Radhe

2004-05-01

Gradient algorithms are the most commonly employed search methods in the routine optimization of IMRT plans. It is well known that local minima can exist for dose-volume-based and biology-based objective functions. The purpose of this paper is to compare the relative speed of different gradient algorithms, to investigate the strategies for accelerating the optimization process, to assess the validity of these strategies, and to study the convergence properties of these algorithms for dose-volume and biological objective functions. With these aims in mind, we implemented Newton's, conjugate gradient (CG), and the steepest decent (SD) algorithms for dose-volume- and EUD-based objective functions. Our implementation of Newton's algorithm approximates the second derivative matrix (Hessian) by its diagonal. The standard SD algorithm and the CG algorithm with "line minimization" were also implemented. In addition, we investigated the use of a variation of the CG algorithm, called the "scaled conjugate gradient" (SCG) algorithm. To accelerate the optimization process, we investigated the validity of the use of a "hybrid optimization" strategy, in which approximations to calculated dose distributions are used during most of the iterations. Published studies have indicated that getting trapped in local minima is not a significant problem. To investigate this issue further, we first obtained, by trial and error, and starting with uniform intensity distributions, the parameters of the dose-volume- or EUD-based objective functions which produced IMRT plans that satisfied the clinical requirements. Using the resulting optimized intensity distributions as the initial guess, we investigated the possibility of getting trapped in a local minimum. For most of the results presented, we used a lung cancer case. To illustrate the generality of our methods, the results for a prostate case are also presented. For both dose-volume and EUD based objective functions, Newton's method far outperforms other algorithms in terms of speed. The SCG algorithm, which avoids expensive "line minimization," can speed up the standard CG algorithm by at least a factor of 2. For the same initial conditions, all algorithms converge essentially to the same plan. However, we demonstrate that for any of the algorithms studied, starting with previously optimized intensity distributions as the initial guess but for different objective function parameters, the solution frequently gets trapped in local minima. We found that the initial intensity distribution obtained from IMRT optimization utilizing objective function parameters, which favor a specific anatomic structure, would lead to a local minimum corresponding to that structure. Our results indicate that from among the gradient algorithms tested, Newton's method appears to be the fastest by far. Different gradient algorithms have the same convergence properties for dose-volume- and EUD-based objective functions. The hybrid dose calculation strategy is valid and can significantly accelerate the optimization process. The degree of acceleration achieved depends on the type of optimization problem being addressed (e.g., IMRT optimization, intensity modulated beam configuration optimization, or objective function parameter optimization). Under special conditions, gradient algorithms will get trapped in local minima, and reoptimization, starting with the results of previous optimization, will lead to solutions that are generally not significantly different from the local minimum.

Alien Genetic Algorithm for Exploration of Search Space

NASA Astrophysics Data System (ADS)

Patel, Narendra; Padhiyar, Nitin

2010-10-01

Genetic Algorithm (GA) is a widely accepted population based stochastic optimization technique used for single and multi objective optimization problems. Various versions of modifications in GA have been proposed in last three decades mainly addressing two issues, namely increasing convergence rate and increasing probability of global minima. While both these. While addressing the first issue, GA tends to converge to a local optima and addressing the second issue corresponds the large computational efforts. Thus, to reduce the contradictory effects of these two aspects, we propose a modification in GA by adding an alien member in the population at every generation. Addition of an Alien member in the current population at every generation increases the probability of obtaining global minima at the same time maintaining higher convergence rate. With two test cases, we have demonstrated the efficacy of the proposed GA by comparing with the conventional GA.

Distributed least-squares estimation of a remote chemical source via convex combination in wireless sensor networks.

PubMed

Cao, Meng-Li; Meng, Qing-Hao; Zeng, Ming; Sun, Biao; Li, Wei; Ding, Cheng-Jun

2014-06-27

This paper investigates the problem of locating a continuous chemical source using the concentration measurements provided by a wireless sensor network (WSN). Such a problem exists in various applications: eliminating explosives or drugs, detecting the leakage of noxious chemicals, etc. The limited power and bandwidth of WSNs have motivated collaborative in-network processing which is the focus of this paper. We propose a novel distributed least-squares estimation (DLSE) method to solve the chemical source localization (CSL) problem using a WSN. The DLSE method is realized by iteratively conducting convex combination of the locally estimated chemical source locations in a distributed manner. Performance assessments of our method are conducted using both simulations and real experiments. In the experiments, we propose a fitting method to identify both the release rate and the eddy diffusivity. The results show that the proposed DLSE method can overcome the negative interference of local minima and saddle points of the objective function, which would hinder the convergence of local search methods, especially in the case of locating a remote chemical source.

Path planning for robotic truss assembly

NASA Technical Reports Server (NTRS)

Sanderson, Arthur C.

1993-01-01

A new Potential Fields approach to the robotic path planning problem is proposed and implemented. Our approach, which is based on one originally proposed by Munger, computes an incremental joint vector based upon attraction to a goal and repulsion from obstacles. By repetitively adding and computing these 'steps', it is hoped (but not guaranteed) that the robot will reach its goal. An attractive force exerted by the goal is found by solving for the the minimum norm solution to the linear Jacobian equation. A repulsive force between obstacles and the robot's links is used to avoid collisions. Its magnitude is inversely proportional to the distance. Together, these forces make the goal the global minimum potential point, but local minima can stop the robot from ever reaching that point. Our approach improves on a basic, potential field paradigm developed by Munger by using an active, adaptive field - what we will call a 'flexible' potential field. Active fields are stronger when objects move towards one another and weaker when they move apart. An adaptive field's strength is individually tailored to be just strong enough to avoid any collision. In addition to the local planner, a global planning algorithm helps the planner to avoid local field minima by providing subgoals. These subgoals are based on the obstacles which caused the local planner to fail. A best-first search algorithm A* is used for graph search.

Nonlinear optimization simplified by hypersurface deformation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stillinger, F.H.; Weber, T.A.

1988-09-01

A general strategy is advanced for simplifying nonlinear optimization problems, the ant-lion method. This approach exploits shape modifications of the cost-function hypersurface which distend basins surrounding low-lying minima (including global minima). By intertwining hypersurface deformations with steepest-descent displacements, the search is concentrated on a small relevant subset of all minima. Specific calculations demonstrating the value of this method are reported for the partitioning of two classes of irregular but nonrandom graphs, the prime-factor graphs and the pi graphs. We also indicate how this approach can be applied to the traveling salesman problem and to design layout optimization, and that itmore » may be useful in combination with simulated annealing strategies.« less

Visualizing and improving the robustness of phase retrieval algorithms

DOE PAGES

Tripathi, Ashish; Leyffer, Sven; Munson, Todd; ...

2015-06-01

Coherent x-ray diffractive imaging is a novel imaging technique that utilizes phase retrieval and nonlinear optimization methods to image matter at nanometer scales. We explore how the convergence properties of a popular phase retrieval algorithm, Fienup's HIO, behave by introducing a reduced dimensionality problem allowing us to visualize and quantify convergence to local minima and the globally optimal solution. We then introduce generalizations of HIO that improve upon the original algorithm's ability to converge to the globally optimal solution.

Visualizing and improving the robustness of phase retrieval algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tripathi, Ashish; Leyffer, Sven; Munson, Todd

Coherent x-ray diffractive imaging is a novel imaging technique that utilizes phase retrieval and nonlinear optimization methods to image matter at nanometer scales. We explore how the convergence properties of a popular phase retrieval algorithm, Fienup's HIO, behave by introducing a reduced dimensionality problem allowing us to visualize and quantify convergence to local minima and the globally optimal solution. We then introduce generalizations of HIO that improve upon the original algorithm's ability to converge to the globally optimal solution.

Applications of hybrid genetic algorithms in seismic tomography

NASA Astrophysics Data System (ADS)

Soupios, Pantelis; Akca, Irfan; Mpogiatzis, Petros; Basokur, Ahmet T.; Papazachos, Constantinos

2011-11-01

Almost all earth sciences inverse problems are nonlinear and involve a large number of unknown parameters, making the application of analytical inversion methods quite restrictive. In practice, most analytical methods are local in nature and rely on a linearized form of the problem equations, adopting an iterative procedure which typically employs partial derivatives in order to optimize the starting (initial) model by minimizing a misfit (penalty) function. Unfortunately, especially for highly non-linear cases, the final model strongly depends on the initial model, hence it is prone to solution-entrapment in local minima of the misfit function, while the derivative calculation is often computationally inefficient and creates instabilities when numerical approximations are used. An alternative is to employ global techniques which do not rely on partial derivatives, are independent of the misfit form and are computationally robust. Such methods employ pseudo-randomly generated models (sampling an appropriately selected section of the model space) which are assessed in terms of their data-fit. A typical example is the class of methods known as genetic algorithms (GA), which achieves the aforementioned approximation through model representation and manipulations, and has attracted the attention of the earth sciences community during the last decade, with several applications already presented for several geophysical problems. In this paper, we examine the efficiency of the combination of the typical regularized least-squares and genetic methods for a typical seismic tomography problem. The proposed approach combines a local (LOM) and a global (GOM) optimization method, in an attempt to overcome the limitations of each individual approach, such as local minima and slow convergence, respectively. The potential of both optimization methods is tested and compared, both independently and jointly, using the several test models and synthetic refraction travel-time date sets that employ the same experimental geometry, wavelength and geometrical characteristics of the model anomalies. Moreover, real data from a crosswell tomographic project for the subsurface mapping of an ancient wall foundation are used for testing the efficiency of the proposed algorithm. The results show that the combined use of both methods can exploit the benefits of each approach, leading to improved final models and producing realistic velocity models, without significantly increasing the required computation time.

Efficient Compressed Sensing Based MRI Reconstruction using Nonconvex Total Variation Penalties

NASA Astrophysics Data System (ADS)

Lazzaro, D.; Loli Piccolomini, E.; Zama, F.

2016-10-01

This work addresses the problem of Magnetic Resonance Image Reconstruction from highly sub-sampled measurements in the Fourier domain. It is modeled as a constrained minimization problem, where the objective function is a non-convex function of the gradient of the unknown image and the constraints are given by the data fidelity term. We propose an algorithm, Fast Non Convex Reweighted (FNCR), where the constrained problem is solved by a reweighting scheme, as a strategy to overcome the non-convexity of the objective function, with an adaptive adjustment of the penalization parameter. We propose a fast iterative algorithm and we can prove that it converges to a local minimum because the constrained problem satisfies the Kurdyka-Lojasiewicz property. Moreover the adaptation of non convex l0 approximation and penalization parameters, by means of a continuation technique, allows us to obtain good quality solutions, avoiding to get stuck in unwanted local minima. Some numerical experiments performed on MRI sub-sampled data show the efficiency of the algorithm and the accuracy of the solution.

Localization from near-source quasi-static electromagnetic fields

NASA Astrophysics Data System (ADS)

Mosher, J. C.

1993-09-01

A wide range of research has been published on the problem of estimating the parameters of electromagnetic and acoustical sources from measurements of signals measured at an array of sensors. In the quasi-static electromagnetic cases examined here, the signal variation from a point source is relatively slow with respect to the signal propagation and the spacing of the array of sensors. As such, the location of the point sources can only be determined from the spatial diversity of the received signal across the array. The inverse source localization problem is complicated by unknown model order and strong local minima. The nonlinear optimization problem is posed for solving for the parameters of the quasi-static source model. The transient nature of the sources can be exploited to allow subspace approaches to separate out the signal portion of the spatial correlation matrix. Decomposition techniques are examined for improved processing, and an adaptation of MUltiple SIgnal Characterization (MUSIC) is presented for solving the source localization problem. Recent results on calculating the Cramer-Rao error lower bounds are extended to the multidimensional problem here. This thesis focuses on the problem of source localization in magnetoencephalography (MEG), with a secondary application to thunderstorm source localization. Comparisons are also made between MEG and its electrical equivalent, electroencephalography (EEG). The error lower bounds are examined in detail for several MEG and EEG configurations, as well as localizing thunderstorm cells over Cape Canaveral and Kennedy Space Center. Time-eigenspectrum is introduced as a parsing technique for improving the performance of the optimization problem.

Localization from near-source quasi-static electromagnetic fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mosher, John Compton

1993-09-01

A wide range of research has been published on the problem of estimating the parameters of electromagnetic and acoustical sources from measurements of signals measured at an array of sensors. In the quasi-static electromagnetic cases examined here, the signal variation from a point source is relatively slow with respect to the signal propagation and the spacing of the array of sensors. As such, the location of the point sources can only be determined from the spatial diversity of the received signal across the array. The inverse source localization problem is complicated by unknown model order and strong local minima. Themore » nonlinear optimization problem is posed for solving for the parameters of the quasi-static source model. The transient nature of the sources can be exploited to allow subspace approaches to separate out the signal portion of the spatial correlation matrix. Decomposition techniques are examined for improved processing, and an adaptation of MUtiple SIgnal Characterization (MUSIC) is presented for solving the source localization problem. Recent results on calculating the Cramer-Rao error lower bounds are extended to the multidimensional problem here. This thesis focuses on the problem of source localization in magnetoencephalography (MEG), with a secondary application to thunderstorm source localization. Comparisons are also made between MEG and its electrical equivalent, electroencephalography (EEG). The error lower bounds are examined in detail for several MEG and EEG configurations, as well as localizing thunderstorm cells over Cape Canaveral and Kennedy Space Center. Time-eigenspectrum is introduced as a parsing technique for improving the performance of the optimization problem.« less

Acoustic Impedance Inversion of Seismic Data Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Eladj, Said; Djarfour, Noureddine; Ferahtia, Djalal; Ouadfeul, Sid-Ali

2013-04-01

The inversion of seismic data can be used to constrain estimates of the Earth's acoustic impedance structure. This kind of problem is usually known to be non-linear, high-dimensional, with a complex search space which may be riddled with many local minima, and results in irregular objective functions. We investigate here the performance and the application of a genetic algorithm, in the inversion of seismic data. The proposed algorithm has the advantage of being easily implemented without getting stuck in local minima. The effects of population size, Elitism strategy, uniform cross-over and lower mutation are examined. The optimum solution parameters and performance were decided as a function of the testing error convergence with respect to the generation number. To calculate the fitness function, we used L2 norm of the sample-to-sample difference between the reference and the inverted trace. The cross-over probability is of 0.9-0.95 and mutation has been tested at 0.01 probability. The application of such a genetic algorithm to synthetic data shows that the inverted acoustic impedance section was efficient. Keywords: Seismic, Inversion, acoustic impedance, genetic algorithm, fitness functions, cross-over, mutation.

Dynamic Inertia Weight Binary Bat Algorithm with Neighborhood Search

PubMed Central

2017-01-01

Binary bat algorithm (BBA) is a binary version of the bat algorithm (BA). It has been proven that BBA is competitive compared to other binary heuristic algorithms. Since the update processes of velocity in the algorithm are consistent with BA, in some cases, this algorithm also faces the premature convergence problem. This paper proposes an improved binary bat algorithm (IBBA) to solve this problem. To evaluate the performance of IBBA, standard benchmark functions and zero-one knapsack problems have been employed. The numeric results obtained by benchmark functions experiment prove that the proposed approach greatly outperforms the original BBA and binary particle swarm optimization (BPSO). Compared with several other heuristic algorithms on zero-one knapsack problems, it also verifies that the proposed algorithm is more able to avoid local minima. PMID:28634487

Dynamic Inertia Weight Binary Bat Algorithm with Neighborhood Search.

PubMed

Huang, Xingwang; Zeng, Xuewen; Han, Rui

2017-01-01

Binary bat algorithm (BBA) is a binary version of the bat algorithm (BA). It has been proven that BBA is competitive compared to other binary heuristic algorithms. Since the update processes of velocity in the algorithm are consistent with BA, in some cases, this algorithm also faces the premature convergence problem. This paper proposes an improved binary bat algorithm (IBBA) to solve this problem. To evaluate the performance of IBBA, standard benchmark functions and zero-one knapsack problems have been employed. The numeric results obtained by benchmark functions experiment prove that the proposed approach greatly outperforms the original BBA and binary particle swarm optimization (BPSO). Compared with several other heuristic algorithms on zero-one knapsack problems, it also verifies that the proposed algorithm is more able to avoid local minima.

Screw dislocation-induced growth spirals as emissive exciton localization centers in Al-rich AlGaN/AlN quantum wells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Funato, Mitsuru, E-mail: funato@kuee.kyoto-u.ac.jp; Banal, Ryan G.; Kawakami, Yoichi

2015-11-15

Screw dislocations in Al-rich AlGaN/AlN quantum wells cause growth spirals with an enhanced Ga incorporation, which create potential minima. Although screw dislocations and their surrounding potential minima suggest non-radiative recombination processes within growth spirals, in reality, screw dislocations are not major non-radiative sinks for carriers. Consequently, carriers localized within growth spirals recombine radiatively without being captured by non-radiative recombination centers, resulting in intense emissions from growth spirals.

Dual stage potential field method for robotic path planning

NASA Astrophysics Data System (ADS)

Singh, Pradyumna Kumar; Parida, Pramod Kumar

2018-04-01

Path planning for autonomous mobile robots are the root for all autonomous mobile systems. Various methods are used for optimization of path to be followed by the autonomous mobile robots. Artificial potential field based path planning method is one of the most used methods for the researchers. Various algorithms have been proposed using the potential field approach. But in most of the common problems are encounters while heading towards the goal or target. i.e. local minima problem, zero potential regions problem, complex shaped obstacles problem, target near obstacle problem. In this paper we provide a new algorithm in which two types of potential functions are used one after another. The former one is to use to get the probable points and later one for getting the optimum path. In this algorithm we consider only the static obstacle and goal.

Seeking Global Minima

NASA Astrophysics Data System (ADS)

Tajuddin, Wan Ahmad

1994-02-01

Ease in finding the configuration at the global energy minimum in a symmetric neural network is important for combinatorial optimization problems. We carry out a comprehensive survey of available strategies for seeking global minima by comparing their performances in the binary representation problem. We recall our previous comparison of steepest descent with analog dynamics, genetic hill-climbing, simulated diffusion, simulated annealing, threshold accepting and simulated tunneling. To this, we add comparisons to other strategies including taboo search and one with field-ordered updating.

Superpixel-based graph cuts for accurate stereo matching

NASA Astrophysics Data System (ADS)

Feng, Liting; Qin, Kaihuai

2017-06-01

Estimating the surface normal vector and disparity of a pixel simultaneously, also known as three-dimensional label method, has been widely used in recent continuous stereo matching problem to achieve sub-pixel accuracy. However, due to the infinite label space, it’s extremely hard to assign each pixel an appropriate label. In this paper, we present an accurate and efficient algorithm, integrating patchmatch with graph cuts, to approach this critical computational problem. Besides, to get robust and precise matching cost, we use a convolutional neural network to learn a similarity measure on small image patches. Compared with other MRF related methods, our method has several advantages: its sub-modular property ensures a sub-problem optimality which is easy to perform in parallel; graph cuts can simultaneously update multiple pixels, avoiding local minima caused by sequential optimizers like belief propagation; it uses segmentation results for better local expansion move; local propagation and randomization can easily generate the initial solution without using external methods. Middlebury experiments show that our method can get higher accuracy than other MRF-based algorithms.

Energy landscapes for a machine learning application to series data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ballard, Andrew J.; Stevenson, Jacob D.; Das, Ritankar

2016-03-28

Methods developed to explore and characterise potential energy landscapes are applied to the corresponding landscapes obtained from optimisation of a cost function in machine learning. We consider neural network predictions for the outcome of local geometry optimisation in a triatomic cluster, where four distinct local minima exist. The accuracy of the predictions is compared for fits using data from single and multiple points in the series of atomic configurations resulting from local geometry optimisation and for alternative neural networks. The machine learning solution landscapes are visualised using disconnectivity graphs, and signatures in the effective heat capacity are analysed in termsmore » of distributions of local minima and their properties.« less

Tight-binding approach to overdamped Brownian motion on a bichromatic periodic potential.

PubMed

Nguyen, P T T; Challis, K J; Jack, M W

2016-02-01

We present a theoretical treatment of overdamped Brownian motion on a time-independent bichromatic periodic potential with spatially fast- and slow-changing components. In our approach, we generalize the Wannier basis commonly used in the analysis of periodic systems to define a basis of S states that are localized at local minima of the potential. We demonstrate that the S states are orthonormal and complete on the length scale of the periodicity of the fast-changing potential, and we use the S-state basis to transform the continuous Smoluchowski equation for the system to a discrete master equation describing hopping between local minima. We identify the parameter regime where the master equation description is valid and show that the interwell hopping rates are well approximated by Kramers' escape rate in the limit of deep potential minima. Finally, we use the master equation to explore the system dynamics and determine the drift and diffusion for the system.

A hybrid Q-learning sine-cosine-based strategy for addressing the combinatorial test suite minimization problem

PubMed Central

Zamli, Kamal Z.; Din, Fakhrud; Bures, Miroslav

2018-01-01

The sine-cosine algorithm (SCA) is a new population-based meta-heuristic algorithm. In addition to exploiting sine and cosine functions to perform local and global searches (hence the name sine-cosine), the SCA introduces several random and adaptive parameters to facilitate the search process. Although it shows promising results, the search process of the SCA is vulnerable to local minima/maxima due to the adoption of a fixed switch probability and the bounded magnitude of the sine and cosine functions (from -1 to 1). In this paper, we propose a new hybrid Q-learning sine-cosine- based strategy, called the Q-learning sine-cosine algorithm (QLSCA). Within the QLSCA, we eliminate the switching probability. Instead, we rely on the Q-learning algorithm (based on the penalty and reward mechanism) to dynamically identify the best operation during runtime. Additionally, we integrate two new operations (Lévy flight motion and crossover) into the QLSCA to facilitate jumping out of local minima/maxima and enhance the solution diversity. To assess its performance, we adopt the QLSCA for the combinatorial test suite minimization problem. Experimental results reveal that the QLSCA is statistically superior with regard to test suite size reduction compared to recent state-of-the-art strategies, including the original SCA, the particle swarm test generator (PSTG), adaptive particle swarm optimization (APSO) and the cuckoo search strategy (CS) at the 95% confidence level. However, concerning the comparison with discrete particle swarm optimization (DPSO), there is no significant difference in performance at the 95% confidence level. On a positive note, the QLSCA statistically outperforms the DPSO in certain configurations at the 90% confidence level. PMID:29771918

A hybrid Q-learning sine-cosine-based strategy for addressing the combinatorial test suite minimization problem.

PubMed

Zamli, Kamal Z; Din, Fakhrud; Ahmed, Bestoun S; Bures, Miroslav

2018-01-01

The sine-cosine algorithm (SCA) is a new population-based meta-heuristic algorithm. In addition to exploiting sine and cosine functions to perform local and global searches (hence the name sine-cosine), the SCA introduces several random and adaptive parameters to facilitate the search process. Although it shows promising results, the search process of the SCA is vulnerable to local minima/maxima due to the adoption of a fixed switch probability and the bounded magnitude of the sine and cosine functions (from -1 to 1). In this paper, we propose a new hybrid Q-learning sine-cosine- based strategy, called the Q-learning sine-cosine algorithm (QLSCA). Within the QLSCA, we eliminate the switching probability. Instead, we rely on the Q-learning algorithm (based on the penalty and reward mechanism) to dynamically identify the best operation during runtime. Additionally, we integrate two new operations (Lévy flight motion and crossover) into the QLSCA to facilitate jumping out of local minima/maxima and enhance the solution diversity. To assess its performance, we adopt the QLSCA for the combinatorial test suite minimization problem. Experimental results reveal that the QLSCA is statistically superior with regard to test suite size reduction compared to recent state-of-the-art strategies, including the original SCA, the particle swarm test generator (PSTG), adaptive particle swarm optimization (APSO) and the cuckoo search strategy (CS) at the 95% confidence level. However, concerning the comparison with discrete particle swarm optimization (DPSO), there is no significant difference in performance at the 95% confidence level. On a positive note, the QLSCA statistically outperforms the DPSO in certain configurations at the 90% confidence level.

A global approach to kinematic path planning to robots with holonomic and nonholonomic constraints

NASA Technical Reports Server (NTRS)

Divelbiss, Adam; Seereeram, Sanjeev; Wen, John T.

1993-01-01

Robots in applications may be subject to holonomic or nonholonomic constraints. Examples of holonomic constraints include a manipulator constrained through the contact with the environment, e.g., inserting a part, turning a crank, etc., and multiple manipulators constrained through a common payload. Examples of nonholonomic constraints include no-slip constraints on mobile robot wheels, local normal rotation constraints for soft finger and rolling contacts in grasping, and conservation of angular momentum of in-orbit space robots. The above examples all involve equality constraints; in applications, there are usually additional inequality constraints such as robot joint limits, self collision and environment collision avoidance constraints, steering angle constraints in mobile robots, etc. The problem of finding a kinematically feasible path that satisfies a given set of holonomic and nonholonomic constraints, of both equality and inequality types is addressed. The path planning problem is first posed as a finite time nonlinear control problem. This problem is subsequently transformed to a static root finding problem in an augmented space which can then be iteratively solved. The algorithm has shown promising results in planning feasible paths for redundant arms satisfying Cartesian path following and goal endpoint specifications, and mobile vehicles with multiple trailers. In contrast to local approaches, this algorithm is less prone to problems such as singularities and local minima.

Sampling the energy landscape of Pt13 with metadynamics

NASA Astrophysics Data System (ADS)

Pavan, Luca; Di Paola, Cono; Baletto, Francesca

2013-02-01

The potential energy surface of a metallic nanoparticle formed by 13 atoms of platinum is efficiently explored using metadynamics in combination with empirical potential molecular dynamics. The scenario obtained is wider and more complex of what was previously reported: more than thirty independent energy basins are found, corresponding to different local minima of Pt. It is demonstrated that in almost all the cases these motifs are local minima even at ab-initio level, hence proving the effectiveness of the method to sample the energy landscape. A classification of the minima in structural families is proposed, and a discussion regarding the shape and the connections between energy basins is reported. ISSPIC 16 - 16th International Symposium on Small Particles and Inorganic Clusters, edited by Kristiaan Temst, Margriet J. Van Bael, Ewald Janssens, H.-G. Boyen and Françoise Remacle.

A Telescopic Binary Learning Machine for Training Neural Networks.

PubMed

Brunato, Mauro; Battiti, Roberto

2017-03-01

This paper proposes a new algorithm based on multiscale stochastic local search with binary representation for training neural networks [binary learning machine (BLM)]. We study the effects of neighborhood evaluation strategies, the effect of the number of bits per weight and that of the maximum weight range used for mapping binary strings to real values. Following this preliminary investigation, we propose a telescopic multiscale version of local search, where the number of bits is increased in an adaptive manner, leading to a faster search and to local minima of better quality. An analysis related to adapting the number of bits in a dynamic way is presented. The control on the number of bits, which happens in a natural manner in the proposed method, is effective to increase the generalization performance. The learning dynamics are discussed and validated on a highly nonlinear artificial problem and on real-world tasks in many application domains; BLM is finally applied to a problem requiring either feedforward or recurrent architectures for feedback control.

The effect of tidal forces on the minimum energy configurations of the full three-body problem

NASA Astrophysics Data System (ADS)

Levine, Edward

We investigate the evolution of minimum energy configurations for the Full Three Body Problem (3BP). A stable ternary asteroid system will gradually become unstable due to the Yarkovsky-O'Keefe-Radzievskii-Paddack (YORP) effect and an unpredictable trajectory will ensue. Through the interaction of tidal torques, energy in the system will dissipate in the form of heat until a stable minimum energy configuration is reached. We present a simulation that describes the dynamical evolution of three bodies under the mutual effects of gravity and tidal torques. Simulations show that bodies do not get stuck in local minima and transition to the predicted minimum energy configuration.

A Change in the Solar He II EUV Global Network Structure as an Indicator of the Geo-Effectiveness of Solar Minima

NASA Technical Reports Server (NTRS)

Didkovsky, L.; Gurman, J. B.

2013-01-01

Solar activity during 2007 - 2009 was very low, causing anomalously low thermospheric density. A comparison of solar extreme ultraviolet (EUV) irradiance in the He II spectral band (26 to 34 nm) from the Solar Extreme ultraviolet Monitor (SEM), one of instruments on the Charge Element and Isotope Analysis System (CELIAS) on board the Solar and Heliospheric Observatory (SOHO) for the two latest solar minima showed a decrease of the absolute irradiance of about 15 +/- 6 % during the solar minimum between Cycles 23 and 24 compared with the Cycle 22/23 minimum when a yearly running-mean filter was used. We found that some local, shorter-term minima including those with the same absolute EUV flux in the SEM spectral band show a higher concentration of spatial power in the global network structure from the 30.4 nm SOHO/Extreme ultraviolet Imaging Telescope (EIT) images for the local minimum of 1996 compared with the minima of 2008 - 2011.We interpret this higher concentration of spatial power in the transition region's global network structure as a larger number of larger-area features on the solar disk. These changes in the global network structure during solar minima may characterize, in part, the geo-effectiveness of the solar He II EUV irradiance in addition to the estimations based on its absolute levels.

Energy Landscape of Social Balance

NASA Astrophysics Data System (ADS)

Marvel, Seth A.; Strogatz, Steven H.; Kleinberg, Jon M.

2009-11-01

We model a close-knit community of friends and enemies as a fully connected network with positive and negative signs on its edges. Theories from social psychology suggest that certain sign patterns are more stable than others. This notion of social “balance” allows us to define an energy landscape for such networks. Its structure is complex: numerical experiments reveal a landscape dimpled with local minima of widely varying energy levels. We derive rigorous bounds on the energies of these local minima and prove that they have a modular structure that can be used to classify them.

Lone pairs: an electrostatic viewpoint.

PubMed

Kumar, Anmol; Gadre, Shridhar R; Mohan, Neetha; Suresh, Cherumuttathu H

2014-01-16

A clear-cut definition of lone pairs has been offered in terms of characteristics of minima in molecular electrostatic potential (MESP). The largest eigenvalue and corresponding eigenvector of the Hessian at the minima are shown to distinguish lone pair regions from the other types of electron localization (such as π bonds). A comparative study of lone pairs as depicted by various other scalar fields such as the Laplacian of electron density and electron localization function is made. Further, an attempt has been made to generalize the definition of lone pairs to the case of cations.

Energy landscape of social balance.

PubMed

Marvel, Seth A; Strogatz, Steven H; Kleinberg, Jon M

2009-11-06

We model a close-knit community of friends and enemies as a fully connected network with positive and negative signs on its edges. Theories from social psychology suggest that certain sign patterns are more stable than others. This notion of social "balance" allows us to define an energy landscape for such networks. Its structure is complex: numerical experiments reveal a landscape dimpled with local minima of widely varying energy levels. We derive rigorous bounds on the energies of these local minima and prove that they have a modular structure that can be used to classify them.

Establishing a Dynamic Self-Adaptation Learning Algorithm of the BP Neural Network and Its Applications

NASA Astrophysics Data System (ADS)

Li, Xiaofeng; Xiang, Suying; Zhu, Pengfei; Wu, Min

2015-12-01

In order to avoid the inherent deficiencies of the traditional BP neural network, such as slow convergence speed, that easily leading to local minima, poor generalization ability and difficulty in determining the network structure, the dynamic self-adaptive learning algorithm of the BP neural network is put forward to improve the function of the BP neural network. The new algorithm combines the merit of principal component analysis, particle swarm optimization, correlation analysis and self-adaptive model, hence can effectively solve the problems of selecting structural parameters, initial connection weights and thresholds and learning rates of the BP neural network. This new algorithm not only reduces the human intervention, optimizes the topological structures of BP neural networks and improves the network generalization ability, but also accelerates the convergence speed of a network, avoids trapping into local minima, and enhances network adaptation ability and prediction ability. The dynamic self-adaptive learning algorithm of the BP neural network is used to forecast the total retail sale of consumer goods of Sichuan Province, China. Empirical results indicate that the new algorithm is superior to the traditional BP network algorithm in predicting accuracy and time consumption, which shows the feasibility and effectiveness of the new algorithm.

Recovering Long-wavelength Velocity Models using Spectrogram Inversion with Single- and Multi-frequency Components

NASA Astrophysics Data System (ADS)

Ha, J.; Chung, W.; Shin, S.

2015-12-01

Many waveform inversion algorithms have been proposed in order to construct subsurface velocity structures from seismic data sets. These algorithms have suffered from computational burden, local minima problems, and the lack of low-frequency components. Computational efficiency can be improved by the application of back-propagation techniques and advances in computing hardware. In addition, waveform inversion algorithms, for obtaining long-wavelength velocity models, could avoid both the local minima problem and the effect of the lack of low-frequency components in seismic data. In this study, we proposed spectrogram inversion as a technique for recovering long-wavelength velocity models. In spectrogram inversion, decomposed frequency components from spectrograms of traces, in the observed and calculated data, are utilized to generate traces with reproduced low-frequency components. Moreover, since each decomposed component can reveal the different characteristics of a subsurface structure, several frequency components were utilized to analyze the velocity features in the subsurface. We performed the spectrogram inversion using a modified SEG/SEGE salt A-A' line. Numerical results demonstrate that spectrogram inversion could also recover the long-wavelength velocity features. However, inversion results varied according to the frequency components utilized. Based on the results of inversion using a decomposed single-frequency component, we noticed that robust inversion results are obtained when a dominant frequency component of the spectrogram was utilized. In addition, detailed information on recovered long-wavelength velocity models was obtained using a multi-frequency component combined with single-frequency components. Numerical examples indicate that various detailed analyses of long-wavelength velocity models can be carried out utilizing several frequency components.

Vacuum selection on axionic landscapes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Gaoyuan; Battefeld, Thorsten, E-mail: gaoyuan.wang@stud.uni-goettingen.de, E-mail: tbattefe@astro.physik.uni-goettingen.de

2016-04-01

We compute the distribution of minima that are reached dynamically on multi-field axionic landscapes, both numerically and analytically. Such landscapes are well suited for inflationary model building due to the presence of shift symmetries and possible alignment effects (the KNP mechanism). The resulting distribution of dynamically reached minima differs considerably from the naive expectation based on counting all vacua. These differences are more pronounced in the presence of many fields due to dynamical selection effects: while low lying minima are preferred as fields roll down the potential, trajectories are also more likely to get trapped by one of the manymore » nearby minima. We show that common analytic arguments based on random matrix theory in the large D-limit to estimate the distribution of minima are insufficient for quantitative arguments pertaining to the dynamically reached ones. This discrepancy is not restricted to axionic potentials. We provide an empirical expression for the expectation value of such dynamically reached minimas' height and argue that the cosmological constant problem is not alleviated in the absence of anthropic arguments. We further comment on the likelihood of inflation on axionic landscapes in the large D-limit.« less

Marginal Shape Deep Learning: Applications to Pediatric Lung Field Segmentation.

PubMed

Mansoor, Awais; Cerrolaza, Juan J; Perez, Geovanny; Biggs, Elijah; Nino, Gustavo; Linguraru, Marius George

2017-02-11

Representation learning through deep learning (DL) architecture has shown tremendous potential for identification, localization, and texture classification in various medical imaging modalities. However, DL applications to segmentation of objects especially to deformable objects are rather limited and mostly restricted to pixel classification. In this work, we propose marginal shape deep learning (MaShDL), a framework that extends the application of DL to deformable shape segmentation by using deep classifiers to estimate the shape parameters. MaShDL combines the strength of statistical shape models with the automated feature learning architecture of DL. Unlike the iterative shape parameters estimation approach of classical shape models that often leads to a local minima, the proposed framework is robust to local minima optimization and illumination changes. Furthermore, since the direct application of DL framework to a multi-parameter estimation problem results in a very high complexity, our framework provides an excellent run-time performance solution by independently learning shape parameter classifiers in marginal eigenspaces in the decreasing order of variation. We evaluated MaShDL for segmenting the lung field from 314 normal and abnormal pediatric chest radiographs and obtained a mean Dice similarity coefficient of 0.927 using only the four highest modes of variation (compared to 0.888 with classical ASM 1 (p-value=0.01) using same configuration). To the best of our knowledge this is the first demonstration of using DL framework for parametrized shape learning for the delineation of deformable objects.

Marginal shape deep learning: applications to pediatric lung field segmentation

NASA Astrophysics Data System (ADS)

Mansoor, Awais; Cerrolaza, Juan J.; Perez, Geovany; Biggs, Elijah; Nino, Gustavo; Linguraru, Marius George

2017-02-01

Representation learning through deep learning (DL) architecture has shown tremendous potential for identification, local- ization, and texture classification in various medical imaging modalities. However, DL applications to segmentation of objects especially to deformable objects are rather limited and mostly restricted to pixel classification. In this work, we propose marginal shape deep learning (MaShDL), a framework that extends the application of DL to deformable shape segmentation by using deep classifiers to estimate the shape parameters. MaShDL combines the strength of statistical shape models with the automated feature learning architecture of DL. Unlike the iterative shape parameters estimation approach of classical shape models that often leads to a local minima, the proposed framework is robust to local minima optimization and illumination changes. Furthermore, since the direct application of DL framework to a multi-parameter estimation problem results in a very high complexity, our framework provides an excellent run-time performance solution by independently learning shape parameter classifiers in marginal eigenspaces in the decreasing order of variation. We evaluated MaShDL for segmenting the lung field from 314 normal and abnormal pediatric chest radiographs and obtained a mean Dice similarity coefficient of 0:927 using only the four highest modes of variation (compared to 0:888 with classical ASM1 (p-value=0:01) using same configuration). To the best of our knowledge this is the first demonstration of using DL framework for parametrized shape learning for the delineation of deformable objects.

Marginal Shape Deep Learning: Applications to Pediatric Lung Field Segmentation

PubMed Central

Mansoor, Awais; Cerrolaza, Juan J.; Perez, Geovanny; Biggs, Elijah; Nino, Gustavo; Linguraru, Marius George

2017-01-01

Representation learning through deep learning (DL) architecture has shown tremendous potential for identification, localization, and texture classification in various medical imaging modalities. However, DL applications to segmentation of objects especially to deformable objects are rather limited and mostly restricted to pixel classification. In this work, we propose marginal shape deep learning (MaShDL), a framework that extends the application of DL to deformable shape segmentation by using deep classifiers to estimate the shape parameters. MaShDL combines the strength of statistical shape models with the automated feature learning architecture of DL. Unlike the iterative shape parameters estimation approach of classical shape models that often leads to a local minima, the proposed framework is robust to local minima optimization and illumination changes. Furthermore, since the direct application of DL framework to a multi-parameter estimation problem results in a very high complexity, our framework provides an excellent run-time performance solution by independently learning shape parameter classifiers in marginal eigenspaces in the decreasing order of variation. We evaluated MaShDL for segmenting the lung field from 314 normal and abnormal pediatric chest radiographs and obtained a mean Dice similarity coefficient of 0.927 using only the four highest modes of variation (compared to 0.888 with classical ASM1 (p-value=0.01) using same configuration). To the best of our knowledge this is the first demonstration of using DL framework for parametrized shape learning for the delineation of deformable objects. PMID:28592911

Total variation regularization for seismic waveform inversion using an adaptive primal dual hybrid gradient method

NASA Astrophysics Data System (ADS)

Yong, Peng; Liao, Wenyuan; Huang, Jianping; Li, Zhenchuan

2018-04-01

Full waveform inversion is an effective tool for recovering the properties of the Earth from seismograms. However, it suffers from local minima caused mainly by the limited accuracy of the starting model and the lack of a low-frequency component in the seismic data. Because of the high velocity contrast between salt and sediment, the relation between the waveform and velocity perturbation is strongly nonlinear. Therefore, salt inversion can easily get trapped in the local minima. Since the velocity of salt is nearly constant, we can make the most of this characteristic with total variation regularization to mitigate the local minima. In this paper, we develop an adaptive primal dual hybrid gradient method to implement total variation regularization by projecting the solution onto a total variation norm constrained convex set, through which the total variation norm constraint is satisfied at every model iteration. The smooth background velocities are first inverted and the perturbations are gradually obtained by successively relaxing the total variation norm constraints. Numerical experiment of the projection of the BP model onto the intersection of the total variation norm and box constraints has demonstrated the accuracy and efficiency of our adaptive primal dual hybrid gradient method. A workflow is designed to recover complex salt structures in the BP 2004 model and the 2D SEG/EAGE salt model, starting from a linear gradient model without using low-frequency data below 3 Hz. The salt inversion processes demonstrate that wavefield reconstruction inversion with a total variation norm and box constraints is able to overcome local minima and inverts the complex salt velocity layer by layer.

From sticky-hard-sphere to Lennard-Jones-type clusters

NASA Astrophysics Data System (ADS)

Trombach, Lukas; Hoy, Robert S.; Wales, David J.; Schwerdtfeger, Peter

2018-04-01

A relation MSHS →LJ between the set of nonisomorphic sticky-hard-sphere clusters MSHS and the sets of local energy minima ML J of the (m ,n ) -Lennard-Jones potential Vmn LJ(r ) =ɛ/n -m [m r-n-n r-m] is established. The number of nonisomorphic stable clusters depends strongly and nontrivially on both m and n and increases exponentially with increasing cluster size N for N ≳10 . While the map from MSHS→MSHS →LJ is noninjective and nonsurjective, the number of Lennard-Jones structures missing from the map is relatively small for cluster sizes up to N =13 , and most of the missing structures correspond to energetically unfavorable minima even for fairly low (m ,n ) . Furthermore, even the softest Lennard-Jones potential predicts that the coordination of 13 spheres around a central sphere is problematic (the Gregory-Newton problem). A more realistic extended Lennard-Jones potential chosen from coupled-cluster calculations for a rare gas dimer leads to a substantial increase in the number of nonisomorphic clusters, even though the potential curve is very similar to a (6,12)-Lennard-Jones potential.

Feature detection on 3D images of dental imprints

NASA Astrophysics Data System (ADS)

Mokhtari, Marielle; Laurendeau, Denis

1994-09-01

A computer vision approach for the extraction of feature points on 3D images of dental imprints is presented. The position of feature points are needed for the measurement of a set of parameters for automatic diagnosis of malocclusion problems in orthodontics. The system for the acquisition of the 3D profile of the imprint, the procedure for the detection of the interstices between teeth, and the approach for the identification of the type of tooth are described, as well as the algorithm for the reconstruction of the surface of each type of tooth. A new approach for the detection of feature points, called the watershed algorithm, is described in detail. The algorithm is a two-stage procedure which tracks the position of local minima at four different scales and produces a final map of the position of the minima. Experimental results of the application of the watershed algorithm on actual 3D images of dental imprints are presented for molars, premolars and canines. The segmentation approach for the analysis of the shape of incisors is also described in detail.

From sticky-hard-sphere to Lennard-Jones-type clusters.

PubMed

Trombach, Lukas; Hoy, Robert S; Wales, David J; Schwerdtfeger, Peter

2018-04-01

A relation M_{SHS→LJ} between the set of nonisomorphic sticky-hard-sphere clusters M_{SHS} and the sets of local energy minima M_{LJ} of the (m,n)-Lennard-Jones potential V_{mn}^{LJ}(r)=ɛ/n-m[mr^{-n}-nr^{-m}] is established. The number of nonisomorphic stable clusters depends strongly and nontrivially on both m and n and increases exponentially with increasing cluster size N for N≳10. While the map from M_{SHS}→M_{SHS→LJ} is noninjective and nonsurjective, the number of Lennard-Jones structures missing from the map is relatively small for cluster sizes up to N=13, and most of the missing structures correspond to energetically unfavorable minima even for fairly low (m,n). Furthermore, even the softest Lennard-Jones potential predicts that the coordination of 13 spheres around a central sphere is problematic (the Gregory-Newton problem). A more realistic extended Lennard-Jones potential chosen from coupled-cluster calculations for a rare gas dimer leads to a substantial increase in the number of nonisomorphic clusters, even though the potential curve is very similar to a (6,12)-Lennard-Jones potential.

Dimensional oscillation. A fast variation of energy embedding gives good results with the AMBER potential energy function.

PubMed

Snow, M E; Crippen, G M

1991-08-01

The structure of the AMBER potential energy surface of the cyclic tetrapeptide cyclotetrasarcosyl is analyzed as a function of the dimensionality of coordinate space. It is found that the number of local energy minima decreases as the dimensionality of the space increases until some limit at which point equipotential subspaces appear. The applicability of energy embedding methods to finding global energy minima in this type of energy-conformation space is explored. Dimensional oscillation, a computationally fast variant of energy embedding is introduced and found to sample conformation space widely and to do a good job of finding global and near-global energy minima.

Improving the Fitness of High-Dimensional Biomechanical Models via Data-Driven Stochastic Exploration

PubMed Central

Bustamante, Carlos D.; Valero-Cuevas, Francisco J.

2010-01-01

The field of complex biomechanical modeling has begun to rely on Monte Carlo techniques to investigate the effects of parameter variability and measurement uncertainty on model outputs, search for optimal parameter combinations, and define model limitations. However, advanced stochastic methods to perform data-driven explorations, such as Markov chain Monte Carlo (MCMC), become necessary as the number of model parameters increases. Here, we demonstrate the feasibility and, what to our knowledge is, the first use of an MCMC approach to improve the fitness of realistically large biomechanical models. We used a Metropolis–Hastings algorithm to search increasingly complex parameter landscapes (3, 8, 24, and 36 dimensions) to uncover underlying distributions of anatomical parameters of a “truth model” of the human thumb on the basis of simulated kinematic data (thumbnail location, orientation, and linear and angular velocities) polluted by zero-mean, uncorrelated multivariate Gaussian “measurement noise.” Driven by these data, ten Markov chains searched each model parameter space for the subspace that best fit the data (posterior distribution). As expected, the convergence time increased, more local minima were found, and marginal distributions broadened as the parameter space complexity increased. In the 36-D scenario, some chains found local minima but the majority of chains converged to the true posterior distribution (confirmed using a cross-validation dataset), thus demonstrating the feasibility and utility of these methods for realistically large biomechanical problems. PMID:19272906

CALIBRATING NON-CONVEX PENALIZED REGRESSION IN ULTRA-HIGH DIMENSION.

PubMed

Wang, Lan; Kim, Yongdai; Li, Runze

2013-10-01

We investigate high-dimensional non-convex penalized regression, where the number of covariates may grow at an exponential rate. Although recent asymptotic theory established that there exists a local minimum possessing the oracle property under general conditions, it is still largely an open problem how to identify the oracle estimator among potentially multiple local minima. There are two main obstacles: (1) due to the presence of multiple minima, the solution path is nonunique and is not guaranteed to contain the oracle estimator; (2) even if a solution path is known to contain the oracle estimator, the optimal tuning parameter depends on many unknown factors and is hard to estimate. To address these two challenging issues, we first prove that an easy-to-calculate calibrated CCCP algorithm produces a consistent solution path which contains the oracle estimator with probability approaching one. Furthermore, we propose a high-dimensional BIC criterion and show that it can be applied to the solution path to select the optimal tuning parameter which asymptotically identifies the oracle estimator. The theory for a general class of non-convex penalties in the ultra-high dimensional setup is established when the random errors follow the sub-Gaussian distribution. Monte Carlo studies confirm that the calibrated CCCP algorithm combined with the proposed high-dimensional BIC has desirable performance in identifying the underlying sparsity pattern for high-dimensional data analysis.

CALIBRATING NON-CONVEX PENALIZED REGRESSION IN ULTRA-HIGH DIMENSION

PubMed Central

Wang, Lan; Kim, Yongdai; Li, Runze

2014-01-01

We investigate high-dimensional non-convex penalized regression, where the number of covariates may grow at an exponential rate. Although recent asymptotic theory established that there exists a local minimum possessing the oracle property under general conditions, it is still largely an open problem how to identify the oracle estimator among potentially multiple local minima. There are two main obstacles: (1) due to the presence of multiple minima, the solution path is nonunique and is not guaranteed to contain the oracle estimator; (2) even if a solution path is known to contain the oracle estimator, the optimal tuning parameter depends on many unknown factors and is hard to estimate. To address these two challenging issues, we first prove that an easy-to-calculate calibrated CCCP algorithm produces a consistent solution path which contains the oracle estimator with probability approaching one. Furthermore, we propose a high-dimensional BIC criterion and show that it can be applied to the solution path to select the optimal tuning parameter which asymptotically identifies the oracle estimator. The theory for a general class of non-convex penalties in the ultra-high dimensional setup is established when the random errors follow the sub-Gaussian distribution. Monte Carlo studies confirm that the calibrated CCCP algorithm combined with the proposed high-dimensional BIC has desirable performance in identifying the underlying sparsity pattern for high-dimensional data analysis. PMID:24948843

On adaptive learning rate that guarantees convergence in feedforward networks.

PubMed

Behera, Laxmidhar; Kumar, Swagat; Patnaik, Awhan

2006-09-01

This paper investigates new learning algorithms (LF I and LF II) based on Lyapunov function for the training of feedforward neural networks. It is observed that such algorithms have interesting parallel with the popular backpropagation (BP) algorithm where the fixed learning rate is replaced by an adaptive learning rate computed using convergence theorem based on Lyapunov stability theory. LF II, a modified version of LF I, has been introduced with an aim to avoid local minima. This modification also helps in improving the convergence speed in some cases. Conditions for achieving global minimum for these kind of algorithms have been studied in detail. The performances of the proposed algorithms are compared with BP algorithm and extended Kalman filtering (EKF) on three bench-mark function approximation problems: XOR, 3-bit parity, and 8-3 encoder. The comparisons are made in terms of number of learning iterations and computational time required for convergence. It is found that the proposed algorithms (LF I and II) are much faster in convergence than other two algorithms to attain same accuracy. Finally, the comparison is made on a complex two-dimensional (2-D) Gabor function and effect of adaptive learning rate for faster convergence is verified. In a nutshell, the investigations made in this paper help us better understand the learning procedure of feedforward neural networks in terms of adaptive learning rate, convergence speed, and local minima.

Spin-diffusions and diffusive molecular dynamics

NASA Astrophysics Data System (ADS)

Farmer, Brittan; Luskin, Mitchell; Plecháč, Petr; Simpson, Gideon

2017-12-01

Metastable configurations in condensed matter typically fluctuate about local energy minima at the femtosecond time scale before transitioning between local minima after nanoseconds or microseconds. This vast scale separation limits the applicability of classical molecular dynamics (MD) methods and has spurned the development of a host of approximate algorithms. One recently proposed method is diffusive MD which aims at integrating a system of ordinary differential equations describing the likelihood of occupancy by one of two species, in the case of a binary alloy, while quasistatically evolving the locations of the atoms. While diffusive MD has shown itself to be efficient and provide agreement with observations, it is fundamentally a model, with unclear connections to classical MD. In this work, we formulate a spin-diffusion stochastic process and show how it can be connected to diffusive MD. The spin-diffusion model couples a classical overdamped Langevin equation to a kinetic Monte Carlo model for exchange amongst the species of a binary alloy. Under suitable assumptions and approximations, spin-diffusion can be shown to lead to diffusive MD type models. The key assumptions and approximations include a well-defined time scale separation, a choice of spin-exchange rates, a low temperature approximation, and a mean field type approximation. We derive several models from different assumptions and show their relationship to diffusive MD. Differences and similarities amongst the models are explored in a simple test problem.

Close packing in curved space by simulated annealing

NASA Astrophysics Data System (ADS)

Wille, L. T.

1987-12-01

The problem of packing spheres of a maximum radius on the surface of a four-dimensional hypersphere is considered. It is shown how near-optimal solutions can be obtained by packing soft spheres, modelled as classical particles interacting under an inverse power potential, followed by a subsequent hardening of the interaction. In order to avoid trapping in high-lying local minima, the simulated annealing method is used to optimise the soft-sphere packing. Several improvements over other work (based on local optimisation of random initial configurations of hard spheres) have been found. The freezing behaviour of this system is discussed as a function of particle number, softness of the potential and cooling rate. Apart from their geometric interest, these results are useful in the study of topological frustration, metallic glasses and quasicrystals.

Determination of elastic moduli from measured acoustic velocities.

PubMed

Brown, J Michael

2018-06-01

Methods are evaluated in solution of the inverse problem associated with determination of elastic moduli for crystals of arbitrary symmetry from elastic wave velocities measured in many crystallographic directions. A package of MATLAB functions provides a robust and flexible environment for analysis of ultrasonic, Brillouin, or Impulsive Stimulated Light Scattering datasets. Three inverse algorithms are considered: the gradient-based methods of Levenberg-Marquardt and Backus-Gilbert, and a non-gradient-based (Nelder-Mead) simplex approach. Several data types are considered: body wave velocities alone, surface wave velocities plus a side constraint on X-ray-diffraction-based axes compressibilities, or joint body and surface wave velocities. The numerical algorithms are validated through comparisons with prior published results and through analysis of synthetic datasets. Although all approaches succeed in finding low-misfit solutions, the Levenberg-Marquardt method consistently demonstrates effectiveness and computational efficiency. However, linearized gradient-based methods, when applied to a strongly non-linear problem, may not adequately converge to the global minimum. The simplex method, while slower, is less susceptible to being trapped in local misfit minima. A "multi-start" strategy (initiate searches from more than one initial guess) provides better assurance that global minima have been located. Numerical estimates of parameter uncertainties based on Monte Carlo simulations are compared to formal uncertainties based on covariance calculations. Copyright © 2018 Elsevier B.V. All rights reserved.

Parallel optimization algorithm for drone inspection in the building industry

NASA Astrophysics Data System (ADS)

Walczyński, Maciej; BoŻejko, Wojciech; Skorupka, Dariusz

2017-07-01

In this paper we present an approach for Vehicle Routing Problem with Drones (VRPD) in case of building inspection from the air. In autonomic inspection process there is a need to determine of the optimal route for inspection drone. This is especially important issue because of the very limited flight time of modern multicopters. The method of determining solutions for Traveling Salesman Problem(TSP), described in this paper bases on Parallel Evolutionary Algorithm (ParEA)with cooperative and independent approach for communication between threads. This method described first by Bożejko and Wodecki [1] bases on the observation that if exists some number of elements on certain positions in a number of permutations which are local minima, then those elements will be in the same position in the optimal solution for TSP problem. Numerical experiments were made on BEM computational cluster with using MPI library.

Time-domain full waveform inversion using instantaneous phase information with damping

NASA Astrophysics Data System (ADS)

Luo, Jingrui; Wu, Ru-Shan; Gao, Fuchun

2018-06-01

In time domain, the instantaneous phase can be obtained from the complex seismic trace using Hilbert transform. The instantaneous phase information has great potential in overcoming the local minima problem and improving the result of full waveform inversion. However, the phase wrapping problem, which comes from numerical calculation, prevents its application. In order to avoid the phase wrapping problem, we choose to use the exponential phase combined with the damping method, which gives instantaneous phase-based multi-stage inversion. We construct the objective functions based on the exponential instantaneous phase, and also derive the corresponding gradient operators. Conventional full waveform inversion and the instantaneous phase-based inversion are compared with numerical examples, which indicates that in the case without low frequency information in seismic data, our method is an effective and efficient approach for initial model construction for full waveform inversion.

An Atlas of O-C Diagrams of Eclipsing Binary Stars

NASA Astrophysics Data System (ADS)

Kreiner, Jerzy M.; Kim, Chun-Hwey; Nha, Il-Seong

The Atlas contains data for 1,138 eclipsing binaries represented by 91,798 minima timings, collected from the usual international and local journals, observatory publications and unpublished minima. Among this source material there is a considerable representation of amateur astronomers. Some timings were found in the card-index catalogue of the Astronomical Observatory of the Jagiellonian University, Cracow. Stars were included in the Atlas provided that they satisfied 3 criteria: (1) at least 20 minima had been times; (2) these minima spanned at least 2,500 cycles; and (3) the 2,500 cycles represented no fewer than 40 years. Some additional stars not strictly satisfying these criteria were also included if useful information was available. For each star, the Atlas contains the (O-C) diagram calculated by the authors and a table of general information containing: binary characteristics; assorted catalogue numbers; the statistics of the collected minima timings; the light elements (light ephemeris); comments and literature references. All of the data and diagrams in the Atlas are also available in electronic form on the Internet at http://www.as.ap.krakow.pl/o- c".

Investigation of transition States in bulk and freestanding film polymer glasses.

PubMed

Jain, Tushar S; de Pablo, Juan J

2004-04-16

We have performed transition state searches on the potential energy landscape for bulk and freestanding film polymer glasses and identified connected minima. An analysis of the displacements between minima shows that the sites that undergo the greatest displacement are highly localized in space for both the bulk and the thin-film systems studied. In the case of the thin film, the clusters originate at the surface and penetrate into the center of the film thereby coupling the relaxation in the center of the film to the mobile surface layer. Furthermore, the energy barriers between minima are lower in the thin film than in the bulk system. These findings can rationalize the experimentally observed depression of the glass transition temperature in freestanding polymer films.

Minimum noise impact aircraft trajectories

NASA Technical Reports Server (NTRS)

Jacobson, I. D.; Melton, R. G.

1981-01-01

Numerical optimization is used to compute the optimum flight paths, based upon a parametric form that implicitly includes some of the problem restrictions. The other constraints are formulated as penalties in the cost function. Various aircraft on multiple trajectores (landing and takeoff) can be considered. The modular design employed allows for the substitution of alternate models of the population distribution, aircraft noise, flight paths, and annoyance, or for the addition of other features (e.g., fuel consumption) in the cost function. A reduction in the required amount of searching over local minima was achieved through use of the presence of statistical lateral dispersion in the flight paths.

Weak variations of Lipschitz graphs and stability of phase boundaries

NASA Astrophysics Data System (ADS)

Grabovsky, Yury; Kucher, Vladislav A.; Truskinovsky, Lev

2011-03-01

In the case of Lipschitz extremals of vectorial variational problems, an important class of strong variations originates from smooth deformations of the corresponding non-smooth graphs. These seemingly singular variations, which can be viewed as combinations of weak inner and outer variations, produce directions of differentiability of the functional and lead to singularity-centered necessary conditions on strong local minima: an equality, arising from stationarity, and an inequality, implying configurational stability of the singularity set. To illustrate the underlying coupling between inner and outer variations, we study in detail the case of smooth surfaces of gradient discontinuity representing, for instance, martensitic phase boundaries in non-linear elasticity.

Noniterative estimation of a nonlinear parameter

NASA Technical Reports Server (NTRS)

Bergstroem, A.

1973-01-01

An algorithm is described which solves the parameters X = (x1,x2,...,xm) and p in an approximation problem Ax nearly equal to y(p), where the parameter p occurs nonlinearly in y. Instead of linearization methods, which require an approximate value of p to be supplied as a priori information, and which may lead to the finding of local minima, the proposed algorithm finds the global minimum by permitting the use of series expansions of arbitrary order, exploiting an a priori knowledge that the addition of a particular function, corresponding to a new column in A, will not improve the goodness of the approximation.

Hybrid General Pattern Search and Simulated Annealing for Industrail Production Planning Problems

NASA Astrophysics Data System (ADS)

Vasant, P.; Barsoum, N.

2010-06-01

In this paper, the hybridization of GPS (General Pattern Search) method and SA (Simulated Annealing) incorporated in the optimization process in order to look for the global optimal solution for the fitness function and decision variables as well as minimum computational CPU time. The real strength of SA approach been tested in this case study problem of industrial production planning. This is due to the great advantage of SA for being easily escaping from trapped in local minima by accepting up-hill move through a probabilistic procedure in the final stages of optimization process. Vasant [1] in his Ph. D thesis has provided 16 different techniques of heuristic and meta-heuristic in solving industrial production problems with non-linear cubic objective functions, eight decision variables and 29 constraints. In this paper, fuzzy technological problems have been solved using hybrid techniques of general pattern search and simulated annealing. The simulated and computational results are compared to other various evolutionary techniques.

Bifurcation analysis of eight coupled degenerate optical parametric oscillators

NASA Astrophysics Data System (ADS)

Ito, Daisuke; Ueta, Tetsushi; Aihara, Kazuyuki

2018-06-01

A degenerate optical parametric oscillator (DOPO) network realized as a coherent Ising machine can be used to solve combinatorial optimization problems. Both theoretical and experimental investigations into the performance of DOPO networks have been presented previously. However a problem remains, namely that the dynamics of the DOPO network itself can lower the search success rates of globally optimal solutions for Ising problems. This paper shows that the problem is caused by pitchfork bifurcations due to the symmetry structure of coupled DOPOs. Some two-parameter bifurcation diagrams of equilibrium points express the performance deterioration. It is shown that the emergence of non-ground states regarding local minima hampers the system from reaching the ground states corresponding to the global minimum. We then describe a parametric strategy for leading a system to the ground state by actively utilizing the bifurcation phenomena. By adjusting the parameters to break particular symmetry, we find appropriate parameter sets that allow the coherent Ising machine to obtain the globally optimal solution alone.

Conformational Sampling of a Biomolecular Rugged Energy Landscape.

PubMed

Rydzewski, Jakub; Jakubowski, Rafal; Nicosia, Giuseppe; Nowak, Wieslaw

2018-01-01

The protein structure refinement using conformational sampling is important in hitherto protein studies. In this paper, we examined the protein structure refinement by means of potential energy minimization using immune computing as a method of sampling conformations. The method was tested on the x-ray structure and 30 decoys of the mutant of [Leu]Enkephalin, a paradigmatic example of the biomolecular multiple-minima problem. In order to score the refined conformations, we used a standard potential energy function with the OPLSAA force field. The effectiveness of the search was assessed using a variety of methods. The robustness of sampling was checked by the energy yield function which measures quantitatively the number of the peptide decoys residing in an energetic funnel. Furthermore, the potential energy-dependent Pareto fronts were calculated to elucidate dissimilarities between peptide conformations and the native state as observed by x-ray crystallography. Our results showed that the probed potential energy landscape of [Leu]Enkephalin is self-similar on different metric scales and that the local potential energy minima of the peptide decoys are metastable, thus they can be refined to conformations whose potential energy is decreased by approximately 250 kJ/mol.

A Darwinian approach to control-structure design

NASA Technical Reports Server (NTRS)

Zimmerman, David C.

1993-01-01

Genetic algorithms (GA's), as introduced by Holland (1975), are one form of directed random search. The form of direction is based on Darwin's 'survival of the fittest' theories. GA's are radically different from the more traditional design optimization techniques. GA's work with a coding of the design variables, as opposed to working with the design variables directly. The search is conducted from a population of designs (i.e., from a large number of points in the design space), unlike the traditional algorithms which search from a single design point. The GA requires only objective function information, as opposed to gradient or other auxiliary information. Finally, the GA is based on probabilistic transition rules, as opposed to deterministic rules. These features allow the GA to attack problems with local-global minima, discontinuous design spaces and mixed variable problems, all in a single, consistent framework.

Activities: Activities to Introduce Maxima-Minima Problems.

ERIC Educational Resources Information Center

Pleacher, David

1991-01-01

Presented are student activities that involve two standard problems from geometry and calculus--the volume of a box and the bank shot on a pool table. Problem solving is emphasized as a method of inquiry and application with descriptions of the results using graphical, numerical, and physical models. (JJK)

3D Clumped Cell Segmentation Using Curvature Based Seeded Watershed.

PubMed

Atta-Fosu, Thomas; Guo, Weihong; Jeter, Dana; Mizutani, Claudia M; Stopczynski, Nathan; Sousa-Neves, Rui

2016-12-01

Image segmentation is an important process that separates objects from the background and also from each other. Applied to cells, the results can be used for cell counting which is very important in medical diagnosis and treatment, and biological research that is often used by scientists and medical practitioners. Segmenting 3D confocal microscopy images containing cells of different shapes and sizes is still challenging as the nuclei are closely packed. The watershed transform provides an efficient tool in segmenting such nuclei provided a reasonable set of markers can be found in the image. In the presence of low-contrast variation or excessive noise in the given image, the watershed transform leads to over-segmentation (a single object is overly split into multiple objects). The traditional watershed uses the local minima of the input image and will characteristically find multiple minima in one object unless they are specified (marker-controlled watershed). An alternative to using the local minima is by a supervised technique called seeded watershed, which supplies single seeds to replace the minima for the objects. Consequently, the accuracy of a seeded watershed algorithm relies on the accuracy of the predefined seeds. In this paper, we present a segmentation approach based on the geometric morphological properties of the 'landscape' using curvatures. The curvatures are computed as the eigenvalues of the Shape matrix, producing accurate seeds that also inherit the original shape of their respective cells. We compare with some popular approaches and show the advantage of the proposed method.

A Minimum Variance Algorithm for Overdetermined TOA Equations with an Altitude Constraint.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Romero, Louis A; Mason, John J.

We present a direct (non-iterative) method for solving for the location of a radio frequency (RF) emitter, or an RF navigation receiver, using four or more time of arrival (TOA) measurements and an assumed altitude above an ellipsoidal earth. Both the emitter tracking problem and the navigation application are governed by the same equations, but with slightly different interpreta- tions of several variables. We treat the assumed altitude as a soft constraint, with a specified noise level, just as the TOA measurements are handled, with their respective noise levels. With 4 or more TOA measurements and the assumed altitude, themore » problem is overdetermined and is solved in the weighted least squares sense for the 4 unknowns, the 3-dimensional position and time. We call the new technique the TAQMV (TOA Altitude Quartic Minimum Variance) algorithm, and it achieves the minimum possible error variance for given levels of TOA and altitude estimate noise. The method algebraically produces four solutions, the least-squares solution, and potentially three other low residual solutions, if they exist. In the lightly overdermined cases where multiple local minima in the residual error surface are more likely to occur, this algebraic approach can produce all of the minima even when an iterative approach fails to converge. Algorithm performance in terms of solution error variance and divergence rate for bas eline (iterative) and proposed approach are given in tables.« less

Application of Simulated Annealing and Related Algorithms to TWTA Design

NASA Technical Reports Server (NTRS)

Radke, Eric M.

2004-01-01

Simulated Annealing (SA) is a stochastic optimization algorithm used to search for global minima in complex design surfaces where exhaustive searches are not computationally feasible. The algorithm is derived by simulating the annealing process, whereby a solid is heated to a liquid state and then cooled slowly to reach thermodynamic equilibrium at each temperature. The idea is that atoms in the solid continually bond and re-bond at various quantum energy levels, and with sufficient cooling time they will rearrange at the minimum energy state to form a perfect crystal. The distribution of energy levels is given by the Boltzmann distribution: as temperature drops, the probability of the presence of high-energy bonds decreases. In searching for an optimal design, local minima and discontinuities are often present in a design surface. SA presents a distinct advantage over other optimization algorithms in its ability to escape from these local minima. Just as high-energy atomic configurations are visited in the actual annealing process in order to eventually reach the minimum energy state, in SA highly non-optimal configurations are visited in order to find otherwise inaccessible global minima. The SA algorithm produces a Markov chain of points in the design space at each temperature, with a monotonically decreasing temperature. A random point is started upon, and the objective function is evaluated at that point. A stochastic perturbation is then made to the parameters of the point to arrive at a proposed new point in the design space, at which the objection function is evaluated as well. If the change in objective function values (Delta)E is negative, the proposed new point is accepted. If (Delta)E is positive, the proposed new point is accepted according to the Metropolis criterion: rho((Delta)f) = exp((-Delta)E/T), where T is the temperature for the current Markov chain. The process then repeats for the remainder of the Markov chain, after which the temperature is decremented and the process repeats. Eventually (and hopefully), a near-globally optimal solution is attained as T approaches zero. Several exciting variants of SA have recently emerged, including Discrete-State Simulated Annealing (DSSA) and Simulated Tempering (ST). The DSSA algorithm takes the thermodynamic analogy one step further by categorizing objective function evaluations into discrete states. In doing so, many of the case-specific problems associated with fine-tuning the SA algorithm can be avoided; for example, theoretical approximations for the initial and final temperature can be derived independently of the case. In this manner, DSSA provides a scheme that is more robust with respect to widely differing design surfaces. ST differs from SA in that the temperature T becomes an additional random variable in the optimization. The system is also kept in equilibrium as the temperature changes, as opposed to the system being driven out of equilibrium as temperature changes in SA. ST is designed to overcome obstacles in design surfaces where numerous local minima are separated by high barriers. These algorithms are incorporated into the optimal design of the traveling-wave tube amplifier (TWTA). The area under scrutiny is the collector, in which it would be ideal to use negative potential to decelerate the spent electron beam to zero kinetic energy just as it reaches the collector surface. In reality this is not plausible due to a number of physical limitations, including repulsion and differing levels of kinetic energy among individual electrons. Instead, the collector is designed with multiple stages depressed below ground potential. The design of this multiple-stage collector is the optimization problem of interest. One remaining problem in SA and DSSA is the difficulty in determining when equilibrium has been reached so that the current Markov chain can be terminated. It has been suggested in recent literature that simulating the thermodynamic properties opecific heat, entropy, and internal energy from the Boltzmann distribution can provide good indicators of having reached equilibrium at a certain temperature. These properties are tested for their efficacy and implemented in SA and DSSA code with respect to TWTA collector optimization.

Loss surface of XOR artificial neural networks

NASA Astrophysics Data System (ADS)

Mehta, Dhagash; Zhao, Xiaojun; Bernal, Edgar A.; Wales, David J.

2018-05-01

Training an artificial neural network involves an optimization process over the landscape defined by the cost (loss) as a function of the network parameters. We explore these landscapes using optimization tools developed for potential energy landscapes in molecular science. The number of local minima and transition states (saddle points of index one), as well as the ratio of transition states to minima, grow rapidly with the number of nodes in the network. There is also a strong dependence on the regularization parameter, with the landscape becoming more convex (fewer minima) as the regularization term increases. We demonstrate that in our formulation, stationary points for networks with Nh hidden nodes, including the minimal network required to fit the XOR data, are also stationary points for networks with Nh+1 hidden nodes when all the weights involving the additional node are zero. Hence, smaller networks trained on XOR data are embedded in the landscapes of larger networks. Our results clarify certain aspects of the classification and sensitivity (to perturbations in the input data) of minima and saddle points for this system, and may provide insight into dropout and network compression.

Stochastic Formalism for Thermally Driven Distribution Frontier: A Nonempirical Approach to the Potential Escape Problem

NASA Astrophysics Data System (ADS)

Akashi, Ryosuke; Nagornov, Yuri S.

2018-06-01

We develop a non-empirical scheme to search for the minimum-energy escape paths from the minima of the potential surface to unknown saddle points nearby. A stochastic algorithm is constructed to move the walkers up the surface through the potential valleys. This method employs only the local gradient and diagonal part of the Hessian matrix of the potential. An application to a two-dimensional model potential is presented to demonstrate the successful finding of the paths to the saddle points. The present scheme could serve as a starting point toward first-principles simulation of rare events across the potential basins free from empirical collective variables.

Geometry for Pie Lovers.

ERIC Educational Resources Information Center

Fisher, William

1982-01-01

An approach to the instruction of maxima and minima problems that works with tools of geometry and algebra is presented. The focus is on a classic pie-cutting problem, which is viewed as an interesting and instructive task that is an excellent application of transformation geometry. (MP)

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

NASA Astrophysics Data System (ADS)

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.

Phase Transition to Exact Susy

NASA Astrophysics Data System (ADS)

Clavelli, L.

2007-04-01

The anthropic principle is based on the observation that, within narrow bounds, the laws of physics are such as to have allowed the evolution of life. The string theoretic approach to understanding this observation is based on the expectation that the effective potential has an enormous number of local minima with different particle masses and perhaps totally different fundamental couplings and space time topology. The vast majority of these alternative universes are totally inhospitable to life, having, for example, vacuum energies near the natural (Planck) scale. The statistics, however, are assumed to be such that a few of these local minima (and not more) have a low enough vacuum energy and suitable other properties to support life. In the inflationary era, the "multiverse" made successive transitions between the available minima until arriving at our current state of low vacuum energy. String theory, however, also suggests that the absolute minimum of the effective potential is exactly supersymmetric. Questions then arise as to why the inflationary era did not end by a transition to one of these, when will the universe make the phase transition to the exactly supersymmetric ground state, and what will be the properties of this final state.

Enhanced ICP for the Registration of Large-Scale 3D Environment Models: An Experimental Study

PubMed Central

Han, Jianda; Yin, Peng; He, Yuqing; Gu, Feng

2016-01-01

One of the main applications of mobile robots is the large-scale perception of the outdoor environment. One of the main challenges of this application is fusing environmental data obtained by multiple robots, especially heterogeneous robots. This paper proposes an enhanced iterative closest point (ICP) method for the fast and accurate registration of 3D environmental models. First, a hierarchical searching scheme is combined with the octree-based ICP algorithm. Second, an early-warning mechanism is used to perceive the local minimum problem. Third, a heuristic escape scheme based on sampled potential transformation vectors is used to avoid local minima and achieve optimal registration. Experiments involving one unmanned aerial vehicle and one unmanned surface vehicle were conducted to verify the proposed technique. The experimental results were compared with those of normal ICP registration algorithms to demonstrate the superior performance of the proposed method. PMID:26891298

Cost effective simulation-based multiobjective optimization in the performance of an internal combustion engine

NASA Astrophysics Data System (ADS)

Aittokoski, Timo; Miettinen, Kaisa

2008-07-01

Solving real-life engineering problems can be difficult because they often have multiple conflicting objectives, the objective functions involved are highly nonlinear and they contain multiple local minima. Furthermore, function values are often produced via a time-consuming simulation process. These facts suggest the need for an automated optimization tool that is efficient (in terms of number of objective function evaluations) and capable of solving global and multiobjective optimization problems. In this article, the requirements on a general simulation-based optimization system are discussed and such a system is applied to optimize the performance of a two-stroke combustion engine. In the example of a simulation-based optimization problem, the dimensions and shape of the exhaust pipe of a two-stroke engine are altered, and values of three conflicting objective functions are optimized. These values are derived from power output characteristics of the engine. The optimization approach involves interactive multiobjective optimization and provides a convenient tool to balance between conflicting objectives and to find good solutions.

Comparison of polynomial approximations and artificial neural nets for response surfaces in engineering optimization

NASA Technical Reports Server (NTRS)

Carpenter, William C.

1991-01-01

Engineering optimization problems involve minimizing some function subject to constraints. In areas such as aircraft optimization, the constraint equations may be from numerous disciplines such as transfer of information between these disciplines and the optimization algorithm. They are also suited to problems which may require numerous re-optimizations such as in multi-objective function optimization or to problems where the design space contains numerous local minima, thus requiring repeated optimizations from different initial designs. Their use has been limited, however, by the fact that development of response surfaces randomly selected or preselected points in the design space. Thus, they have been thought to be inefficient compared to algorithms to the optimum solution. A development has taken place in the last several years which may effect the desirability of using response surfaces. It may be possible that artificial neural nets are more efficient in developing response surfaces than polynomial approximations which have been used in the past. This development is the concern of the work.

Best dispersal strategies in spatially heterogeneous environments: optimization of the principal eigenvalue for indefinite fractional Neumann problems.

PubMed

Pellacci, Benedetta; Verzini, Gianmaria

2018-05-01

We study the positive principal eigenvalue of a weighted problem associated with the Neumann spectral fractional Laplacian. This analysis is related to the investigation of the survival threshold in population dynamics. Our main result concerns the optimization of such threshold with respect to the fractional order [Formula: see text], the case [Formula: see text] corresponding to the standard Neumann Laplacian: when the habitat is not too fragmented, the principal positive eigenvalue can not have local minima for [Formula: see text]. As a consequence, the best strategy for survival is either following the diffusion with [Formula: see text] (i.e. Brownian diffusion), or with the lowest possible s (i.e. diffusion allowing long jumps), depending on the size of the domain. In addition, we show that analogous results hold for the standard fractional Laplacian in [Formula: see text], in periodic environments.

An opinion formation based binary optimization approach for feature selection

NASA Astrophysics Data System (ADS)

Hamedmoghadam, Homayoun; Jalili, Mahdi; Yu, Xinghuo

2018-02-01

This paper proposed a novel optimization method based on opinion formation in complex network systems. The proposed optimization technique mimics human-human interaction mechanism based on a mathematical model derived from social sciences. Our method encodes a subset of selected features to the opinion of an artificial agent and simulates the opinion formation process among a population of agents to solve the feature selection problem. The agents interact using an underlying interaction network structure and get into consensus in their opinions, while finding better solutions to the problem. A number of mechanisms are employed to avoid getting trapped in local minima. We compare the performance of the proposed method with a number of classical population-based optimization methods and a state-of-the-art opinion formation based method. Our experiments on a number of high dimensional datasets reveal outperformance of the proposed algorithm over others.

76 FR 77939 - Proposed Provision of Navigation Services for the Next Generation Air Transportation System...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-15

... navigation for en route through non-precision instrument approaches. GPS is an internationally accepted... Localizer Performance with Vertical guidance (LPV). These approaches are equivalent to Category I ILS, but... approach procedures with LPV or localizer performance (LP) non-precision lines of minima to all qualified...

Robust spike sorting of retinal ganglion cells tuned to spot stimuli.

PubMed

Ghahari, Alireza; Badea, Tudor C

2016-08-01

We propose an automatic spike sorting approach for the data recorded from a microelectrode array during visual stimulation of wild type retinas with tiled spot stimuli. The approach first detects individual spikes per electrode by their signature local minima. With the mixture probability distribution of the local minima estimated afterwards, it applies a minimum-squared-error clustering algorithm to sort the spikes into different clusters. A template waveform for each cluster per electrode is defined, and a number of reliability tests are performed on it and its corresponding spikes. Finally, a divisive hierarchical clustering algorithm is used to deal with the correlated templates per cluster type across all the electrodes. According to the measures of performance of the spike sorting approach, it is robust even in the cases of recordings with low signal-to-noise ratio.

Many-body optimization using an ab initio monte carlo method.

PubMed

Haubein, Ned C; McMillan, Scott A; Broadbelt, Linda J

2003-01-01

Advances in computing power have made it possible to study solvated molecules using ab initio quantum chemistry. Inclusion of discrete solvent molecules is required to determine geometric information about solute/solvent clusters. Monte Carlo methods are well suited to finding minima in many-body systems, and ab initio methods are applicable to the widest range of systems. A first principles Monte Carlo (FPMC) method was developed to find minima in many-body systems, and emphasis was placed on implementing moves that increase the likelihood of finding minimum energy structures. Partial optimization and molecular interchange moves aid in finding minima and overcome the incomplete sampling that is unavoidable when using ab initio methods. FPMC was validated by studying the boron trifluoride-water system, and then the method was used to examine the methyl carbenium ion in water to demonstrate its application to solvation problems.

'Extremotaxis': computing with a bacterial-inspired algorithm.

PubMed

Nicolau, Dan V; Burrage, Kevin; Nicolau, Dan V; Maini, Philip K

2008-01-01

We present a general-purpose optimization algorithm inspired by "run-and-tumble", the biased random walk chemotactic swimming strategy used by the bacterium Escherichia coli to locate regions of high nutrient concentration The method uses particles (corresponding to bacteria) that swim through the variable space (corresponding to the attractant concentration profile). By constantly performing temporal comparisons, the particles drift towards the minimum or maximum of the function of interest. We illustrate the use of our method with four examples. We also present a discrete version of the algorithm. The new algorithm is expected to be useful in combinatorial optimization problems involving many variables, where the functional landscape is apparently stochastic and has local minima, but preserves some derivative structure at intermediate scales.

[Interactions of DNA bases with individual water molecules. Molecular mechanics and quantum mechanics computation results vs. experimental data].

PubMed

Gonzalez, E; Lino, J; Deriabina, A; Herrera, J N F; Poltev, V I

2013-01-01

To elucidate details of the DNA-water interactions we performed the calculations and systemaitic search for minima of interaction energy of the systems consisting of one of DNA bases and one or two water molecules. The results of calculations using two force fields of molecular mechanics (MM) and correlated ab initio method MP2/6-31G(d, p) of quantum mechanics (QM) have been compared with one another and with experimental data. The calculations demonstrated a qualitative agreement between geometry characteristics of the most of local energy minima obtained via different methods. The deepest minima revealed by MM and QM methods correspond to water molecule position between two neighbor hydrophilic centers of the base and to the formation by water molecule of hydrogen bonds with them. Nevertheless, the relative depth of some minima and peculiarities of mutual water-base positions in' these minima depend on the method used. The analysis revealed insignificance of some differences in the results of calculations performed via different methods and the importance of other ones for the description of DNA hydration. The calculations via MM methods enable us to reproduce quantitatively all the experimental data on the enthalpies of complex formation of single water molecule with the set of mono-, di-, and trimethylated bases, as well as on water molecule locations near base hydrophilic atoms in the crystals of DNA duplex fragments, while some of these data cannot be rationalized by QM calculations.

Enhanced intelligent water drops algorithm for multi-depot vehicle routing problem

PubMed Central

Akutsah, Francis; Olusanya, Micheal O.; Adewumi, Aderemi O.

2018-01-01

The intelligent water drop algorithm is a swarm-based metaheuristic algorithm, inspired by the characteristics of water drops in the river and the environmental changes resulting from the action of the flowing river. Since its appearance as an alternative stochastic optimization method, the algorithm has found applications in solving a wide range of combinatorial and functional optimization problems. This paper presents an improved intelligent water drop algorithm for solving multi-depot vehicle routing problems. A simulated annealing algorithm was introduced into the proposed algorithm as a local search metaheuristic to prevent the intelligent water drop algorithm from getting trapped into local minima and also improve its solution quality. In addition, some of the potential problematic issues associated with using simulated annealing that include high computational runtime and exponential calculation of the probability of acceptance criteria, are investigated. The exponential calculation of the probability of acceptance criteria for the simulated annealing based techniques is computationally expensive. Therefore, in order to maximize the performance of the intelligent water drop algorithm using simulated annealing, a better way of calculating the probability of acceptance criteria is considered. The performance of the proposed hybrid algorithm is evaluated by using 33 standard test problems, with the results obtained compared with the solutions offered by four well-known techniques from the subject literature. Experimental results and statistical tests show that the new method possesses outstanding performance in terms of solution quality and runtime consumed. In addition, the proposed algorithm is suitable for solving large-scale problems. PMID:29554662

Enhanced intelligent water drops algorithm for multi-depot vehicle routing problem.

PubMed

Ezugwu, Absalom E; Akutsah, Francis; Olusanya, Micheal O; Adewumi, Aderemi O

2018-01-01

The intelligent water drop algorithm is a swarm-based metaheuristic algorithm, inspired by the characteristics of water drops in the river and the environmental changes resulting from the action of the flowing river. Since its appearance as an alternative stochastic optimization method, the algorithm has found applications in solving a wide range of combinatorial and functional optimization problems. This paper presents an improved intelligent water drop algorithm for solving multi-depot vehicle routing problems. A simulated annealing algorithm was introduced into the proposed algorithm as a local search metaheuristic to prevent the intelligent water drop algorithm from getting trapped into local minima and also improve its solution quality. In addition, some of the potential problematic issues associated with using simulated annealing that include high computational runtime and exponential calculation of the probability of acceptance criteria, are investigated. The exponential calculation of the probability of acceptance criteria for the simulated annealing based techniques is computationally expensive. Therefore, in order to maximize the performance of the intelligent water drop algorithm using simulated annealing, a better way of calculating the probability of acceptance criteria is considered. The performance of the proposed hybrid algorithm is evaluated by using 33 standard test problems, with the results obtained compared with the solutions offered by four well-known techniques from the subject literature. Experimental results and statistical tests show that the new method possesses outstanding performance in terms of solution quality and runtime consumed. In addition, the proposed algorithm is suitable for solving large-scale problems.

A Simple Label Switching Algorithm for Semisupervised Structural SVMs.

PubMed

Balamurugan, P; Shevade, Shirish; Sundararajan, S

2015-10-01

In structured output learning, obtaining labeled data for real-world applications is usually costly, while unlabeled examples are available in abundance. Semisupervised structured classification deals with a small number of labeled examples and a large number of unlabeled structured data. In this work, we consider semisupervised structural support vector machines with domain constraints. The optimization problem, which in general is not convex, contains the loss terms associated with the labeled and unlabeled examples, along with the domain constraints. We propose a simple optimization approach that alternates between solving a supervised learning problem and a constraint matching problem. Solving the constraint matching problem is difficult for structured prediction, and we propose an efficient and effective label switching method to solve it. The alternating optimization is carried out within a deterministic annealing framework, which helps in effective constraint matching and avoiding poor local minima, which are not very useful. The algorithm is simple and easy to implement. Further, it is suitable for any structured output learning problem where exact inference is available. Experiments on benchmark sequence labeling data sets and a natural language parsing data set show that the proposed approach, though simple, achieves comparable generalization performance.

Shape optimization techniques for musical instrument design

NASA Astrophysics Data System (ADS)

Henrique, Luis; Antunes, Jose; Carvalho, Joao S.

2002-11-01

The design of musical instruments is still mostly based on empirical knowledge and costly experimentation. One interesting improvement is the shape optimization of resonating components, given a number of constraints (allowed parameter ranges, shape smoothness, etc.), so that vibrations occur at specified modal frequencies. Each admissible geometrical configuration generates an error between computed eigenfrequencies and the target set. Typically, error surfaces present many local minima, corresponding to suboptimal designs. This difficulty can be overcome using global optimization techniques, such as simulated annealing. However these methods are greedy, concerning the number of function evaluations required. Thus, the computational effort can be unacceptable if complex problems, such as bell optimization, are tackled. Those issues are addressed in this paper, and a method for improving optimization procedures is proposed. Instead of using the local geometric parameters as searched variables, the system geometry is modeled in terms of truncated series of orthogonal space-funcitons, and optimization is performed on their amplitude coefficients. Fourier series and orthogonal polynomials are typical such functions. This technique reduces considerably the number of searched variables, and has a potential for significant computational savings in complex problems. It is illustrated by optimizing the shapes of both current and uncommon marimba bars.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodríguez-Cantano, Rocío; Pérez de Tudela, Ricardo; Bartolomei, Massimiliano

Coronene-doped helium clusters have been studied by means of classical and quantum mechanical (QM) methods using a recently developed He–C{sub 24}H{sub 12} global potential based on the use of optimized atom-bond improved Lennard-Jones functions. Equilibrium energies and geometries at global and local minima for systems with up to 69 He atoms were calculated by means of an evolutive algorithm and a basin-hopping approach and compared with results from path integral Monte Carlo (PIMC) calculations at 2 K. A detailed analysis performed for the smallest sizes shows that the precise localization of the He atoms forming the first solvation layer overmore » the molecular substrate is affected by differences between relative potential minima. The comparison of the PIMC results with the predictions from the classical approaches and with diffusion Monte Carlo results allows to examine the importance of both the QM and thermal effects.« less

Acceleration of the Particle Swarm Optimization for Peierls-Nabarro modeling of dislocations in conventional and high-entropy alloys

NASA Astrophysics Data System (ADS)

Pei, Zongrui; Eisenbach, Markus

2017-06-01

Dislocations are among the most important defects in determining the mechanical properties of both conventional alloys and high-entropy alloys. The Peierls-Nabarro model supplies an efficient pathway to their geometries and mobility. The difficulty in solving the integro-differential Peierls-Nabarro equation is how to effectively avoid the local minima in the energy landscape of a dislocation core. Among the other methods to optimize the dislocation core structures, we choose the algorithm of Particle Swarm Optimization, an algorithm that simulates the social behaviors of organisms. By employing more particles (bigger swarm) and more iterative steps (allowing them to explore for longer time), the local minima can be effectively avoided. But this would require more computational cost. The advantage of this algorithm is that it is readily parallelized in modern high computing architecture. We demonstrate the performance of our parallelized algorithm scales linearly with the number of employed cores.

Exploring conformational preferences of alanine tetrapeptide by CCSD(T), MP2, and dispersion-corrected DFT methods

NASA Astrophysics Data System (ADS)

Kang, Young Kee; Park, Hae Sook

2018-06-01

The 129 local minima of the alanine tetrapeptide with relative energy < 10 kcal/mol were identified at the ωB97X-D/6-311++G(d,p) level of theory from initial structures generated by combining nine local minima of each residue. The CCSD(T), MP2, and dispersion-corrected DFT levels of theory with various basis sets were assessed for relative energies of the 24 representative conformations. The best performance was obtained at the double-hybrid DSD-PBEP86-D3BJ/def2-QZVP level of theory with RMSD = 0.12 kcal/mol against the CCSD(T)/CBS-limit energies. The ωB97X-D/def2-QZVP and CAM-B3LYP-D3BJ/def2-QZVP levels of theory can be an alternative level of theory with marginal deviations for conformational study of peptides.

Accelerated Enveloping Distribution Sampling: Enabling Sampling of Multiple End States while Preserving Local Energy Minima.

PubMed

Perthold, Jan Walther; Oostenbrink, Chris

2018-05-17

Enveloping distribution sampling (EDS) is an efficient approach to calculate multiple free-energy differences from a single molecular dynamics (MD) simulation. However, the construction of an appropriate reference-state Hamiltonian that samples all states efficiently is not straightforward. We propose a novel approach for the construction of the EDS reference-state Hamiltonian, related to a previously described procedure to smoothen energy landscapes. In contrast to previously suggested EDS approaches, our reference-state Hamiltonian preserves local energy minima of the combined end-states. Moreover, we propose an intuitive, robust and efficient parameter optimization scheme to tune EDS Hamiltonian parameters. We demonstrate the proposed method with established and novel test systems and conclude that our approach allows for the automated calculation of multiple free-energy differences from a single simulation. Accelerated EDS promises to be a robust and user-friendly method to compute free-energy differences based on solid statistical mechanics.

Optical levitation of absorbing particles with a nominally Gaussian laser beam.

PubMed

Huisken, Jan; Stelzer, Ernst H K

2002-07-15

We use a Gaussian laser beam to study the levitation of absorbing Mie particles. Several metal oxide particles are stably levitated, and their movement over time is recorded. Our studies show that the position of each particle is highly dependent on the other particles' locations. The observations are explained by the phenomenon of thermal creep. The increased local pressure that is due to a temperature gradient along the particle's surface induces levitation. The particles rest close to minima in the intensity distribution near the optical axis. An experiment is suggested that can be used to locate these minima in a laser beam.

Simulated annealing two-point ray tracing

NASA Astrophysics Data System (ADS)

Velis, Danilo R.; Ulrych, Tadeusz J.

We present a new method for solving the two-point seismic ray tracing problem based on Fermat's principle. The algorithm overcomes some well known difficulties that arise in standard ray shooting and bending methods. Problems related to: (1) the selection of new take-off angles, and (2) local minima in multipathing cases, are overcome by using an efficient simulated annealing (SA) algorithm. At each iteration, the ray is propagated from the source by solving a standard initial value problem. The last portion of the raypath is then forced to pass through the receiver. Using SA, the total traveltime is then globally minimized by obtaining the initial conditions that produce the absolute minimum path. The procedure is suitable for tracing rays through 2D complex structures, although it can be extended to deal with 3D velocity media. Not only direct waves, but also reflected and head-waves can be incorporated in the scheme. One important advantage is its simplicity, in as much as any available or user-preferred initial value solver system can be used. A number of clarifying examples of multipathing in 2D media are examined.

Surface matching for correlation of virtual models: Theory and application

NASA Technical Reports Server (NTRS)

Caracciolo, Roberto; Fanton, Francesco; Gasparetto, Alessandro

1994-01-01

Virtual reality can enable a robot user to off line generate and test in a virtual environment a sequence of operations to be executed by the robot in an assembly cell. Virtual models of objects are to be correlated to the real entities they represent by means of a suitable transformation. A solution to the correlation problem, which is basically a problem of 3-dimensional adjusting, has been found exploiting the surface matching theory. An iterative algorithm has been developed, which matches the geometric surface representing the shape of the virtual model of an object, with a set of points measured on the surface in the real world. A peculiar feature of the algorithm is to work also if there is no one-to-one correspondence between the measured points and those representing the surface model. Furthermore the problem of avoiding convergence to local minima is solved, by defining a starting point of states ensuring convergence to the global minimum. The developed algorithm has been tested by simulation. Finally, this paper proposes a specific application, i.e., correlating a robot cell, equipped for biomedical use with its virtual representation.

Shape regularized active contour based on dynamic programming for anatomical structure segmentation

NASA Astrophysics Data System (ADS)

Yu, Tianli; Luo, Jiebo; Singhal, Amit; Ahuja, Narendra

2005-04-01

We present a method to incorporate nonlinear shape prior constraints into segmenting different anatomical structures in medical images. Kernel space density estimation (KSDE) is used to derive the nonlinear shape statistics and enable building a single model for a class of objects with nonlinearly varying shapes. The object contour is coerced by image-based energy into the correct shape sub-distribution (e.g., left or right lung), without the need for model selection. In contrast to an earlier algorithm that uses a local gradient-descent search (susceptible to local minima), we propose an algorithm that iterates between dynamic programming (DP) and shape regularization. DP is capable of finding an optimal contour in the search space that maximizes a cost function related to the difference between the interior and exterior of the object. To enforce the nonlinear shape prior, we propose two shape regularization methods, global and local regularization. Global regularization is applied after each DP search to move the entire shape vector in the shape space in a gradient descent fashion to the position of probable shapes learned from training. The regularized shape is used as the starting shape for the next iteration. Local regularization is accomplished through modifying the search space of the DP. The modified search space only allows a certain amount of deformation of the local shape from the starting shape. Both regularization methods ensure the consistency between the resulted shape with the training shapes, while still preserving DP"s ability to search over a large range and avoid local minima. Our algorithm was applied to two different segmentation tasks for radiographic images: lung field and clavicle segmentation. Both applications have shown that our method is effective and versatile in segmenting various anatomical structures under prior shape constraints; and it is robust to noise and local minima caused by clutter (e.g., blood vessels) and other similar structures (e.g., ribs). We believe that the proposed algorithm represents a major step in the paradigm shift to object segmentation under nonlinear shape constraints.

Optimal correction and design parameter search by modern methods of rigorous global optimization

NASA Astrophysics Data System (ADS)

Makino, K.; Berz, M.

2011-07-01

Frequently the design of schemes for correction of aberrations or the determination of possible operating ranges for beamlines and cells in synchrotrons exhibit multitudes of possibilities for their correction, usually appearing in disconnected regions of parameter space which cannot be directly qualified by analytical means. In such cases, frequently an abundance of optimization runs are carried out, each of which determines a local minimum depending on the specific chosen initial conditions. Practical solutions are then obtained through an often extended interplay of experienced manual adjustment of certain suitable parameters and local searches by varying other parameters. However, in a formal sense this problem can be viewed as a global optimization problem, i.e. the determination of all solutions within a certain range of parameters that lead to a specific optimum. For example, it may be of interest to find all possible settings of multiple quadrupoles that can achieve imaging; or to find ahead of time all possible settings that achieve a particular tune; or to find all possible manners to adjust nonlinear parameters to achieve correction of high order aberrations. These tasks can easily be phrased in terms of such an optimization problem; but while mathematically this formulation is often straightforward, it has been common belief that it is of limited practical value since the resulting optimization problem cannot usually be solved. However, recent significant advances in modern methods of rigorous global optimization make these methods feasible for optics design for the first time. The key ideas of the method lie in an interplay of rigorous local underestimators of the objective functions, and by using the underestimators to rigorously iteratively eliminate regions that lie above already known upper bounds of the minima, in what is commonly known as a branch-and-bound approach. Recent enhancements of the Differential Algebraic methods used in particle optics for the computation of aberrations allow the determination of particularly sharp underestimators for large regions. As a consequence, the subsequent progressive pruning of the allowed search space as part of the optimization progresses is carried out particularly effectively. The end result is the rigorous determination of the single or multiple optimal solutions of the parameter optimization, regardless of their location, their number, and the starting values of optimization. The methods are particularly powerful if executed in interplay with genetic optimizers generating their new populations within the currently active unpruned space. Their current best guess provides rigorous upper bounds of the minima, which can then beneficially be used for better pruning. Examples of the method and its performance will be presented, including the determination of all operating points of desired tunes or chromaticities, etc. in storage ring lattices.

Computationally efficient characterization of potential energy surfaces based on fingerprint distances

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schaefer, Bastian; Goedecker, Stefan, E-mail: stefan.goedecker@unibas.ch

2016-07-21

An analysis of the network defined by the potential energy minima of multi-atomic systems and their connectivity via reaction pathways that go through transition states allows us to understand important characteristics like thermodynamic, dynamic, and structural properties. Unfortunately computing the transition states and reaction pathways in addition to the significant energetically low-lying local minima is a computationally demanding task. We here introduce a computationally efficient method that is based on a combination of the minima hopping global optimization method and the insight that uphill barriers tend to increase with increasing structural distances of the educt and product states. This methodmore » allows us to replace the exact connectivity information and transition state energies with alternative and approximate concepts. Without adding any significant additional cost to the minima hopping global optimization approach, this method allows us to generate an approximate network of the minima, their connectivity, and a rough measure for the energy needed for their interconversion. This can be used to obtain a first qualitative idea on important physical and chemical properties by means of a disconnectivity graph analysis. Besides the physical insight obtained by such an analysis, the gained knowledge can be used to make a decision if it is worthwhile or not to invest computational resources for an exact computation of the transition states and the reaction pathways. Furthermore it is demonstrated that the here presented method can be used for finding physically reasonable interconversion pathways that are promising input pathways for methods like transition path sampling or discrete path sampling.« less

Navigation of autonomous vehicles for oil spill cleaning in dynamic and uncertain environments

NASA Astrophysics Data System (ADS)

Jin, Xin; Ray, Asok

2014-04-01

In the context of oil spill cleaning by autonomous vehicles in dynamic and uncertain environments, this paper presents a multi-resolution algorithm that seamlessly integrates the concepts of local navigation and global navigation based on the sensory information; the objective here is to enable adaptive decision making and online replanning of vehicle paths. The proposed algorithm provides a complete coverage of the search area for clean-up of the oil spills and does not suffer from the problem of having local minima, which is commonly encountered in potential-field-based methods. The efficacy of the algorithm is tested on a high-fidelity player/stage simulator for oil spill cleaning in a harbour, where the underlying oil weathering process is modelled as 2D random-walk particle tracking. A preliminary version of this paper was presented by X. Jin and A. Ray as 'Coverage Control of Autonomous Vehicles for Oil Spill Cleaning in Dynamic and Uncertain Environments', Proceedings of the American Control Conference, Washington, DC, June 2013, pp. 2600-2605.

Combining pressure and temperature control in dynamics on energy landscapes

NASA Astrophysics Data System (ADS)

Hoffmann, Karl Heinz; Christian Schön, J.

2017-05-01

Complex systems from science, technology or mathematics usually appear to be very different in their specific dynamical evolution. However, the concept of an energy landscape with its basins corresponding to locally ergodic regions separated by energy barriers provides a unifying approach to the description of complex systems dynamics. In such systems one is often confronted with the task to control the dynamics such that a certain basin is reached with the highest possible probability. Typically one aims for the global minimum, e.g. when dealing with global optimization problems, but frequently other local minima such as the metastable compounds in materials science are of primary interest. Here we show how this task can be solved by applying control theory using magnesium fluoride as an example system, where different modifications of MgF2 are considered as targets. In particular, we generalize previous work restricted to temperature controls only and present controls which simultaneously adjust temperature and pressure in an optimal fashion.

Minima de L'intégrale D'action du Problème Newtoniende 4 Corps de Masses Égales Dans R3: Orbites `Hip-Hop'

NASA Astrophysics Data System (ADS)

Chenciner, Alain; Venturelli, Andrea

2000-09-01

We consider the problem of 4 bodies of equal masses in R 3 for the Newtonian r-1 potential. We address the question of the absolute minima of the action integral among (anti)symmetric loops of class H 1 whose period is fixed. It is the simplest case for which the results of [4] (corrected in [5]) do not apply: the minima cannot be the relative equilibria whose configuration is an absolute minimum of the potential among the configurations having a given moment of inertia with respect to their center of mass. This is because the regular tetrahedron cannot have a relative equilibrium motion in R 3 (see [2]). We show that the absolute minima of the action are not homographic motions. We also show that if we force the configuration to admit a certain type of symmetry of order 4, the absolute minimum is a collisionless orbit whose configuration ‘hesitates’ between the central configuration of the square and the one of the tetrahedron. We call these orbits ‘hip-hop’. A similar result holds in case of a symmetry of order 3 where the central configuration of the equilateral triangle with a body at the center of mass replaces the square.

Automated parameterization of intermolecular pair potentials using global optimization techniques

NASA Astrophysics Data System (ADS)

Krämer, Andreas; Hülsmann, Marco; Köddermann, Thorsten; Reith, Dirk

2014-12-01

In this work, different global optimization techniques are assessed for the automated development of molecular force fields, as used in molecular dynamics and Monte Carlo simulations. The quest of finding suitable force field parameters is treated as a mathematical minimization problem. Intricate problem characteristics such as extremely costly and even abortive simulations, noisy simulation results, and especially multiple local minima naturally lead to the use of sophisticated global optimization algorithms. Five diverse algorithms (pure random search, recursive random search, CMA-ES, differential evolution, and taboo search) are compared to our own tailor-made solution named CoSMoS. CoSMoS is an automated workflow. It models the parameters' influence on the simulation observables to detect a globally optimal set of parameters. It is shown how and why this approach is superior to other algorithms. Applied to suitable test functions and simulations for phosgene, CoSMoS effectively reduces the number of required simulations and real time for the optimization task.

Multistrategy Self-Organizing Map Learning for Classification Problems

PubMed Central

Hasan, S.; Shamsuddin, S. M.

2011-01-01

Multistrategy Learning of Self-Organizing Map (SOM) and Particle Swarm Optimization (PSO) is commonly implemented in clustering domain due to its capabilities in handling complex data characteristics. However, some of these multistrategy learning architectures have weaknesses such as slow convergence time always being trapped in the local minima. This paper proposes multistrategy learning of SOM lattice structure with Particle Swarm Optimisation which is called ESOMPSO for solving various classification problems. The enhancement of SOM lattice structure is implemented by introducing a new hexagon formulation for better mapping quality in data classification and labeling. The weights of the enhanced SOM are optimised using PSO to obtain better output quality. The proposed method has been tested on various standard datasets with substantial comparisons with existing SOM network and various distance measurement. The results show that our proposed method yields a promising result with better average accuracy and quantisation errors compared to the other methods as well as convincing significant test. PMID:21876686

SfM with MRFs: discrete-continuous optimization for large-scale structure from motion.

PubMed

Crandall, David J; Owens, Andrew; Snavely, Noah; Huttenlocher, Daniel P

2013-12-01

Recent work in structure from motion (SfM) has built 3D models from large collections of images downloaded from the Internet. Many approaches to this problem use incremental algorithms that solve progressively larger bundle adjustment problems. These incremental techniques scale poorly as the image collection grows, and can suffer from drift or local minima. We present an alternative framework for SfM based on finding a coarse initial solution using hybrid discrete-continuous optimization and then improving that solution using bundle adjustment. The initial optimization step uses a discrete Markov random field (MRF) formulation, coupled with a continuous Levenberg-Marquardt refinement. The formulation naturally incorporates various sources of information about both the cameras and points, including noisy geotags and vanishing point (VP) estimates. We test our method on several large-scale photo collections, including one with measured camera positions, and show that it produces models that are similar to or better than those produced by incremental bundle adjustment, but more robustly and in a fraction of the time.

Cryogenic Tank Structure Sizing With Structural Optimization Method

NASA Technical Reports Server (NTRS)

Wang, J. T.; Johnson, T. F.; Sleight, D. W.; Saether, E.

2001-01-01

Structural optimization methods in MSC /NASTRAN are used to size substructures and to reduce the weight of a composite sandwich cryogenic tank for future launch vehicles. Because the feasible design space of this problem is non-convex, many local minima are found. This non-convex problem is investigated in detail by conducting a series of analyses along a design line connecting two feasible designs. Strain constraint violations occur for some design points along the design line. Since MSC/NASTRAN uses gradient-based optimization procedures. it does not guarantee that the lowest weight design can be found. In this study, a simple procedure is introduced to create a new starting point based on design variable values from previous optimization analyses. Optimization analysis using this new starting point can produce a lower weight design. Detailed inputs for setting up the MSC/NASTRAN optimization analysis and final tank design results are presented in this paper. Approaches for obtaining further weight reductions are also discussed.

Synthesizing optimal waste blends

DOE Office of Scientific and Technical Information (OSTI.GOV)

Narayan, V.; Diwekar, W.M.; Hoza, M.

Vitrification of tank wastes to form glass is a technique that will be used for the disposal of high-level waste at Hanford. Process and storage economics show that minimizing the total number of glass logs produced is the key to keeping cost as low as possible. The amount of glass produced can be reduced by blending of the wastes. The optimal way to combine the tanks to minimize the vole of glass can be determined from a discrete blend calculation. However, this problem results in a combinatorial explosion as the number of tanks increases. Moreover, the property constraints make thismore » problem highly nonconvex where many algorithms get trapped in local minima. In this paper the authors examine the use of different combinatorial optimization approaches to solve this problem. A two-stage approach using a combination of simulated annealing and nonlinear programming (NLP) is developed. The results of different methods such as the heuristics approach based on human knowledge and judgment, the mixed integer nonlinear programming (MINLP) approach with GAMS, and branch and bound with lower bound derived from the structure of the given blending problem are compared with this coupled simulated annealing and NLP approach.« less

Einstein-Podolsky-Rosen-like separability indicators for two-mode Gaussian states

NASA Astrophysics Data System (ADS)

Marian, Paulina; Marian, Tudor A.

2018-02-01

We investigate the separability of the two-mode Gaussian states (TMGSs) by using the variances of a pair of Einstein-Podolsky-Rosen (EPR)-like observables. Our starting point is inspired by the general necessary condition of separability introduced by Duan et al (2000 Phys. Rev. Lett. 84 2722). We evaluate the minima of the normalized forms of both the product and sum of such variances, as well as that of a regularized sum. Making use of Simon’s separability criterion, which is based on the condition of positivity of the partial transpose (PPT) of the density matrix (Simon 2000 Phys. Rev. Lett. 84 2726), we prove that these minima are separability indicators in their own right. They appear to quantify the greatest amount of EPR-like correlations that can be created in a TMGS by means of local operations. Furthermore, we reconsider the EPR-like approach to the separability of TMGSs which was developed by Duan et al with no reference to the PPT condition. By optimizing the regularized form of their EPR-like uncertainty sum, we derive a separability indicator for any TMGS. We prove that the corresponding EPR-like condition of separability is manifestly equivalent to Simon’s PPT one. The consistency of these two distinct approaches (EPR-like and PPT) affords a better understanding of the examined separability problem, whose explicit solution found long ago by Simon covers all situations of interest.

Ultra-wideband electronics, design methods, algorithms, and systems for dielectric spectroscopy of isolated B16 tumor cells in liquid medium

NASA Astrophysics Data System (ADS)

Maxwell, Erick N.

Quantifying and characterizing isolated tumor cells (ITCs) is of interest in surgical pathology and cytology for its potential to provide data for cancer staging, classification, and treatment. Although the independent prognostic significance of circulating ITCs has not been proven, their presence is gaining clinical relevance as an indicator. However, researchers have not established an optimal method for detecting ITCs. Consequently, this Ph.D. dissertation is concerned with the development and evaluation of dielectric spectroscopy as a low-cost method for cell characterization and quantification. In support of this goal, ultra-wideband (UWB), microwave pulse generator circuits, coaxial transmission line fixtures, permittivity extraction algorithms, and dielectric spectroscopy measurement systems were developed for evaluating the capacity to quantify B16-F10 tumor cells in suspension. First, this research addressed challenges in developing tunable UWB circuits for pulse generation. In time-domain dielectric spectroscopy, a tunable UWB pulse generator facilitates exploration of microscopic dielectric mechanisms, which contribute to dispersion characteristics. Conventional approaches to tunable pulse generator design have resulted in complex circuit topologies and unsymmetrical waveform morphologies. In this research, a new design approach for low-complexity, tunable, sub-nanosecond and UWB pulse generator was developed. This approach was applied to the development of a novel generator that produces symmetrical waveforms (patent pending 60/597,746). Next, this research addressed problems with transmission-reflection (T/R) measurement of cell suspensions. In T/R measurement, coaxial transmission line fixtures have historically required an elaborate sample holder for containing liquids, resulting in high cost and complexity. Furthermore, the algorithms used to extract T/R dielectric properties have suffered from myriad problems including local minima and halfwavelength resonance. In this dissertation, a simple coaxial transmission line fixture for holding liquids by dispensing with the air-core assumption inherent in previous designs was developed (patent pending 60/916,042). In addition, a genetic algorithm was applied towards extracting dielectric properties from measurement data to circumvent problems of local minima and half wavelength resonance. Finally, in this research the capacity for using dielectric properties to quantify isolated B16-F10 tumor cells in McCoy's liquid medium was investigated. In so doing, the utility of the Maxwell-Wagner mixture formula for cell quantification was demonstrated by measuring distinct dielectric properties for differing volumes of cell suspensions using frequency- and time-domain dielectric spectroscopy.

Augmenting Photoinduced Charge Transport in a Single-Component Gel System: Controlled In Situ Gel-Crystal Transformation at Room Temperature.

PubMed

Satapathy, Sitakanta; Prabakaran, Palani; Prasad, Edamana

2018-04-20

Smart single-component materials with versatile functions require pre-programming of a higher order molecular assembly. An electroactive supergelator (c=0.07 wt %) triphenylamine core-appended poly(aryl ether) dendron (TPAPAE) is described, where substantial dendritic effects improve the order and crystallinity by switching the local minima from self-assembled molecular wires to thermodynamically favorable global minima of ordered crystals, ripened within the fibers. Controlled in situ phase change at room temperature ultimately stabilized the mixed valence states in the single-component supramolecular assembly with photoluminescence and photoinduced charge transport amplified by two orders of magnitude. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Learning Extrema Problems Using a Non-Differential Approach in a Digital Dynamic Environment: The Case of High-Track yet Low-Achievers

ERIC Educational Resources Information Center

Dvir, Assaf; Tabach, Michal

2017-01-01

High schools commonly use a differential approach to teach minima and maxima geometric problems. Although calculus serves as a systematic and powerful technique, this rigorous instrument might hinder students' ability to understand the behavior and constraints of the objective function. The proliferation of digital environments allowed us to adopt…

Conservatism of lizard thermal tolerances and body temperatures across evolutionary history and geography.

PubMed

Grigg, Joseph W; Buckley, Lauren B

2013-04-23

Species may exhibit similar thermal tolerances via either common ancestry or environmental filtering and local adaptation, if the species inhabit similar environments. We ask whether upper and lower thermal limits (critical thermal maxima and minima) and body temperatures are more strongly conserved across evolutionary history or geography for lizard populations distributed globally. We find that critical thermal maxima are highly conserved with location accounting for a higher proportion of the variation than phylogeny. Notably, thermal tolerance breadth is conserved across the phylogeny despite critical thermal minima showing little niche conservatism. Body temperatures observed during activity in the field show the greatest degree of conservatism, with phylogeny accounting for most of the variation. This suggests that propensities for thermoregulatory behaviour, which can buffer body temperatures from environmental variation, are similar within lineages. Phylogeny and geography constrain thermal tolerances similarly within continents, but variably within clades. Conservatism of thermal tolerances across lineages suggests that the potential for local adaptation to alleviate the impacts of climate change on lizards may be limited.

Dense colloidal mixtures in an external sinusoidal potential

NASA Astrophysics Data System (ADS)

Capellmann, R. F.; Khisameeva, A.; Platten, F.; Egelhaaf, S. U.

2018-03-01

Concentrated binary colloidal mixtures containing particles with a size ratio 1:2.4 were exposed to a periodic potential that was realized using a light field, namely, two crossed laser beams creating a fringe pattern. The arrangement of the particles was recorded using optical microscopy and characterized in terms of the pair distribution function along the minima, the occupation probability perpendicular to the minima, the angular bond distribution, and the average potential energy per particle. The particle arrangement was investigated in dependence of the importance of particle-potential and particle-particle interactions by changing the potential amplitude and particle concentration, respectively. An increase in the potential amplitude leads to a stronger localization, especially of the large particles, but also results in an increasing fraction of small particles being located closer to the potential maxima, which also occurs upon increasing the particle density. Furthermore, increasing the potential amplitude induces a local demixing of the two particle species, whereas an increase in the total packing fraction favors a more homogeneous arrangement.

Acceleration of the Particle Swarm Optimization for Peierls–Nabarro modeling of dislocations in conventional and high-entropy alloys

DOE PAGES

Pei, Zongrui; Max-Planck-Inst. fur Eisenforschung, Duseldorf; Eisenbach, Markus

2017-02-06

Dislocations are among the most important defects in determining the mechanical properties of both conventional alloys and high-entropy alloys. The Peierls-Nabarro model supplies an efficient pathway to their geometries and mobility. The difficulty in solving the integro-differential Peierls-Nabarro equation is how to effectively avoid the local minima in the energy landscape of a dislocation core. Among the other methods to optimize the dislocation core structures, we choose the algorithm of Particle Swarm Optimization, an algorithm that simulates the social behaviors of organisms. By employing more particles (bigger swarm) and more iterative steps (allowing them to explore for longer time), themore » local minima can be effectively avoided. But this would require more computational cost. The advantage of this algorithm is that it is readily parallelized in modern high computing architecture. We demonstrate the performance of our parallelized algorithm scales linearly with the number of employed cores.« less

Detection of pulmonary nodules in CT images based on fuzzy integrated active contour model and hybrid parametric mixture model.

PubMed

Li, Bin; Chen, Kan; Tian, Lianfang; Yeboah, Yao; Ou, Shanxing

2013-01-01

The segmentation and detection of various types of nodules in a Computer-aided detection (CAD) system present various challenges, especially when (1) the nodule is connected to a vessel and they have very similar intensities; (2) the nodule with ground-glass opacity (GGO) characteristic possesses typical weak edges and intensity inhomogeneity, and hence it is difficult to define the boundaries. Traditional segmentation methods may cause problems of boundary leakage and "weak" local minima. This paper deals with the above mentioned problems. An improved detection method which combines a fuzzy integrated active contour model (FIACM)-based segmentation method, a segmentation refinement method based on Parametric Mixture Model (PMM) of juxta-vascular nodules, and a knowledge-based C-SVM (Cost-sensitive Support Vector Machines) classifier, is proposed for detecting various types of pulmonary nodules in computerized tomography (CT) images. Our approach has several novel aspects: (1) In the proposed FIACM model, edge and local region information is incorporated. The fuzzy energy is used as the motivation power for the evolution of the active contour. (2) A hybrid PMM Model of juxta-vascular nodules combining appearance and geometric information is constructed for segmentation refinement of juxta-vascular nodules. Experimental results of detection for pulmonary nodules show desirable performances of the proposed method.

Recovery of the parameters of cancellous bone by inversion of effective velocities, and transmission and reflection coefficients

NASA Astrophysics Data System (ADS)

Buchanan, James L.; Gilbert, Robert P.; Ou, Miao-jung Y.

2011-12-01

Estimating the parameters of an elastic or poroelastic medium from reflected or transmitted acoustic data is an important but difficult problem. Use of the Nelder-Mead simplex method to minimize an objective function measuring the discrepancy between some observable and its value calculated from a model for a trial set of parameters has been tried by several authors. In this paper, the difficulty with this direct approach, which is the existence of numerous local minima of the objective function, is documented for the in vitro experiment in which a specimen in a water tank is subject to an ultrasonic pulse. An indirect approach, based on the numerical solution of the equations for a set of ‘effective’ velocities and transmission coefficients, is then observed empirically to ameliorate the difficulties posed by the direct approach.

Range image registration based on hash map and moth-flame optimization

NASA Astrophysics Data System (ADS)

Zou, Li; Ge, Baozhen; Chen, Lei

2018-03-01

Over the past decade, evolutionary algorithms (EAs) have been introduced to solve range image registration problems because of their robustness and high precision. However, EA-based range image registration algorithms are time-consuming. To reduce the computational time, an EA-based range image registration algorithm using hash map and moth-flame optimization is proposed. In this registration algorithm, a hash map is used to avoid over-exploitation in registration process. Additionally, we present a search equation that is better at exploration and a restart mechanism to avoid being trapped in local minima. We compare the proposed registration algorithm with the registration algorithms using moth-flame optimization and several state-of-the-art EA-based registration algorithms. The experimental results show that the proposed algorithm has a lower computational cost than other algorithms and achieves similar registration precision.

The role of molecular structure of sugar-phosphate backbone and nucleic acid bases in the formation of single-stranded and double-stranded DNA structures.

PubMed

Poltev, Valeri; Anisimov, Victor M; Danilov, Victor I; Garcia, Dolores; Sanchez, Carolina; Deriabina, Alexandra; Gonzalez, Eduardo; Rivas, Francisco; Polteva, Nina

2014-06-01

Our previous DFT computations of deoxydinucleoside monophosphate complexes with Na(+)-ions (dDMPs) have demonstrated that the main characteristics of Watson-Crick (WC) right-handed duplex families are predefined in the local energy minima of dDMPs. In this work, we study the mechanisms of contribution of chemically monotonous sugar-phosphate backbone and the bases into the double helix irregularity. Geometry optimization of sugar-phosphate backbone produces energy minima matching the WC DNA conformations. Studying the conformational variability of dDMPs in response to sequence permutation, we found that simple replacement of bases in the previously fully optimized dDMPs, e.g. by constructing Pyr-Pur from Pur-Pyr, and Pur-Pyr from Pyr-Pur sequences, while retaining the backbone geometry, automatically produces the mutual base position characteristic of the target sequence. Based on that, we infer that the directionality and the preferable regions of the sugar-phosphate torsions, combined with the difference of purines from pyrimidines in ring shape, determines the sequence dependence of the structure of WC DNA. No such sequence dependence exists in dDMPs corresponding to other DNA conformations (e.g., Z-family and Hoogsteen duplexes). Unlike other duplexes, WC helix is unique by its ability to match the local energy minima of the free single strand to the preferable conformations of the duplex. Copyright © 2013 Wiley Periodicals, Inc.

Autonomous Modelling of X-ray Spectra Using Robust Global Optimization Methods

NASA Astrophysics Data System (ADS)

Rogers, Adam; Safi-Harb, Samar; Fiege, Jason

2015-08-01

The standard approach to model fitting in X-ray astronomy is by means of local optimization methods. However, these local optimizers suffer from a number of problems, such as a tendency for the fit parameters to become trapped in local minima, and can require an involved process of detailed user intervention to guide them through the optimization process. In this work we introduce a general GUI-driven global optimization method for fitting models to X-ray data, written in MATLAB, which searches for optimal models with minimal user interaction. We directly interface with the commonly used XSPEC libraries to access the full complement of pre-existing spectral models that describe a wide range of physics appropriate for modelling astrophysical sources, including supernova remnants and compact objects. Our algorithm is powered by the Ferret genetic algorithm and Locust particle swarm optimizer from the Qubist Global Optimization Toolbox, which are robust at finding families of solutions and identifying degeneracies. This technique will be particularly instrumental for multi-parameter models and high-fidelity data. In this presentation, we provide details of the code and use our techniques to analyze X-ray data obtained from a variety of astrophysical sources.

Cross-flow vortex structure and transition measurements using multi-element hot films

NASA Technical Reports Server (NTRS)

Agarwal, Naval K.; Mangalam, Siva M.; Maddalon, Dal V.; Collier, Fayette S., Jr.

1991-01-01

An experiment on a 45-degree swept wing was conducted to study three-dimensional boundary-layer characteristics using surface-mounted, micro-thin, multi-element hot-film sensors. Cross-flow vortex structure and boundary-layer transition were measured from the simultaneously acquired signals of the hot films. Spanwise variation of the root-mean-square (RMS) hot-film signal show a local minima and maxima. The distance between two minima corresponds to the stationary cross-flow vortex wavelength and agrees with naphthalene flow-visualization results. The chordwise and spanwise variation of amplified traveling (nonstationary) cross-flow disturbance characteristics were measured as Reynolds number was varied. The frequency of the most amplified cross-flow disturbances agrees with linear stability theory.

A comparative analysis of numerical approaches to the mechanics of elastic sheets

NASA Astrophysics Data System (ADS)

Taylor, Michael; Davidovitch, Benny; Qiu, Zhanlong; Bertoldi, Katia

2015-06-01

Numerically simulating deformations in thin elastic sheets is a challenging problem in computational mechanics due to destabilizing compressive stresses that result in wrinkling. Determining the location, structure, and evolution of wrinkles in these problems has important implications in design and is an area of increasing interest in the fields of physics and engineering. In this work, several numerical approaches previously proposed to model equilibrium deformations in thin elastic sheets are compared. These include standard finite element-based static post-buckling approaches as well as a recently proposed method based on dynamic relaxation, which are applied to the problem of an annular sheet with opposed tractions where wrinkling is a key feature. Numerical solutions are compared to analytic predictions of the ground state, enabling a quantitative evaluation of the predictive power of the various methods. Results indicate that static finite element approaches produce local minima that are highly sensitive to initial imperfections, relying on a priori knowledge of the equilibrium wrinkling pattern to generate optimal results. In contrast, dynamic relaxation is much less sensitive to initial imperfections and can generate low-energy solutions for a wide variety of loading conditions without requiring knowledge of the equilibrium solution beforehand.

TMI Rain Rate Estimation Over Land and Ocean Utilizing Convective and Stratiform Discrimination

NASA Technical Reports Server (NTRS)

Prabhakara, C.; Iacovazzi, R., Jr.; Weinman, J. A.; Dalu, G.

1999-01-01

Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometer brightness temperature data in the 85 GHz channel (T85) reveal distinct local minima in a regional map containing a Mesoscale Convective System (MCS). This is because of relatively small footprint size (approximately 5.5 km) and strong extinction properties in this channel of the TMI. A map of rain rate for that region, deduced from simultaneous measurements made by the Precipitation Radar (PR) on board the TRMM satellite, reveals that these T85 minima, produced by scattering, correspond to local PR rain maxima. Utilizing the PR rain rate map as a guide, we infer from TMI data the presence of three different kinds of thunderstorms or Cbs. They are young, mature, and decaying Cbs that have a scale of about 20 km on the average. Two parameters enable us to infer these three kinds of Cbs objectively: a) the magnitude of scattering depression deduced from local T85 minima and b) the mean horizontal gradient of T85 around such minima. Knowing the category of a given Cb, we can estimate the rain rate associated with it. Such estimation is done with the help of relationships linking T85 minimum to rain rate in each Cb type. Similarly, a weak background rain rate in all the areas where T85 is less than 260 K is deduced with another relationship linking T85 to rain rate. In our rain retrieval model, this background rain constitutes the stratiform rain where the Cbs are absent. Initially, these relationships are optimized or tuned utilizing the PR and TMI data of a few MCS events. After such tuning, the model is applied to independent MCS cases. The areal distribution of light (1-10 mm/hr), moderate (10-20 mm/hr), and intense (> 20 mm/hr) rain rates are retrieved satisfactorally. Accuracy in the estimates of the light, moderate and intense rain areas and the mean rain rates associated with such areas in these independent MCS cases is on the average about 15%. Taking advantage of this ability of our retrieval method, one could derive the latent heat input into the atmosphere over the 760 km wide swath of the TMI radiometer in the tropics.

[Automated processing of electrophysiologic signals].

PubMed

Korenevskiĭ, N A; Gubanov, V V

1995-01-01

The paper outlines a diagram of a multichannel analyzer of electrophysiological signals while are significantly non-stationary (such as those of electroencephalograms, myograms, etc.), by using a method based on the ranging procedure by the change-over points which may be the points of infection, impaired locality, minima, maxima, discontinuity, etc.

Non-ambiguous recovery of Biot poroelastic parameters of cellular panels using ultrasonicwaves

NASA Astrophysics Data System (ADS)

Ogam, Erick; Fellah, Z. E. A.; Sebaa, Naima; Groby, J.-P.

2011-03-01

The inverse problem of the recovery of the poroelastic parameters of open-cell soft plastic foam panels is solved by employing transmitted ultrasonic waves (USW) and the Biot-Johnson-Koplik-Champoux-Allard (BJKCA) model. It is shown by constructing the objective functional given by the total square of the difference between predictions from the BJKCA interaction model and experimental data obtained with transmitted USW that the inverse problem is ill-posed, since the functional exhibits several local minima and maxima. In order to solve this problem, which is beyond the capability of most off-the-shelf iterative nonlinear least squares optimization algorithms (such as the Levenberg Marquadt or Nelder-Mead simplex methods), simple strategies are developed. The recovered acoustic parameters are compared with those obtained using simpler interaction models and a method employing asymptotic phase velocity of the transmitted USW. The retrieved elastic moduli are validated by solving an inverse vibration spectroscopy problem with data obtained from beam-like specimens cut from the panels using an equivalent solid elastodynamic model as estimator. The phase velocities are reconstructed using computed, measured resonance frequencies and a time-frequency decomposition of transient waves induced in the beam specimen. These confirm that the elastic parameters recovered using vibration are valid over the frequency range ofstudy.

Computational study of the rovibrational spectrum of CO₂-CS₂.

PubMed

Brown, James; Wang, Xiao-Gang; Carrington, Tucker; Grubbs, G S; Dawes, Richard

2014-03-21

A new intermolecular potential energy surface, rovibrational transition frequencies, and line strengths are computed for CO2-CS2. The potential is made by fitting energies obtained from explicitly correlated coupled-cluster calculations using an interpolating moving least squares method. The rovibrational Schrödinger equation is solved with a symmetry-adapted Lanczos algorithm and an uncoupled product basis set. All four intermolecular coordinates are included in the calculation. In agreement with previous experiments, the global minimum of the potential energy surface (PES) is cross shaped. The PES also has slipped-parallel minima. Rovibrational wavefunctions are localized in the cross minima and the slipped-parallel minima. Vibrational parent analysis was used to assign vibrational labels to rovibrational states. Tunneling occurs between the two cross minima. Because more than one symmetry operation interconverts the two wells, the symmetry (-oo) of the upper component of the tunneling doublet is different from the symmetry (-ee) of the tunneling coordinate. This unusual situation is due to the multidimensional nature of the double well tunneling. For the cross ground vibrational state, calculated rotational constants differ from their experimental counterparts by less than 0.0001 cm(-1). Most rovibrational states were found to be incompatible with the standard effective rotational Hamiltonian often used to fit spectra. This appears to be due to coupling between internal and overall rotation of the dimer. A simple 2D model accounting for internal rotation was used for two cross-shaped fundamentals to obtain good fits.

[Supercomputer investigation of the protein-ligand system low-energy minima].

PubMed

Oferkin, I V; Sulimov, A V; Katkova, E V; Kutov, D K; Grigoriev, F V; Kondakova, O A; Sulimov, V B

2015-01-01

The accuracy of the protein-ligand binding energy calculations and ligand positioning is strongly influenced by the choice of the docking target function. This work demonstrates the evaluation of the five different target functions used in docking: functions based on MMFF94 force field and functions based on PM7 quantum-chemical method accounting or without accounting the implicit solvent model (PCM, COSMO or SGB). For these purposes the ligand positions corresponding to the minima of the target function and the experimentally known ligand positions in the protein active site (crystal ligand positions) were compared. Each function was examined on the same test-set of 16 protein-ligand complexes. The new parallelized docking program FLM based on Monte Carlo search algorithm was developed to perform the comprehensive low-energy minima search and to calculate the protein-ligand binding energy. This study demonstrates that the docking target function based on the MMFF94 force field can be used to detect the crystal or near crystal positions of the ligand by the finding the low-energy local minima spectrum of the target function. The importance of solvent accounting in the docking process for the accurate ligand positioning is also shown. The accuracy of the ligand positioning as well as the correlation between the calculated and experimentally determined protein-ligand binding energies are improved when the MMFF94 force field is substituted by the new PM7 method with implicit solvent accounting.

Software for Fermat's Principle and Lenses

ERIC Educational Resources Information Center

Mihas, Pavlos

2012-01-01

Fermat's principle is considered as a unifying concept. It is usually presented erroneously as a "least time principle". In this paper we present some software that shows cases of maxima and minima and the application of Fermat's principle to the problem of focusing in lenses. (Contains 12 figures.)

Machine learning prediction for classification of outcomes in local minimisation

NASA Astrophysics Data System (ADS)

Das, Ritankar; Wales, David J.

2017-01-01

Machine learning schemes are employed to predict which local minimum will result from local energy minimisation of random starting configurations for a triatomic cluster. The input data consists of structural information at one or more of the configurations in optimisation sequences that converge to one of four distinct local minima. The ability to make reliable predictions, in terms of the energy or other properties of interest, could save significant computational resources in sampling procedures that involve systematic geometry optimisation. Results are compared for two energy minimisation schemes, and for neural network and quadratic functions of the inputs.

The q-G method : A q-version of the Steepest Descent method for global optimization.

PubMed

Soterroni, Aline C; Galski, Roberto L; Scarabello, Marluce C; Ramos, Fernando M

2015-01-01

In this work, the q-Gradient (q-G) method, a q-version of the Steepest Descent method, is presented. The main idea behind the q-G method is the use of the negative of the q-gradient vector of the objective function as the search direction. The q-gradient vector, or simply the q-gradient, is a generalization of the classical gradient vector based on the concept of Jackson's derivative from the q-calculus. Its use provides the algorithm an effective mechanism for escaping from local minima. The q-G method reduces to the Steepest Descent method when the parameter q tends to 1. The algorithm has three free parameters and it is implemented so that the search process gradually shifts from global exploration in the beginning to local exploitation in the end. We evaluated the q-G method on 34 test functions, and compared its performance with 34 optimization algorithms, including derivative-free algorithms and the Steepest Descent method. Our results show that the q-G method is competitive and has a great potential for solving multimodal optimization problems.

A LAMMPS implementation of volume-temperature replica exchange molecular dynamics

NASA Astrophysics Data System (ADS)

Liu, Liang-Chun; Kuo, Jer-Lai

2015-04-01

A driver module for executing volume-temperature replica exchange molecular dynamics (VTREMD) was developed for the LAMMPS package. As a patch code, the VTREMD module performs classical molecular dynamics (MD) with Monte Carlo (MC) decisions between MD runs. The goal of inserting the MC step was to increase the breadth of sampled configurational space. In this method, states receive better sampling by making temperature or density swaps with their neighboring states. As an accelerated sampling method, VTREMD is particularly useful to explore states at low temperatures, where systems are easily trapped in local potential wells. As functional examples, TIP4P/Ew and TIP4P/2005 water models were analyzed using VTREMD. The phase diagram in this study covered the deeply supercooled regime, and this test served as a suitable demonstration of the usefulness of VTREMD in overcoming the slow dynamics problem. To facilitate using the current code, attention was also paid on how to optimize the exchange efficiency by using grid allocation. VTREMD was useful for studying systems with rough energy landscapes, such as those with numerous local minima or multiple characteristic time scales.

Symmetry breaking in linear multipole traps

NASA Astrophysics Data System (ADS)

Pedregosa-Gutierrez, J.; Champenois, C.; Kamsap, M. R.; Hagel, G.; Houssin, M.; Knoop, M.

2018-03-01

Radiofrequency multipole traps have been used for some decades in cold collision experiments and are gaining interest for precision spectroscopy due to their low micromotion contribution and the predicted unusual cold-ion structures. However, the experimental realisation is not yet fully controlled, and open questions in the operation of these devices remain. We present experimental observations of symmetry breaking of the trapping potential in a macroscopic octupole trap with laser-cooled ions. Numerical simulations have been performed in order to explain the appearance of additional local potential minima and be able to control them in a next step. We characterise these additional potential minima, in particular with respect to their position, their potential depth and their probability of population as a function of the radial and angular displacement of the trapping rods.

Relaxation dynamics of C60

NASA Astrophysics Data System (ADS)

Walsh, Tiffany R.; Wales, David J.

1998-10-01

The relaxation dynamics of C60 from high-energy isomers to Buckminsterfullerene is examined using a master equation approach. An exhaustive catalog of the C60 fullerene isomers containing only five- and six-membered rings is combined with knowledge of the Stone-Wales rearrangements that connect all such isomers. Full geometry optimizations have been performed for all the minima and the transition states which connect them up to six Stone-Wales steps away from the global minimum. A density-functional tight-binding potential was employed to provide a quantum mechanical description of the bonding. The resulting picture of the potential energy landscape reveals a "weeping willow" structure which offers a clear explanation for the relatively long relaxation times observed experimentally. We also predict the most important transient local minima on the annealing pathway.

H2, fixed architecture, control design for large scale systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Mercadal, Mathieu

1990-01-01

The H2, fixed architecture, control problem is a classic linear quadratic Gaussian (LQG) problem whose solution is constrained to be a linear time invariant compensator with a decentralized processing structure. The compensator can be made of p independent subcontrollers, each of which has a fixed order and connects selected sensors to selected actuators. The H2, fixed architecture, control problem allows the design of simplified feedback systems needed to control large scale systems. Its solution becomes more complicated, however, as more constraints are introduced. This work derives the necessary conditions for optimality for the problem and studies their properties. It is found that the filter and control problems couple when the architecture constraints are introduced, and that the different subcontrollers must be coordinated in order to achieve global system performance. The problem requires the simultaneous solution of highly coupled matrix equations. The use of homotopy is investigated as a numerical tool, and its convergence properties studied. It is found that the general constrained problem may have multiple stabilizing solutions, and that these solutions may be local minima or saddle points for the quadratic cost. The nature of the solution is not invariant when the parameters of the system are changed. Bifurcations occur, and a solution may continuously transform into a nonstabilizing compensator. Using a modified homotopy procedure, fixed architecture compensators are derived for models of large flexible structures to help understand the properties of the constrained solutions and compare them to the corresponding unconstrained ones.

Direct measurement of the free energy of aging hard sphere colloidal glasses.

PubMed

Zargar, Rojman; Nienhuis, Bernard; Schall, Peter; Bonn, Daniel

2013-06-21

The nature of the glass transition is one of the most important unsolved problems in condensed matter physics. The difference between glasses and liquids is believed to be caused by very large free energy barriers for particle rearrangements; however, so far it has not been possible to confirm this experimentally. We provide the first quantitative determination of the free energy for an aging hard sphere colloidal glass. The determination of the free energy allows for a number of new insights in the glass transition, notably the quantification of the strong spatial and temporal heterogeneity in the free energy. A study of the local minima of the free energy reveals that the observed variations are directly related to the rearrangements of the particles. Our main finding is that the probability of particle rearrangements shows a power law dependence on the free energy changes associated with the rearrangements similar to the Gutenberg-Richter law in seismology.

Development and experimentation of LQR/APF guidance and control for autonomous proximity maneuvers of multiple spacecraft

NASA Astrophysics Data System (ADS)

Bevilacqua, R.; Lehmann, T.; Romano, M.

2011-04-01

This work introduces a novel control algorithm for close proximity multiple spacecraft autonomous maneuvers, based on hybrid linear quadratic regulator/artificial potential function (LQR/APF), for applications including autonomous docking, on-orbit assembly and spacecraft servicing. Both theoretical developments and experimental validation of the proposed approach are presented. Fuel consumption is sub-optimized in real-time through re-computation of the LQR at each sample time, while performing collision avoidance through the APF and a high level decisional logic. The underlying LQR/APF controller is integrated with a customized wall-following technique and a decisional logic, overcoming problems such as local minima. The algorithm is experimentally tested on a four spacecraft simulators test bed at the Spacecraft Robotics Laboratory of the Naval Postgraduate School. The metrics to evaluate the control algorithm are: autonomy of the system in making decisions, successful completion of the maneuver, required time, and propellant consumption.

Inherent Structure versus Geometric Metric for State Space Discretization

PubMed Central

Liu, Hanzhong; Li, Minghai; Fan, Jue; Huo, Shuanghong

2016-01-01

Inherent structure (IS) and geometry-based clustering methods are commonly used for analyzing molecular dynamics trajectories. ISs are obtained by minimizing the sampled conformations into local minima on potential/effective energy surface. The conformations that are minimized into the same energy basin belong to one cluster. We investigate the influence of the applications of these two methods of trajectory decomposition on our understanding of the thermodynamics and kinetics of alanine tetrapeptide. We find that at the micro cluster level, the IS approach and root-mean-square deviation (RMSD) based clustering method give totally different results. Depending on the local features of energy landscape, the conformations with close RMSDs can be minimized into different minima, while the conformations with large RMSDs could be minimized into the same basin. However, the relaxation timescales calculated based on the transition matrices built from the micro clusters are similar. The discrepancy at the micro cluster level leads to different macro clusters. Although the dynamic models established through both clustering methods are validated approximately Markovian, the IS approach seems to give a meaningful state space discretization at the macro cluster level. PMID:26915811

A molecular dynamics study of slow base flipping in DNA using conformational flooding.

PubMed

Bouvier, Benjamin; Grubmüller, Helmut

2007-08-01

Individual DNA bases are known to be able to flip out of the helical stack, providing enzymes with access to the genetic information otherwise hidden inside the helix. Consequently, base flipping is a necessary first step to many more complex biological processes such as DNA transcription or replication. Much remains unknown about this elementary step, despite a wealth of experimental and theoretical studies. From the theoretical point of view, the involved timescale of milliseconds or longer requires the use of enhanced sampling techniques. In contrast to previous theoretical studies employing umbrella sampling along a predefined flipping coordinate, this study attempts to induce flipping without prior knowledge of the pathway, using information from a molecular dynamics simulation of a B-DNA fragment and the conformational flooding method. The relevance to base flipping of the principal components of the simulation is assayed, and a combination of modes optimally related to the flipping of the base through either helical groove is derived for each of the two bases of the central guanine-cytosine basepair. By applying an artificial flooding potential along these collective coordinates, the flipping mechanism is accelerated to within the scope of molecular dynamics simulations. The associated free energy surface is found to feature local minima corresponding to partially flipped states, particularly relevant to flipping in isolated DNA; further transitions from these minima to the fully flipped conformation are accelerated by additional flooding potentials. The associated free energy profiles feature similar barrier heights for both bases and pathways; the flipped state beyond is a broad and rugged attraction basin, only a few kcal/mol higher in energy than the closed conformation. This result diverges from previous works but echoes some aspects of recent experimental findings, justifying the need for novel approaches to this difficult problem: this contribution represents a first step in this direction. Important structural factors involved in flipping, both local (sugar-phosphate backbone dihedral angles) and global (helical axis bend), are also identified.

Robust Speech Enhancement Using Two-Stage Filtered Minima Controlled Recursive Averaging

NASA Astrophysics Data System (ADS)

Ghourchian, Negar; Selouani, Sid-Ahmed; O'Shaughnessy, Douglas

In this paper we propose an algorithm for estimating noise in highly non-stationary noisy environments, which is a challenging problem in speech enhancement. This method is based on minima-controlled recursive averaging (MCRA) whereby an accurate, robust and efficient noise power spectrum estimation is demonstrated. We propose a two-stage technique to prevent the appearance of musical noise after enhancement. This algorithm filters the noisy speech to achieve a robust signal with minimum distortion in the first stage. Subsequently, it estimates the residual noise using MCRA and removes it with spectral subtraction. The proposed Filtered MCRA (FMCRA) performance is evaluated using objective tests on the Aurora database under various noisy environments. These measures indicate the higher output SNR and lower output residual noise and distortion.

A novel neural-wavelet approach for process diagnostics and complex system modeling

NASA Astrophysics Data System (ADS)

Gao, Rong

Neural networks have been effective in several engineering applications because of their learning abilities and robustness. However certain shortcomings, such as slow convergence and local minima, are always associated with neural networks, especially neural networks applied to highly nonlinear and non-stationary problems. These problems can be effectively alleviated by integrating a new powerful tool, wavelets, into conventional neural networks. The multi-resolution analysis and feature localization capabilities of the wavelet transform offer neural networks new possibilities for learning. A neural wavelet network approach developed in this thesis enjoys fast convergence rate with little possibility to be caught at a local minimum. It combines the localization properties of wavelets with the learning abilities of neural networks. Two different testbeds are used for testing the efficiency of the new approach. The first is magnetic flowmeter-based process diagnostics: here we extend previous work, which has demonstrated that wavelet groups contain process information, to more general process diagnostics. A loop at Applied Intelligent Systems Lab (AISL) is used for collecting and analyzing data through the neural-wavelet approach. The research is important for thermal-hydraulic processes in nuclear and other engineering fields. The neural-wavelet approach developed is also tested with data from the electric power grid. More specifically, the neural-wavelet approach is used for performing short-term and mid-term prediction of power load demand. In addition, the feasibility of determining the type of load using the proposed neural wavelet approach is also examined. The notion of cross scale product has been developed as an expedient yet reliable discriminator of loads. Theoretical issues involved in the integration of wavelets and neural networks are discussed and future work outlined.

New Features for Neuron Classification.

PubMed

Hernández-Pérez, Leonardo A; Delgado-Castillo, Duniel; Martín-Pérez, Rainer; Orozco-Morales, Rubén; Lorenzo-Ginori, Juan V

2018-04-28

This paper addresses the problem of obtaining new neuron features capable of improving results of neuron classification. Most studies on neuron classification using morphological features have been based on Euclidean geometry. Here three one-dimensional (1D) time series are derived from the three-dimensional (3D) structure of neuron instead, and afterwards a spatial time series is finally constructed from which the features are calculated. Digitally reconstructed neurons were separated into control and pathological sets, which are related to three categories of alterations caused by epilepsy, Alzheimer's disease (long and local projections), and ischemia. These neuron sets were then subjected to supervised classification and the results were compared considering three sets of features: morphological, features obtained from the time series and a combination of both. The best results were obtained using features from the time series, which outperformed the classification using only morphological features, showing higher correct classification rates with differences of 5.15, 3.75, 5.33% for epilepsy and Alzheimer's disease (long and local projections) respectively. The morphological features were better for the ischemia set with a difference of 3.05%. Features like variance, Spearman auto-correlation, partial auto-correlation, mutual information, local minima and maxima, all related to the time series, exhibited the best performance. Also we compared different evaluators, among which ReliefF was the best ranked.

Neural Network and Nearest Neighbor Algorithms for Enhancing Sampling of Molecular Dynamics.

PubMed

Galvelis, Raimondas; Sugita, Yuji

2017-06-13

The free energy calculations of complex chemical and biological systems with molecular dynamics (MD) are inefficient due to multiple local minima separated by high-energy barriers. The minima can be escaped using an enhanced sampling method such as metadynamics, which apply bias (i.e., importance sampling) along a set of collective variables (CV), but the maximum number of CVs (or dimensions) is severely limited. We propose a high-dimensional bias potential method (NN2B) based on two machine learning algorithms: the nearest neighbor density estimator (NNDE) and the artificial neural network (ANN) for the bias potential approximation. The bias potential is constructed iteratively from short biased MD simulations accounting for correlation among CVs. Our method is capable of achieving ergodic sampling and calculating free energy of polypeptides with up to 8-dimensional bias potential.

Toward Rigorous Parameterization of Underconstrained Neural Network Models Through Interactive Visualization and Steering of Connectivity Generation

PubMed Central

Nowke, Christian; Diaz-Pier, Sandra; Weyers, Benjamin; Hentschel, Bernd; Morrison, Abigail; Kuhlen, Torsten W.; Peyser, Alexander

2018-01-01

Simulation models in many scientific fields can have non-unique solutions or unique solutions which can be difficult to find. Moreover, in evolving systems, unique final state solutions can be reached by multiple different trajectories. Neuroscience is no exception. Often, neural network models are subject to parameter fitting to obtain desirable output comparable to experimental data. Parameter fitting without sufficient constraints and a systematic exploration of the possible solution space can lead to conclusions valid only around local minima or around non-minima. To address this issue, we have developed an interactive tool for visualizing and steering parameters in neural network simulation models. In this work, we focus particularly on connectivity generation, since finding suitable connectivity configurations for neural network models constitutes a complex parameter search scenario. The development of the tool has been guided by several use cases—the tool allows researchers to steer the parameters of the connectivity generation during the simulation, thus quickly growing networks composed of multiple populations with a targeted mean activity. The flexibility of the software allows scientists to explore other connectivity and neuron variables apart from the ones presented as use cases. With this tool, we enable an interactive exploration of parameter spaces and a better understanding of neural network models and grapple with the crucial problem of non-unique network solutions and trajectories. In addition, we observe a reduction in turn around times for the assessment of these models, due to interactive visualization while the simulation is computed. PMID:29937723

Tidal effects in differentiated viscoelastic bodies: a numerical approach

NASA Astrophysics Data System (ADS)

Walterová, M.; Běhounková, M.

2017-09-01

The majority of confirmed terrestrial exoplanets orbits close to their host stars and their evolution was likely altered by tidal interaction. Nevertheless, due to their viscoelastic properties on the tidal frequencies, their response cannot be described exactly by standardly employed constant-lag models. We therefore introduce a tidal model based on the numerical evaluation of a continuum mechanics problem describing the deformation of viscoelastic (Maxwell or Andrade) planetary mantles subjected to external force. We apply the method on a model Earth-size planet orbiting a low-mass star and study the effect of the orbital eccentricity, the mantle viscosity and the chosen rheology on the tidal dissipation, the complex Love numbers and the tidal torque. The number of stable spin states (i.e., zero tidal torque) grows with increasing mantle viscosity, similarly to the analytical model of Correia et al. (Astron Astrophys 571:A50, 2014) for homogeneous bodies. This behavior is only slightly influenced by the rheology used. Similarly, the Love numbers do not distinctly depend on the considered rheological model. The increase in viscosity affects the amplitude of their variations. The tidal heating described by the Maxwell rheology attains local minima associated with low spin-orbit resonances, with depth and shape depending on both the eccentricity and the viscosity. For the Andrade rheology, the minima at low resonances are very shallow and the tidal heating for all viscosities resembles a "fluid limit." The tidal heating is the quantity influenced the most by the rheology, having thus possible impact on the internal thermal evolution.

Time series analysis of collective motions in proteins

NASA Astrophysics Data System (ADS)

Alakent, Burak; Doruker, Pemra; ćamurdan, Mehmet C.

2004-01-01

The dynamics of α-amylase inhibitor tendamistat around its native state is investigated using time series analysis of the principal components of the Cα atomic displacements obtained from molecular dynamics trajectories. Collective motion along a principal component is modeled as a homogeneous nonstationary process, which is the result of the damped oscillations in local minima superimposed on a random walk. The motion in local minima is described by a stationary autoregressive moving average model, consisting of the frequency, damping factor, moving average parameters and random shock terms. Frequencies for the first 50 principal components are found to be in the 3-25 cm-1 range, which are well correlated with the principal component indices and also with atomistic normal mode analysis results. Damping factors, though their correlation is less pronounced, decrease as principal component indices increase, indicating that low frequency motions are less affected by friction. The existence of a positive moving average parameter indicates that the stochastic force term is likely to disturb the mode in opposite directions for two successive sampling times, showing the modes tendency to stay close to minimum. All these four parameters affect the mean square fluctuations of a principal mode within a single minimum. The inter-minima transitions are described by a random walk model, which is driven by a random shock term considerably smaller than that for the intra-minimum motion. The principal modes are classified into three subspaces based on their dynamics: essential, semiconstrained, and constrained, at least in partial consistency with previous studies. The Gaussian-type distributions of the intermediate modes, called "semiconstrained" modes, are explained by asserting that this random walk behavior is not completely free but between energy barriers.

Pyrrole multimers and pyrrole-acetylene hydrogen bonded complexes studied in N2 and para-H2 matrixes using matrix isolation infrared spectroscopy and ab initio computations

NASA Astrophysics Data System (ADS)

Sarkar, Shubhra; Ramanathan, N.; Gopi, R.; Sundararajan, K.

2017-12-01

Hydrogen bonded interaction of pyrrole multimer and acetylene-pyrrole complexes were studied in N2 and p-H2 matrixes. DFT computations showed T-shaped geometry for the pyrrole dimer and cyclic complex for the trimer and tetramer were the most stable structures, stabilized by Nsbnd H⋯π interactions. The experimental vibrational wavenumbers observed in N2 and p-H2 matrixes for the pyrrole multimers were correlated with the computed wavenumbers. Computations performed at MP2/aug-cc-pVDZ level of theory showed that C2H2 and C4H5N forms 1:1 hydrogen-bonded complexes stabilized by Csbnd H⋯π interaction (Complex A), Nsbnd H⋯π interaction (Complex B) and π⋯π interaction (Complex C), where the former complex is the global minimum and latter two complexes were the first and second local minima, respectively. Experimentally, 1:1 C2H2sbnd C4H5N complexes A (global minimum) and B (first local minimum) were identified from the shifts in the Nsbnd H stretching, Nsbnd H bending, Csbnd H bending region of pyrrole and Csbnd H asymmetric stretching and bending region of C2H2 in N2 and p-H2 matrixes. Computations were also performed for the higher complexes and found two minima corresponding to the 1:2 C2H2sbnd C4H5N and three minima for the 2:1 C2H2sbnd C4H5N complexes. Experimentally the global minimum 1:2 and 2:1 C2H2sbnd C4H5N complexes were identified in N2 and p-H2 matrixes.

Design and implementation of non-linear image processing functions for CMOS image sensor

NASA Astrophysics Data System (ADS)

Musa, Purnawarman; Sudiro, Sunny A.; Wibowo, Eri P.; Harmanto, Suryadi; Paindavoine, Michel

2012-11-01

Today, solid state image sensors are used in many applications like in mobile phones, video surveillance systems, embedded medical imaging and industrial vision systems. These image sensors require the integration in the focal plane (or near the focal plane) of complex image processing algorithms. Such devices must meet the constraints related to the quality of acquired images, speed and performance of embedded processing, as well as low power consumption. To achieve these objectives, low-level analog processing allows extracting the useful information in the scene directly. For example, edge detection step followed by a local maxima extraction will facilitate the high-level processing like objects pattern recognition in a visual scene. Our goal was to design an intelligent image sensor prototype achieving high-speed image acquisition and non-linear image processing (like local minima and maxima calculations). For this purpose, we present in this article the design and test of a 64×64 pixels image sensor built in a standard CMOS Technology 0.35 μm including non-linear image processing. The architecture of our sensor, named nLiRIC (non-Linear Rapid Image Capture), is based on the implementation of an analog Minima/Maxima Unit. This MMU calculates the minimum and maximum values (non-linear functions), in real time, in a 2×2 pixels neighbourhood. Each MMU needs 52 transistors and the pitch of one pixel is 40×40 mu m. The total area of the 64×64 pixels is 12.5mm2. Our tests have shown the validity of the main functions of our new image sensor like fast image acquisition (10K frames per second), minima/maxima calculations in less then one ms.

MinFinder v2.0: An improved version of MinFinder

NASA Astrophysics Data System (ADS)

Tsoulos, Ioannis G.; Lagaris, Isaac E.

2008-10-01

A new version of the "MinFinder" program is presented that offers an augmented linking procedure for Fortran-77 subprograms, two additional stopping rules and a new start-point rejection mechanism that saves a significant portion of gradient and function evaluations. The method is applied on a set of standard test functions and the results are reported. New version program summaryProgram title: MinFinder v2.0 Catalogue identifier: ADWU_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADWU_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC Licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 14 150 No. of bytes in distributed program, including test data, etc.: 218 144 Distribution format: tar.gz Programming language used: GNU C++, GNU FORTRAN, GNU C Computer: The program is designed to be portable in all systems running the GNU C++ compiler Operating system: Linux, Solaris, FreeBSD RAM: 200 000 bytes Classification: 4.9 Catalogue identifier of previous version: ADWU_v1_0 Journal reference of previous version: Computer Physics Communications 174 (2006) 166-179 Does the new version supersede the previous version?: Yes Nature of problem: A multitude of problems in science and engineering are often reduced to minimizing a function of many variables. There are instances that a local optimum does not correspond to the desired physical solution and hence the search for a better solution is required. Local optimization techniques can be trapped in any local minimum. Global optimization is then the appropriate tool. For example, solving a non-linear system of equations via optimization, one may encounter many local minima that do not correspond to solutions, i.e. they are far from zero. Solution method: Using a uniform pdf, points are sampled from a rectangular domain. A clustering technique, based on a typical distance and a gradient criterion, is used to decide from which points a local search should be started. Further searching is terminated when all the local minima inside the search domain are thought to be found. This is accomplished via three stopping rules: the "double-box" stopping rule, the "observables" stopping rule and the "expected minimizers" stopping rule. Reasons for the new version: The link procedure for source code in Fortran 77 is enhanced, two additional stopping rules are implemented and a new criterion for accepting-start points, that economizes on function and gradient calls, is introduced. Summary of revisions:Addition of command line parameters to the utility program make_program. Augmentation of the link process for Fortran 77 subprograms, by linking the final executable with the g2c library. Addition of two probabilistic stopping rules. Introduction of a rejection mechanism to the Checking step of the original method, that reduces the number of gradient evaluations. Additional comments: A technical report describing the revisions, experiments and test runs is packaged with the source code. Running time: Depending on the objective function.

An investigation of isomerization pathways of epoxysaccharides

NASA Astrophysics Data System (ADS)

Andrianov, V. M.; Kirillova, S. G.; Zhbankov, R. G.

1997-07-01

Direct and reverse interconversion pathways of six epoxysaccharide molecules, namely, three molecules with epoxypyranose rings: methyl 2,3-anhydro-2,3,4-trideoxy- β- D-lyxohexopyranoside, methyl 2,3-anhydro-4-deoxy- α- D, L-ribo- and - α- D, L-lyxohexopyranosides and three molecules with epoxypyranose rings: methyl 2,6-di- O-acetyl-3,4-anhydro- α- D, L-( 6,6- 2H2) derivatives of talopyranoside and galactopyranoside, and methyl 3,4-anhydro- α- D, L-allopyranoside were simulated by the Wiberg and Boyd method. This made it possible to determine all stationary and intermediate forms in which anhydropyranose rings can exist. Calculations of barrier heights for interconversion and energies of global minima have shown that conformations revealed in X-ray studies are more favorable. Most of the local minima found lie in the vicinity of the boat (B) forms, the other minima correspond to conformations possessing symmetry elements of the skew-boat (S) and twist (T) forms. The interconversion pathways of the molecules investigated are presented on the Cremer-Pople diagram. We studied the effect of various structural factors on the character of conformational transformations, heights of transition barriers, the form of the ground state, and the energy of stationary forms, and their number and location on the Cremer-Pople diagram.

Dimer formation of perylene: An ultracold spectroscopic and computational study

NASA Astrophysics Data System (ADS)

Birer, Ö.; Yurtsever, E.

2015-10-01

The electronic spectra of perylene inside helium nanodroplets recorded by the depletion method are presented. The results show two broad peaks in addition to sharp monomer vibronic transitions due to dimer formation. In order to understand the details of the spectra, first the dimer formation is studied by DFT and SCS-MP2 calculations and then the electronic spectra are calculated at the minima of the potential energy surface (PES). Theoretical calculations show that there are two low-lying energetically degenerate dimer structures; namely a parallel displaced one and a rotated stacked one. PES around these minima is very flat with a number of local minima at higher energies which at the experimental temperatures cannot be populated. Even though thermodynamically these two structures are equally populated, dynamical considerations point out that in helium droplet the parallel displaced geometry is encouraged by the natural alignment of the molecules due to the acquired angular momentum following the pick-up process. The calculated spectrum of the parallel displaced geometry predicts the positions of the dimer transitions within 30 nm of the experimental spectrum. Furthermore, the difference between the two dimer transitions is accurately predicted to be about 25 nm while the experimental difference was about 20 nm. Such a small difference could only be detected due to the ultracold conditions helium nanodroplets provided.

Cluster Differences Scaling with a Within-Clusters Loss Component and a Fuzzy Successive Approximation Strategy To Avoid Local Minima.

ERIC Educational Resources Information Center

Heiser, Willem J.; And Others

1997-01-01

The least squares loss function of cluster differences scaling, originally defined only on residuals of pairs allocated to different clusters, is extended with a loss component for pairs allocated to the same cluster. Findings show that this makes the method equivalent to multidimensional scaling with cluster constraints on the coordinates. (SLD)

"In Situ" Observation of a Soap-Film Catenoid--A Simple Educational Physics Experiment

ERIC Educational Resources Information Center

Ito, Masato; Sato, Taku

2010-01-01

The solution to the Euler-Lagrange equation is an extremal functional. To understand that the functional is stationary at local extrema (maxima or minima), we propose a physics experiment that involves using a soap film to form a catenoid. A catenoid is a surface that is formed between two coaxial circular rings and is classified mathematically as…

Pyridine adsorption and diffusion on Pt(111) investigated with density functional theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kolsbjerg, Esben L.; Groves, Michael N.; Hammer, Bjørk, E-mail: hammer@phys.au.dk

2016-04-28

The adsorption, diffusion, and dissociation of pyridine, C{sub 5}H{sub 5}N, on Pt(111) are investigated with van der Waals-corrected density functional theory. An elaborate search for local minima in the adsorption potential energy landscape reveals that the intact pyridine adsorbs with the aromatic ring parallel to the surface. Piecewise interconnections of the local minima in the energy landscape reveal that the most favourable diffusion path for pyridine has a barrier of 0.53 eV. In the preferred path, the pyridine remains parallel to the surface while performing small single rotational steps with a carbon-carbon double bond hinged above a single Pt atom.more » The origin of the diffusion pathway is discussed in terms of the C{sub 2}–Pt π-bond being stronger than the corresponding CN–Pt π-bond. The energy barrier and reaction enthalpy for dehydrogenation of adsorbed pyridine into an adsorbed, upright bound α-pyridyl species are calculated to 0.71 eV and 0.18 eV, respectively (both zero-point energy corrected). The calculations are used to rationalize previous experimental observations from the literature for pyridine on Pt(111).« less

Unambiguous Signature of the Berry Phase in Intense Laser Dissociation of Diatomic Molecules.

PubMed

Bouakline, Foudhil

2018-05-03

We report strong evidence of Berry phase effects in intense laser dissociation of D 2 + molecules, manifested as Aharonov-Bohm-like oscillations in the photofragment angular distribution (PAD). Our calculations show that this interference pattern strongly depends on the parity of the diatom initial rotational state, (-1) j . Indeed, the PAD local maxima (minima) observed in one case ( j odd) correspond to local minima (maxima) in the other case ( j even). Using simple topological arguments, we clearly show that such interference conversion is a direct signature of the Berry phase. The sole effect of the latter on the rovibrational wave function is a sign change of the relative phase between two interfering components, which wind in opposite senses around a light-induced conical intersection (LICI). Therefore, encirclement of the LICI leads to constructive ( j odd) or destructive ( j even) self-interference of the initial nuclear wavepacket in the dissociative limit. To corroborate our theoretical findings, we suggest an experiment of strong-field indirect dissociation of D 2 + molecules, comparing the PAD of the ortho and para molecular species in directions nearly perpendicular to the laser polarization axis.

Improved transition path sampling methods for simulation of rare events

NASA Astrophysics Data System (ADS)

Chopra, Manan; Malshe, Rohit; Reddy, Allam S.; de Pablo, J. J.

2008-04-01

The free energy surfaces of a wide variety of systems encountered in physics, chemistry, and biology are characterized by the existence of deep minima separated by numerous barriers. One of the central aims of recent research in computational chemistry and physics has been to determine how transitions occur between deep local minima on rugged free energy landscapes, and transition path sampling (TPS) Monte-Carlo methods have emerged as an effective means for numerical investigation of such transitions. Many of the shortcomings of TPS-like approaches generally stem from their high computational demands. Two new algorithms are presented in this work that improve the efficiency of TPS simulations. The first algorithm uses biased shooting moves to render the sampling of reactive trajectories more efficient. The second algorithm is shown to substantially improve the accuracy of the transition state ensemble by introducing a subset of local transition path simulations in the transition state. The system considered in this work consists of a two-dimensional rough energy surface that is representative of numerous systems encountered in applications. When taken together, these algorithms provide gains in efficiency of over two orders of magnitude when compared to traditional TPS simulations.

Radionuclide activities and metal concentrations in sediments of the Sebou Estuary, NW Morocco, following a flooding event.

PubMed

Laissaoui, A; Mas, J L; Hurtado, S; Ziad, N; Villa, M; Benmansour, M

2013-06-01

This study presents metal concentrations (Fe, Mg, Mn, Co, Cu, Zn, Pb, As, Sr and V) and radionuclide activities ((40)K, (137)Cs, (210)Pb, (226)Ra, (228)Ac, (234)Th and (212)Pb) in surface deposits and a sediment core from the Sebou Estuary, Northwest Morocco. Samples were collected in April 2009, about 2 months after a flooding event, and analysed using a well-type coaxial gamma-ray detector and inductively coupled plasma-quadrupole mass spectrometry. Activities of radionuclides and concentrations of almost all elements in surface samples displayed only moderate spatial variation, suggesting homogenous deposition of eroded local soil in response to intense precipitation. Excess (210)Pb displayed relatively constant activity throughout the sediment core, preventing dating and precluding determination of the historical accumulation rates of pollutants at the core site. Some elements showed non-systematic trends with depth and displayed local maxima and minima. Other elements presented relatively systematic concentration trends or relatively constant levels with discrete maxima and/or minima. Except for Mn, Sr and Cr, all metal concentrations in sediment were below levels typical of polluted systems, suggesting little human impact or losses of metals from sediment particles.

Inherent structure versus geometric metric for state space discretization.

PubMed

Liu, Hanzhong; Li, Minghai; Fan, Jue; Huo, Shuanghong

2016-05-30

Inherent structure (IS) and geometry-based clustering methods are commonly used for analyzing molecular dynamics trajectories. ISs are obtained by minimizing the sampled conformations into local minima on potential/effective energy surface. The conformations that are minimized into the same energy basin belong to one cluster. We investigate the influence of the applications of these two methods of trajectory decomposition on our understanding of the thermodynamics and kinetics of alanine tetrapeptide. We find that at the microcluster level, the IS approach and root-mean-square deviation (RMSD)-based clustering method give totally different results. Depending on the local features of energy landscape, the conformations with close RMSDs can be minimized into different minima, while the conformations with large RMSDs could be minimized into the same basin. However, the relaxation timescales calculated based on the transition matrices built from the microclusters are similar. The discrepancy at the microcluster level leads to different macroclusters. Although the dynamic models established through both clustering methods are validated approximately Markovian, the IS approach seems to give a meaningful state space discretization at the macrocluster level in terms of conformational features and kinetics. © 2016 Wiley Periodicals, Inc.

Structural features of small benzene clusters (C6H6)n (n ≤ 30) as investigated with the all-atom OPLS potential.

PubMed

Takeuchi, Hiroshi

2012-10-18

The structures of the simplest aromatic clusters, benzene clusters (C(6)H(6))(n), are not well elucidated. In the present study, benzene clusters (C(6)H(6))(n) (n ≤ 30) were investigated with the all-atom optimized parameters for liquid simulation (OPLS) potential. The global minima and low-lying minima of the benzene clusters were searched with the heuristic method combined with geometrical perturbations. The structural features and growth sequence of the clusters were examined by carrying out local structure analyses and structural similarity evaluation with rotational constants. Because of the anisotropic interaction between the benzene molecules, the local structures consisting of 13 molecules are considerably deviated from regular icosahedron, and the geometries of some of the clusters are inconsistent with the shapes constructed by the interior molecules. The distribution of the angle between the lines normal to two neighboring benzene rings is anisotropic in the clusters, whereas that in the liquid benzene is nearly isotropic. The geometries and energies of the low-lying configurations and the saddle points between them suggest that most of the configurations previously detected in supersonic expansions take different orientations for one to four neighboring molecules.

Quantum tomography for collider physics: illustrations with lepton-pair production

NASA Astrophysics Data System (ADS)

Martens, John C.; Ralston, John P.; Takaki, J. D. Tapia

2018-01-01

Quantum tomography is a method to experimentally extract all that is observable about a quantum mechanical system. We introduce quantum tomography to collider physics with the illustration of the angular distribution of lepton pairs. The tomographic method bypasses much of the field-theoretic formalism to concentrate on what can be observed with experimental data. We provide a practical, experimentally driven guide to model-independent analysis using density matrices at every step. Comparison with traditional methods of analyzing angular correlations of inclusive reactions finds many advantages in the tomographic method, which include manifest Lorentz covariance, direct incorporation of positivity constraints, exhaustively complete polarization information, and new invariants free from frame conventions. For example, experimental data can determine the entanglement entropy of the production process. We give reproducible numerical examples and provide a supplemental standalone computer code that implements the procedure. We also highlight a property of complex positivity that guarantees in a least-squares type fit that a local minimum of a χ 2 statistic will be a global minimum: There are no isolated local minima. This property with an automated implementation of positivity promises to mitigate issues relating to multiple minima and convention dependence that have been problematic in previous work on angular distributions.

TRMM Microwave Radiometer Rain Rate Estimation Method with Convective and Stratiform Discrimination

NASA Technical Reports Server (NTRS)

Prabhakara, Cuddapah; Iacovazzi, R.; Weinman, J. A.; Dalu, G.; Einaudi, Franco (Technical Monitor)

2000-01-01

Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometer brightness temperature data in the 85 GHz channel (T85) reveal distinct local minima (T85min) in a regional map containing a Mesoscale Convective System (MCS). A map of surface rain rate for that region, deduced from simultaneous measurements made by the Precipitation Radar (PR) on board the TRMM satellite, reveals that these T85min, produced by scattering, correspond to local PR rain maxima. Utilizing the PR rain rate map as a guide, we have developed a TMI algorithm to retrieve convective and stratiform rain. In this algorithm, two parameters are used to classify three kinds of thunderstorms (Cbs) based on the T85 data: a) the magnitude of scattering depression deduced from local T85mi, and b) the mean horizontal gradient of T85 around such minima. Initially, the algorithm is optimized or tuned utilizing the PR and TMI data of a few MCS events. The areal distribution of light (1-10 mm/hr), moderate (10-20 mm/hr), and intense (greater than or equal to 20 mm/hr) rain rates are retrieved on the average with an accuracy of about 15%. Taking advantage of this ability of our retrieval method, one could derive the latent heat input into the atmosphere over the 760 km wide swath of the TMI radiometer in the tropics.

Analysis and design of numerical schemes for gas dynamics 1: Artificial diffusion, upwind biasing, limiters and their effect on accuracy and multigrid convergence

NASA Technical Reports Server (NTRS)

Jameson, Antony

1994-01-01

The theory of non-oscillatory scalar schemes is developed in this paper in terms of the local extremum diminishing (LED) principle that maxima should not increase and minima should not decrease. This principle can be used for multi-dimensional problems on both structured and unstructured meshes, while it is equivalent to the total variation diminishing (TVD) principle for one-dimensional problems. A new formulation of symmetric limited positive (SLIP) schemes is presented, which can be generalized to produce schemes with arbitrary high order of accuracy in regions where the solution contains no extrema, and which can also be implemented on multi-dimensional unstructured meshes. Systems of equations lead to waves traveling with distinct speeds and possibly in opposite directions. Alternative treatments using characteristic splitting and scalar diffusive fluxes are examined, together with modification of the scalar diffusion through the addition of pressure differences to the momentum equations to produce full upwinding in supersonic flow. This convective upwind and split pressure (CUSP) scheme exhibits very rapid convergence in multigrid calculations of transonic flow, and provides excellent shock resolution at very high Mach numbers.

A model reduction approach to numerical inversion for a parabolic partial differential equation

NASA Astrophysics Data System (ADS)

Borcea, Liliana; Druskin, Vladimir; Mamonov, Alexander V.; Zaslavsky, Mikhail

2014-12-01

We propose a novel numerical inversion algorithm for the coefficients of parabolic partial differential equations, based on model reduction. The study is motivated by the application of controlled source electromagnetic exploration, where the unknown is the subsurface electrical resistivity and the data are time resolved surface measurements of the magnetic field. The algorithm presented in this paper considers inversion in one and two dimensions. The reduced model is obtained with rational interpolation in the frequency (Laplace) domain and a rational Krylov subspace projection method. It amounts to a nonlinear mapping from the function space of the unknown resistivity to the small dimensional space of the parameters of the reduced model. We use this mapping as a nonlinear preconditioner for the Gauss-Newton iterative solution of the inverse problem. The advantage of the inversion algorithm is twofold. First, the nonlinear preconditioner resolves most of the nonlinearity of the problem. Thus the iterations are less likely to get stuck in local minima and the convergence is fast. Second, the inversion is computationally efficient because it avoids repeated accurate simulations of the time-domain response. We study the stability of the inversion algorithm for various rational Krylov subspaces, and assess its performance with numerical experiments.

Comparing feed-forward versus neural gas as estimators: application to coke wastewater treatment.

PubMed

Machón-González, Iván; López-García, Hilario; Rodríguez-Iglesias, Jesús; Marañón-Maison, Elena; Castrillón-Peláez, Leonor; Fernández-Nava, Yolanda

2013-01-01

Numerous papers related to the estimation of wastewater parameters have used artificial neural networks. Although successful results have been reported, different problems have arisen such as overtraining, local minima and model instability. In this paper, two types of neural networks, feed-forward and neural gas, are trained to obtain a model that estimates the values of nitrates in the effluent stream of a three-step activated sludge system (two oxic and one anoxic). Placing the denitrification (anoxic) step at the head of the process can force denitrifying bacteria to use internal organic carbon. However, methanol has to be added to achieve high denitrification efficiencies in some industrial wastewaters. The aim of this paper is to compare the two networks in addition to suggesting a methodology to validate the models. The influence of the neighbourhood radius is important in the neural gas approach and must be selected correctly. Neural gas performs well due to its cooperation--competition procedure, with no problems of stability or overfitting arising in the experimental results. The neural gas model is also interesting for use as a direct plant model because of its robustness and deterministic behaviour.

Orbital optimisation in the perfect pairing hierarchy: applications to full-valence calculations on linear polyacenes

NASA Astrophysics Data System (ADS)

Lehtola, Susi; Parkhill, John; Head-Gordon, Martin

2018-03-01

We describe the implementation of orbital optimisation for the models in the perfect pairing hierarchy. Orbital optimisation, which is generally necessary to obtain reliable results, is pursued at perfect pairing (PP) and perfect quadruples (PQ) levels of theory for applications on linear polyacenes, which are believed to exhibit strong correlation in the π space. While local minima and σ-π symmetry breaking solutions were found for PP orbitals, no such problems were encountered for PQ orbitals. The PQ orbitals are used for single-point calculations at PP, PQ and perfect hextuples (PH) levels of theory, both only in the π subspace, as well as in the full σπ valence space. It is numerically demonstrated that the inclusion of single excitations is necessary also when optimised orbitals are used. PH is found to yield good agreement with previously published density matrix renormalisation group data in the π space, capturing over 95% of the correlation energy. Full-valence calculations made possible by our novel, efficient code reveal that strong correlations are weaker when larger basis sets or active spaces are employed than in previous calculations. The largest full-valence PH calculations presented correspond to a (192e,192o) problem.

Social Milieu Oriented Routing: A New Dimension to Enhance Network Security in WSNs.

PubMed

Liu, Lianggui; Chen, Li; Jia, Huiling

2016-02-19

In large-scale wireless sensor networks (WSNs), in order to enhance network security, it is crucial for a trustor node to perform social milieu oriented routing to a target a trustee node to carry out trust evaluation. This challenging social milieu oriented routing with more than one end-to-end Quality of Trust (QoT) constraint has proved to be NP-complete. Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this challenging problem. However, existing solutions cannot guarantee the efficiency of searching; that is, they can hardly avoid obtaining partial optimal solutions during a searching process. Quantum annealing (QA) uses delocalization and tunneling to avoid falling into local minima without sacrificing execution time. This has been proven a promising way to many optimization problems in recently published literatures. In this paper, for the first time, with the help of a novel approach, that is, configuration path-integral Monte Carlo (CPIMC) simulations, a QA-based optimal social trust path (QA_OSTP) selection algorithm is applied to the extraction of the optimal social trust path in large-scale WSNs. Extensive experiments have been conducted, and the experiment results demonstrate that QA_OSTP outperforms its heuristic opponents.

Cloud and convection frequencies over the southeast United States as related to small-scale geographic features

NASA Technical Reports Server (NTRS)

Gibson, Harold M.; Vonder Haar, Thomas H.

1990-01-01

Based on relatively high spatial and temporal resolution satelite data collected at 0700 CST and at each hour from 1000 CST to 1700 CST during the summer of 1986, cloud and convection variations over the area from Mississippi east to Georgia and from the Gulf of Mexico north to Tennessee are discussed. The data analyses show an average maximum cloud frequency over the land areas at 1400 local time and a maximum of deep convection one hour later. Both cloudiness and deep convection are found to be at a maximum during the nocturnal hours over the Gulf of Mexico. Cloud frequency shows a strong relationship to small terrain features. Small fresh water bodies have cloud minima relative to the surroundings in the afternoon hours. Higher, steep terrain shows cloud maxima and the adjacent lower terrain exhibits afternoon cloud minima due to a divergence of mountain breeze caused by the valley.

Amyloid Polymorphism in the Protein Folding and Aggregation Energy Landscape.

PubMed

Adamcik, Jozef; Mezzenga, Raffaele

2018-02-15

Protein folding involves a large number of steps and conformations in which the folding protein samples different thermodynamic states characterized by local minima. Kinetically trapped on- or off-pathway intermediates are metastable folding intermediates towards the lowest absolute energy minima, which have been postulated to be the natively folded state where intramolecular interactions dominate, and the amyloid state where intermolecular interactions dominate. However, this view largely neglects the rich polymorphism found within amyloid species. We review the protein folding energy landscape in view of recent findings identifying specific transition routes among different amyloid polymorphs. Observed transitions such as twisted ribbon→crystal or helical ribbon→nanotube, and forbidden transitions such helical ribbon↛crystal, are discussed and positioned within the protein folding and aggregation energy landscape. Finally, amyloid crystals are identified as the ground state of the protein folding and aggregation energy landscape. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Inferring neural activity from BOLD signals through nonlinear optimization.

PubMed

Vakorin, Vasily A; Krakovska, Olga O; Borowsky, Ron; Sarty, Gordon E

2007-11-01

The blood oxygen level-dependent (BOLD) fMRI signal does not measure neuronal activity directly. This fact is a key concern for interpreting functional imaging data based on BOLD. Mathematical models describing the path from neural activity to the BOLD response allow us to numerically solve the inverse problem of estimating the timing and amplitude of the neuronal activity underlying the BOLD signal. In fact, these models can be viewed as an advanced substitute for the impulse response function. In this work, the issue of estimating the dynamics of neuronal activity from the observed BOLD signal is considered within the framework of optimization problems. The model is based on the extended "balloon" model and describes the conversion of neuronal signals into the BOLD response through the transitional dynamics of the blood flow-inducing signal, cerebral blood flow, cerebral blood volume and deoxyhemoglobin concentration. Global optimization techniques are applied to find a control input (the neuronal activity and/or the biophysical parameters in the model) that causes the system to follow an admissible solution to minimize discrepancy between model and experimental data. As an alternative to a local linearization (LL) filtering scheme, the optimization method escapes the linearization of the transition system and provides a possibility to search for the global optimum, avoiding spurious local minima. We have found that the dynamics of the neural signals and the physiological variables as well as the biophysical parameters can be robustly reconstructed from the BOLD responses. Furthermore, it is shown that spiking off/on dynamics of the neural activity is the natural mathematical solution of the model. Incorporating, in addition, the expansion of the neural input by smooth basis functions, representing a low-pass filtering, allows us to model local field potential (LFP) solutions instead of spiking solutions.

Recent Minima of 171 Eclipsing Binary Stars

NASA Astrophysics Data System (ADS)

Samolyk, G.

2015-12-01

This paper continues the publication of times of minima for 171 eclipsing binary stars from observations reported to the AAVSO EB section. Times of minima from observations received by the author from March 2015 thru October 2015 are presented.

Mean curvature and texture constrained composite weighted random walk algorithm for optic disc segmentation towards glaucoma screening.

PubMed

Panda, Rashmi; Puhan, N B; Panda, Ganapati

2018-02-01

Accurate optic disc (OD) segmentation is an important step in obtaining cup-to-disc ratio-based glaucoma screening using fundus imaging. It is a challenging task because of the subtle OD boundary, blood vessel occlusion and intensity inhomogeneity. In this Letter, the authors propose an improved version of the random walk algorithm for OD segmentation to tackle such challenges. The algorithm incorporates the mean curvature and Gabor texture energy features to define the new composite weight function to compute the edge weights. Unlike the deformable model-based OD segmentation techniques, the proposed algorithm remains unaffected by curve initialisation and local energy minima problem. The effectiveness of the proposed method is verified with DRIVE, DIARETDB1, DRISHTI-GS and MESSIDOR database images using the performance measures such as mean absolute distance, overlapping ratio, dice coefficient, sensitivity, specificity and precision. The obtained OD segmentation results and quantitative performance measures show robustness and superiority of the proposed algorithm in handling the complex challenges in OD segmentation.

Applications of Monte Carlo method to nonlinear regression of rheological data

NASA Astrophysics Data System (ADS)

Kim, Sangmo; Lee, Junghaeng; Kim, Sihyun; Cho, Kwang Soo

2018-02-01

In rheological study, it is often to determine the parameters of rheological models from experimental data. Since both rheological data and values of the parameters vary in logarithmic scale and the number of the parameters is quite large, conventional method of nonlinear regression such as Levenberg-Marquardt (LM) method is usually ineffective. The gradient-based method such as LM is apt to be caught in local minima which give unphysical values of the parameters whenever the initial guess of the parameters is far from the global optimum. Although this problem could be solved by simulated annealing (SA), the Monte Carlo (MC) method needs adjustable parameter which could be determined in ad hoc manner. We suggest a simplified version of SA, a kind of MC methods which results in effective values of the parameters of most complicated rheological models such as the Carreau-Yasuda model of steady shear viscosity, discrete relaxation spectrum and zero-shear viscosity as a function of concentration and molecular weight.

A Novel Hybrid Firefly Algorithm for Global Optimization.

PubMed

Zhang, Lina; Liu, Liqiang; Yang, Xin-She; Dai, Yuntao

Global optimization is challenging to solve due to its nonlinearity and multimodality. Traditional algorithms such as the gradient-based methods often struggle to deal with such problems and one of the current trends is to use metaheuristic algorithms. In this paper, a novel hybrid population-based global optimization algorithm, called hybrid firefly algorithm (HFA), is proposed by combining the advantages of both the firefly algorithm (FA) and differential evolution (DE). FA and DE are executed in parallel to promote information sharing among the population and thus enhance searching efficiency. In order to evaluate the performance and efficiency of the proposed algorithm, a diverse set of selected benchmark functions are employed and these functions fall into two groups: unimodal and multimodal. The experimental results show better performance of the proposed algorithm compared to the original version of the firefly algorithm (FA), differential evolution (DE) and particle swarm optimization (PSO) in the sense of avoiding local minima and increasing the convergence rate.

A Novel Hybrid Firefly Algorithm for Global Optimization

PubMed Central

Zhang, Lina; Liu, Liqiang; Yang, Xin-She; Dai, Yuntao

2016-01-01

Global optimization is challenging to solve due to its nonlinearity and multimodality. Traditional algorithms such as the gradient-based methods often struggle to deal with such problems and one of the current trends is to use metaheuristic algorithms. In this paper, a novel hybrid population-based global optimization algorithm, called hybrid firefly algorithm (HFA), is proposed by combining the advantages of both the firefly algorithm (FA) and differential evolution (DE). FA and DE are executed in parallel to promote information sharing among the population and thus enhance searching efficiency. In order to evaluate the performance and efficiency of the proposed algorithm, a diverse set of selected benchmark functions are employed and these functions fall into two groups: unimodal and multimodal. The experimental results show better performance of the proposed algorithm compared to the original version of the firefly algorithm (FA), differential evolution (DE) and particle swarm optimization (PSO) in the sense of avoiding local minima and increasing the convergence rate. PMID:27685869

An improved grey wolf optimizer algorithm for the inversion of geoelectrical data

NASA Astrophysics Data System (ADS)

Li, Si-Yu; Wang, Shu-Ming; Wang, Peng-Fei; Su, Xiao-Lu; Zhang, Xin-Song; Dong, Zhi-Hui

2018-05-01

The grey wolf optimizer (GWO) is a novel bionics algorithm inspired by the social rank and prey-seeking behaviors of grey wolves. The GWO algorithm is easy to implement because of its basic concept, simple formula, and small number of parameters. This paper develops a GWO algorithm with a nonlinear convergence factor and an adaptive location updating strategy and applies this improved grey wolf optimizer (improved grey wolf optimizer, IGWO) algorithm to geophysical inversion problems using magnetotelluric (MT), DC resistivity and induced polarization (IP) methods. Numerical tests in MATLAB 2010b for the forward modeling data and the observed data show that the IGWO algorithm can find the global minimum and rarely sinks to the local minima. For further study, inverted results using the IGWO are contrasted with particle swarm optimization (PSO) and the simulated annealing (SA) algorithm. The outcomes of the comparison reveal that the IGWO and PSO similarly perform better in counterpoising exploration and exploitation with a given number of iterations than the SA.

Experiences with serial and parallel algorithms for channel routing using simulated annealing

NASA Technical Reports Server (NTRS)

Brouwer, Randall Jay

1988-01-01

Two algorithms for channel routing using simulated annealing are presented. Simulated annealing is an optimization methodology which allows the solution process to back up out of local minima that may be encountered by inappropriate selections. By properly controlling the annealing process, it is very likely that the optimal solution to an NP-complete problem such as channel routing may be found. The algorithm presented proposes very relaxed restrictions on the types of allowable transformations, including overlapping nets. By freeing that restriction and controlling overlap situations with an appropriate cost function, the algorithm becomes very flexible and can be applied to many extensions of channel routing. The selection of the transformation utilizes a number of heuristics, still retaining the pseudorandom nature of simulated annealing. The algorithm was implemented as a serial program for a workstation, and a parallel program designed for a hypercube computer. The details of the serial implementation are presented, including many of the heuristics used and some of the resulting solutions.

Examination of Bursty Electromagnetic Waves Observed During Intervals of Turbulent Magnetosheath Reconnection

NASA Technical Reports Server (NTRS)

Adrian, Mark L.; Wendel, D. E.

2011-01-01

We investigate observations of intense bursts of electromagnetic waves in association with magnetic reconnection in the turbulent magnetosheath. These structured, broadband bursts occur above 80-Hz, often displaying features reminiscent of absorption bands and are observed at local minima in the magnetic field. We present detailed analyses of these intense bursts of electromagnetic waves and quantify their proximity to X- and O-nulls.

Description of third instars of Cochliomyia minima (Diptera: Calliphoridae) from West Indies, and updated identification key.

PubMed

Yusseff-Vanegas, S

2014-09-01

The blow fly Cochliomyia minima Shannon is endemic to the Caribbean, and it has great potential for forensic applications because of its abundance and broad distribution in the region. However, its larval stages are unknown. Here, I update previously published identification keys by describing for the first time the morphology of C. minima larvae. The larvae of C. minima are found to be very similar to those of Cochliomyia macellaria F., but the former can be easily identified by the oral sclerite completely pigmented, visible as a spike between mouth hooks. The description of C. minima larvae in this study will be useful to forensic scientists in the Caribbean region.

Conformational analysis of methylphenidate: comparison of molecular orbital and molecular mechanics methods

NASA Astrophysics Data System (ADS)

Gilbert, Kathleen M.; Skawinski, William J.; Misra, Milind; Paris, Kristina A.; Naik, Neelam H.; Buono, Ronald A.; Deutsch, Howard M.; Venanzi, Carol A.

2004-11-01

Methylphenidate (MP) binds to the cocaine binding site on the dopamine transporter and inhibits reuptake of dopamine, but does not appear to have the same abuse potential as cocaine. This study, part of a comprehensive effort to identify a drug treatment for cocaine abuse, investigates the effect of choice of calculation technique and of solvent model on the conformational potential energy surface (PES) of MP and a rigid methylphenidate (RMP) analogue which exhibits the same dopamine transporter binding affinity as MP. Conformational analysis was carried out by the AM1 and AM1/SM5.4 semiempirical molecular orbital methods, a molecular mechanics method (Tripos force field with the dielectric set equal to that of vacuum or water) and the HF/6-31G* molecular orbital method in vacuum phase. Although all three methods differ somewhat in the local details of the PES, the general trends are the same for neutral and protonated MP. In vacuum phase, protonation has a distinctive effect in decreasing the regions of space available to the local conformational minima. Solvent has little effect on the PES of the neutral molecule and tends to stabilize the protonated species. The random search (RS) conformational analysis technique using the Tripos force field was found to be capable of locating the minima found by the molecular orbital methods using systematic grid search. This suggests that the RS/Tripos force field/vacuum phase protocol is a reasonable choice for locating the local minima of MP. However, the Tripos force field gave significantly larger phenyl ring rotational barriers than the molecular orbital methods for MP and RMP. For both the neutral and protonated cases, all three methods found the phenyl ring rotational barriers for the RMP conformers/invertamers (denoted as cte, tte, and cta) to be: cte, tte> MP > cta. Solvation has negligible effect on the phenyl ring rotational barrier of RMP. The B3LYP/6-31G* density functional method was used to calculate the phenyl ring rotational barrier for neutral MP and gave results very similar to those of the HF/6-31G* method.

Toward a detailed understanding of search trajectories in fragment assembly approaches to protein structure prediction

PubMed Central

Handl, Julia; Lovell, Simon C.

2016-01-01

ABSTRACT Energy functions, fragment libraries, and search methods constitute three key components of fragment‐assembly methods for protein structure prediction, which are all crucial for their ability to generate high‐accuracy predictions. All of these components are tightly coupled; efficient searching becomes more important as the quality of fragment libraries decreases. Given these relationships, there is currently a poor understanding of the strengths and weaknesses of the sampling approaches currently used in fragment‐assembly techniques. Here, we determine how the performance of search techniques can be assessed in a meaningful manner, given the above problems. We describe a set of techniques that aim to reduce the impact of the energy function, and assess exploration in view of the search space defined by a given fragment library. We illustrate our approach using Rosetta and EdaFold, and show how certain features of these methods encourage or limit conformational exploration. We demonstrate that individual trajectories of Rosetta are susceptible to local minima in the energy landscape, and that this can be linked to non‐uniform sampling across the protein chain. We show that EdaFold's novel approach can help balance broad exploration with locating good low‐energy conformations. This occurs through two mechanisms which cannot be readily differentiated using standard performance measures: exclusion of false minima, followed by an increasingly focused search in low‐energy regions of conformational space. Measures such as ours can be helpful in characterizing new fragment‐based methods in terms of the quality of conformational exploration realized. Proteins 2016; 84:411–426. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc. PMID:26799916

Scan-based volume animation driven by locally adaptive articulated registrations.

PubMed

Rhee, Taehyun; Lewis, J P; Neumann, Ulrich; Nayak, Krishna S

2011-03-01

This paper describes a complete system to create anatomically accurate example-based volume deformation and animation of articulated body regions, starting from multiple in vivo volume scans of a specific individual. In order to solve the correspondence problem across volume scans, a template volume is registered to each sample. The wide range of pose variations is first approximated by volume blend deformation (VBD), providing proper initialization of the articulated subject in different poses. A novel registration method is presented to efficiently reduce the computation cost while avoiding strong local minima inherent in complex articulated body volume registration. The algorithm highly constrains the degrees of freedom and search space involved in the nonlinear optimization, using hierarchical volume structures and locally constrained deformation based on the biharmonic clamped spline. Our registration step establishes a correspondence across scans, allowing a data-driven deformation approach in the volume domain. The results provide an occlusion-free person-specific 3D human body model, asymptotically accurate inner tissue deformations, and realistic volume animation of articulated movements driven by standard joint control estimated from the actual skeleton. Our approach also addresses the practical issues arising in using scans from living subjects. The robustness of our algorithms is tested by their applications on the hand, probably the most complex articulated region in the body, and the knee, a frequent subject area for medical imaging due to injuries. © 2011 IEEE

Recovery from Maunder-like Grand Minima in a Babcock–Leighton Solar Dynamo Model

NASA Astrophysics Data System (ADS)

Karak, Bidya Binay; Miesch, Mark

2018-06-01

The Sun occasionally goes through Maunder-like extended grand minima when its magnetic activity drops considerably from the normal activity level for several decades. Many possible theories have been proposed to explain the origin of these minima. However, how the Sun managed to recover from such inactive phases every time is even more enigmatic. The Babcock–Leighton type dynamos, which are successful in explaining many features of the solar cycle remarkably well, are not expected to operate during grand minima due to the lack of a sufficient number of sunspots. In this Letter, we explore the question of how the Sun could recover from grand minima through the Babcock–Leighton dynamo. In our three-dimensional dynamo model, grand minima are produced spontaneously as a result of random variations in the tilt angle of emerging active regions. We find that the Babcock–Leighton process can still operate during grand minima with only a minimal number of sunspots, and that the model can emerge from such phases without the need for an additional generation mechanism for the poloidal field. The essential ingredient in our model is a downward magnetic pumping, which inhibits the diffusion of the magnetic flux across the solar surface.

The effect of boundary shape and minima selection on single limb stance postural stability.

PubMed

Cobb, Stephen C; Joshi, Mukta N; Bazett-Jones, David M; Earl-Boehm, Jennifer E

2012-11-01

The effect of time-to-boundary minima selection and stability limit definition was investigated during eyes open and eyes closed condition single-limb stance postural stability. Anteroposterior and mediolateral time-to-boundary were computed using the mean and standard deviation (SD) of all time-to-boundary minima during a trial, and the mean and SD of only the 10 absolute time-to-boundary minima. Time-to-boundary with rectangular, trapezoidal, and multisegmented polygon defined stability limits were also calculated. Spearman's rank correlation coefficient test results revealed significant medium-large correlations between anteroposterior and mediolateral time-to-boundary scores calculated using both the mean and SD of the 10 absolute time-to-boundary minima and of all the time-to-boundary minima. Friedman test results revealed significant mediolateral time-to-boundary differences between boundary shape definitions. Follow-up Wilcoxon signed rank test results revealed significant differences between the rectangular boundary shape and both the trapezoidal and multisegmented polygon shapes during the eyes open and eyes closed conditions when both the mean and the SD of the time-to-boundary minima were used to represent postural stability. Significant differences were also revealed between the trapezoidal and multisegmented polygon definitions during the eyes open condition when the SD of the time-to-boundary minima was used to represent postural stability. Based on these findings, the overall results (i.e., stable versus unstable participants or groups) of studies computing postural stability using different minima selection can be compared. With respect to boundary shape, the trapezoid or multisegmented polygon shapes may be more appropriate than the rectangular shape as they more closely represent the anatomical shape of the stance foot.

Crossover from localized to cascade relaxations in metallic glasses

DOE PAGES

Fan, Yue; Iwashita, Takuya; Egami, Takeshi

2015-07-21

Thermally activated deformation is investigated in two metallic glass systems with different cooling histories. By probing the atomic displacements and stress changes on the potential energy landscape, two deformation modes, a localized process and cascade process, have observed. The localized deformation involves fewer than 30 atoms and appears in both systems, and its size is invariant with cooling history. However, the cascade deformation is more frequently observed in the fast quenched system than in the slowly quenched system. As a result, the origin of the cascade process in the fast quenched system is attributed to the higher density of localmore » minima on the underlying potential energy landscape.« less

Analyzing structural variations along strike in a deep-water thrust belt

NASA Astrophysics Data System (ADS)

Totake, Yukitsugu; Butler, Robert W. H.; Bond, Clare E.; Aziz, Aznan

2018-03-01

We characterize a deep-water fold-thrust arrays imaged by a high-resolution 3D seismic dataset in the offshore NW Borneo, Malaysia, to understand the kinematics behind spatial arrangement of structural variations throughout the fold-thrust system. The seismic volume used covers two sub-parallel fold trains associated with a series of fore-thrusts and back-thrusts. We measured fault heave, shortening value, fold geometries (forelimb dip, interlimb angle and crest depth) along strike in individual fold trains. Heave plot on strike projection allows to identify individual thrust segments showing semi-elliptical to triangular to bimodal patterns, and linkages of these segments. The linkage sites are marked by local minima in cumulative heave. These local heave minima are compensated by additional structures, such as small imbricate thrusts and tight folds indicated by large forelimb dip and small interlimb angle. Complementary profiles of the shortening amount for the two fold trains result in smoother gradient of total shortening across the structures. We interpret this reflects kinematic interaction between two fold-thrust trains. This type of along-strike variation analysis provides comprehensive understanding of a fold-thrust system and may provide an interpretative strategy for inferring the presence of complex multiple faults in less well-imaged parts of seismic volumes.

Phase transitions in colloidal fluids: Kinetically or thermodynamically controlled?

NASA Astrophysics Data System (ADS)

Duran-Olivencia, Miguel A.; Yatsyshin, Peter; Lutsko, James F.; Kalliadasis, Serafim

2017-11-01

In recent years, a flurry of experimental observations suggests that most phase transitions occur in a multistage manner and via intermediate phases. These precursors to the final phase are commonly understood as the local minima of the free energy of the system. Inherently, the classical paradigm of nucleation has no capacity to describe neither the origin nor the role played by these precursors in the nucleation pathway. Here we present a systematic theoretical framework capable of describing the precursor phases in a self-consistent way. We demonstrate that nucleation precursors can appear even in situations involving a single free-energy barrier. This contradicts previous phenomenological approaches, which always characterise intermediate phases as the minima of a complex free-energy landscape. We show that a kinetically-induced mechanism temporarily stabilises an intermediate phase, which thus is not the result of a local minimum of the free energy but a consequence of the entropic cost of cluster formation. Moreover, the appearance of precursors does not seem to influence the overall nucleation time, which is governed by the free-energy barrier. The mechanism uncovered in this study can be used to explain recently reported experimental findings in crystallisation. European Research Council - Advanced Grant No. 247031; Engineering and Physical Sciences Research Council - Grant Nos. EP/L020564 and EP/L025159.

Timing of AB And eclipses

NASA Astrophysics Data System (ADS)

Kozyreva, V. S.; Ibrahimov, M. A.; Gaynullina, E. R.; Karimov, R. G.; Hafizov, B. M.; Satovskii, B. L.; Krushevska, V. N.; Kuznyetsova, Yu. G.; Bogomazov, A. I.; Irsmambetova, T. R.; Tutukov, A. V.

2018-01-01

This study aims timing the eclipses of the short period low mass binary star AB And. The times of minima are taken from the literature and from our observations in October 2013 (22 times of minima) and in August 2014 (23 times of minima). We find and discuss an inaccuracy in the determination of the types of minima in the previous investigation by Li et al. (2014). We study the secular evolution of the central binary's orbital period and the possibility of the existence of third and fourth companions in the system.

Global optimization of additive potential energy functions: Predicting binary Lennard-Jones clusters

NASA Astrophysics Data System (ADS)

Kolossváry, István; Bowers, Kevin J.

2010-11-01

We present a method for minimizing additive potential-energy functions. Our hidden-force algorithm can be described as an intricate multiplayer tug-of-war game in which teams try to break an impasse by randomly assigning some players to drop their ropes while the others are still tugging until a partial impasse is reached, then, instructing the dropouts to resume tugging, for all teams to come to a new overall impasse. Utilizing our algorithm in a non-Markovian parallel Monte Carlo search, we found 17 new putative global minima for binary Lennard-Jones clusters in the size range of 90-100 particles. The method is efficient enough that an unbiased search was possible; no potential-energy surface symmetries were exploited. All new minima are comprised of three nested polyicosahedral or polytetrahedral shells when viewed as a nested set of Connolly surfaces (though the shell structure has previously gone unscrutinized, known minima are often qualitatively similar). Unlike known minima, in which the outer and inner shells are comprised of the larger and smaller atoms, respectively, in 13 of the new minima, the atoms are not as clearly separated by size. Furthermore, while some known minima have inner shells stabilized by larger atoms, four of the new minima have outer shells stabilized by smaller atoms.

Structure optimisation by thermal cycling for the hydrophobic-polar lattice model of protein folding

NASA Astrophysics Data System (ADS)

Günther, Florian; Möbius, Arnulf; Schreiber, Michael

2017-03-01

The function of a protein depends strongly on its spatial structure. Therefore the transition from an unfolded stage to the functional fold is one of the most important problems in computational molecular biology. Since the corresponding free energy landscapes exhibit huge numbers of local minima, the search for the lowest-energy configurations is very demanding. Because of that, efficient heuristic algorithms are of high value. In the present work, we investigate whether and how the thermal cycling (TC) approach can be applied to the hydrophobic-polar (HP) lattice model of protein folding. Evaluating the efficiency of TC for a set of two- and three-dimensional examples, we compare the performance of this strategy with that of multi-start local search (MSLS) procedures and that of simulated annealing (SA). For this aim, we incorporated several simple but rather efficient modifications into the standard procedures: in particular, a strong improvement was achieved by also allowing energy conserving state modifications. Furthermore, the consideration of ensembles instead of single samples was found to greatly improve the efficiency of TC. In the framework of different benchmarks, for all considered HP sequences, we found TC to be far superior to SA, and to be faster than Wang-Landau sampling.

A Topside Equatorial Ionospheric Density and Composition Climatology During and After Extreme Solar Minimum

NASA Technical Reports Server (NTRS)

Klenzing, J. H.; Simoes, F.; Ivanov, S.; Heelis, R. A.; Bilitza, D.; Pfaff, R. F.; Rowland, D. E.

2011-01-01

During the recent solar minimum, solar activity reached the lowest levels observed during the space age. This extremely low solar activity has accompanied a number of unexpected observations in the Earth's ionosphere and thermosphere when compared to previous solar minima. Among these are the fact that the ionosphere is significantly contracted beyond expectations based on empirical models. Climatological altitude profiles of ion density and composition measurements near the magnetic dip equator are constructed from the C/NOFS satellite to characterize the shape of the top side ionosphere during the recent solar minimum and into the new solar cycle. The variation of the profiles with respect to local time, season, and solar activity are compared to the IRI-2007 model. Building on initial results reported by Heelis et al. [2009], here we describe the extent of the contracted ionosphere, which is found to persist throughout 2009. The shape of the ionosphere during 2010 is found to be consistent with observations from previous solar minima.

Topside Equatorial Ionospheric Density and Composition During and After Extreme Solar Minimum

NASA Technical Reports Server (NTRS)

Klenzing, J.; Simoes, F.; Ivanov, S.; Heelis, R. A.; Bilitza, D.; Pfaff, R.; Rowland, D.

2011-01-01

During the recent solar minimum, solar activity reached the lowest levels observed during the space age. This extremely low solar activity has accompanied a number of unexpected observations in the Earth s ionosphere-thermosphere system when compared to previous solar minima. Among these are the fact that the ionosphere is significantly contracted beyond expectations based on empirical models. Altitude profiles of ion density and composition measurements near the magnetic dip equator are constructed from the Communication/Navigation Outage Forecast System (C/NOFS) satellite to characterize the shape of the topside ionosphere during the recent solar minimum and into the new solar cycle. The variation of the profiles with respect to local time, season, and solar activity are compared to the IRI-2007 model. Building on initial results reported by Heelis et al. (2009), here we describe the extent of the contracted ionosphere, which is found to persist throughout 2009. The shape of the ionosphere during 2010 is found to be consistent with observations from previous solar minima.

On the ion-pair dissociation mechanisms in the small NaCl·(H2 O)6 cluster: A perspective from reaction path search calculations.

PubMed

Takayanagi, Toshiyuki; Nakatomi, Taiki; Yonetani, Yoshiteru

2018-04-20

We performed reaction path search calculations for the NaCl·(H 2 O) 6 cluster using the global reaction route mapping (GRRM) code to understand the atomic-level mechanisms of the NaCl → Na +  + Cl - ionic dissociation induced by water solvents. Low-lying minima, transition states connecting two local minima and corresponding intrinsic reaction coordinates on the potential energy surface are explored. We found that the NaCl distances at the transitions states for the dissociation pathways were distributed in a relatively wide range of 2.7-3.7 Å and that the NaCl distance at the transition state did not correlate with the commonly used solvation coordinates. This suggests that the definition of the transition states with specific structures as well as good reaction coordinate is very difficult for the ionic dissociation process even in a small water cluster. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

The cosmic radiation in the heliosphere at successive solar minima

NASA Technical Reports Server (NTRS)

Mcdonald, Frank B.; Moraal, Harm; Reinecke, J. P. L.; Lal, Nand; Mcguire, Robert E.

1992-01-01

Cosmic ray observations at 1 AU are compared for the last three solar minimum periods along with the 1977/1989 and 1987 Pioneer 10 and Voyager 1 and 2 data from the outer heliosphere. There is good agreement between the 1965 and 1987 Galactic cosmic ray H and He spectra at 1 AU. Significant and complex differences are found between the 1977/1978 and 1987 measurements of the Galactic and anomalous cosmic ray components at 1 and 15 AU. In the outer heliosphere there are negative latitudinal gradients that reach their maximum magnitude when the inclination of the outer heliosphere current sheet is at a minimum. The radial gradients decrease with heliocentric distance as about 1/r exp 0.7 and do not differ significantly at the successive solar minima. The measured radial and latitudinal gradients are used to estimate the particle transport parameters in the outer heliosphere. Using the local interstellar He spectrum of Webber et al. (1987), it is estimated that the modulation boundary is of the order of 160 AU.

Inhomogeneous screening of gate electric field by interface states in graphene FETs

NASA Astrophysics Data System (ADS)

Singh, Anil Kumar; Gupta, Anjan Kumar

2017-09-01

The electronic states at graphene-SiO2 interface and their inhomogeneity is investigated using the back-gate-voltage dependence of local tunnel spectra acquired with a scanning tunneling microscope. The conductance spectra show two, or occasionally three, minima that evolve along the bias-voltage axis with the back gate voltage. This evolution is modeled using tip-gating and interface states. The energy dependent interface states’ density, Dit(E) , required to model the back-gate evolution of the minima, is found to have significant inhomogeneity in its energy-width. A broad Dit(E) leads to an effect similar to a reduction in the Fermi velocity while the narrow Dit(E) leads to the pinning of the Fermi energy close to the Dirac point, as observed in some places, due to enhanced screening of the gate electric field by the narrow Dit(E) . Finally, this also demonstrates STM as a tool to probe the density of interface states in various 2D Dirac materials.

Can nonadditive dispersion forces explain chain formation of nanoparticles?

NASA Astrophysics Data System (ADS)

Kwaadgras, Bas W.; Verdult, Maarten W. J.; Dijkstra, Marjolein; van Roij, René

2013-03-01

We study to what extent dielectric nanoparticles prefer to self-assemble into linear chains or into more compact structures. To calculate the Van der Waals (VdW) attraction between the clusters we use the Coupled Dipole Method (CDM), which treats each atom in the nanoparticle as an inducible oscillating point dipole. The VdW attraction then results from the full many-body interactions between the dipoles. For non-capped nanoparticles, we calculate in which configuration the VdW attraction is maximal. We find that in virtually all cases we studied, many-body effects only result in local potential minima at the linear configuration, as opposed to global ones, and that these metastable minima are in most cases rather shallow compared to the thermal energy. In this work, we also compare the CDM results with those from Hamaker-de Boer and Axilrod-Teller theory to investigate the influence of the many-body effects and the accuracy of these two approximate methods.

14 CFR 121.625 - Alternate Airport weather minima.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 3 2014-01-01 2014-01-01 false Alternate Airport weather minima. 121.625... Alternate Airport weather minima. Except as provided in § 121.624 for ETOPS Alternate Airports, no person may list an airport as an alternate in the dispatch or flight release unless the appropriate weather...

14 CFR 121.625 - Alternate Airport weather minima.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 3 2012-01-01 2012-01-01 false Alternate Airport weather minima. 121.625... Alternate Airport weather minima. Except as provided in § 121.624 for ETOPS Alternate Airports, no person may list an airport as an alternate in the dispatch or flight release unless the appropriate weather...

14 CFR 121.625 - Alternate Airport weather minima.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 3 2011-01-01 2011-01-01 false Alternate Airport weather minima. 121.625... Alternate Airport weather minima. Except as provided in § 121.624 for ETOPS Alternate Airports, no person may list an airport as an alternate in the dispatch or flight release unless the appropriate weather...

14 CFR 121.625 - Alternate Airport weather minima.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 3 2013-01-01 2013-01-01 false Alternate Airport weather minima. 121.625... Alternate Airport weather minima. Except as provided in § 121.624 for ETOPS Alternate Airports, no person may list an airport as an alternate in the dispatch or flight release unless the appropriate weather...

14 CFR 121.625 - Alternate Airport weather minima.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Alternate Airport weather minima. 121.625... Alternate Airport weather minima. Except as provided in § 121.624 for ETOPS Alternate Airports, no person may list an airport as an alternate in the dispatch or flight release unless the appropriate weather...

Essential Roles of Local Auxin Biosynthesis in Plant Development and in Adaptation to Environmental Changes.

PubMed

Zhao, Yunde

2018-04-29

It has been a dominant dogma in plant biology that the self-organizing polar auxin transport system is necessary and sufficient to generate auxin maxima and minima that are essential for almost all aspects of plant growth and development. However, in the past few years, it has become clear that local auxin biosynthesis is required for a suite of developmental processes, including embryogenesis, endosperm development, root development, and floral initiation and patterning. Moreover, it was discovered that local auxin biosynthesis maintains optimal plant growth in response to environmental signals, including light, temperature, pathogens, and toxic metals. In this article, I discuss the recent progress in auxin biosynthesis research and the paradigm shift in recognizing the important roles of local auxin biosynthesis in plant biology.

D3h [A-CE3-A]- (E = Al and Ga, A = Si, Ge, Sn, and Pb): A new class of hexatomic mono-anionic species with trigonal bipyramidal carbon

NASA Astrophysics Data System (ADS)

Wu, Yan-Bo; Li, Yan-Qin; Bai, Hui; Lu, Hai-Gang; Li, Si-Dian; Zhai, Hua-Jin; Wang, Zhi-Xiang

2014-03-01

The non-classical trigonal bipyramidal carbon (TBPC) arrangement generally exists as transition states (TSs) in nucleophilic bimolecular substitution (SN2) reactions. Nevertheless, chemists have been curious about whether such a carbon bonding could be stable in equilibrium structures for decades. As the TBPC arrangement was normally realized as cationic species theoretically and experimentally, only one anionic example ([At-C(CN)3-At]-) was computationally devised. Herein, we report the design of a new class of anionic TBPC species by using the strategy similar to that for stabilizing the non-classical planar hypercoordinate carbon. When electron deficient Al and Ga were used as the equatorial ligands, eight D3h [A-CE3-A]- (E = Al and Ga, A = Si, Ge, Sn, and Pb) TBPC structures were found to be the energy minima rather than TSs at both the B3LYP and MP2 levels. Remarkably, the energetic results at the CCSD(T) optimization level further identify [Ge-CAl3-Ge]- and [Sn-CGa3-Sn]- even to be the global minima and [Si-CAl3-Si]- and [Ge-CGa3-Ge]- to be the local minima, only slightly higher than their global minima. The electronic structure analyses reveal that the substantial ionic C-E bonding, the peripheral E-A covalent bonding, and the axial mc-2e (multi center-two electrons) bonding play roles in stabilizing these TBPC structures. The structural simplicity and the high thermodynamic stability suggest that some of these species may be generated and captured in the gas phase. Furthermore, as mono-anionic species, their first vertical detachment energies are differentiable from those of their nearest isomers, which would facilitate their characterization via experiments such as the negative ion photoelectron spectroscopy.

Microstructure from ferroelastic transitions using strain pseudospin clock models in two and three dimensions: A local mean-field analysis

NASA Astrophysics Data System (ADS)

Vasseur, Romain; Lookman, Turab; Shenoy, Subodh R.

2010-09-01

We show how microstructure can arise in first-order ferroelastic structural transitions, in two and three spatial dimensions, through a local mean-field approximation of their pseudospin Hamiltonians, that include anisotropic elastic interactions. Such transitions have symmetry-selected physical strains as their NOP -component order parameters, with Landau free energies that have a single zero-strain “austenite” minimum at high temperatures, and spontaneous-strain “martensite” minima of NV structural variants at low temperatures. The total free energy also has gradient terms, and power-law anisotropic effective interactions, induced by “no-dislocation” St Venant compatibility constraints. In a reduced description, the strains at Landau minima induce temperature dependent, clocklike ZNV+1 Hamiltonians, with NOP -component strain-pseudospin vectors S⃗ pointing to NV+1 discrete values (including zero). We study elastic texturing in five such first-order structural transitions through a local mean-field approximation of their pseudospin Hamiltonians, that include the power-law interactions. As a prototype, we consider the two-variant square/rectangle transition, with a one-component pseudospin taking NV+1=3 values of S=0,±1 , as in a generalized Blume-Capel model. We then consider transitions with two-component (NOP=2) pseudospins: the equilateral to centered rectangle (NV=3) ; the square to oblique polygon (NV=4) ; the triangle to oblique (NV=6) transitions; and finally the three-dimensional (3D) cubic to tetragonal transition (NV=3) . The local mean-field solutions in two-dimensional and 3D yield oriented domain-wall patterns as from continuous-variable strain dynamics, showing the discrete-variable models capture the essential ferroelastic texturings. Other related Hamiltonians illustrate that structural transitions in materials science can be the source of interesting spin models in statistical mechanics.

Numerical convergence and validation of the DIMP inverse particle transport model

DOE PAGES

Nelson, Noel; Azmy, Yousry

2017-09-01

The data integration with modeled predictions (DIMP) model is a promising inverse radiation transport method for solving the special nuclear material (SNM) holdup problem. Unlike previous methods, DIMP is a completely passive nondestructive assay technique that requires no initial assumptions regarding the source distribution or active measurement time. DIMP predicts the most probable source location and distribution through Bayesian inference and quasi-Newtonian optimization of predicted detector re-sponses (using the adjoint transport solution) with measured responses. DIMP performs well with for-ward hemispherical collimation and unshielded measurements, but several considerations are required when using narrow-view collimated detectors. DIMP converged well to themore » correct source distribution as the number of synthetic responses increased. DIMP also performed well for the first experimental validation exercise after applying a collimation factor, and sufficiently reducing the source search vol-ume's extent to prevent the optimizer from getting stuck in local minima. DIMP's simple point detector response function (DRF) is being improved to address coplanar false positive/negative responses, and an angular DRF is being considered for integration with the next version of DIMP to account for highly collimated responses. Overall, DIMP shows promise for solving the SNM holdup inverse problem, especially once an improved optimization algorithm is implemented.« less

Hybrid annealing: Coupling a quantum simulator to a classical computer

NASA Astrophysics Data System (ADS)

Graß, Tobias; Lewenstein, Maciej

2017-05-01

Finding the global minimum in a rugged potential landscape is a computationally hard task, often equivalent to relevant optimization problems. Annealing strategies, either classical or quantum, explore the configuration space by evolving the system under the influence of thermal or quantum fluctuations. The thermal annealing dynamics can rapidly freeze the system into a low-energy configuration, and it can be simulated well on a classical computer, but it easily gets stuck in local minima. Quantum annealing, on the other hand, can be guaranteed to find the true ground state and can be implemented in modern quantum simulators; however, quantum adiabatic schemes become prohibitively slow in the presence of quasidegeneracies. Here, we propose a strategy which combines ideas from simulated annealing and quantum annealing. In such a hybrid algorithm, the outcome of a quantum simulator is processed on a classical device. While the quantum simulator explores the configuration space by repeatedly applying quantum fluctuations and performing projective measurements, the classical computer evaluates each configuration and enforces a lowering of the energy. We have simulated this algorithm for small instances of the random energy model, showing that it potentially outperforms both simulated thermal annealing and adiabatic quantum annealing. It becomes most efficient for problems involving many quasidegenerate ground states.

Nonlinear inversion of electrical resistivity imaging using pruning Bayesian neural networks

NASA Astrophysics Data System (ADS)

Jiang, Fei-Bo; Dai, Qian-Wei; Dong, Li

2016-06-01

Conventional artificial neural networks used to solve electrical resistivity imaging (ERI) inversion problem suffer from overfitting and local minima. To solve these problems, we propose to use a pruning Bayesian neural network (PBNN) nonlinear inversion method and a sample design method based on the K-medoids clustering algorithm. In the sample design method, the training samples of the neural network are designed according to the prior information provided by the K-medoids clustering results; thus, the training process of the neural network is well guided. The proposed PBNN, based on Bayesian regularization, is used to select the hidden layer structure by assessing the effect of each hidden neuron to the inversion results. Then, the hyperparameter α k , which is based on the generalized mean, is chosen to guide the pruning process according to the prior distribution of the training samples under the small-sample condition. The proposed algorithm is more efficient than other common adaptive regularization methods in geophysics. The inversion of synthetic data and field data suggests that the proposed method suppresses the noise in the neural network training stage and enhances the generalization. The inversion results with the proposed method are better than those of the BPNN, RBFNN, and RRBFNN inversion methods as well as the conventional least squares inversion.

On the use of harmony search algorithm in the training of wavelet neural networks

NASA Astrophysics Data System (ADS)

Lai, Kee Huong; Zainuddin, Zarita; Ong, Pauline

2015-10-01

Wavelet neural networks (WNNs) are a class of feedforward neural networks that have been used in a wide range of industrial and engineering applications to model the complex relationships between the given inputs and outputs. The training of WNNs involves the configuration of the weight values between neurons. The backpropagation training algorithm, which is a gradient-descent method, can be used for this training purpose. Nonetheless, the solutions found by this algorithm often get trapped at local minima. In this paper, a harmony search-based algorithm is proposed for the training of WNNs. The training of WNNs, thus can be formulated as a continuous optimization problem, where the objective is to maximize the overall classification accuracy. Each candidate solution proposed by the harmony search algorithm represents a specific WNN architecture. In order to speed up the training process, the solution space is divided into disjoint partitions during the random initialization step of harmony search algorithm. The proposed training algorithm is tested onthree benchmark problems from the UCI machine learning repository, as well as one real life application, namely, the classification of electroencephalography signals in the task of epileptic seizure detection. The results obtained show that the proposed algorithm outperforms the traditional harmony search algorithm in terms of overall classification accuracy.

On the Relationship between Variational Level Set-Based and SOM-Based Active Contours

PubMed Central

Abdelsamea, Mohammed M.; Gnecco, Giorgio; Gaber, Mohamed Medhat; Elyan, Eyad

2015-01-01

Most Active Contour Models (ACMs) deal with the image segmentation problem as a functional optimization problem, as they work on dividing an image into several regions by optimizing a suitable functional. Among ACMs, variational level set methods have been used to build an active contour with the aim of modeling arbitrarily complex shapes. Moreover, they can handle also topological changes of the contours. Self-Organizing Maps (SOMs) have attracted the attention of many computer vision scientists, particularly in modeling an active contour based on the idea of utilizing the prototypes (weights) of a SOM to control the evolution of the contour. SOM-based models have been proposed in general with the aim of exploiting the specific ability of SOMs to learn the edge-map information via their topology preservation property and overcoming some drawbacks of other ACMs, such as trapping into local minima of the image energy functional to be minimized in such models. In this survey, we illustrate the main concepts of variational level set-based ACMs, SOM-based ACMs, and their relationship and review in a comprehensive fashion the development of their state-of-the-art models from a machine learning perspective, with a focus on their strengths and weaknesses. PMID:25960736

Parameter identification in ODE models with oscillatory dynamics: a Fourier regularization approach

NASA Astrophysics Data System (ADS)

Chiara D'Autilia, Maria; Sgura, Ivonne; Bozzini, Benedetto

2017-12-01

In this paper we consider a parameter identification problem (PIP) for data oscillating in time, that can be described in terms of the dynamics of some ordinary differential equation (ODE) model, resulting in an optimization problem constrained by the ODEs. In problems with this type of data structure, simple application of the direct method of control theory (discretize-then-optimize) yields a least-squares cost function exhibiting multiple ‘low’ minima. Since in this situation any optimization algorithm is liable to fail in the approximation of a good solution, here we propose a Fourier regularization approach that is able to identify an iso-frequency manifold {{ S}} of codimension-one in the parameter space \

Computing Nash equilibria through computational intelligence methods

NASA Astrophysics Data System (ADS)

Pavlidis, N. G.; Parsopoulos, K. E.; Vrahatis, M. N.

2005-03-01

Nash equilibrium constitutes a central solution concept in game theory. The task of detecting the Nash equilibria of a finite strategic game remains a challenging problem up-to-date. This paper investigates the effectiveness of three computational intelligence techniques, namely, covariance matrix adaptation evolution strategies, particle swarm optimization, as well as, differential evolution, to compute Nash equilibria of finite strategic games, as global minima of a real-valued, nonnegative function. An issue of particular interest is to detect more than one Nash equilibria of a game. The performance of the considered computational intelligence methods on this problem is investigated using multistart and deflection.

CCOMP: An efficient algorithm for complex roots computation of determinantal equations

NASA Astrophysics Data System (ADS)

Zouros, Grigorios P.

2018-01-01

In this paper a free Python algorithm, entitled CCOMP (Complex roots COMPutation), is developed for the efficient computation of complex roots of determinantal equations inside a prescribed complex domain. The key to the method presented is the efficient determination of the candidate points inside the domain which, in their close neighborhood, a complex root may lie. Once these points are detected, the algorithm proceeds to a two-dimensional minimization problem with respect to the minimum modulus eigenvalue of the system matrix. In the core of CCOMP exist three sub-algorithms whose tasks are the efficient estimation of the minimum modulus eigenvalues of the system matrix inside the prescribed domain, the efficient computation of candidate points which guarantee the existence of minima, and finally, the computation of minima via bound constrained minimization algorithms. Theoretical results and heuristics support the development and the performance of the algorithm, which is discussed in detail. CCOMP supports general complex matrices, and its efficiency, applicability and validity is demonstrated to a variety of microwave applications.

The adventive status of Salvinia minima and S. molestain the southern United States and the related distribution of the weevil Cyrtobagous salviniae

USGS Publications Warehouse

Jacono, Colette C.; Davern, Tracy R.; Center, Ted D.

2001-01-01

The recent introduction of Salvinia molesta constitutes a serious threat to aquatic systems in the warm temperate regions of the United States. Salvinia minima, the only other member of Salviniaceae present in North America, is considered native by current floras. Evidence is presented which suggests that Salvinia minima was also introduced to North America, probably during the late 1920s and early 1930s. Likely sites of introduction and subsequent range expansions are identified. The accidentally introduced salvinia weevil, putatively Cyrtobagous salviniae, was found to occur widely on S. minima in Florida but is not established in other states. The disparate distribution of this Salvinia herbivore may account for the reduced aggressiveness of S. minima in Florida as compared to its troublesome growth in Texas and LOUisiana, where the weevil is not yet known.

VizieR Online Data Catalog: UY UMa and EF Boo compiled time of minima (Yu+, 2017)

NASA Astrophysics Data System (ADS)

Yu, Y.-X.; Zhang, X.-D.; Hu, K.; Xiang, F.-Y.

2017-11-01

In order to construct the (O-C) diagram to analyze the period change of UY UMa, we have performed a careful search for all available times of light minima. A total of 76 times of light minima were collected and listed in Table 2. >From the literatures and two well-known databases (i.e., the O-C gateway (http://var.astro.cz/ocgate) and the Lichtenknecker database of the BAV (http://www.bav-astro.de/LkDB/index.php)), we have collected a total of 75 available times of light minima for EF Boo, which are summarized in Table 3. (3 data files).

Fast-Flowering Mini-Maize: Seed to Seed in 60 Days

PubMed Central

McCaw, Morgan E.; Wallace, Jason G.; Albert, Patrice S.; Buckler, Edward S.; Birchler, James A.

2016-01-01

Two lines of Zea mays were developed as a short-generation model for maize. The Fast-Flowering Mini-Maize (FFMM) lines A and B are robust inbred lines with a significantly shorter generation time, much smaller stature, and better greenhouse adaptation than traditional maize varieties. Five generations a year are typical. FFMM is the result of a modified double-cross hybrid between four fast-flowering lines: Neuffer’s Early ACR (full color), Alexander’s Early Early Synthetic, Tom Thumb Popcorn, and Gaspe Flint, followed by selection for early flowering and desirable morphology throughout an 11-generation selfing regime. Lines A and B were derived from different progeny of the initial hybrid, and crosses between Mini-Maize A and B exhibit heterosis. The ancestry of each genomic region of Mini-Maize A and B was inferred from the four founder populations using genotyping by sequencing. Other genetic and genomic tools for these lines include karyotypes for both lines A and B, kernel genetic markers y1 (white endosperm) and R1-scm2 (purple endosperm and embryo) introgressed into Mini-Maize A, and ∼24× whole-genome resequencing data for Mini-Maize A. PMID:27440866

On Quasi-biennial Oscillations in Chromospheric Macrospicules and Their Potential Relation to the Global Solar Magnetic Field

NASA Astrophysics Data System (ADS)

Kiss, T. S.; Erdélyi, R.

2018-04-01

This study aims to provide further evidence for the potential influence of the global solar magnetic field on localized chromospheric jets, the macrospicules (MS). To find a connection between the long-term variation of properties of MS and other solar activity proxies, including, e.g., the temporal variation of the frequency shift of solar global oscillations, sunspot area, etc., a database overarching seven years of observations was compiled. This database contains 362 MS, based on observations at the 30.4 nm of the Atmospheric Imaging Assembly on board the Solar Dynamics Observatory. Three of the five investigated physical properties of MS show a clear long-term temporal variation after smoothing the raw data. Wavelet analysis of the temporal variation of maximum length, maximum area, and average velocity is carried out. The results reveal a strong pattern of periodicities at around 2 years (also referred to as quasi-biennial oscillations—QBOs). A comparison with solar activity proxies that also possess the properties of QBOs provides some interesting features: the minima and maxima of QBOs of MS properties occur at around the same epoch as the minima and maxima of these activity proxies. For most of the time span investigated, the oscillations are out of phase. This out-of-phase behavior was also corroborated by a cross-correlation analysis. These results suggest that the physical processes that generate and drive the long-term evolution of the global solar activity proxies may be coupled to the short-term local physical processes driving the macrospicules, and, therefore modulate the properties of local dynamics.

Computer aided detection of brain micro-bleeds in traumatic brain injury

NASA Astrophysics Data System (ADS)

van den Heuvel, T. L. A.; Ghafoorian, M.; van der Eerden, A. W.; Goraj, B. M.; Andriessen, T. M. J. C.; ter Haar Romeny, B. M.; Platel, B.

2015-03-01

Brain micro-bleeds (BMBs) are used as surrogate markers for detecting diffuse axonal injury in traumatic brain injury (TBI) patients. The location and number of BMBs have been shown to influence the long-term outcome of TBI. To further study the importance of BMBs for prognosis, accurate localization and quantification are required. The task of annotating BMBs is laborious, complex and prone to error, resulting in a high inter- and intra-reader variability. In this paper we propose a computer-aided detection (CAD) system to automatically detect BMBs in MRI scans of moderate to severe neuro-trauma patients. Our method consists of four steps. Step one: preprocessing of the data. Both susceptibility (SWI) and T1 weighted MRI scans are used. The images are co-registered, a brain-mask is generated, the bias field is corrected, and the image intensities are normalized. Step two: initial candidates for BMBs are selected as local minima in the processed SWI scans. Step three: feature extraction. BMBs appear as round or ovoid signal hypo-intensities on SWI. Twelve features are computed to capture these properties of a BMB. Step four: Classification. To identify BMBs from the set of local minima using their features, different classifiers are trained on a database of 33 expert annotated scans and 18 healthy subjects with no BMBs. Our system uses a leave-one-out strategy to analyze its performance. With a sensitivity of 90% and 1.3 false positives per BMB, our CAD system shows superior results compared to state-of-the-art BMB detection algorithms (developed for non-trauma patients).

Full Waveform Inversion for Seismic Velocity And Anelastic Losses in Heterogeneous Structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Askan, A.; /Carnegie Mellon U.; Akcelik, V.

2009-04-30

We present a least-squares optimization method for solving the nonlinear full waveform inverse problem of determining the crustal velocity and intrinsic attenuation properties of sedimentary valleys in earthquake-prone regions. Given a known earthquake source and a set of seismograms generated by the source, the inverse problem is to reconstruct the anelastic properties of a heterogeneous medium with possibly discontinuous wave velocities. The inverse problem is formulated as a constrained optimization problem, where the constraints are the partial and ordinary differential equations governing the anelastic wave propagation from the source to the receivers in the time domain. This leads to amore » variational formulation in terms of the material model plus the state variables and their adjoints. We employ a wave propagation model in which the intrinsic energy-dissipating nature of the soil medium is modeled by a set of standard linear solids. The least-squares optimization approach to inverse wave propagation presents the well-known difficulties of ill posedness and multiple minima. To overcome ill posedness, we include a total variation regularization functional in the objective function, which annihilates highly oscillatory material property components while preserving discontinuities in the medium. To treat multiple minima, we use a multilevel algorithm that solves a sequence of subproblems on increasingly finer grids with increasingly higher frequency source components to remain within the basin of attraction of the global minimum. We illustrate the methodology with high-resolution inversions for two-dimensional sedimentary models of the San Fernando Valley, under SH-wave excitation. We perform inversions for both the seismic velocity and the intrinsic attenuation using synthetic waveforms at the observer locations as pseudoobserved data.« less

A hybrid neural networks-fuzzy logic-genetic algorithm for grade estimation

NASA Astrophysics Data System (ADS)

Tahmasebi, Pejman; Hezarkhani, Ardeshir

2012-05-01

The grade estimation is a quite important and money/time-consuming stage in a mine project, which is considered as a challenge for the geologists and mining engineers due to the structural complexities in mineral ore deposits. To overcome this problem, several artificial intelligence techniques such as Artificial Neural Networks (ANN) and Fuzzy Logic (FL) have recently been employed with various architectures and properties. However, due to the constraints of both methods, they yield the desired results only under the specific circumstances. As an example, one major problem in FL is the difficulty of constructing the membership functions (MFs).Other problems such as architecture and local minima could also be located in ANN designing. Therefore, a new methodology is presented in this paper for grade estimation. This method which is based on ANN and FL is called "Coactive Neuro-Fuzzy Inference System" (CANFIS) which combines two approaches, ANN and FL. The combination of these two artificial intelligence approaches is achieved via the verbal and numerical power of intelligent systems. To improve the performance of this system, a Genetic Algorithm (GA) - as a well-known technique to solve the complex optimization problems - is also employed to optimize the network parameters including learning rate, momentum of the network and the number of MFs for each input. A comparison of these techniques (ANN, Adaptive Neuro-Fuzzy Inference System or ANFIS) with this new method (CANFIS-GA) is also carried out through a case study in Sungun copper deposit, located in East-Azerbaijan, Iran. The results show that CANFIS-GA could be a faster and more accurate alternative to the existing time-consuming methodologies for ore grade estimation and that is, therefore, suggested to be applied for grade estimation in similar problems.

A hybrid neural networks-fuzzy logic-genetic algorithm for grade estimation

PubMed Central

Tahmasebi, Pejman; Hezarkhani, Ardeshir

2012-01-01

The grade estimation is a quite important and money/time-consuming stage in a mine project, which is considered as a challenge for the geologists and mining engineers due to the structural complexities in mineral ore deposits. To overcome this problem, several artificial intelligence techniques such as Artificial Neural Networks (ANN) and Fuzzy Logic (FL) have recently been employed with various architectures and properties. However, due to the constraints of both methods, they yield the desired results only under the specific circumstances. As an example, one major problem in FL is the difficulty of constructing the membership functions (MFs).Other problems such as architecture and local minima could also be located in ANN designing. Therefore, a new methodology is presented in this paper for grade estimation. This method which is based on ANN and FL is called “Coactive Neuro-Fuzzy Inference System” (CANFIS) which combines two approaches, ANN and FL. The combination of these two artificial intelligence approaches is achieved via the verbal and numerical power of intelligent systems. To improve the performance of this system, a Genetic Algorithm (GA) – as a well-known technique to solve the complex optimization problems – is also employed to optimize the network parameters including learning rate, momentum of the network and the number of MFs for each input. A comparison of these techniques (ANN, Adaptive Neuro-Fuzzy Inference System or ANFIS) with this new method (CANFIS–GA) is also carried out through a case study in Sungun copper deposit, located in East-Azerbaijan, Iran. The results show that CANFIS–GA could be a faster and more accurate alternative to the existing time-consuming methodologies for ore grade estimation and that is, therefore, suggested to be applied for grade estimation in similar problems. PMID:25540468

Whole-body Motion Planning with Simple Dynamics and Full Kinematics

DTIC Science & Technology

2014-08-01

optimizations can take an excessively long time to run, and may also suffer from local minima. Thus, this approach can become intractable for complex robots...motions like jumping and climbing. Additionally, the point-mass model suggests that the centroidal angular momentum is zero, which is not valid for motions...use in the DARPA Robotics Challenge. A. Jumping Our first example is to command the robot to jump off the ground, as illustrated in Fig.4. We assign

An Evaluation of the Sniffer Global Optimization Algorithm Using Standard Test Functions

NASA Astrophysics Data System (ADS)

Butler, Roger A. R.; Slaminka, Edward E.

1992-03-01

The performance of Sniffer—a new global optimization algorithm—is compared with that of Simulated Annealing. Using the number of function evaluations as a measure of efficiency, the new algorithm is shown to be significantly better at finding the global minimum of seven standard test functions. Several of the test functions used have many local minima and very steep walls surrounding the global minimum. Such functions are intended to thwart global minimization algorithms.

Metastability in the Spin-1 Blume-Emery-Griffiths Model within Constant Coupling Approximation

NASA Astrophysics Data System (ADS)

Ekiz, C.

2017-02-01

In this paper, the equilibrium properties of spin-1 Blume-Emery-Griffiths model are studied by using constant-coupling approximation. The dipolar and quadrupolar order parameters, the stable, metastable and unstable states and free energy of the model are investigated. The states are defined in terms of local minima of the free energy of system. The numerical calculations are presented for several values of exchange interactions on the simple cubic lattice with q = 6.

Training product unit neural networks with genetic algorithms

NASA Technical Reports Server (NTRS)

Janson, D. J.; Frenzel, J. F.; Thelen, D. C.

1991-01-01

The training of product neural networks using genetic algorithms is discussed. Two unusual neural network techniques are combined; product units are employed instead of the traditional summing units and genetic algorithms train the network rather than backpropagation. As an example, a neural netork is trained to calculate the optimum width of transistors in a CMOS switch. It is shown how local minima affect the performance of a genetic algorithm, and one method of overcoming this is presented.

A statistical-based scheduling algorithm in automated data path synthesis

NASA Technical Reports Server (NTRS)

Jeon, Byung Wook; Lursinsap, Chidchanok

1992-01-01

In this paper, we propose a new heuristic scheduling algorithm based on the statistical analysis of the cumulative frequency distribution of operations among control steps. It has a tendency of escaping from local minima and therefore reaching a globally optimal solution. The presented algorithm considers the real world constraints such as chained operations, multicycle operations, and pipelined data paths. The result of the experiment shows that it gives optimal solutions, even though it is greedy in nature.

Nonclassicality and decoherence of photon-added squeezed coherent Schrödinger kitten states in a Kerr medium

NASA Astrophysics Data System (ADS)

Chakrabarti, R.; Yogesh, V.

2018-01-01

We study the nonclassicality of the evolution of a superposition of an arbitrary number of photon-added squeezed coherent Schrödinger cat states in a nonlinear Kerr medium. The nonlinearity of the medium gives rise to the periodicities of the quantities such as the Wehrl entropy SQ and the negativity δW of the W-distribution, and a series of local minima of these quantities arise at the rational submultiples of the said period. At these local minima the evolving state coincides with the transient Yurke-Stoler type of photon-added squeezed kitten states, which, for the choice of the phase space variables reflecting their macroscopic nature, show extremely short-lived behavior. Proceeding further we provide the closed form tomograms, which furnish the alternate description of these short-lived states. The increasing complexity in the kitten formations induces more number of interference terms that trigger more quantumness of the corresponding states. The nonclassical depth of the photon-added squeezed kitten states are observed to be of maximum possible value. Employing the Lindblad master equation approach we study the amplitude and the phase damping models for the initial state considered here. In the phase damping model the nonclassicality is not completely erased even in the long time limit when the dynamical quantities, such as the negativity δW and the tomogram, assume nontrivial asymptotic values.

Pathways to exotic metastable silicon allotropes

DOE PAGES

Haberl, Bianca; Strobel, Timothy A.; Bradby, Jodie E.

2016-09-27

The Group 14 element silicon possesses a complex free-energy landscape with many (local) minima, allowing for the formation of a variety of unusual structures, some of which may be stabilized at ambient conditions. Such exotic silicon allotropes represent a significant opportunity to address the ever-increasing demand for novel materials with tailored functionality since these exotic forms are expected to exhibit superlative properties including optimized band gaps for solar power conversion. The application of pressure is a well-recognized and uniquely powerful method to access exotic states of silicon since it promotes large changes to atomic bonding. Conventional high-pressure syntheses, however, lackmore » the capability to access many of these local minima and only four forms of exotic silicon allotropes have been recovered over the last 50 years. However, more recently, signifi- cant advances in high pressure methodologies and the use of novel precursor materials have yielded at least three more recoverable exotic Si structures. This review aims to give an overview of these innovative methods of high-pressure application and precursor selection and the recent discoveries of new Si allotropes. The background context of the conventional pressure methods and multitude of predicted new phases are also provided. Furthermore, this review also offers a perspective for possible access to many further exotic functional allotropes not only of silicon but also of other materials, in a technologically feasible manner« less

Learning, memory, and the role of neural network architecture.

PubMed

Hermundstad, Ann M; Brown, Kevin S; Bassett, Danielle S; Carlson, Jean M

2011-06-01

The performance of information processing systems, from artificial neural networks to natural neuronal ensembles, depends heavily on the underlying system architecture. In this study, we compare the performance of parallel and layered network architectures during sequential tasks that require both acquisition and retention of information, thereby identifying tradeoffs between learning and memory processes. During the task of supervised, sequential function approximation, networks produce and adapt representations of external information. Performance is evaluated by statistically analyzing the error in these representations while varying the initial network state, the structure of the external information, and the time given to learn the information. We link performance to complexity in network architecture by characterizing local error landscape curvature. We find that variations in error landscape structure give rise to tradeoffs in performance; these include the ability of the network to maximize accuracy versus minimize inaccuracy and produce specific versus generalizable representations of information. Parallel networks generate smooth error landscapes with deep, narrow minima, enabling them to find highly specific representations given sufficient time. While accurate, however, these representations are difficult to generalize. In contrast, layered networks generate rough error landscapes with a variety of local minima, allowing them to quickly find coarse representations. Although less accurate, these representations are easily adaptable. The presence of measurable performance tradeoffs in both layered and parallel networks has implications for understanding the behavior of a wide variety of natural and artificial learning systems.

Thermodynamic stability of biomolecules and evolution.

PubMed

Chakravarty, Ashim K

2017-08-01

The thermodynamic stability of biomolecules in the perspective of evolution is a complex issue and needs discussion. Intra molecular bonds maintain the structure and the state of internal energy (E) of a biomolecule at "local minima". In this communication, possibility of loss in internal energy level of a biomolecule through the changes in the bonds has been discussed, that might earn more thermodynamic stability for the molecule. In the process variations in structure and functions of the molecule could occur. Thus, E of a biomolecule is likely to have energy stature for minimization. Such change in energy status is an intrinsic factor for evolving biomolecules buying more stability and generating variations in the structure and function of DNA molecules undergoing natural selection. Thus, the variations might very well contribute towards the process of evolution. A brief discussion on conserved sequence in the light of proposition in this communication has been made at the end. Extension of the idea may resolve certain standing problems in evolution, such as maintenance of conserved sequences in genome of diverse species, pre- versus post adaptive mutations, 'orthogenesis', etc. Copyright © 2017 Elsevier Ltd. All rights reserved.

Improved numerical methods for infinite spin chains with long-range interactions

NASA Astrophysics Data System (ADS)

Nebendahl, V.; Dür, W.

2013-02-01

We present several improvements of the infinite matrix product state (iMPS) algorithm for finding ground states of one-dimensional quantum systems with long-range interactions. As a main ingredient, we introduce the superposed multioptimization method, which allows an efficient optimization of exponentially many MPS of different lengths at different sites all in one step. Here, the algorithm becomes protected against position-dependent effects as caused by spontaneously broken translational invariance. So far, these have been a major obstacle to convergence for the iMPS algorithm if no prior knowledge of the system's translational symmetry was accessible. Further, we investigate some more general methods to speed up calculations and improve convergence, which might be partially interesting in a much broader context, too. As a more special problem, we also look into translational invariant states close to an invariance-breaking phase transition and show how to avoid convergence into wrong local minima for such systems. Finally, we apply these methods to polar bosons with long-range interactions. We calculate several detailed Devil's staircases with the corresponding phase diagrams and investigate some supersolid properties.

Deep Convolutional Extreme Learning Machine and Its Application in Handwritten Digit Classification

PubMed Central

Yang, Xinyi

2016-01-01

In recent years, some deep learning methods have been developed and applied to image classification applications, such as convolutional neuron network (CNN) and deep belief network (DBN). However they are suffering from some problems like local minima, slow convergence rate, and intensive human intervention. In this paper, we propose a rapid learning method, namely, deep convolutional extreme learning machine (DC-ELM), which combines the power of CNN and fast training of ELM. It uses multiple alternate convolution layers and pooling layers to effectively abstract high level features from input images. Then the abstracted features are fed to an ELM classifier, which leads to better generalization performance with faster learning speed. DC-ELM also introduces stochastic pooling in the last hidden layer to reduce dimensionality of features greatly, thus saving much training time and computation resources. We systematically evaluated the performance of DC-ELM on two handwritten digit data sets: MNIST and USPS. Experimental results show that our method achieved better testing accuracy with significantly shorter training time in comparison with deep learning methods and other ELM methods. PMID:27610128

Brain-Inspired Constructive Learning Algorithms with Evolutionally Additive Nonlinear Neurons

NASA Astrophysics Data System (ADS)

Fang, Le-Heng; Lin, Wei; Luo, Qiang

In this article, inspired partially by the physiological evidence of brain’s growth and development, we developed a new type of constructive learning algorithm with evolutionally additive nonlinear neurons. The new algorithms have remarkable ability in effective regression and accurate classification. In particular, the algorithms are able to sustain a certain reduction of the loss function when the dynamics of the trained network are bogged down in the vicinity of the local minima. The algorithm augments the neural network by adding only a few connections as well as neurons whose activation functions are nonlinear, nonmonotonic, and self-adapted to the dynamics of the loss functions. Indeed, we analytically demonstrate the reduction dynamics of the algorithm for different problems, and further modify the algorithms so as to obtain an improved generalization capability for the augmented neural networks. Finally, through comparing with the classical algorithm and architecture for neural network construction, we show that our constructive learning algorithms as well as their modified versions have better performances, such as faster training speed and smaller network size, on several representative benchmark datasets including the MNIST dataset for handwriting digits.

Unsupervised sputum color image segmentation for lung cancer diagnosis based on a Hopfield neural network

NASA Astrophysics Data System (ADS)

Sammouda, Rachid; Niki, Noboru; Nishitani, Hiroshi; Nakamura, S.; Mori, Shinichiro

1997-04-01

The paper presents a method for automatic segmentation of sputum cells with color images, to develop an efficient algorithm for lung cancer diagnosis based on a Hopfield neural network. We formulate the segmentation problem as a minimization of an energy function constructed with two terms, the cost-term as a sum of squared errors, and the second term a temporary noise added to the network as an excitation to escape certain local minima with the result of being closer to the global minimum. To increase the accuracy in segmenting the regions of interest, a preclassification technique is used to extract the sputum cell regions within the color image and remove those of the debris cells. The former is then given with the raw image to the input of Hopfield neural network to make a crisp segmentation by assigning each pixel to label such as background, cytoplasm, and nucleus. The proposed technique has yielded correct segmentation of complex scene of sputum prepared by ordinary manual staining method in most of the tested images selected from our database containing thousands of sputum color images.

Deep Convolutional Extreme Learning Machine and Its Application in Handwritten Digit Classification.

PubMed

Pang, Shan; Yang, Xinyi

2016-01-01

In recent years, some deep learning methods have been developed and applied to image classification applications, such as convolutional neuron network (CNN) and deep belief network (DBN). However they are suffering from some problems like local minima, slow convergence rate, and intensive human intervention. In this paper, we propose a rapid learning method, namely, deep convolutional extreme learning machine (DC-ELM), which combines the power of CNN and fast training of ELM. It uses multiple alternate convolution layers and pooling layers to effectively abstract high level features from input images. Then the abstracted features are fed to an ELM classifier, which leads to better generalization performance with faster learning speed. DC-ELM also introduces stochastic pooling in the last hidden layer to reduce dimensionality of features greatly, thus saving much training time and computation resources. We systematically evaluated the performance of DC-ELM on two handwritten digit data sets: MNIST and USPS. Experimental results show that our method achieved better testing accuracy with significantly shorter training time in comparison with deep learning methods and other ELM methods.

Optimising mobile phase composition, its flow-rate and column temperature in HPLC using taboo search.

PubMed

Guillaume, Y C; Peyrin, E

2000-03-06

A chemometric methodology is proposed to study the separation of seven p-hydroxybenzoic esters in reversed phase liquid chromatography (RPLC). Fifteen experiments were found to be necessary to find a mathematical model which linked a novel chromatographic response function (CRF) with the column temperature, the water fraction in the mobile phase and its flow rate. The CRF optimum was determined using a new algorithm based on Glover's taboo search (TS). A flow-rate of 0.9 ml min(-1) with a water fraction of 0.64 in the ACN-water mixture and a column temperature of 10 degrees C gave the most efficient separation conditions. The usefulness of TS was compared with the pure random search (PRS) and simplex search (SS). As demonstrated by calculations, the algorithm avoids entrapment in local minima and continues the search to give a near-optimal final solution. Unlike other methods of global optimisation, this procedure is generally applicable, easy to implement, derivative free, conceptually simple and could be used in the future for much more complex optimisation problems.

Apparatus for separating particles utilizing engineered acoustic contrast capture particles

DOEpatents

Kaduchak, Gregory; Ward, Michael D

2014-10-21

An apparatus for separating particles from a medium includes a capillary defining a flow path therein that is in fluid communication with a medium source. The medium source includes engineered acoustic contrast capture particle having a predetermined acoustic contrast. The apparatus includes a vibration generator that is operable to produce at least one acoustic field within the flow path. The acoustic field produces a force potential minima for positive acoustic contrast particles and a force potential minima for negative acoustic contrast particles in the flow path and drives the engineered acoustic contrast capture particles to either the force potential minima for positive acoustic contrast particles or the force potential minima for negative acoustic contrast particles.

Apparatus for separating particles utilizing engineered acoustic contrast capture particles

DOEpatents

Kaduchak, Gregory [Los Alamos, NM; Ward, Michael D [Los Alamos, NM

2011-12-27

An apparatus for separating particles from a medium includes a capillary defining a flow path therein that is in fluid communication with a medium source. The medium source includes engineered acoustic contrast capture particle having a predetermined acoustic contrast. The apparatus includes a vibration generator that is operable to produce at least one acoustic field within the flow path. The acoustic field produces a force potential minima for positive acoustic contrast particles and a force potential minima for negative acoustic contrast particles in the flow path and drives the engineered acoustic contrast capture particles to either the force potential minima for positive acoustic contrast particles or the force potential minima for negative acoustic contrast particles.

Quantum Dynamics Study of the Potential Energy Minima Effect on Energy Efficiency for the F- + CH3Cl → FCH3 + Cl- Reaction.

PubMed

Li, Yida; Wang, Yuping; Wang, Dunyou

2017-04-13

The Polanyi rules on the energy efficiency on reactivity are summarized solely from the locations of barriers on the potential energy surfaces. Here, our quantum dynamics study for the F - + CH 3 Cl → FCH 3 + Cl - reaction shows that the two potential energy minima in the entrance channel on the potential energy surface play an essential role in energy efficiency on reactivity. The reactivity of this reaction is dominated by the low collision energies where two distinctive reaction mechanisms involve the two minima in the entrance channel. Overall, the Cl-CH 3 stretching motion and C-H 3 umbrella motion both are more efficient than the translational motion in promoting this reaction. Although this reaction has a negative energy barrier, our study shows that it is the minima in the entrance channel, together with the energy barrier relative to these minima, that determine the energy efficacy on reactivity.

More efficient evolutionary strategies for model calibration with watershed model for demonstration

NASA Astrophysics Data System (ADS)

Baggett, J. S.; Skahill, B. E.

2008-12-01

Evolutionary strategies allow automatic calibration of more complex models than traditional gradient based approaches, but they are more computationally intensive. We present several efficiency enhancements for evolution strategies, many of which are not new, but when combined have been shown to dramatically decrease the number of model runs required for calibration of synthetic problems. To reduce the number of expensive model runs we employ a surrogate objective function for an adaptively determined fraction of the population at each generation (Kern et al., 2006). We demonstrate improvements to the adaptive ranking strategy that increase its efficiency while sacrificing little reliability and further reduce the number of model runs required in densely sampled parts of parameter space. Furthermore, we include a gradient individual in each generation that is usually not selected when the search is in a global phase or when the derivatives are poorly approximated, but when selected near a smooth local minimum can dramatically increase convergence speed (Tahk et al., 2007). Finally, the selection of the gradient individual is used to adapt the size of the population near local minima. We show, by incorporating these enhancements into the Covariance Matrix Adaption Evolution Strategy (CMAES; Hansen, 2006), that their synergetic effect is greater than their individual parts. This hybrid evolutionary strategy exploits smooth structure when it is present but degrades to an ordinary evolutionary strategy, at worst, if smoothness is not present. Calibration of 2D-3D synthetic models with the modified CMAES requires approximately 10%-25% of the model runs of ordinary CMAES. Preliminary demonstration of this hybrid strategy will be shown for watershed model calibration problems. Hansen, N. (2006). The CMA Evolution Strategy: A Comparing Review. In J.A. Lozano, P. Larrañga, I. Inza and E. Bengoetxea (Eds.). Towards a new evolutionary computation. Advances in estimation of distribution algorithms. pp. 75-102, Springer Kern, S., N. Hansen and P. Koumoutsakos (2006). Local Meta-Models for Optimization Using Evolution Strategies. In Ninth International Conference on Parallel Problem Solving from Nature PPSN IX, Proceedings, pp.939-948, Berlin: Springer. Tahk, M., Woo, H., and Park. M, (2007). A hybrid optimization of evolutionary and gradient search. Engineering Optimization, (39), 87-104.

Comparison of solar activity during last two minima on turn of Activity Cycles 22/23 and 23/24

NASA Astrophysics Data System (ADS)

Gryciuk, Magdalena; Gburek, Szymon; Siarkowski, Marek; Podgorski, Piotr; Sylwester, Janusz; Farnik, Frantisek

2013-07-01

The subject of our work is the review and comparison of solar activity during the last two solar minima that occurred between recent activity cycles. We use the soft X-ray global solar corona observations covering the two nine-months long time intervals in 1997/98 and 2009. Data from RF15-I multichannel photometer are used for the penultimate minimum. For the last unusually deep and prolonged solar activity minimum in 2009 the data from SphinX spectrophotometer are used. Comparison of measurements from both minima takes place in the overlapping energy range 2-15 keV. We focus on the active region formation, evolution and flaring productivity during respective minima.

Diurnal water relations of walnut trees - Implications for remote sensing

NASA Technical Reports Server (NTRS)

Weber, James A.; Ustin, Susan L.

1991-01-01

Leaflet water content (WC), relative water content (RWC), and water potential, Phi(lf) were measured as indicators of diurnal change in tree water status in an experimental walnut orchard receiving two irrigation treatments: 100 and 33 percent of potential evapotranspiration (PET). Diurnal change was greatest in Phi(lf) throughout the experimental period, with minima occurring each day in early to mid-afternoon and maxima between midnight and sunrise. Leaflet WC and RWC were lower in the afternoon than at night, but had greater variability so that the diurnal pattern was not as clear. Comparison between the pattern of Phi(lf) and dielectric constants (DCs) measured from probes inserted 2 cm into a tree hole showed that both declined nearly in parallel in the morning. Phi(lf) recovered more rapidly than DC in the afternoon. This temporal discrepancy could be caused by cavitation of xylem elements in the vicinity of the DC probe. Microwave backscatter for L- and X-bands also measured diurnal variation that had local minima in the afternoon, but the pattern among wavelength and polarization signatures was complex.

Robust Multiple Linear Regression.

DTIC Science & Technology

1982-12-01

difficulty, but it might have more solutions corresponding to local minima. Influence Function of M-Estimates The influence function describes the effect...distributionn n function. In case of M-Estimates the influence function was found to be pro- portional to and given as T(X F)) " C(xpF,T) = .(X.T(F) F(dx...where the inverse of any distribution function F is defined in the usual way as F- (s) = inf{x IF(x) > s) 0<sə Influence Function of L-Estimates In a

Rotation-libration in a hierarchic supramolecular rotor-stator system: arrhenius activation and retardation by local interaction.

PubMed

Wahl, Markus; Stöhr, Meike; Spillmann, Hannes; Jung, Thomas A; Gade, Lutz H

2007-04-07

Fourfold symmetric zinc-octaethylporphyrin (OEP) has been incorporated in the holes of the hexagonal molecular network generated by thermal dehydrogenation of 4,9-diaminoperylene-quinone-3,10-diimine (DPDI) on a Cu(111) surface and displayed hindered rotation; the reorganization between the potential minima, a rotation-libration, which is characterized by an activation energy of ED=0.17+/-0.03 eV, has been monitored in the STM tunnelling currents as a bi-state "switching".

The motion of a charged particle on a Riemannian surface under a non-zero magnetic field

NASA Astrophysics Data System (ADS)

Castilho, Cesar Augusto Rodrigues

In this thesis we study the motion of a charged particle on a Riemmanian surface under the influence of a positive magnetic field B. Using Moser's Twist Theorem and ideas from classical pertubation theory we find sufficient conditions to perpetually trap the motion of a particle with a sufficient large charge in a neighborhood of a level set of the magnetic field. The conditions on the level set of the magnetic field that guarantee the trapping are local and hold near all non- degenerate critical local minima or maxima of B. Using sympletic reduction we apply the results of our work to certain S1-invariant magnetic fields on R3.

The Motion of a Charged Particle on a Riemannian Surface under a Non-Zero Magnetic Field

NASA Astrophysics Data System (ADS)

Castilho, César

2001-03-01

In this paper we study the motion of a charged particle on a Riemmanian surface under the influence of a positive magnetic field B. Using Moser's Twist Theorem and ideas from classical pertubation theory we find sufficient conditions to perpetually trap the motion of a particle with a sufficient large charge in a neighborhood of a level set of the magnetic field. The conditions on the level set of the magnetic field that guarantee the trapping are local and hold near all non-degenerate critical local minima or maxima of B. Using symplectic reduction we apply the results of our work to certain S1-invariant magnetic fields on R3.

Coherent electronic wave packet motion in C(60) controlled by the waveform and polarization of few-cycle laser fields.

PubMed

Li, H; Mignolet, B; Wachter, G; Skruszewicz, S; Zherebtsov, S; Süssmann, F; Kessel, A; Trushin, S A; Kling, Nora G; Kübel, M; Ahn, B; Kim, D; Ben-Itzhak, I; Cocke, C L; Fennel, T; Tiggesbäumker, J; Meiwes-Broer, K-H; Lemell, C; Burgdörfer, J; Levine, R D; Remacle, F; Kling, M F

2015-03-27

Strong laser fields can be used to trigger an ultrafast molecular response that involves electronic excitation and ionization dynamics. Here, we report on the experimental control of the spatial localization of the electronic excitation in the C_{60} fullerene exerted by an intense few-cycle (4 fs) pulse at 720 nm. The control is achieved by tailoring the carrier-envelope phase and the polarization of the laser pulse. We find that the maxima and minima of the photoemission-asymmetry parameter along the laser-polarization axis are synchronized with the localization of the coherent electronic wave packet at around the time of ionization.

Pivot methods for global optimization

NASA Astrophysics Data System (ADS)

Stanton, Aaron Fletcher

A new algorithm is presented for the location of the global minimum of a multiple minima problem. It begins with a series of randomly placed probes in phase space, and then uses an iterative redistribution of the worst probes into better regions of phase space until a chosen convergence criterion is fulfilled. The method quickly converges, does not require derivatives, and is resistant to becoming trapped in local minima. Comparison of this algorithm with others using a standard test suite demonstrates that the number of function calls has been decreased conservatively by a factor of about three with the same degrees of accuracy. Two major variations of the method are presented, differing primarily in the method of choosing the probes that act as the basis for the new probes. The first variation, termed the lowest energy pivot method, ranks all probes by their energy and keeps the best probes. The probes being discarded select from those being kept as the basis for the new cycle. In the second variation, the nearest neighbor pivot method, all probes are paired with their nearest neighbor. The member of each pair with the higher energy is relocated in the vicinity of its neighbor. Both methods are tested against a standard test suite of functions to determine their relative efficiency, and the nearest neighbor pivot method is found to be the more efficient. A series of Lennard-Jones clusters is optimized with the nearest neighbor method, and a scaling law is found for cpu time versus the number of particles in the system. The two methods are then compared more explicitly, and finally a study in the use of the pivot method for solving the Schroedinger equation is presented. The nearest neighbor method is found to be able to solve the ground state of the quantum harmonic oscillator from a pure random initialization of the wavefunction.

Applications of Hilbert Spectral Analysis for Speech and Sound Signals

NASA Technical Reports Server (NTRS)

Huang, Norden E.

2003-01-01

A new method for analyzing nonlinear and nonstationary data has been developed, and the natural applications are to speech and sound signals. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time, which give sharp identifications of imbedded structures. This method invention can be used to process all acoustic signals. Specifically, it can process the speech signals for Speech synthesis, Speaker identification and verification, Speech recognition, and Sound signal enhancement and filtering. Additionally, as the acoustical signals from machinery are essentially the way the machines are talking to us. Therefore, the acoustical signals, from the machines, either from sound through air or vibration on the machines, can tell us the operating conditions of the machines. Thus, we can use the acoustic signal to diagnosis the problems of machines.

A multi-populations multi-strategies differential evolution algorithm for structural optimization of metal nanoclusters

NASA Astrophysics Data System (ADS)

Fan, Tian-E.; Shao, Gui-Fang; Ji, Qing-Shuang; Zheng, Ji-Wen; Liu, Tun-dong; Wen, Yu-Hua

2016-11-01

Theoretically, the determination of the structure of a cluster is to search the global minimum on its potential energy surface. The global minimization problem is often nondeterministic-polynomial-time (NP) hard and the number of local minima grows exponentially with the cluster size. In this article, a multi-populations multi-strategies differential evolution algorithm has been proposed to search the globally stable structure of Fe and Cr nanoclusters. The algorithm combines a multi-populations differential evolution with an elite pool scheme to keep the diversity of the solutions and avoid prematurely trapping into local optima. Moreover, multi-strategies such as growing method in initialization and three differential strategies in mutation are introduced to improve the convergence speed and lower the computational cost. The accuracy and effectiveness of our algorithm have been verified by comparing the results of Fe clusters with Cambridge Cluster Database. Meanwhile, the performance of our algorithm has been analyzed by comparing the convergence rate and energy evaluations with the classical DE algorithm. The multi-populations, multi-strategies mutation and growing method in initialization in our algorithm have been considered respectively. Furthermore, the structural growth pattern of Cr clusters has been predicted by this algorithm. The results show that the lowest-energy structure of Cr clusters contains many icosahedra, and the number of the icosahedral rings rises with increasing size.

Minima in generalized oscillator strengths for initially excited hydrogen-like atoms

NASA Technical Reports Server (NTRS)

Matsuzawa, M.; Omidvar, K.; Inokuti, M.

1976-01-01

Generalized oscillator strengths for transitions from an initially excited state of a hydrogenic atom to final states (either discrete or continuum) have complicated structures, including minima and shoulders, as functions of the momentum transfer. Extensive calculations carried out in the present work have revealed certain systematics of these structures. Some implications of the minima to the energy dependence of the inner-shell ionization cross section of heavy atoms by proton impact are discussed.

Optimized System Identification

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Longman, Richard W.

1999-01-01

In system identification, one usually cares most about finding a model whose outputs are as close as possible to the true system outputs when the same input is applied to both. However, most system identification algorithms do not minimize this output error. Often they minimize model equation error instead, as in typical least-squares fits using a finite-difference model, and it is seen here that this distinction is significant. Here, we develop a set of system identification algorithms that minimize output error for multi-input/multi-output and multi-input/single-output systems. This is done with sequential quadratic programming iterations on the nonlinear least-squares problems, with an eigendecomposition to handle indefinite second partials. This optimization minimizes a nonlinear function of many variables, and hence can converge to local minima. To handle this problem, we start the iterations from the OKID (Observer/Kalman Identification) algorithm result. Not only has OKID proved very effective in practice, it minimizes an output error of an observer which has the property that as the data set gets large, it converges to minimizing the criterion of interest here. Hence, it is a particularly good starting point for the nonlinear iterations here. Examples show that the methods developed here eliminate the bias that is often observed using any system identification methods of either over-estimating or under-estimating the damping of vibration modes in lightly damped structures.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mishra, P.; Purdue University, West Lafayette, Indiana 47907; Verma, K.

Borazine is isoelectronic with benzene and is popularly referred to as inorganic benzene. The study of non-covalent interactions with borazine and comparison with its organic counterpart promises to show interesting similarities and differences. The motivation of the present study of the borazine-water interaction, for the first time, stems from such interesting possibilities. Hydrogen-bonded complexes of borazine and water were studied using matrix isolation infrared spectroscopy and quantum chemical calculations. Computations were performed at M06-2X and MP2 levels of theory using 6-311++G(d,p) and aug-cc-pVDZ basis sets. At both the levels of theory, the complex involving an N–H⋯O interaction, where the N–Hmore » of borazine serves as the proton donor to the oxygen of water was found to be the global minimum, in contrast to the benzene-water system, which showed an H–π interaction. The experimentally observed infrared spectra of the complexes corroborated well with our computations for the complex corresponding to the global minimum. In addition to the global minimum, our computations also located two local minima on the borazine-water potential energy surface. Of the two local minima, one corresponded to a structure where the water was the proton donor to the nitrogen of borazine, approaching the borazine ring from above the plane of the ring; a structure that resembled the global minimum in the benzene-water H–π complex. The second local minimum corresponded to an interaction of the oxygen of water with the boron of borazine, which can be termed as the boron bond. Clearly the borazine-water system presents a richer landscape than the benzene-water system.« less

Conformational Analysis of Retinoic Acids: Effects of Steric Interactions on Nonplanar Conjugated Polyenes

PubMed Central

Cox, Bryan D.; Muccio, Donald D.; Hamilton, Tracy P.

2013-01-01

Retinoic acids and other vitamin A analogs contain a trimethylcyclohexenyl ring in conjugation with a polyene chain joined at carbon-6 (C6) and carbon-7 (C7). A MP2-SCS/cc-pVDZ// B3LYP/6-31G(d) 2-D potential energy surface was computed for all-trans retinoic acid, which had 6 minima (3 enantiomeric pairs). The global minima were distorted s-gauche enantiomers (6–7 = 53°) with half-chair conformations of the ring. Distorted s-gauche enantiomers (6–7 = 55°) with inverted half-chair ring conformations were 1.7 kJ/mol above the global minima. The s-trans enantiomers (6–7 = 164°) were 11.3 kJ/mol above the global minima. Steric energies were computed by the method of Guo and Karplus to identify key structural elements in retinoic acids which determines their conformation. Small molecule crystal structures in the CCDC database with trimethylcyclohexenyl ring and exocyclic double bonds have ring-chain geometries near to one of the 6 energy minima of retinoic acids, except for retinaldehyde iminium cations. PMID:25798372

Conformational Analysis of Retinoic Acids: Effects of Steric Interactions on Nonplanar Conjugated Polyenes.

PubMed

Cox, Bryan D; Muccio, Donald D; Hamilton, Tracy P

2013-05-01

Retinoic acids and other vitamin A analogs contain a trimethylcyclohexenyl ring in conjugation with a polyene chain joined at carbon-6 (C6) and carbon-7 (C7). A MP2-SCS/cc-pVDZ// B3LYP/6-31G(d) 2-D potential energy surface was computed for all- trans retinoic acid, which had 6 minima (3 enantiomeric pairs). The global minima were distorted s-gauche enantiomers ( 6-7 = 53°) with half-chair conformations of the ring. Distorted s-gauche enantiomers ( 6-7 = 55°) with inverted half-chair ring conformations were 1.7 kJ/mol above the global minima. The s-trans enantiomers ( 6-7 = 164°) were 11.3 kJ/mol above the global minima. Steric energies were computed by the method of Guo and Karplus to identify key structural elements in retinoic acids which determines their conformation. Small molecule crystal structures in the CCDC database with trimethylcyclohexenyl ring and exocyclic double bonds have ring-chain geometries near to one of the 6 energy minima of retinoic acids, except for retinaldehyde iminium cations.

Identity of Ṭaṅkārī (Physalis Minima Linn.) in Ayurvedic Classics: A Literature Review

PubMed Central

Kallianpur, Supriya S; Gokarn, Rohit A; Rajashekhar, N

2016-01-01

Proper identification of drugs and their use in proper doses are important for successful treatment. Physalis minima Linn commonly known as country gooseberry has anti-cancerous, anti-diabetic, analgesic, antipyretic and anti-inflammatory potentials. The present paper is aimed to ascertain the proper identity of Ṭaṅkārī (Physalis minima Linn.) in Ayurvedic classics by a meticulous search and hence a review of the drug Ṭaṅkārī (Physalis minima Linn) was carried out in the texts of Ayurveda, modern literature, journals and online publications. The result of the search showed that the name “Ṭaṅkārī” is not found in Vedic lore. In Saṃhitās, it is mentioned in Bhāvaprakāśa. Reference of the drug “Śārṅgeṣṭhā” is found in Bṛhattrayī, Bhela, Kāśyapa, Cakradatta and Vaṅgasena. It is variously named as Cirapoṭikā, Kākatikta, and Vāyasī by ḍalhaṇa and he describes it as gaura (pale), vartula (round), and as having avaguṇṭhita/veṣṭhita (covered) fruit which matches the description of Ṭaṅkārī (P. minima Linn). A search for terms Kākatikta and Vāyasī showed Kākatikta to be synonymous to Śārṅgeṣṭhā and Vāyasī to be synonymous to both Kākatikta and Kākamācī (Solanum nigrum). Madanapāla and Śāligrāma Nighaṇṭus have mentioned the name Cirapoṭikā to be synonymous with Ṭaṅkārī. Śodhala has used the term Parpoṭī as a synonym of Ṭaṅkārī, which is the Gujarati name of P. minima Linn. Recent authors have considered Śārṅgeṣṭhā as either P. minima or Cardiospermum helicabum. The regional names of P. minima are Cirpoṭi (Hindi), Cirboli (Marathi), also the folklore uses and pharmacological activities of P. minima are in accordance with the indications of Śārṅgeṣṭhā in classics. Thus with a complete review of both Ayurveda and modern literatures, it can be concluded that the drug mentioned as Ṭaṅkārī in Bhāvaprakāśa is the same as Śārṅgeṣṭhā mentioned in the classics. Cirapoṭikā and Kākatikta are its synonyms. Cardiospermum helicabum is Karṇaspoṭha, and hence Śārṅgeṣṭhā of classics is P. minima which is supported by the regional names, pharmacological activity and folklore claims. PMID:28182025

Foraging on the potential energy surface: a swarm intelligence-based optimizer for molecular geometry.

PubMed

Wehmeyer, Christoph; Falk von Rudorff, Guido; Wolf, Sebastian; Kabbe, Gabriel; Schärf, Daniel; Kühne, Thomas D; Sebastiani, Daniel

2012-11-21

We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular cluster structures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometry optimization of molecular cluster structures and show its performance for clusters with 2-57 particles and different interatomic interaction potentials.

Foraging on the potential energy surface: A swarm intelligence-based optimizer for molecular geometry

NASA Astrophysics Data System (ADS)

Wehmeyer, Christoph; Falk von Rudorff, Guido; Wolf, Sebastian; Kabbe, Gabriel; Schärf, Daniel; Kühne, Thomas D.; Sebastiani, Daniel

2012-11-01

We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular cluster structures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometry optimization of molecular cluster structures and show its performance for clusters with 2-57 particles and different interatomic interaction potentials.

Active appearance pyramids for object parametrisation and fitting.

PubMed

Zhang, Qiang; Bhalerao, Abhir; Dickenson, Edward; Hutchinson, Charles

2016-08-01

Object class representation is one of the key problems in various medical image analysis tasks. We propose a part-based parametric appearance model we refer to as an Active Appearance Pyramid (AAP). The parts are delineated by multi-scale Local Feature Pyramids (LFPs) for superior spatial specificity and distinctiveness. An AAP models the variability within a population with local translations of multi-scale parts and linear appearance variations of the assembly of the parts. It can fit and represent new instances by adjusting the shape and appearance parameters. The fitting process uses a two-step iterative strategy: local landmark searching followed by shape regularisation. We present a simultaneous local feature searching and appearance fitting algorithm based on the weighted Lucas and Kanade method. A shape regulariser is derived to calculate the maximum likelihood shape with respect to the prior and multiple landmark candidates from multi-scale LFPs, with a compact closed-form solution. We apply the 2D AAP on the modelling of variability in patients with lumbar spinal stenosis (LSS) and validate its performance on 200 studies consisting of routine axial and sagittal MRI scans. Intervertebral sagittal and parasagittal cross-sections are typically used for the diagnosis of LSS, we therefore build three AAPs on L3/4, L4/5 and L5/S1 axial cross-sections and three on parasagittal slices. Experiments show significant improvement in convergence range, robustness to local minima and segmentation precision compared with Constrained Local Models (CLMs), Active Shape Models (ASMs) and Active Appearance Models (AAMs), as well as superior performance in appearance reconstruction compared with AAMs. We also validate the performance on 3D CT volumes of hip joints from 38 studies. Compared to AAMs, AAPs achieve a higher segmentation and reconstruction precision. Moreover, AAPs have a significant improvement in efficiency, consuming about half the memory and less than 10% of the training time and 15% of the testing time. Copyright © 2016 Elsevier B.V. All rights reserved.

Video shot boundary detection using region-growing-based watershed method

NASA Astrophysics Data System (ADS)

Wang, Jinsong; Patel, Nilesh; Grosky, William

2004-10-01

In this paper, a novel shot boundary detection approach is presented, based on the popular region growing segmentation method - Watershed segmentation. In image processing, gray-scale pictures could be considered as topographic reliefs, in which the numerical value of each pixel of a given image represents the elevation at that point. Watershed method segments images by filling up basins with water starting at local minima, and at points where water coming from different basins meet, dams are built. In our method, each frame in the video sequences is first transformed from the feature space into the topographic space based on a density function. Low-level features are extracted from frame to frame. Each frame is then treated as a point in the feature space. The density of each point is defined as the sum of the influence functions of all neighboring data points. The height function that is originally used in Watershed segmentation is then replaced by inverting the density at the point. Thus, all the highest density values are transformed into local minima. Subsequently, Watershed segmentation is performed in the topographic space. The intuitive idea under our method is that frames within a shot are highly agglomerative in the feature space and have higher possibilities to be merged together, while those frames between shots representing the shot changes are not, hence they have less density values and are less likely to be clustered by carefully extracting the markers and choosing the stopping criterion.

Determining Geometric Parameters of Agricultural Trees from Laser Scanning Data Obtained with Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Hadas, E.; Jozkow, G.; Walicka, A.; Borkowski, A.

2018-05-01

The estimation of dendrometric parameters has become an important issue for agriculture planning and for the efficient management of orchards. Airborne Laser Scanning (ALS) data is widely used in forestry and many algorithms for automatic estimation of dendrometric parameters of individual forest trees were developed. Unfortunately, due to significant differences between forest and fruit trees, some contradictions exist against adopting the achievements of forestry science to agricultural studies indiscriminately. In this study we present the methodology to identify individual trees in apple orchard and estimate heights of individual trees, using high-density LiDAR data (3200 points/m2) obtained with Unmanned Aerial Vehicle (UAV) equipped with Velodyne HDL32-E sensor. The processing strategy combines the alpha-shape algorithm, principal component analysis (PCA) and detection of local minima. The alpha-shape algorithm is used to separate tree rows. In order to separate trees in a single row, we detect local minima on the canopy profile and slice polygons from alpha-shape results. We successfully separated 92 % of trees in the test area. 6 % of trees in orchard were not separated from each other and 2 % were sliced into two polygons. The RMSE of tree heights determined from the point clouds compared to field measurements was equal to 0.09 m, and the correlation coefficient was equal to 0.96. The results confirm the usefulness of LiDAR data from UAV platform in orchard inventory.

Automatic initialization for 3D bone registration

NASA Astrophysics Data System (ADS)

Foroughi, Pezhman; Taylor, Russell H.; Fichtinger, Gabor

2008-03-01

In image-guided bone surgery, sample points collected from the surface of the bone are registered to the preoperative CT model using well-known registration methods such as Iterative Closest Point (ICP). These techniques are generally very sensitive to the initial alignment of the datasets. Poor initialization significantly increases the chances of getting trapped local minima. In order to reduce the risk of local minima, the registration is manually initialized by locating the sample points close to the corresponding points on the CT model. In this paper, we present an automatic initialization method that aligns the sample points collected from the surface of pelvis with CT model of the pelvis. The main idea is to exploit a mean shape of pelvis created from a large number of CT scans as the prior knowledge to guide the initial alignment. The mean shape is constant for all registrations and facilitates the inclusion of application-specific information into the registration process. The CT model is first aligned with the mean shape using the bilateral symmetry of the pelvis and the similarity of multiple projections. The surface points collected using ultrasound are then aligned with the pelvis mean shape. This will, in turn, lead to initial alignment of the sample points with the CT model. The experiments using a dry pelvis and two cadavers show that the method can align the randomly dislocated datasets close enough for successful registration. The standard ICP has been used for final registration of datasets.

Computing frequency by using generalized zero-crossing applied to intrinsic mode functions

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

2006-01-01

This invention presents a method for computing Instantaneous Frequency by applying Empirical Mode Decomposition to a signal and using Generalized Zero-Crossing (GZC) and Extrema Sifting. The GZC approach is the most direct, local, and also the most accurate in the mean. Furthermore, this approach will also give a statistical measure of the scattering of the frequency value. For most practical applications, this mean frequency localized down to quarter of a wave period is already a well-accepted result. As this method physically measures the period, or part of it, the values obtained can serve as the best local mean over the period to which it applies. Through Extrema Sifting, instead of the cubic spline fitting, this invention constructs the upper envelope and the lower envelope by connecting local maxima points and local minima points of the signal with straight lines, respectively, when extracting a collection of Intrinsic Mode Functions (IMFs) from a signal under consideration.

Small-Tip-Angle Spokes Pulse Design Using Interleaved Greedy and Local Optimization Methods

PubMed Central

Grissom, William A.; Khalighi, Mohammad-Mehdi; Sacolick, Laura I.; Rutt, Brian K.; Vogel, Mika W.

2013-01-01

Current spokes pulse design methods can be grouped into methods based either on sparse approximation or on iterative local (gradient descent-based) optimization of the transverse-plane spatial frequency locations visited by the spokes. These two classes of methods have complementary strengths and weaknesses: sparse approximation-based methods perform an efficient search over a large swath of candidate spatial frequency locations but most are incompatible with off-resonance compensation, multifrequency designs, and target phase relaxation, while local methods can accommodate off-resonance and target phase relaxation but are sensitive to initialization and suboptimal local cost function minima. This article introduces a method that interleaves local iterations, which optimize the radiofrequency pulses, target phase patterns, and spatial frequency locations, with a greedy method to choose new locations. Simulations and experiments at 3 and 7 T show that the method consistently produces single- and multifrequency spokes pulses with lower flip angle inhomogeneity compared to current methods. PMID:22392822

Extremal Optimization for Quadratic Unconstrained Binary Problems

NASA Astrophysics Data System (ADS)

Boettcher, S.

We present an implementation of τ-EO for quadratic unconstrained binary optimization (QUBO) problems. To this end, we transform modify QUBO from its conventional Boolean presentation into a spin glass with a random external field on each site. These fields tend to be rather large compared to the typical coupling, presenting EO with a challenging two-scale problem, exploring smaller differences in couplings effectively while sufficiently aligning with those strong external fields. However, we also find a simple solution to that problem that indicates that those external fields apparently tilt the energy landscape to a such a degree such that global minima become more easy to find than those of spin glasses without (or very small) fields. We explore the impact of the weight distribution of the QUBO formulation in the operations research literature and analyze their meaning in a spin-glass language. This is significant because QUBO problems are considered among the main contenders for NP-hard problems that could be solved efficiently on a quantum computer such as D-Wave.

CCD Times of Minima of Selected Eclipsing Binaries

NASA Astrophysics Data System (ADS)

Zejda, Miloslav

2004-12-01

682 CCD minima observations of 259 eclipsing binaries made mainly by author are presented. The observed stars were chosen mainly from catalogue BRKA of observing programme of BRNO-Variable Star Section of CAS.

Coupled factors influencing detachment of nano- and micro-sized particles from primary minima.

PubMed

Shen, Chongyang; Lazouskaya, Volha; Jin, Yan; Li, Baoguo; Ma, Zhiqiang; Zheng, Wenjuan; Huang, Yuanfang

2012-06-01

This study examined the detachments of nano- and micro-sized colloids from primary minima in the presence of cation exchange by laboratory column experiments. Colloids were initially deposited in columns packed with glass beads at 0.2 M CaCl(2) in the primary minima of Derjaguin-Landau-Verwey-Overbeek (DLVO) interaction energies. Then, the columns were flushed with NaCl solutions with different ionic strengths (i.e., 0.001, 0.01, 0.1 and 0.2 M). Detachments were observed at all ionic strengths and were particularly significant for the nanoparticle. The detachments increased with increasing electrolyte concentration for the nanoparticle whereas increased from 0.001 M to 0.01 M and decreased with further increasing electrolyte concentration for the micro-sized colloid. The observations were attributed to coupled influence of cation exchange, short-range repulsion, surface roughness, surface charge heterogeneity, and deposition in the secondary minima. The detachments of colloids from primary minima challenge the common belief that colloid interaction in primary minimum is irreversible and resistant to disturbance in solution ionic strength and composition. Although the significance of surface roughness, surface charge heterogeneity, and secondary minima on colloid deposition has been widely recognized, our study implies that they also play important roles in colloid detachment. Whereas colloid detachment is frequently associated with decrease of ionic strength, our results show that increase of ionic strength can also cause detachment due to influence of cation exchange. Copyright © 2012 Elsevier B.V. All rights reserved.

Detailed Structure of the Tropical Upper Troposphere and Lower Stratosphere as Revealed by Balloon Sonde Observations of Water Vapor, Ozone, Temperature, and Winds During the NASA TCSP and TC4 Campaigns

NASA Technical Reports Server (NTRS)

Selkirk, Henry B.; Vomel, Holger; Canossa, Jessica Maria Valverde; Pfister, Leonhard; Diaz, Jorge Andres; Fernandez, Walter; Amador, Jorge; Stolz, Werner; Peng, Grace S.

2010-01-01

We report on balloon sonde measurements of water vapor and ozone using the cryogenic frost point hygrometer and electrochemical concentration cell ozonesondes made at Alajuela, Costa Rica (10.0 N, 84.2 W) during two NASA airborne campaigns: the Tropical Convective Systems and Processes (TCSP) mission in July 2005 and the Tropical Composition, Clouds, and Climate Coupling Experiment (TC4), July - August 2007. In both campaigns we found an upper troposphere that was frequently supersaturated but no evidence that deep convection had reached the tropopause. The balloon sondes were complemented by campaigns of 4 times daily high-resolution radiosondes from mid-June through mid-August in both years. The radiosonde data reveal vertically propagating equatorial waves that caused a large increase in the variability of temperature in the tropical tropopause layer (TTL). These waves episodically produced cold point tropopauses (CPTs) above 18 km, yet in neither campaign was saturation observed above approx 380 K or 17 km. The averages of the water vapor minima below this level were 5.2 ppmv in TCSP and 4.8 ppmv in TC4, and the individual profile minima all lay at or above approx 360 K. The average minima in this 360 C380 K layer provide a better estimate of the effective stratospheric entry value than the average mixing ratio at the CPT. We refer to this upper portion of the TTL as the tropopause saturation layer and consider it to be the locus of the final dehydration of nascent stratospheric air. As such, it is the local equivalent to the tape head of the water vapor tape recorder.

Understanding density functional theory (DFT) and completing it in practice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bagayoko, Diola

2014-12-15

We review some salient points in the derivation of density functional theory (DFT) and of the local density approximation (LDA) of it. We then articulate an understanding of DFT and LDA that seems to be ignored in the literature. We note the well-established failures of many DFT and LDA calculations to reproduce the measured energy gaps of finite systems and band gaps of semiconductors and insulators. We then illustrate significant differences between the results from self consistent calculations using single trial basis sets and those from computations following the Bagayoko, Zhao, and Williams (BZW) method, as enhanced by Ekuma andmore » Franklin (BZW-EF). Unlike the former, the latter calculations verifiably attain the absolute minima of the occupied energies, as required by DFT. These minima are one of the reasons for the agreement between their results and corresponding, experimental ones for the band gap and a host of other properties. Further, we note predictions of DFT BZW-EF calculations that have been confirmed by experiment. Our subsequent description of the BZW-EF method ends with the application of the Rayleigh theorem in the selection, among the several calculations the method requires, of the one whose results have a full, physics content ascribed to DFT. This application of the Rayleigh theorem adds to or completes DFT, in practice, to preserve the physical content of unoccupied, low energy levels. Discussions, including implications of the method, and a short conclusion follow the description of the method. The successive augmentation of the basis set in the BZW-EF method, needed for the application of the Rayleigh theorem, is also necessary in the search for the absolute minima of the occupied energies, in practice.« less

Solar Cycle Variability and Grand Minima Induced by Joy's Law Scatter

NASA Astrophysics Data System (ADS)

Karak, Bidya Binay; Miesch, Mark S.

2017-08-01

The strength of the solar cycle varies from one cycle to another in an irregular manner and the extreme example of this irregularity is the Maunder minimum when Sun produced only a few spots for several years. We explore the cause of these variabilities using a 3D Babcock--Leighton dynamo. In this model, based on the toroidal flux at the base of the convection zone, bipolar magnetic regions (BMRs) are produced with flux, tilt angle, and time of emergence all obtain from their observed distributions. The dynamo growth is limited by a tilt quenching.The randomnesses in the BMR emergences make the poloidal field unequal and eventually cause an unequal solar cycle. When observed fluctuations of BMR tilts around Joy's law, i.e., a standard deviation of 15 degrees, are considered, our model produces a variation in the solar cycle comparable to the observed solar cycle variability. Tilt scatter also causes occasional Maunder-like grand minima, although the observed scatter does not reproduce correct statistics of grand minima. However, when we double the tilt scatter, we find grand minima consistent with observations. Importantly, our dynamo model can operate even during grand minima with only a few BMRs, without requiring any additional alpha effect.

Using and comparing metaheuristic algorithms for optimizing bidding strategy viewpoint of profit maximization of generators

NASA Astrophysics Data System (ADS)

Mousavi, Seyed Hosein; Nazemi, Ali; Hafezalkotob, Ashkan

2015-03-01

With the formation of the competitive electricity markets in the world, optimization of bidding strategies has become one of the main discussions in studies related to market designing. Market design is challenged by multiple objectives that need to be satisfied. The solution of those multi-objective problems is searched often over the combined strategy space, and thus requires the simultaneous optimization of multiple parameters. The problem is formulated analytically using the Nash equilibrium concept for games composed of large numbers of players having discrete and large strategy spaces. The solution methodology is based on a characterization of Nash equilibrium in terms of minima of a function and relies on a metaheuristic optimization approach to find these minima. This paper presents some metaheuristic algorithms to simulate how generators bid in the spot electricity market viewpoint of their profit maximization according to the other generators' strategies, such as genetic algorithm (GA), simulated annealing (SA) and hybrid simulated annealing genetic algorithm (HSAGA) and compares their results. As both GA and SA are generic search methods, HSAGA is also a generic search method. The model based on the actual data is implemented in a peak hour of Tehran's wholesale spot market in 2012. The results of the simulations show that GA outperforms SA and HSAGA on computing time, number of function evaluation and computing stability, as well as the results of calculated Nash equilibriums by GA are less various and different from each other than the other algorithms.

Determining the Depth of Infinite Horizontal Cylindrical Sources from Spontaneous Polarization Data

NASA Astrophysics Data System (ADS)

Cooper, G. R. J.; Stettler, E. H.

2017-03-01

Previously published semi-automatic interpretation methods that use ratios of analytic signal amplitudes of orders that differ by one to determine the distance to potential field sources are shown also to apply to self-potential (S.P.) data when the source is a horizontal cylinder. Local minima of the distance (when it becomes closest to zero) give the source depth. The method was applied to an S.P. anomaly from the Bourkes Luck potholes district in Mpumalanga Province, South Africa, and gave results that were confirmed by drilling.

The multiuniverse transition in superfluid 3He

NASA Astrophysics Data System (ADS)

Bunkov, Yury

2013-10-01

The symmetry-breaking phase transitions of the universe and of superfluid 3He may lead to the formation of different states with different order parameters. In both cases the energy potential below the transition temperature has a complicated multidimensional profile with many local minima and saddle points, which correspond to different states. Consequently, not only topological defects, but also islands of different metastable states can be created. Using 3He we can analyse the properties and experimental consequences of such transitions and, in particular, the first-order phase transition between the two low symmetry states.

The multiuniverse transition in superfluid 3He.

PubMed

Bunkov, Yury

2013-10-09

The symmetry-breaking phase transitions of the universe and of superfluid (3)He may lead to the formation of different states with different order parameters. In both cases the energy potential below the transition temperature has a complicated multidimensional profile with many local minima and saddle points, which correspond to different states. Consequently, not only topological defects, but also islands of different metastable states can be created. Using (3)He we can analyse the properties and experimental consequences of such transitions and, in particular, the first-order phase transition between the two low symmetry states.

Methanol clusters (CH3OH)n: putative global minimum-energy structures from model potentials and dispersion-corrected density functional theory.

PubMed

Kazachenko, Sergey; Bulusu, Satya; Thakkar, Ajit J

2013-06-14

Putative global minima are reported for methanol clusters (CH3OH)n with n ≤ 15. The predictions are based on global optimization of three intermolecular potential energy models followed by local optimization and single-point energy calculations using two variants of dispersion-corrected density functional theory. Recurring structural motifs include folded and/or twisted rings, folded rings with a short branch, and stacked rings. Many of the larger structures are stabilized by weak C-H···O bonds.

CCD Times of Minima of Faint Eclipsing Binaries in 2000

NASA Astrophysics Data System (ADS)

Zejda, Miloslav

2002-06-01

196 CCD minima observations of 122 eclipsing binaries made by the author in 2000 are presented. The observed stars were chosen from the catalogue BRKA of observing programme of BRNO-Variable Star Section of CAS.

Matching shapes with self-intersections: application to leaf classification.

PubMed

Mokhtarian, Farzin; Abbasi, Sadegh

2004-05-01

We address the problem of two-dimensional (2-D) shape representation and matching in presence of self-intersection for large image databases. This may occur when part of an object is hidden behind another part and results in a darker section in the gray level image of the object. The boundary contour of the object must include the boundary of this part which is entirely inside the outline of the object. The Curvature Scale Space (CSS) image of a shape is a multiscale organization of its inflection points as it is smoothed. The CSS-based shape representation method has been selected for MPEG-7 standardization. We study the effects of contour self-intersection on the Curvature Scale Space image. When there is no self-intersection, the CSS image contains several arch shape contours, each related to a concavity or a convexity of the shape. Self intersections create contours with minima as well as maxima in the CSS image. An efficient shape representation method has been introduced in this paper which describes a shape using the maxima as well as the minima of its CSS contours. This is a natural generalization of the conventional method which only includes the maxima of the CSS image contours. The conventional matching algorithm has also been modified to accommodate the new information about the minima. The method has been successfully used in a real world application to find, for an unknown leaf, similar classes from a database of classified leaf images representing different varieties of chrysanthemum. For many classes of leaves, self-intersection is inevitable during the scanning of the image. Therefore the original contributions of this paper is the generalization of the Curvature Scale Space representation to the class of 2-D contours with self-intersection, and its application to the classification of Chrysanthemum leaves.

Parameter estimation procedure for complex non-linear systems: calibration of ASM No. 1 for N-removal in a full-scale oxidation ditch.

PubMed

Abusam, A; Keesman, K J; van Straten, G; Spanjers, H; Meinema, K

2001-01-01

When applied to large simulation models, the process of parameter estimation is also called calibration. Calibration of complex non-linear systems, such as activated sludge plants, is often not an easy task. On the one hand, manual calibration of such complex systems is usually time-consuming, and its results are often not reproducible. On the other hand, conventional automatic calibration methods are not always straightforward and often hampered by local minima problems. In this paper a new straightforward and automatic procedure, which is based on the response surface method (RSM) for selecting the best identifiable parameters, is proposed. In RSM, the process response (output) is related to the levels of the input variables in terms of a first- or second-order regression model. Usually, RSM is used to relate measured process output quantities to process conditions. However, in this paper RSM is used for selecting the dominant parameters, by evaluating parameters sensitivity in a predefined region. Good results obtained in calibration of ASM No. 1 for N-removal in a full-scale oxidation ditch proved that the proposed procedure is successful and reliable.

Epidemic spreading on evolving signed networks

NASA Astrophysics Data System (ADS)

Saeedian, M.; Azimi-Tafreshi, N.; Jafari, G. R.; Kertesz, J.

2017-02-01

Most studies of disease spreading consider the underlying social network as obtained without the contagion, though epidemic influences people's willingness to contact others: A "friendly" contact may be turned to "unfriendly" to avoid infection. We study the susceptible-infected disease-spreading model on signed networks, in which each edge is associated with a positive or negative sign representing the friendly or unfriendly relation between its end nodes. In a signed network, according to Heider's theory, edge signs evolve such that finally a state of structural balance is achieved, corresponding to no frustration in physics terms. However, the danger of infection affects the evolution of its edge signs. To describe the coupled problem of the sign evolution and disease spreading, we generalize the notion of structural balance by taking into account the state of the nodes. We introduce an energy function and carry out Monte Carlo simulations on complete networks to test the energy landscape, where we find local minima corresponding to the so-called jammed states. We study the effect of the ratio of initial friendly to unfriendly connections on the propagation of disease. The steady state can be balanced or a jammed state such that a coexistence occurs between susceptible and infected nodes in the system.

An improved parameter estimation and comparison for soft tissue constitutive models containing an exponential function.

PubMed

Aggarwal, Ankush

2017-08-01

Motivated by the well-known result that stiffness of soft tissue is proportional to the stress, many of the constitutive laws for soft tissues contain an exponential function. In this work, we analyze properties of the exponential function and how it affects the estimation and comparison of elastic parameters for soft tissues. In particular, we find that as a consequence of the exponential function there are lines of high covariance in the elastic parameter space. As a result, one can have widely varying mechanical parameters defining the tissue stiffness but similar effective stress-strain responses. Drawing from elementary algebra, we propose simple changes in the norm and the parameter space, which significantly improve the convergence of parameter estimation and robustness in the presence of noise. More importantly, we demonstrate that these changes improve the conditioning of the problem and provide a more robust solution in the case of heterogeneous material by reducing the chances of getting trapped in a local minima. Based upon the new insight, we also propose a transformed parameter space which will allow for rational parameter comparison and avoid misleading conclusions regarding soft tissue mechanics.

Chaotic particle swarm optimization with mutation for classification.

PubMed

Assarzadeh, Zahra; Naghsh-Nilchi, Ahmad Reza

2015-01-01

In this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classify patterns of different classes in the feature space. The introduced mutation operators and chaotic sequences allows us to overcome the problem of early convergence into a local minima associated with particle swarm optimization algorithms. That is, the mutation operator sharpens the convergence and it tunes the best possible solution. Furthermore, to remove the irrelevant data and reduce the dimensionality of medical datasets, a feature selection approach using binary version of the proposed particle swarm optimization is introduced. In order to demonstrate the effectiveness of our proposed classifier, mutation-based classifier particle swarm optimization, it is checked out with three sets of data classifications namely, Wisconsin diagnostic breast cancer, Wisconsin breast cancer and heart-statlog, with different feature vector dimensions. The proposed algorithm is compared with different classifier algorithms including k-nearest neighbor, as a conventional classifier, particle swarm-classifier, genetic algorithm, and Imperialist competitive algorithm-classifier, as more sophisticated ones. The performance of each classifier was evaluated by calculating the accuracy, sensitivity, specificity and Matthews's correlation coefficient. The experimental results show that the mutation-based classifier particle swarm optimization unequivocally performs better than all the compared algorithms.

A novel approach for detection and classification of mammographic microcalcifications using wavelet analysis and extreme learning machine.

PubMed

Malar, E; Kandaswamy, A; Chakravarthy, D; Giri Dharan, A

2012-09-01

The objective of this paper is to reveal the effectiveness of wavelet based tissue texture analysis for microcalcification detection in digitized mammograms using Extreme Learning Machine (ELM). Microcalcifications are tiny deposits of calcium in the breast tissue which are potential indicators for early detection of breast cancer. The dense nature of the breast tissue and the poor contrast of the mammogram image prohibit the effectiveness in identifying microcalcifications. Hence, a new approach to discriminate the microcalcifications from the normal tissue is done using wavelet features and is compared with different feature vectors extracted using Gray Level Spatial Dependence Matrix (GLSDM) and Gabor filter based techniques. A total of 120 Region of Interests (ROIs) extracted from 55 mammogram images of mini-Mias database, including normal and microcalcification images are used in the current research. The network is trained with the above mentioned features and the results denote that ELM produces relatively better classification accuracy (94%) with a significant reduction in training time than the other artificial neural networks like Bayesnet classifier, Naivebayes classifier, and Support Vector Machine. ELM also avoids problems like local minima, improper learning rate, and over fitting. Copyright © 2012 Elsevier Ltd. All rights reserved.

Correlating precursory declines in groundwater radon with earthquake magnitude.

PubMed

Kuo, T

2014-01-01

Both studies at the Antung hot spring in eastern Taiwan and at the Paihe spring in southern Taiwan confirm that groundwater radon can be a consistent tracer for strain changes in the crust preceding an earthquake when observed in a low-porosity fractured aquifer surrounded by a ductile formation. Recurrent anomalous declines in groundwater radon were observed at the Antung D1 monitoring well in eastern Taiwan prior to the five earthquakes of magnitude (Mw ): 6.8, 6.1, 5.9, 5.4, and 5.0 that occurred on December 10, 2003; April 1, 2006; April 15, 2006; February 17, 2008; and July 12, 2011, respectively. For earthquakes occurring on the longitudinal valley fault in eastern Taiwan, the observed radon minima decrease as the earthquake magnitude increases. The above correlation has been proven to be useful for early warning local large earthquakes. In southern Taiwan, radon anomalous declines prior to the 2010 Mw 6.3 Jiasian, 2012 Mw 5.9 Wutai, and 2012 ML 5.4 Kaohsiung earthquakes were also recorded at the Paihe spring. For earthquakes occurring on different faults in southern Taiwan, the correlation between the observed radon minima and the earthquake magnitude is not yet possible. © 2013, National Ground Water Association.

Information processing in network architecture of genome controlled signal transduction circuit. A proposed theoretical explanation.

PubMed

Chakraborty, Chiranjib; Sarkar, Bimal Kumar; Patel, Pratiksha; Agoramoorthy, Govindasamy

2012-01-01

In this paper, Shannon information theory has been applied to elaborate cell signaling. It is proposed that in the cellular network architecture, four components viz. source (DNA), transmitter (mRNA), receiver (protein) and destination (another protein) are involved. The message transmits from source (DNA) to transmitter (mRNA) and then passes through a noisy channel reaching finally the receiver (protein). The protein synthesis process is here considered as the noisy channel. Ultimately, signal is transmitted from receiver to destination (another protein). The genome network architecture elements were compared with genetic alphabet L = {A, C, G, T} with a biophysical model based on the popular Shannon information theory. This study found the channel capacity as maximum for zero error (sigma = 0) and at this condition, transition matrix becomes a unit matrix with rank 4. The transition matrix will be erroneous and finally at sigma = 1 channel capacity will be localized maxima with a value of 0.415 due to the increased value at sigma. On the other hand, minima exists at sigma = 0.75, where all transition probabilities become 0.25 and uncertainty will be maximum resulting in channel capacity with the minima value of zero.

Global optimization of ionic Mg(n)F(2n) (n=1-30) clusters.

PubMed

Francisco, E; Martín Pendás, A; Blanco, M A

2005-12-15

The global optimization basin-hopping (BH) method has been used to locate the global minima (GM) of Mg(n)F(2n) (n=1-30) clusters using a Born-Mayer-type potential. Some of the GM were particularly difficult to find, requiring more than 1.5 x 10(4) BH steps. We have found that both the binding energy per MgF2 unit and the effective volume of the GM isomers increase almost linearly with n, and that cluster symmetry decreases with cluster size. The data derived from the BH runs reveal a growing density of local minima just above the GM as n increases. Despite this, the attraction basin around each GM is relatively large, since after all their atomic coordinates are randomly displaced by values as high as 2.0 bohrs, the perturbed structures, upon reoptimization, relax back to the GM in more than 50% of the cases (except for n=10 and 11). The relative stabilities derived from energy second differences suggest that n=8,10,13,15, and 20 are probably the magic numbers for these systems. Mass spectrum experiments would be very useful to clarify this issue.

Electrostatic interaction between stereocilia: II. Influence on the mechanical properties of the hair bundle.

PubMed

Dolgobrodov, S G; Lukashkin, A N; Russell, I J

2000-12-01

This paper is based on our model [Dolgobrodov et al., 2000. Hear. Res., submitted for publication] in which we examine the significance of the polyanionic surface layers of stereocilia for electrostatic interaction between them. We analyse how electrostatic forces modify the mechanical properties of the sensory hair bundle. Different charge distribution profiles within the glycocalyx are considered. When modelling a typical experiment on bundle stiffness measurements, applying an external force to the tallest row of stereocilia shows that the asymptotic stiffness of the hair bundle for negative displacements is always larger than the asymptotic stiffness for positive displacements. This increase in stiffness is monotonic for even charge distribution and shows local minima when the negative charge is concentrated in a thinner layer within the cell coat. The minima can also originate from the co-operative effect of electrostatic repulsion and inter-ciliary links with non-linear mechanical properties. Existing experimental observations are compared with the predictions of the model. We conclude that the forces of electrostatic interaction between stereocilia may influence the mechanical properties of the hair bundle and, being strongly non-linear, contribute to the non-linear phenomena, which have been recorded from the auditory periphery.

Comparison of Nightside Midlatitude Ionospheric Flows from DMSP and SuperDARN During Stormtime Penetration Events

NASA Astrophysics Data System (ADS)

Hairston, M. R.; Coley, W. R.; Ruohoniemi, J. M.

2016-12-01

July through September 2015 was a relatively quiet period punctuated by nine small to moderate geomagnetic storms (Dst minima ranging from -25 to -98 nT). We are conducting a study of the subauroral midlatitude ionospheric zonal flows in the predawn morning sector (magnetic local times ranging from 2.2 to 5.6 hours) using satellite data from DMSP F15 and F16 along with the midlatitude SuperDARN radars. We will present an empirical model of the background quiettime flows based on these data and then compare those flows to the observed stormtimes flows. The stormtime data will be used to explore the extent of the penetration electric field in this predawn region. Additional satellite flow data from other local times (evening and dayside) will also be presented to check for any local time variation in the extent of the penetration electric field.

On the heteroclinic connection problem for multi-well gradient systems

NASA Astrophysics Data System (ADS)

Zuniga, Andres; Sternberg, Peter

2016-10-01

We revisit the existence problem of heteroclinic connections in RN associated with Hamiltonian systems involving potentials W :RN → R having several global minima. Under very mild assumptions on W we present a simple variational approach to first find geodesics minimizing length of curves joining any two of the potential wells, where length is computed with respect to a degenerate metric having conformal factor √{ W}. Then we show that when such a minimizing geodesic avoids passing through other wells of the potential at intermediate times, it gives rise to a heteroclinic connection between the two wells. This work improves upon the approach of [22] and represents a more geometric alternative to the approaches of e.g. [5,10,14,17] for finding such connections.

Exploring the Connection Between Sampling Problems in Bayesian Inference and Statistical Mechanics

NASA Technical Reports Server (NTRS)

Pohorille, Andrew

2006-01-01

The Bayesian and statistical mechanical communities often share the same objective in their work - estimating and integrating probability distribution functions (pdfs) describing stochastic systems, models or processes. Frequently, these pdfs are complex functions of random variables exhibiting multiple, well separated local minima. Conventional strategies for sampling such pdfs are inefficient, sometimes leading to an apparent non-ergodic behavior. Several recently developed techniques for handling this problem have been successfully applied in statistical mechanics. In the multicanonical and Wang-Landau Monte Carlo (MC) methods, the correct pdfs are recovered from uniform sampling of the parameter space by iteratively establishing proper weighting factors connecting these distributions. Trivial generalizations allow for sampling from any chosen pdf. The closely related transition matrix method relies on estimating transition probabilities between different states. All these methods proved to generate estimates of pdfs with high statistical accuracy. In another MC technique, parallel tempering, several random walks, each corresponding to a different value of a parameter (e.g. "temperature"), are generated and occasionally exchanged using the Metropolis criterion. This method can be considered as a statistically correct version of simulated annealing. An alternative approach is to represent the set of independent variables as a Hamiltonian system. Considerab!e progress has been made in understanding how to ensure that the system obeys the equipartition theorem or, equivalently, that coupling between the variables is correctly described. Then a host of techniques developed for dynamical systems can be used. Among them, probably the most powerful is the Adaptive Biasing Force method, in which thermodynamic integration and biased sampling are combined to yield very efficient estimates of pdfs. The third class of methods deals with transitions between states described by rate constants. These problems are isomorphic with chemical kinetics problems. Recently, several efficient techniques for this purpose have been developed based on the approach originally proposed by Gillespie. Although the utility of the techniques mentioned above for Bayesian problems has not been determined, further research along these lines is warranted

Experimental evidence for the blue-shifted hydrogen-bonded complexes of CHF3 with π-electron donors.

PubMed

Gopi, R; Ramanathan, N; Sundararajan, K

2017-06-15

Blue-shifted hydrogen-bonded complexes of fluoroform (CHF 3 ) with benzene (C 6 H 6 ) and acetylene (C 2 H 2 ) have been investigated using matrix isolation infrared spectroscopy and ab initio computations. For CHF 3 -C 6 H 6 complex, calculations performed at the B3LYP and MP2 levels of theory using 6-311++G (d,p) and aug-cc-pVDZ basis sets discerned two minima corresponding to a 1:1 hydrogen-bonded complex. The global minimum correlated to a structure, where the interaction is between the hydrogen of CHF 3 and the π-electrons of C 6 H 6 and a weak local minimum was stabilized through H…F interaction. For the CHF 3 -C 2 H 2 complex, computation performed at MP2/aug-cc-pVDZ level of theory yielded two minima, corresponding to the cyclic C-H…π complex A (global) and a linear C-H…F (n-σ) complex B (local). Experimentally a blue-shift of 32.3cm -1 and 7.7cm -1 was observed in the ν 1 C-H stretching mode of CHF 3 sub-molecule in Ar matrix for the 1:1 C-H…π complexes of CHF 3 with C 6 H 6 and C 2 H 2 respectively. Natural bond orbital (NBO), Atoms-in-molecule (AIM) and energy decomposition (EDA) analyses were carried out to explain the blue-shifting and the nature of the interaction in these complexes. Copyright © 2017 Elsevier B.V. All rights reserved.

Reconciling Structural and Thermodynamic Predictions Using All-Atom and Coarse-Grain Force Fields: The Case of Charged Oligo-Arginine Translocation into DMPC Bilayers

PubMed Central

2015-01-01

Using the translocation of short, charged cationic oligo-arginine peptides (mono-, di-, and triarginine) from bulk aqueous solution into model DMPC bilayers, we explore the question of the similarity of thermodynamic and structural predictions obtained from molecular dynamics simulations using all-atom and Martini coarse-grain force fields. Specifically, we estimate potentials of mean force associated with translocation using standard all-atom (CHARMM36 lipid) and polarizable and nonpolarizable Martini force fields, as well as a series of modified Martini-based parameter sets. We find that we are able to reproduce qualitative features of potentials of mean force of single amino acid side chain analogues into model bilayers. In particular, modifications of peptide–water and peptide–membrane interactions allow prediction of free energy minima at the bilayer–water interface as obtained with all-atom force fields. In the case of oligo-arginine peptides, the modified parameter sets predict interfacial free energy minima as well as free energy barriers in almost quantitative agreement with all-atom force field based simulations. Interfacial free energy minima predicted by a modified coarse-grained parameter set are −2.51, −4.28, and −5.42 for mono-, di-, and triarginine; corresponding values from all-atom simulations are −0.83, −3.33, and −3.29, respectively, all in units of kcal/mol. We found that a stronger interaction between oligo-arginine and the membrane components and a weaker interaction between oligo-arginine and water are crucial for producing such minima in PMFs using the polarizable CG model. The difference between bulk aqueous and bilayer center states predicted by the modified coarse-grain force field are 11.71, 14.14, and 16.53 kcal/mol, and those by the all-atom model are 6.94, 8.64, and 12.80 kcal/mol; those are of almost the same order of magnitude. Our simulations also demonstrate a remarkable similarity in the structural aspects of the ensemble of configurations generated using the all-atom and coarse-grain force fields. Both resolutions show that oligo-arginine peptides adopt preferential orientations as they translocate into the bilayer. The guiding theme centers on charged groups maintaining coordination with polar and charged bilayer components as well as local water. We also observe similar behaviors related with membrane deformations. PMID:25290376

Reconciling structural and thermodynamic predictions using all-atom and coarse-grain force fields: the case of charged oligo-arginine translocation into DMPC bilayers.

PubMed

Hu, Yuan; Sinha, Sudipta Kumar; Patel, Sandeep

2014-10-16

Using the translocation of short, charged cationic oligo-arginine peptides (mono-, di-, and triarginine) from bulk aqueous solution into model DMPC bilayers, we explore the question of the similarity of thermodynamic and structural predictions obtained from molecular dynamics simulations using all-atom and Martini coarse-grain force fields. Specifically, we estimate potentials of mean force associated with translocation using standard all-atom (CHARMM36 lipid) and polarizable and nonpolarizable Martini force fields, as well as a series of modified Martini-based parameter sets. We find that we are able to reproduce qualitative features of potentials of mean force of single amino acid side chain analogues into model bilayers. In particular, modifications of peptide-water and peptide-membrane interactions allow prediction of free energy minima at the bilayer-water interface as obtained with all-atom force fields. In the case of oligo-arginine peptides, the modified parameter sets predict interfacial free energy minima as well as free energy barriers in almost quantitative agreement with all-atom force field based simulations. Interfacial free energy minima predicted by a modified coarse-grained parameter set are -2.51, -4.28, and -5.42 for mono-, di-, and triarginine; corresponding values from all-atom simulations are -0.83, -3.33, and -3.29, respectively, all in units of kcal/mol. We found that a stronger interaction between oligo-arginine and the membrane components and a weaker interaction between oligo-arginine and water are crucial for producing such minima in PMFs using the polarizable CG model. The difference between bulk aqueous and bilayer center states predicted by the modified coarse-grain force field are 11.71, 14.14, and 16.53 kcal/mol, and those by the all-atom model are 6.94, 8.64, and 12.80 kcal/mol; those are of almost the same order of magnitude. Our simulations also demonstrate a remarkable similarity in the structural aspects of the ensemble of configurations generated using the all-atom and coarse-grain force fields. Both resolutions show that oligo-arginine peptides adopt preferential orientations as they translocate into the bilayer. The guiding theme centers on charged groups maintaining coordination with polar and charged bilayer components as well as local water. We also observe similar behaviors related with membrane deformations.

Enhanced sampling techniques in molecular dynamics simulations of biological systems.

PubMed

Bernardi, Rafael C; Melo, Marcelo C R; Schulten, Klaus

2015-05-01

Molecular dynamics has emerged as an important research methodology covering systems to the level of millions of atoms. However, insufficient sampling often limits its application. The limitation is due to rough energy landscapes, with many local minima separated by high-energy barriers, which govern the biomolecular motion. In the past few decades methods have been developed that address the sampling problem, such as replica-exchange molecular dynamics, metadynamics and simulated annealing. Here we present an overview over theses sampling methods in an attempt to shed light on which should be selected depending on the type of system property studied. Enhanced sampling methods have been employed for a broad range of biological systems and the choice of a suitable method is connected to biological and physical characteristics of the system, in particular system size. While metadynamics and replica-exchange molecular dynamics are the most adopted sampling methods to study biomolecular dynamics, simulated annealing is well suited to characterize very flexible systems. The use of annealing methods for a long time was restricted to simulation of small proteins; however, a variant of the method, generalized simulated annealing, can be employed at a relatively low computational cost to large macromolecular complexes. Molecular dynamics trajectories frequently do not reach all relevant conformational substates, for example those connected with biological function, a problem that can be addressed by employing enhanced sampling algorithms. This article is part of a Special Issue entitled Recent developments of molecular dynamics. Copyright © 2014 Elsevier B.V. All rights reserved.

a New Multimodal Multi-Criteria Route Planning Model by Integrating a Fuzzy-Ahp Weighting Method and a Simulated Annealing Algorithm

NASA Astrophysics Data System (ADS)

Ghaderi, F.; Pahlavani, P.

2015-12-01

A multimodal multi-criteria route planning (MMRP) system provides an optimal multimodal route from an origin point to a destination point considering two or more criteria in a way this route can be a combination of public and private transportation modes. In this paper, the simulate annealing (SA) and the fuzzy analytical hierarchy process (fuzzy AHP) were combined in order to find this route. In this regard, firstly, the effective criteria that are significant for users in their trip were determined. Then the weight of each criterion was calculated using the fuzzy AHP weighting method. The most important characteristic of this weighting method is the use of fuzzy numbers that aids the users to consider their uncertainty in pairwise comparison of criteria. After determining the criteria weights, the proposed SA algorithm were used for determining an optimal route from an origin to a destination. One of the most important problems in a meta-heuristic algorithm is trapping in local minima. In this study, five transportation modes, including subway, bus rapid transit (BRT), taxi, walking, and bus were considered for moving between nodes. Also, the fare, the time, the user's bother, and the length of the path were considered as effective criteria for solving the problem. The proposed model was implemented in an area in centre of Tehran in a GUI MATLAB programming language. The results showed a high efficiency and speed of the proposed algorithm that support our analyses.

Detection-dependent kinetics as a probe of folding landscape microstructure.

PubMed

Yang, Wei Yuan; Gruebele, Martin

2004-06-30

The folding landscapes of polypeptides and proteins exhibit a hierarchy of local minima. The causes range from proline isomerization all the way down to microstructure in the free energy caused by residual frustration inherent in even the best 20 amino acid design. The corresponding time scales range from hours to submicroseconds. The smallest microstructures are difficult to detect. We have measured the folding/unfolding kinetics of the engineered trpzip2 peptide at different tryptophan fluorescence wavelengths, each yielding a different rate. Wavelength-dependent folding kinetics on 0.1-2 mus time scales show that different microstructures with a range of solvent exposure and local dynamics are populated. We estimate a lower limit for the roughness of the free energy surface based on the range of rates observed.

Time-dependent local density approximation study of iodine photoionization delay

NASA Astrophysics Data System (ADS)

Magrakvelidze, Maia; Chakraborty, Himadri

2017-04-01

We investigate dipole quantum phases and Wigner-Smith (WS) time delays in the photoionization of iodine using Kohn-Sham time-dependent local density approximation (TDLDA) with the Leeuwen and Baerends exchange-correlation functional. Study of the effects of electron correlations on the absolute as well as relative delays in emissions from both valence 5p and 5s, and core 4d, 4p and 4s levels has been carried out. Particular emphasis is paid to unravel the role of correlations to induce structures in the delay as a function of energy at resonances and Cooper minima. The results should encourage attosecond measurements of iodine photoemission and probe the WS-temporal landscape of an open-shell atomic system. This work was supported by the U.S. National Science Foundation.

Localization or tunneling in asymmetric double-well potentials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Dae-Yup, E-mail: dsong@sunchon.ac.kr

An asymmetric double-well potential is considered, assuming that the wells are parabolic around the minima. The WKB wave function of a given energy is constructed inside the barrier between the wells. By matching the WKB function to the exact wave functions of the parabolic wells on both sides of the barrier, for two almost degenerate states, we find a quantization condition for the energy levels which reproduces the known energy splitting formula between the two states. For the other low-lying non-degenerate states, we show that the eigenfunction should be primarily localized in one of the wells with negligible magnitude inmore » the other. Using Dekker’s method (Dekker, 1987), the present analysis generalizes earlier results for weakly biased double-well potentials to systems with arbitrary asymmetry.« less

Allelopathic Activity and Chemical Composition of Rhynchosia minima (L.) DC. Essential Oil from Egypt.

PubMed

Abd El-Gawad, Ahmed M; El-Amier, Yasser A; Bonanomi, Giuliano

2018-01-01

Aromatic plants attract the attention of many researchers worldwide due to their worthy applications in agriculture, human prosperity, and the environment. Essential oil (EO) could be exploited as effective alternatives to synthetic compounds as it has several biological activities including allelopathy. The EO from the aerial parts of Rhynchosia minima was extracted by hydrodistillation and investigated by gas chromatography/mass spectrometry (GC/MS). Different concentrations (50, 100, 150 and 200 μL L -1 ) of the EO were prepared for investigation of their allelopathic potential on two weeds; Dactyloctenium aegyptium and Rumex dentatus. Twenty-eight compounds, mainly sesquiterpenes (69.13%) were determined. The major compounds are α-eudesmol, 2-allyl-5-tert-butylhydroquinone, caryophyllene oxide, trans-caryophyllene, and τ-cadinol. The EO from the R. minima showed a significant inhibition of D. aegyptium and R. dentatus germination, while the seedling growth was stimulated. Therefore, it is not recommended to treat these noxious weeds with the EO of R. minima before the germination. In contrast, the apparent stimulatory effect on the seedling growth offers further studies to use the EO of R. minima to enhance the fitness of different economic crops. However, characterization of green bio-herbicides such as EO (allelochemicals) from wild plants raises a new opportunity for the incorporation of new technology of bio-control against the noxious weeds. © 2018 Wiley-VHCA AG, Zurich, Switzerland.

Sunrise effects on VLF signals propagating over a long north-south path

NASA Astrophysics Data System (ADS)

Clilverd, Mark A.; Thomson, Neil R.; Rodger, Craig J.

1999-07-01

We present a detailed study of the times of amplitude minima observed on the 12-Mm path from NAA (24 kHz, 1 MW, Cutler, Maine) to Faraday, Antarctica, during the period 1990-1995. (NAA is a naval transmitter call sign.) This study represents the first account of the effect of the sunrise terminator when it is parallel to a propagation path at some times of the year. Since the NAA-Faraday path is within 3° of the north-south meridian, parallel orientation happens close to the equinoxes, while the maximum angle of incidence occurs during the solstices. During the solstices the terminator takes a significant length of time to cross the entire propagation path, so modal conversion effects are observed over a range of hours. During the equinoxes, however, the leading edge of the night-day transition region crosses the whole propagation path within 20 min. The interpretation of the timing of minima is consistent with modal conversion taking place as the sunrise terminator crosses the NAA-Faraday transmission path at specific, consistent locations. The timing of minima is remarkably consistent from year to year. Long wave propagation modeling is used to show that the location of nightside minima at an altitude of 45-75 km in the subionospheric waveguide represents the location of the sunrise terminator on the great circle path when dayside minima occur.

Shape Optimization of Cylindrical Shell for Interior Noise

NASA Technical Reports Server (NTRS)

Robinson, Jay H.

1999-01-01

In this paper an analytic method is used to solve for the cross spectral density of the interior acoustic response of a cylinder with nonuniform thickness subjected to turbulent boundary layer excitation. The cylinder is of honeycomb core construction with the thickness of the core material expressed as a cosine series in the circumferential direction. The coefficients of this series are used as the design variable in the optimization study. The objective function is the space and frequency averaged acoustic response. Results confirm the presence of multiple local minima as previously reported and demonstrate the potential for modest noise reduction.

Spitzer Observations of OGLE-2015-BLG-1212 Reveal a New Path toward Breaking Strong Microlens Degeneracies

NASA Technical Reports Server (NTRS)

Bozza, V.; Shvartzvald, Y.; Udalski, A.; Novati, S.Calchi; Bond, I. A.; Han, C.; Hundertmark, M.; Poleski, R.; Pawlak, M.; Szymanski, M. K.;

Energy-switching potential energy surface for ground-state C3

NASA Astrophysics Data System (ADS)

Rocha, C. M. R.; Varandas, A. J. C.

2018-05-01

The multiple energy switching scheme [J. Chem. Phys. 119 (2003) 2596] has been used to improve the double many-body expansion (DMBE II) potential energy surface of C3 near its linear global minima by morphing it with an accurate Taylor-series expansion [J. Chem. Phys. 144 (2016) 044307]. The final ES form attains the accuracy of the local form in reproducing the rovibrational spectrum of C3 while keeping unaltered all key attributes of the original DMBE II, namely conical intersection seams and dissociative channels. The ES form is therefore commended for adiabatic spectroscopic and reaction dynamics studies.

A Method to Retrieve Rainfall Rate over Land from TRMM Observations

NASA Technical Reports Server (NTRS)

Prabhakara, C.; Iacovazzi, R., Jr.; Yoo, J.-M.

2002-01-01

Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) observations over mesoscale convective systems (MCSs) reveal that there are localized maxima in the rain rate with a scale of about 10 to 20 km that represent thunderstorms (Cbs). Some of these Cbs are developing or intense, while others are decaying or weak. These Cbs constitute only about 20 % of the rain area of a given MCS. Outside of Cbs, the average rain rate is much weaker than that within Cbs. From an analysis of the PR data, we find that the spatial distribution of rain and its character, convective or stratiform, is highly inhomogeneous. This complex nature of rain exists on a scale comparable to that of a Cb. The 85 GHz brightness temperature, T85, observations of the TRMM Microwave Imager (TMI) radiometer taken over an MCS reflect closely the PR rain rate pattern over land. Local maxima in rain rate shown by PR are observed as local minima in T85. Where there are no minima in T85, PR observations indicate there is light rain. However, the TMI brightness temperature measurements (Tbs) have poor ability to discriminate convective rain from stratiform rain. For this reason, a TMI rain retrieval procedure that depends primarily on the magnitude of Tbs performs poorly. In order to retrieve rain rate from TMI data on land one has to include the spatial distribution information deduced from the T85 data in the retrieval method. Then, quantitative estimation of rain rate can be accomplished. A TMI rain retrieval method developed along these lines can yield estimates of rain rate and its frequency distribution which agree closely with that given by PR. We find the current TRMM project TMI (Version 5) rain retrieval algorithm on land could be improved with the retrieval scheme developed here. To support the conceptual frame work of the rain retrieval method developed here, a theoretical analysis of the TMI brightness temperatures in convective and stratiform regions is presented.

Stochastic Methods for Aircraft Design

NASA Technical Reports Server (NTRS)

Pelz, Richard B.; Ogot, Madara

1998-01-01

The global stochastic optimization method, simulated annealing (SA), was adapted and applied to various problems in aircraft design. The research was aimed at overcoming the problem of finding an optimal design in a space with multiple minima and roughness ubiquitous to numerically generated nonlinear objective functions. SA was modified to reduce the number of objective function evaluations for an optimal design, historically the main criticism of stochastic methods. SA was applied to many CFD/MDO problems including: low sonic-boom bodies, minimum drag on supersonic fore-bodies, minimum drag on supersonic aeroelastic fore-bodies, minimum drag on HSCT aeroelastic wings, FLOPS preliminary design code, another preliminary aircraft design study with vortex lattice aerodynamics, HSR complete aircraft aerodynamics. In every case, SA provided a simple, robust and reliable optimization method which found optimal designs in order 100 objective function evaluations. Perhaps most importantly, from this academic/industrial project, technology has been successfully transferred; this method is the method of choice for optimization problems at Northrop Grumman.

Fast-flowering mini-maize: seed to seed in 60 days

USDA-ARS?s Scientific Manuscript database

Two lines of Zea mays were developed as a short-generation model for maize. The Fast-Flowering Mini-Maize (FFMM) lines A and B are robust inbred lines with a significantly shorter generation time, much smaller stature, and better greenhouse adaptation than traditional maize varieties. Five generatio...

Kepler-Daten von BR Cyg

NASA Astrophysics Data System (ADS)

Pagel, Lienhard

2015-01-01

In the Kepler field is the eclipsing binary BR Cyg. He is a BAV program star. In the KIC (Kepler Input Catalogue) he is associated with the identifier kplr009899416 [1]. There have been determined 1084 minima and as many secondary minima. Acknowledgement: This paper makes use of data from the Kepler exoplanetarchive.

Extending DFT-based genetic algorithms by atom-to-place re-assignment via perturbation theory: A systematic and unbiased approach to structures of mixed-metallic clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weigend, Florian, E-mail: florian.weigend@kit.edu

2014-10-07

Energy surfaces of metal clusters usually show a large variety of local minima. For homo-metallic species the energetically lowest can be found reliably with genetic algorithms, in combination with density functional theory without system-specific parameters. For mixed-metallic clusters this is much more difficult, as for a given arrangement of nuclei one has to find additionally the best of many possibilities of assigning different metal types to the individual positions. In the framework of electronic structure methods this second issue is treatable at comparably low cost at least for elements with similar atomic number by means of first-order perturbation theory, asmore » shown previously [F. Weigend, C. Schrodt, and R. Ahlrichs, J. Chem. Phys. 121, 10380 (2004)]. In the present contribution the extension of a genetic algorithm with the re-assignment of atom types to atom sites is proposed and tested for the search of the global minima of PtHf{sub 12} and [LaPb{sub 7}Bi{sub 7}]{sup 4−}. For both cases the (putative) global minimum is reliably found with the extended technique, which is not the case for the “pure” genetic algorithm.« less

Communication: Potentials of mean force study of ionic liquid ion pair aggregation in polar covalent molecule solvents

NASA Astrophysics Data System (ADS)

Bandlamudi, Santosh Rathan Paul; Benjamin, Kenneth M.

2018-05-01

Molecular dynamics (MD) simulations were conducted for 1-ethyl-3-methylimidazolium methylsulfate [EMIM][MeSO4] dissolved in six polar covalent molecules [acetic acid, acetone, chloroform, dimethyl sulfoxide (DMSO), isopropyl alcohol, and methanol] to understand the free energies of ionic liquid (IL) ion pairing/aggregation in the limit of infinite dilution. Free energy landscapes or potentials of mean force (PMF) were computed using umbrella sampling and the weighted histogram analysis method. The PMF studies showed the strongest IL ion pairing in chloroform, and the strength of IL ion pairing decreases in the order of chloroform, acetone, propanol, acetic acid, DMSO, and methanol. In the limit of infinite dilution, the free energy curves for IL ion aggregation in co-solvents were characterized by two distinct minima [global (˜3.6 Å) and local (˜5.7 Å)], while free energy values at these minima differed significantly for IL in each co-solvent. The PMF studies were extended for determining the free energy of IL ion aggregation as a function of concentration of methanol. Studies showed that as the concentration of methanol increased, the free energy of ion aggregation decreased, suggesting greater ion pair stability, in agreement with previously reported MD clustering and radial distribution function data.

Adults of the Waterfern Weevil, Stenopelmus rufinasus Gyllenhal (Coleoptera: Curculionidae) feed on a Non-Host Plant Salvinia minima Baker, in Louisiana

USDA-ARS?s Scientific Manuscript database

The waterfern weevil, Stenopelmus refinasus Gyllenhal, has previously been reported as host-specific, only feeding on plants in the genus Azolla. We report the first observations of S. rufinasus feeding on a non-host plant, Salvinia minima Baker, within the United States....

Grand minima of solar activity and sociodynamics of culture

NASA Astrophysics Data System (ADS)

Vladimirsky, B. M.

2012-12-01

Indices of creative productivity introduced by C. Murrey were used to verify S. Ertel's conclusion about a global increase in creative productivity during the prolonged minimum of solar activity in 1640-1710. It was found that these indices for mathematicians, philosophers, and scientists increase in the Maunder era by factor of 1.6 in comparison with intervals of the same length before and after the minimum. A similar effect was obtained for mathematicians and philosophers for five earlier equitype minima in total (an increase by a factor of 1.9). The regularity that is revealed is confirmed by the fact that the most important achievements of high-ranking mathematicians and philosophers during the whole time period (2300 years) considered in this study fall on epochs of reduced levels of solar activity. The rise in the probability of the generation of rational ideas during grand minima is reflected also in the fact that they precede the appearance of written language and farming. Ultra-low-frequency electromagnetic fields appear to serve as a physical agent stimulating the activity of the brain's left hemisphere during the epochs of minima.

The Nature of Grand Minima and Maxima from Fully Nonlinear Flux Transport Dynamos

DOE Office of Scientific and Technical Information (OSTI.GOV)

Inceoglu, Fadil; Arlt, Rainer; Rempel, Matthias, E-mail: finceoglu@aip.de

We aim to investigate the nature and occurrence characteristics of grand solar minimum and maximum periods, which are observed in the solar proxy records such as {sup 10}Be and {sup 14}C, using a fully nonlinear Babcock–Leighton type flux transport dynamo including momentum and entropy equations. The differential rotation and meridional circulation are generated from the effect of turbulent Reynolds stress and are subjected to back-reaction from the magnetic field. To generate grand minimum- and maximum-like periods in our simulations, we used random fluctuations in the angular momentum transport process, namely the Λ-mechanism, and in the Babcock–Leighton mechanism. To characterize themore » nature and occurrences of the identified grand minima and maxima in our simulations, we used the waiting time distribution analyses, which reflect whether the underlying distribution arises from a random or a memory-bearing process. The results show that, in the majority of the cases, the distributions of grand minima and maxima reveal that the nature of these events originates from memoryless processes. We also found that in our simulations the meridional circulation speed tends to be smaller during grand maximum, while it is faster during grand minimum periods. The radial differential rotation tends to be larger during grand maxima, while it is smaller during grand minima. The latitudinal differential rotation, on the other hand, is found to be larger during grand minima.« less

Rivaling the World's Smallest Reptiles: Discovery of Miniaturized and Microendemic New Species of Leaf Chameleons (Brookesia) from Northern Madagascar

PubMed Central

Glaw, Frank; Köhler, Jörn; Townsend, Ted M.; Vences, Miguel

2012-01-01

Background One clade of Malagasy leaf chameleons, the Brookesia minima group, is known to contain species that rank among the smallest amniotes in the world. We report on a previously unrecognized radiation of these miniaturized lizards comprising four new species described herein. Methodology/Principal Findings The newly discovered species appear to be restricted to single, mostly karstic, localities in extreme northern Madagascar: Brookesia confidens sp. n. from Ankarana, B. desperata sp. n. from Forêt d'Ambre, B. micra sp. n. from the islet Nosy Hara, and B. tristis sp. n. from Montagne des Français. Molecular phylogenetic analyses based on one mitochondrial and two nuclear genes of all nominal species in the B. minima group congruently support that the four new species, together with B. tuberculata from Montagne d'Ambre in northern Madagascar, form a strongly supported clade. This suggests that these species have diversified in geographical proximity in this small area. All species of the B. minima group, including the four newly described ones, are characterized by very deep genetic divergences of 18–32% in the ND2 gene and >6% in the 16S rRNA gene. Despite superficial similarities among all species of this group, their status as separate evolutionary lineages is also supported by moderate to strong differences in external morphology, and by clear differences in hemipenis structure. Conclusion/Significance The newly discovered dwarf chameleon species represent striking cases of miniaturization and microendemism and suggest the possibility of a range size-body size relationship in Malagasy reptiles. The newly described Brookesia micra reaches a maximum snout-vent length in males of 16 mm, and its total length in both sexes is less than 30 mm, ranking it among the smallest amniote vertebrates in the world. With a distribution limited to a very small islet, this species may represent an extreme case of island dwarfism. PMID:22348069

North west area of Tuscany, Italy : Are the solar maximum and solar minima a particular period for increased frequency of floods and local geological destabilization ?

NASA Astrophysics Data System (ADS)

Casati, Michele; Straser, Valentino; Feron, Alessandro

2017-04-01

The purpose of this study is to verify a possible relationship between solar activity transitions (minimum and maximum), seismic activity and atmospheric circulation in a particular area. The hypothesis has already been advanced by other authors and is found in studies, for example: [Sytinsky A.D.,1980,1987,1997][Mazzarella,Palumbo, 1989][Odintsov, et al, 2006][Khachikyan, Inchin, Lozbin, 2012][Czymzik,Markus, 2013][Nedeljko,Vujović,2014]. The geographical area studied is approximately 8x13 km sq. and includes villages such as Fivizzano and Equi Terme, in north-west Tuscany, Italy, on the Lunigiana/Garfagnana border. The North Apuan Fault Zone" (NAFZ) is found in the area of study and major historical earthquakes have occurred in this area [Di Naccio Deborah, et al., 2013]. In this research, we compared the local seismicity with heavy rainfall (in quantity) that occurred in a short time frame in this area (measured by the daily rain gauge accumulations). These events occurred during the numerous floods from 2009 to 2013 (the transition between the solar cycle SC23 and SC24 solar and the rise of solar cycle SC24). The data was provided by the hydrological sector of the Tuscan Region Hydrological Service (SIR) and the LaMMA consortium. In this study we hypothesize, a slow and continuous destabilizing action on local geological structures, due to the multiple and violent atmospheric disturbances (V-shaped, flash floods, squall-line, etc..). Destabilization that led to an earthquake of magnitude Mw 5.36, which occurred on 21 June 2013. Comparing the SIDC count of sunspots with: a) the historical local seismic events catalogue with magnitude M4.5 + (CPTI15, the 2015 version of the Parametric Catalogue of Italian Earthquakes), b) the recent earthquakes of magnitude M 2.5+, which occurred from 1984 (ISIDe working group (2016) version 1.0), and c) the historical reconstructed maximum annual flows of the Serchio river from 1750, the daily maximum annual flows of the Magra river since 1939 (Data provided by Serchio River Authority and Aauthority and Magra Interregional River Authority), we observe that floods and/or local seismic events occur more frequently when there are solar maximum and solar minima.

Chemopreventive Agents from Physalis minima Function as Michael Reaction Acceptors

PubMed Central

Men, Ruizhi; Li, Ning; Ding, Chihong; Tang, Yingzhan; Xing, Yachao; Ding, Wanjing; Ma, Zhongjun

2016-01-01

Background: The fruits of some varieties of genus Physalis have been used as delicious fruits and functional food in the Northeast of China. Materials and Methods: To reveal the functional material basis, we performed bioactivity-guided phytochemical research and chemopreventive effect assay of the constituents from Physalis minima. Results: It was demonstrated that the ethyl acetate extract of P. minima L. (EEPM) had potential quinone reductase (QR) inducing activity with induction ratio (IR, QR induction activity) value of 1.47 ± 0.24, and glutathione binding property as potential Michael reaction acceptors (with an α, β-unsaturated ketone moiety). Furthermore, bioactivity-guided phytochemical research led eight compounds (1–8), which were elucidated as 3-isopropyl-5-acetoxycyclohexene-2-one-1 (1), isophysalin B (2), physalin G (3), physalin D (4), physalin I (5), physordinose B (6), stigmasterol-3-O-β-D-glucopyranoside (7) and 5α-6β-dihydroxyphysalin R (8) on the basis of nuclear magnetic resonance spectroscopy analyses and HRESIMS. Then, isophysalin B (2) and physordinose B (6) showed significant QR inducing activity with IR value of 2.80 ± 0.19 and 2.38 ± 0.46, respectively. SUMMARY An ultra-performance liquid chromatographic method with glutathione as the substrate was used to detect the Michael reaction acceptors in extracts of Physalis minima (EPM)We investigated the chemical constituents of EPM guided by biological activity methodIsophysalin B (1) and physordinose B (6) showed strong quinone reductase inducing activity with induction ratio values of 2.80 ± 0.19 and 2.38 ± 0.46This study generated useful information for consumers and many encourage researchers to utilize edible fruits from Physalis as a source of phytochemicals Abbreviations used: EPM: Extracts of Physalis minima, EEPM: Ethyl acetate extract of Physalis minima L., GSH: Glutathione, MRAs: Michael reaction acceptors, QR: Quinone reductase. PMID:27279713

Effects of Energy Dissipation in the Sphere-Restricted Full Three-Body Problem

NASA Astrophysics Data System (ADS)

Gabriel, T. S. J.

Recently, the classical N-Body Problem has been adjusted to account for celestial bodies made of constituents of finite density. By imposing a minima on the achievable distance between particles, minimum energy resting states are allowed by the problem. The Full N-Body Problem allows for the dissipation of mechanical energy through surface-surface interactions via impacts or by way of tidal deformation. Barring exogeneous forces and allowing for the dissipation of energy, these systems have discrete, and sometimes multiple, minimum energy states for a given angular momentum. Building the dynamical framework of such finite density systems is a necessary process in outlining the evolution of rubble pile asteroids and other gravitational-granular systems such as protoplanetary discs, and potentially planetary rings, from a theoretical point of view. In all cases, resting states are expected to occur as a necessary step in the ongoing processes of solar system formation and evolution. Previous studies of this problem have been performed in the N=3 case where the bodies are indistinguishable spheres, with all possible relative equilibria and their stability having been identified as a function of the angular momentum of the system. These studies uncovered that at certain levels of angular momentum there exists two minimum energy states, a global and local minimum. Thus a question of interest is in which of these states a dissipative system would preferentially settle and the sensitivity of results to changes in dissipation parameters. Assuming equal-sized, perfectly-rigid bodies, this study investigates the dynamical evolution of three spheres under the influence of mutual gravity and impact mechanics as a function of dissipation parameters. A purpose-written, C-based, Hard Sphere Discrete Element Method code has been developed to integrate trajectories and resolve contact mechanics as grains evolve into minimum energy configurations. By testing many randomized initial conditions, statistics are measured regarding minimum energy states for a given angular momentum range. A trend in the Sphere-Restricted Full Three-Body Problem producing an end state of one configuration over another is found as a function of angular momentum and restitution.

Saddle point localization of molecular wavefunctions.

PubMed

Mellau, Georg Ch; Kyuberis, Alexandra A; Polyansky, Oleg L; Zobov, Nikolai; Field, Robert W

2016-09-15

The quantum mechanical description of isomerization is based on bound eigenstates of the molecular potential energy surface. For the near-minimum regions there is a textbook-based relationship between the potential and eigenenergies. Here we show how the saddle point region that connects the two minima is encoded in the eigenstates of the model quartic potential and in the energy levels of the [H, C, N] potential energy surface. We model the spacing of the eigenenergies with the energy dependent classical oscillation frequency decreasing to zero at the saddle point. The eigenstates with the smallest spacing are localized at the saddle point. The analysis of the HCN ↔ HNC isomerization states shows that the eigenstates with small energy spacing relative to the effective (v1, v3, ℓ) bending potentials are highly localized in the bending coordinate at the transition state. These spectroscopically detectable states represent a chemical marker of the transition state in the eigenenergy spectrum. The method developed here provides a basis for modeling characteristic patterns in the eigenenergy spectrum of bound states.

Adaptation, Growth, and Resilience in Biological Distribution Networks

NASA Astrophysics Data System (ADS)

Ronellenfitsch, Henrik; Katifori, Eleni

Highly optimized complex transport networks serve crucial functions in many man-made and natural systems such as power grids and plant or animal vasculature. Often, the relevant optimization functional is nonconvex and characterized by many local extrema. In general, finding the global, or nearly global optimum is difficult. In biological systems, it is believed that such an optimal state is slowly achieved through natural selection. However, general coarse grained models for flow networks with local positive feedback rules for the vessel conductivity typically get trapped in low efficiency, local minima. We show how the growth of the underlying tissue, coupled to the dynamical equations for network development, can drive the system to a dramatically improved optimal state. This general model provides a surprisingly simple explanation for the appearance of highly optimized transport networks in biology such as plant and animal vasculature. In addition, we show how the incorporation of spatially collective fluctuating sources yields a minimal model of realistic reticulation in distribution networks and thus resilience against damage.

Comparison of two interpolation methods for empirical mode decomposition based evaluation of radiographic femur bone images.

PubMed

Udhayakumar, Ganesan; Sujatha, Chinnaswamy Manoharan; Ramakrishnan, Swaminathan

2013-01-01

Analysis of bone strength in radiographic images is an important component of estimation of bone quality in diseases such as osteoporosis. Conventional radiographic femur bone images are used to analyze its architecture using bi-dimensional empirical mode decomposition method. Surface interpolation of local maxima and minima points of an image is a crucial part of bi-dimensional empirical mode decomposition method and the choice of appropriate interpolation depends on specific structure of the problem. In this work, two interpolation methods of bi-dimensional empirical mode decomposition are analyzed to characterize the trabecular femur bone architecture of radiographic images. The trabecular bone regions of normal and osteoporotic femur bone images (N = 40) recorded under standard condition are used for this study. The compressive and tensile strength regions of the images are delineated using pre-processing procedures. The delineated images are decomposed into their corresponding intrinsic mode functions using interpolation methods such as Radial basis function multiquadratic and hierarchical b-spline techniques. Results show that bi-dimensional empirical mode decomposition analyses using both interpolations are able to represent architectural variations of femur bone radiographic images. As the strength of the bone depends on architectural variation in addition to bone mass, this study seems to be clinically useful.

Chaotic Particle Swarm Optimization with Mutation for Classification

PubMed Central

Assarzadeh, Zahra; Naghsh-Nilchi, Ahmad Reza

2015-01-01

In this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classify patterns of different classes in the feature space. The introduced mutation operators and chaotic sequences allows us to overcome the problem of early convergence into a local minima associated with particle swarm optimization algorithms. That is, the mutation operator sharpens the convergence and it tunes the best possible solution. Furthermore, to remove the irrelevant data and reduce the dimensionality of medical datasets, a feature selection approach using binary version of the proposed particle swarm optimization is introduced. In order to demonstrate the effectiveness of our proposed classifier, mutation-based classifier particle swarm optimization, it is checked out with three sets of data classifications namely, Wisconsin diagnostic breast cancer, Wisconsin breast cancer and heart-statlog, with different feature vector dimensions. The proposed algorithm is compared with different classifier algorithms including k-nearest neighbor, as a conventional classifier, particle swarm-classifier, genetic algorithm, and Imperialist competitive algorithm-classifier, as more sophisticated ones. The performance of each classifier was evaluated by calculating the accuracy, sensitivity, specificity and Matthews's correlation coefficient. The experimental results show that the mutation-based classifier particle swarm optimization unequivocally performs better than all the compared algorithms. PMID:25709937

A trajectory planning scheme for spacecraft in the space station environment. M.S. Thesis - University of California

NASA Technical Reports Server (NTRS)

Soller, Jeffrey Alan; Grunwald, Arthur J.; Ellis, Stephen R.

1991-01-01

Simulated annealing is used to solve a minimum fuel trajectory problem in the space station environment. The environment is special because the space station will define a multivehicle environment in space. The optimization surface is a complex nonlinear function of the initial conditions of the chase and target crafts. Small permutations in the input conditions can result in abrupt changes to the optimization surface. Since no prior knowledge about the number or location of local minima on the surface is available, the optimization must be capable of functioning on a multimodal surface. It was reported in the literature that the simulated annealing algorithm is more effective on such surfaces than descent techniques using random starting points. The simulated annealing optimization was found to be capable of identifying a minimum fuel, two-burn trajectory subject to four constraints which are integrated into the optimization using a barrier method. The computations required to solve the optimization are fast enough that missions could be planned on board the space station. Potential applications for on board planning of missions are numerous. Future research topics may include optimal planning of multi-waypoint maneuvers using a knowledge base to guide the optimization, and a study aimed at developing robust annealing schedules for potential on board missions.

ClusPro: an automated docking and discrimination method for the prediction of protein complexes.

PubMed

Comeau, Stephen R; Gatchell, David W; Vajda, Sandor; Camacho, Carlos J

2004-01-01

Predicting protein interactions is one of the most challenging problems in functional genomics. Given two proteins known to interact, current docking methods evaluate billions of docked conformations by simple scoring functions, and in addition to near-native structures yield many false positives, i.e. structures with good surface complementarity but far from the native. We have developed a fast algorithm for filtering docked conformations with good surface complementarity, and ranking them based on their clustering properties. The free energy filters select complexes with lowest desolvation and electrostatic energies. Clustering is then used to smooth the local minima and to select the ones with the broadest energy wells-a property associated with the free energy at the binding site. The robustness of the method was tested on sets of 2000 docked conformations generated for 48 pairs of interacting proteins. In 31 of these cases, the top 10 predictions include at least one near-native complex, with an average RMSD of 5 A from the native structure. The docking and discrimination method also provides good results for a number of complexes that were used as targets in the Critical Assessment of PRedictions of Interactions experiment. The fully automated docking and discrimination server ClusPro can be found at http://structure.bu.edu

Local efficiency in fluvial systems: Lessons from Icicle Bend

NASA Astrophysics Data System (ADS)

Jerin, Tasnuba; Phillips, Jonathan

2017-04-01

Development of fluvial systems is often described and modeled in terms of principles related to maxima, minima, or optima of various hydraulic or energy parameters that can generally be encompassed by a principle of efficiency selection (more efficient flow routes tend to be preferentially selected and enhanced). However, efficiency selection is highly localized, and the cumulative effects of these local events may or may not produce more efficient pathways at a broader scale. This is illustrated by the case of Icicle Bend on Shawnee Run, a limestone bedrock stream in central Kentucky. Field evidence indicates that a paleochannel was abandoned during downcutting of the stream, and the relocation was analyzed using a flow partitioning model. The bend represents abandonment of a steeper, straighter, more efficient channel at the reach scale in favor of a longer, currently less steep and less efficient flow path. This apparently occurred owing to capture of Shawnee Run flow by a subsurface karst flow path that was subsequently exhumed. The development of Icicle Bend illustrates the local nature of efficiency selection and the role of historical contingency in geomorphic evolution.

Representing and computing regular languages on massively parallel networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, M.I.; O'Sullivan, J.A.; Boysam, B.

1991-01-01

This paper proposes a general method for incorporating rule-based constraints corresponding to regular languages into stochastic inference problems, thereby allowing for a unified representation of stochastic and syntactic pattern constraints. The authors' approach first established the formal connection of rules to Chomsky grammars, and generalizes the original work of Shannon on the encoding of rule-based channel sequences to Markov chains of maximum entropy. This maximum entropy probabilistic view leads to Gibb's representations with potentials which have their number of minima growing at precisely the exponential rate that the language of deterministically constrained sequences grow. These representations are coupled to stochasticmore » diffusion algorithms, which sample the language-constrained sequences by visiting the energy minima according to the underlying Gibbs' probability law. The coupling to stochastic search methods yields the all-important practical result that fully parallel stochastic cellular automata may be derived to generate samples from the rule-based constraint sets. The production rules and neighborhood state structure of the language of sequences directly determines the necessary connection structures of the required parallel computing surface. Representations of this type have been mapped to the DAP-510 massively-parallel processor consisting of 1024 mesh-connected bit-serial processing elements for performing automated segmentation of electron-micrograph images.« less

Hybrid optimization and Bayesian inference techniques for a non-smooth radiation detection problem

DOE PAGES

Stefanescu, Razvan; Schmidt, Kathleen; Hite, Jason; ...

2016-12-12

In this paper, we propose several algorithms to recover the location and intensity of a radiation source located in a simulated 250 × 180 m block of an urban center based on synthetic measurements. Radioactive decay and detection are Poisson random processes, so we employ likelihood functions based on this distribution. Owing to the domain geometry and the proposed response model, the negative logarithm of the likelihood is only piecewise continuous differentiable, and it has multiple local minima. To address these difficulties, we investigate three hybrid algorithms composed of mixed optimization techniques. For global optimization, we consider simulated annealing, particlemore » swarm, and genetic algorithm, which rely solely on objective function evaluations; that is, they do not evaluate the gradient in the objective function. By employing early stopping criteria for the global optimization methods, a pseudo-optimum point is obtained. This is subsequently utilized as the initial value by the deterministic implicit filtering method, which is able to find local extrema in non-smooth functions, to finish the search in a narrow domain. These new hybrid techniques, combining global optimization and implicit filtering address, difficulties associated with the non-smooth response, and their performances, are shown to significantly decrease the computational time over the global optimization methods. To quantify uncertainties associated with the source location and intensity, we employ the delayed rejection adaptive Metropolis and DiffeRential Evolution Adaptive Metropolis algorithms. Finally, marginal densities of the source properties are obtained, and the means of the chains compare accurately with the estimates produced by the hybrid algorithms.« less

Antibiotic activity of Emerimicin IV isolated from Emericellopsis minima from Talcahuano Bay, Chile.

PubMed

Inostroza, Alejandro; Lara, Liliana; Paz, Cristian; Perez, Andrés; Galleguillos, Felipe; Hernandez, Victor; Becerra, José; González-Rocha, Gerardo; Silva, Mario

2018-06-01

Due to the increasing emergence of resistance of bacterial pathogens to current antibiotics, we have examined the marine fungi present in sea sediments obtained 200 m offshore to discover new antibacterial compounds active against multidrug-resistant bacteria. One strain, identified as Emericellopsis minima, was isolated from sediments of Talcahuano Bay (Chile). From the liquid culture of E. minima, we isolated Emerimicin IV, a unique fungal peptaibol that exhibited antibacterial activity. The structure of this compound was assigned by interpretation of 1 H NMR and HR-LCMS data. Emerimicin IV showed bacteriostatic activity against clinical isolates of methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus faecalis with MIC values ranging between 100 and 12.5 μg/mL.

Systems and methods for separating particles utilizing engineered acoustic contrast capture particles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaduchak, Gregory; Ward, Michael D.

An apparatus for separating particles from a medium includes a capillary defining a flow path therein that is in fluid communication with a medium source. The medium source includes engineered acoustic contrast capture particle having a predetermined acoustic contrast. The apparatus includes a vibration generator that is operable to produce at least one acoustic field within the flow path. The acoustic field produces a force potential minima for positive acoustic contrast particles and a force potential minima for negative acoustic contrast particles in the flow path and drives the engineered acoustic contrast capture particles to either the force potential minimamore » for positive acoustic contrast particles or the force potential minima for negative acoustic contrast particles.« less

Apparatus for separating particles utilizing engineered acoustic contrast capture particles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaduchak, Gregory; Ward, Michael D

An apparatus for separating particles from a medium includes a capillary defining a flow path therein that is in fluid communication with a medium source. The medium source includes engineered acoustic contrast capture particle having a predetermined acoustic contrast. The apparatus includes a vibration generator that is operable to produce at least one acoustic field within the flow path. The acoustic field produces a force potential minima for positive acoustic contrast particles and a force potential minima for negative acoustic contrast particles in the flow path and drives the engineered acoustic contrast capture particles to either the force potential minimamore » for positive acoustic contrast particles or the force potential minima for negative acoustic contrast particles.« less

Incorporation of perception-based information in robot learning using fuzzy reinforcement learning agents

NASA Astrophysics Data System (ADS)

Zhou, Changjiu; Meng, Qingchun; Guo, Zhongwen; Qu, Wiefen; Yin, Bo

2002-04-01

Robot learning in unstructured environments has been proved to be an extremely challenging problem, mainly because of many uncertainties always present in the real world. Human beings, on the other hand, seem to cope very well with uncertain and unpredictable environments, often relying on perception-based information. Furthermore, humans beings can also utilize perceptions to guide their learning on those parts of the perception-action space that are actually relevant to the task. Therefore, we conduct a research aimed at improving robot learning through the incorporation of both perception-based and measurement-based information. For this reason, a fuzzy reinforcement learning (FRL) agent is proposed in this paper. Based on a neural-fuzzy architecture, different kinds of information can be incorporated into the FRL agent to initialise its action network, critic network and evaluation feedback module so as to accelerate its learning. By making use of the global optimisation capability of GAs (genetic algorithms), a GA-based FRL (GAFRL) agent is presented to solve the local minima problem in traditional actor-critic reinforcement learning. On the other hand, with the prediction capability of the critic network, GAs can perform a more effective global search. Different GAFRL agents are constructed and verified by using the simulation model of a physical biped robot. The simulation analysis shows that the biped learning rate for dynamic balance can be improved by incorporating perception-based information on biped balancing and walking evaluation. The biped robot can find its application in ocean exploration, detection or sea rescue activity, as well as military maritime activity.

Topology Trivialization and Large Deviations for the Minimum in the Simplest Random Optimization

NASA Astrophysics Data System (ADS)

Fyodorov, Yan V.; Le Doussal, Pierre

2014-01-01

Finding the global minimum of a cost function given by the sum of a quadratic and a linear form in N real variables over (N-1)-dimensional sphere is one of the simplest, yet paradigmatic problems in Optimization Theory known as the "trust region subproblem" or "constraint least square problem". When both terms in the cost function are random this amounts to studying the ground state energy of the simplest spherical spin glass in a random magnetic field. We first identify and study two distinct large-N scaling regimes in which the linear term (magnetic field) leads to a gradual topology trivialization, i.e. reduction in the total number {N}_{tot} of critical (stationary) points in the cost function landscape. In the first regime {N}_{tot} remains of the order N and the cost function (energy) has generically two almost degenerate minima with the Tracy-Widom (TW) statistics. In the second regime the number of critical points is of the order of unity with a finite probability for a single minimum. In that case the mean total number of extrema (minima and maxima) of the cost function is given by the Laplace transform of the TW density, and the distribution of the global minimum energy is expected to take a universal scaling form generalizing the TW law. Though the full form of that distribution is not yet known to us, one of its far tails can be inferred from the large deviation theory for the global minimum. In the rest of the paper we show how to use the replica method to obtain the probability density of the minimum energy in the large-deviation approximation by finding both the rate function and the leading pre-exponential factor.

Long range stress correlations in the inherent structures of liquids at rest

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chowdhury, Sadrul; Abraham, Sneha; Hudson, Toby

2016-03-28

Simulation studies of the atomic shear stress in the local potential energy minima (inherent structures) are reported for binary liquid mixtures in 2D and 3D. These inherent structure stresses are fundamental to slow stress relaxation and high viscosity in supercooled liquids. We find that the atomic shear stress in the inherent structures (IS’s) of both liquids at rest exhibits slowly decaying anisotropic correlations. We show that the stress correlations contribute significantly to the variance of the total shear stress of the IS configurations and consider the origins of the anisotropy and spatial extent of the stress correlations.

Anharmonicity and self-similarity of the free energy landscape of protein G.

PubMed

Pontiggia, F; Colombo, G; Micheletti, C; Orland, H

2007-01-26

The near-native free-energy landscape of protein G is investigated through 0.4-micros-long atomistic molecular dynamics simulations in an explicit solvent. A theoretical and computational framework is used to assess the time dependence of salient thermodynamical features. While the quasiharmonic character of the free energy is found to degrade in a few ns, the slow modes display a very mild dependence on the trajectory duration. This property originates from a striking self-similarity of the free-energy landscape embodied by the consistency of the principal directions of the local minima, where the system dwells for several ns, and of the virtual jumps connecting them.

WKB approximation and tunneling in theories with noncanonical kinetic terms

NASA Astrophysics Data System (ADS)

González, Mariana Carrillo; Masoumi, Ali; Solomon, Adam R.; Trodden, Mark

2017-09-01

Tunneling is a fascinating aspect of quantum mechanics that renders the local minima of a potential meta-stable, with important consequences for particle physics, for the early hot stage of the universe, and more speculatively, for the behavior of the putative multiverse. While this phenomenon has been studied extensively for systems which have canonical kinetic terms, many theories of fundamental physics contain fields with noncanonical kinetic structures. It is therefore desirable to have a detailed framework for calculating tunneling rates and initial states after tunneling for these theories. In this work we present such a rigorous formulation and illustrate its use by applying it to a number of examples.

Free energy landscapes of small peptides in an implicit solvent model determined by force-biased multicanonical molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Watanabe, Yukihisa S.; Kim, Jae Gil; Fukunishi, Yoshifumi; Nakamura, Haruki

2004-12-01

In order to investigate whether the implicit solvent (GB/SA) model could reproduce the free energy landscapes of peptides, the potential of mean forces (PMFs) of eight tripeptides was examined and compared with the PMFs of the explicit water model. The force-biased multicanonical molecular dynamics method was used for the enhanced conformational sampling. Consequently, the GB/SA model reproduced almost all the global and local minima in the PMFs observed with the explicit water model. However, the GB/SA model overestimated frequencies of the structures that are stabilized by intra-peptide hydrogen bonds.

Bursty, Broadband Electromagnetic Waves Associated with Thin Current Layers and Turbulent Magnetosheath Reconnection

NASA Technical Reports Server (NTRS)

Adrian, M. L.; Wendel, D. E.

2011-01-01

We investigate observations of intense bursts of electromagnetic wave energy in association with the thin current layers of turbulent magnetosheath reconnection. These observed emissions form two distinct types: (i) broadband emissions that extend continuously to lOs of Hertz; and (ii) structured bursts of emitted energy that occur above 80-Hz, often displaying features reminiscent of absorption bands and are observed at local minima in the magnetic field. We present detailed analyses of these intense bursts of electromagnetic energy and quantify their proximity to X- and O-nulls, as well as their correlation to the amount of magnetic energy converted by the process of magnetic reconnection.

Phase retrieval in generalized optical interferometry systems.

PubMed

Farriss, Wesley E; Fienup, James R; Malhotra, Tanya; Vamivakas, A Nick

2018-02-05

Modal analysis of an optical field via generalized interferometry (GI) is a novel technique that treats said field as a linear superposition of transverse modes and recovers the amplitudes of modal weighting coefficients. We use phase retrieval by nonlinear optimization to recover the phase of these modal weighting coefficients. Information diversity increases the robustness of the algorithm by better constraining the solution. Additionally, multiple sets of random starting phase values assist the algorithm in overcoming local minima. The algorithm was able to recover nearly all coefficient phases for simulated fields consisting of up to 21 superpositioned Hermite Gaussian modes from simulated data and proved to be resilient to shot noise.

Medial-based deformable models in nonconvex shape-spaces for medical image segmentation.

PubMed

McIntosh, Chris; Hamarneh, Ghassan

2012-01-01

We explore the application of genetic algorithms (GA) to deformable models through the proposition of a novel method for medical image segmentation that combines GA with nonconvex, localized, medial-based shape statistics. We replace the more typical gradient descent optimizer used in deformable models with GA, and the convex, implicit, global shape statistics with nonconvex, explicit, localized ones. Specifically, we propose GA to reduce typical deformable model weaknesses pertaining to model initialization, pose estimation and local minima, through the simultaneous evolution of a large number of models. Furthermore, we constrain the evolution, and thus reduce the size of the search-space, by using statistically-based deformable models whose deformations are intuitive (stretch, bulge, bend) and are driven in terms of localized principal modes of variation, instead of modes of variation across the entire shape that often fail to capture localized shape changes. Although GA are not guaranteed to achieve the global optima, our method compares favorably to the prevalent optimization techniques, convex/nonconvex gradient-based optimizers and to globally optimal graph-theoretic combinatorial optimization techniques, when applied to the task of corpus callosum segmentation in 50 mid-sagittal brain magnetic resonance images.

Feasibility of Equivalent Dipole Models for Electroencephalogram-Based Brain Computer Interfaces.

PubMed

Schimpf, Paul H

2017-09-15

This article examines the localization errors of equivalent dipolar sources inverted from the surface electroencephalogram in order to determine the feasibility of using their location as classification parameters for non-invasive brain computer interfaces. Inverse localization errors are examined for two head models: a model represented by four concentric spheres and a realistic model based on medical imagery. It is shown that the spherical model results in localization ambiguity such that a number of dipolar sources, with different azimuths and varying orientations, provide a near match to the electroencephalogram of the best equivalent source. No such ambiguity exists for the elevation of inverted sources, indicating that for spherical head models, only the elevation of inverted sources (and not the azimuth) can be expected to provide meaningful classification parameters for brain-computer interfaces. In a realistic head model, all three parameters of the inverted source location are found to be reliable, providing a more robust set of parameters. In both cases, the residual error hypersurfaces demonstrate local minima, indicating that a search for the best-matching sources should be global. Source localization error vs. signal-to-noise ratio is also demonstrated for both head models.

Algorithm based on the Thomson problem for determination of equilibrium structures of metal nanoclusters

NASA Astrophysics Data System (ADS)

Arias, E.; Florez, E.; Pérez-Torres, J. F.

2017-06-01

A new algorithm for the determination of equilibrium structures suitable for metal nanoclusters is proposed. The algorithm performs a stochastic search of the minima associated with the nuclear potential energy function restricted to a sphere (similar to the Thomson problem), in order to guess configurations of the nuclear positions. Subsequently, the guessed configurations are further optimized driven by the total energy function using the conventional gradient descent method. This methodology is equivalent to using the valence shell electron pair repulsion model in guessing initial configurations in the traditional molecular quantum chemistry. The framework is illustrated in several clusters of increasing complexity: Cu7, Cu9, and Cu11 as benchmark systems, and Cu38 and Ni9 as novel systems. New equilibrium structures for Cu9, Cu11, Cu38, and Ni9 are reported.

Algorithm based on the Thomson problem for determination of equilibrium structures of metal nanoclusters.

PubMed

Arias, E; Florez, E; Pérez-Torres, J F

2017-06-28

A new algorithm for the determination of equilibrium structures suitable for metal nanoclusters is proposed. The algorithm performs a stochastic search of the minima associated with the nuclear potential energy function restricted to a sphere (similar to the Thomson problem), in order to guess configurations of the nuclear positions. Subsequently, the guessed configurations are further optimized driven by the total energy function using the conventional gradient descent method. This methodology is equivalent to using the valence shell electron pair repulsion model in guessing initial configurations in the traditional molecular quantum chemistry. The framework is illustrated in several clusters of increasing complexity: Cu 7 , Cu 9 , and Cu 11 as benchmark systems, and Cu 38 and Ni 9 as novel systems. New equilibrium structures for Cu 9 , Cu 11 , Cu 38 , and Ni 9 are reported.

Toroidal high-spin isomers in the nucleus 304120

NASA Astrophysics Data System (ADS)

Staszczak, A.; Wong, Cheuk-Yin; Kosior, A.

2017-05-01

Background: Strongly deformed oblate superheavy nuclei form an intriguing region where the toroidal nuclear structures may bifurcate from the oblate spheroidal shape. The bifurcation may be facilitated when the nucleus is endowed with a large angular moment about the symmetry axis with I =Iz . The toroidal high-K isomeric states at their local energy minima can be theoretically predicted using the cranked self-consistent Skyrme-Hartree-Fock method. Purpose: We use the cranked Skyrme-Hartree-Fock method to predict the properties of the toroidal high-spin isomers in the superheavy nucleus 120304184. Method: Our method consists of three steps: First, we use the deformation-constrained Skyrme-Hartree-Fock-Bogoliubov approach to search for the nuclear density distributions with toroidal shapes. Next, using these toroidal distributions as starting configurations, we apply an additional cranking constraint of a large angular momentum I =Iz about the symmetry z axis and search for the energy minima of the system as a function of the deformation. In the last step, if a local energy minimum with I =Iz is found, we perform at this point the cranked symmetry- and deformation-unconstrained Skyrme-Hartree-Fock calculations to locate a stable toroidal high-spin isomeric state in free convergence. Results: We have theoretically located two toroidal high-spin isomeric states of 120304184 with an angular momentum I =Iz=81 ℏ (proton 2p-2h, neutron 4p-4h excitation) and I =Iz=208 ℏ (proton 5p-5h, neutron 8p-8h) at the quadrupole moment deformations Q20=-297.7 b and Q20=-300.8 b with energies 79.2 and 101.6 MeV above the spherical ground state, respectively. The nuclear density distributions of the toroidal high-spin isomers 120304184(Iz=81 ℏ and 208 ℏ ) have the maximum density close to the nuclear matter density, 0.16 fm-3, and a torus major to minor radius aspect ratio R /d =3.25 . Conclusions: We demonstrate that aligned angular momenta of Iz=81 ℏ and 208 ℏ arising from multiparticle-multihole excitations in the toroidal system of 120304184 can lead to high-spin isomeric states, even though the toroidal shape of 120304184 without spin is unstable. Toroidal energy minima without spin may be possible for superheavy nuclei with higher atomic numbers, Z ≳122 , as reported previously [7 A. Staszczak and C. Y. Wong, Acta Phys. Pol. B 40, 753 (2008)].

Toroidal high-spin isomers in the nucleus 120 304

DOE PAGES

Staszczak, A.; Wong, Cheuk-Yin; Kosior, A.

2017-05-22

Strongly deformed oblate superheavy nuclei form an intriguing region where the toroidal nuclear structures may bifurcate from the oblate spheroidal shape. The bifurcation may be facilitated when the nucleus is endowed with a large angular moment about the symmetry axis withmore » $$I=I_{z}$$. The toroidal high-$K$ isomeric states at their local energy minima can be theoretically predicted using the cranked self-consistent Skyrme-Hartree-Fock method. We use the cranked Skyrme-Hartree-Fock method to predict the properties of the toroidal high-spin isomers in the superheavy nucleus $$^{304}{120}_{184}$$. This method consists of three steps: first, we use the deformation-constrained Skyrme-Hartree-Fock-Bogoliubov approach to search for the nuclear density distributions with toroidal shapes. Next, using these toroidal distributions as starting configurations we apply an additional cranking constraint of a large angular momentum $$I=I_{z}$$ about the symmetry $z$-axis and search for the energy minima of the system as a function of the deformation. In the last step, if a local energy minimum with $$I=I_{z}$$ is found, we perform at this point the cranked symmetry- and deformation-unconstrained Skyrme-Hartree-Fock calculations to locate a stable toroidal high-spin isomeric state in free convergence. Furthemore, we have theoretically located two toroidal high-spin isomeric states of $$^{304}{120}_{184}$$ with an angular momentum $I$=$$I_z$$=81$$\\hbar$$ (proton 2p-2h, neutron 4p-4h excitation) and $I$=$$I_z$$=208$$\\hbar$$ (proton 5p-5h, neutron 8p-8h) at the quadrupole moment deformations $$Q_{20}=-297.7$$~b and $$Q_{20}=-300.8$$~b with energies 79.2 MeV and 101.6 MeV above the spherical ground state, respectively. The nuclear density distributions of the toroidal high-spin isomers $$^{304}{120}_{184}(I_z$$=81$$\\hbar$$ and 208$$\\hbar$$) have the maximum density close to the nuclear matter density, 0.16 fm$$^{-3}$$, and a torus major to minor radius aspect ratio $R/d=3.25$. Here, we demonstrate that aligned angular momenta of $$I_z$$=81$$\\hbar$$ and 208$$\\hbar$$ arising from multi-particle-multi-hole excitations in the toroidal system of $$^{304}{120}_{184}$$ can lead to high-spin isomeric states, even though the toroidal shape of $$^{304}120_{184}$$ without spin is unstable. Toroidal energy minima without spin may be possible for superheavy nuclei with higher atomic numbers, $$Z\\gtrsim$$122, as reported previously [A. Staszczak and C. Y. Wong,Acta Phys. Pol. B 40 , 753 (2008)].« less

A fucoidan fraction purified from Chnoospora minima; a potential inhibitor of LPS-induced inflammatory responses.

PubMed

Fernando, I P Shanura; Sanjeewa, K K Asanka; Samarakoon, Kalpa W; Lee, Won Woo; Kim, Hyun-Soo; Kang, Nalae; Ranasinghe, P; Lee, Hyi-Seung; Jeon, You-Jin

2017-11-01

Fucoidans are an interesting group of bioactive sulfated polysaccharides abundant in brown seaweeds. The current study highlights the enrichment and extraction of fucoidan from Chnoospora minima by means of enzyme-assistant extraction using Celluclast and evaluation of its anti-inflammatory potential through in vitro and in vivo studies. The purified C. minima fucoidan (F2,4) inhibited the nitrous oxide (NO) production (IC 50 =27.82±0.88μg/ml) and expression of PGE 2 through the subsequent downregulation of iNOS and COX-2 expression in lipopolysaccharide (LPS) stimulated RAW 264.7 macrophages. F2,4 downregulated TNF-α, IL1-β, and IL-6 in RAW 264.7 macrophages in a dose-dependent manner and suppressed NO and ROS production in LPS stimulated zebrafish embryos while exerting a protective effect against the cell damage caused by LPS. Polysaccharide structural characterization was performed using FTIR, HPAE-PAD analysis of the monosaccharide content and NMR spectroscopy. Current findings confirm the potential anti-inflammatory activity of fucoidan purified from C. minima and elaborate its potential application as a functional ingredient in consumer products. Copyright © 2017 Elsevier B.V. All rights reserved.

Weiss oscillations and particle-hole symmetry at the half-filled Landau level

NASA Astrophysics Data System (ADS)

Cheung, Alfred K. C.; Raghu, S.; Mulligan, Michael

2017-06-01

Particle-hole symmetry in the lowest Landau level of the two-dimensional electron gas requires the electrical Hall conductivity to equal ±e2/2 h at half filling. We study the consequences of weakly broken particle-hole symmetry for magnetoresistance oscillations about half filling in the presence of an applied periodic one-dimensional electrostatic potential using the Dirac composite fermion theory proposed by Son [Son, Phys. Rev. X 5, 031027 (2015), 10.1103/PhysRevX.5.031027]. At fixed electron density, the oscillation minima are asymmetrically biased towards higher magnetic fields, while at fixed magnetic field the oscillations occur symmetrically as the electron density is varied about half filling. We find an approximate "sum rule" obeyed for all pairs of oscillation minima that can be tested in experiment. The locations of the magnetoresistance oscillation minima for the composite fermion theory of Halperin, Lee, and Read (HLR) and its particle-hole conjugate agree exactly. Within the current experimental resolution, the locations of the oscillation minima produced by the Dirac composite fermion coincide with those of HLR. These results may indicate that all three composite fermion theories describe the same long-wavelength physics.

Weiss oscillations and particle-hole symmetry at the half-filled Landau level

DOE PAGES

Cheung, Alfred K. C.; Raghu, S.; Mulligan, Michael

2017-06-15

Particle-hole symmetry in the lowest Landau level of the two-dimensional electron gas requires the electrical Hall conductivity to equal ± e 2/2h at half filling. Here, we study the consequences of weakly broken particle-hole symmetry for magnetoresistance oscillations about half filling in the presence of an applied periodic one-dimensional electrostatic potential using the Dirac composite fermion theory proposed by Son [Son, Phys. Rev. X 5, 031027 (2015)]. At fixed electron density, the oscillation minima are asymmetrically biased towards higher magnetic fields, while at fixed magnetic field the oscillations occur symmetrically as the electron density is varied about half filling. Wemore » find an approximate “sum rule” obeyed for all pairs of oscillation minima that can be tested in experiment. The locations of the magnetoresistance oscillation minima for the composite fermion theory of Halperin, Lee, and Read (HLR) and its particle-hole conjugate agree exactly. Within the current experimental resolution, the locations of the oscillation minima produced by the Dirac composite fermion coincide with those of HLR. These results may indicate that all three composite fermion theories describe the same long-wavelength physics.« less

Geomagnetic detection of the sectorial solar magnetic field and the historical peculiarity of minimum 23-24

USGS Publications Warehouse

Love, Jeffrey J.; Rigler, J.

2012-01-01

[1] Analysis is made of the geomagnetic-activityaaindex covering solar cycle 11 to the beginning of 24, 1868–2011. Autocorrelation shows 27.0-d recurrent geomagnetic activity that is well-known to be prominent during solar-cycle minima; some minima also exhibit a smaller amount of 13.5-d recurrence. Previous work has shown that the recent solar minimum 23–24 exhibited 9.0 and 6.7-d recurrence in geomagnetic and heliospheric data, but those recurrence intervals were not prominently present during the preceding minima 21–22 and 22–23. Using annual-averages and solar-cycle averages of autocorrelations of the historicalaadata, we put these observations into a long-term perspective: none of the 12 minima preceding 23–24 exhibited prominent 9.0 and 6.7-d geomagnetic activity recurrence. We show that the detection of these recurrence intervals can be traced to an unusual combination of sectorial spherical-harmonic structure in the solar magnetic field and anomalously low sunspot number. We speculate that 9.0 and 6.7-d recurrence is related to transient large-scale, low-latitude organization of the solar dynamo, such as seen in some numerical simulations.

Weiss oscillations and particle-hole symmetry at the half-filled Landau level

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cheung, Alfred K. C.; Raghu, S.; Mulligan, Michael

Particle-hole symmetry in the lowest Landau level of the two-dimensional electron gas requires the electrical Hall conductivity to equal ± e 2/2h at half filling. Here, we study the consequences of weakly broken particle-hole symmetry for magnetoresistance oscillations about half filling in the presence of an applied periodic one-dimensional electrostatic potential using the Dirac composite fermion theory proposed by Son [Son, Phys. Rev. X 5, 031027 (2015)]. At fixed electron density, the oscillation minima are asymmetrically biased towards higher magnetic fields, while at fixed magnetic field the oscillations occur symmetrically as the electron density is varied about half filling. Wemore » find an approximate “sum rule” obeyed for all pairs of oscillation minima that can be tested in experiment. The locations of the magnetoresistance oscillation minima for the composite fermion theory of Halperin, Lee, and Read (HLR) and its particle-hole conjugate agree exactly. Within the current experimental resolution, the locations of the oscillation minima produced by the Dirac composite fermion coincide with those of HLR. These results may indicate that all three composite fermion theories describe the same long-wavelength physics.« less

The mechanism of addition to a CN triple bond. An ab initio study of the first stages of the Stephen, Gatterman and Houben-Hoesch reactions

NASA Astrophysics Data System (ADS)

Alagona, Giuliano; Tomasi, Jacopo

The mechanism of addition of HCl to the triple bond of RCN (R=H, CH,) is studied by means of ab initio SCF and CI calculations. Geometries and energies of minima (initial H-bonded complexes, products) and saddle points (transition state) are completed by a determination of the intrinsic reaction coordinate and of a relatively large portion of the energy hypersurface. The evolution of the electronic structure along the reaction coordinate is interpreted using localized orbitals. Particular attention is paid to the effect of chemical substitution, for which a new test, based on the electrostatic forces acting on nuclei along the reaction coordinate, has been employed. CI calculations performed over canonical and localized orbitals are compared to determine whether the latter formulation is more convenient for non-equilibrium geometries.

Three-dimensional morphologies of inclined equiaxed dendrites growing under forced convection by phase-field-lattice Boltzmann method

NASA Astrophysics Data System (ADS)

Sakane, Shinji; Takaki, Tomohiro; Ohno, Munekazu; Shibuta, Yasushi; Shimokawabe, Takashi; Aoki, Takayuki

2018-02-01

Three-dimensional growth morphologies of equiaxed dendrites growing under forced convection, with their preferred growth direction inclined from the flow direction, were investigated by performing large-scale phase-field lattice Boltzmann simulations on a graphical-processing-unit supercomputer. The tip velocities of the dendrite arms with their preferred growth directions inclined toward the upstream and downstream directions increased and decreased, respectively, as a result of forced convection. In addition, the tip velocities decreased monotonically as the angle between the preferred growth direction and the upstream direction increased. Here, the degree of acceleration of the upstream tips was larger than the degree of deceleration of the downstream tips. The angles between the actual tip growth directions and the preferred growth direction of the dendrite arms exhibited a characteristic change with two local maxima and two local minima.

Mean Field Limits for Interacting Diffusions in a Two-Scale Potential

NASA Astrophysics Data System (ADS)

Gomes, S. N.; Pavliotis, G. A.

2018-06-01

In this paper, we study the combined mean field and homogenization limits for a system of weakly interacting diffusions moving in a two-scale, locally periodic confining potential, of the form considered in Duncan et al. (Brownian motion in an N-scale periodic potential, arXiv:1605.05854, 2016b). We show that, although the mean field and homogenization limits commute for finite times, they do not, in general, commute in the long time limit. In particular, the bifurcation diagrams for the stationary states can be different depending on the order with which we take the two limits. Furthermore, we construct the bifurcation diagram for the stationary McKean-Vlasov equation in a two-scale potential, before passing to the homogenization limit, and we analyze the effect of the multiple local minima in the confining potential on the number and the stability of stationary solutions.

Individual electron and hole localization in submonolayer InN quantum sheets embedded in GaN

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feix, F., E-mail: feix@pdi-berlin.de; Flissikowski, T.; Chèze, C.

2016-07-25

We investigate sub-monolayer InN quantum sheets embedded in GaN(0001) by temperature-dependent photoluminescence spectroscopy under both continuous-wave and pulsed excitation. Both the peak energy and the linewidth of the emission band associated with the quantum sheets exhibit an anomalous dependence on temperature indicative of carrier localization. Photoluminescence transients reveal a power law decay at low temperatures reflecting that the recombining electrons and holes occupy spatially separate, individual potential minima reminiscent of conventional (In,Ga)N(0001) quantum wells exhibiting the characteristic disorder of a random alloy. At elevated temperatures, carrier delocalization sets in and is accompanied by a thermally activated quenching of the emission.more » We ascribe the strong nonradiative recombination to extended states in the GaN barriers and confirm our assumption by a simple rate-equation model.« less

MONSS: A multi-objective nonlinear simplex search approach

NASA Astrophysics Data System (ADS)

Zapotecas-Martínez, Saúl; Coello Coello, Carlos A.

2016-01-01

This article presents a novel methodology for dealing with continuous box-constrained multi-objective optimization problems (MOPs). The proposed algorithm adopts a nonlinear simplex search scheme in order to obtain multiple elements of the Pareto optimal set. The search is directed by a well-distributed set of weight vectors, each of which defines a scalarization problem that is solved by deforming a simplex according to the movements described by Nelder and Mead's method. Considering an MOP with n decision variables, the simplex is constructed using n+1 solutions which minimize different scalarization problems defined by n+1 neighbor weight vectors. All solutions found in the search are used to update a set of solutions considered to be the minima for each separate problem. In this way, the proposed algorithm collectively obtains multiple trade-offs among the different conflicting objectives, while maintaining a proper representation of the Pareto optimal front. In this article, it is shown that a well-designed strategy using just mathematical programming techniques can be competitive with respect to the state-of-the-art multi-objective evolutionary algorithms against which it was compared.

An energy-based perturbation and a taboo strategy for improving the searching ability of stochastic structural optimization methods

NASA Astrophysics Data System (ADS)

Cheng, Longjiu; Cai, Wensheng; Shao, Xueguang

2005-03-01

An energy-based perturbation and a new idea of taboo strategy are proposed for structural optimization and applied in a benchmark problem, i.e., the optimization of Lennard-Jones (LJ) clusters. It is proved that the energy-based perturbation is much better than the traditional random perturbation both in convergence speed and searching ability when it is combined with a simple greedy method. By tabooing the most wide-spread funnel instead of the visited solutions, the hit rate of other funnels can be significantly improved. Global minima of (LJ) clusters up to 200 atoms are found with high efficiency.

B.R.N.O. Contributions #40 Times of minima

NASA Astrophysics Data System (ADS)

Juryšek, J.; Hoňková, K.; Šmelcer, L.; Mašek, M.; Lehký, M.; Bílek, F.; Mazanec, J.; Hanžl, D.; Magris, M.; Nosál, P.; Bragagnolo, U.; Medulka, T.; Vraš&tacute; ák, M.; Urbaník, M.; Auer, R. F.; Sergey, I.; Jacobsen, J.; Alessandroni, M. R.; Andreatta, C.; Antonio, Ch. F.; Artola, R.; Audejean, M.; Balanzino, L.; Banfi, M.; Bazán, R. S.; Borgonovo, M.; Cagaš, P.; Čaloud, J.; Campos, F.; Čapková, H.; Černíková, V.; Červinka, L.; Chiavassa, A.; Dřevěný, R.; Durantini, L. H.; Ferraro, M. E.; Ferrero, G.; Girardini, C.; Gudmundsson, S.; Guzzo, P.; Guevara, N.; Hladík, B.; Horník, M.; Jakš, S.; Janoštiak, L.; Jelínek, M.; Kalášek, J.; Kalmbach, R.; Kubica, T.; Kučáková, H.; Liška, J.; Lomoz, F.; López, O. Ch.; Lovato, B. M.; Morero, S.; Mrllák, R.; Mrňák, P.; Persha, G.; Pignata, R.; Pintr, P.; Popov, A.; Portillo, L. F. T.; Quiñones, C.; Rodriguez, E.; Ruocco, N.; Scaggiante, F.; Scavuzzo, A.; Šebela, P.; Šimkovič, S.; Školník, V.; Skubák, P.; Smolka, M.; Špecián, M.; Šuchaň, J.; Tornatore, M.; Trnka, J.; Tylšar, M.; Walter, F.; Zardin, D.; Zejda, M.; Zíbar, M.; Ziková, A.

2017-03-01

This paper presents 3394 times of minima for 1096 objects acquired by 82 members and cooperating observers of the Variable Star and Exoplanet Section of the Czech Astronomical Society (B.R.N.O. Observing project). Observations were carried out between October 2014 and November 2016. Some newly discovered stars by the observers of project B.R.N.O. are included in the list.

Optimization of coronagraph design for segmented aperture telescopes

NASA Astrophysics Data System (ADS)

Jewell, Jeffrey; Ruane, Garreth; Shaklan, Stuart; Mawet, Dimitri; Redding, Dave

2017-09-01

The goal of directly imaging Earth-like planets in the habitable zone of other stars has motivated the design of coronagraphs for use with large segmented aperture space telescopes. In order to achieve an optimal trade-off between planet light throughput and diffracted starlight suppression, we consider coronagraphs comprised of a stage of phase control implemented with deformable mirrors (or other optical elements), pupil plane apodization masks (gray scale or complex valued), and focal plane masks (either amplitude only or complex-valued, including phase only such as the vector vortex coronagraph). The optimization of these optical elements, with the goal of achieving 10 or more orders of magnitude in the suppression of on-axis (starlight) diffracted light, represents a challenging non-convex optimization problem with a nonlinear dependence on control degrees of freedom. We develop a new algorithmic approach to the design optimization problem, which we call the "Auxiliary Field Optimization" (AFO) algorithm. The central idea of the algorithm is to embed the original optimization problem, for either phase or amplitude (apodization) in various planes of the coronagraph, into a problem containing additional degrees of freedom, specifically fictitious "auxiliary" electric fields which serve as targets to inform the variation of our phase or amplitude parameters leading to good feasible designs. We present the algorithm, discuss details of its numerical implementation, and prove convergence to local minima of the objective function (here taken to be the intensity of the on-axis source in a "dark hole" region in the science focal plane). Finally, we present results showing application of the algorithm to both unobscured off-axis and obscured on-axis segmented telescope aperture designs. The application of the AFO algorithm to the coronagraph design problem has produced solutions which are capable of directly imaging planets in the habitable zone, provided end-to-end telescope system stability requirements can be met. Ongoing work includes advances of the AFO algorithm reported here to design in additional robustness to a resolved star, and other phase or amplitude aberrations to be encountered in a real segmented aperture space telescope.

Theoretical Studies of Interactions between O-Phosphorylated and Standard Amino-Acid Side-Chain Models in Water

PubMed Central

Wiśniewska, Marta; Sobolewski, Emil; Ołdziej, Stanisław; Liwo, Adam; Scheraga, Harold A.; Makowski, Mariusz

2015-01-01

Phosphorylation is a common post-translational modification of the amino-acid side chains (serine, tyrosine, and threonine) that contain hydroxyl groups. The transfer of the negatively charged phosphate group from an ATP molecule to such amino-acid side chains leads to changes in the local conformations of proteins and the pattern of interactions with other amino-acid side-chains. A convenient characteristic of the side chain–side chain interactions in the context of an aqueous environment is the potential of mean force (PMF) in water. A series of umbrella-sampling molecular dynamic (MD) simulations with the AMBER force field were carried out for pairs of O-phosphorylated serine (pSer), threonine (pThr), and tyrosine, (pTyr) with natural amino acids in a TIP3P water model as a solvent at 298 K. The weighted-histogram analysis method was used to calculate the four-dimensional potentials of mean force. The results demonstrate that the positions and depths of the contact minima and the positions and heights of the desolvation maxima, including their dependence on the relative orientation depend on the character of the interacting pairs. More distinct minima are observed for oppositely charged pairs such as, e.g., O-phosphorylated side-chains and positively charged ones, such as the side-chains of lysine and arginine. PMID:26100791

The role of Shabansky orbits in the generation of compression-related EMIC waves

NASA Astrophysics Data System (ADS)

McCollough, J. P.; Elkington, S. R.; Baker, D.

2009-12-01

Electromagnetic ion-cyclotron (EMIC) waves arise from temperature anisotropies in trapped warm plasma populations. In particular, EMIC waves at high L values near local noon are often found to be related to magnetospheric compression events. There are several possible mechanisms that can generate these temperature anisotropies: energizing processes, including adiabatic compression and shock-induced and radial transport; and non-energizing processes, such as drift shell splitting and the effects of off-equatorial minima on particle populations. In this work we investigate the role of off-equatorial minima in the generation of temperature anisotropies both at the magnetic equator and at higher latitudes. There are two kinds of behavior particles undergo in response: particles with high equatorial pitch angles (EPAs) are forced to execute so-called Shabanksy orbits and mirror at high latitudes without passing through the equator, and those with lower EPAs will pass through the equator with higher EPAs than before; as a result, perpendicular energies increase at the cost of parallel energies. By using a 3D particle tracing code in a tunable analytic compressed-dipole field, we parameterize the effects of Shabansky orbits on the anisotropy of the warm plasma. These results as well as evidence from simulations of a real event in which EMIC waves were observed (the compression event of 29 June 2007) are presented.

Flow-duration-frequency behaviour of British rivers based on annual minima data

NASA Astrophysics Data System (ADS)

Zaidman, Maxine D.; Keller, Virginie; Young, Andrew R.; Cadman, Daniel

2003-06-01

A comparison of different probability distribution models for describing the flow-duration-frequency behaviour of annual minima flow events in British rivers is reported. Twenty-five catchments were included in the study, each having stable and natural flow records of at least 30 years in length. Time series of annual minima D-day average flows were derived for each record using durations ( D) of 1, 7, 30, 60, 90, and 365 days and used to construct low flow frequency curves. In each case the Gringorten plotting position formula was used to determine probabilities (of non-exceedance). Four distribution types—Generalised Extreme Value (GEV), Generalised Logistic (GL), Pearson Type-3 (PE3) and Generalised Pareto (GP)—were used to model the probability distribution function for each site. L-moments were used to parameterise individual models, whilst goodness-of-fit tests were used to assess their match to the sample data. The study showed that where short durations (i.e. 60 days or less) were considered, high storage catchments tended to be best represented by GL and GEV distribution models whilst low storage catchments were best described by PE3 or GEV models. However, these models produced reasonable results only within a limited range (e.g. models for high storage catchments did not produce sensible estimates of return periods where the prescribed flow was less than 10% of the mean flow). For annual minima series derived using long duration flow averages (e.g. more than 90 days), GP and GEV models were generally more applicable. The study suggests that longer duration minima do not conform to the same distribution types as short durations, and that catchment properties can influence the type of distribution selected.

Computationally Efficient Characterization of Potential Energy Surfaces Based on Fingerprint Distances

NASA Astrophysics Data System (ADS)

Schaefer, Bastian; Goedecker, Stefan; Goedecker Group Team

Based on Lennard-Jones, Silicon, Sodium-Chloride and Gold clusters, it was found that uphill barrier energies of transition states between directly connected minima tend to increase with increasing structural differences of the two minima. Based on this insight it also turned out that post-processing minima hopping data at a negligible computational cost allows to obtain qualitative topological information on potential energy surfaces that can be stored in so called qualitative connectivity databases. These qualitative connectivity databases are used for generating fingerprint disconnectivity graphs that allow to obtain a first qualitative idea on thermodynamic and kinetic properties of a system of interest. This research was supported by the NCCR MARVEL, funded by the Swiss National Science Foundation. Computer time was provided by the Swiss National Supercomputing Centre (CSCS) under Project ID No. s499.

Urban Policies and Earthquake Risk Mitigation

NASA Astrophysics Data System (ADS)

Sarlo, Antonella

2008-07-01

The paper aims at proposing some considerations about some recent experiences of research carried out on the theme of earthquake risk mitigation and combining policies and actions of mitigation with urban development strategies. The objective was to go beyond the classical methodological approach aiming at defining a "technical" evaluation of the earthquake risk through a procedure which can correlate the three "components" of danger, exposure and vulnerability. These researches experiment, in terms of methodology and application, with a new category of interpretation and strategy: the so-called Struttura Urbana Minima (Minimum urban structure). Actually, the introduction of the Struttura Urbana Minima establishes a different approach towards the theme of safety in the field of earthquake risk, since it leads to a wider viewpoint, combining the building aspect of the issue with the purely urban one, involving not only town planning, but also social and managerial implications. In this sense the constituent logic of these researches is strengthened by two fundamental issues: - The social awareness of earthquake; - The inclusion of mitigation policies in the ordinary strategies for town and territory management. Three main aspects of the first point, that is of the "social awareness of earthquake", characterize this issue and demand to be considered within a prevention policy: - The central role of the risk as a social production, - The central role of the local community consent, - The central role of the local community capability to plan Therefore, consent, considered not only as acceptance, but above all as participation in the elaboration and implementation of choices, plays a crucial role in the wider issue of prevention policies. As far as the second point is concerned, the inclusion of preventive mitigation policies in ordinary strategies for the town and territory management demands the identification of criteria of choice and priorities of intervention and, as a consequence, the opportunity to promote an approach to the theme of mitigation policies realized through strategic principles and systemic logics able to shift the problem from the building to the town. The critical aspects of this theme are tied to three main issues: - The sharing of the way of interpreting town planning, - The integration of multiple objectives in one intervention tool, - The measures which can be adopted for an effective prevention policy. The above-mentioned elements have inspired these researches experimented on Calabrian towns. In particular, in this paper the experience carried out on Reggio Calabria is proposed. Its cultural roots derive from the principles and criteria experimented in small Calabrian towns, but it modifies them according to the complexity of the urban settlement, introducing also some experimental concepts and methodological approaches.

Increasing Slew Performance of Reaction Wheel Attitude Control Systems

DTIC Science & Technology

2013-09-01

vectors in any arbitrary direction creates the momentum envelope (Chapter IV). The shape of the reaction wheel momentum envelope is a polyhedron [15...performance. This procedural limitation further reduces the operable reaction wheel momentum space polyhedron to the largest inscribed sphere, which...respective plane. These minima are also the global minima, each marked in magenta. The four-wheel polyhedron is again shown in three orthogonal views in

Is There a CME Rate Floor? CME and Magnetic Flux Values for the Last Four Solar Cycle Minima

NASA Astrophysics Data System (ADS)

Webb, D. F.; Howard, R. A.; St. Cyr, O. C.; Vourlidas, A.

2017-12-01

The recent prolonged activity minimum has led to the question of whether there is a base level of the solar magnetic field evolution that yields a “floor” in activity levels and also in the solar wind magnetic field strength. Recently, a flux transport model coupled with magneto-frictional simulations has been used to simulate the continuous magnetic field evolution in the global solar corona for over 15 years, from 1996 to 2012. Flux rope eruptions in the simulations are estimated (Yeates), and the results are in remarkable agreement with the shape of the SOlar Heliospheric Observatory/Large Angle and Spectrometric Coronagraph Experiment coronal mass ejection (CME) rate distribution. The eruption rates at the two recent minima approximate the observed-corrected CME rates, supporting the idea of a base level of solar magnetic activity. In this paper, we address this issue by comparing annual averages of the CME occurrence rates during the last four solar cycle minima with several tracers of the global solar magnetic field. We conclude that CME activity never ceases during a cycle, but maintains a base level of 1 CME every 1.5 to ∼3 days during minima. We discuss the sources of these CMEs.

Analysis of B3LYP and MP2 conformational population distributions in trans-nicotine, acetylcholine, and ABT-594

NASA Astrophysics Data System (ADS)

Mora, M.; Castro, M. E.; Niño, A.; Melendez, F. J.; Muñoz-Caro, C.

This work presents an analysis of the equivalence of MP2 and DFT (B3LYP functional) conformational populations. As a test case, we select three cholinergic agents (trans-nicotine, acetylcholine, and the nicotinic analgesic ABT-594), where the minima on the conformational energy hypersurfaces expand a large range of energies (˜0-30 kJ mol-1). From energetic and structural data obtained in vacuo at the MP2 and B3LYP/cc-pVDZ levels, we build conformational partition functions, including the effect of the conformational kinetic energy and the rotovibrational coupling. Our results at a physiological temperature (37°C) show qualitative agreement in all cases. Quantitative agreement, however, is only found for trans-nicotine and ABT-594. In the first case, energy minima differ by <0.2 kJ mol-1. Therefore, the equivalence of structural results translates in the equivalence of the conformational distribution. For ABT-594, the minima are separated by as much as 8.0 kJ mol-1, and the conformational energy determines the conformational distribution. In this case, the slight relative variation of conformational energy, between B3LYP and MP2, does not affect the population, since the secondary minima are high in energy and very low in population.

Hybrid genetic algorithm in the Hopfield network for maximum 2-satisfiability problem

NASA Astrophysics Data System (ADS)

Kasihmuddin, Mohd Shareduwan Mohd; Sathasivam, Saratha; Mansor, Mohd. Asyraf

2017-08-01

Heuristic method was designed for finding optimal solution more quickly compared to classical methods which are too complex to comprehend. In this study, a hybrid approach that utilizes Hopfield network and genetic algorithm in doing maximum 2-Satisfiability problem (MAX-2SAT) was proposed. Hopfield neural network was used to minimize logical inconsistency in interpretations of logic clauses or program. Genetic algorithm (GA) has pioneered the implementation of methods that exploit the idea of combination and reproduce a better solution. The simulation incorporated with and without genetic algorithm will be examined by using Microsoft Visual 2013 C++ Express software. The performance of both searching techniques in doing MAX-2SAT was evaluate based on global minima ratio, ratio of satisfied clause and computation time. The result obtained form the computer simulation demonstrates the effectiveness and acceleration features of genetic algorithm in doing MAX-2SAT in Hopfield network.

Improved Gravitation Field Algorithm and Its Application in Hierarchical Clustering

PubMed Central

Zheng, Ming; Sun, Ying; Liu, Gui-xia; Zhou, You; Zhou, Chun-guang

2012-01-01

Background Gravitation field algorithm (GFA) is a new optimization algorithm which is based on an imitation of natural phenomena. GFA can do well both for searching global minimum and multi-minima in computational biology. But GFA needs to be improved for increasing efficiency, and modified for applying to some discrete data problems in system biology. Method An improved GFA called IGFA was proposed in this paper. Two parts were improved in IGFA. The first one is the rule of random division, which is a reasonable strategy and makes running time shorter. The other one is rotation factor, which can improve the accuracy of IGFA. And to apply IGFA to the hierarchical clustering, the initial part and the movement operator were modified. Results Two kinds of experiments were used to test IGFA. And IGFA was applied to hierarchical clustering. The global minimum experiment was used with IGFA, GFA, GA (genetic algorithm) and SA (simulated annealing). Multi-minima experiment was used with IGFA and GFA. The two experiments results were compared with each other and proved the efficiency of IGFA. IGFA is better than GFA both in accuracy and running time. For the hierarchical clustering, IGFA is used to optimize the smallest distance of genes pairs, and the results were compared with GA and SA, singular-linkage clustering, UPGMA. The efficiency of IGFA is proved. PMID:23173043

Plasma phenomena observed in the MAP/WINE campaign

NASA Technical Reports Server (NTRS)

Friedrich, M.

1989-01-01

The wealth of plasma data gathered in the MAP/WINE campaign allows insight into the generation of electron densities on a large, and the nature of the ions on a small scale. The associated measurements of winds and charged particles help to understand the morphology of the midlatitude ionization which turns out to correlate poorly with geomagnetic activity, but at least slightly with the prevailing winds. A somewhat clearer connection seems to exist between stratospheric warmings and radio wave absorption minima. On the local scale the interpretation of the rocket measurements of positive ions was helped by simultaneous observations of temperatures and atomic oxygen. The relevance of the description winter anomaly for high latitude electron density profiles are examined.

Water-soluble Au13 clusters protected by binary thiolates: Structural accommodation and the use for chemosensing

NASA Astrophysics Data System (ADS)

Ding, Weihua; Huang, Chuanqi; Guan, Lingmei; Liu, Xianhu; Luo, Zhixun; Li, Weixue

2017-05-01

Here we report a successful synthesis of water-soluble 13-atoms gold clusters under the monolayer protection of binary thiolates, glutathione and penicillamine, under a molecular formula of Au13(SG)5(PA)7. This monolayer-protected cluster (MPC) finds decent stability and is demonstrated to possess an icosahedral geometry pertaining to structural accommodation in contrast to a planar bare Au13 of local minima energy. Natural bond orbital (NBO) analysis depicts the interaction patterns between gold and the ligands, enlightening to understand the origin of enhanced stability of the Au13 MPCs. Further, the water-soluble Au13 MPCs are found to be a decent candidate for chemosensing and bioimaging.

Energy landscapes for machine learning

NASA Astrophysics Data System (ADS)

Ballard, Andrew J.; Das, Ritankar; Martiniani, Stefano; Mehta, Dhagash; Sagun, Levent; Stevenson, Jacob D.; Wales, David J.

Machine learning techniques are being increasingly used as flexible non-linear fitting and prediction tools in the physical sciences. Fitting functions that exhibit multiple solutions as local minima can be analysed in terms of the corresponding machine learning landscape. Methods to explore and visualise molecular potential energy landscapes can be applied to these machine learning landscapes to gain new insight into the solution space involved in training and the nature of the corresponding predictions. In particular, we can define quantities analogous to molecular structure, thermodynamics, and kinetics, and relate these emergent properties to the structure of the underlying landscape. This Perspective aims to describe these analogies with examples from recent applications, and suggest avenues for new interdisciplinary research.

Hopf solitons on compact manifolds

NASA Astrophysics Data System (ADS)

Ward, R. S.

2018-02-01

Hopf solitons in the Skyrme-Faddeev system on R3 typically have a complicated structure, in particular when the Hopf number Q is large. By contrast, if we work on a compact 3-manifold M, and the energy functional consists only of the Skyrme term (the strong-coupling limit), then the picture simplifies. There is a topological lower bound E ≥ Q on the energy, and the local minima of E can look simple even for large Q. The aim here is to describe and investigate some of these solutions, when M is S3, T3, or S2 × S1. In addition, we review the more elementary baby-Skyrme system, with M being S2 or T2.

Fast globally optimal segmentation of cells in fluorescence microscopy images.

PubMed

Bergeest, Jan-Philip; Rohr, Karl

2011-01-01

Accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression in high-throughput screening applications. We propose a new approach for segmenting cell nuclei which is based on active contours and convex energy functionals. Compared to previous work, our approach determines the global solution. Thus, the approach does not suffer from local minima and the segmentation result does not depend on the initialization. We also suggest a numeric approach for efficiently computing the solution. The performance of our approach has been evaluated using fluorescence microscopy images of different cell types. We have also performed a quantitative comparison with previous segmentation approaches.

Structures and Binding Energies of the Naphthalene Dimer in Its Ground and Excited States.

PubMed

Dubinets, N O; Safonov, A A; Bagaturyants, A A

2016-05-05

Possible structures of the naphthalene dimer corresponding to local energy minima in the ground and excited (excimer) electronic states are comprehensively investigated using DFT-D and TDDFT-D methods with a special accent on the excimer structures. The corresponding binding and electronic transition energies are calculated, and the nature of the electronic states in different structures is analyzed. Several parallel (stacked) and T-shaped structures were found in both the ground and excited (excimer) states in a rather narrow energy range. The T-shaped structure with the lowest energy in the excited state exhibits a marked charge transfer from the upright molecule to the base one.

Variational formulation and stability analysis of a three dimensional superelastic model for shape memory alloys

NASA Astrophysics Data System (ADS)

Alessi, Roberto; Pham, Kim

2016-02-01

This paper presents a variational framework for the three-dimensional macroscopic modelling of superelastic shape memory alloys in an isothermal setting. Phase transformation is accounted through a unique second order tensorial internal variable, acting as the transformation strain. Postulating the total strain energy density as the sum of a free energy and a dissipated energy, the model depends on two material scalar functions of the norm of the transformation strain and a material scalar constant. Appropriate calibration of these material functions allows to render a wide range of constitutive behaviours including stress-softening and stress-hardening. The quasi-static evolution problem of a domain is formulated in terms of two physical principles based on the total energy of the system: a stability criterion, which selects the local minima of the total energy, and an energy balance condition, which ensures the consistency of the evolution of the total energy with respect to the external loadings. The local phase transformation laws in terms of Kuhn-Tucker relations are deduced from the first-order stability condition and the energy balance condition. The response of the model is illustrated with a numerical traction-torsion test performed on a thin-walled cylinder. Evolutions of homogeneous states are given for proportional and non-proportional loadings. Influence of the stress-hardening/softening properties on the evolution of the transformation domain is emphasized. Finally, in view of an identification process, the issue of stability of homogeneous states in a multi-dimensional setting is answered based on the study of second-order derivative of the total energy. Explicit necessary and sufficient conditions of stability are provided.

Topographic effects on infrasound propagation.

PubMed

McKenna, Mihan H; Gibson, Robert G; Walker, Bob E; McKenna, Jason; Winslow, Nathan W; Kofford, Aaron S

2012-01-01

Infrasound data were collected using portable arrays in a region of variable terrain elevation to quantify the effects of topography on observed signal amplitude and waveform features at distances less than 25 km from partially contained explosive sources during the Frozen Rock Experiment (FRE) in 2006. Observed infrasound signals varied in amplitude and waveform complexity, indicating propagation effects that are due in part to repeated local maxima and minima in the topography on the scale of the dominant wavelengths of the observed data. Numerical simulations using an empirically derived pressure source function combining published FRE accelerometer data and historical data from Project ESSEX, a time-domain parabolic equation model that accounted for local terrain elevation through terrain-masking, and local meteorological atmospheric profiles were able to explain some but not all of the observed signal features. Specifically, the simulations matched the timing of the observed infrasound signals but underestimated the waveform amplitude observed behind terrain features, suggesting complex scattering and absorption of energy associated with variable topography influences infrasonic energy more than previously observed. © 2012 Acoustical Society of America.

Time-marching multi-grid seismic tomography

NASA Astrophysics Data System (ADS)

Tong, P.; Yang, D.; Liu, Q.

2016-12-01

From the classic ray-based traveltime tomography to the state-of-the-art full waveform inversion, because of the nonlinearity of seismic inverse problems, a good starting model is essential for preventing the convergence of the objective function toward local minima. With a focus on building high-accuracy starting models, we propose the so-called time-marching multi-grid seismic tomography method in this study. The new seismic tomography scheme consists of a temporal time-marching approach and a spatial multi-grid strategy. We first divide the recording period of seismic data into a series of time windows. Sequentially, the subsurface properties in each time window are iteratively updated starting from the final model of the previous time window. There are at least two advantages of the time-marching approach: (1) the information included in the seismic data of previous time windows has been explored to build the starting models of later time windows; (2) seismic data of later time windows could provide extra information to refine the subsurface images. Within each time window, we use a multi-grid method to decompose the scale of the inverse problem. Specifically, the unknowns of the inverse problem are sampled on a coarse mesh to capture the macro-scale structure of the subsurface at the beginning. Because of the low dimensionality, it is much easier to reach the global minimum on a coarse mesh. After that, finer meshes are introduced to recover the micro-scale properties. That is to say, the subsurface model is iteratively updated on multi-grid in every time window. We expect that high-accuracy starting models should be generated for the second and later time windows. We will test this time-marching multi-grid method by using our newly developed eikonal-based traveltime tomography software package tomoQuake. Real application results in the 2016 Kumamoto earthquake (Mw 7.0) region in Japan will be demonstrated.

Free energy landscape of a biomolecule in dihedral principal component space: sampling convergence and correspondence between structures and minima.

PubMed

Maisuradze, Gia G; Leitner, David M

2007-05-15

Dihedral principal component analysis (dPCA) has recently been developed and shown to display complex features of the free energy landscape of a biomolecule that may be absent in the free energy landscape plotted in principal component space due to mixing of internal and overall rotational motion that can occur in principal component analysis (PCA) [Mu et al., Proteins: Struct Funct Bioinfo 2005;58:45-52]. Another difficulty in the implementation of PCA is sampling convergence, which we address here for both dPCA and PCA using a tetrapeptide as an example. We find that for both methods the sampling convergence can be reached over a similar time. Minima in the free energy landscape in the space of the two largest dihedral principal components often correspond to unique structures, though we also find some distinct minima to correspond to the same structure. 2007 Wiley-Liss, Inc.

On the origin of a very close similarity between the spectra of the supernova type 1 in NGC 3198 and the absorption of DQ HeR

NASA Technical Reports Server (NTRS)

Mustel, E. R.

1979-01-01

The type 1 supernova discovered late in 1966 in NGC 3198 has broad minima in its spectrum break down into a number of significantly narrower absorption bands. The broad minima of tau, sigma and mu, which usually show no details in the spectra of type supernovas, contain a number of narrow absorption bands. The reality of most of these absorption bands is demonstrated by comparison of recordings of spectra of the supernova presented for two moments in time. These minima (particularly of tau and mu,) are a result of blending of several broad absorption bands. The minimum of tau should be a blend of intensive and very broad Fe absorption lines, in which the lower level is metastable. The wavelengths of these line are: 5169, 5198, 5235, 5276, 5317, 5363A.

Is there a stable B2Π state for the CNO molecule?

NASA Astrophysics Data System (ADS)

Marian, Christel; Hess, Bernd A.; Schöttke, Sigrid; Buenker, Robert J.

1987-07-01

We report MRD-CI calculations on the ground state X2Π and the excited states A2Σ + and B2Π of the CNO molecule in linear geometry. The surfaces for oxygen and carbon extraction are calculated using a limited CI expansion of 47 configuration state functions; in the vicinity of the minima obtained with this procedure large-scale CI calculations are carried out including deter-mination of the spin-orbit splitting of the 2Π states of the minima. We find that the B2Π state will be difficult to detect spectroscopically due to an avoided crossing just at the equilibrium geometry of the ground state at RCN = 2.25 a.u., RNO = 2.30 a.u. Accordingly we find two shallow minima for B2Π at RCN = 2.33 a.u., RNO = 2.91 a.u. and RCN = 2.78 a.u., RNO = 2.28 a.u., respectively.

Torsion-wagging tunneling and vibrational states in hydrazine determined from its ab initio potential energy surface

NASA Astrophysics Data System (ADS)

Łodyga, Wiesław; Makarewicz, Jan

2012-05-01

Geometries, anharmonic vibrations, and torsion-wagging (TW) multiplets of hydrazine and its deuterated species are studied using high-level ab initio methods employing the second-order Møller-Plesset perturbation theory (MP2) as well as the coupled cluster singles and doubles model including connected triple corrections, CCSD(T), in conjunction with extended basis sets containing diffuse and core functions. To describe the splitting patterns caused by tunneling in TW states, the 3D potential energy surface (PES) for the large-amplitude TW modes is constructed. Stationary points in the 3D PES, including equivalent local minima and saddle points are characterized. Using this 3D PES, a flexible Hamiltonian is built numerically and then employed to solve the vibrational problem for TW coupled motion. The calculated ground state rav structure is expected to be more reliable than the experimental one that has been determined using a simplified structural model. The calculated fundamental frequencies allowed resolution of the assignment problems discussed earlier in the literature. The determined energy barriers, including the contributions from the small-amplitude vibrations, to the tunneling of the symmetric and antisymmetric wagging mode of 1997 cm-1 and 3454 cm-1, respectively, are in reasonable agreement with the empirical estimates of 2072 cm-1 and 3312 cm-1, respectively [W. Łodyga et al. J. Mol. Spectrosc. 183, 374 (1997), 10.1006/jmsp.1997.7271]. However, the empirical torsion barrier of 934 cm-1 appears to be overestimated. The ab initio calculations yield two torsion barriers: cis and trans of 744 cm-1 and 2706 cm-1, respectively. The multiplets of the excited torsion states are predicted from the refined 3D PES.

Molecular simulation of surfactant-assisted protein refolding

NASA Astrophysics Data System (ADS)

Lu, Diannan; Liu, Zheng; Liu, Zhixia; Zhang, Minlian; Ouyang, Pingkai

2005-04-01

Protein refolding to its native state in vitro is a challenging problem in biotechnology, i.e., in the biomedical, pharmaceutical, and food industry. Protein aggregation and misfolding usually inhibit the recovery of proteins with their native states. These problems can be partially solved by adding a surfactant into a suitable solution environment. However, the process of this surfactant-assisted protein refolding is not well understood. In this paper, we wish to report on the first-ever simulations of surfactant-assisted protein refolding. For these studies, we defined a simple model for the protein and the surfactant and investigated how a surfactant affected the folding behavior of a two-dimensional lattice protein molecule. The model protein and model surfactant were chosen such that we could capture the important features of the folding process and the interaction between the protein and the surfactant, namely, the hydrophobic interaction. It was shown that, in the absence of surfactants, a protein in an "energy trap" conformation, i.e., a local energy minima, could not fold into the native form, which was characterized by a global energy minimum. The addition of surfactants created folding pathways via the formation of protein-surfactant complexes and thus enabled the conformations that fell into energy trap states to escape from these traps and to form the native proteins. The simulation results also showed that it was necessary to match the hydrophobicity of surfactant to the concentration of denaturant, which was added to control the folding or unfolding of a protein. The surfactants with different hydrophobicity had their own concentration range on assisting protein refolding. All of these simulations agreed well with experimental results reported elsewhere, indicating both the validity of the simulations presented here and the potential application of the simulations for the design of a surfactant on assisting protein refolding.

Computational Study of a Vortex-Ring Pair Interacting with a Constant-Temperature Heated Wall

NASA Astrophysics Data System (ADS)

Jabbar, Hussam; Naguib, Ahmed

2017-11-01

Impinging jets are used widely in industrial and manufacturing processes because of their ability to increase the heat transfer rate from the impingement surface. The vortical structures of these jets have an important influence on the heat transfer; by affecting the thermal boundary layer (TBL) during their interaction with the wall. In order to better understand the physics of this interaction, particularly when pairing of two vortices happens near the wall, a simplified model problem of two isolated vortex rings interacting with a flat wall is investigated computationally using ANSYS FLUENT 17.1. Observations of the vorticity field, the temperature field, the wall shear stress, the TBL and the Nusselt number (Nu) provide insight into the association of local Nu maxima/minima with different flow features. The results provide physical understanding of the flow processes leading to enhancement/deterioration of Nu due to vortex-wall interaction. Additionally, the characteristics of the vortical structures are quantified, and possible correlations between the temporal development of these characteristics and the evolution of the maximum/minimum Nu are investigated. The results are compared to those involving a single vortex ring in order to understand the effect of vortex pairing. This work is supported by NSF Grant Number CBET-1603720. Hussam Jabbar also acknowledges the fellowship support from Higher Committee for Education Development in Iraq (HCED).

Subspace K-means clustering.

PubMed

Timmerman, Marieke E; Ceulemans, Eva; De Roover, Kim; Van Leeuwen, Karla

2013-12-01

To achieve an insightful clustering of multivariate data, we propose subspace K-means. Its central idea is to model the centroids and cluster residuals in reduced spaces, which allows for dealing with a wide range of cluster types and yields rich interpretations of the clusters. We review the existing related clustering methods, including deterministic, stochastic, and unsupervised learning approaches. To evaluate subspace K-means, we performed a comparative simulation study, in which we manipulated the overlap of subspaces, the between-cluster variance, and the error variance. The study shows that the subspace K-means algorithm is sensitive to local minima but that the problem can be reasonably dealt with by using partitions of various cluster procedures as a starting point for the algorithm. Subspace K-means performs very well in recovering the true clustering across all conditions considered and appears to be superior to its competitor methods: K-means, reduced K-means, factorial K-means, mixtures of factor analyzers (MFA), and MCLUST. The best competitor method, MFA, showed a performance similar to that of subspace K-means in easy conditions but deteriorated in more difficult ones. Using data from a study on parental behavior, we show that subspace K-means analysis provides a rich insight into the cluster characteristics, in terms of both the relative positions of the clusters (via the centroids) and the shape of the clusters (via the within-cluster residuals).

Converging free energies of binding in cucurbit[7]uril and octa-acid host-guest systems from SAMPL4 using expanded ensemble simulations

NASA Astrophysics Data System (ADS)

Monroe, Jacob I.; Shirts, Michael R.

2014-04-01

Molecular containers such as cucurbit[7]uril (CB7) and the octa-acid (OA) host are ideal simplified model test systems for optimizing and analyzing methods for computing free energies of binding intended for use with biologically relevant protein-ligand complexes. To this end, we have performed initially blind free energy calculations to determine the free energies of binding for ligands of both the CB7 and OA hosts. A subset of the selected guest molecules were those included in the SAMPL4 prediction challenge. Using expanded ensemble simulations in the dimension of coupling host-guest intermolecular interactions, we are able to show that our estimates in most cases can be demonstrated to fully converge and that the errors in our estimates are due almost entirely to the assigned force field parameters and the choice of environmental conditions used to model experiment. We confirm the convergence through the use of alternative simulation methodologies and thermodynamic pathways, analyzing sampled conformations, and directly observing changes of the free energy with respect to simulation time. Our results demonstrate the benefits of enhanced sampling of multiple local free energy minima made possible by the use of expanded ensemble molecular dynamics and may indicate the presence of significant problems with current transferable force fields for organic molecules when used for calculating binding affinities, especially in non-protein chemistries.

Converging free energies of binding in cucurbit[7]uril and octa-acid host-guest systems from SAMPL4 using expanded ensemble simulations.

PubMed

Monroe, Jacob I; Shirts, Michael R

2014-04-01

Molecular containers such as cucurbit[7]uril (CB7) and the octa-acid (OA) host are ideal simplified model test systems for optimizing and analyzing methods for computing free energies of binding intended for use with biologically relevant protein-ligand complexes. To this end, we have performed initially blind free energy calculations to determine the free energies of binding for ligands of both the CB7 and OA hosts. A subset of the selected guest molecules were those included in the SAMPL4 prediction challenge. Using expanded ensemble simulations in the dimension of coupling host-guest intermolecular interactions, we are able to show that our estimates in most cases can be demonstrated to fully converge and that the errors in our estimates are due almost entirely to the assigned force field parameters and the choice of environmental conditions used to model experiment. We confirm the convergence through the use of alternative simulation methodologies and thermodynamic pathways, analyzing sampled conformations, and directly observing changes of the free energy with respect to simulation time. Our results demonstrate the benefits of enhanced sampling of multiple local free energy minima made possible by the use of expanded ensemble molecular dynamics and may indicate the presence of significant problems with current transferable force fields for organic molecules when used for calculating binding affinities, especially in non-protein chemistries.

Structures and electron affinities of the di-arsenic fluorides As2Fn/As2Fn- (n=1-8).

PubMed

Kasalová, Veronika; Schaefer, Henry F

2005-04-15

Developments in the preparation of new materials for microelectronics are focusing new attention on molecular systems incorporating several arsenic atoms. A systematic investigation of the As2Fn/As2Fn- systems was carried out using Density Functional Theory methods and a DZP++ quality basis set. Global and low-lying local geometric minima and relative energies are discussed and compared. The three types of neutral-anion separations reported in this work are: the adiabatic electron affinity (EAad), the vertical electron affinity (EAvert), and the vertical detachment energy (VDE). Harmonic vibrational frequencies pertaining to the global minimum for each compound are reported. From the first four studied species (As2Fn, n=1-4), all neutral molecules and their anions are shown to be stable with respect to As-As bond breaking. The neutral As2F molecule and its anion are predicted to have Cs symmetry. We find the trans F-As-As-F isomer of C2h symmetry and a pyramidalized vinylidene-like As-As-F2- isomer of Cs symmetry to be the global minima for the As2F2 and As2F2- species, respectively. The lowest lying minima of As2F3 and As2F3- are vinyl radical-like structures F-As-As-F2 of Cs symmetry. The neutral As2F4 global minimum is a trans-bent (like Si2H4) F2-As-As-F2 isomer of C2 symmetry, while its anion is predicted to have an unusual fluorine-bridged (C(1)) structure. The global minima of the neutral As2Fn species, n=5-8, are weakly bound complexes, held together by dipole-dipole interactions. All such structures have the AsFm-AsFn form, where (m,n) is (2,3) for As2F5, (3,3) for As2F6, (4,3) for As2F7), and (5,3) for As2F8. For As2F8 the beautiful pentavalent F4As-AsF4 structure (analogous to the stable AsF5 molecule) lies about 30 kcal/mol above the AsF3 . . . AsF5 complex. The stability of AsF(5) depends crucially on the strong As-F bonds, and replacing one of these with an As-As bond (in F4As-AsF4) has a very negative impact on the molecule's stability. The anions As2Fn-, n=5-8, are shown to be stable with respect to the As-As bond breaking, and we predict that all of them have fluorine-bridged or fluorine-linked structures. The zero-point vibrational energy corrected adiabatic electron affinities are predicted to be 2.28 eV (As2F), 1.95 eV (As2F2), 2.39 eV (As2F3), 1.71 eV (As2F4), 2.72 eV (As2F5), 1.79 eV (As2F6), 5.26 eV (As2F7), and 3.40 eV (As2F8) from the BHLYP method. Vertical detachment energies are rather large, especially for species with fluorine-bridged global minima, having values up to 6.45 eV (As2F7, BHLYP).

Conjugate gradient determination of optimal plane changes for a class of three-impulse transfers between noncoplanar circular orbits

NASA Technical Reports Server (NTRS)

Burrows, R. R.

1972-01-01

A particular type of three-impulse transfer between two circular orbits is analyzed. The possibility of three plane changes is recognized, and the problem is to optimally distribute these plane changes to minimize the sum of the individual impulses. Numerical difficulties and their solution are discussed. Numerical results obtained from a conjugate gradient technique are presented for both the case where the individual plane changes are unconstrained and for the case where they are constrained. Possibly not unexpectedly, multiple minima are found. The techniques presented could be extended to the finite burn case, but primarily the contents are addressed to preliminary mission design and vehicle sizing.

Radar signal categorization using a neural network

NASA Technical Reports Server (NTRS)

Anderson, James A.; Gately, Michael T.; Penz, P. Andrew; Collins, Dean R.

1991-01-01

Neural networks were used to analyze a complex simulated radar environment which contains noisy radar pulses generated by many different emitters. The neural network used is an energy minimizing network (the BSB model) which forms energy minima - attractors in the network dynamical system - based on learned input data. The system first determines how many emitters are present (the deinterleaving problem). Pulses from individual simulated emitters give rise to separate stable attractors in the network. Once individual emitters are characterized, it is possible to make tentative identifications of them based on their observed parameters. As a test of this idea, a neural network was used to form a small data base that potentially could make emitter identifications.

Galactic Cosmic-ray Transport in the Global Heliosphere: A Four-Dimensional Stochastic Model

NASA Astrophysics Data System (ADS)

Florinski, V.

2009-04-01

We study galactic cosmic-ray transport in the outer heliosphere and heliosheath using a newly developed transport model based on stochastic integration of the phase-space trajectories of Parker's equation. The model employs backward integration of the diffusion-convection transport equation using Ito calculus and is four-dimensional in space+momentum. We apply the model to the problem of galactic proton transport in the heliosphere during a negative solar minimum. Model results are compared with the Voyager measurements of galactic proton radial gradients and spectra in the heliosheath. We show that the heliosheath is not as efficient in diverting cosmic rays during solar minima as predicted by earlier two-dimensional models.

Two-Color V and R CCD Photometry of the SW Sex-Type Eclipsing Cataclysmic Variable V1315 Aql

NASA Astrophysics Data System (ADS)

Andronov, I. L.; Baklanov, A. V.; Burwitz, V.

2005-08-01

The V-R color index shows a complicated behaviour during the eclipse, being largest at the brightness minimum, but showing asymmetric minima at phases -0.07 and +0.13. The hump at the light curve occurs after the eclipse, contrary to systems with the "hot spot". The phases of minima in V and R are 0.0092(17) and 0.0062(17), respectively, for the mean date JD=2453202.

The complex lightcurve of 1992 NA

NASA Technical Reports Server (NTRS)

Wisniewski, Wieslaw Z.; Harris, A. W.

1994-01-01

Amor asteroid 1992 NA was monitored during three nights at a large phase angle of -65 deg. The lightcurves obtained did not reveal a repeatable curve with two maxima and two minima. However, some features suggested a periodicity with three maxima and three minima. A satisfactory composite lightcurve of this form was obtained by means of an 'eyeball' fit and by Fourier analysis. Individual and composite lightcurves are presented. The observed colors are consistent with the C class.

Optical Model and Cross Section Uncertainties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Herman,M.W.; Pigni, M.T.; Dietrich, F.S.

2009-10-05

Distinct minima and maxima in the neutron total cross section uncertainties were observed in model calculations using spherical optical potential. We found this oscillating structure to be a general feature of quantum mechanical wave scattering. Specifically, we analyzed neutron interaction with 56Fe from 1 keV up to 65 MeV, and investigated physical origin of the minima.We discuss their potential importance for practical applications as well as the implications for the uncertainties in total and absorption cross sections.

Wave function delocalization and large-amplitude vibrations of helium on corrugated aromatic microsurfaces: tetracene.He and pentacene.He van der Waals complexes.

PubMed

Xu, Minzhong; Bacić, Zlatko

2007-08-09

We report accurate quantum three-dimensional calculations of highly excited intermolecular vibrational states of the van der Waals (vdW) complexes tetracene.He and pentacene.He in the S1 excited electronic state. The aromatic molecules were taken to be rigid and the intermolecular potential energy surfaces (IPESs) were modeled as a sum of atom-atom Lennard-Jones pair potentials. The IPESs are corrugated in the direction of the long (x) axis of the aromatic molecules, due to the presence of the symmetrically equivalent global double minimum for tetracene.He, and a triple minimum (central global minimum and two equivalent local minima) for pentacene.He, on each side of the aromatic plane. Both IPESs have two additional minor equivalent local minima further away from the center of the molecule. The vdW vibrational states analyzed in this work cover about 80% of the well depths of the IPESs. The mode coupling is generally weak for those states whose out-of-plane (z) mode is unexcited. However, the z-mode fundamental is strongly coupled to the short-axis (y) in-plane mode, so that the pure z-mode excitation could not be identified. The He atom exhibits large in-plane spatial delocalizaton already in the ground vdW vibrational state, which increases rapidly upon the excitation of the in-plane x and y modes, with little hindrance by the corrugation of the aromatic microsurfaces. For the vdW vibrational energies considered, the He atom spatial delocalization reaches Deltax and Deltay values of approximately 5 and 4 A, respectively, and is limited only by the finite size of the aromatic substrates. Side-crossing delocalization of the wave functions on both sides of the molecular plane is found at excitation energies >30 cm(-1), giving rise to the energy splittings of the pairs of states symmetric/antisymmetric with respect to the aromatic plane; the splittings show strong vdW vibrational mode specificity.

Application of time series analysis on molecular dynamics simulations of proteins: a study of different conformational spaces by principal component analysis.

PubMed

Alakent, Burak; Doruker, Pemra; Camurdan, Mehmet C

2004-09-08

Time series analysis is applied on the collective coordinates obtained from principal component analysis of independent molecular dynamics simulations of alpha-amylase inhibitor tendamistat and immunity protein of colicin E7 based on the Calpha coordinates history. Even though the principal component directions obtained for each run are considerably different, the dynamics information obtained from these runs are surprisingly similar in terms of time series models and parameters. There are two main differences in the dynamics of the two proteins: the higher density of low frequencies and the larger step sizes for the interminima motions of colicin E7 than those of alpha-amylase inhibitor, which may be attributed to the higher number of residues of colicin E7 and/or the structural differences of the two proteins. The cumulative density function of the low frequencies in each run conforms to the expectations from the normal mode analysis. When different runs of alpha-amylase inhibitor are projected on the same set of eigenvectors, it is found that principal components obtained from a certain conformational region of a protein has a moderate explanation power in other conformational regions and the local minima are similar to a certain extent, while the height of the energy barriers in between the minima significantly change. As a final remark, time series analysis tools are further exploited in this study with the motive of explaining the equilibrium fluctuations of proteins. Copyright 2004 American Institute of Physics

Application of time series analysis on molecular dynamics simulations of proteins: A study of different conformational spaces by principal component analysis

NASA Astrophysics Data System (ADS)

Alakent, Burak; Doruker, Pemra; Camurdan, Mehmet C.

2004-09-01

Time series analysis is applied on the collective coordinates obtained from principal component analysis of independent molecular dynamics simulations of α-amylase inhibitor tendamistat and immunity protein of colicin E7 based on the Cα coordinates history. Even though the principal component directions obtained for each run are considerably different, the dynamics information obtained from these runs are surprisingly similar in terms of time series models and parameters. There are two main differences in the dynamics of the two proteins: the higher density of low frequencies and the larger step sizes for the interminima motions of colicin E7 than those of α-amylase inhibitor, which may be attributed to the higher number of residues of colicin E7 and/or the structural differences of the two proteins. The cumulative density function of the low frequencies in each run conforms to the expectations from the normal mode analysis. When different runs of α-amylase inhibitor are projected on the same set of eigenvectors, it is found that principal components obtained from a certain conformational region of a protein has a moderate explanation power in other conformational regions and the local minima are similar to a certain extent, while the height of the energy barriers in between the minima significantly change. As a final remark, time series analysis tools are further exploited in this study with the motive of explaining the equilibrium fluctuations of proteins.

Noise in Graphene Superlattices Grown on Hexagonal Boron Nitride.

PubMed

Li, Xuefei; Lu, Xiaobo; Li, Tiaoyang; Yang, Wei; Fang, Jianming; Zhang, Guangyu; Wu, Yanqing

2015-11-24

Existing in almost all electronic systems, the current noise spectral density, originated from the fluctuation of current, is by nature far more sensitive than the mean value of current, the most common characteristic parameter in electronic devices. Existing models on its origin of either carrier number or mobility are adopted in practically all electronic devices. For the past few decades, there has been no experimental evidence for direct association between 1/f noise and any other kinetic phenomena in solid state devices. Here, in the study of a van der Waals heterostructure of graphene on hexagonal BN superlattice, satellite Dirac points have been characterized through 1/f noise spectral density with pronounced local minima and asymmetric magnitude associated with its unique energy dispersion spectrum, which can only be revealed by scanning tunneling microscopy and low temperature magneto-transport measurement. More importantly, these features even emerge in the noise spectra of devices showing no minima in electric current, and are robust at all temperatures down to 4.3 K. In addition, graphene on h-BN exhibits a record low noise level of 1.6 × 10(-9) μm(2) Hz(-1) at 10 Hz, more than 1 order of magnitude lower than previous results for graphene on SiO2. Such an epitaxial van der Waals material system not only enables an unprecedented characterization of fundamentals in solids by 1/f noise, but its superior interface also provides a key and feasible solution for further improvement of the noise level for graphene devices.

Investigations of the Rg-BrCl (Rg = He, Ne, Ar, Kr, Xe) binary van der Waals complexes: ab initio intermolecular potential energy surfaces, vibrational states and predicted pure rotational transition frequencies

NASA Astrophysics Data System (ADS)

Li, Song; Zheng, Rui; Chen, Shan-Jun; Chen, Yan; Chen, Peng

2017-03-01

The intermolecular potential energy surfaces (PESs) of the ground electronic state for the Rg-BrCl (Rg = He, Ne, Ar, Kr, Xe) van der Waals complexes have been constructed by using the coupled-cluster method in combination with the augmented quadruple-zeta correlation-consistent basis sets supplemented with an additional set of bond functions. The features of the anisotropic PESs for these complexes are remarkably similar, which are characterized by three minima and two saddle points between them. The global minimum corresponds to a collinear Rg-Br-Cl configuration. Two local minima, correlate with an anti-linear Rg-Cl-Br geometry and a nearly T-shaped structure, can also be located on each PES. The quantum bound state calculations enable us to investigate intermolecular vibrational states and rotational energy levels of the complexes. The transition frequencies are predicted and are fitted to obtain their corresponding spectroscopic constants. In general, the periodic trends are observed for this complex family. Comparisons with available experimental data for the collinear isomer of Ar-BrCl demonstrate reliability of our theoretical predictions, and our results for the other two isomers of Ar-BrCl as well as for other members of the complex family are also anticipated to be trustable. Except for the collinear isomer of Ar-BrCl, the data presented in this paper would be beneficial to improve our knowledge for these experimentally unknown species.

Chemical dynamics between wells across a time-dependent barrier: Self-similarity in the Lagrangian descriptor and reactive basins.

PubMed

Junginger, Andrej; Duvenbeck, Lennart; Feldmaier, Matthias; Main, Jörg; Wunner, Günter; Hernandez, Rigoberto

2017-08-14

In chemical or physical reaction dynamics, it is essential to distinguish precisely between reactants and products for all times. This task is especially demanding in time-dependent or driven systems because therein the dividing surface (DS) between these states often exhibits a nontrivial time-dependence. The so-called transition state (TS) trajectory has been seen to define a DS which is free of recrossings in a large number of one-dimensional reactions across time-dependent barriers and thus, allows one to determine exact reaction rates. A fundamental challenge to applying this method is the construction of the TS trajectory itself. The minimization of Lagrangian descriptors (LDs) provides a general and powerful scheme to obtain that trajectory even when perturbation theory fails. Both approaches encounter possible breakdowns when the overall potential is bounded, admitting the possibility of returns to the barrier long after the trajectories have reached the product or reactant wells. Such global dynamics cannot be captured by perturbation theory. Meanwhile, in the LD-DS approach, it leads to the emergence of additional local minima which make it difficult to extract the optimal branch associated with the desired TS trajectory. In this work, we illustrate this behavior for a time-dependent double-well potential revealing a self-similar structure of the LD, and we demonstrate how the reflections and side-minima can be addressed by an appropriate modification of the LD associated with the direct rate across the barrier.

Ordovician sponges from west-central and east-central Alaska and western Yukon Territory, Canada

USGS Publications Warehouse

Rigby, J.K.; Blodgett, R.B.; Britt, B.B.

2008-01-01

Moderate collections of fossil sponges have been recovered over a several-year period from a few scattered localities in west-central and east-central Alaska, and from westernmost Yukon Territory of Canada. Two fragments of the demosponge agelasiid cliefdenellid, Cliefdenella alaskaensis Stock, 1981, and mostly small unidentifiable additional fragments were recovered from a limestone debris flow bed in the White Mountain area, McGrath A-4 Quadrangle in west-central Alaska. Fragments of the agelasiid actinomorph girtyocoeliids Girtyocoeliana epiporata (Rigby & Potter, 1986) and Girtyocoelia minima n. sp., plus a specimen of the vaceletid colospongiid Corymbospongia amplia Rigby, Karl, Blodgett & Baichtal, 2005, were collected from probable Ashgillian age beds in the Livengood B-5 Quadrangle in east-central Alaska. A more extensive suite of corymbospongiids, including Corymbospongia betella Rigby, Potter & Blodgett, 1988, C. mica Rigby & Potter, 1986, and C.(?) perforata Rigby & Potter, 1986, along with the vaceletiid colospongiids Pseudo-imperatoria minima? (Rigby & Potter, 1986), and Pseudoimperatoria media (Rigby & Potter, 1986), and with the heteractinid Nucha naucum? Pickett & Jell, 1983, were recovered from uppermost part of the Jones Ridge Limestone (Ashgillian), on the south flank of Jones Ridge, in the Sheep Mountain Quadrangle, in westernmost Yukon Territory, Canada. The fossil sponges from the McGrath A-4 and Livengood B-5 quadrangles were recovered from attached Siberian terranes, and those from the Sheep Mountain Quadrangle were recovered from an allochthonous Laurentian terrane in the Yukon Territory.

New Light-Time Curve of Eclipsing Binary AM Leo

NASA Astrophysics Data System (ADS)

Gorda, S. Yu.; Matveeva, E. A.

2017-12-01

We present 72 photoelectric and CCD times of minima of eclipsing binary AM Leo obtained mainly during at Kourovka Astronomical Observatory of the Ural Federal University in Russia. We obtained new values of period of 50.5 years and eccentricity of 0.28 of the orbit of the eclipsing pair around the mass center of the system AM Leo with the third body. These results have been received taking into account the times of minima taken from literature and obtained from to .

Method and apparatus for thickness measurement using microwaves

DOEpatents

Woskov, Paul [Bedford, MA; Lamar, David A [West Richland, WA

2001-01-01

The method for measuring the thickness of a material which transmits a detectable amount of microwave radiation includes irradiating the material with coherent microwave radiation tuned over a frequency range. Reflected microwave radiation is detected, the reflected radiation having maxima and minima over the frequency range as a result of coherent interference of microwaves reflected from reflecting surfaces of the material. The thickness of the material is determined from the period of the maxima and minima along with knowledge of the index of refraction of the material.

Oxygen-induced recombination centers in as-grown Czochralski silicon crystals

NASA Technical Reports Server (NTRS)

Nauka, K.; Gatos, H. C.; Lagowski, J.

1983-01-01

Simultaneous quantitative microprofiles of the interstitial oxygen concentration and of the excess carrier lifetime are obtained in Czochralski-grown Si crystals employing double laser absorption scanning. It is found that oxygen concentration maxima and minima along the crystal growth direction coincide with lifetime minima and maxima, respectively. Another finding is that the magnitude of oxygen-induced lifetime changes increases dramatically in going from the center to the periphery of the crystal. The findings discussed imply that 'as-grown' oxygen precipitates figure in lifetime-limiting processes.

Hybrid insolation forcing of Pliocene monsoon dynamics in West Africa

NASA Astrophysics Data System (ADS)

Kuechler, Rony R.; Dupont, Lydie M.; Schefuß, Enno

2018-01-01

The Pliocene is regarded as a potential analogue for future climate with conditions generally warmer-than-today and higher-than-preindustrial atmospheric CO2 levels. Here we present the first orbitally resolved records of continental hydrology and vegetation changes from West Africa for two Pliocene time intervals (5.0-4.6 Ma, 3.6-3.0 Ma), which we compare with records from the last glacial cycle (Kuechler et al., 2013). Our results indicate that changes in local insolation alone are insufficient to explain the full degree of hydrologic variations. Generally two modes of interacting insolation forcings are observed: during eccentricity maxima, when precession was strong, the West African monsoon was driven by summer insolation; during eccentricity minima, when precession-driven variations in local insolation were minimal, obliquity-driven changes in the summer latitudinal insolation gradient became dominant. This hybrid monsoonal forcing concept explains orbitally controlled tropical climate changes, incorporating the forcing mechanism of latitudinal gradients for the Pliocene, which probably increased in importance during subsequent Northern Hemisphere glaciations.

Multivariate Copula Analysis Toolbox (MvCAT): Describing dependence and underlying uncertainty using a Bayesian framework

NASA Astrophysics Data System (ADS)

Sadegh, Mojtaba; Ragno, Elisa; AghaKouchak, Amir

2017-06-01

We present a newly developed Multivariate Copula Analysis Toolbox (MvCAT) which includes a wide range of copula families with different levels of complexity. MvCAT employs a Bayesian framework with a residual-based Gaussian likelihood function for inferring copula parameters and estimating the underlying uncertainties. The contribution of this paper is threefold: (a) providing a Bayesian framework to approximate the predictive uncertainties of fitted copulas, (b) introducing a hybrid-evolution Markov Chain Monte Carlo (MCMC) approach designed for numerical estimation of the posterior distribution of copula parameters, and (c) enabling the community to explore a wide range of copulas and evaluate them relative to the fitting uncertainties. We show that the commonly used local optimization methods for copula parameter estimation often get trapped in local minima. The proposed method, however, addresses this limitation and improves describing the dependence structure. MvCAT also enables evaluation of uncertainties relative to the length of record, which is fundamental to a wide range of applications such as multivariate frequency analysis.

Generation and detection of pure valley current by electrically induced Berry curvature in bilayer graphene

NASA Astrophysics Data System (ADS)

Shimazaki, Y.; Yamamoto, M.; Borzenets, I. V.; Watanabe, K.; Taniguchi, T.; Tarucha, S.

2015-12-01

The field of `Valleytronics’ has recently been attracting growing interest as a promising concept for the next generation electronics, because non-dissipative pure valley currents with no accompanying net charge flow can be manipulated for computational use, akin to pure spin currents. Valley is a quantum number defined in an electronic system whose energy bands contain energetically degenerate but non-equivalent local minima (conduction band) or maxima (valence band) due to a certain crystal structure. Specifically, spatial inversion symmetry broken two-dimensional honeycomb lattice systems exhibiting Berry curvature is a subset of possible systems that enable optical, magnetic and electrical control of the valley degree of freedom. Here we use dual-gated bilayer graphene to electrically induce and control broken inversion symmetry (or Berry curvature) as well as the carrier density for generating and detecting the pure valley current. In the insulating regime, at zero-magnetic field, we observe a large nonlocal resistance that scales cubically with the local resistivity, which is evidence of pure valley current.

Using Minimum-Surface Bodies for Iteration Space Partitioning

NASA Technical Reports Server (NTRS)

Frumlin, Michael; VanderWijngaart, Rob F.; Biegel, Bryan (Technical Monitor)

2001-01-01

A number of known techniques for improving cache performance in scientific computations involve the reordering of the iteration space. Some of these reorderings can be considered as coverings of the iteration space with the sets having good surface-to-volume ratio. Use of such sets reduces the number of cache misses in computations of local operators having the iteration space as a domain. We study coverings of iteration spaces represented by structured and unstructured grids. For structured grids we introduce a covering based on successive minima tiles of the interference lattice of the grid. We show that the covering has good surface-to-volume ratio and present a computer experiment showing actual reduction of the cache misses achieved by using these tiles. For unstructured grids no cache efficient covering can be guaranteed. We present a triangulation of a 3-dimensional cube such that any local operator on the corresponding grid has significantly larger number of cache misses than a similar operator on a structured grid.

Energy barriers, entropy barriers, and non-Arrhenius behavior in a minimal glassy model.

PubMed

Du, Xin; Weeks, Eric R

2016-06-01

We study glassy dynamics using a simulation of three soft Brownian particles confined to a two-dimensional circular region. If the circular region is large, the disks freely rearrange, but rearrangements are rarer for smaller system sizes. We directly measure a one-dimensional free-energy landscape characterizing the dynamics. This landscape has two local minima corresponding to the two distinct disk configurations, separated by a free-energy barrier that governs the rearrangement rate. We study several different interaction potentials and demonstrate that the free-energy barrier is composed of a potential-energy barrier and an entropic barrier. The heights of both of these barriers depend on temperature and system size, demonstrating how non-Arrhenius behavior can arise close to the glass transition.

2 D-Conductivity of thin Pd films condensed at low temperatures

NASA Astrophysics Data System (ADS)

Dumpich, G.; Kristen, H.; Wassermann, E. F.

1983-09-01

Resistance measurements have been made on quenched condensed Pd films with thicknesses between 25 Å and 350Å. The films are prepared under different evaporation conditions by varying the system pressure between 10-8 and 10-5 mbar. Resistance minima with a logarithmic increase of the sheet resistance are observed for thick films ( d<350Å) condensed under intentionally “bad” (10-5 mbar) vacuum conditions, as well as for thin films ( d<50Å) condensed at pressures around 10-8 mbar. Structure investigations show that the thick films are granular. For these films the relation of granularity to 2 D localization is discussed. The thin films are continuous and the logarithmic resistance increase is in agreement with predictions of 2 D-theories.

Memory effects in soap film arrangements

NASA Astrophysics Data System (ADS)

Vandewalle, Nicolas; Dorbolo, Stephane; Lumay, Geoffroy; Schockmel, Julien; Noirhomme, Martial

2012-02-01

We report experiments on soap film configurations in a triangular prism for which the shape factor can be changed continuously. Two stable configurations can be observed for a range of the shape factor h. A hysteretic behaviour is found, due to the occurence of another local minima in the free energy. Experiments demonstrate that soap films can be trapped in a particular configuration being different from a global surface minimization. This metastability can be evidenced from a geometrical model based on idealized structures. Depending on the configuration, providing clues on the structural relaxations taking place into 3D foams, such as T1 rearrangements. The composition of the liquid is also investigated leading to dynamical picture of the transition. (Phys. Rev. E 83, 021403 (2011))

Density variations of plastic carriers in metallic glasses during aging

NASA Astrophysics Data System (ADS)

Fan, Yue; Iwashita, Takuya; Egami, Takeshi

Thermally induced deformation in metallic glasses was investigated by sampling the potential energy landscape (PEL) and probing the changes in the atomic properties (e.g. energy, displacement, stress). We demonstrate that there exists a universal plastic carrier in amorphous materials, which corresponds to the hopping between local minima on PEL. However very interestingly, the density of plastic carrier is largely affected by the aging history of the glasses. The higher fictive temperature (i . e . fast cooling rate), the larger density of plastic carrier is contained in the system. In particular, we observe a scaling of ρ~exp(- α/Tfic) , which is consistent with the prediction of shear transformation zone theory. The work is supported by U.S. Department of Energy.

Learning-based controller for biotechnology processing, and method of using

DOEpatents

Johnson, John A.; Stoner, Daphne L.; Larsen, Eric D.; Miller, Karen S.; Tolle, Charles R.

2004-09-14

The present invention relates to process control where some of the controllable parameters are difficult or impossible to characterize. The present invention relates to process control in biotechnology of such systems, but not limited to. Additionally, the present invention relates to process control in biotechnology minerals processing. In the inventive method, an application of the present invention manipulates a minerals bioprocess to find local exterma (maxima or minima) for selected output variables/process goals by using a learning-based controller for bioprocess oxidation of minerals during hydrometallurgical processing. The learning-based controller operates with or without human supervision and works to find processor optima without previously defined optima due to the non-characterized nature of the process being manipulated.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Li; Fuhrer, Tobias; Schaefer, Bastian

Measuring similarities/dissimilarities between atomic structures is important for the exploration of potential energy landscapes. However, the cell vectors together with the coordinates of the atoms, which are generally used to describe periodic systems, are quantities not directly suitable as fingerprints to distinguish structures. Based on a characterization of the local environment of all atoms in a cell, we introduce crystal fingerprints that can be calculated easily and define configurational distances between crystalline structures that satisfy the mathematical properties of a metric. This distance between two configurations is a measure of their similarity/dissimilarity and it allows in particular to distinguish structures.more » The new method can be a useful tool within various energy landscape exploration schemes, such as minima hopping, random search, swarm intelligence algorithms, and high-throughput screenings.« less

Implications of Extended Solar Minima

NASA Technical Reports Server (NTRS)

Adams, Mitzi L.; Davis, J. M.

2009-01-01

Since the discovery of periodicity in the solar cycle, the historical record of sunspot number has been carefully examined, attempting to make predictions about the next cycle. Much emphasis has been on predicting the maximum amplitude and length of the next cycle. Because current space-based and suborbital instruments are designed to study active phenomena, there is considerable interest in estimating the length and depth of the current minimum. We have developed criteria for the definition of a minimum and applied it to the historical sunspot record starting in 1749. In doing so, we find that 1) the current minimum is not yet unusually long and 2) there is no obvious way of predicting when, using our definition, the current minimum may end. However, by grouping the data into 22- year cycles there is an interesting pattern of extended minima that recurs every fourth or fifth 22-year cycle. A preliminary comparison of this pattern with other records, suggests the possibility of a correlation between extended minima and lower levels of solar irradiance.

Ultrasound-Assisted Extraction, Antioxidant and Anticancer Activities of the Polysaccharides from Rhynchosia minima Root.

PubMed

Jia, Xuejing; Zhang, Chao; Hu, Jie; He, Muxue; Bao, Jiaolin; Wang, Kai; Li, Peng; Chen, Meiwan; Wan, Jianbo; Su, Huanxing; Zhang, Qingwen; He, Chengwei

2015-11-23

Box-Behnken design (BBD), one of the most common response surface methodology (RSM) methods, was used to optimize the experimental conditions for ultrasound-assisted extraction of polysaccharides from Rhynchosia minima root (PRM). The antioxidant abilities and anticancer activity of purified polysaccharide fractions were also measured. The results showed that optimal extraction parameters were as follows: ultrasound exposure time, 21 min; ratio of water to material, 46 mL/g; ultrasound extraction temperature, 63 °C. Under these conditions, the maximum yield of PRM was 16.95%±0.07%. Furthermore, the main monosaccharides of purified fractions were Ara and Gal. PRM3 and PRM5 exhibited remarkable DPPH radical scavenging activities and reducing power in vitro. PRM3 showed strong inhibitory activities on the growth of MCF-7 cells in vitro. The above results indicate that polysaccharides from R. minima root have the potential to be developed as natural antioxidants and anticancer ingredients for the food and pharmaceutical industries.

OBSERVATIONS AND MODELING OF NORTH-SOUTH ASYMMETRIES USING A FLUX TRANSPORT DYNAMO

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shetye, Juie; Tripathi, Durgesh; Dikpati, Mausumi

2015-02-01

The peculiar behavior of solar cycle 23 and its prolonged minima has been one of the most studied problems over the past few years. In the present paper, we study the asymmetries in active region magnetic flux in the northern and southern hemispheres during the complete solar cycle 23 and the rising phase of solar cycle 24. During the declining phase of solar cycle 23, we find that the magnetic flux in the southern hemisphere is about 10 times stronger than that in the northern hemisphere; however, during the rising phase of cycle 24, this trend is reversed. The magnetic fluxmore » becomes about a factor of four stronger in the northern hemisphere than in the southern hemisphere. Additionally, we find that there was a significant delay (about five months) in change of the polarity in the southern hemisphere in comparison with the northern hemisphere. These results provide us with hints of how the toroidal fluxes have contributed to the solar dynamo during the prolonged minima in solar cycle 23 and in the rising phase of solar cycle 24. Using a solar flux-transport dynamo model, we demonstrate that persistently stronger sunspot cycles in one hemisphere could be caused by the effect of greater inflows into active region belts in that hemisphere. Observations indicate that greater inflows are associated with stronger activity. Some other change or difference in meridional circulation between hemispheres could cause the weaker hemisphere to become the stronger one.« less

Magnetic to magnetic and kinetic to magnetic energy transfers at the top of the Earth's core

NASA Astrophysics Data System (ADS)

Huguet, Ludovic; Amit, Hagay; Alboussière, Thierry

2016-11-01

We develop the theory for the magnetic to magnetic and kinetic to magnetic energy transfer between different spherical harmonic degrees due to the interaction of fluid flow and radial magnetic field at the top of the Earth's core. We show that non-zero secular variation of the total magnetic energy could be significant and may provide evidence for the existence of stretching secular variation, which suggests the existence of radial motions at the top of the Earth's core-whole core convection or MAC waves. However, the uncertainties of the small scales of the geomagnetic field prevent a definite conclusion. Combining core field and flow models we calculate the detailed magnetic to magnetic and kinetic to magnetic energy transfer matrices. The magnetic to magnetic energy transfer shows a complex behaviour with local and non-local transfers. The spectra of magnetic to magnetic energy transfers show clear maxima and minima, suggesting an energy cascade. The kinetic to magnetic energy transfers, which are much weaker due to the weak poloidal flow, are either local or non-local between degree one and higher degrees. The patterns observed in the matrices resemble energy transfer patterns that are typically found in 3-D MHD numerical simulations.

Determination of hyporheic travel time distributions and other parameters from concurrent conservative and reactive tracer tests by local-in-global optimization

NASA Astrophysics Data System (ADS)

Knapp, Julia L. A.; Cirpka, Olaf A.

2017-06-01

The complexity of hyporheic flow paths requires reach-scale models of solute transport in streams that are flexible in their representation of the hyporheic passage. We use a model that couples advective-dispersive in-stream transport to hyporheic exchange with a shape-free distribution of hyporheic travel times. The model also accounts for two-site sorption and transformation of reactive solutes. The coefficients of the model are determined by fitting concurrent stream-tracer tests of conservative (fluorescein) and reactive (resazurin/resorufin) compounds. The flexibility of the shape-free models give rise to multiple local minima of the objective function in parameter estimation, thus requiring global-search algorithms, which is hindered by the large number of parameter values to be estimated. We present a local-in-global optimization approach, in which we use a Markov-Chain Monte Carlo method as global-search method to estimate a set of in-stream and hyporheic parameters. Nested therein, we infer the shape-free distribution of hyporheic travel times by a local Gauss-Newton method. The overall approach is independent of the initial guess and provides the joint posterior distribution of all parameters. We apply the described local-in-global optimization method to recorded tracer breakthrough curves of three consecutive stream sections, and infer section-wise hydraulic parameter distributions to analyze how hyporheic exchange processes differ between the stream sections.

Numerical analysis of spectral properties of coupled oscillator Schroedinger operators. I - Single and double well anharmonic oscillators

NASA Technical Reports Server (NTRS)

Isaacson, D.; Isaacson, E. L.; Paes-Leme, P. J.; Marchesin, D.

1981-01-01

Several methods for computing many eigenvalues and eigenfunctions of a single anharmonic oscillator Schroedinger operator whose potential may have one or two minima are described. One of the methods requires the solution of an ill-conditioned generalized eigenvalue problem. This method has the virtue of using a bounded amount of work to achieve a given accuracy in both the single and double well regions. Rigorous bounds are given, and it is proved that the approximations converge faster than any inverse power of the size of the matrices needed to compute them. The results of computations for the g:phi(4):1 theory are presented. These results indicate that the methods actually converge exponentially fast.

Testing the statistical compatibility of independent data sets

NASA Astrophysics Data System (ADS)

Maltoni, M.; Schwetz, T.

2003-08-01

We discuss a goodness-of-fit method which tests the compatibility between statistically independent data sets. The method gives sensible results even in cases where the χ2 minima of the individual data sets are very low or when several parameters are fitted to a large number of data points. In particular, it avoids the problem that a possible disagreement between data sets becomes diluted by data points which are insensitive to the crucial parameters. A formal derivation of the probability distribution function for the proposed test statistics is given, based on standard theorems of statistics. The application of the method is illustrated on data from neutrino oscillation experiments, and its complementarity to the standard goodness-of-fit is discussed.

Transformation of general binary MRF minimization to the first-order case.

PubMed

Ishikawa, Hiroshi

2011-06-01

We introduce a transformation of general higher-order Markov random field with binary labels into a first-order one that has the same minima as the original. Moreover, we formalize a framework for approximately minimizing higher-order multi-label MRF energies that combines the new reduction with the fusion-move and QPBO algorithms. While many computer vision problems today are formulated as energy minimization problems, they have mostly been limited to using first-order energies, which consist of unary and pairwise clique potentials, with a few exceptions that consider triples. This is because of the lack of efficient algorithms to optimize energies with higher-order interactions. Our algorithm challenges this restriction that limits the representational power of the models so that higher-order energies can be used to capture the rich statistics of natural scenes. We also show that some minimization methods can be considered special cases of the present framework, as well as comparing the new method experimentally with other such techniques.

Multibeam 3D Underwater SLAM with Probabilistic Registration.

PubMed

Palomer, Albert; Ridao, Pere; Ribas, David

2016-04-20

This paper describes a pose-based underwater 3D Simultaneous Localization and Mapping (SLAM) using a multibeam echosounder to produce high consistency underwater maps. The proposed algorithm compounds swath profiles of the seafloor with dead reckoning localization to build surface patches (i.e., point clouds). An Iterative Closest Point (ICP) with a probabilistic implementation is then used to register the point clouds, taking into account their uncertainties. The registration process is divided in two steps: (1) point-to-point association for coarse registration and (2) point-to-plane association for fine registration. The point clouds of the surfaces to be registered are sub-sampled in order to decrease both the computation time and also the potential of falling into local minima during the registration. In addition, a heuristic is used to decrease the complexity of the association step of the ICP from O(n2) to O(n) . The performance of the SLAM framework is tested using two real world datasets: First, a 2.5D bathymetric dataset obtained with the usual down-looking multibeam sonar configuration, and second, a full 3D underwater dataset acquired with a multibeam sonar mounted on a pan and tilt unit.

Empirical Model of the Location of the Main Ionospheric Trough

NASA Astrophysics Data System (ADS)

Deminov, M. G.; Shubin, V. N.

2018-05-01

The empirical model of the location of the main ionospheric trough (MIT) is developed based on an analysis of data from CHAMP satellite measured at the altitudes of 350-450 km during 2000-2007; the model is presented in the form of the analytical dependence of the invariant latitude of the trough minimum Φm on the magnetic local time (MLT), the geomagnetic activity, and the geographical longitude for the Northern and Southern Hemispheres. The time-weighted average index Kp(τ), the coefficient of which τ = 0.6 is determined by the requirement of the model minimum deviation from experimental data, is used as an indicator of geomagnetic activity. The model has no limitations, either in local time or geomagnetic activity. However, the initial set of MIT minima mainly contains data dealing with an interval of 16-08 MLT for Kp(τ) < 6; therefore, the model is rather qualitative outside this interval. It is also established that (a) the use of solar local time (SLT) instead of MLT increases the model error no more than by 5-10%; (b) the amplitude of the longitudinal effect at the latitude of MIT minimum in geomagnetic (invariant) coordinates is ten times lower than that in geographical coordinates.

Estimating cellular parameters through optimization procedures: elementary principles and applications.

PubMed

Kimura, Akatsuki; Celani, Antonio; Nagao, Hiromichi; Stasevich, Timothy; Nakamura, Kazuyuki

2015-01-01

Construction of quantitative models is a primary goal of quantitative biology, which aims to understand cellular and organismal phenomena in a quantitative manner. In this article, we introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental data. The aim of optimization is to minimize the sum of squared errors (SSE) in a prediction or to maximize likelihood. A (local) maximum of likelihood or (local) minimum of the SSE can efficiently be identified using gradient approaches. Addition of a stochastic process enables us to identify the global maximum/minimum without becoming trapped in local maxima/minima. Sampling approaches take advantage of increasing computational power to test numerous sets of parameters in order to determine the optimum set. By combining Bayesian inference with gradient or sampling approaches, we can estimate both the optimum parameters and the form of the likelihood function related to the parameters. Finally, we introduce four examples of research that utilize parameter optimization to obtain biological insights from quantified data: transcriptional regulation, bacterial chemotaxis, morphogenesis, and cell cycle regulation. With practical knowledge of parameter optimization, cell and developmental biologists can develop realistic models that reproduce their observations and thus, obtain mechanistic insights into phenomena of interest.

Minimizing Cache Misses Using Minimum-Surface Bodies

NASA Technical Reports Server (NTRS)

Frumkin, Michael; VanderWijngaart, Rob; Biegel, Bryan (Technical Monitor)

2002-01-01

A number of known techniques for improving cache performance in scientific computations involve the reordering of the iteration space. Some of these reorderings can be considered as coverings of the iteration space with the sets having good surface-to-volume ratio. Use of such sets reduces the number of cache misses in computations of local operators having the iteration space as a domain. First, we derive lower bounds which any algorithm must suffer while computing a local operator on a grid. Then we explore coverings of iteration spaces represented by structured and unstructured grids which allow us to approach these lower bounds. For structured grids we introduce a covering by successive minima tiles of the interference lattice of the grid. We show that the covering has low surface-to-volume ratio and present a computer experiment showing actual reduction of the cache misses achieved by using these tiles. For planar unstructured grids we show existence of a covering which reduces the number of cache misses to the level of structured grids. On the other hand, we present a triangulation of a 3-dimensional cube such that any local operator on the corresponding grid has significantly larger number of cache misses than a similar operator on a structured grid.

A TRMM Microwave Radiometer Rain Rate Estimation Method with Convective and Stratiform Discrimination

NASA Technical Reports Server (NTRS)

Prabhakara, C.; Iacovazzi, R., Jr.; Weinman, J. A.; Dalu, G.

1999-01-01

Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometer brightness temperature data in the 85 GHz channel (T85) reveal distinct local minima (T85min) in a regional map containing a Mesoscale Convective System (MCS). This is because of relatively small footprint size (approximately 5.5 km) and strong extinction properties in this channel of the TMI. A map of surface rain rate for that region, deduced from simultaneous measurements made by the Precipitation Radar (PR) on board the TRMM satellite, reveals that these T85(sub min), produced by scattering, correspond to local PR rain maxima. Utilizing the PR rain rate map as a guide, we infer empirically from TMI data the presence of three different kinds of thunderstorms or Cbs. These Cbs are classified as young, mature, and decaying types, and are assumed to have a scale of about 20 km on the average. Two parameters are used to classify these three kinds of Cbs based on the T85 data: a) the magnitude of scattering depression deduced from local T85(sub min) and b) the mean horizontal gradient of T85 around such minima. Knowing the category of a given Cb, we can estimate the rain rate associated with it. Such estimation is done with the help of relationships linking T85min to rain rate in each Cb type. Similarly, a weak background rain rate in all the areas where T85 is less than 260 K is deduced with another relationship linking T85 to rain rate. In our rain retrieval model, this background rain constitutes stratiform rain where the Cbs are absent. Initially, these relationships are optimized or tuned utilizing the PR and TMI data of a few MCS events. After such tuning, the model is applied to independent MCS cases. The areal distribution of light (1-10 mm/hr), moderate (10-20 mm/hr), and intense (>= 20 mm/hr) rain rates are retrieved satisfactorily. Accuracy in the estimates of the light, moderate, and intense rain areas and the mean rain rates associated with such areas in these independent MCS cases is on the average about 15 %. Taking advantage of this ability of our retrieval method, one could derive the latent heat input into the atmosphere over the 760 km wide swath of the TMI radiometer in the tropics.

Basics of SAR Polarimetry II

DTIC Science & Technology

2007-02-01

on the Poincare sphere are considered, which reduces to 3K ε for the mono-static reciprocal case. It plays an essential role in Czyz’s alternate...from above derivations that the co-pol-null minima ’ 1cn ρ and ’ 2cn ρ lie in a plane spanned by the co-pol-maxima (cross-pol-minima) and the ...maxima ( 2211 , xncmxncm ρρρρ == ) and the pair ( S1, S2 ) of cross-pol maxima ( ’ 2,1xm ρ ) lie in one main cross-sectional plane of the

Energy as a witness of multipartite entanglement in chains of arbitrary spins

NASA Astrophysics Data System (ADS)

Troiani, F.; Siloi, I.

2012-09-01

We develop a general approach for deriving the energy minima of biseparable states in chains of arbitrary spins s, and we report numerical results for spin values s≤5/2 (with N≤8). The minima provide a set of threshold values for exchange energy that allow us to detect different degrees of multipartite entanglement in one-dimensional spin systems. We finally demonstrate that the Heisenberg exchange Hamiltonian of N spins has a nondegenerate N-partite entangled ground state, and it can thus witness such correlations in all finite spin chains.

Opportunities and challenges to conserve water on the landscape in snow-dominated forests: The quest for the radiative minima and more...

NASA Astrophysics Data System (ADS)

Link, T. E.; Kumar, M.; Pomeroy, J. W.; Seyednasrollah, B.; Ellis, C. R.; Lawler, R.; Essery, R.

2012-12-01

In mountainous, forested environments, vegetation exerts a strong control on snowcover dynamics that affect ecohydrological processes, streamflow regimes, and riparian health. Snowcover deposition and ablation patterns in forests are controlled by a complex combination of canopy interception processes coupled with radiative and turbulent heat flux patterns related to topographic and canopy cover variations. In seasonal snow environments, snowcover ablation dynamics in forests are dominated by net radiation. Recent research indicates that in small canopy gaps a net radiation minima relative to both open and forested environments can occur, but depends strongly on solar angle, gap size, slope, canopy height and stem density. The optimal gap size to minimize radiation to snow was estimated to have a diameter between 1 and 2 times the surrounding vegetation height. Physically-based snowmelt simulations indicate that gaps may increase SWE and desynchronize snowmelt by approximately 3 weeks between north and south facing slopes, relative to undisturbed forests. On east and west facing slopes, small gaps cause melt to be slightly delayed relative to intact forests, and have a minimal effect on melt synchronicity between slopes. Recent research focused on canopy thinning also indicates that a net radiation minima occurs in canopies of intermediate densities. Physically-based radiative transfer simulations using a discrete tree-based model indicate that in mid-latitude level forests, the annually-integrated radiative minima occurs at a tree spacing of 2.65 relative to the canopy height. The radiative minima was found to occur in denser forests on south-facing slopes and sparser forests on north-facing slopes. The radiative minimums in thinned forests are controlled by solar angle, crown geometry and density, tree spacing, slope, and aspect. These results indicate that both gap and homogeneous forest thinning may be used to reduce snowmelt rates or alter melt synchronicity, but the exact configuration will be highly spatially variable. Development of management strategies to conserve water on the landscape to enhance forest and riparian health in a changing climate must also rigorously evaluate the effects of canopy thinning and specific hydrometeorological conditions on net radiation, turbulent fluxes, and snow interception processes.

Ab Initio and Analytic Intermolecular Potentials for Ar–CH3OH

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tasic, Uros; Alexeev, Yuri; Vayner, Grigoriy

2006-09-20

Ab initio calculations at the CCSD(T)/aug-cc-pVTZ level of theory were used to characterize the Ar–CH₃y6tOH intermolecular potential energy surface (PES). Potential energy curves were calculated for four different Ar + CH₃OH orientations and used to derive an analytic function for the intermolecular PES. A sum of Ar–C, Ar–O, Ar–H(C), and Ar–H(O) two-body potentials gives an excellent fit to these potential energy curves up to 100 kcal mol¯¹, and adding an additional r¯¹n term to the Buckingham two-body potential results in only a minor improvement in the fit. Three Ar–CH₃OH van der Waals minima were found from the CCSD(T)/aug-cc-pVTZ//MP2/aug-cc-pVTZ calculations. Themore » structure of the global minimum is in overall good agreement with experiment (X.-C. Tan, L. Sun and R. L. Kuczkowski, J. Mol. Spectrosc., 1995, 171, 248). It is T-shaped with the hydroxyl H-atom syn with respect to Ar. Extrapolated to the complete basis set (CBS) limit, the global minimum has a well depth of 0.72 kcal mol¯¹ with basis set superposition error (BSSE) correction. The aug-cc-pVTZ basis set gives a well depth only 0.10 kcal mol¯¹ smaller than this value. The well depths of the other two minima are within 0.16 kcal mol¯¹ of the global minimum. The analytic Ar–CH₃OH intermolecular potential also identifies these three minima as the only van der Waals minima and the structures predicted by the analytic potential are similar to the ab initio structures. The analytic potential identifies the same global minimum and the predicted well depths for the minima are within 0.05 kcal mol¯1 of the ab initio values. Combining this Ar–CH₃OH intermolecular potential with a potential for a OH-terminated alkylthiolate self-assembled monolayer surface (i.e., HO-SAM) provides a potential to model Ar + HO-SAM collisions.« less

Randomly iterated search and statistical competency as powerful inversion tools for deformation source modeling: Application to volcano interferometric synthetic aperture radar data

NASA Astrophysics Data System (ADS)

Shirzaei, M.; Walter, T. R.

2009-10-01

Modern geodetic techniques provide valuable and near real-time observations of volcanic activity. Characterizing the source of deformation based on these observations has become of major importance in related monitoring efforts. We investigate two random search approaches, simulated annealing (SA) and genetic algorithm (GA), and utilize them in an iterated manner. The iterated approach helps to prevent GA in general and SA in particular from getting trapped in local minima, and it also increases redundancy for exploring the search space. We apply a statistical competency test for estimating the confidence interval of the inversion source parameters, considering their internal interaction through the model, the effect of the model deficiency, and the observational error. Here, we present and test this new randomly iterated search and statistical competency (RISC) optimization method together with GA and SA for the modeling of data associated with volcanic deformations. Following synthetic and sensitivity tests, we apply the improved inversion techniques to two episodes of activity in the Campi Flegrei volcanic region in Italy, observed by the interferometric synthetic aperture radar technique. Inversion of these data allows derivation of deformation source parameters and their associated quality so that we can compare the two inversion methods. The RISC approach was found to be an efficient method in terms of computation time and search results and may be applied to other optimization problems in volcanic and tectonic environments.

Acceleration of saddle-point searches with machine learning.

PubMed

Peterson, Andrew A

2016-08-21

In atomistic simulations, the location of the saddle point on the potential-energy surface (PES) gives important information on transitions between local minima, for example, via transition-state theory. However, the search for saddle points often involves hundreds or thousands of ab initio force calls, which are typically all done at full accuracy. This results in the vast majority of the computational effort being spent calculating the electronic structure of states not important to the researcher, and very little time performing the calculation of the saddle point state itself. In this work, we describe how machine learning (ML) can reduce the number of intermediate ab initio calculations needed to locate saddle points. Since machine-learning models can learn from, and thus mimic, atomistic simulations, the saddle-point search can be conducted rapidly in the machine-learning representation. The saddle-point prediction can then be verified by an ab initio calculation; if it is incorrect, this strategically has identified regions of the PES where the machine-learning representation has insufficient training data. When these training data are used to improve the machine-learning model, the estimates greatly improve. This approach can be systematized, and in two simple example problems we demonstrate a dramatic reduction in the number of ab initio force calls. We expect that this approach and future refinements will greatly accelerate searches for saddle points, as well as other searches on the potential energy surface, as machine-learning methods see greater adoption by the atomistics community.

Hands-on parameter search for neural simulations by a MIDI-controller.

PubMed

Eichner, Hubert; Borst, Alexander

2011-01-01

Computational neuroscientists frequently encounter the challenge of parameter fitting--exploring a usually high dimensional variable space to find a parameter set that reproduces an experimental data set. One common approach is using automated search algorithms such as gradient descent or genetic algorithms. However, these approaches suffer several shortcomings related to their lack of understanding the underlying question, such as defining a suitable error function or getting stuck in local minima. Another widespread approach is manual parameter fitting using a keyboard or a mouse, evaluating different parameter sets following the users intuition. However, this process is often cumbersome and time-intensive. Here, we present a new method for manual parameter fitting. A MIDI controller provides input to the simulation software, where model parameters are then tuned according to the knob and slider positions on the device. The model is immediately updated on every parameter change, continuously plotting the latest results. Given reasonably short simulation times of less than one second, we find this method to be highly efficient in quickly determining good parameter sets. Our approach bears a close resemblance to tuning the sound of an analog synthesizer, giving the user a very good intuition of the problem at hand, such as immediate feedback if and how results are affected by specific parameter changes. In addition to be used in research, our approach should be an ideal teaching tool, allowing students to interactively explore complex models such as Hodgkin-Huxley or dynamical systems.

Hands-On Parameter Search for Neural Simulations by a MIDI-Controller

PubMed Central

Eichner, Hubert; Borst, Alexander

2011-01-01

Computational neuroscientists frequently encounter the challenge of parameter fitting – exploring a usually high dimensional variable space to find a parameter set that reproduces an experimental data set. One common approach is using automated search algorithms such as gradient descent or genetic algorithms. However, these approaches suffer several shortcomings related to their lack of understanding the underlying question, such as defining a suitable error function or getting stuck in local minima. Another widespread approach is manual parameter fitting using a keyboard or a mouse, evaluating different parameter sets following the users intuition. However, this process is often cumbersome and time-intensive. Here, we present a new method for manual parameter fitting. A MIDI controller provides input to the simulation software, where model parameters are then tuned according to the knob and slider positions on the device. The model is immediately updated on every parameter change, continuously plotting the latest results. Given reasonably short simulation times of less than one second, we find this method to be highly efficient in quickly determining good parameter sets. Our approach bears a close resemblance to tuning the sound of an analog synthesizer, giving the user a very good intuition of the problem at hand, such as immediate feedback if and how results are affected by specific parameter changes. In addition to be used in research, our approach should be an ideal teaching tool, allowing students to interactively explore complex models such as Hodgkin-Huxley or dynamical systems. PMID:22066027

Acceleration of saddle-point searches with machine learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peterson, Andrew A., E-mail: andrew-peterson@brown.edu

In atomistic simulations, the location of the saddle point on the potential-energy surface (PES) gives important information on transitions between local minima, for example, via transition-state theory. However, the search for saddle points often involves hundreds or thousands of ab initio force calls, which are typically all done at full accuracy. This results in the vast majority of the computational effort being spent calculating the electronic structure of states not important to the researcher, and very little time performing the calculation of the saddle point state itself. In this work, we describe how machine learning (ML) can reduce the numbermore » of intermediate ab initio calculations needed to locate saddle points. Since machine-learning models can learn from, and thus mimic, atomistic simulations, the saddle-point search can be conducted rapidly in the machine-learning representation. The saddle-point prediction can then be verified by an ab initio calculation; if it is incorrect, this strategically has identified regions of the PES where the machine-learning representation has insufficient training data. When these training data are used to improve the machine-learning model, the estimates greatly improve. This approach can be systematized, and in two simple example problems we demonstrate a dramatic reduction in the number of ab initio force calls. We expect that this approach and future refinements will greatly accelerate searches for saddle points, as well as other searches on the potential energy surface, as machine-learning methods see greater adoption by the atomistics community.« less

Time and Space Resolved High Harmonic Imaging of Electron Tunnelling from Molecules

NASA Astrophysics Data System (ADS)

Smirnova, O.

2009-05-01

High harmonic generation in intense laser fields carries the promise of combining sub-Angstrom spatial and attosecond temporal resolution of electronic structures and dynamics in molecules, see e.g. [1-3]. High harmonic emission occurs when an electron detached from a molecule by an intense laser field recombines with the parent ion [4]. Similar to Young's double-slit experiment, recombination to several ``lobes'' of the same molecular orbital can produce interference minima and maxima in harmonic intensities [1]. These minima (maxima) carry structural information -- they occur when the de-Broglie wavelength of the recombining electron matches distances between the centers. We demonstrate both theoretically and experimentally that amplitude minima (maxima) in the harmonic spectra can also have dynamical origin, reflecting multi-electron dynamics in the molecule. We use high harmonic spectra to record this dynamics and reconstruct the position of the hole left in the molecule after ionization. Experimental data are consistent with the hole starting in different places as the ionization dynamics changes from tunnelling to the multi-photon regime. Importantly, hole localization and subsequent attosecond dynamics are induced even in the tunnelling limit. Thus, even ``static'' tunnelling induced by a tip of a tunnelling microscope will generate similar attosecond dynamics in a sample. We anticipate that our approach will become standard in disentangling spatial and temporal information from high harmonic spectra of molecules.[4pt] In collaboration with Serguei Patchkovskii, National Research Council, 100 Sussex Drive, Ottawa, Ontario K1A 0R6, Canada; Yann Mairesse, NRC Canada and CELIA, Universit'e Bordeaux I, UMR 5107 (CNRS, Bordeaux 1, CEA), 351 Cours de la Lib'eration, 33405 Talence Cedex, France; Nirit Dudovich, NRC Canada and Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel; David Villeneuve, Paul Corkum, NRC Canada; and Misha Yu. Ivanov, NRC Canada and Imperial College of Science, Technology and Medicine, London SW7 2BW, United Kingdom. [4pt] [1] Lein, M., et al. Phys. Rev. Lett. 88, 183903 (2002).[0pt] [2] Itatani, J. et al. Nature 432, 834 (2004).[0pt] [3] Baker, S. et al Science 312, 424 (2006).[0pt] [4] Corkum, P. B.Phys. Rev. Lett. 71, 1994 (1993).

Implementing Badhwar-O'Neill Galactic Cosmic Ray Model for the Analysis of Space Radiation Exposure

NASA Technical Reports Server (NTRS)

Kim, Myung-Hee Y.; O'Neill, Patrick M.; Slaba, Tony C.

2014-01-01

For the analysis of radiation risks to astronauts and planning exploratory space missions, accurate energy spectrum of galactic cosmic radiation (GCR) is necessary. Characterization of the ionizing radiation environment is challenging because the interplanetary plasma and radiation fields are modulated by solar disturbances and the radiation doses received by astronauts in interplanetary space are likewise influenced. A model of the Badhwar-O'Neill 2011 (BO11) GCR environment, which is represented by GCR deceleration potential theta, has been derived by utilizing all of the GCR measurements from balloons, satellites, and the newer NASA Advanced Composition Explorer (ACE). In the BO11 model, the solar modulation level is derived from the mean international sunspot numbers with time-delay, which has been calibrated with actual flight instrument measurements to produce better GCR flux data fit during solar minima. GCR fluxes provided by the BO11 model were compared with various spacecraft measurements at 1 AU, and further comparisons were made for the tissue equivalent proportional counters measurements at low Earth orbits using the high-charge and energy transport (HZETRN) code and various GCR models. For the comparison of the absorbed dose and dose equivalent calculations with the measurements by Radiation Assessment Detector (RAD) at Gale crater on Mars, the intensities and energies of GCR entering the heliosphere were calculated by using the BO11 model, which accounts for time-dependent attenuation of the local interstellar spectrum of each element. The BO11 model, which has emphasized for the last 24 solar minima, showed in relatively good agreement with the RAD data for the first 200 sols, but it was resulted in to be less well during near the solar maximum of solar cycle 24 due to subtleties in the changing heliospheric conditions. By performing the error analysis of the BO11 model and the optimization in reducing overall uncertainty, the resultant BO13 model corrects the fit at solar maxima as well as being accurate at solar minima. The BO13 model is implemented to the NASA Space Cancer Risk model for the assessment of radiation risks. Overall cumulative probability distribution of solar modulation parameters represents the percentile rank of the average interplanetary GCR environment, and the probabilistic radiation risks can be assessed for various levels of GCR environment to support mission design and operational planning for future manned space exploration missions.

Quantum Heterogeneous Computing for Satellite Positioning Optimization

NASA Astrophysics Data System (ADS)

Bass, G.; Kumar, V.; Dulny, J., III

2016-12-01

Hard optimization problems occur in many fields of academic study and practical situations. We present results in which quantum heterogeneous computing is used to solve a real-world optimization problem: satellite positioning. Optimization problems like this can scale very rapidly with problem size, and become unsolvable with traditional brute-force methods. Typically, such problems have been approximately solved with heuristic approaches; however, these methods can take a long time to calculate and are not guaranteed to find optimal solutions. Quantum computing offers the possibility of producing significant speed-up and improved solution quality. There are now commercially available quantum annealing (QA) devices that are designed to solve difficult optimization problems. These devices have 1000+ quantum bits, but they have significant hardware size and connectivity limitations. We present a novel heterogeneous computing stack that combines QA and classical machine learning and allows the use of QA on problems larger than the quantum hardware could solve in isolation. We begin by analyzing the satellite positioning problem with a heuristic solver, the genetic algorithm. The classical computer's comparatively large available memory can explore the full problem space and converge to a solution relatively close to the true optimum. The QA device can then evolve directly to the optimal solution within this more limited space. Preliminary experiments, using the Quantum Monte Carlo (QMC) algorithm to simulate QA hardware, have produced promising results. Working with problem instances with known global minima, we find a solution within 8% in a matter of seconds, and within 5% in a few minutes. Future studies include replacing QMC with commercially available quantum hardware and exploring more problem sets and model parameters. Our results have important implications for how heterogeneous quantum computing can be used to solve difficult optimization problems in any field.

Quantum dynamics of the vibrations of helium bound to the nanosurface of a large planar organic molecule: phthalocyanine . He van der Waals complex.

PubMed

Gibbons, Brittney R; Xu, Minzhong; Bacić, Zlatko

2009-04-23

We report rigorous quantum three-dimensional calculations of highly excited intermolecular vibrational states of the van der Waals (vdW) complex phthalocyanine.He (Pc.He). The Pc molecule was treated as rigid and the intermolecular potential energy surface (IPES) was represented as a sum of atom-atom Lennard-Jones pair potentials. The IPES has four equivalent global minima on the diagonals of the square-shaped Pc, inside its five-membered rings, and four slightly shallower local minima between them, creating a distinctive corrugation pattern of the molecular nanosurface. The vdW vibrational states analyzed in this work extend to about two-thirds of the well depth of the IPES. For the assignment of the in-plane (xy) vdW vibrational excitations it was necessary to resort to two sets of quantum numbers, the Cartesian quantum numbers [nu(x), nu(y)] and the quantum numbers (v, l) of the 2D isotropic oscillator, depending on the nodal structure and the symmetry of the wave functions. The delocalization of the He atom parallel to the molecular surface is large already in the ground vdW state. It increases rapidly with the number of quanta in the in-plane vdW vibrations, with the maximum root-mean-square amplitudes Deltax and Deltay of about 7 au at the excitation energies around 40 cm(-1). The wave functions of the highly excited states tend to be delocalized over the entire nanosurface and often have a square shape, reflecting that of the substrate.

Rotationally adiabatic pair interactions of para- and ortho-hydrogen with the halogen molecules F2, Cl2, and Br2.

PubMed

Berg, Matthias; Accardi, Antonio; Paulus, Beate; Schmidt, Burkhard

2014-08-21

The present work is concerned with the weak interactions between hydrogen and halogen molecules, i.e., the interactions of pairs H2-X2 with X = F, Cl, Br, which are dominated by dispersion and quadrupole-quadrupole forces. The global minimum of the four-dimensional (4D) coupled cluster with singles and doubles and perturbative triples (CCSD(T)) pair potentials is always a T shaped structure where H2 acts as the hat of the T, with well depths (De) of 1.3, 2.4, and 3.1 kJ/mol for F2, Cl2, and Br2, respectively. MP2/AVQZ results, in reasonable agreement with CCSD(T) results extrapolated to the basis set limit, are used for detailed scans of the potentials. Due to the large difference in the rotational constants of the monomers, in the adiabatic approximation, one can solve the rotational Schrödinger equation for H2 in the potential of the X2 molecule. This yields effective two-dimensional rotationally adiabatic potential energy surfaces where pH2 and oH2 are point-like particles. These potentials for the H2-X2 complexes have global and local minima for effective linear and T-shaped complexes, respectively, which are separated by 0.4-1.0 kJ/mol, where oH2 binds stronger than pH2 to X2, due to higher alignment to minima structures of the 4D-pair potential. Further, we provide fits of an analytical function to the rotationally adiabatic potentials.

Investigations of the Rg-BrCl (Rg=He, Ne, Ar, Kr, Xe) binary van der Waals complexes: ab initio intermolecular potential energy surfaces, vibrational states and predicted pure rotational transition frequencies.

PubMed

Li, Song; Zheng, Rui; Chen, Shan-Jun; Chen, Yan; Chen, Peng

2017-03-05

The intermolecular potential energy surfaces (PESs) of the ground electronic state for the Rg-BrCl (Rg=He, Ne, Ar, Kr, Xe) van der Waals complexes have been constructed by using the coupled-cluster method in combination with the augmented quadruple-zeta correlation-consistent basis sets supplemented with an additional set of bond functions. The features of the anisotropic PESs for these complexes are remarkably similar, which are characterized by three minima and two saddle points between them. The global minimum corresponds to a collinear Rg-Br-Cl configuration. Two local minima, correlate with an anti-linear Rg-Cl-Br geometry and a nearly T-shaped structure, can also be located on each PES. The quantum bound state calculations enable us to investigate intermolecular vibrational states and rotational energy levels of the complexes. The transition frequencies are predicted and are fitted to obtain their corresponding spectroscopic constants. In general, the periodic trends are observed for this complex family. Comparisons with available experimental data for the collinear isomer of Ar-BrCl demonstrate reliability of our theoretical predictions, and our results for the other two isomers of Ar-BrCl as well as for other members of the complex family are also anticipated to be trustable. Except for the collinear isomer of Ar-BrCl, the data presented in this paper would be beneficial to improve our knowledge for these experimentally unknown species. Copyright © 2016 Elsevier B.V. All rights reserved.

Puckering transitions in cyclohexane: Revisited

NASA Astrophysics Data System (ADS)

Kang, Young Kee; Park, Hae Sook

2018-06-01

The interconversion pathways along the puckering transitions in cyclohexane were explored on the two-dimensional projection of the Cremer-Pople sphere using DFT methods and the CCSD(T), MP2, and dispersion-corrected DFT methods with various basis sets were assessed for the relative energies of local minima and transition states for the representative puckering transition pathways. The ωB97X-D/cc-pVTZ and ωB97X-D/def2-QZVP levels of theory well reproduced the relative energies with RMSD = 0.13 kcal/mol against the CCSD(T)/CBS-limit energies. The calculated activation parameters for chair to twist-boat interconversion of cyclohexane at the ωB97X-D/cc-pVTZ//(PCM) M06-2X/6-31+G(d) level of theory were consistent with the observed values.

Geological criteria and geophysical methods of natural bitumen deposits preparation to the development

NASA Astrophysics Data System (ADS)

Uspensky, B. V.; Borovsky, M. Ya; Vafin, R. F.; Valeeva, S. E.; Mudarisova, R. A.

2018-05-01

The article considers the provisions of the ontogenesis of the following factors in the formation of natural bitumen clusters in the Permian deposits of the Melekesskiy region: genetic, geodynamic, structural and hydrogeological. It is shown that tectonically weakened zones and zones of Neogene incisions development are fixed by high-precision gravimetry in the form of intense local minima of gravity. A favorable factor contributing to the "strengthening" of anomalous geophysical effects is the coincidence of the locations of these geological section heterogeneities in the plan. It is recommended at the stage of experimental-industrial operation a complex of geophysical methods for monitoring the processes of natural bitumen deposits development by means of secondary impact on the formation. High-precision magnetic, thermal and electrical prospecting in various modifications are used.

A quasi-physical algorithm for the structure optimization in an off-lattice protein model.

PubMed

Liu, Jing-Fa; Huang, Wen-Qi

2006-02-01

In this paper, we study an off-lattice protein AB model with two species of monomers, hydrophobic and hydrophilic, and present a heuristic quasi-physical algorithm. First, by elaborately simulating the movement of the smooth solids in the physical world, we find low-energy conformations for a given monomer chain. A subsequent off-trap strategy is then proposed to trigger a jump for a stuck situation in order to get out of the local minima. The algorithm has been tested in the three-dimensional AB model for all sequences with lengths of 13-55 monomers. In several cases, we renew the putative ground state energy values. The numerical results show that the proposed methods are very promising for finding the ground states of proteins.

On the Circulation Manifold for Two Adjacent Lifting Sections

NASA Technical Reports Server (NTRS)

Zannetti, Luca; Iollo, Angelo

1998-01-01

The circulation functional relative to two adjacent lifting sections is studied for two cases. In the first case we consider two adjacent circles. The circulation is computed as a function of the displacement of the secondary circle along the axis joining the two centers and of the angle of attack of the secondary circle, The gradient of such functional is computed by deriving a set of elliptic functions with respect both to their argument and to their Period. In the second case studied, we considered a wing-flap configuration. The circulation is computed by some implicit mappings, whose differentials with respect to the variation of the geometrical configuration in the physical space are found by divided differences. Configurations giving rise to local maxima and minima in the circulation manifold are presented.

Swarm-wavelet based extreme learning machine for finger movement classification on transradial amputees.

PubMed

Anam, Khairul; Al-Jumaily, Adel

2014-01-01

The use of a small number of surface electromyography (EMG) channels on the transradial amputee in a myoelectric controller is a big challenge. This paper proposes a pattern recognition system using an extreme learning machine (ELM) optimized by particle swarm optimization (PSO). PSO is mutated by wavelet function to avoid trapped in a local minima. The proposed system is used to classify eleven imagined finger motions on five amputees by using only two EMG channels. The optimal performance of wavelet-PSO was compared to a grid-search method and standard PSO. The experimental results show that the proposed system is the most accurate classifier among other tested classifiers. It could classify 11 finger motions with the average accuracy of about 94 % across five amputees.

Mathematics of gravitational lensing: multiple imaging and magnification

NASA Astrophysics Data System (ADS)

Petters, A. O.; Werner, M. C.

2010-09-01

The mathematical theory of gravitational lensing has revealed many generic and global properties. Beginning with multiple imaging, we review Morse-theoretic image counting formulas and lower bound results, and complex-algebraic upper bounds in the case of single and multiple lens planes. We discuss recent advances in the mathematics of stochastic lensing, discussing a general formula for the global expected number of minimum lensed images as well as asymptotic formulas for the probability densities of the microlensing random time delay functions, random lensing maps, and random shear, and an asymptotic expression for the global expected number of micro-minima. Multiple imaging in optical geometry and a spacetime setting are treated. We review global magnification relation results for model-dependent scenarios and cover recent developments on universal local magnification relations for higher order caustics.

Bursty, Broadband Electromagnetic Waves Associated with Three-Dimensional Nulls Observed in Turbulent Magnetosheath Reconnection

NASA Technical Reports Server (NTRS)

Adrian, Mark L.; Wendel, D. E.

2012-01-01

We investigate observations of intense bursts of electromagnetic wave energy in association with the thin current layers of turbulent magnetosheath reconnection. These observed emissions - typically detected in the layers immediately outside of the current layer proper - form two distinct types: (i) broadband emissions that extend continuously to lOs of Hertz; and (ii) structured bursts of emitted energy that occur above 80-Hz, often displaying features reminiscent of absorption bands and are observed near the local minima in the magnetic field. We present detailed analyses of these intense bursts of electromagnetic energy and quantify their proximity to X-IO-nulls and magnetic spine connected null pairs, as well as their correlation - if any - to the amount of magnetic energy converted by the process of magnetic reconnection.

Study of the Structural Stability in Intermetallics Using Displacive Transformation Paths

NASA Astrophysics Data System (ADS)

Sob, M.; Wang, L. G.; Vitek, V.

1997-03-01

Relative structural stability of TiAl, FeAl, NiAl and NiTi is studied by investigating displacive phase transformation paths. These include the well known tetragonal (Bain's) and trigonal deformation paths which correspond to large homogeneous straining, and also more complex paths that include the shuffling of atomic planes. The results of full-potential APW total energy calculations show that all higher-energy cubic structures studied are locally unstable with respect to some deformation modes. There may or may not be symmetry-dictated energy extrema corresponding to cubic lattices depending on the atomic ordering. However, other energy extrema that are not imposed by symmetry requirements occur along the transformation paths. Configurations corresponding to energy minima may represent metastable structures that can play an important role in interfaces and other extended defects.

Fast detection of the fuzzy communities based on leader-driven algorithm

NASA Astrophysics Data System (ADS)

Fang, Changjian; Mu, Dejun; Deng, Zhenghong; Hu, Jun; Yi, Chen-He

2018-03-01

In this paper, we present the leader-driven algorithm (LDA) for learning community structure in networks. The algorithm allows one to find overlapping clusters in a network, an important aspect of real networks, especially social networks. The algorithm requires no input parameters and learns the number of clusters naturally from the network. It accomplishes this using leadership centrality in a clever manner. It identifies local minima of leadership centrality as followers which belong only to one cluster, and the remaining nodes are leaders which connect clusters. In this way, the number of clusters can be learned using only the network structure. The LDA is also an extremely fast algorithm, having runtime linear in the network size. Thus, this algorithm can be used to efficiently cluster extremely large networks.

Recoil Inversion in the Photodissociation of Carbonyl Sulfide near 234 nm.

PubMed

Sofikitis, Dimitris; Suarez, Jaime; Schmidt, Johan A; Rakitzis, T Peter; Farantos, Stavros C; Janssen, Maurice H M

2017-06-23

We report the observation of recoil inversion of the CO (v=0, J_{CO}=66) state in the UV dissociation of lab-frame oriented carbonyl sulfide (OCS). This state is ejected in the opposite direction with respect to all other (>30) states and in absence of any OCS rotation, thus resulting in spatial filtering of this particular high-J rovibrational state. This inversion is caused by resonances occurring in shallow local minima of the molecular potential, which bring the sulfur closer to the oxygen than the carbon atom, and is a striking example where such subtleties severely modify the photofragment trajectories. The resonant behavior is observed only in the photofragment trajectories and not in their population, showing that stereodynamic measurements from oriented molecules offer an indispensable probe for exploring energy landscapes.

Skeletonization applied to magnetic resonance angiography images

NASA Astrophysics Data System (ADS)

Nystroem, Ingela

1998-06-01

When interpreting and analyzing magnetic resonance angiography images, the 3D overall tree structure and the thickness of the blood vessels are of interest. This shape information may be easier to obtain from the skeleton of the blood vessels. Skeletonization of digital volume objects denotes either reduction to a 2D structure consisting of 3D surfaces, and curves, or reduction to a 1D structure consisting of 3D curves only. Thin elongated objects, such as blood vessels, are well suited for reduction to curve skeletons. Our results indicate that the tree structure of the vascular system is well represented by the skeleton. Positions for possible artery stenoses may be identified by locating local minima in curve skeletons, where the skeletal voxels are labeled with the distance to the original background.

Sculpting bespoke mountains: Determining free energies with basis expansions

NASA Astrophysics Data System (ADS)

Whitmer, Jonathan K.; Fluitt, Aaron M.; Antony, Lucas; Qin, Jian; McGovern, Michael; de Pablo, Juan J.

2015-07-01

The intriguing behavior of a wide variety of physical systems, ranging from amorphous solids or glasses to proteins, is a direct manifestation of underlying free energy landscapes riddled with local minima separated by large barriers. Exploring such landscapes has arguably become one of statistical physics's great challenges. A new method is proposed here for uniform sampling of rugged free energy surfaces. The method, which relies on special Green's functions to approximate the Dirac delta function, improves significantly on existing simulation techniques by providing a boundary-agnostic approach that is capable of mapping complex features in multidimensional free energy surfaces. The usefulness of the proposed approach is established in the context of a simple model glass former and model proteins, demonstrating improved convergence and accuracy over existing methods.

Matrix isolation infrared spectra and photochemistry of hydantoin.

PubMed

Ildiz, Gulce Ogruc; Nunes, Cláudio M; Fausto, Rui

2013-01-31

Hydantoin (C(3)H(4)N(2)O(2), 2,4-imidazolidinedione) was isolated in argon matrix at 10 K and its infrared spectrum and unimolecular photochemistry were investigated. The molecular structure of the compound was studied both at the DFT(B3LYP) and MP2 levels of approximation with valence triple- and quadruple-ζ basis sets (6-311++G(d,p); cc-pVQZ). It was concluded that the minima in the potential energy surfaces of the molecule correspond to C(1) symmetry structures. However, the energy barrier separating the two-equivalent-by-symmetry minima stays below their zero-point energy, which makes the C(s) symmetry structure, which separates the two minima, the experimentally relevant one. The electronic structure of the molecule was studied in detail by performing the Natural Bond Orbital analysis of its electronic configuration within the DFT(B3LYP)/cc-pVQZ space. The infrared spectrum of the matrix isolated compound was fully assigned also with help of the theoretically predicted spectrum. Upon irradiation at λ = 230 nm, matrix-isolated hydantoin was found to photofragment into isocyanic acid, CO, and methylenimine.

Using tethered triblock copolymers to mediate the interaction between substrates

NASA Astrophysics Data System (ADS)

Chern, Shyh-Shi; Zhulina, Ekaterina B.; Pickett, Galen T.; Balazs, Anna C.

1998-04-01

Using scaling analysis and a self-consistent field (SCF) theory, we compress two copolymer-coated surfaces and isolate conditions that yield multiple, distinct minima in the interaction profile. We focus on planar surfaces that are coated with ABC triblock copolymers. Tethered to the surface by the last monomer in the C block, the copolymers are grafted at relatively low densities. The surrounding solution is a poor solvent for both the A and C blocks, and is a good solvent for the B blocks. Through scaling theory, we pinpoint the parameters that yield two minima in the interaction profile. The SCF calculations reveal the changes in the morphology of the polymers as the layers are compressed. Through both studies, we determine how the morphological changes give rise to the observed surface interactions. The results provide guidelines for creating polymer-coated colloidal systems that can form two stable crystal structures. Such systems could be used for bistable, optical switches. The findings also yield a prescription for creating systems that exhibit additional minima in the free energy of interaction.

The first orbital parameters and period variation of the short-period eclipsing binary AQ Boo

NASA Astrophysics Data System (ADS)

Wang, Shuai; Zhang, Liyun; Pi, Qingfeng; Han, Xianming L.; Zhang, Xiliang; Lu, Hongpeng; Wang, Daimei; Li, TongAn

2016-10-01

We obtained the first VRI CCD light curves of the short-period contact eclipsing binary AQ Boo, which was observed on March 22 and April 19 in 2014 at Xinglong station of National Astronomical Observatories, and on January 20, 21 and February 28 in 2015 at Kunming station of Yunnan Observatories of Chinese Academy of Sciences, China. Using our six newly obtained minima and the minima that other authors obtained previously, we revised the ephemeris of AQ Boo. By fitting the O-C (observed minus calculated) values of the minima, the orbital period of AQ Boo shows a decreasing tendency P˙ = - 1.47(0.17) ×10-7 days/year. We interpret the phenomenon by mass transfer from the secondary (more massive) component to the primary (less massive) one. By using the updated Wilson & Devinney program, we also derived the photometric orbital parameters of AQ Boo for the first time. We conclude that AQ Boo is a near contact binary with a low contact factor of 14.43%, and will become an over-contact system as the mass transfer continues.

Minimum of the order parameter fluctuations of seismicity before major earthquakes in Japan.

PubMed

Sarlis, Nicholas V; Skordas, Efthimios S; Varotsos, Panayiotis A; Nagao, Toshiyasu; Kamogawa, Masashi; Tanaka, Haruo; Uyeda, Seiya

2013-08-20

It has been shown that some dynamic features hidden in the time series of complex systems can be uncovered if we analyze them in a time domain called natural time χ. The order parameter of seismicity introduced in this time domain is the variance of χ weighted for normalized energy of each earthquake. Here, we analyze the Japan seismic catalog in natural time from January 1, 1984 to March 11, 2011, the day of the M9 Tohoku earthquake, by considering a sliding natural time window of fixed length comprised of the number of events that would occur in a few months. We find that the fluctuations of the order parameter of seismicity exhibit distinct minima a few months before all of the shallow earthquakes of magnitude 7.6 or larger that occurred during this 27-y period in the Japanese area. Among the minima, the minimum before the M9 Tohoku earthquake was the deepest. It appears that there are two kinds of minima, namely precursory and nonprecursory, to large earthquakes.

The limits of local correlation theory: electronic delocalization and chemically smooth potential energy surfaces.

PubMed

Subotnik, Joseph E; Sodt, Alex; Head-Gordon, Martin

2008-01-21

Local coupled-cluster theory provides an algorithm for measuring electronic correlation quickly, using only the spatial locality of localized electronic orbitals. Previously, we showed [J. Subotnik et al., J. Chem. Phys. 125, 074116 (2006)] that one may construct a local coupled-cluster singles-doubles theory which (i) yields smooth potential energy surfaces and (ii) achieves near linear scaling. That theory selected which orbitals to correlate based only on the distances between the centers of different, localized orbitals, and the approximate potential energy surfaces were characterized as smooth using only visual identification. This paper now extends our previous algorithm in three important ways. First, locality is now based on both the distances between the centers of orbitals as well as the spatial extent of the orbitals. We find that, by accounting for the spatial extent of a delocalized orbital, one can account for electronic correlation in systems with some electronic delocalization using fast correlation methods designed around orbital locality. Second, we now enforce locality on not just the amplitudes (which measure the exact electron-electron correlation), but also on the two-electron integrals themselves (which measure the bare electron-electron interaction). Our conclusion is that we can bump integrals as well as amplitudes, thereby gaining a tremendous increase in speed and paradoxically increasing the accuracy of our LCCSD approach. Third and finally, we now make a rigorous definition of chemical smoothness as requiring that potential energy surfaces not support artificial maxima, minima, or inflection points. By looking at first and second derivatives from finite difference techniques, we demonstrate complete chemical smoothness of our potential energy surfaces (bumping both amplitudes and integrals). These results are significant both from a theoretical and from a computationally practical point of view.

Forecasting Kp from solar wind data: input parameter study using 3-hour averages and 3-hour range values

NASA Astrophysics Data System (ADS)

Wintoft, Peter; Wik, Magnus; Matzka, Jürgen; Shprits, Yuri

2017-11-01

We have developed neural network models that predict Kp from upstream solar wind data. We study the importance of various input parameters, starting with the magnetic component Bz, particle density n, and velocity V and then adding total field B and the By component. As we also notice a seasonal and UT variation in average Kp we include functions of day-of-year and UT. Finally, as Kp is a global representation of the maximum range of geomagnetic variation over 3-hour UT intervals we conclude that sudden changes in the solar wind can have a big effect on Kp, even though it is a 3-hour value. Therefore, 3-hour solar wind averages will not always appropriately represent the solar wind condition, and we introduce 3-hour maxima and minima values to some degree address this problem. We find that introducing total field B and 3-hour maxima and minima, derived from 1-minute solar wind data, have a great influence on the performance. Due to the low number of samples for high Kp values there can be considerable variation in predicted Kp for different networks with similar validation errors. We address this issue by using an ensemble of networks from which we use the median predicted Kp. The models (ensemble of networks) provide prediction lead times in the range 20-90 min given by the time it takes a solar wind structure to travel from L1 to Earth. Two models are implemented that can be run with real time data: (1) IRF-Kp-2017-h3 uses the 3-hour averages of the solar wind data and (2) IRF-Kp-2017 uses in addition to the averages, also the minima and maxima values. The IRF-Kp-2017 model has RMS error of 0.55 and linear correlation of 0.92 based on an independent test set with final Kp covering 2 years using ACE Level 2 data. The IRF-Kp-2017-h3 model has RMSE = 0.63 and correlation = 0.89. We also explore the errors when tested on another two-year period with real-time ACE data which gives RMSE = 0.59 for IRF-Kp-2017 and RMSE = 0.73 for IRF-Kp-2017-h3. The errors as function of Kp and for different years are also studied.

Statistical mechanics of neocortical interactions. Derivation of short-term-memory capacity

NASA Astrophysics Data System (ADS)

Ingber, Lester

1984-06-01

A theory developed by the author to describe macroscopic neocortical interactions demonstrates that empirical values of chemical and electrical parameters of synaptic interactions establish several minima of the path-integral Lagrangian as a function of excitatory and inhibitory columnar firings. The number of possible minima, their time scales of hysteresis and probable reverberations, and their nearest-neighbor columnar interactions are all consistent with well-established empirical rules of human short-term memory. Thus, aspects of conscious experience are derived from neuronal firing patterns, using modern methods of nonlinear nonequilibrium statistical mechanics to develop realistic explicit synaptic interactions.

Comparative Magnetic Minima: Characterizing Quiet Times in the Sun and Stars. Symposium of the International Astronomical Union (286th) Held in Mendoza, Argentina on October 3-7, 2011

DTIC Science & Technology

2011-10-01

11:15 – 11:45 Invited Talk – Stars in Magnetic Grand Minima: Where Are They and What Are They Like? Steven Saar (Presentation file) 11:45 – 12:00...of Archaeology and Ancient History, University Rd, Leicester LE1 7RH, United Kingdom IAUS 279 Death of Massive Stars: Supernovae and Gamma-Ray Bursts...of Astronomy & Astrophysics, 525 Davey Lab, University Park, PA 16802, USA IAUS 283 Planetary Nebulae: an Eye to the Future A. MANCHADO, Instituto de

Photometric geodesy of main-belt asteroids. III - Additional lightcurves

NASA Technical Reports Server (NTRS)

Weidenschilling, S. J.; Chapman, C. R.; Davis, D. R.; Greenberg, R.; Levy, D. H.

1990-01-01

A total of 107 complete or partial lightcurves are presented for 59 different asteroids over the 1982-1989 period. Unusual lightcurves with unequal minima and maxima at large amplitudes are preferentially seen for M-type asteroids. Some asteroids, such as 16 Psyche and 201 Penelope, exhibit lightcurves combining large amplitude with very unequal brightness for both maxima and both minima, even at small phase angles. An M-type asteroid is believed to consist of a metal core of a differentiated parent body that has had its rocky mantle completely removed by one or more large impacts.

Derivative, maxima and minima in a graphical context

NASA Astrophysics Data System (ADS)

Rivera-Figueroa, Antonio; Ponce-Campuzano, Juan Carlos

2013-03-01

A deeper learning of the properties and applications of the derivative for the study of functions may be achieved when teachers present lessons within a highly graphic context, linking the geometric illustrations to formal proofs. Each concept is better understood and more easily retained when it is presented and explained visually using graphs. In this article, we explore the conditions of necessity or sufficiency of the criteria for determining the maxima and minima of a function. The implications for the teaching of derivatives and functions in undergraduate courses are discussed in light of our analysis of textbooks.

Photometric geodesy of main-belt asteroids. III. Additional lightcurves

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weidenschilling, S.J.; Chapman, C.R.; Davis, D.R.

1990-08-01

A total of 107 complete or partial lightcurves are presented for 59 different asteroids over the 1982-1989 period. Unusual lightcurves with unequal minima and maxima at large amplitudes are preferentially seen for M-type asteroids. Some asteroids, such as 16 Psyche and 201 Penelope, exhibit lightcurves combining large amplitude with very unequal brightness for both maxima and both minima, even at small phase angles. An M-type asteroid is believed to consist of a metal core of a differentiated parent body that has had its rocky mantle completely removed by one or more large impacts. 39 refs.

The Effect of the Ionosphere on Radiowave Signals and Systems Performance Based on Ionospheric Effects Symposium Held on 1-3 May 1990

DTIC Science & Technology

1990-05-03

winter and a minimum in summer ; in contrast, at sunspot maximum the seasonal peaks tend to occur around the equinoxes and the minima in summer . ’riis is...more clearly seen in Figures 4(b) ahnd 4(c). Note that around sunspot maximum the summer noon value may be less than the summer midnight value. (3) The...seasonal variation of the midnight values show summer peaks and winter minima with high values near the peaks of the sunspot cycles and low values

Thermal analysis of fractures at Cerberus Fossae, Mars: Detection of air convection in the porous debris apron

NASA Astrophysics Data System (ADS)

Antoine, R.; Lopez, T.; Baratoux, D.; Rabinowicz, M.; Kurita, K.

2011-08-01

This study investigates the cause of high nighttime temperatures within Cerberus Fossae, a system of fractures affecting the Central Elysium Planitia. The inner parts (walls and floor) of the fractures are up to 40 K warmer than the surrounding plains. However, several temperature profiles exhibit a local temperature minima occurring in the central part of the fractures. We examined first the influence of cooling efficiency at night in the case of a strong reduction of the sky proportion induced by the fracture's geometry. However, the lack of correlation between temperature and sky proportion, calculated from extracted Mars Orbiter Laser Altimeter (MOLA) profiles argues against this hypothesis. Albedo variations were considered but appear to be limited within the fractures, and are generally not correlated with the temperatures. Variations of the thermal properties of bedrocks exposures, debris aprons and sand dunes inferred from high-resolution images do not either correlate with temperature variations within the fractures. As none of these factors taken alone, or combined, can satisfactorily explain the temperature variations within and near the fracture, we suggest that geothermal heat transported by air convection within the porous debris aprons may contribute to explain high temperatures at night and the local minima on the fracture floor. The conditions for the occurrence of the suggested phenomenon and the consequences on the surface temperature are numerically explored. A conservative geothermal gradient of 20 mW/m 2 was used in the simulations, this value being consistent with either inferred lithosphere elastic thicknesses below the shield volcanoes of the Tharsis dome or values predicted from numerical simulations of the thermal evolution of Mars. The model results indicate that temperature differences of 10-20 K between the central and upper parts of the fracture are explained in the case of high Darcy velocities which require high permeability values (5 × 10 -6 m 2). The presence of coarse material composing the debris aprons may explain why this key criteria was met in the context of Cerberus Fossae.

New insights into the folding of a β-sheet miniprotein in a reduced space of collective hydrogen bond variables: application to a hydrodynamic analysis of the folding flow.

PubMed

Kalgin, Igor V; Caflisch, Amedeo; Chekmarev, Sergei F; Karplus, Martin

2013-05-23

A new analysis of the 20 μs equilibrium folding/unfolding molecular dynamics simulations of the three-stranded antiparallel β-sheet miniprotein (beta3s) in implicit solvent is presented. The conformation space is reduced in dimensionality by introduction of linear combinations of hydrogen bond distances as the collective variables making use of a specially adapted principal component analysis (PCA); i.e., to make structured conformations more pronounced, only the formed bonds are included in determining the principal components. It is shown that a three-dimensional (3D) subspace gives a meaningful representation of the folding behavior. The first component, to which eight native hydrogen bonds make the major contribution (four in each beta hairpin), is found to play the role of the reaction coordinate for the overall folding process, while the second and third components distinguish the structured conformations. The representative points of the trajectory in the 3D space are grouped into conformational clusters that correspond to locally stable conformations of beta3s identified in earlier work. A simplified kinetic network based on the three components is constructed, and it is complemented by a hydrodynamic analysis. The latter, making use of "passive tracers" in 3D space, indicates that the folding flow is much more complex than suggested by the kinetic network. A 2D representation of streamlines shows there are vortices which correspond to repeated local rearrangement, not only around minima of the free energy surface but also in flat regions between minima. The vortices revealed by the hydrodynamic analysis are apparently not evident in folding pathways generated by transition-path sampling. Making use of the fact that the values of the collective hydrogen bond variables are linearly related to the Cartesian coordinate space, the RMSD between clusters is determined. Interestingly, the transition rates show an approximate exponential correlation with distance in the hydrogen bond subspace. Comparison with the many published studies shows good agreement with the present analysis for the parts that can be compared, supporting the robust character of our understanding of this "hydrogen atom" of protein folding.

Hierarchical Coupling of First-Principles Molecular Dynamics with Advanced Sampling Methods.

PubMed

Sevgen, Emre; Giberti, Federico; Sidky, Hythem; Whitmer, Jonathan K; Galli, Giulia; Gygi, Francois; de Pablo, Juan J

2018-05-14

We present a seamless coupling of a suite of codes designed to perform advanced sampling simulations, with a first-principles molecular dynamics (MD) engine. As an illustrative example, we discuss results for the free energy and potential surfaces of the alanine dipeptide obtained using both local and hybrid density functionals (DFT), and we compare them with those of a widely used classical force field, Amber99sb. In our calculations, the efficiency of first-principles MD using hybrid functionals is augmented by hierarchical sampling, where hybrid free energy calculations are initiated using estimates obtained with local functionals. We find that the free energy surfaces obtained from classical and first-principles calculations differ. Compared to DFT results, the classical force field overestimates the internal energy contribution of high free energy states, and it underestimates the entropic contribution along the entire free energy profile. Using the string method, we illustrate how these differences lead to different transition pathways connecting the metastable minima of the alanine dipeptide. In larger peptides, those differences would lead to qualitatively different results for the equilibrium structure and conformation of these molecules.