Dynamic Optimization

NASA Technical Reports Server (NTRS)

Laird, Philip

1992-01-01

We distinguish static and dynamic optimization of programs: whereas static optimization modifies a program before runtime and is based only on its syntactical structure, dynamic optimization is based on the statistical properties of the input source and examples of program execution. Explanation-based generalization is a commonly used dynamic optimization method, but its effectiveness as a speedup-learning method is limited, in part because it fails to separate the learning process from the program transformation process. This paper describes a dynamic optimization technique called a learn-optimize cycle that first uses a learning element to uncover predictable patterns in the program execution and then uses an optimization algorithm to map these patterns into beneficial transformations. The technique has been used successfully for dynamic optimization of pure Prolog.

Reactive multi-particle collision dynamics with reactive boundary conditions

NASA Astrophysics Data System (ADS)

Sayyidmousavi, Alireza; Rohlf, Katrin

2018-07-01

In the present study, an off-lattice particle-based method called the reactive multi-particle collision (RMPC) dynamics is extended to model reaction-diffusion systems with reactive boundary conditions in which the a priori diffusion coefficient of the particles needs to be maintained throughout the simulation. To this end, the authors have made use of the so-called bath particles whose purpose is only to ensure proper diffusion of the main particles in the system. In order to model partial adsorption by a reactive boundary in the RMPC, the probability of a particle being adsorbed, once it hits the boundary, is calculated by drawing an analogy between the RMPC and Brownian Dynamics. The main advantages of the RMPC compared to other molecular based methods are less computational cost as well as conservation of mass, energy and momentum in the collision and free streaming steps. The proposed approach is tested on three reaction-diffusion systems and very good agreement with the solutions to their corresponding partial differential equations is observed.

Contour detection improved by context-adaptive surround suppression.

PubMed

Sang, Qiang; Cai, Biao; Chen, Hao

2017-01-01

Recently, many image processing applications have taken advantage of a psychophysical and neurophysiological mechanism, called "surround suppression" to extract object contour from a natural scene. However, these traditional methods often adopt a single suppression model and a fixed input parameter called "inhibition level", which needs to be manually specified. To overcome these drawbacks, we propose a novel model, called "context-adaptive surround suppression", which can automatically control the effect of surround suppression according to image local contextual features measured by a surface estimator based on a local linear kernel. Moreover, a dynamic suppression method and its stopping mechanism are introduced to avoid manual intervention. The proposed algorithm is demonstrated and validated by a broad range of experimental results.

Immunity-Based Optimal Estimation Approach for a New Real Time Group Elevator Dynamic Control Application for Energy and Time Saving

PubMed Central

Baygin, Mehmet; Karakose, Mehmet

2013-01-01

Nowadays, the increasing use of group elevator control systems owing to increasing building heights makes the development of high-performance algorithms necessary in terms of time and energy saving. Although there are many studies in the literature about this topic, they are still not effective enough because they are not able to evaluate all features of system. In this paper, a new approach of immune system-based optimal estimate is studied for dynamic control of group elevator systems. The method is mainly based on estimation of optimal way by optimizing all calls with genetic, immune system and DNA computing algorithms, and it is evaluated with a fuzzy system. The system has a dynamic feature in terms of the situation of calls and the option of the most appropriate algorithm, and it also adaptively works in terms of parameters such as the number of floors and cabins. This new approach which provides both time and energy saving was carried out in real time. The experimental results comparatively demonstrate the effects of method. With dynamic and adaptive control approach in this study carried out, a significant progress on group elevator control systems has been achieved in terms of time and energy efficiency according to traditional methods. PMID:23935433

Thermalization as an invisibility cloak for fragile quantum superpositions

NASA Astrophysics Data System (ADS)

Hahn, Walter; Fine, Boris V.

2017-07-01

We propose a method for protecting fragile quantum superpositions in many-particle systems from dephasing by external classical noise. We call superpositions "fragile" if dephasing occurs particularly fast, because the noise couples very differently to the superposed states. The method consists of letting a quantum superposition evolve under the internal thermalization dynamics of the system, followed by a time-reversal manipulation known as Loschmidt echo. The thermalization dynamics makes the superposed states almost indistinguishable during most of the above procedure. We validate the method by applying it to a cluster of spins ½.

Reinforcement learning for resource allocation in LEO satellite networks.

PubMed

Usaha, Wipawee; Barria, Javier A

2007-06-01

In this paper, we develop and assess online decision-making algorithms for call admission and routing for low Earth orbit (LEO) satellite networks. It has been shown in a recent paper that, in a LEO satellite system, a semi-Markov decision process formulation of the call admission and routing problem can achieve better performance in terms of an average revenue function than existing routing methods. However, the conventional dynamic programming (DP) numerical solution becomes prohibited as the problem size increases. In this paper, two solution methods based on reinforcement learning (RL) are proposed in order to circumvent the computational burden of DP. The first method is based on an actor-critic method with temporal-difference (TD) learning. The second method is based on a critic-only method, called optimistic TD learning. The algorithms enhance performance in terms of requirements in storage, computational complexity and computational time, and in terms of an overall long-term average revenue function that penalizes blocked calls. Numerical studies are carried out, and the results obtained show that the RL framework can achieve up to 56% higher average revenue over existing routing methods used in LEO satellite networks with reasonable storage and computational requirements.

Classification of Domain Movements in Proteins Using Dynamic Contact Graphs

PubMed Central

Taylor, Daniel; Cawley, Gavin; Hayward, Steven

2013-01-01

A new method for the classification of domain movements in proteins is described and applied to 1822 pairs of structures from the Protein Data Bank that represent a domain movement in two-domain proteins. The method is based on changes in contacts between residues from the two domains in moving from one conformation to the other. We argue that there are five types of elemental contact changes and that these relate to five model domain movements called: “free”, “open-closed”, “anchored”, “sliding-twist”, and “see-saw.” A directed graph is introduced called the “Dynamic Contact Graph” which represents the contact changes in a domain movement. In many cases a graph, or part of a graph, provides a clear visual metaphor for the movement it represents and is a motif that can be easily recognised. The Dynamic Contact Graphs are often comprised of disconnected subgraphs indicating independent regions which may play different roles in the domain movement. The Dynamic Contact Graph for each domain movement is decomposed into elemental Dynamic Contact Graphs, those that represent elemental contact changes, allowing us to count the number of instances of each type of elemental contact change in the domain movement. This naturally leads to sixteen classes into which the 1822 domain movements are classified. PMID:24260562

Target Detection and Classification Using Seismic and PIR Sensors

DTIC Science & Technology

2012-06-01

time series analysis via wavelet - based partitioning,” Signal Process...regard, this paper presents a wavelet - based method for target detection and classification. The proposed method has been validated on data sets of...The work reported in this paper makes use of a wavelet - based feature extraction method , called Symbolic Dynamic Filtering (SDF) [12]–[14]. The

Structural dynamic analysis of the Space Shuttle Main Engine

NASA Technical Reports Server (NTRS)

Scott, L. P.; Jamison, G. T.; Mccutcheon, W. A.; Price, J. M.

1981-01-01

This structural dynamic analysis supports development of the SSME by evaluating components subjected to critical dynamic loads, identifying significant parameters, and evaluating solution methods. Engine operating parameters at both rated and full power levels are considered. Detailed structural dynamic analyses of operationally critical and life limited components support the assessment of engine design modifications and environmental changes. Engine system test results are utilized to verify analytic model simulations. The SSME main chamber injector assembly is an assembly of 600 injector elements which are called LOX posts. The overall LOX post analysis procedure is shown.

Visual question answering using hierarchical dynamic memory networks

NASA Astrophysics Data System (ADS)

Shang, Jiayu; Li, Shiren; Duan, Zhikui; Huang, Junwei

2018-04-01

Visual Question Answering (VQA) is one of the most popular research fields in machine learning which aims to let the computer learn to answer natural language questions with images. In this paper, we propose a new method called hierarchical dynamic memory networks (HDMN), which takes both question attention and visual attention into consideration impressed by Co-Attention method, which is the best (or among the best) algorithm for now. Additionally, we use bi-directional LSTMs, which have a better capability to remain more information from the question and image, to replace the old unit so that we can capture information from both past and future sentences to be used. Then we rebuild the hierarchical architecture for not only question attention but also visual attention. What's more, we accelerate the algorithm via a new technic called Batch Normalization which helps the network converge more quickly than other algorithms. The experimental result shows that our model improves the state of the art on the large COCO-QA dataset, compared with other methods.

From seconds to months: an overview of multi-scale dynamics of mobile telephone calls

NASA Astrophysics Data System (ADS)

Saramäki, Jari; Moro, Esteban

2015-06-01

Big Data on electronic records of social interactions allow approaching human behaviour and sociality from a quantitative point of view with unforeseen statistical power. Mobile telephone Call Detail Records (CDRs), automatically collected by telecom operators for billing purposes, have proven especially fruitful for understanding one-to-one communication patterns as well as the dynamics of social networks that are reflected in such patterns. We present an overview of empirical results on the multi-scale dynamics of social dynamics and networks inferred from mobile telephone calls. We begin with the shortest timescales and fastest dynamics, such as burstiness of call sequences between individuals, and "zoom out" towards longer temporal and larger structural scales, from temporal motifs formed by correlated calls between multiple individuals to long-term dynamics of social groups. We conclude this overview with a future outlook.

Dynamic game balancing implementation using adaptive algorithm in mobile-based Safari Indonesia game

NASA Astrophysics Data System (ADS)

Yuniarti, Anny; Nata Wardanie, Novita; Kuswardayan, Imam

2018-03-01

In developing a game there is one method that should be applied to maintain the interest of players, namely dynamic game balancing. Dynamic game balancing is a process to match a player’s playing style with the behaviour, attributes, and game environment. This study applies dynamic game balancing using adaptive algorithm in scrolling shooter game type called Safari Indonesia which developed using Unity. The game of this type is portrayed by a fighter aircraft character trying to defend itself from insistent enemy attacks. This classic game is chosen to implement adaptive algorithms because it has quite complex attributes to be developed using dynamic game balancing. Tests conducted by distributing questionnaires to a number of players indicate that this method managed to reduce frustration and increase the pleasure factor in playing.

The life of a meander bend: Connecting shape and dynamics via analysis of a numerical model

NASA Astrophysics Data System (ADS)

Schwenk, Jon; Lanzoni, Stefano; Foufoula-Georgiou, Efi

2015-04-01

Analysis of bend-scale meandering river dynamics is a problem of theoretical and practical interest. This work introduces a method for extracting and analyzing the history of individual meander bends from inception until cutoff (called "atoms") by tracking backward through time the set of two cutoff nodes in numerical meander migration models. Application of this method to a simplified yet physically based model provides access to previously unavailable bend-scale meander dynamics over long times and at high temporal resolutions. We find that before cutoffs, the intrinsic model dynamics invariably simulate a prototypical cutoff atom shape we dub simple. Once perturbations from cutoffs occur, two other archetypal cutoff planform shapes emerge called long and round that are distinguished by a stretching along their long and perpendicular axes, respectively. Three measures of meander migration—growth rate, average migration rate, and centroid migration rate—are introduced to capture the dynamic lives of individual bends and reveal that similar cutoff atom geometries share similar dynamic histories. Specifically, through the lens of the three shape types, simples are seen to have the highest growth and average migration rates, followed by rounds, and finally longs. Using the maximum average migration rate as a metric describing an atom's dynamic past, we show a strong connection between it and two metrics of cutoff geometry. This result suggests both that early formative dynamics may be inferred from static cutoff planforms and that there exists a critical period early in a meander bend's life when its dynamic trajectory is most sensitive to cutoff perturbations. An example of how these results could be applied to Mississippi River oxbow lakes with unknown historic dynamics is shown. The results characterize the underlying model and provide a framework for comparisons against more complex models and observed dynamics.

Time-dependent structural transformation analysis to high-level Petri net model with active state transition diagram.

PubMed

Li, Chen; Nagasaki, Masao; Saito, Ayumu; Miyano, Satoru

2010-04-01

With an accumulation of in silico data obtained by simulating large-scale biological networks, a new interest of research is emerging for elucidating how living organism functions over time in cells. Investigating the dynamic features of current computational models promises a deeper understanding of complex cellular processes. This leads us to develop a method that utilizes structural properties of the model over all simulation time steps. Further, user-friendly overviews of dynamic behaviors can be considered to provide a great help in understanding the variations of system mechanisms. We propose a novel method for constructing and analyzing a so-called active state transition diagram (ASTD) by using time-course simulation data of a high-level Petri net. Our method includes two new algorithms. The first algorithm extracts a series of subnets (called temporal subnets) reflecting biological components contributing to the dynamics, while retaining positive mathematical qualities. The second one creates an ASTD composed of unique temporal subnets. ASTD provides users with concise information allowing them to grasp and trace how a key regulatory subnet and/or a network changes with time. The applicability of our method is demonstrated by the analysis of the underlying model for circadian rhythms in Drosophila. Building ASTD is a useful means to convert a hybrid model dealing with discrete, continuous and more complicated events to finite time-dependent states. Based on ASTD, various analytical approaches can be applied to obtain new insights into not only systematic mechanisms but also dynamics.

Dynamic pattern matcher using incomplete data

NASA Technical Reports Server (NTRS)

Johnson, Gordon G. (Inventor); Wang, Lui (Inventor)

1993-01-01

This invention relates generally to pattern matching systems, and more particularly to a method for dynamically adapting the system to enhance the effectiveness of a pattern match. Apparatus and methods for calculating the similarity between patterns are known. There is considerable interest, however, in the storage and retrieval of data, particularly, when the search is called or initiated by incomplete information. For many search algorithms, a query initiating a data search requires exact information, and the data file is searched for an exact match. Inability to find an exact match thus results in a failure of the system or method.

An Efficient Solution Method for Multibody Systems with Loops Using Multiple Processors

NASA Technical Reports Server (NTRS)

Ghosh, Tushar K.; Nguyen, Luong A.; Quiocho, Leslie J.

2015-01-01

This paper describes a multibody dynamics algorithm formulated for parallel implementation on multiprocessor computing platforms using the divide-and-conquer approach. The system of interest is a general topology of rigid and elastic articulated bodies with or without loops. The algorithm divides the multibody system into a number of smaller sets of bodies in chain or tree structures, called "branches" at convenient joints called "connection points", and uses an Order-N (O (N)) approach to formulate the dynamics of each branch in terms of the unknown spatial connection forces. The equations of motion for the branches, leaving the connection forces as unknowns, are implemented in separate processors in parallel for computational efficiency, and the equations for all the unknown connection forces are synthesized and solved in one or several processors. The performances of two implementations of this divide-and-conquer algorithm in multiple processors are compared with an existing method implemented on a single processor.

A framework to observe and evaluate the sustainability of human-natural systems in a complex dynamic context.

PubMed

Satanarachchi, Niranji; Mino, Takashi

2014-01-01

This paper aims to explore the prominent implications of the process of observing complex dynamics linked to sustainability in human-natural systems and to propose a framework for sustainability evaluation by introducing the concept of sustainability boundaries. Arguing that both observing and evaluating sustainability should engage awareness of complex dynamics from the outset, we try to embody this idea in the framework by two complementary methods, namely, the layer view- and dimensional view-based methods, which support the understanding of a reflexive and iterative sustainability process. The framework enables the observation of complex dynamic sustainability contexts, which we call observation metastructures, and enable us to map the contexts to sustainability boundaries.

Static Methods in the Design of Nonlinear Automatic Control Systems,

DTIC Science & Technology

1984-06-27

227 Chapter VI. Ways of Decrease of the Number of Statistical Nodes During the Research of Nonlinear Systems...at present occupies the central place. This region of research was called the statistical dynamics of nonlinear H automatic control systems...receives further development in the numerous research of Soviet and C foreign scientists. Special role in the development of the statistical dynamics of

Application of interactive computer graphics in wind-tunnel dynamic model testing

NASA Technical Reports Server (NTRS)

Doggett, R. V., Jr.; Hammond, C. E.

1975-01-01

The computer-controlled data-acquisition system recently installed for use with a transonic dynamics tunnel was described. This includes a discussion of the hardware/software features of the system. A subcritical response damping technique, called the combined randomdec/moving-block method, for use in windtunnel-model flutter testing, that has been implemented on the data-acquisition system, is described in some detail. Some results using the method are presented and the importance of using interactive graphics in applying the technique in near real time during wind-tunnel test operations is discussed.

Differential Variance Analysis: a direct method to quantify and visualize dynamic heterogeneities

NASA Astrophysics Data System (ADS)

Pastore, Raffaele; Pesce, Giuseppe; Caggioni, Marco

2017-03-01

Many amorphous materials show spatially heterogenous dynamics, as different regions of the same system relax at different rates. Such a signature, known as Dynamic Heterogeneity, has been crucial to understand the nature of the jamming transition in simple model systems and is currently considered very promising to characterize more complex fluids of industrial and biological relevance. Unfortunately, measurements of dynamic heterogeneities typically require sophisticated experimental set-ups and are performed by few specialized groups. It is now possible to quantitatively characterize the relaxation process and the emergence of dynamic heterogeneities using a straightforward method, here validated on video microscopy data of hard-sphere colloidal glasses. We call this method Differential Variance Analysis (DVA), since it focuses on the variance of the differential frames, obtained subtracting images at different time-lags. Moreover, direct visualization of dynamic heterogeneities naturally appears in the differential frames, when the time-lag is set to the one corresponding to the maximum dynamic susceptibility. This approach opens the way to effectively characterize and tailor a wide variety of soft materials, from complex formulated products to biological tissues.

Digital micromirror device camera with per-pixel coded exposure for high dynamic range imaging.

PubMed

Feng, Wei; Zhang, Fumin; Wang, Weijing; Xing, Wei; Qu, Xinghua

2017-05-01

In this paper, we overcome the limited dynamic range of the conventional digital camera, and propose a method of realizing high dynamic range imaging (HDRI) from a novel programmable imaging system called a digital micromirror device (DMD) camera. The unique feature of the proposed new method is that the spatial and temporal information of incident light in our DMD camera can be flexibly modulated, and it enables the camera pixels always to have reasonable exposure intensity by DMD pixel-level modulation. More importantly, it allows different light intensity control algorithms used in our programmable imaging system to achieve HDRI. We implement the optical system prototype, analyze the theory of per-pixel coded exposure for HDRI, and put forward an adaptive light intensity control algorithm to effectively modulate the different light intensity to recover high dynamic range images. Via experiments, we demonstrate the effectiveness of our method and implement the HDRI on different objects.

The Effect of Mixing Events on the Dynamics of pH1N1 Outbreaks at Small Residential Colleges

ERIC Educational Resources Information Center

Palin, Karen; Greer, Meredith L.

2012-01-01

Objective: The authors examine the dynamics and the impact of all-campus events on pH1N1 spread at Bates College in fall 2009, with comparisons to 3 other campuses. Participants: Students (N = 285) presented or called in to the Bates Health Center with symptoms consistent with influenza-like illness. Methods: Health Center staff at Bates collected…

Interaction sorting method for molecular dynamics on multi-core SIMD CPU architecture.

PubMed

Matvienko, Sergey; Alemasov, Nikolay; Fomin, Eduard

2015-02-01

Molecular dynamics (MD) is widely used in computational biology for studying binding mechanisms of molecules, molecular transport, conformational transitions, protein folding, etc. The method is computationally expensive; thus, the demand for the development of novel, much more efficient algorithms is still high. Therefore, the new algorithm designed in 2007 and called interaction sorting (IS) clearly attracted interest, as it outperformed the most efficient MD algorithms. In this work, a new IS modification is proposed which allows the algorithm to utilize SIMD processor instructions. This paper shows that the improvement provides an additional gain in performance, 9% to 45% in comparison to the original IS method.

Hamiltonian Dynamics of Spider-Type Multirotor Rigid Bodies Systems

NASA Astrophysics Data System (ADS)

Doroshin, Anton V.

2010-03-01

This paper sets out to develop a spider-type multiple-rotor system which can be used for attitude control of spacecraft. The multirotor system contains a large number of rotor-equipped rays, so it was called a ``Spider-type System,'' also it can be called ``Rotary Hedgehog.'' These systems allow using spinups and captures of conjugate rotors to perform compound attitude motion of spacecraft. The paper describes a new method of spacecraft attitude reorientation and new mathematical model of motion in Hamilton form. Hamiltonian dynamics of the system is investigated with the help of Andoyer-Deprit canonical variables. These variables allow obtaining exact solution for hetero- and homoclinic orbits in phase space of the system motion, which are very important for qualitative analysis.

Time-dependent structural transformation analysis to high-level Petri net model with active state transition diagram

PubMed Central

2010-01-01

Background With an accumulation of in silico data obtained by simulating large-scale biological networks, a new interest of research is emerging for elucidating how living organism functions over time in cells. Investigating the dynamic features of current computational models promises a deeper understanding of complex cellular processes. This leads us to develop a method that utilizes structural properties of the model over all simulation time steps. Further, user-friendly overviews of dynamic behaviors can be considered to provide a great help in understanding the variations of system mechanisms. Results We propose a novel method for constructing and analyzing a so-called active state transition diagram (ASTD) by using time-course simulation data of a high-level Petri net. Our method includes two new algorithms. The first algorithm extracts a series of subnets (called temporal subnets) reflecting biological components contributing to the dynamics, while retaining positive mathematical qualities. The second one creates an ASTD composed of unique temporal subnets. ASTD provides users with concise information allowing them to grasp and trace how a key regulatory subnet and/or a network changes with time. The applicability of our method is demonstrated by the analysis of the underlying model for circadian rhythms in Drosophila. Conclusions Building ASTD is a useful means to convert a hybrid model dealing with discrete, continuous and more complicated events to finite time-dependent states. Based on ASTD, various analytical approaches can be applied to obtain new insights into not only systematic mechanisms but also dynamics. PMID:20356411

Double optical gating

NASA Astrophysics Data System (ADS)

Gilbertson, Steve

The observation and control of dynamics in atomic and molecular targets requires the use of laser pulses with duration less than the characteristic timescale of the process which is to be manipulated. For electron dynamics, this time scale is on the order of attoseconds where 1 attosecond = 10 -18 seconds. In order to generate pulses on this time scale, different gating methods have been proposed. The idea is to extract or "gate" a single pulse from an attosecond pulse train and switch off all the other pulses. While previous methods have had some success, they are very difficult to implement and so far very few labs have access to these unique light sources. The purpose of this work is to introduce a new method, called double optical gating (DOG), and to demonstrate its effectiveness at generating high contrast single isolated attosecond pulses from multi-cycle lasers. First, the method is described in detail and is investigated in the spectral domain. The resulting attosecond pulses produced are then temporally characterized through attosecond streaking. A second method of gating, called generalized double optical gating (GDOG), is also introduced. This method allows attosecond pulse generation directly from a carrier-envelope phase un-stabilized laser system for the first time. Next the methods of DOG and GDOG are implemented in attosecond applications like high flux pulses and extreme broadband spectrum generation. Finally, the attosecond pulses themselves are used in experiments. First, an attosecond/femtosecond cross correlation is used for characterization of spatial and temporal properties of femtosecond pulses. Then, an attosecond pump, femtosecond probe experiment is conducted to observe and control electron dynamics in helium for the first time.

Theory of the development of alternans in the heart during controlled diastolic interval pacing

NASA Astrophysics Data System (ADS)

Otani, Niels F.

2017-09-01

The beat-to-beat alternation in action potential durations (APDs) in the heart, called APD alternans, has been linked to the development of serious cardiac rhythm disorders, including ventricular tachycardia and fibrillation. The length of the period between action potentials, called the diastolic interval (DI), is a key dynamical variable in the standard theory of alternans development. Thus, methods that control the DI may be useful in preventing dangerous cardiac rhythms. In this study, we examine the dynamics of alternans during controlled-DI pacing using a series of single-cell and one-dimensional (1D) fiber models of alternans dynamics. We find that a model that combines a so-called memory model with a calcium cycling model can reasonably explain two key experimental results: the possibility of alternans during constant-DI pacing and the phase lag of APDs behind DIs during sinusoidal-DI pacing. We also find that these results can be replicated by incorporating the memory model into an amplitude equation description of a 1D fiber. The 1D fiber result is potentially concerning because it seems to suggest that constant-DI control of alternans can only be effective over only a limited region in space.

A Verification System for Distributed Objects with Asynchronous Method Calls

NASA Astrophysics Data System (ADS)

Ahrendt, Wolfgang; Dylla, Maximilian

We present a verification system for Creol, an object-oriented modeling language for concurrent distributed applications. The system is an instance of KeY, a framework for object-oriented software verification, which has so far been applied foremost to sequential Java. Building on KeY characteristic concepts, like dynamic logic, sequent calculus, explicit substitutions, and the taclet rule language, the system presented in this paper addresses functional correctness of Creol models featuring local cooperative thread parallelism and global communication via asynchronous method calls. The calculus heavily operates on communication histories which describe the interfaces of Creol units. Two example scenarios demonstrate the usage of the system.

Numerical solution of stiff systems of ordinary differential equations with applications to electronic circuits

NASA Technical Reports Server (NTRS)

Rosenbaum, J. S.

1971-01-01

Systems of ordinary differential equations in which the magnitudes of the eigenvalues (or time constants) vary greatly are commonly called stiff. Such systems of equations arise in nuclear reactor kinetics, the flow of chemically reacting gas, dynamics, control theory, circuit analysis and other fields. The research reported develops an A-stable numerical integration technique for solving stiff systems of ordinary differential equations. The method, which is called the generalized trapezoidal rule, is a modification of the trapezoidal rule. However, the method is computationally more efficient than the trapezoidal rule when the solution of the almost-discontinuous segments is being calculated.

Adaptive dynamic programming for discrete-time linear quadratic regulation based on multirate generalised policy iteration

NASA Astrophysics Data System (ADS)

Chun, Tae Yoon; Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho

2018-06-01

In this paper, we propose two multirate generalised policy iteration (GPI) algorithms applied to discrete-time linear quadratic regulation problems. The proposed algorithms are extensions of the existing GPI algorithm that consists of the approximate policy evaluation and policy improvement steps. The two proposed schemes, named heuristic dynamic programming (HDP) and dual HDP (DHP), based on multirate GPI, use multi-step estimation (M-step Bellman equation) at the approximate policy evaluation step for estimating the value function and its gradient called costate, respectively. Then, we show that these two methods with the same update horizon can be considered equivalent in the iteration domain. Furthermore, monotonically increasing and decreasing convergences, so called value iteration (VI)-mode and policy iteration (PI)-mode convergences, are proved to hold for the proposed multirate GPIs. Further, general convergence properties in terms of eigenvalues are also studied. The data-driven online implementation methods for the proposed HDP and DHP are demonstrated and finally, we present the results of numerical simulations performed to verify the effectiveness of the proposed methods.

Unstructured mesh methods for CFD

NASA Technical Reports Server (NTRS)

Peraire, J.; Morgan, K.; Peiro, J.

1990-01-01

Mesh generation methods for Computational Fluid Dynamics (CFD) are outlined. Geometric modeling is discussed. An advancing front method is described. Flow past a two engine Falcon aeroplane is studied. An algorithm and associated data structure called the alternating digital tree, which efficiently solves the geometric searching problem is described. The computation of an initial approximation to the steady state solution of a given poblem is described. Mesh generation for transient flows is described.

Uncertainty Propagation Methods for High-Dimensional Complex Systems

NASA Astrophysics Data System (ADS)

Mukherjee, Arpan

Researchers are developing ever smaller aircraft called Micro Aerial Vehicles (MAVs). The Space Robotics Group has joined the field by developing a dragonfly-inspired MAV. This thesis presents two contributions to this project. The first is the development of a dynamical model of the internal MAV components to be used for tuning design parameters and as a future plant model. This model is derived using the Lagrangian method and differs from others because it accounts for the internal dynamics of the system. The second contribution of this thesis is an estimation algorithm that can be used to determine prototype performance and verify the dynamical model from the first part. Based on the Gauss-Newton Batch Estimator, this algorithm uses a single camera and known points of interest on the wing to estimate the wing kinematic angles. Unlike other single-camera methods, this method is probabilistically based rather than being geometric.

Complexity of EEG-signal in Time Domain - Possible Biomedical Application

NASA Astrophysics Data System (ADS)

Klonowski, Wlodzimierz; Olejarczyk, Elzbieta; Stepien, Robert

2002-07-01

Human brain is a highly complex nonlinear system. So it is not surprising that in analysis of EEG-signal, which represents overall activity of the brain, the methods of Nonlinear Dynamics (or Chaos Theory as it is commonly called) can be used. Even if the signal is not chaotic these methods are a motivating tool to explore changes in brain activity due to different functional activation states, e.g. different sleep stages, or to applied therapy, e.g. exposure to chemical agents (drugs) and physical factors (light, magnetic field). The methods supplied by Nonlinear Dynamics reveal signal characteristics that are not revealed by linear methods like FFT. Better understanding of principles that govern dynamics and complexity of EEG-signal can help to find `the signatures' of different physiological and pathological states of human brain, quantitative characteristics that may find applications in medical diagnostics.

Advertisement-call modification, male competition and female preference in the bird-voiced treefrog Hyla avivoca

PubMed Central

Martínez-Rivera, Carlos César; Gerhardt, H. Carl

2009-01-01

Senders and receivers influence dynamic characteristics of the signals used for mate attraction over different time scales. On a moment-to-moment basis, interactions among senders competing for a mate influence dynamic characteristics, whereas the preferences of receivers of the opposite gender exert an influence over evolutionary time. We observed and recorded the calling patterns of the bird-voiced treefrog Hyla avivoca, to assess how the dynamic characters of calls vary during interactions among groups of males in a chorus. This question was also addressed using playback experiments with males. Playback experiments with females showed how changes in dynamic call properties are likely to affect male mating success. Frogs calling in pairs, groups, or in response to playbacks produced longer calls than did isolated males. During call overlap, males often increased the duration of the silent interval (gaps) between the pulses of their calls so that the pulses of the calls of two neighbors interdigitated. This change resulted in increased variability of pulse rate, a traditionally static acoustic property; however, males also produced high proportions of non-overlapped calls in which variability in pulse rate was low and had species-typical values. Females preferred long calls to short and average-duration calls, and non-overlapped calls to overlapped calls. Given a choice between pairs of overlapped calls, females preferred pairs in which the proportion of overlap was low and pairs in which the pulses of such calls interdigitated completely. The observed patterns of vocal competition thus reflect the preferences of conspecific females, which have influenced the evolution of the calling behavior of H. avivoca. PMID:19789730

Global Optimal Trajectory in Chaos and NP-Hardness

NASA Astrophysics Data System (ADS)

Latorre, Vittorio; Gao, David Yang

This paper presents an unconventional theory and method for solving general nonlinear dynamical systems. Instead of the direct iterative methods, the discretized nonlinear system is first formulated as a global optimization problem via the least squares method. A newly developed canonical duality theory shows that this nonconvex minimization problem can be solved deterministically in polynomial time if a global optimality condition is satisfied. The so-called pseudo-chaos produced by linear iterative methods are mainly due to the intrinsic numerical error accumulations. Otherwise, the global optimization problem could be NP-hard and the nonlinear system can be really chaotic. A conjecture is proposed, which reveals the connection between chaos in nonlinear dynamics and NP-hardness in computer science. The methodology and the conjecture are verified by applications to the well-known logistic equation, a forced memristive circuit and the Lorenz system. Computational results show that the canonical duality theory can be used to identify chaotic systems and to obtain realistic global optimal solutions in nonlinear dynamical systems. The method and results presented in this paper should bring some new insights into nonlinear dynamical systems and NP-hardness in computational complexity theory.

Model-based restoration using light vein for range-gated imaging systems.

PubMed

Wang, Canjin; Sun, Tao; Wang, Tingfeng; Wang, Rui; Guo, Jin; Tian, Yuzhen

2016-09-10

The images captured by an airborne range-gated imaging system are degraded by many factors, such as light scattering, noise, defocus of the optical system, atmospheric disturbances, platform vibrations, and so on. The characteristics of low illumination, few details, and high noise make the state-of-the-art restoration method fail. In this paper, we present a restoration method especially for range-gated imaging systems. The degradation process is divided into two parts: the static part and the dynamic part. For the static part, we establish the physical model of the imaging system according to the laser transmission theory, and estimate the static point spread function (PSF). For the dynamic part, a so-called light vein feature extraction method is presented to estimate the fuzzy parameter of the atmospheric disturbance and platform movement, which make contributions to the dynamic PSF. Finally, combined with the static and dynamic PSF, an iterative updating framework is used to restore the image. Compared with the state-of-the-art methods, the proposed method can effectively suppress ringing artifacts and achieve better performance in a range-gated imaging system.

Leap-dynamics: efficient sampling of conformational space of proteins and peptides in solution.

PubMed

Kleinjung, J; Bayley, P; Fraternali, F

2000-03-31

A molecular simulation scheme, called Leap-dynamics, that provides efficient sampling of protein conformational space in solution is presented. The scheme is a combined approach using a fast sampling method, imposing conformational 'leaps' to force the system over energy barriers, and molecular dynamics (MD) for refinement. The presence of solvent is approximated by a potential of mean force depending on the solvent accessible surface area. The method has been successfully applied to N-acetyl-L-alanine-N-methylamide (alanine dipeptide), sampling experimentally observed conformations inaccessible to MD alone under the chosen conditions. The method predicts correctly the increased partial flexibility of the mutant Y35G compared to native bovine pancreatic trypsin inhibitor. In particular, the improvement over MD consists of the detection of conformational flexibility that corresponds closely to slow motions identified by nuclear magnetic resonance techniques.

Photogrammetry and Videogrammetry Methods Development for Solar Sail Structures. Masters Thesis awarded by George Washington Univ.

NASA Technical Reports Server (NTRS)

Pappa, Richard S. (Technical Monitor); Black, Jonathan T.

2003-01-01

This report discusses the development and application of metrology methods called photogrammetry and videogrammetry that make accurate measurements from photographs. These methods have been adapted for the static and dynamic characterization of gossamer structures, as four specific solar sail applications demonstrate. The applications prove that high-resolution, full-field, non-contact static measurements of solar sails using dot projection photogrammetry are possible as well as full-field, non-contact, dynamic characterization using dot projection videogrammetry. The accuracy of the measurement of the resonant frequencies and operating deflection shapes that were extracted surpassed expectations. While other non-contact measurement methods exist, they are not full-field and require significantly more time to take data.

Hamiltonian Dynamics of Spider-Type Multirotor Rigid Bodies Systems

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

Doroshin, Anton V.

2010-03-01

This paper sets out to develop a spider-type multiple-rotor system which can be used for attitude control of spacecraft. The multirotor system contains a large number of rotor-equipped rays, so it was called a 'Spider-type System', also it can be called 'Rotary Hedgehog'. These systems allow using spinups and captures of conjugate rotors to perform compound attitude motion of spacecraft. The paper describes a new method of spacecraft attitude reorientation and new mathematical model of motion in Hamilton form. Hamiltonian dynamics of the system is investigated with the help of Andoyer-Deprit canonical variables. These variables allow obtaining exact solution formore » hetero- and homoclinic orbits in phase space of the system motion, which are very important for qualitative analysis.« less

Field Crickets Compensate for Unattractive Static Long-Distance Call Components by Increasing Dynamic Signalling Effort.

PubMed

McAuley, Emily M; Bertram, Susan M

2016-01-01

The evolution of multiple sexual signals presents a dilemma since individuals selecting a mate should pay attention to the most honest signal and ignore the rest; however, multiple signals may evolve if, together, they provide more information to the receiver than either one would alone. Static and dynamic signals, for instance, can act as multiple messages, providing information on different aspects of signaller quality that reflect condition at different time scales. While the nature of static signals makes them difficult or impossible for individuals to augment, dynamic signals are much more susceptible to temporary fluctuations in effort. We investigated whether male Texas field crickets, Gryllus texensis, that produce unattractive static signals compensate by dynamically increasing their calling effort. Our findings lend partial support to the compensation hypothesis, as males that called at unattractive carrier frequencies (a static trait) spent more time calling each night (a dynamic trait). Interestingly, this finding was most pronounced in males that called with attractive pulse characteristics (static traits) but did not occur in males that called with unattractive pulse characteristics. Males that signalled with unattractive pulse characteristics (duration and pause) spent less time calling through the night. Our correlative findings on wild caught males suggest that only males that signal with attractive pulse characteristics may be able to afford to pay the costs of both trait exaggeration and increased calling effort to compensate for poor carrier frequencies.

Generating relevant kinetic Monte Carlo catalogs using temperature accelerated dynamics with control over the accuracy

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

Chatterjee, Abhijit; Voter, Arthur

2009-01-01

We develop a variation of the temperature accelerated dynamics (TAD) method, called the p-TAD method, that efficiently generates an on-the-fly kinetic Monte Carlo (KMC) process catalog with control over the accuracy of the catalog. It is assumed that transition state theory is valid. The p-TAD method guarantees that processes relevant at the timescales of interest to the simulation are present in the catalog with a chosen confidence. A confidence measure associated with the process catalog is derived. The dynamics is then studied using the process catalog with the KMC method. Effective accuracy of a p-TAD calculation is derived when amore » KMC catalog is reused for conditions different from those the catalog was originally generated for. Different KMC catalog generation strategies that exploit the features of the p-TAD method and ensure higher accuracy and/or computational efficiency are presented. The accuracy and the computational requirements of the p-TAD method are assessed. Comparisons to the original TAD method are made. As an example, we study dynamics in sub-monolayer Ag/Cu(110) at the time scale of seconds using the p-TAD method. It is demonstrated that the p-TAD method overcomes several challenges plaguing the conventional KMC method.« less

A Dynamic Alternative to the Scientific Method

ERIC Educational Resources Information Center

Musante, Susan

2009-01-01

Scotchmoor and a team of natural scientists, social scientists, philosophers, and educators developed a Web site called Understanding Science ("www.understandingscience.org") to explain to teachers, students, and the general public "how science "really" works." The site, launched in January 2009 and funded by the National Science Foundation,…

Field Crickets Compensate for Unattractive Static Long-Distance Call Components by Increasing Dynamic Signalling Effort

PubMed Central

McAuley, Emily M.

2016-01-01

The evolution of multiple sexual signals presents a dilemma since individuals selecting a mate should pay attention to the most honest signal and ignore the rest; however, multiple signals may evolve if, together, they provide more information to the receiver than either one would alone. Static and dynamic signals, for instance, can act as multiple messages, providing information on different aspects of signaller quality that reflect condition at different time scales. While the nature of static signals makes them difficult or impossible for individuals to augment, dynamic signals are much more susceptible to temporary fluctuations in effort. We investigated whether male Texas field crickets, Gryllus texensis, that produce unattractive static signals compensate by dynamically increasing their calling effort. Our findings lend partial support to the compensation hypothesis, as males that called at unattractive carrier frequencies (a static trait) spent more time calling each night (a dynamic trait). Interestingly, this finding was most pronounced in males that called with attractive pulse characteristics (static traits) but did not occur in males that called with unattractive pulse characteristics. Males that signalled with unattractive pulse characteristics (duration and pause) spent less time calling through the night. Our correlative findings on wild caught males suggest that only males that signal with attractive pulse characteristics may be able to afford to pay the costs of both trait exaggeration and increased calling effort to compensate for poor carrier frequencies. PMID:27936045

Prediction of dynamical systems by symbolic regression

NASA Astrophysics Data System (ADS)

Quade, Markus; Abel, Markus; Shafi, Kamran; Niven, Robert K.; Noack, Bernd R.

2016-07-01

We study the modeling and prediction of dynamical systems based on conventional models derived from measurements. Such algorithms are highly desirable in situations where the underlying dynamics are hard to model from physical principles or simplified models need to be found. We focus on symbolic regression methods as a part of machine learning. These algorithms are capable of learning an analytically tractable model from data, a highly valuable property. Symbolic regression methods can be considered as generalized regression methods. We investigate two particular algorithms, the so-called fast function extraction which is a generalized linear regression algorithm, and genetic programming which is a very general method. Both are able to combine functions in a certain way such that a good model for the prediction of the temporal evolution of a dynamical system can be identified. We illustrate the algorithms by finding a prediction for the evolution of a harmonic oscillator based on measurements, by detecting an arriving front in an excitable system, and as a real-world application, the prediction of solar power production based on energy production observations at a given site together with the weather forecast.

SWCD: a sliding window and self-regulated learning-based background updating method for change detection in videos

NASA Astrophysics Data System (ADS)

Işık, Şahin; Özkan, Kemal; Günal, Serkan; Gerek, Ömer Nezih

2018-03-01

Change detection with background subtraction process remains to be an unresolved issue and attracts research interest due to challenges encountered on static and dynamic scenes. The key challenge is about how to update dynamically changing backgrounds from frames with an adaptive and self-regulated feedback mechanism. In order to achieve this, we present an effective change detection algorithm for pixelwise changes. A sliding window approach combined with dynamic control of update parameters is introduced for updating background frames, which we called sliding window-based change detection. Comprehensive experiments on related test videos show that the integrated algorithm yields good objective and subjective performance by overcoming illumination variations, camera jitters, and intermittent object motions. It is argued that the obtained method makes a fair alternative in most types of foreground extraction scenarios; unlike case-specific methods, which normally fail for their nonconsidered scenarios.

Simulation of spacecraft attitude dynamics using TREETOPS and model-specific computer Codes

NASA Technical Reports Server (NTRS)

Cochran, John E.; No, T. S.; Fitz-Coy, Norman G.

1989-01-01

The simulation of spacecraft attitude dynamics and control using the generic, multi-body code called TREETOPS and other codes written especially to simulate particular systems is discussed. Differences in the methods used to derive equations of motion--Kane's method for TREETOPS and the Lagrangian and Newton-Euler methods, respectively, for the other two codes--are considered. Simulation results from the TREETOPS code are compared with those from the other two codes for two example systems. One system is a chain of rigid bodies; the other consists of two rigid bodies attached to a flexible base body. Since the computer codes were developed independently, consistent results serve as a verification of the correctness of all the programs. Differences in the results are discussed. Results for the two-rigid-body, one-flexible-body system are useful also as information on multi-body, flexible, pointing payload dynamics.

Algorithms and software for nonlinear structural dynamics

NASA Technical Reports Server (NTRS)

Belytschko, Ted; Gilbertsen, Noreen D.; Neal, Mark O.

1989-01-01

The objective of this research is to develop efficient methods for explicit time integration in nonlinear structural dynamics for computers which utilize both concurrency and vectorization. As a framework for these studies, the program WHAMS, which is described in Explicit Algorithms for the Nonlinear Dynamics of Shells (T. Belytschko, J. I. Lin, and C.-S. Tsay, Computer Methods in Applied Mechanics and Engineering, Vol. 42, 1984, pp 225 to 251), is used. There are two factors which make the development of efficient concurrent explicit time integration programs a challenge in a structural dynamics program: (1) the need for a variety of element types, which complicates the scheduling-allocation problem; and (2) the need for different time steps in different parts of the mesh, which is here called mixed delta t integration, so that a few stiff elements do not reduce the time steps throughout the mesh.

Online gaming for learning optimal team strategies in real time

NASA Astrophysics Data System (ADS)

Hudas, Gregory; Lewis, F. L.; Vamvoudakis, K. G.

2010-04-01

This paper first presents an overall view for dynamical decision-making in teams, both cooperative and competitive. Strategies for team decision problems, including optimal control, zero-sum 2-player games (H-infinity control) and so on are normally solved for off-line by solving associated matrix equations such as the Riccati equation. However, using that approach, players cannot change their objectives online in real time without calling for a completely new off-line solution for the new strategies. Therefore, in this paper we give a method for learning optimal team strategies online in real time as team dynamical play unfolds. In the linear quadratic regulator case, for instance, the method learns the Riccati equation solution online without ever solving the Riccati equation. This allows for truly dynamical team decisions where objective functions can change in real time and the system dynamics can be time-varying.

Similarity recognition of online data curves based on dynamic spatial time warping for the estimation of lithium-ion battery capacity

NASA Astrophysics Data System (ADS)

Tao, Laifa; Lu, Chen; Noktehdan, Azadeh

2015-10-01

Battery capacity estimation is a significant recent challenge given the complex physical and chemical processes that occur within batteries and the restrictions on the accessibility of capacity degradation data. In this study, we describe an approach called dynamic spatial time warping, which is used to determine the similarities of two arbitrary curves. Unlike classical dynamic time warping methods, this approach can maintain the invariance of curve similarity to the rotations and translations of curves, which is vital in curve similarity search. Moreover, it utilizes the online charging or discharging data that are easily collected and do not require special assumptions. The accuracy of this approach is verified using NASA battery datasets. Results suggest that the proposed approach provides a highly accurate means of estimating battery capacity at less time cost than traditional dynamic time warping methods do for different individuals and under various operating conditions.

Methods and analysis of realizing randomized grouping.

PubMed

Hu, Liang-Ping; Bao, Xiao-Lei; Wang, Qi

2011-07-01

Randomization is one of the four basic principles of research design. The meaning of randomization includes two aspects: one is to randomly select samples from the population, which is known as random sampling; the other is to randomly group all the samples, which is called randomized grouping. Randomized grouping can be subdivided into three categories: completely, stratified and dynamically randomized grouping. This article mainly introduces the steps of complete randomization, the definition of dynamic randomization and the realization of random sampling and grouping by SAS software.

Further steps in the modeling of behavioural crowd dynamics, good news for safe handling. Comment on "Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management" by Nicola Bellomo et al.

NASA Astrophysics Data System (ADS)

Knopoff, Damián A.

2016-09-01

The recent review paper [4] constitutes a valuable contribution on the understanding, modeling and simulation of crowd dynamics in extreme situations. It provides a very comprehensive revision about the complexity features of the system under consideration, scaling and the consequent justification of the used methods. In particular, macro and microscopic models have so far been used to model crowd dynamics [9] and authors appropriately explain that working at the mesoscale is a good choice to deal with the heterogeneous behaviour of walkers as well as with the difficulty of their deterministic identification. In this way, methods based on the kinetic theory and statistical dynamics are employed, more precisely the so-called kinetic theory for active particles [7]. This approach has successfully been applied in the modeling of several complex dynamics, with recent applications to learning [2,8] that constitutes the key to understand communication and is of great importance in social dynamics and behavioral sciences.

What is dynamics in quantum gravity?

NASA Astrophysics Data System (ADS)

Małkiewicz, Przemysław

2017-10-01

The appearance of the Hamiltonian constraint in the canonical formalism for general relativity reflects the lack of a fixed external time. The dynamics of general relativistic systems can be expressed with respect to an arbitrarily chosen internal degree of freedom, the so-called internal clock. We investigate the way in which the choice of internal clock determines the quantum dynamics and how much different quantum dynamics induced by different clocks are. We develop our method of comparison by extending the Hamilton-Jacobi theory of contact transformations to include a new type of transformation which transforms both the canonical variables and the internal clock. We employ our method to study the quantum dynamics of the Friedmann-Lemaitre model and obtain semiclassical corrections to the classical dynamics, which depend on the choice of internal clock. For a unique quantisation map we find the abundance of inequivalent semiclassical corrections induced by quantum dynamics taking place in different internal clocks. It follows that the concepts like minimal volume, maximal curvature and the number of quantum bounces, often used to describe quantum effects in cosmological models, depend on the choice of internal clock.

Dynamical sensitivity control of a single-spin quantum sensor.

PubMed

Lazariev, Andrii; Arroyo-Camejo, Silvia; Rahane, Ganesh; Kavatamane, Vinaya Kumar; Balasubramanian, Gopalakrishnan

2017-07-26

The Nitrogen-Vacancy (NV) defect in diamond is a unique quantum system that offers precision sensing of nanoscale physical quantities at room temperature beyond the current state-of-the-art. The benchmark parameters for nanoscale magnetometry applications are sensitivity, spectral resolution, and dynamic range. Under realistic conditions the NV sensors controlled by conventional sensing schemes suffer from limitations of these parameters. Here we experimentally show a new method called dynamical sensitivity control (DYSCO) that boost the benchmark parameters and thus extends the practical applicability of the NV spin for nanoscale sensing. In contrast to conventional dynamical decoupling schemes, where π pulse trains toggle the spin precession abruptly, the DYSCO method allows for a smooth, analog modulation of the quantum probe's sensitivity. Our method decouples frequency selectivity and spectral resolution unconstrained over the bandwidth (1.85 MHz-392 Hz in our experiments). Using DYSCO we demonstrate high-accuracy NV magnetometry without |2π| ambiguities, an enhancement of the dynamic range by a factor of 4 · 10 3 , and interrogation times exceeding 2 ms in off-the-shelf diamond. In a broader perspective the DYSCO method provides a handle on the inherent dynamics of quantum systems offering decisive advantages for NV centre based applications notably in quantum information and single molecule NMR/MRI.

Spectral gap optimization of order parameters for sampling complex molecular systems

PubMed Central

Tiwary, Pratyush; Berne, B. J.

2016-01-01

In modern-day simulations of many-body systems, much of the computational complexity is shifted to the identification of slowly changing molecular order parameters called collective variables (CVs) or reaction coordinates. A vast array of enhanced-sampling methods are based on the identification and biasing of these low-dimensional order parameters, whose fluctuations are important in driving rare events of interest. Here, we describe a new algorithm for finding optimal low-dimensional CVs for use in enhanced-sampling biasing methods like umbrella sampling, metadynamics, and related methods, when limited prior static and dynamic information is known about the system, and a much larger set of candidate CVs is specified. The algorithm involves estimating the best combination of these candidate CVs, as quantified by a maximum path entropy estimate of the spectral gap for dynamics viewed as a function of that CV. The algorithm is called spectral gap optimization of order parameters (SGOOP). Through multiple practical examples, we show how this postprocessing procedure can lead to optimization of CV and several orders of magnitude improvement in the convergence of the free energy calculated through metadynamics, essentially giving the ability to extract useful information even from unsuccessful metadynamics runs. PMID:26929365

Cooperative quantum-behaved particle swarm optimization with dynamic varying search areas and Lévy flight disturbance.

PubMed

Li, Desheng

2014-01-01

This paper proposes a novel variant of cooperative quantum-behaved particle swarm optimization (CQPSO) algorithm with two mechanisms to reduce the search space and avoid the stagnation, called CQPSO-DVSA-LFD. One mechanism is called Dynamic Varying Search Area (DVSA), which takes charge of limiting the ranges of particles' activity into a reduced area. On the other hand, in order to escape the local optima, Lévy flights are used to generate the stochastic disturbance in the movement of particles. To test the performance of CQPSO-DVSA-LFD, numerical experiments are conducted to compare the proposed algorithm with different variants of PSO. According to the experimental results, the proposed method performs better than other variants of PSO on both benchmark test functions and the combinatorial optimization issue, that is, the job-shop scheduling problem.

Electrostatics of proteins in dielectric solvent continua. II. Hamiltonian reaction field dynamics

NASA Astrophysics Data System (ADS)

Bauer, Sebastian; Tavan, Paul; Mathias, Gerald

2014-03-01

In Paper I of this work [S. Bauer, G. Mathias, and P. Tavan, J. Chem. Phys. 140, 104102 (2014)] we have presented a reaction field (RF) method, which accurately solves the Poisson equation for proteins embedded in dielectric solvent continua at a computational effort comparable to that of polarizable molecular mechanics (MM) force fields. Building upon these results, here we suggest a method for linearly scaling Hamiltonian RF/MM molecular dynamics (MD) simulations, which we call "Hamiltonian dielectric solvent" (HADES). First, we derive analytical expressions for the RF forces acting on the solute atoms. These forces properly account for all those conditions, which have to be self-consistently fulfilled by RF quantities introduced in Paper I. Next we provide details on the implementation, i.e., we show how our RF approach is combined with a fast multipole method and how the self-consistency iterations are accelerated by the use of the so-called direct inversion in the iterative subspace. Finally we demonstrate that the method and its implementation enable Hamiltonian, i.e., energy and momentum conserving HADES-MD, and compare in a sample application on Ac-Ala-NHMe the HADES-MD free energy landscape at 300 K with that obtained in Paper I by scanning of configurations and with one obtained from an explicit solvent simulation.

Exploring high dimensional free energy landscapes: Temperature accelerated sliced sampling

NASA Astrophysics Data System (ADS)

Awasthi, Shalini; Nair, Nisanth N.

2017-03-01

Biased sampling of collective variables is widely used to accelerate rare events in molecular simulations and to explore free energy surfaces. However, computational efficiency of these methods decreases with increasing number of collective variables, which severely limits the predictive power of the enhanced sampling approaches. Here we propose a method called Temperature Accelerated Sliced Sampling (TASS) that combines temperature accelerated molecular dynamics with umbrella sampling and metadynamics to sample the collective variable space in an efficient manner. The presented method can sample a large number of collective variables and is advantageous for controlled exploration of broad and unbound free energy basins. TASS is also shown to achieve quick free energy convergence and is practically usable with ab initio molecular dynamics techniques.

Dynamic variable selection in SNP genotype autocalling from APEX microarray data.

PubMed

Podder, Mohua; Welch, William J; Zamar, Ruben H; Tebbutt, Scott J

2006-11-30

Single nucleotide polymorphisms (SNPs) are DNA sequence variations, occurring when a single nucleotide--adenine (A), thymine (T), cytosine (C) or guanine (G)--is altered. Arguably, SNPs account for more than 90% of human genetic variation. Our laboratory has developed a highly redundant SNP genotyping assay consisting of multiple probes with signals from multiple channels for a single SNP, based on arrayed primer extension (APEX). This mini-sequencing method is a powerful combination of a highly parallel microarray with distinctive Sanger-based dideoxy terminator sequencing chemistry. Using this microarray platform, our current genotype calling system (known as SNP Chart) is capable of calling single SNP genotypes by manual inspection of the APEX data, which is time-consuming and exposed to user subjectivity bias. Using a set of 32 Coriell DNA samples plus three negative PCR controls as a training data set, we have developed a fully-automated genotyping algorithm based on simple linear discriminant analysis (LDA) using dynamic variable selection. The algorithm combines separate analyses based on the multiple probe sets to give a final posterior probability for each candidate genotype. We have tested our algorithm on a completely independent data set of 270 DNA samples, with validated genotypes, from patients admitted to the intensive care unit (ICU) of St. Paul's Hospital (plus one negative PCR control sample). Our method achieves a concordance rate of 98.9% with a 99.6% call rate for a set of 96 SNPs. By adjusting the threshold value for the final posterior probability of the called genotype, the call rate reduces to 94.9% with a higher concordance rate of 99.6%. We also reversed the two independent data sets in their training and testing roles, achieving a concordance rate up to 99.8%. The strength of this APEX chemistry-based platform is its unique redundancy having multiple probes for a single SNP. Our model-based genotype calling algorithm captures the redundancy in the system considering all the underlying probe features of a particular SNP, automatically down-weighting any 'bad data' corresponding to image artifacts on the microarray slide or failure of a specific chemistry. In this regard, our method is able to automatically select the probes which work well and reduce the effect of other so-called bad performing probes in a sample-specific manner, for any number of SNPs.

Molecular dynamics simulation of a needle-sphere binary mixture

NASA Astrophysics Data System (ADS)

Raghavan, Karthik

This paper investigates the dynamic behaviour of a hard needle-sphere binary system using a novel numerical technique called the Newton homotopy continuation (NHC) method. This mixture is representative of a polymer melt where both long chain molecules and monomers coexist. Since the intermolecular forces are generated from hard body interactions, the consequence of missed collisions or incorrect collision sequences have a significant bearing on the dynamic properties of the fluid. To overcome this problem, in earlier work NHC was chosen over traditional Newton-Raphson methods to solve the hard body dynamics of a needle fluid in random media composed of overlapping spheres. Furthermore, the simplicity of interactions and dynamics allows us to focus our research directly on the effects of particle shape and density on the transport behaviour of the mixture. These studies are also compared with earlier works that examined molecular chains in porous media primarily to understand the differences in molecular transport in the bulk versus porous systems.

A Method on Dynamic Path Planning for Robotic Manipulator Autonomous Obstacle Avoidance Based on an Improved RRT Algorithm.

PubMed

Wei, Kun; Ren, Bingyin

2018-02-13

In a future intelligent factory, a robotic manipulator must work efficiently and safely in a Human-Robot collaborative and dynamic unstructured environment. Autonomous path planning is the most important issue which must be resolved first in the process of improving robotic manipulator intelligence. Among the path-planning methods, the Rapidly Exploring Random Tree (RRT) algorithm based on random sampling has been widely applied in dynamic path planning for a high-dimensional robotic manipulator, especially in a complex environment because of its probability completeness, perfect expansion, and fast exploring speed over other planning methods. However, the existing RRT algorithm has a limitation in path planning for a robotic manipulator in a dynamic unstructured environment. Therefore, an autonomous obstacle avoidance dynamic path-planning method for a robotic manipulator based on an improved RRT algorithm, called Smoothly RRT (S-RRT), is proposed. This method that targets a directional node extends and can increase the sampling speed and efficiency of RRT dramatically. A path optimization strategy based on the maximum curvature constraint is presented to generate a smooth and curved continuous executable path for a robotic manipulator. Finally, the correctness, effectiveness, and practicability of the proposed method are demonstrated and validated via a MATLAB static simulation and a Robot Operating System (ROS) dynamic simulation environment as well as a real autonomous obstacle avoidance experiment in a dynamic unstructured environment for a robotic manipulator. The proposed method not only provides great practical engineering significance for a robotic manipulator's obstacle avoidance in an intelligent factory, but also theoretical reference value for other type of robots' path planning.

Motion synthesis and force distribution analysis for a biped robot.

PubMed

Trojnacki, Maciej T; Zielińska, Teresa

2011-01-01

In this paper, the method of generating biped robot motion using recorded human gait is presented. The recorded data were modified taking into account the velocity available for robot drives. Data includes only selected joint angles, therefore the missing values were obtained considering the dynamic postural stability of the robot, which means obtaining an adequate motion trajectory of the so-called Zero Moment Point (ZMT). Also, the method of determining the ground reaction forces' distribution during the biped robot's dynamic stable walk is described. The method was developed by the authors. Following the description of equations characterizing the dynamics of robot's motion, the values of the components of ground reaction forces were symbolically determined as well as the coordinates of the points of robot's feet contact with the ground. The theoretical considerations have been supported by computer simulation and animation of the robot's motion. This was done using Matlab/Simulink package and Simulink 3D Animation Toolbox, and it has proved the proposed method.

Distributed collaborative probabilistic design for turbine blade-tip radial running clearance using support vector machine of regression

NASA Astrophysics Data System (ADS)

Fei, Cheng-Wei; Bai, Guang-Chen

2014-12-01

To improve the computational precision and efficiency of probabilistic design for mechanical dynamic assembly like the blade-tip radial running clearance (BTRRC) of gas turbine, a distribution collaborative probabilistic design method-based support vector machine of regression (SR)(called as DCSRM) is proposed by integrating distribution collaborative response surface method and support vector machine regression model. The mathematical model of DCSRM is established and the probabilistic design idea of DCSRM is introduced. The dynamic assembly probabilistic design of aeroengine high-pressure turbine (HPT) BTRRC is accomplished to verify the proposed DCSRM. The analysis results reveal that the optimal static blade-tip clearance of HPT is gained for designing BTRRC, and improving the performance and reliability of aeroengine. The comparison of methods shows that the DCSRM has high computational accuracy and high computational efficiency in BTRRC probabilistic analysis. The present research offers an effective way for the reliability design of mechanical dynamic assembly and enriches mechanical reliability theory and method.

Transition Manifolds of Complex Metastable Systems: Theory and Data-Driven Computation of Effective Dynamics.

PubMed

Bittracher, Andreas; Koltai, Péter; Klus, Stefan; Banisch, Ralf; Dellnitz, Michael; Schütte, Christof

2018-01-01

We consider complex dynamical systems showing metastable behavior, but no local separation of fast and slow time scales. The article raises the question of whether such systems exhibit a low-dimensional manifold supporting its effective dynamics. For answering this question, we aim at finding nonlinear coordinates, called reaction coordinates, such that the projection of the dynamics onto these coordinates preserves the dominant time scales of the dynamics. We show that, based on a specific reducibility property, the existence of good low-dimensional reaction coordinates preserving the dominant time scales is guaranteed. Based on this theoretical framework, we develop and test a novel numerical approach for computing good reaction coordinates. The proposed algorithmic approach is fully local and thus not prone to the curse of dimension with respect to the state space of the dynamics. Hence, it is a promising method for data-based model reduction of complex dynamical systems such as molecular dynamics.

Generalized composite multiscale permutation entropy and Laplacian score based rolling bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Zheng, Jinde; Pan, Haiyang; Yang, Shubao; Cheng, Junsheng

2018-01-01

Multiscale permutation entropy (MPE) is a recently proposed nonlinear dynamic method for measuring the randomness and detecting the nonlinear dynamic change of time series and can be used effectively to extract the nonlinear dynamic fault feature from vibration signals of rolling bearing. To solve the drawback of coarse graining process in MPE, an improved MPE method called generalized composite multiscale permutation entropy (GCMPE) was proposed in this paper. Also the influence of parameters on GCMPE and its comparison with the MPE are studied by analyzing simulation data. GCMPE was applied to the fault feature extraction from vibration signal of rolling bearing and then based on the GCMPE, Laplacian score for feature selection and the Particle swarm optimization based support vector machine, a new fault diagnosis method for rolling bearing was put forward in this paper. Finally, the proposed method was applied to analyze the experimental data of rolling bearing. The analysis results show that the proposed method can effectively realize the fault diagnosis of rolling bearing and has a higher fault recognition rate than the existing methods.

Implementation of Advanced Inventory Management Functionality in Automated Dispensing Cabinets

PubMed Central

Webb, Aaron; Lund, Jim

2015-01-01

Background: Automated dispensing cabinets (ADCs) are an integral component of distribution models in pharmacy departments across the country. There are significant challenges to optimizing ADC inventory management while minimizing use of labor and capital resources. The role of enhanced inventory control functionality is not fully defined. Objective: The aim of this project is to improve ADC inventory management by leveraging dynamic inventory standards and a low inventory alert platform. Methods: Two interventional groups and 1 historical control were included in the study. Each intervention group consisted of 6 ADCs that tested enhanced inventory management functionality. Interventions included dynamic inventory standards and a low inventory alert messaging system. Following separate implementation of each platform, dynamic inventory and low inventory alert systems were applied concurrently to all 12 ADCs. Outcome measures included number and duration of daily stockouts, ADC inventory turns, and number of phone calls related to stockouts received by pharmacy staff. Results: Low inventory alerts reduced both the number and duration of stockouts. Dynamic inventory standards reduced the number of daily stockouts without changing the inventory turns and duration of stockouts. No change was observed in number of calls related to stockouts made to pharmacy staff. Conclusions: Low inventory alerts and dynamic inventory standards are feasible mechanisms to help optimize ADC inventory management while minimizing labor and capital resources. PMID:26448672

Representing climate, disturbance, and vegetation interactions in landscape models

Treesearch

Robert E. Keane; Donald McKenzie; Donald A. Falk; Erica A.H. Smithwick; Carol Miller; Lara-Karena B. Kellogg

2015-01-01

The prospect of rapidly changing climates over the next century calls for methods to predict their effects on myriad, interactive ecosystem processes. Spatially explicit models that simulate ecosystem dynamics at fine (plant, stand) to coarse (regional, global) scales are indispensable tools for meeting this challenge under a variety of possible futures. A special...

Teaching Complex Dynamic Systems to Young Students with StarLogo

ERIC Educational Resources Information Center

Klopfer, Eric; Yoon, Susan; Um, Tricia

2005-01-01

In this paper, we report on a program of study called Adventures in Modeling that challenges the traditional scientific method approach in science classrooms using StarLogo modeling software. Drawing upon previous successful efforts with older students, and the related work of other projects working with younger students, we explore: (a) What can…

Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification.

PubMed

Verschuuren, Marlies; De Vylder, Jonas; Catrysse, Hannes; Robijns, Joke; Philips, Wilfried; De Vos, Winnok H

2017-01-01

A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND), which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows.

Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification

PubMed Central

Verschuuren, Marlies; De Vylder, Jonas; Catrysse, Hannes; Robijns, Joke; Philips, Wilfried

2017-01-01

A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND), which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows. PMID:28125723

Automatic generation of efficient orderings of events for scheduling applications

NASA Technical Reports Server (NTRS)

Morris, Robert A.

1994-01-01

In scheduling a set of tasks, it is often not known with certainty how long a given event will take. We call this duration uncertainty. Duration uncertainty is a primary obstacle to the successful completion of a schedule. If a duration of one task is longer than expected, the remaining tasks are delayed. The delay may result in the abandonment of the schedule itself, a phenomenon known as schedule breakage. One response to schedule breakage is on-line, dynamic rescheduling. A more recent alternative is called proactive rescheduling. This method uses statistical data about the durations of events in order to anticipate the locations in the schedule where breakage is likely prior to the execution of the schedule. It generates alternative schedules at such sensitive points, which can be then applied by the scheduler at execution time, without the delay incurred by dynamic rescheduling. This paper proposes a technique for making proactive error management more effective. The technique is based on applying a similarity-based method of clustering to the problem of identifying similar events in a set of events.

Modeling the Multi-Body System Dynamics of a Flexible Solar Sail Spacecraft

NASA Technical Reports Server (NTRS)

Kim, Young; Stough, Robert; Whorton, Mark

2005-01-01

Solar sail propulsion systems enable a wide range of space missions that are not feasible with current propulsion technology. Hardware concepts and analytical methods have matured through ground development to the point that a flight validation mission is now realizable. Much attention has been given to modeling the structural dynamics of the constituent elements, but to date an integrated system level dynamics analysis has been lacking. Using a multi-body dynamics and control analysis tool called TREETOPS, the coupled dynamics of the sailcraft bus, sail membranes, flexible booms, and control system sensors and actuators of a representative solar sail spacecraft are investigated to assess system level dynamics and control issues. With this tool, scaling issues and parametric trade studies can be performed to study achievable performance, control authority requirements, and control/structure interaction assessments.

IBiSA_Tools: A Computational Toolkit for Ion-Binding State Analysis in Molecular Dynamics Trajectories of Ion Channels.

PubMed

Kasahara, Kota; Kinoshita, Kengo

2016-01-01

Ion conduction mechanisms of ion channels are a long-standing conundrum. Although the molecular dynamics (MD) method has been extensively used to simulate ion conduction dynamics at the atomic level, analysis and interpretation of MD results are not straightforward due to complexity of the dynamics. In our previous reports, we proposed an analytical method called ion-binding state analysis to scrutinize and summarize ion conduction mechanisms by taking advantage of a variety of analytical protocols, e.g., the complex network analysis, sequence alignment, and hierarchical clustering. This approach effectively revealed the ion conduction mechanisms and their dependence on the conditions, i.e., ion concentration and membrane voltage. Here, we present an easy-to-use computational toolkit for ion-binding state analysis, called IBiSA_tools. This toolkit consists of a C++ program and a series of Python and R scripts. From the trajectory file of MD simulations and a structure file, users can generate several images and statistics of ion conduction processes. A complex network named ion-binding state graph is generated in a standard graph format (graph modeling language; GML), which can be visualized by standard network analyzers such as Cytoscape. As a tutorial, a trajectory of a 50 ns MD simulation of the Kv1.2 channel is also distributed with the toolkit. Users can trace the entire process of ion-binding state analysis step by step. The novel method for analysis of ion conduction mechanisms of ion channels can be easily used by means of IBiSA_tools. This software is distributed under an open source license at the following URL: http://www.ritsumei.ac.jp/~ktkshr/ibisa_tools/.

Transition Manifolds of Complex Metastable Systems

NASA Astrophysics Data System (ADS)

Bittracher, Andreas; Koltai, Péter; Klus, Stefan; Banisch, Ralf; Dellnitz, Michael; Schütte, Christof

2018-04-01

We consider complex dynamical systems showing metastable behavior, but no local separation of fast and slow time scales. The article raises the question of whether such systems exhibit a low-dimensional manifold supporting its effective dynamics. For answering this question, we aim at finding nonlinear coordinates, called reaction coordinates, such that the projection of the dynamics onto these coordinates preserves the dominant time scales of the dynamics. We show that, based on a specific reducibility property, the existence of good low-dimensional reaction coordinates preserving the dominant time scales is guaranteed. Based on this theoretical framework, we develop and test a novel numerical approach for computing good reaction coordinates. The proposed algorithmic approach is fully local and thus not prone to the curse of dimension with respect to the state space of the dynamics. Hence, it is a promising method for data-based model reduction of complex dynamical systems such as molecular dynamics.

Calculated temperature dependence of elastic constants and phonon dispersion of hcp and bcc beryllium

NASA Astrophysics Data System (ADS)

Hahn, Steven; Arapan, Sergiu; Harmon, Bruce; Eriksson, Olle

2011-03-01

Conventional first principle methods for calculating lattice dynamics are unable to calculate high temperature thermophysical properties of materials containing modes that are entropically stabilized. In this presentation we use a relatively new approach called self-consistent ab initio lattice dynamics (SCAILD) to study the hcp to bcc transition (1530 K) in beryllium. The SCAILD method goes beyond the harmonic approximation to include phonon-phonon interactions and produces a temperature-dependent phonon dispersion. In the high temperature bcc structure, phonon-phonon interactions dynamically stabilize the N-point phonon. Fits to the calculated phonon dispersion were used to determine the temperature dependence of the elastic constants in the hcp and bcc phases. Work at the Ames Laboratory was supported by the Department of Energy-Basic Energy Sciences under Contract No. DE-AC02-07CH11358.

Cooperative Quantum-Behaved Particle Swarm Optimization with Dynamic Varying Search Areas and Lévy Flight Disturbance

PubMed Central

Li, Desheng

2014-01-01

This paper proposes a novel variant of cooperative quantum-behaved particle swarm optimization (CQPSO) algorithm with two mechanisms to reduce the search space and avoid the stagnation, called CQPSO-DVSA-LFD. One mechanism is called Dynamic Varying Search Area (DVSA), which takes charge of limiting the ranges of particles' activity into a reduced area. On the other hand, in order to escape the local optima, Lévy flights are used to generate the stochastic disturbance in the movement of particles. To test the performance of CQPSO-DVSA-LFD, numerical experiments are conducted to compare the proposed algorithm with different variants of PSO. According to the experimental results, the proposed method performs better than other variants of PSO on both benchmark test functions and the combinatorial optimization issue, that is, the job-shop scheduling problem. PMID:24851085

Role of Molecular Dynamics and Related Methods in Drug Discovery.

PubMed

De Vivo, Marco; Masetti, Matteo; Bottegoni, Giovanni; Cavalli, Andrea

2016-05-12

Molecular dynamics (MD) and related methods are close to becoming routine computational tools for drug discovery. Their main advantage is in explicitly treating structural flexibility and entropic effects. This allows a more accurate estimate of the thermodynamics and kinetics associated with drug-target recognition and binding, as better algorithms and hardware architectures increase their use. Here, we review the theoretical background of MD and enhanced sampling methods, focusing on free-energy perturbation, metadynamics, steered MD, and other methods most consistently used to study drug-target binding. We discuss unbiased MD simulations that nowadays allow the observation of unsupervised ligand-target binding, assessing how these approaches help optimizing target affinity and drug residence time toward improved drug efficacy. Further issues discussed include allosteric modulation and the role of water molecules in ligand binding and optimization. We conclude by calling for more prospective studies to attest to these methods' utility in discovering novel drug candidates.

Brain network dynamics characterization in epileptic seizures. Joint directed graph and pairwise synchronization measures

NASA Astrophysics Data System (ADS)

Rodrigues, A. C.; Machado, B. S.; Florence, G.; Hamad, A. P.; Sakamoto, A. C.; Fujita, A.; Baccalá, L. A.; Amaro, E.; Sameshima, K.

2014-12-01

Here we propose and evaluate a new approach to analyse multichannel mesial temporal lobe epilepsy EEG data from eight patients through complex network and synchronization theories. The method employs a Granger causality test to infer the directed connectivity graphs and a wavelet transform based phase synchronization measure whose characteristics allow studying dynamical transitions during epileptic seizures. We present a new combined graph measure that quantifies the level of network hub formation, called network hub out-degree, which closely reflects the level of synchronization observed during the ictus.

Counting motifs in dynamic networks.

PubMed

Mukherjee, Kingshuk; Hasan, Md Mahmudul; Boucher, Christina; Kahveci, Tamer

2018-04-11

A network motif is a sub-network that occurs frequently in a given network. Detection of such motifs is important since they uncover functions and local properties of the given biological network. Finding motifs is however a computationally challenging task as it requires solving the costly subgraph isomorphism problem. Moreover, the topology of biological networks change over time. These changing networks are called dynamic biological networks. As the network evolves, frequency of each motif in the network also changes. Computing the frequency of a given motif from scratch in a dynamic network as the network topology evolves is infeasible, particularly for large and fast evolving networks. In this article, we design and develop a scalable method for counting the number of motifs in a dynamic biological network. Our method incrementally updates the frequency of each motif as the underlying network's topology evolves. Our experiments demonstrate that our method can update the frequency of each motif in orders of magnitude faster than counting the motif embeddings every time the network changes. If the network evolves more frequently, the margin with which our method outperforms the existing static methods, increases. We evaluated our method extensively using synthetic and real datasets, and show that our method is highly accurate(≥ 96%) and that it can be scaled to large dense networks. The results on real data demonstrate the utility of our method in revealing interesting insights on the evolution of biological processes.

Gibbs Sampler-Based λ-Dynamics and Rao-Blackwell Estimator for Alchemical Free Energy Calculation.

PubMed

Ding, Xinqiang; Vilseck, Jonah Z; Hayes, Ryan L; Brooks, Charles L

2017-06-13

λ-dynamics is a generalized ensemble method for alchemical free energy calculations. In traditional λ-dynamics, the alchemical switch variable λ is treated as a continuous variable ranging from 0 to 1 and an empirical estimator is utilized to approximate the free energy. In the present article, we describe an alternative formulation of λ-dynamics that utilizes the Gibbs sampler framework, which we call Gibbs sampler-based λ-dynamics (GSLD). GSLD, like traditional λ-dynamics, can be readily extended to calculate free energy differences between multiple ligands in one simulation. We also introduce a new free energy estimator, the Rao-Blackwell estimator (RBE), for use in conjunction with GSLD. Compared with the current empirical estimator, the advantage of RBE is that RBE is an unbiased estimator and its variance is usually smaller than the current empirical estimator. We also show that the multistate Bennett acceptance ratio equation or the unbinned weighted histogram analysis method equation can be derived using the RBE. We illustrate the use and performance of this new free energy computational framework by application to a simple harmonic system as well as relevant calculations of small molecule relative free energies of solvation and binding to a protein receptor. Our findings demonstrate consistent and improved performance compared with conventional alchemical free energy methods.

The linguistic and interactional factors impacting recognition and dispatch in emergency calls for out-of-hospital cardiac arrest: a mixed-method linguistic analysis study protocol

PubMed Central

Riou, Marine; Ball, Stephen; Williams, Teresa A; Whiteside, Austin; O’Halloran, Kay L; Bray, Janet; Perkins, Gavin D; Cameron, Peter; Fatovich, Daniel M; Inoue, Madoka; Bailey, Paul; Brink, Deon; Smith, Karen; Della, Phillip; Finn, Judith

2017-01-01

Introduction Emergency telephone calls placed by bystanders are crucial to the recognition of out-of-hospital cardiac arrest (OHCA), fast ambulance dispatch and initiation of early basic life support. Clear and efficient communication between caller and call-taker is essential to this time-critical emergency, yet few studies have investigated the impact that linguistic factors may have on the nature of the interaction and the resulting trajectory of the call. This research aims to provide a better understanding of communication factors impacting on the accuracy and timeliness of ambulance dispatch. Methods and analysis A dataset of OHCA calls and their corresponding metadata will be analysed from an interdisciplinary perspective, combining linguistic analysis and health services research. The calls will be transcribed and coded for linguistic and interactional variables and then used to answer a series of research questions about the recognition of OHCA and the delivery of basic life-support instructions to bystanders. Linguistic analysis of calls will provide a deeper understanding of the interactional dynamics between caller and call-taker which may affect recognition and dispatch for OHCA. Findings from this research will translate into recommendations for modifications of the protocols for ambulance dispatch and provide directions for further research. Ethics and dissemination The study has been approved by the Curtin University Human Research Ethics Committee (HR128/2013) and the St John Ambulance Western Australia Research Advisory Group. Findings will be published in peer-reviewed journals and communicated to key audiences, including ambulance dispatch professionals. PMID:28694349

Hidden Markov induced Dynamic Bayesian Network for recovering time evolving gene regulatory networks

NASA Astrophysics Data System (ADS)

Zhu, Shijia; Wang, Yadong

2015-12-01

Dynamic Bayesian Networks (DBN) have been widely used to recover gene regulatory relationships from time-series data in computational systems biology. Its standard assumption is ‘stationarity’, and therefore, several research efforts have been recently proposed to relax this restriction. However, those methods suffer from three challenges: long running time, low accuracy and reliance on parameter settings. To address these problems, we propose a novel non-stationary DBN model by extending each hidden node of Hidden Markov Model into a DBN (called HMDBN), which properly handles the underlying time-evolving networks. Correspondingly, an improved structural EM algorithm is proposed to learn the HMDBN. It dramatically reduces searching space, thereby substantially improving computational efficiency. Additionally, we derived a novel generalized Bayesian Information Criterion under the non-stationary assumption (called BWBIC), which can help significantly improve the reconstruction accuracy and largely reduce over-fitting. Moreover, the re-estimation formulas for all parameters of our model are derived, enabling us to avoid reliance on parameter settings. Compared to the state-of-the-art methods, the experimental evaluation of our proposed method on both synthetic and real biological data demonstrates more stably high prediction accuracy and significantly improved computation efficiency, even with no prior knowledge and parameter settings.

Moles: Tool-Assisted Environment Isolation with Closures

NASA Astrophysics Data System (ADS)

de Halleux, Jonathan; Tillmann, Nikolai

Isolating test cases from environment dependencies is often desirable, as it increases test reliability and reduces test execution time. However, code that calls non-virtual methods or consumes sealed classes is often impossible to test in isolation. Moles is a new lightweight framework which addresses this problem. For any .NET method, Moles allows test-code to provide alternative implementations, given as .NET delegates, for which C# provides very concise syntax while capturing local variables in a closure object. Using code instrumentation, the Moles framework will redirect calls to provided delegates instead of the original methods. The Moles framework is designed to work together with the dynamic symbolic execution tool Pex to enable automated test generation. In a case study, testing code programmed against the Microsoft SharePoint Foundation API, we achieved full code coverage while running tests in isolation without an actual SharePoint server. The Moles framework integrates with .NET and Visual Studio.

Use of personalized Dynamic Treatment Regimes (DTRs) and Sequential Multiple Assignment Randomized Trials (SMARTs) in mental health studies

PubMed Central

Liu, Ying; ZENG, Donglin; WANG, Yuanjia

2014-01-01

Summary Dynamic treatment regimens (DTRs) are sequential decision rules tailored at each point where a clinical decision is made based on each patient’s time-varying characteristics and intermediate outcomes observed at earlier points in time. The complexity, patient heterogeneity, and chronicity of mental disorders call for learning optimal DTRs to dynamically adapt treatment to an individual’s response over time. The Sequential Multiple Assignment Randomized Trial (SMARTs) design allows for estimating causal effects of DTRs. Modern statistical tools have been developed to optimize DTRs based on personalized variables and intermediate outcomes using rich data collected from SMARTs; these statistical methods can also be used to recommend tailoring variables for designing future SMART studies. This paper introduces DTRs and SMARTs using two examples in mental health studies, discusses two machine learning methods for estimating optimal DTR from SMARTs data, and demonstrates the performance of the statistical methods using simulated data. PMID:25642116

Neural-Dynamic-Method-Based Dual-Arm CMG Scheme With Time-Varying Constraints Applied to Humanoid Robots.

PubMed

Zhang, Zhijun; Li, Zhijun; Zhang, Yunong; Luo, Yamei; Li, Yuanqing

2015-12-01

We propose a dual-arm cyclic-motion-generation (DACMG) scheme by a neural-dynamic method, which can remedy the joint-angle-drift phenomenon of a humanoid robot. In particular, according to a neural-dynamic design method, first, a cyclic-motion performance index is exploited and applied. This cyclic-motion performance index is then integrated into a quadratic programming (QP)-type scheme with time-varying constraints, called the time-varying-constrained DACMG (TVC-DACMG) scheme. The scheme includes the kinematic motion equations of two arms and the time-varying joint limits. The scheme can not only generate the cyclic motion of two arms for a humanoid robot but also control the arms to move to the desired position. In addition, the scheme considers the physical limit avoidance. To solve the QP problem, a recurrent neural network is presented and used to obtain the optimal solutions. Computer simulations and physical experiments demonstrate the effectiveness and the accuracy of such a TVC-DACMG scheme and the neural network solver.

Matrix product algorithm for stochastic dynamics on networks applied to nonequilibrium Glauber dynamics

NASA Astrophysics Data System (ADS)

Barthel, Thomas; De Bacco, Caterina; Franz, Silvio

2018-01-01

We introduce and apply an efficient method for the precise simulation of stochastic dynamical processes on locally treelike graphs. Networks with cycles are treated in the framework of the cavity method. Such models correspond, for example, to spin-glass systems, Boolean networks, neural networks, or other technological, biological, and social networks. Building upon ideas from quantum many-body theory, our approach is based on a matrix product approximation of the so-called edge messages—conditional probabilities of vertex variable trajectories. Computation costs and accuracy can be tuned by controlling the matrix dimensions of the matrix product edge messages (MPEM) in truncations. In contrast to Monte Carlo simulations, the algorithm has a better error scaling and works for both single instances as well as the thermodynamic limit. We employ it to examine prototypical nonequilibrium Glauber dynamics in the kinetic Ising model. Because of the absence of cancellation effects, observables with small expectation values can be evaluated accurately, allowing for the study of decay processes and temporal correlations.

Nonlinear dynamical systems for theory and research in ergonomics.

PubMed

Guastello, Stephen J

2017-02-01

Nonlinear dynamical systems (NDS) theory offers new constructs, methods and explanations for phenomena that have in turn produced new paradigms of thinking within several disciplines of the behavioural sciences. This article explores the recent developments of NDS as a paradigm in ergonomics. The exposition includes its basic axioms, the primary constructs from elementary dynamics and so-called complexity theory, an overview of its methods, and growing areas of application within ergonomics. The applications considered here include: psychophysics, iconic displays, control theory, cognitive workload and fatigue, occupational accidents, resilience of systems, team coordination and synchronisation in systems. Although these applications make use of different subsets of NDS constructs, several of them share the general principles of the complex adaptive system. Practitioner Summary: Nonlinear dynamical systems theory reframes problems in ergonomics that involve complex systems as they change over time. The leading applications to date include psychophysics, control theory, cognitive workload and fatigue, biomechanics, occupational accidents, resilience of systems, team coordination and synchronisation of system components.

A fractal approach to dynamic inference and distribution analysis

PubMed Central

van Rooij, Marieke M. J. W.; Nash, Bertha A.; Rajaraman, Srinivasan; Holden, John G.

2013-01-01

Event-distributions inform scientists about the variability and dispersion of repeated measurements. This dispersion can be understood from a complex systems perspective, and quantified in terms of fractal geometry. The key premise is that a distribution's shape reveals information about the governing dynamics of the system that gave rise to the distribution. Two categories of characteristic dynamics are distinguished: additive systems governed by component-dominant dynamics and multiplicative or interdependent systems governed by interaction-dominant dynamics. A logic by which systems governed by interaction-dominant dynamics are expected to yield mixtures of lognormal and inverse power-law samples is discussed. These mixtures are described by a so-called cocktail model of response times derived from human cognitive performances. The overarching goals of this article are twofold: First, to offer readers an introduction to this theoretical perspective and second, to offer an overview of the related statistical methods. PMID:23372552

Dynamic surface tension measurements of ionic surfactants using maximum bubble pressure tensiometry

NASA Astrophysics Data System (ADS)

Ortiz, Camilla U.; Moreno, Norman; Sharma, Vivek

Dynamic surface tension refers to the time dependent variation in surface tension, and is intimately linked with the rate of mass transfer of a surfactant from liquid sub-phase to the interface. The diffusion- or adsorption-limited kinetics of mass transfer to interfaces is said to impact the so-called foamability and the Gibbs-Marangoni elasticity of surfaces. Dynamic surface tension measurements carried out with conventional methods like pendant drop analysis, Wilhelmy plate, etc. are limited in their temporal resolution (>50 ms). In this study, we describe design and application of maximum bubble pressure tensiometry for the measurement of dynamic surface tension effects at extremely short (1-50 ms) timescales. Using experiments and theory, we discuss the overall adsorption kinetics of charged surfactants, paying special attention to the influence of added salt on dynamic surface tension.

Seeing real-space dynamics of liquid water through inelastic x-ray scattering.

PubMed

Iwashita, Takuya; Wu, Bin; Chen, Wei-Ren; Tsutsui, Satoshi; Baron, Alfred Q R; Egami, Takeshi

2017-12-01

Water is ubiquitous on earth, but we know little about the real-space motion of molecules in liquid water. We demonstrate that high-resolution inelastic x-ray scattering measurement over a wide range of momentum and energy transfer makes it possible to probe real-space, real-time dynamics of water molecules through the so-called Van Hove function. Water molecules are found to be strongly correlated in space and time with coupling between the first and second nearest-neighbor molecules. The local dynamic correlation of molecules observed here is crucial to a fundamental understanding of the origin of the physical properties of water, including viscosity. The results also suggest that the quantum-mechanical nature of hydrogen bonds could influence its dynamics. The approach used here offers a powerful experimental method for investigating real-space dynamics of liquids.

Building dynamic population graph for accurate correspondence detection.

PubMed

Du, Shaoyi; Guo, Yanrong; Sanroma, Gerard; Ni, Dong; Wu, Guorong; Shen, Dinggang

2015-12-01

In medical imaging studies, there is an increasing trend for discovering the intrinsic anatomical difference across individual subjects in a dataset, such as hand images for skeletal bone age estimation. Pair-wise matching is often used to detect correspondences between each individual subject and a pre-selected model image with manually-placed landmarks. However, the large anatomical variability across individual subjects can easily compromise such pair-wise matching step. In this paper, we present a new framework to simultaneously detect correspondences among a population of individual subjects, by propagating all manually-placed landmarks from a small set of model images through a dynamically constructed image graph. Specifically, we first establish graph links between models and individual subjects according to pair-wise shape similarity (called as forward step). Next, we detect correspondences for the individual subjects with direct links to any of model images, which is achieved by a new multi-model correspondence detection approach based on our recently-published sparse point matching method. To correct those inaccurate correspondences, we further apply an error detection mechanism to automatically detect wrong correspondences and then update the image graph accordingly (called as backward step). After that, all subject images with detected correspondences are included into the set of model images, and the above two steps of graph expansion and error correction are repeated until accurate correspondences for all subject images are established. Evaluations on real hand X-ray images demonstrate that our proposed method using a dynamic graph construction approach can achieve much higher accuracy and robustness, when compared with the state-of-the-art pair-wise correspondence detection methods as well as a similar method but using static population graph. Copyright © 2015 Elsevier B.V. All rights reserved.

Kernel-based least squares policy iteration for reinforcement learning.

PubMed

Xu, Xin; Hu, Dewen; Lu, Xicheng

2007-07-01

In this paper, we present a kernel-based least squares policy iteration (KLSPI) algorithm for reinforcement learning (RL) in large or continuous state spaces, which can be used to realize adaptive feedback control of uncertain dynamic systems. By using KLSPI, near-optimal control policies can be obtained without much a priori knowledge on dynamic models of control plants. In KLSPI, Mercer kernels are used in the policy evaluation of a policy iteration process, where a new kernel-based least squares temporal-difference algorithm called KLSTD-Q is proposed for efficient policy evaluation. To keep the sparsity and improve the generalization ability of KLSTD-Q solutions, a kernel sparsification procedure based on approximate linear dependency (ALD) is performed. Compared to the previous works on approximate RL methods, KLSPI makes two progresses to eliminate the main difficulties of existing results. One is the better convergence and (near) optimality guarantee by using the KLSTD-Q algorithm for policy evaluation with high precision. The other is the automatic feature selection using the ALD-based kernel sparsification. Therefore, the KLSPI algorithm provides a general RL method with generalization performance and convergence guarantee for large-scale Markov decision problems (MDPs). Experimental results on a typical RL task for a stochastic chain problem demonstrate that KLSPI can consistently achieve better learning efficiency and policy quality than the previous least squares policy iteration (LSPI) algorithm. Furthermore, the KLSPI method was also evaluated on two nonlinear feedback control problems, including a ship heading control problem and the swing up control of a double-link underactuated pendulum called acrobot. Simulation results illustrate that the proposed method can optimize controller performance using little a priori information of uncertain dynamic systems. It is also demonstrated that KLSPI can be applied to online learning control by incorporating an initial controller to ensure online performance.

A Nonlinear Dynamics-Based Estimator for Functional Electrical Stimulation: Preliminary Results From Lower-Leg Extension Experiments.

PubMed

Allen, Marcus; Zhong, Qiang; Kirsch, Nicholas; Dani, Ashwin; Clark, William W; Sharma, Nitin

2017-12-01

Miniature inertial measurement units (IMUs) are wearable sensors that measure limb segment or joint angles during dynamic movements. However, IMUs are generally prone to drift, external magnetic interference, and measurement noise. This paper presents a new class of nonlinear state estimation technique called state-dependent coefficient (SDC) estimation to accurately predict joint angles from IMU measurements. The SDC estimation method uses limb dynamics, instead of limb kinematics, to estimate the limb state. Importantly, the nonlinear limb dynamic model is formulated into state-dependent matrices that facilitate the estimator design without performing a Jacobian linearization. The estimation method is experimentally demonstrated to predict knee joint angle measurements during functional electrical stimulation of the quadriceps muscle. The nonlinear knee musculoskeletal model was identified through a series of experiments. The SDC estimator was then compared with an extended kalman filter (EKF), which uses a Jacobian linearization and a rotation matrix method, which uses a kinematic model instead of the dynamic model. Each estimator's performance was evaluated against the true value of the joint angle, which was measured through a rotary encoder. The experimental results showed that the SDC estimator, the rotation matrix method, and EKF had root mean square errors of 2.70°, 2.86°, and 4.42°, respectively. Our preliminary experimental results show the new estimator's advantage over the EKF method but a slight advantage over the rotation matrix method. However, the information from the dynamic model allows the SDC method to use only one IMU to measure the knee angle compared with the rotation matrix method that uses two IMUs to estimate the angle.

Molecular dynamics for dense matter

NASA Astrophysics Data System (ADS)

Maruyama, Toshiki; Watanabe, Gentaro; Chiba, Satoshi

2012-08-01

We review a molecular dynamics method for nucleon many-body systems called quantum molecular dynamics (QMD), and our studies using this method. These studies address the structure and the dynamics of nuclear matter relevant to neutron star crusts, supernova cores, and heavy-ion collisions. A key advantage of QMD is that we can study dynamical processes of nucleon many-body systems without any assumptions about the nuclear structure. First, we focus on the inhomogeneous structures of low-density nuclear matter consisting not only of spherical nuclei but also of nuclear "pasta", i.e., rod-like and slab-like nuclei. We show that pasta phases can appear in the ground and equilibrium states of nuclear matter without assuming nuclear shape. Next, we show our simulation of compression of nuclear matter which corresponds to the collapsing stage of supernovae. With the increase in density, a crystalline solid of spherical nuclei changes to a triangular lattice of rods by connecting neighboring nuclei. Finally, we discuss fragment formation in expanding nuclear matter. Our results suggest that a generally accepted scenario based on the liquid-gas phase transition is not plausible at lower temperatures.

Unveiling causal activity of complex networks

NASA Astrophysics Data System (ADS)

Williams-García, Rashid V.; Beggs, John M.; Ortiz, Gerardo

2017-07-01

We introduce a novel tool for analyzing complex network dynamics, allowing for cascades of causally-related events, which we call causal webs (c-webs), to be separated from other non-causally-related events. This tool shows that traditionally-conceived avalanches may contain mixtures of spatially-distinct but temporally-overlapping cascades of events, and dynamical disorder or noise. In contrast, c-webs separate these components, unveiling previously hidden features of the network and dynamics. We apply our method to mouse cortical data with resulting statistics which demonstrate for the first time that neuronal avalanches are not merely composed of causally-related events. The original version of this article was uploaded to the arXiv on March 17th, 2016 [1].

Mystic: Implementation of the Static Dynamic Optimal Control Algorithm for High-Fidelity, Low-Thrust Trajectory Design

NASA Technical Reports Server (NTRS)

Whiffen, Gregory J.

2006-01-01

Mystic software is designed to compute, analyze, and visualize optimal high-fidelity, low-thrust trajectories, The software can be used to analyze inter-planetary, planetocentric, and combination trajectories, Mystic also provides utilities to assist in the operation and navigation of low-thrust spacecraft. Mystic will be used to design and navigate the NASA's Dawn Discovery mission to orbit the two largest asteroids, The underlying optimization algorithm used in the Mystic software is called Static/Dynamic Optimal Control (SDC). SDC is a nonlinear optimal control method designed to optimize both 'static variables' (parameters) and dynamic variables (functions of time) simultaneously. SDC is a general nonlinear optimal control algorithm based on Bellman's principal.

Dynamic principle for ensemble control tools.

PubMed

Samoletov, A; Vasiev, B

2017-11-28

Dynamical equations describing physical systems in contact with a thermal bath are commonly extended by mathematical tools called "thermostats." These tools are designed for sampling ensembles in statistical mechanics. Here we propose a dynamic principle underlying a range of thermostats which is derived using fundamental laws of statistical physics and ensures invariance of the canonical measure. The principle covers both stochastic and deterministic thermostat schemes. Our method has a clear advantage over a range of proposed and widely used thermostat schemes that are based on formal mathematical reasoning. Following the derivation of the proposed principle, we show its generality and illustrate its applications including design of temperature control tools that differ from the Nosé-Hoover-Langevin scheme.

Dynamic Analysis of Large In-Space Deployable Membrane Antennas

NASA Technical Reports Server (NTRS)

Fang, Houfei; Yang, Bingen; Ding, Hongli; Hah, John; Quijano, Ubaldo; Huang, John

2006-01-01

This paper presents a vibration analysis of an eight-meter diameter membrane reflectarray antenna, which is composed of a thin membrane and a deployable frame. This analysis process has two main steps. In the first step, a two-variable-parameter (2-VP) membrane model is developed to determine the in-plane stress distribution of the membrane due to pre-tensioning, which eventually yields the differential stiffness of the membrane. In the second step, the obtained differential stiffness is incorporated in a dynamic equation governing the transverse vibration of the membrane-frame assembly. This dynamic equation is then solved by a semi-analytical method, called the Distributed Transfer Function Method (DTFM), which produces the natural frequencies and mode shapes of the antenna. The combination of the 2-VP model and the DTFM provides an accurate prediction of the in-plane stress distribution and modes of vibration for the antenna.

In vivo optical imaging and dynamic contrast methods for biomedical research

PubMed Central

Hillman, Elizabeth M. C.; Amoozegar, Cyrus B.; Wang, Tracy; McCaslin, Addason F. H.; Bouchard, Matthew B.; Mansfield, James; Levenson, Richard M.

2011-01-01

This paper provides an overview of optical imaging methods commonly applied to basic research applications. Optical imaging is well suited for non-clinical use, since it can exploit an enormous range of endogenous and exogenous forms of contrast that provide information about the structure and function of tissues ranging from single cells to entire organisms. An additional benefit of optical imaging that is often under-exploited is its ability to acquire data at high speeds; a feature that enables it to not only observe static distributions of contrast, but to probe and characterize dynamic events related to physiology, disease progression and acute interventions in real time. The benefits and limitations of in vivo optical imaging for biomedical research applications are described, followed by a perspective on future applications of optical imaging for basic research centred on a recently introduced real-time imaging technique called dynamic contrast-enhanced small animal molecular imaging (DyCE). PMID:22006910

Towards a self-consistent dynamical nuclear model

NASA Astrophysics Data System (ADS)

Roca-Maza, X.; Niu, Y. F.; Colò, G.; Bortignon, P. F.

2017-04-01

Density functional theory (DFT) is a powerful and accurate tool, exploited in nuclear physics to investigate the ground-state and some of the collective properties of nuclei along the whole nuclear chart. Models based on DFT are not, however, suitable for the description of single-particle dynamics in nuclei. Following the field theoretical approach by A Bohr and B R Mottelson to describe nuclear interactions between single-particle and vibrational degrees of freedom, we have taken important steps towards the building of a microscopic dynamic nuclear model. In connection with this, one important issue that needs to be better understood is the renormalization of the effective interaction in the particle-vibration approach. One possible way to renormalize the interaction is by the so-called subtraction method. In this contribution, we will implement the subtraction method in our model for the first time and study its consequences.

Dynamic ADMM for Real-Time Optimal Power Flow

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

Dall-Anese, Emiliano; Zhang, Yijian; Hong, Mingyi

This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearization of the AC power flow equations, and it leverages the so-called alternating direction method of multipliers (ADMM). The steps of the ADMM, however, are suitably modified to accommodate appropriate measurements from the distribution network and the DERs. With the aid of these measurements, the resultant algorithm can enforce given operational constraints in spite of inaccuracies in the representation ofmore » the AC power flows, and it avoids ubiquitous metering to gather the state of noncontrollable resources. Optimality and convergence of the proposed algorithm are established in terms of tracking of the solution of a convex surrogate of the AC optimal power flow problem.« less

Dynamic ADMM for Real-Time Optimal Power Flow: Preprint

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

Dall-Anese, Emiliano; Zhang, Yijian; Hong, Mingyi

This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearizations of the AC power flow equations, and it leverages the so-called alternating direction method of multipliers (ADMM). The steps of the ADMM, however, are suitably modified to accommodate appropriate measurements from the distribution network and the DERs. With the aid of these measurements, the resultant algorithm can enforce given operational constraints in spite of inaccuracies in the representation ofmore » the AC power flows, and it avoids ubiquitous metering to gather the state of non-controllable resources. Optimality and convergence of the propose algorithm are established in terms of tracking of the solution of a convex surrogate of the AC optimal power flow problem.« less

Spotting the difference in molecular dynamics simulations of biomolecules

NASA Astrophysics Data System (ADS)

Sakuraba, Shun; Kono, Hidetoshi

2016-08-01

Comparing two trajectories from molecular simulations conducted under different conditions is not a trivial task. In this study, we apply a method called Linear Discriminant Analysis with ITERative procedure (LDA-ITER) to compare two molecular simulation results by finding the appropriate projection vectors. Because LDA-ITER attempts to determine a projection such that the projections of the two trajectories do not overlap, the comparison does not suffer from a strong anisotropy, which is an issue in protein dynamics. LDA-ITER is applied to two test cases: the T4 lysozyme protein simulation with or without a point mutation and the allosteric protein PDZ2 domain of hPTP1E with or without a ligand. The projection determined by the method agrees with the experimental data and previous simulations. The proposed procedure, which complements existing methods, is a versatile analytical method that is specialized to find the "difference" between two trajectories.

Accelerating atomistic simulations through self-learning bond-boost hyperdynamics

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

Perez, Danny; Voter, Arthur F

2008-01-01

By altering the potential energy landscape on which molecular dynamics are carried out, the hyperdynamics method of Voter enables one to significantly accelerate the simulation state-to-state dynamics of physical systems. While very powerful, successful application of the method entails solving the subtle problem of the parametrization of the so-called bias potential. In this study, we first clarify the constraints that must be obeyed by the bias potential and demonstrate that fast sampling of the biased landscape is key to the obtention of proper kinetics. We then propose an approach by which the bond boost potential of Miron and Fichthorn canmore » be safely parametrized based on data acquired in the course of a molecular dynamics simulation. Finally, we introduce a procedure, the Self-Learning Bond Boost method, in which the parametrization is step efficiently carried out on-the-fly for each new state that is visited during the simulation by safely ramping up the strength of the bias potential up to its optimal value. The stability and accuracy of the method are demonstrated.« less

Coarse-grained molecular dynamics simulations for giant protein-DNA complexes

NASA Astrophysics Data System (ADS)

Takada, Shoji

Biomolecules are highly hierarchic and intrinsically flexible. Thus, computational modeling calls for multi-scale methodologies. We have been developing a coarse-grained biomolecular model where on-average 10-20 atoms are grouped into one coarse-grained (CG) particle. Interactions among CG particles are tuned based on atomistic interactions and the fluctuation matching algorithm. CG molecular dynamics methods enable us to simulate much longer time scale motions of much larger molecular systems than fully atomistic models. After broad sampling of structures with CG models, we can easily reconstruct atomistic models, from which one can continue conventional molecular dynamics simulations if desired. Here, we describe our CG modeling methodology for protein-DNA complexes, together with various biological applications, such as the DNA duplication initiation complex, model chromatins, and transcription factor dynamics on chromatin-like environment.

On the feasibility of a transient dynamic design analysis

NASA Astrophysics Data System (ADS)

Cunniff, Patrick F.; Pohland, Robert D.

1993-05-01

The Dynamic Design Analysis Method has been used for the past 30 years as part of the Navy's efforts to shock-harden heavy shipboard equipment. This method which has been validated several times employs normal mode theory and design shock values. This report examines the degree of success that may be achieved by using simple equipment-vehicle models that produce time history responses which are equivalent to the responses that would be achieved using spectral design values employed by the Dynamic Design Analysis Method. These transient models are constructed by attaching the equipment's modal oscillators to the vehicle which is composed of rigid masses and elastic springs. Two methods have been developed for constructing these transient models. Each method generates the parameters of the vehicles so as to approximate the required damaging effects, such that the transient model is excited by an idealized impulse applied to the vehicle mass to which the equipment modal oscillators are attached. The first method called the Direct Modeling Method, is limited to equipment with at most three-degrees of freedom and the vehicle consists of a single lumped mass and spring. The Optimization Modeling Method, which is based on the simplex method for optimization, has been used successfully with a variety of vehicle models and equipment sizes.

Patterns of call communication between group-housed zebra finches change during the breeding cycle.

PubMed

Gill, Lisa F; Goymann, Wolfgang; Ter Maat, Andries; Gahr, Manfred

2015-10-06

Vocal signals such as calls play a crucial role for survival and successful reproduction, especially in group-living animals. However, call interactions and call dynamics within groups remain largely unexplored because their relation to relevant contexts or life-history stages could not be studied with individual-level resolution. Using on-bird microphone transmitters, we recorded the vocalisations of individual zebra finches (Taeniopygia guttata) behaving freely in social groups, while females and males previously unknown to each other passed through different stages of the breeding cycle. As birds formed pairs and shifted their reproductive status, their call repertoire composition changed. The recordings revealed that calls occurred non-randomly in fine-tuned vocal interactions and decreased within groups while pair-specific patterns emerged. Call-type combinations of vocal interactions changed within pairs and were associated with successful egg-laying, highlighting a potential fitness relevance of calling dynamics in communication systems.

A spectral-spatial-dynamic hierarchical Bayesian (SSD-HB) model for estimating soybean yield

NASA Astrophysics Data System (ADS)

Kazama, Yoriko; Kujirai, Toshihiro

2014-10-01

A method called a "spectral-spatial-dynamic hierarchical-Bayesian (SSD-HB) model," which can deal with many parameters (such as spectral and weather information all together) by reducing the occurrence of multicollinearity, is proposed. Experiments conducted on soybean yields in Brazil fields with a RapidEye satellite image indicate that the proposed SSD-HB model can predict soybean yield with a higher degree of accuracy than other estimation methods commonly used in remote-sensing applications. In the case of the SSD-HB model, the mean absolute error between estimated yield of the target area and actual yield is 0.28 t/ha, compared to 0.34 t/ha when conventional PLS regression was applied, showing the potential effectiveness of the proposed model.

An historical survey of computational methods in optimal control.

NASA Technical Reports Server (NTRS)

Polak, E.

1973-01-01

Review of some of the salient theoretical developments in the specific area of optimal control algorithms. The first algorithms for optimal control were aimed at unconstrained problems and were derived by using first- and second-variation methods of the calculus of variations. These methods have subsequently been recognized as gradient, Newton-Raphson, or Gauss-Newton methods in function space. A much more recent addition to the arsenal of unconstrained optimal control algorithms are several variations of conjugate-gradient methods. At first, constrained optimal control problems could only be solved by exterior penalty function methods. Later algorithms specifically designed for constrained problems have appeared. Among these are methods for solving the unconstrained linear quadratic regulator problem, as well as certain constrained minimum-time and minimum-energy problems. Differential-dynamic programming was developed from dynamic programming considerations. The conditional-gradient method, the gradient-projection method, and a couple of feasible directions methods were obtained as extensions or adaptations of related algorithms for finite-dimensional problems. Finally, the so-called epsilon-methods combine the Ritz method with penalty function techniques.

1997 Technology Applications Report,

DTIC Science & Technology

1997-01-01

handle high -power loads at microwave radio frequencies , microwave vacuum tubes remain the chosen technology to amplify high power. Aria Microwave...structure called the active RF cavity amplifier (ARFCA). With this design , the amplifier handles high -power loads at radio and microwave frequencies ...developed this technology using BMDO-funded modeling methods designed to simulate the dynamics of large space-based structures. Because it increases

The stochastic control of the F-8C aircraft using the Multiple Model Adaptive Control (MMAC) method

NASA Technical Reports Server (NTRS)

Athans, M.; Dunn, K. P.; Greene, E. S.; Lee, W. H.; Sandel, N. R., Jr.

1975-01-01

The purpose of this paper is to summarize results obtained for the adaptive control of the F-8C aircraft using the so-called Multiple Model Adaptive Control method. The discussion includes the selection of the performance criteria for both the lateral and the longitudinal dynamics, the design of the Kalman filters for different flight conditions, the 'identification' aspects of the design using hypothesis testing ideas, and the performance of the closed loop adaptive system.

An introductory orientation to clinical pathology core and on-call responsibilities.

PubMed

Pappas, A A; Drew, M J; Flick, J; Fink, L; Fuller, G L; Hough, A J

1994-05-01

An introductory 4-week orientation for clinical pathology is described. There were 76 hours of lectures, 74 hours of conferences, and 68 hours of laboratories for a total of 221 hours. During the orientation, all calls handled by the residents were evaluated as to resolution, patient outcome, and interaction required. Eighty calls were received during the orientation from 57 technologists (71%), 16 physicians (20%), and seven nurses (9%). The calls originated concerning the following: blood banking, 37 (46%); hematology, 21 (27%); chemistry, 14 (18%); microbiology, five (6%); and administration, three (4%). Sixty percent of the calls were consultative and 40% were supervisory. Ninety-nine percent were handled appropriately by the residents. Patient outcome was moderately or significantly affected in 44% of all calls, divided between 67% of all consultative calls and 9% of all supervisory calls. Significant pathologist interaction was required in 49% of all calls, divided between 71% of the consultative calls and 16% of the supervisory calls. Using this integrated, dynamic system of resident instruction, on-call experience, and evaluation, residents quickly gain confidence in handling call, didactic clinical consultation, and patient management. The orientation and on-call system described provides for a relevant and dynamic system for resident education.

Dynamic-thresholding level set: a novel computer-aided volumetry method for liver tumors in hepatic CT images

NASA Astrophysics Data System (ADS)

Cai, Wenli; Yoshida, Hiroyuki; Harris, Gordon J.

2007-03-01

Measurement of the volume of focal liver tumors, called liver tumor volumetry, is indispensable for assessing the growth of tumors and for monitoring the response of tumors to oncology treatments. Traditional edge models, such as the maximum gradient and zero-crossing methods, often fail to detect the accurate boundary of a fuzzy object such as a liver tumor. As a result, the computerized volumetry based on these edge models tends to differ from manual segmentation results performed by physicians. In this study, we developed a novel computerized volumetry method for fuzzy objects, called dynamic-thresholding level set (DT level set). An optimal threshold value computed from a histogram tends to shift, relative to the theoretical threshold value obtained from a normal distribution model, toward a smaller region in the histogram. We thus designed a mobile shell structure, called a propagating shell, which is a thick region encompassing the level set front. The optimal threshold calculated from the histogram of the shell drives the level set front toward the boundary of a liver tumor. When the volume ratio between the object and the background in the shell approaches one, the optimal threshold value best fits the theoretical threshold value and the shell stops propagating. Application of the DT level set to 26 hepatic CT cases with 63 biopsy-confirmed hepatocellular carcinomas (HCCs) and metastases showed that the computer measured volumes were highly correlated with those of tumors measured manually by physicians. Our preliminary results showed that DT level set was effective and accurate in estimating the volumes of liver tumors detected in hepatic CT images.

System Dynamics in Distance Education and a Call to Develop a Standard Model

ERIC Educational Resources Information Center

Shaffer, Steven C.

2005-01-01

This paper describes systems dynamics, reviews the literature of uses of systems concepts in distance education (DE), presents a preliminary model, and ends in a call to researchers to contribute to the building of a standard model of DE. (Contains 4 figures.)

Towards a formal definition of static and dynamic electronic correlations.

PubMed

Benavides-Riveros, Carlos L; Lathiotakis, Nektarios N; Marques, Miguel A L

2017-05-24

Some of the most spectacular failures of density-functional and Hartree-Fock theories are related to an incorrect description of the so-called static electron correlation. Motivated by recent progress in the N-representability problem of the one-body density matrix for pure states, we propose a method to quantify the static contribution to the electronic correlation. By studying several molecular systems we show that our proposal correlates well with our intuition of static and dynamic electron correlation. Our results bring out the paramount importance of the occupancy of the highest occupied natural spin-orbital in such quantification.

Ground shake test of the UH-60A helicopter airframe and comparison with NASTRAN finite element model predictions

NASA Technical Reports Server (NTRS)

Howland, G. R.; Durno, J. A.; Twomey, W. J.

1990-01-01

Sikorsky Aircraft, together with the other major helicopter airframe manufacturers, is engaged in a study to improve the use of finite element analysis to predict the dynamic behavior of helicopter airframes, under a rotorcraft structural dynamics program called DAMVIBS (Design Analysis Methods for VIBrationS), sponsored by the NASA-Langley. The test plan and test results are presented for a shake test of the UH-60A BLACK HAWK helicopter. A comparison is also presented of test results with results obtained from analysis using a NASTRAN finite element model.

Using collective variables to drive molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Fiorin, Giacomo; Klein, Michael L.; Hénin, Jérôme

2013-12-01

A software framework is introduced that facilitates the application of biasing algorithms to collective variables of the type commonly employed to drive massively parallel molecular dynamics (MD) simulations. The modular framework that is presented enables one to combine existing collective variables into new ones, and combine any chosen collective variable with available biasing methods. The latter include the classic time-dependent biases referred to as steered MD and targeted MD, the temperature-accelerated MD algorithm, as well as the adaptive free-energy biases called metadynamics and adaptive biasing force. The present modular software is extensible, and portable between commonly used MD simulation engines.

Art of war hidden in Kolmogorov's equations.

PubMed

Lauren, Michael K; McIntosh, Gregory C; Perry, Nigel; Moffat, James

2007-03-01

Here we discuss how Kolmogorov's work on turbulence can be used as the inspiration for a new description of battlefield dynamics. The method presented may also represent a new way of describing self-organizing dynamical systems, in place of conventional differential equation approaches. The key finding is that the rate of attrition in a battle appears to be a function of the fractal dimension of the opposing forces. It is suggested that, this being the case, the fractal dimension could be used as a surrogate to represent the organizational efficiency of one force relative to another, commonly called Command and Control.

Robust Measurements of Phase Response Curves Realized via Multicycle Weighted Spike-Triggered Averages

NASA Astrophysics Data System (ADS)

Imai, Takashi; Ota, Kaiichiro; Aoyagi, Toshio

2017-02-01

Phase reduction has been extensively used to study rhythmic phenomena. As a result of phase reduction, the rhythm dynamics of a given system can be described using the phase response curve. Measuring this characteristic curve is an important step toward understanding a system's behavior. Recently, a basic idea for a new measurement method (called the multicycle weighted spike-triggered average method) was proposed. This paper confirms the validity of this method by providing an analytical proof and demonstrates its effectiveness in actual experimental systems by applying the method to an oscillating electric circuit. Some practical tips to use the method are also presented.

Seeing real-space dynamics of liquid water through inelastic x-ray scattering

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

Iwashita, Takuya; Wu, Bin; Chen, Wei-Ren

Water is ubiquitous on earth, but we know little about the real-space motion of molecules in liquid water. We demonstrate that high-resolution inelastic x-ray scattering measurement over a wide range of momentum and energy transfer makes it possible to probe real-space, real-time dynamics of water molecules through the so-called Van Hove function. Water molecules are found to be strongly correlated in space and time with coupling between the first and second nearest-neighbor molecules. The local dynamic correlation of molecules observed here is crucial to a fundamental understanding of the origin of the physical properties of water, including viscosity. The resultsmore » also suggest that the quantum-mechanical nature of hydrogen bonds could influence its dynamics. Finally, the approach used here offers a powerful experimental method for investigating real-space dynamics of liquids.« less

Seeing real-space dynamics of liquid water through inelastic x-ray scattering

DOE PAGES

Iwashita, Takuya; Wu, Bin; Chen, Wei-Ren; ...

2017-12-22

Water is ubiquitous on earth, but we know little about the real-space motion of molecules in liquid water. We demonstrate that high-resolution inelastic x-ray scattering measurement over a wide range of momentum and energy transfer makes it possible to probe real-space, real-time dynamics of water molecules through the so-called Van Hove function. Water molecules are found to be strongly correlated in space and time with coupling between the first and second nearest-neighbor molecules. The local dynamic correlation of molecules observed here is crucial to a fundamental understanding of the origin of the physical properties of water, including viscosity. The resultsmore » also suggest that the quantum-mechanical nature of hydrogen bonds could influence its dynamics. Finally, the approach used here offers a powerful experimental method for investigating real-space dynamics of liquids.« less

Reproducing the scaling laws for Slow and Fast ruptures

NASA Astrophysics Data System (ADS)

Romanet, Pierre; Bhat, Harsha; Madariaga, Raúl

2017-04-01

Modelling long term behaviour of large, natural fault systems, that are geometrically complex, is a challenging problem. This is why most of the research so far has concentrated on modelling the long term response of single planar fault system. To overcome this limitation, we appeal to a novel algorithm called the Fast Multipole Method which was developed in the context of modelling gravitational N-body problems. This method allows us to decrease the computational complexity of the calculation from O(N2) to O(N log N), N being the number of discretised elements on the fault. We then adapted this method to model the long term quasi-dynamic response of two faults, with step-over like geometry, that are governed by rate and state friction laws. We assume the faults have spatially uniform rate weakening friction. The results show that when stress interaction between faults is accounted, a complex spectrum of slip (including slow-slip events, dynamic ruptures and partial ruptures) emerges naturally. The simulated slow-slip and dynamic events follow the scaling law inferred by Ide et al. 2007 i. e. M ∝ T for slow-slip events and M ∝ T2 (in 2D) for dynamic events.

Dynamic MTF measurement

NASA Astrophysics Data System (ADS)

Bardoux, Alain; Gimenez, Thierry; Jamin, Nicolas; Seve, Frederic

2017-11-01

MTF (Modulation Transfer Frequency) of a detector is a key parameter for imagers. When image is not moving on the detector, MTF can be measured by some methods (knife edge, slanted slit,…). But with LEO satellites, image is moving on the surface of the detector, and MTF has to be measured in the same way: that is what we call "dynamic MTF". CNES (French Space Agency) has built a specific bench in order to measure dynamic MTF of detectors (CCD and CMOS), especially with component working in TDI (Time delay and integration) mode. The method is based on a moving edge, synchronized with the movement of charges inside the TDI detector. The moving part is a rotating cube, allowing a very stable movement of the image on the surface of the detector The main difficulties were: - stability of the rotating speed - synchronization between cube speed and charge transfer inside the detectors - synchronization between cube position and data acquisition. Different methods have been tested for the displacement of the knife edge: - geometrical displacement - electrical shift of the charge transfer clocks. Static MTF has been performed before dynamic measurements, in order to fix a reference measurement, Then dynamic MTF bench has been set up. The results, for a TDI CCD show a very good precision. So this bench is validated, and the dynamic MTF value of the TDI CCD is confirmed.

Applicability of transfer tensor method for open quantum system dynamics.

PubMed

Gelzinis, Andrius; Rybakovas, Edvardas; Valkunas, Leonas

2017-12-21

Accurate simulations of open quantum system dynamics is a long standing issue in the field of chemical physics. Exact methods exist, but are costly, while perturbative methods are limited in their applicability. Recently a new black-box type method, called transfer tensor method (TTM), was proposed [J. Cerrillo and J. Cao, Phys. Rev. Lett. 112, 110401 (2014)]. It allows one to accurately simulate long time dynamics with a numerical cost of solving a time-convolution master equation, provided many initial system evolution trajectories are obtained from some exact method beforehand. The possible time-savings thus strongly depend on the ratio of total versus initial evolution lengths. In this work, we investigate the parameter regimes where an application of TTM would be most beneficial in terms of computational time. We identify several promising parameter regimes. Although some of them correspond to cases when perturbative theories could be expected to perform well, we find that the accuracy of such approaches depends on system parameters in a more complex way than it is commonly thought. We propose that the TTM should be applied whenever system evolution is expected to be long and accuracy of perturbative methods cannot be ensured or in cases when the system under consideration does not correspond to any single perturbative regime.

Dynamical decoupling of unbounded Hamiltonians

NASA Astrophysics Data System (ADS)

Arenz, Christian; Burgarth, Daniel; Facchi, Paolo; Hillier, Robin

2018-03-01

We investigate the possibility to suppress interactions between a finite dimensional system and an infinite dimensional environment through a fast sequence of unitary kicks on the finite dimensional system. This method, called dynamical decoupling, is known to work for bounded interactions, but physical environments such as bosonic heat baths are usually modeled with unbounded interactions; hence, here, we initiate a systematic study of dynamical decoupling for unbounded operators. We develop a sufficient decoupling criterion for arbitrary Hamiltonians and a necessary decoupling criterion for semibounded Hamiltonians. We give examples for unbounded Hamiltonians where decoupling works and the limiting evolution as well as the convergence speed can be explicitly computed. We show that decoupling does not always work for unbounded interactions and we provide both physically and mathematically motivated examples.

Electron wavepacket dynamics in highly quasi-degenerate coupled electronic states: a theory for chemistry where the notion of adiabatic potential energy surface loses the sense.

PubMed

Yonehara, Takehiro; Takatsuka, Kazuo

2012-12-14

We develop a theory and the method of its application for chemical dynamics in systems, in which the adiabatic potential energy hyper-surfaces (PES) are densely quasi-degenerate to each other in a wide range of molecular geometry. Such adiabatic electronic states tend to couple each other through strong nonadiabatic interactions. Technically, therefore, it is often extremely hard to accurately single out the individual PES in those systems. Moreover, due to the mutual nonadiabatic couplings that may spread wide in space and due to the energy-time uncertainty relation, the notion of the isolated and well-defined potential energy surface should lose the sense. On the other hand, such dense electronic states should offer a very interesting molecular field in which chemical reactions to proceed in characteristic manners. However, to treat these systems, the standard theoretical framework of chemical reaction dynamics, which starts from the Born-Oppenheimer approximation and ends up with quantum nuclear wavepacket dynamics, is not very useful. We here explore this problem with our developed nonadiabatic electron wavepacket theory, which we call the phase-space averaging and natural branching (PSANB) method [T. Yonehara and K. Takatsuka, J. Chem. Phys. 129, 134109 (2008)], or branching-path representation, in which the packets are propagated in time along the non-Born-Oppenheimer branching paths. In this paper, after outlining the basic theory, we examine using a one-dimensional model how well the PSANB method works with such densely quasi-degenerate nonadiabatic systems. To do so, we compare the performance of PSANB with the full quantum mechanical results and those given by the fewest switches surface hopping (FSSH) method, which is known to be one of the most reliable and flexible methods to date. It turns out that the PSANB electron wavepacket approach actually yields very good results with far fewer initial sampling paths. Then we apply the electron wavepacket dynamics in path-branching representation and the so-called semiclassical Ehrenfest theory to a hydrogen molecule embedded in twelve membered boron cluster (B(12)) in excited states, which are densely quasi-degenerate due to the vacancy in 2p orbitals of boron atom [1s(2)2s(2)2p(1)]. Bond dissociation of the hydrogen molecule quickly takes place in the cluster and the resultant hydrogen atoms are squeezed out to the surface of the cluster. We further study collision dynamics between H(2) and B(12), which also gives interesting phenomena. The present study suggests an interesting functionality of the boron clusters.

Identification of a novel dynamic red blindness in human by event-related brain potentials.

PubMed

Zhang, Jiahua; Kong, Weijia; Yang, Zhongle

2010-12-01

Dynamic color is an important carrier that takes information in some special occupations. However, up to the present, there are no available and objective tests to evaluate dynamic color processing. To investigate the characteristics of dynamic color processing, we adopted two patterns of visual stimulus called "onset-offset" which reflected static color stimuli and "sustained moving" without abrupt mode which reflected dynamic color stimuli to evoke event-related brain potentials (ERPs) in primary color amblyopia patients (abnormal group) and subjects with normal color recognition ability (normal group). ERPs were recorded by Neuroscan system. The results showed that in the normal group, ERPs in response to the dynamic red stimulus showed frontal positive amplitudes with a latency of about 180 ms, a negative peak at about 240 ms and a peak latency of the late positive potential (LPP) in a time window between 290 and 580 ms. In the abnormal group, ERPs in response to the dynamic red stimulus were fully lost and characterized by vanished amplitudes between 0 and 800 ms. No significant difference was noted in ERPs in response to the dynamic green and blue stimulus between the two groups (P>0.05). ERPs of the two groups in response to the static red, green and blue stimulus were not much different, showing a transient negative peak at about 170 ms and a peak latency of LPP in a time window between 350 and 650 ms. Our results first revealed that some subjects who were not identified as color blindness under static color recognition could not completely apperceive a sort of dynamic red stimulus by ERPs, which was called "dynamic red blindness". Furthermore, these results also indicated that low-frequency ERPs induced by "sustained moving" may be a good and new method to test dynamic color perception competence.

From Weakly Chaotic Dynamics to Deterministic Subdiffusion via Copula Modeling

NASA Astrophysics Data System (ADS)

Nazé, Pierre

2018-03-01

Copula modeling consists in finding a probabilistic distribution, called copula, whereby its coupling with the marginal distributions of a set of random variables produces their joint distribution. The present work aims to use this technique to connect the statistical distributions of weakly chaotic dynamics and deterministic subdiffusion. More precisely, we decompose the jumps distribution of Geisel-Thomae map into a bivariate one and determine the marginal and copula distributions respectively by infinite ergodic theory and statistical inference techniques. We verify therefore that the characteristic tail distribution of subdiffusion is an extreme value copula coupling Mittag-Leffler distributions. We also present a method to calculate the exact copula and joint distributions in the case where weakly chaotic dynamics and deterministic subdiffusion statistical distributions are already known. Numerical simulations and consistency with the dynamical aspects of the map support our results.

Patterns of call communication between group-housed zebra finches change during the breeding cycle

PubMed Central

Gill, Lisa F; Goymann, Wolfgang; Ter Maat, Andries; Gahr, Manfred

2015-01-01

Vocal signals such as calls play a crucial role for survival and successful reproduction, especially in group-living animals. However, call interactions and call dynamics within groups remain largely unexplored because their relation to relevant contexts or life-history stages could not be studied with individual-level resolution. Using on-bird microphone transmitters, we recorded the vocalisations of individual zebra finches (Taeniopygia guttata) behaving freely in social groups, while females and males previously unknown to each other passed through different stages of the breeding cycle. As birds formed pairs and shifted their reproductive status, their call repertoire composition changed. The recordings revealed that calls occurred non-randomly in fine-tuned vocal interactions and decreased within groups while pair-specific patterns emerged. Call-type combinations of vocal interactions changed within pairs and were associated with successful egg-laying, highlighting a potential fitness relevance of calling dynamics in communication systems. DOI: http://dx.doi.org/10.7554/eLife.07770.001 PMID:26441403

Synthesized airfoil data method for prediction of dynamic stall and unsteady airloads

NASA Technical Reports Server (NTRS)

Gangwani, S. T.

1983-01-01

A detailed analysis of dynamic stall experiments has led to a set of relatively compact analytical expressions, called synthesized unsteady airfoil data, which accurately describe in the time-domain the unsteady aerodynamic characteristics of stalled airfoils. An analytical research program was conducted to expand and improve this synthesized unsteady airfoil data method using additional available sets of unsteady airfoil data. The primary objectives were to reduce these data to synthesized form for use in rotor airload prediction analyses and to generalize the results. Unsteady drag data were synthesized which provided the basis for successful expansion of the formulation to include computation of the unsteady pressure drag of airfoils and rotor blades. Also, an improved prediction model for airfoil flow reattachment was incorporated in the method. Application of this improved unsteady aerodynamics model has resulted in an improved correlation between analytic predictions and measured full scale helicopter blade loads and stress data.

New Methods for the Analysis of Heartbeat Behavior in Risk Stratification

PubMed Central

Glass, Leon; Lerma, Claudia; Shrier, Alvin

2011-01-01

Developing better methods for risk stratification for tachyarrhythmic sudden cardiac remains a major challenge for physicians and scientists. Since the transition from sinus rhythm to ventricular tachycardia/fibrillation happens by different mechanisms in different people, it is unrealistic to think that a single measure will be adequate to provide a good index for risk stratification. We analyze the dynamical properties of ventricular premature complexes over 24 h in an effort to understand the underlying mechanisms of ventricular arrhythmias and to better understand the arrhythmias that occur in individual patients. Two dimensional density plots, called heartprints, correlate characteristic features of the dynamics of premature ventricular complexes and the sinus rate. Heartprints show distinctive characteristics in individual patients. Based on a better understanding of the natures of transitions from sinus rhythm to sudden cardiac and the mechanisms of arrhythmia prior to cardiac arrest, it should be possible to develop better methods for risk stratification. PMID:22144963

The 3D dynamics of the Cosserat rod as applied to continuum robotics

NASA Astrophysics Data System (ADS)

Jones, Charles Rees

2011-12-01

In the effort to simulate the biologically inspired continuum robot's dynamic capabilities, researchers have been faced with the daunting task of simulating---in real-time---the complete three dimensional dynamics of the "beam-like" structure which includes the three "stiff" degrees-of-freedom transverse and dilational shear. Therefore, researchers have traditionally limited the difficulty of the problem with simplifying assumptions. This study, however, puts forward a solution which makes no simplifying assumptions and trades off only the real-time requirement of the desired solution. The solution is a Finite Difference Time Domain method employing an explicit single step method with cheap right hands sides. The cheap right hand sides are the result of a rather ingenious formulation of the classical beam called the Cosserat rod by, first, the Cosserat brothers and, later, Stuart S. Antman which results in five nonlinear but uncoupled equations that require only multiplication and addition. The method is therefore suitable for hardware implementation thus moving the real-time requirement from a software solution to a hardware solution.

Discrete Event-based Performance Prediction for Temperature Accelerated Dynamics

NASA Astrophysics Data System (ADS)

Junghans, Christoph; Mniszewski, Susan; Voter, Arthur; Perez, Danny; Eidenbenz, Stephan

2014-03-01

We present an example of a new class of tools that we call application simulators, parameterized fast-running proxies of large-scale scientific applications using parallel discrete event simulation (PDES). We demonstrate our approach with a TADSim application simulator that models the Temperature Accelerated Dynamics (TAD) method, which is an algorithmically complex member of the Accelerated Molecular Dynamics (AMD) family. The essence of the TAD application is captured without the computational expense and resource usage of the full code. We use TADSim to quickly characterize the runtime performance and algorithmic behavior for the otherwise long-running simulation code. We further extend TADSim to model algorithm extensions to standard TAD, such as speculative spawning of the compute-bound stages of the algorithm, and predict performance improvements without having to implement such a method. Focused parameter scans have allowed us to study algorithm parameter choices over far more scenarios than would be possible with the actual simulation. This has led to interesting performance-related insights into the TAD algorithm behavior and suggested extensions to the TAD method.

Dynamical analysis of an orbiting three-rigid-body system

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

Pagnozzi, Daniele, E-mail: daniele.pagnozzi@strath.ac.uk, E-mail: james.biggs@strath.ac.uk; Biggs, James D., E-mail: daniele.pagnozzi@strath.ac.uk, E-mail: james.biggs@strath.ac.uk

2014-12-10

The development of multi-joint-spacecraft mission concepts calls for a deeper understanding of their nonlinear dynamics to inform and enhance system design. This paper presents a study of a three-finite-shape rigid-body system under the action of an ideal central gravitational field. The aim of this paper is to gain an insight into the natural dynamics of this system. The Hamiltonian dynamics is derived and used to identify relative attitude equilibria of the system with respect to the orbital reference frame. Then a numerical investigation of the behaviour far from the equilibria is provided using tools from modern dynamical systems theory suchmore » as energy methods, phase portraits and Poincarè maps. Results reveal a complex structure of the dynamics as well as the existence of connections between some of the equilibria. Stable equilibrium configurations appear to be surrounded by very narrow regions of regular and quasi-regular motions. Trajectories evolve on chaotic motions in the rest of the domain.« less

Infant perception of the rotating Kanizsa square.

PubMed

Yoshino, Daisuke; Idesawa, Masanori; Kanazawa, So; Yamaguchi, Masami K

2010-04-01

This study examined the perception of the rotating Kanizsa square by using a fixed-trial familiarization method. If the Kanizsa square is rotated across the pacmen, adult observers perceive not only a rotating illusory square, but also an illusory expansion/contraction motion of this square. The phenomenon is called a "rotational dynamic illusion". In experiments 1 and 2, we investigated whether infants perceived the rotational dynamic illusion, finding that 3-8-month-old infants perceived the rotational dynamic illusion as a simple rotation of the Kanizsa square. In experiment 3, we investigated whether infants perceived the rotational dynamic illusion as a rotation of the Kanizsa square or as a deformation of shape, finding that 3-4-month-old infants did perceive the rotational dynamic illusion as a rotation of the Kanizsa square. Our results show that while 3-8-month-old infants perceive the rotating Kanizsa square, however, it is difficult for the infants to extract expansion/contraction motion from the rotational dynamic illusion. Copyright 2010 Elsevier Inc. All rights reserved.

MulVAL Extensions for Dynamic Asset Protection

DTIC Science & Technology

2006-04-01

called Skybox Security and an AI-based project called CycSecure were identified as interesting and relatively mature projects, which deserve closer...dynamic asset protection solution. A critique of the Skybox Security and CycSecure solutions, with respect to the requirements of dynamic asset...particulièrement, un produit du commerce appelé Skybox Security et un projet d’IA appelé CycSecure ont été désignés comme étant des projets

Integrating Dynamic Data and Sensors with Semantic 3D City Models in the Context of Smart Cities

NASA Astrophysics Data System (ADS)

Chaturvedi, K.; Kolbe, T. H.

2016-10-01

Smart cities provide effective integration of human, physical and digital systems operating in the built environment. The advancements in city and landscape models, sensor web technologies, and simulation methods play a significant role in city analyses and improving quality of life of citizens and governance of cities. Semantic 3D city models can provide substantial benefits and can become a central information backbone for smart city infrastructures. However, current generation semantic 3D city models are static in nature and do not support dynamic properties and sensor observations. In this paper, we propose a new concept called Dynamizer allowing to represent highly dynamic data and providing a method for injecting dynamic variations of city object properties into the static representation. The approach also provides direct capability to model complex patterns based on statistics and general rules and also, real-time sensor observations. The concept is implemented as an Application Domain Extension for the CityGML standard. However, it could also be applied to other GML-based application schemas including the European INSPIRE data themes and national standards for topography and cadasters like the British Ordnance Survey Mastermap or the German cadaster standard ALKIS.

Complete characterization of the stability of cluster synchronization in complex dynamical networks.

PubMed

Sorrentino, Francesco; Pecora, Louis M; Hagerstrom, Aaron M; Murphy, Thomas E; Roy, Rajarshi

2016-04-01

Synchronization is an important and prevalent phenomenon in natural and engineered systems. In many dynamical networks, the coupling is balanced or adjusted to admit global synchronization, a condition called Laplacian coupling. Many networks exhibit incomplete synchronization, where two or more clusters of synchronization persist, and computational group theory has recently proved to be valuable in discovering these cluster states based on the topology of the network. In the important case of Laplacian coupling, additional synchronization patterns can exist that would not be predicted from the group theory analysis alone. Understanding how and when clusters form, merge, and persist is essential for understanding collective dynamics, synchronization, and failure mechanisms of complex networks such as electric power grids, distributed control networks, and autonomous swarming vehicles. We describe a method to find and analyze all of the possible cluster synchronization patterns in a Laplacian-coupled network, by applying methods of computational group theory to dynamically equivalent networks. We present a general technique to evaluate the stability of each of the dynamically valid cluster synchronization patterns. Our results are validated in an optoelectronic experiment on a five-node network that confirms the synchronization patterns predicted by the theory.

Mapping Conformational Dynamics of Proteins Using Torsional Dynamics Simulations

PubMed Central

Gangupomu, Vamshi K.; Wagner, Jeffrey R.; Park, In-Hee; Jain, Abhinandan; Vaidehi, Nagarajan

2013-01-01

All-atom molecular dynamics simulations are widely used to study the flexibility of protein conformations. However, enhanced sampling techniques are required for simulating protein dynamics that occur on the millisecond timescale. In this work, we show that torsional molecular dynamics simulations enhance protein conformational sampling by performing conformational search in the low-frequency torsional degrees of freedom. In this article, we use our recently developed torsional-dynamics method called Generalized Newton-Euler Inverse Mass Operator (GNEIMO) to study the conformational dynamics of four proteins. We investigate the use of the GNEIMO method in simulations of the conformationally flexible proteins fasciculin and calmodulin, as well as the less flexible crambin and bovine pancreatic trypsin inhibitor. For the latter two proteins, the GNEIMO simulations with an implicit-solvent model reproduced the average protein structural fluctuations and sample conformations similar to those from Cartesian simulations with explicit solvent. The application of GNEIMO with replica exchange to the study of fasciculin conformational dynamics produced sampling of two of this protein’s experimentally established conformational substates. Conformational transition of calmodulin from the Ca2+-bound to the Ca2+-free conformation occurred readily with GNEIMO simulations. Moreover, the GNEIMO method generated an ensemble of conformations that satisfy about half of both short- and long-range interresidue distances obtained from NMR structures of holo to apo transitions in calmodulin. Although unconstrained all-atom Cartesian simulations have failed to sample transitions between the substates of fasciculin and calmodulin, GNEIMO simulations show the transitions in both systems. The relatively short simulation times required to capture these long-timescale conformational dynamics indicate that GNEIMO is a promising molecular-dynamics technique for studying domain motion in proteins. PMID:23663843

Mapping conformational dynamics of proteins using torsional dynamics simulations.

PubMed

Gangupomu, Vamshi K; Wagner, Jeffrey R; Park, In-Hee; Jain, Abhinandan; Vaidehi, Nagarajan

2013-05-07

All-atom molecular dynamics simulations are widely used to study the flexibility of protein conformations. However, enhanced sampling techniques are required for simulating protein dynamics that occur on the millisecond timescale. In this work, we show that torsional molecular dynamics simulations enhance protein conformational sampling by performing conformational search in the low-frequency torsional degrees of freedom. In this article, we use our recently developed torsional-dynamics method called Generalized Newton-Euler Inverse Mass Operator (GNEIMO) to study the conformational dynamics of four proteins. We investigate the use of the GNEIMO method in simulations of the conformationally flexible proteins fasciculin and calmodulin, as well as the less flexible crambin and bovine pancreatic trypsin inhibitor. For the latter two proteins, the GNEIMO simulations with an implicit-solvent model reproduced the average protein structural fluctuations and sample conformations similar to those from Cartesian simulations with explicit solvent. The application of GNEIMO with replica exchange to the study of fasciculin conformational dynamics produced sampling of two of this protein's experimentally established conformational substates. Conformational transition of calmodulin from the Ca(2+)-bound to the Ca(2+)-free conformation occurred readily with GNEIMO simulations. Moreover, the GNEIMO method generated an ensemble of conformations that satisfy about half of both short- and long-range interresidue distances obtained from NMR structures of holo to apo transitions in calmodulin. Although unconstrained all-atom Cartesian simulations have failed to sample transitions between the substates of fasciculin and calmodulin, GNEIMO simulations show the transitions in both systems. The relatively short simulation times required to capture these long-timescale conformational dynamics indicate that GNEIMO is a promising molecular-dynamics technique for studying domain motion in proteins. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Three-dimensional sensing methodology combining stereo vision and phase-measuring profilometry based on dynamic programming

NASA Astrophysics Data System (ADS)

Lee, Hyunki; Kim, Min Young; Moon, Jeon Il

2017-12-01

Phase measuring profilometry and moiré methodology have been widely applied to the three-dimensional shape measurement of target objects, because of their high measuring speed and accuracy. However, these methods suffer from inherent limitations called a correspondence problem, or 2π-ambiguity problem. Although a kind of sensing method to combine well-known stereo vision and phase measuring profilometry (PMP) technique simultaneously has been developed to overcome this problem, it still requires definite improvement for sensing speed and measurement accuracy. We propose a dynamic programming-based stereo PMP method to acquire more reliable depth information and in a relatively small time period. The proposed method efficiently fuses information from two stereo sensors in terms of phase and intensity simultaneously based on a newly defined cost function of dynamic programming. In addition, the important parameters are analyzed at the view point of the 2π-ambiguity problem and measurement accuracy. To analyze the influence of important hardware and software parameters related to the measurement performance and to verify its efficiency, accuracy, and sensing speed, a series of experimental tests were performed with various objects and sensor configurations.

Variable horizon in a peridynamic medium

DOE PAGES

Silling, Stewart A.; Littlewood, David J.; Seleson, Pablo

2015-12-10

Here, a notion of material homogeneity is proposed for peridynamic bodies with variable horizon but constant bulk properties. A relation is derived that scales the force state according to the position-dependent horizon while keeping the bulk properties unchanged. Using this scaling relation, if the horizon depends on position, artifacts called ghost forces may arise in a body under a homogeneous deformation. These artifacts depend on the second derivative of the horizon and can be reduced by employing a modified equilibrium equation using a new quantity called the partial stress. Bodies with piecewise constant horizon can be modeled without ghost forcesmore » by using a simpler technique called a splice. As a limiting case of zero horizon, both the partial stress and splice techniques can be used to achieve local-nonlocal coupling. Computational examples, including dynamic fracture in a one-dimensional model with local-nonlocal coupling, illustrate the methods.« less

Comparison between different adsorption-desorption kinetics schemes in two dimensional lattice gas

NASA Astrophysics Data System (ADS)

Huespe, V. J.; Belardinelli, R. E.; Pereyra, V. D.; Manzi, S. J.

2017-12-01

Monte Carlo simulation is used to study the adsorption-desorption kinetics in the framework of the kinetic lattice-gas model. Three schemes of the so-called hard dynamics and five schemes of the so called soft dynamics were used for this purpose. It is observed that for the hard dynamic schemes, the equilibrium and non-equilibrium observable, such as adsorption isotherms, sticking coefficients, and thermal desorption spectra, have a normal or physical sustainable behavior. While for the soft dynamics schemes, with the exception of the transition state theory, the equilibrium and non-equilibrium observables have several problems.

Dual-Schemata Model

NASA Astrophysics Data System (ADS)

Taniguchi, Tadahiro; Sawaragi, Tetsuo

In this paper, a new machine-learning method, called Dual-Schemata model, is presented. Dual-Schemata model is a kind of self-organizational machine learning methods for an autonomous robot interacting with an unknown dynamical environment. This is based on Piaget's Schema model, that is a classical psychological model to explain memory and cognitive development of human beings. Our Dual-Schemata model is developed as a computational model of Piaget's Schema model, especially focusing on sensori-motor developing period. This developmental process is characterized by a couple of two mutually-interacting dynamics; one is a dynamics formed by assimilation and accommodation, and the other dynamics is formed by equilibration and differentiation. By these dynamics schema system enables an agent to act well in a real world. This schema's differentiation process corresponds to a symbol formation process occurring within an autonomous agent when it interacts with an unknown, dynamically changing environment. Experiment results obtained from an autonomous facial robot in which our model is embedded are presented; an autonomous facial robot becomes able to chase a ball moving in various ways without any rewards nor teaching signals from outside. Moreover, emergence of concepts on the target movements within a robot is shown and discussed in terms of fuzzy logics on set-subset inclusive relationships.

Low-rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging

PubMed Central

Ravishankar, Saiprasad; Moore, Brian E.; Nadakuditi, Raj Rao; Fessler, Jeffrey A.

2017-01-01

Sparsity-based approaches have been popular in many applications in image processing and imaging. Compressed sensing exploits the sparsity of images in a transform domain or dictionary to improve image recovery from undersampled measurements. In the context of inverse problems in dynamic imaging, recent research has demonstrated the promise of sparsity and low-rank techniques. For example, the patches of the underlying data are modeled as sparse in an adaptive dictionary domain, and the resulting image and dictionary estimation from undersampled measurements is called dictionary-blind compressed sensing, or the dynamic image sequence is modeled as a sum of low-rank and sparse (in some transform domain) components (L+S model) that are estimated from limited measurements. In this work, we investigate a data-adaptive extension of the L+S model, dubbed LASSI, where the temporal image sequence is decomposed into a low-rank component and a component whose spatiotemporal (3D) patches are sparse in some adaptive dictionary domain. We investigate various formulations and efficient methods for jointly estimating the underlying dynamic signal components and the spatiotemporal dictionary from limited measurements. We also obtain efficient sparsity penalized dictionary-blind compressed sensing methods as special cases of our LASSI approaches. Our numerical experiments demonstrate the promising performance of LASSI schemes for dynamic magnetic resonance image reconstruction from limited k-t space data compared to recent methods such as k-t SLR and L+S, and compared to the proposed dictionary-blind compressed sensing method. PMID:28092528

An Inquiry: Effectiveness of the Complex Empirical Mode Decomposition Method, the Hilbert-Huang Transform, and the Fast-Fourier Transform for Analysis of Dynamic Objects

DTIC Science & Technology

2012-03-01

graphical user interface (GUI) called ALPINE© [18]. Then, it will be converted into a 10 MAT-file that can be read into MATLAB®. At this point...breathing [3]. For comparison purposes, Balocchi et al. recorded the respiratory signal simultaneously with the tachogram (or EKG ) signal. As previously...primary authors, worked to create his own code for implementing the method proposed by Rilling et al. Through reading the BEMD paper and proceeding to

The analysis of dynamic characteristics and wind-induced displacement response of space Beam String Structure

NASA Astrophysics Data System (ADS)

Chen, Yong Jian; Feng, Zhen Fa; Qi, Ai; Huang, Ying

2018-06-01

The Beam String Structure structural system, also called BSS, has the advantages of lighter dead weight and greater flexibility. The wind load is the main design control factor. The dynamic characteristics and wind-induced displacement response of BSS are studied by the finite element method. The roof structure of the stadium roof of the Fuzhou Olympic Sports Center is the engineering background. 1)The numerical model was built by ANSYS, by shape finding, determine the initial stress state of structural members such as external cables; 2)From the analysis of dynamic characteristics, the main mode of vibration is the vibration of cables; 3)The wind speed spectrum of MATLAB generation structure is obtained by AR method, the structural response of the structure under static wind load and fluctuating wind load is calculated. From the analysis result, considering the equivalent static wind load of BSS , the design of adverse wind is not safe, and the fluctuating wind load should be taken into account.

Enhanced High Performance Power Compensation Methodology by IPFC Using PIGBT-IDVR

PubMed Central

Arumugom, Subramanian; Rajaram, Marimuthu

2015-01-01

Currently, power systems are involuntarily controlled without high speed control and are frequently initiated, therefore resulting in a slow process when compared with static electronic devices. Among various power interruptions in power supply systems, voltage dips play a central role in causing disruption. The dynamic voltage restorer (DVR) is a process based on voltage control that compensates for line transients in the distributed system. To overcome these issues and to achieve a higher speed, a new methodology called the Parallel IGBT-Based Interline Dynamic Voltage Restorer (PIGBT-IDVR) method has been proposed, which mainly spotlights the dynamic processing of energy reloads in common dc-linked energy storage with less adaptive transition. The interline power flow controller (IPFC) scheme has been employed to manage the power transmission between the lines and the restorer method for controlling the reactive power in the individual lines. By employing the proposed methodology, the failure of a distributed system has been avoided and provides better performance than the existing methodologies. PMID:26613101

Modeling local extinction in turbulent combustion using an embedding method

NASA Astrophysics Data System (ADS)

Knaus, Robert; Pantano, Carlos

2012-11-01

Local regions of extinction in diffusion flames, called ``flame holes,'' can reduce the efficiency of combustion and increase the production of certain pollutants. At sufficiently high speeds, a flame may also be lifted from the rim of the burner to a downstream location that may be stable. These two phenomena share a common underlying mechanism of propagation related to edge-flame dynamics where chemistry and fluid mechanics are equally important. We present a formulation that describes the formation, propagation, and growth of flames holes on the stoichiometric surface using edge flame dynamics. The boundary separating the flame from the quenched region is modeled using a progress variable defined on the moving stoichiometric surface that is embedded in the three-dimensional space using an extension algorithm. This Cartesian problem is solved using a high-order finite-volume WENO method extended to this nonconservative problem. This algorithm can track the dynamics of flame holes in a turbulent reacting-shear layer and model flame liftoff without requiring full chemistry calculations.

Modelling malaria control by introduction of larvivorous fish.

PubMed

Lou, Yijun; Zhao, Xiao-Qiang

2011-10-01

Malaria creates serious health and economic problems which call for integrated management strategies to disrupt interactions among mosquitoes, the parasite and humans. In order to reduce the intensity of malaria transmission, malaria vector control may be implemented to protect individuals against infective mosquito bites. As a sustainable larval control method, the use of larvivorous fish is promoted in some circumstances. To evaluate the potential impacts of this biological control measure on malaria transmission, we propose and investigate a mathematical model describing the linked dynamics between the host-vector interaction and the predator-prey interaction. The model, which consists of five ordinary differential equations, is rigorously analysed via theories and methods of dynamical systems. We derive four biologically plausible and insightful quantities (reproduction numbers) that completely determine the community composition. Our results suggest that the introduction of larvivorous fish can, in principle, have important consequences for malaria dynamics, but also indicate that this would require strong predators on larval mosquitoes. Integrated strategies of malaria control are analysed to demonstrate the biological application of our developed theory.

Dynamic modeling approaches to characterize the functioning of health systems: A systematic review of the literature.

PubMed

Chang, Angela Y; Ogbuoji, Osondu; Atun, Rifat; Verguet, Stéphane

2017-12-01

Universal Health Coverage (UHC) is one of the targets for the United Nations Sustainable Development Goal 3. The impetus for UHC has led to an increased demand for time-sensitive tools to enhance our knowledge of how health systems function and to evaluate impact of system interventions. We define the field of "health system modeling" (HSM) as an area of research where dynamic mathematical models can be designed in order to describe, predict, and quantitatively capture the functioning of health systems. HSM can be used to explore the dynamic relationships among different system components, including organizational design, financing and other resources (such as investments in resources and supply chain management systems) - what we call "inputs" - on access, coverage, and quality of care - what we call "outputs", toward improved health system "outcomes", namely increased levels and fairer distributions of population health and financial risk protection. We undertook a systematic review to identify the existing approaches used in HSM. We identified "systems thinking" - a conceptual and qualitative description of the critical interactions within a health system - as an important underlying precursor to HSM, and collated a critical collection of such articles. We then reviewed and categorized articles from two schools of thoughts: "system dynamics" (SD)" and "susceptible-infected-recovered-plus" (SIR+). SD emphasizes the notion of accumulations of stocks in the system, inflows and outflows, and causal feedback structure to predict intended and unintended consequences of policy interventions. The SIR + models link a typical disease transmission model with another that captures certain aspects of the system that impact the outcomes of the main model. These existing methods provide critical insights in informing the design of HSM, and provide a departure point to extend this research agenda. We highlight the opportunity to advance modeling methods to further understand the dynamics between health system inputs and outputs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatio-Temporal Dynamics of Field Cricket Calling Behaviour: Implications for Female Mate Search and Mate Choice.

PubMed

Nandi, Diptarup; Balakrishnan, Rohini

2016-01-01

Amount of calling activity (calling effort) is a strong determinant of male mating success in species such as orthopterans and anurans that use acoustic communication in the context of mating behaviour. While many studies in crickets have investigated the determinants of calling effort, patterns of variability in male calling effort in natural choruses remain largely unexplored. Within-individual variability in calling activity across multiple nights of calling can influence female mate search and mate choice strategies. Moreover, calling site fidelity across multiple nights of calling can also affect the female mate sampling strategy. We therefore investigated the spatio-temporal dynamics of acoustic signaling behaviour in a wild population of the field cricket species Plebeiogryllus guttiventris. We first studied the consistency of calling activity by quantifying variation in male calling effort across multiple nights of calling using repeatability analysis. Callers were inconsistent in their calling effort across nights and did not optimize nightly calling effort to increase their total number of nights spent calling. We also estimated calling site fidelity of males across multiple nights by quantifying movement of callers. Callers frequently changed their calling sites across calling nights with substantial displacement but without any significant directionality. Finally, we investigated trade-offs between within-night calling effort and energetically expensive calling song features such as call intensity and chirp rate. Calling effort was not correlated with any of the calling song features, suggesting that energetically expensive song features do not constrain male calling effort. The two key features of signaling behaviour, calling effort and call intensity, which determine the duration and spatial coverage of the sexual signal, are therefore uncorrelated and function independently.

Acousto-Optical Method of Encoding and Visualization of Underwater Space

DTIC Science & Technology

2014-01-27

neurons which are mathematically described as coupled nonlinear oscillators that are slightly unstable. They have a property called ’ Self - Referential ... self - regulating process which is represented by Equation (5) in the ensuing description. [0083] The input/output circuitry 64 outputs signals that...other words, self -correcting dynamics of the Na and Ca ions in the membranes are closely related to the sensing and the flopping of motion actuators

On the suppression of vaccination dissent.

PubMed

Martin, Brian

2015-02-01

Dissenters from the dominant views about vaccination sometimes are subject to adverse actions, including abusive comment, threats, formal complaints,censorship, and de registration, a phenomenon that can be called suppression of dissent. Three types of cases are examined: scientists and physicians; a high-profile researcher; and a citizen campaigner. Comparing the methods used in these different types of cases provides a preliminary framework for understanding the dynamics of suppression in terms of vulnerabilities.

A comparison of the lattice discrete particle method to the finite-element method and the K&C material model for simulating the static and dynamic response of concrete.

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

Smith, Jovanca J.; Bishop, Joseph E.

2013-11-01

This report summarizes the work performed by the graduate student Jovanca Smith during a summer internship in the summer of 2012 with the aid of mentor Joe Bishop. The projects were a two-part endeavor that focused on the use of the numerical model called the Lattice Discrete Particle Model (LDPM). The LDPM is a discrete meso-scale model currently used at Northwestern University and the ERDC to model the heterogeneous quasi-brittle material, concrete. In the first part of the project, LDPM was compared to the Karagozian and Case Concrete Model (K&C) used in Presto, an explicit dynamics finite-element code, developed atmore » Sandia National Laboratories. In order to make this comparison, a series of quasi-static numerical experiments were performed, namely unconfined uniaxial compression tests on four varied cube specimen sizes, three-point bending notched experiments on three proportional specimen sizes, and six triaxial compression tests on a cylindrical specimen. The second part of this project focused on the application of LDPM to simulate projectile perforation on an ultra high performance concrete called CORTUF. This application illustrates the strengths of LDPM over traditional continuum models.« less

Dynamical modeling and analysis of large cellular regulatory networks

NASA Astrophysics Data System (ADS)

Bérenguier, D.; Chaouiya, C.; Monteiro, P. T.; Naldi, A.; Remy, E.; Thieffry, D.; Tichit, L.

2013-06-01

The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

CoMoDo: identifying dynamic protein domains based on covariances of motion.

PubMed

Wieninger, Silke A; Ullmann, G Matthias

2015-06-09

Most large proteins are built of several domains, compact units which enable functional protein motions. Different domain assignment approaches exist, which mostly rely on concepts of stability, folding, and evolution. We describe the automatic assignment method CoMoDo, which identifies domains based on protein dynamics. Covariances of atomic fluctuations, here calculated by an Elastic Network Model, are used to group residues into domains of different hierarchical levels. The so-called dynamic domains facilitate the study of functional protein motions involved in biological processes like ligand binding and signal transduction. By applying CoMoDo to a large number of proteins, we demonstrate that dynamic domains exhibit features absent in the commonly assigned structural domains, which can deliver insight into the interactions between domains and between subunits of multimeric proteins. CoMoDo is distributed as free open source software at www.bisb.uni-bayreuth.de/CoMoDo.html .

Deconvolution of subcellular protrusion heterogeneity and the underlying actin regulator dynamics from live cell imaging.

PubMed

Wang, Chuangqi; Choi, Hee June; Kim, Sung-Jin; Desai, Aesha; Lee, Namgyu; Kim, Dohoon; Bae, Yongho; Lee, Kwonmoo

2018-04-27

Cell protrusion is morphodynamically heterogeneous at the subcellular level. However, the mechanism of cell protrusion has been understood based on the ensemble average of actin regulator dynamics. Here, we establish a computational framework called HACKS (deconvolution of heterogeneous activity in coordination of cytoskeleton at the subcellular level) to deconvolve the subcellular heterogeneity of lamellipodial protrusion from live cell imaging. HACKS identifies distinct subcellular protrusion phenotypes based on machine-learning algorithms and reveals their underlying actin regulator dynamics at the leading edge. Using our method, we discover "accelerating protrusion", which is driven by the temporally ordered coordination of Arp2/3 and VASP activities. We validate our finding by pharmacological perturbations and further identify the fine regulation of Arp2/3 and VASP recruitment associated with accelerating protrusion. Our study suggests HACKS can identify specific subcellular protrusion phenotypes susceptible to pharmacological perturbation and reveal how actin regulator dynamics are changed by the perturbation.

Solutions of burnt-bridge models for molecular motor transport.

PubMed

Morozov, Alexander Yu; Pronina, Ekaterina; Kolomeisky, Anatoly B; Artyomov, Maxim N

2007-03-01

Transport of molecular motors, stimulated by interactions with specific links between consecutive binding sites (called "bridges"), is investigated theoretically by analyzing discrete-state stochastic "burnt-bridge" models. When an unbiased diffusing particle crosses the bridge, the link can be destroyed ("burned") with a probability p , creating a biased directed motion for the particle. It is shown that for probability of burning p=1 the system can be mapped into a one-dimensional single-particle hopping model along the periodic infinite lattice that allows one to calculate exactly all dynamic properties. For the general case of p<1 a theoretical method is developed and dynamic properties are computed explicitly. Discrete-time and continuous-time dynamics for periodic distribution of bridges and different burning dynamics are analyzed and compared. Analytical predictions are supported by extensive Monte Carlo computer simulations. Theoretical results are applied for analysis of the experiments on collagenase motor proteins.

Thermal elastohydrodynamic lubrication of spur gears

NASA Technical Reports Server (NTRS)

Wang, K. L.; Cheng, H. S.

1980-01-01

An analysis and computer program called TELSGE were developed to predict the variations of dynamic load, surface temperature, and lubricant film thickness along the contacting path during the engagement of a pair of involute spur gears. The analysis of dynamic load includes the effect of gear inertia, the effect of load sharing of adjacent teeth, and the effect of variable tooth stiffness which are obtained by a finite-element method. Results obtained from TELSGE for the dynamic load distributions along the contacting path for various speeds of a pair of test gears show patterns similar to that observed experimentally. Effects of damping ratio, contact ratio, tip relief, and tooth error on the dynamic load were examined. In addition, two dimensionless charts are included for predicting the maximum equilibrium surface temperature, which can be used to estimate directly the lubricant film thickness based on well established EHD analysis.

Exact Solutions of Burnt-Bridge Models for Molecular Motor Transport

NASA Astrophysics Data System (ADS)

Morozov, Alexander; Pronina, Ekaterina; Kolomeisky, Anatoly; Artyomov, Maxim

2007-03-01

Transport of molecular motors, stimulated by interactions with specific links between consecutive binding sites (called ``bridges''), is investigated theoretically by analyzing discrete-state stochastic ``burnt-bridge'' models. When an unbiased diffusing particle crosses the bridge, the link can be destroyed (``burned'') with a probability p, creating a biased directed motion for the particle. It is shown that for probability of burning p=1 the system can be mapped into one-dimensional single-particle hopping model along the periodic infinite lattice that allows one to calculate exactly all dynamic properties. For general case of p<1 a new theoretical method is developed, and dynamic properties are computed explicitly. Discrete-time and continuous-time dynamics, periodic and random distribution of bridges and different burning dynamics are analyzed and compared. Theoretical predictions are supported by extensive Monte Carlo computer simulations. Theoretical results are applied for analysis of the experiments on collagenase motor proteins.

Solutions of burnt-bridge models for molecular motor transport

NASA Astrophysics Data System (ADS)

Morozov, Alexander Yu.; Pronina, Ekaterina; Kolomeisky, Anatoly B.; Artyomov, Maxim N.

2007-03-01

Transport of molecular motors, stimulated by interactions with specific links between consecutive binding sites (called “bridges”), is investigated theoretically by analyzing discrete-state stochastic “burnt-bridge” models. When an unbiased diffusing particle crosses the bridge, the link can be destroyed (“burned”) with a probability p , creating a biased directed motion for the particle. It is shown that for probability of burning p=1 the system can be mapped into a one-dimensional single-particle hopping model along the periodic infinite lattice that allows one to calculate exactly all dynamic properties. For the general case of p<1 a theoretical method is developed and dynamic properties are computed explicitly. Discrete-time and continuous-time dynamics for periodic distribution of bridges and different burning dynamics are analyzed and compared. Analytical predictions are supported by extensive Monte Carlo computer simulations. Theoretical results are applied for analysis of the experiments on collagenase motor proteins.

PBxplore: a tool to analyze local protein structure and deformability with Protein Blocks

PubMed Central

Craveur, Pierrick; Joseph, Agnel Praveen; Jallu, Vincent

2017-01-01

This paper describes the development and application of a suite of tools, called PBxplore, to analyze the dynamics and deformability of protein structures using Protein Blocks (PBs). Proteins are highly dynamic macromolecules, and a classical way to analyze their inherent flexibility is to perform molecular dynamics simulations. The advantage of using small structural prototypes such as PBs is to give a good approximation of the local structure of the protein backbone. More importantly, by reducing the conformational complexity of protein structures, PBs allow analysis of local protein deformability which cannot be done with other methods and had been used efficiently in different applications. PBxplore is able to process large amounts of data such as those produced by molecular dynamics simulations. It produces frequencies, entropy and information logo outputs as text and graphics. PBxplore is available at https://github.com/pierrepo/PBxplore and is released under the open-source MIT license. PMID:29177113

Degree-Pruning Dynamic Programming Approaches to Central Time Series Minimizing Dynamic Time Warping Distance.

PubMed

Sun, Tao; Liu, Hongbo; Yu, Hong; Chen, C L Philip

2016-06-28

The central time series crystallizes the common patterns of the set it represents. In this paper, we propose a global constrained degree-pruning dynamic programming (g(dp)²) approach to obtain the central time series through minimizing dynamic time warping (DTW) distance between two time series. The DTW matching path theory with global constraints is proved theoretically for our degree-pruning strategy, which is helpful to reduce the time complexity and computational cost. Our approach can achieve the optimal solution between two time series. An approximate method to the central time series of multiple time series [called as m_g(dp)²] is presented based on DTW barycenter averaging and our g(dp)² approach by considering hierarchically merging strategy. As illustrated by the experimental results, our approaches provide better within-group sum of squares and robustness than other relevant algorithms.

dynGENIE3: dynamical GENIE3 for the inference of gene networks from time series expression data.

PubMed

Huynh-Thu, Vân Anh; Geurts, Pierre

2018-02-21

The elucidation of gene regulatory networks is one of the major challenges of systems biology. Measurements about genes that are exploited by network inference methods are typically available either in the form of steady-state expression vectors or time series expression data. In our previous work, we proposed the GENIE3 method that exploits variable importance scores derived from Random forests to identify the regulators of each target gene. This method provided state-of-the-art performance on several benchmark datasets, but it could however not specifically be applied to time series expression data. We propose here an adaptation of the GENIE3 method, called dynamical GENIE3 (dynGENIE3), for handling both time series and steady-state expression data. The proposed method is evaluated extensively on the artificial DREAM4 benchmarks and on three real time series expression datasets. Although dynGENIE3 does not systematically yield the best performance on each and every network, it is competitive with diverse methods from the literature, while preserving the main advantages of GENIE3 in terms of scalability.

Efficiency optimization of a fast Poisson solver in beam dynamics simulation

NASA Astrophysics Data System (ADS)

Zheng, Dawei; Pöplau, Gisela; van Rienen, Ursula

2016-01-01

Calculating the solution of Poisson's equation relating to space charge force is still the major time consumption in beam dynamics simulations and calls for further improvement. In this paper, we summarize a classical fast Poisson solver in beam dynamics simulations: the integrated Green's function method. We introduce three optimization steps of the classical Poisson solver routine: using the reduced integrated Green's function instead of the integrated Green's function; using the discrete cosine transform instead of discrete Fourier transform for the Green's function; using a novel fast convolution routine instead of an explicitly zero-padded convolution. The new Poisson solver routine preserves the advantages of fast computation and high accuracy. This provides a fast routine for high performance calculation of the space charge effect in accelerators.

Shortcuts to adiabaticity. Suppression of pair production in driven Dirac dynamics

DOE PAGES

Deffner, Sebastian

2015-12-21

By achieving effectively adiabatic dynamics in finite time, we have found that it is our ubiquitous goal in virtually all areas of modern physics. So-called shortcuts to adiabaticity refer to a set of methods and techniques that allow us to produce in a short time the same final state that would result from an adiabatic, infinitely slow process. In this paper we generalize one of these methods—the fast-forward technique—to driven Dirac dynamics. We find that our main result shortcuts to adiabaticity for the (1+1)-dimensional Dirac equation are facilitated by a combination of both scalar and pseudoscalar potentials. Our findings aremore » illustrated for two analytically solvable examples, namely charged particles driven in spatially homogeneous and linear vector fields.« less

Dynamics of Hollow Atom Formation in Intense X-Ray Pulses Probed by Partial Covariance Mapping

NASA Astrophysics Data System (ADS)

Frasinski, L. J.; Zhaunerchyk, V.; Mucke, M.; Squibb, R. J.; Siano, M.; Eland, J. H. D.; Linusson, P.; v. d. Meulen, P.; Salén, P.; Thomas, R. D.; Larsson, M.; Foucar, L.; Ullrich, J.; Motomura, K.; Mondal, S.; Ueda, K.; Osipov, T.; Fang, L.; Murphy, B. F.; Berrah, N.; Bostedt, C.; Bozek, J. D.; Schorb, S.; Messerschmidt, M.; Glownia, J. M.; Cryan, J. P.; Coffee, R. N.; Takahashi, O.; Wada, S.; Piancastelli, M. N.; Richter, R.; Prince, K. C.; Feifel, R.

2013-08-01

When exposed to ultraintense x-radiation sources such as free electron lasers (FELs) the innermost electronic shell can efficiently be emptied, creating a transient hollow atom or molecule. Understanding the femtosecond dynamics of such systems is fundamental to achieving atomic resolution in flash diffraction imaging of noncrystallized complex biological samples. We demonstrate the capacity of a correlation method called “partial covariance mapping” to probe the electron dynamics of neon atoms exposed to intense 8 fs pulses of 1062 eV photons. A complete picture of ionization processes competing in hollow atom formation and decay is visualized with unprecedented ease and the map reveals hitherto unobserved nonlinear sequences of photoionization and Auger events. The technique is particularly well suited to the high counting rate inherent in FEL experiments.

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service's evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version's confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA. PMID:24772033

Mobile phone call data as a regional socio-economic proxy indicator.

PubMed

Šćepanović, Sanja; Mishkovski, Igor; Hui, Pan; Nurminen, Jukka K; Ylä-Jääski, Antti

2015-01-01

The advent of publishing anonymized call detail records opens the door for temporal and spatial human dynamics studies. Such studies, besides being useful for creating universal models for mobility patterns, could be also used for creating new socio-economic proxy indicators that will not rely only on the local or state institutions. In this paper, from the frequency of calls at different times of the day, in different small regional units (sub-prefectures) in Côte d'Ivoire, we infer users' home and work sub-prefectures. This division of users enables us to analyze different mobility and calling patterns for the different regions. We then compare how those patterns correlate to the data from other sources, such as: news for particular events in the given period, census data, economic activity, poverty index, power plants and energy grid data. Our results show high correlation in many of the cases revealing the diversity of socio-economic insights that can be inferred using only mobile phone call data. The methods and the results may be particularly relevant to policy-makers engaged in poverty reduction initiatives as they can provide an affordable tool in the context of resource-constrained developing economies, such as Côte d'Ivoire's.

Overlapping community detection based on link graph using distance dynamics

NASA Astrophysics Data System (ADS)

Chen, Lei; Zhang, Jing; Cai, Li-Jun

2018-01-01

The distance dynamics model was recently proposed to detect the disjoint community of a complex network. To identify the overlapping structure of a network using the distance dynamics model, an overlapping community detection algorithm, called L-Attractor, is proposed in this paper. The process of L-Attractor mainly consists of three phases. In the first phase, L-Attractor transforms the original graph to a link graph (a new edge graph) to assure that one node has multiple distances. In the second phase, using the improved distance dynamics model, a dynamic interaction process is introduced to simulate the distance dynamics (shrink or stretch). Through the dynamic interaction process, all distances converge, and the disjoint community structure of the link graph naturally manifests itself. In the third phase, a recovery method is designed to convert the disjoint community structure of the link graph to the overlapping community structure of the original graph. Extensive experiments are conducted on the LFR benchmark networks as well as real-world networks. Based on the results, our algorithm demonstrates higher accuracy and quality than other state-of-the-art algorithms.

An efficient and guaranteed stable numerical method for continuous modeling of infiltration and redistribution with a shallow dynamic water table

NASA Astrophysics Data System (ADS)

Lai, Wencong; Ogden, Fred L.; Steinke, Robert C.; Talbot, Cary A.

2015-03-01

We have developed a one-dimensional numerical method to simulate infiltration and redistribution in the presence of a shallow dynamic water table. This method builds upon the Green-Ampt infiltration with Redistribution (GAR) model and incorporates features from the Talbot-Ogden (T-O) infiltration and redistribution method in a discretized moisture content domain. The redistribution scheme is more physically meaningful than the capillary weighted redistribution scheme in the T-O method. Groundwater dynamics are considered in this new method instead of hydrostatic groundwater front. It is also computationally more efficient than the T-O method. Motion of water in the vadose zone due to infiltration, redistribution, and interactions with capillary groundwater are described by ordinary differential equations. Numerical solutions to these equations are computationally less expensive than solutions of the highly nonlinear Richards' (1931) partial differential equation. We present results from numerical tests on 11 soil types using multiple rain pulses with different boundary conditions, with and without a shallow water table and compare against the numerical solution of Richards' equation (RE). Results from the new method are in satisfactory agreement with RE solutions in term of ponding time, deponding time, infiltration rate, and cumulative infiltrated depth. The new method, which we call "GARTO" can be used as an alternative to the RE for 1-D coupled surface and groundwater models in general situations with homogeneous soils with dynamic water table. The GARTO method represents a significant advance in simulating groundwater surface water interactions because it very closely matches the RE solution while being computationally efficient, with guaranteed mass conservation, and no stability limitations that can affect RE solvers in the case of a near-surface water table.

State-and-transition simulation models: a framework for forecasting landscape change

USGS Publications Warehouse

Daniel, Colin; Frid, Leonardo; Sleeter, Benjamin M.; Fortin, Marie-Josée

2016-01-01

SummaryA wide range of spatially explicit simulation models have been developed to forecast landscape dynamics, including models for projecting changes in both vegetation and land use. While these models have generally been developed as separate applications, each with a separate purpose and audience, they share many common features.We present a general framework, called a state-and-transition simulation model (STSM), which captures a number of these common features, accompanied by a software product, called ST-Sim, to build and run such models. The STSM method divides a landscape into a set of discrete spatial units and simulates the discrete state of each cell forward as a discrete-time-inhomogeneous stochastic process. The method differs from a spatially interacting Markov chain in several important ways, including the ability to add discrete counters such as age and time-since-transition as state variables, to specify one-step transition rates as either probabilities or target areas, and to represent multiple types of transitions between pairs of states.We demonstrate the STSM method using a model of land-use/land-cover (LULC) change for the state of Hawai'i, USA. Processes represented in this example include expansion/contraction of agricultural lands, urbanization, wildfire, shrub encroachment into grassland and harvest of tree plantations; the model also projects shifts in moisture zones due to climate change. Key model output includes projections of the future spatial and temporal distribution of LULC classes and moisture zones across the landscape over the next 50 years.State-and-transition simulation models can be applied to a wide range of landscapes, including questions of both land-use change and vegetation dynamics. Because the method is inherently stochastic, it is well suited for characterizing uncertainty in model projections. When combined with the ST-Sim software, STSMs offer a simple yet powerful means for developing a wide range of models of landscape dynamics.

State-Resolved Metal Nanoparticle Dynamics Viewed through the Combined Lenses of Ultrafast and Magneto-optical Spectroscopies.

PubMed

Zhao, Tian; Herbert, Patrick J; Zheng, Hongjun; Knappenberger, Kenneth L

2018-06-19

Electronic carrier dynamics play pivotal roles in the functional properties of nanomaterials. For colloidal metals, the mechanisms and influences of these dynamics are structure dependent. The coherent carrier dynamics of collective plasmon modes for nanoparticles (approximately 2 nm and larger) determine optical amplification factors that are important to applied spectroscopy techniques. In the nanocluster domain (sub-2 nm), carrier coupling to vibrational modes affects photoluminescence yields. The performance of photocatalytic materials featuring both nanoparticles and nanoclusters also depends on the relaxation dynamics of nonequilibrium charge carriers. The challenges for developing comprehensive descriptions of carrier dynamics spanning both domains are multifold. Plasmon coherences are short-lived, persisting for only tens of femtoseconds. Nanoclusters exhibit discrete carrier dynamics that can persist for microseconds in some cases. On this time scale, many state-dependent processes, including vibrational relaxation, charge transfer, and spin conversion, affect carrier dynamics in ways that are nonscalable but, rather, structure specific. Hence, state-resolved spectroscopy methods are needed for understanding carrier dynamics in the nanocluster domain. Based on these considerations, a detailed understanding of structure-dependent carrier dynamics across length scales requires an appropriate combination of spectroscopic methods. Plasmon mode-specific dynamics can be obtained through ultrafast correlated light and electron microscopy (UCLEM), which pairs interferometric nonlinear optical (INLO) with electron imaging methods. INLO yields nanostructure spectral resonance responses, which capture the system's homogeneous line width and coherence dynamics. State-resolved nanocluster dynamics can be obtained by pairing ultrafast with magnetic-optical spectroscopy methods. In particular, variable-temperature variable-field (VTVH) spectroscopies allow quantification of transient, excited states, providing quantification of important parameters such as spin and orbital angular momenta as well as the energy gaps that separate electronic fine structure states. Ultrafast two-dimensional electronic spectroscopy (2DES) can be used to understand how these details influence state-to-state carrier dynamics. In combination, VTVH and 2DES methods can provide chemists with detailed information regarding the structure-dependent and state-specific flow of energy through metal nanoclusters. In this Account, we highlight recent advances toward understanding structure-dependent carrier dynamics for metals spanning the sub-nanometer to tens of nanometers length scale. We demonstrate the use of UCLEM methods for arresting interband scattering effects. For sub-nanometer thiol-protected nanoclusters, we discuss the effectiveness of VTVH for distinguishing state-specific radiative recombination originating from a gold core versus organometallic protecting layers. This state specificity is refined further using femtosecond 2DES and two-color methods to isolate so-called superatom state dynamics and vibrationally mediated spin-conversion and emission processes. Finally, we discuss prospects for merging VTVH and 2DES methods into a single platform.

GeneNetFinder2: Improved Inference of Dynamic Gene Regulatory Relations with Multiple Regulators.

PubMed

Han, Kyungsook; Lee, Jeonghoon

2016-01-01

A gene involved in complex regulatory interactions may have multiple regulators since gene expression in such interactions is often controlled by more than one gene. Another thing that makes gene regulatory interactions complicated is that regulatory interactions are not static, but change over time during the cell cycle. Most research so far has focused on identifying gene regulatory relations between individual genes in a particular stage of the cell cycle. In this study we developed a method for identifying dynamic gene regulations of several types from the time-series gene expression data. The method can find gene regulations with multiple regulators that work in combination or individually as well as those with single regulators. The method has been implemented as the second version of GeneNetFinder (hereafter called GeneNetFinder2) and tested on several gene expression datasets. Experimental results with gene expression data revealed the existence of genes that are not regulated by individual genes but rather by a combination of several genes. Such gene regulatory relations cannot be found by conventional methods. Our method finds such regulatory relations as well as those with multiple, independent regulators or single regulators, and represents gene regulatory relations as a dynamic network in which different gene regulatory relations are shown in different stages of the cell cycle. GeneNetFinder2 is available at http://bclab.inha.ac.kr/GeneNetFinder and will be useful for modeling dynamic gene regulations with multiple regulators.

A tone mapping operator based on neural and psychophysical models of visual perception

NASA Astrophysics Data System (ADS)

Cyriac, Praveen; Bertalmio, Marcelo; Kane, David; Vazquez-Corral, Javier

2015-03-01

High dynamic range imaging techniques involve capturing and storing real world radiance values that span many orders of magnitude. However, common display devices can usually reproduce intensity ranges only up to two to three orders of magnitude. Therefore, in order to display a high dynamic range image on a low dynamic range screen, the dynamic range of the image needs to be compressed without losing details or introducing artefacts, and this process is called tone mapping. A good tone mapping operator must be able to produce a low dynamic range image that matches as much as possible the perception of the real world scene. We propose a two stage tone mapping approach, in which the first stage is a global method for range compression based on a gamma curve that equalizes the lightness histogram the best, and the second stage performs local contrast enhancement and color induction using neural activity models for the visual cortex.

The use of Lanczos's method to solve the large generalized symmetric definite eigenvalue problem

NASA Technical Reports Server (NTRS)

Jones, Mark T.; Patrick, Merrell L.

1989-01-01

The generalized eigenvalue problem, Kx = Lambda Mx, is of significant practical importance, especially in structural enginering where it arises as the vibration and buckling problem. A new algorithm, LANZ, based on Lanczos's method is developed. LANZ uses a technique called dynamic shifting to improve the efficiency and reliability of the Lanczos algorithm. A new algorithm for solving the tridiagonal matrices that arise when using Lanczos's method is described. A modification of Parlett and Scott's selective orthogonalization algorithm is proposed. Results from an implementation of LANZ on a Convex C-220 show it to be superior to a subspace iteration code.

Study designs appropriate for the workplace.

PubMed

Hogue, C J

1986-01-01

Carlo and Hearn have called for "refinement of old [epidemiologic] methods and an ongoing evaluation of where methods fit in the overall scheme as we address the multiple complexities of reproductive hazard assessment." This review is an attempt to bring together the current state-of-the-art methods for problem definition and hypothesis testing available to the occupational epidemiologist. For problem definition, meta analysis can be utilized to narrow the field of potential causal hypotheses. Passive active surveillance may further refine issues for analytic research. Within analytic epidemiology, several methods may be appropriate for the workplace setting. Those discussed here may be used to estimate the risk ratio in either a fixed or dynamic population.

Pricing unit-linked insurance with guaranteed benefit

NASA Astrophysics Data System (ADS)

Iqbal, M.; Novkaniza, F.; Novita, M.

2017-07-01

Unit-linked insurance is an investment-linked insurance, that is, the given benefit is the premium investment out-come. Recently, the most widely marketed insurance in the industry is unit-linked insurance with guaranteed benefit. With guaranteed benefit applied, the insurance benefits form is similar to the payoff form of European call option. Thereby, pricing European call option is involved in pricing unit-linked insurance with guaranteed benefit. The dynamics of investment outcome is assumed to follow stochastic interest rate. Hence, change of measure methods is used in pricing unit-linked insurance. The discount factor with stochastic interest rate needs to be modified as well to be zero coupon bond price. Eventually, the insurance premium is calculated by equivalence principle with guaranteed benefit and insurance period explicitly given.

Large Scale Data Analysis and Knowledge Extraction in Communication Data

DTIC Science & Technology

2017-03-31

this purpose, we developed a novel method the " Correlation Density Ran!C’ which finds probability density distribution of related frequent event on all...which is called " Correlation Density Rank", is developed to derive the community tree from the network. As in the real world, where a network is...Community Structure in Dynamic Social Networks using the Correlation Density Rank," 2014 ASE BigData/SocialCom/Cybersecurity Conference, Stanford

Application of a fast skyline computation algorithm for serendipitous searching problems

NASA Astrophysics Data System (ADS)

Koizumi, Kenichi; Hiraki, Kei; Inaba, Mary

2018-02-01

Skyline computation is a method of extracting interesting entries from a large population with multiple attributes. These entries, called skyline or Pareto optimal entries, are known to have extreme characteristics that cannot be found by outlier detection methods. Skyline computation is an important task for characterizing large amounts of data and selecting interesting entries with extreme features. When the population changes dynamically, the task of calculating a sequence of skyline sets is called continuous skyline computation. This task is known to be difficult to perform for the following reasons: (1) information of non-skyline entries must be stored since they may join the skyline in the future; (2) the appearance or disappearance of even a single entry can change the skyline drastically; (3) it is difficult to adopt a geometric acceleration algorithm for skyline computation tasks with high-dimensional datasets. Our new algorithm called jointed rooted-tree (JR-tree) manages entries using a rooted tree structure. JR-tree delays extend the tree to deep levels to accelerate tree construction and traversal. In this study, we presented the difficulties in extracting entries tagged with a rare label in high-dimensional space and the potential of fast skyline computation in low-latency cell identification technology.

Malware analysis using visualized image matrices.

PubMed

Han, KyoungSoo; Kang, BooJoong; Im, Eul Gyu

2014-01-01

This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively.

On the selection of ordinary differential equation models with application to predator-prey dynamical models.

PubMed

Zhang, Xinyu; Cao, Jiguo; Carroll, Raymond J

2015-03-01

We consider model selection and estimation in a context where there are competing ordinary differential equation (ODE) models, and all the models are special cases of a "full" model. We propose a computationally inexpensive approach that employs statistical estimation of the full model, followed by a combination of a least squares approximation (LSA) and the adaptive Lasso. We show the resulting method, here called the LSA method, to be an (asymptotically) oracle model selection method. The finite sample performance of the proposed LSA method is investigated with Monte Carlo simulations, in which we examine the percentage of selecting true ODE models, the efficiency of the parameter estimation compared to simply using the full and true models, and coverage probabilities of the estimated confidence intervals for ODE parameters, all of which have satisfactory performances. Our method is also demonstrated by selecting the best predator-prey ODE to model a lynx and hare population dynamical system among some well-known and biologically interpretable ODE models. © 2014, The International Biometric Society.

Comparison of ensemble post-processing approaches, based on empirical and dynamical error modelisation of rainfall-runoff model forecasts

NASA Astrophysics Data System (ADS)

Chardon, J.; Mathevet, T.; Le Lay, M.; Gailhard, J.

2012-04-01

In the context of a national energy company (EDF : Electricité de France), hydro-meteorological forecasts are necessary to ensure safety and security of installations, meet environmental standards and improve water ressources management and decision making. Hydrological ensemble forecasts allow a better representation of meteorological and hydrological forecasts uncertainties and improve human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. An operational hydrological ensemble forecasting chain has been developed at EDF since 2008 and is being used since 2010 on more than 30 watersheds in France. This ensemble forecasting chain is characterized ensemble pre-processing (rainfall and temperature) and post-processing (streamflow), where a large human expertise is solicited. The aim of this paper is to compare 2 hydrological ensemble post-processing methods developed at EDF in order improve ensemble forecasts reliability (similar to Monatanari &Brath, 2004; Schaefli et al., 2007). The aim of the post-processing methods is to dress hydrological ensemble forecasts with hydrological model uncertainties, based on perfect forecasts. The first method (called empirical approach) is based on a statistical modelisation of empirical error of perfect forecasts, by streamflow sub-samples of quantile class and lead-time. The second method (called dynamical approach) is based on streamflow sub-samples of quantile class and streamflow variation, and lead-time. On a set of 20 watersheds used for operational forecasts, results show that both approaches are necessary to ensure a good post-processing of hydrological ensemble, allowing a good improvement of reliability, skill and sharpness of ensemble forecasts. The comparison of the empirical and dynamical approaches shows the limits of the empirical approach which is not able to take into account hydrological dynamic and processes, i. e. sample heterogeneity. For a same streamflow range corresponds different processes such as rising limbs or recession, where uncertainties are different. The dynamical approach improves reliability, skills and sharpness of forecasts and globally reduces confidence intervals width. When compared in details, the dynamical approach allows a noticeable reduction of confidence intervals during recessions where uncertainty is relatively lower and a slight increase of confidence intervals during rising limbs or snowmelt where uncertainty is greater. The dynamic approach, validated by forecaster's experience that considered the empirical approach not discriminative enough, improved forecaster's confidence and communication of uncertainties. Montanari, A. and Brath, A., (2004). A stochastic approach for assessing the uncertainty of rainfall-runoff simulations. Water Resources Research, 40, W01106, doi:10.1029/2003WR002540. Schaefli, B., Balin Talamba, D. and Musy, A., (2007). Quantifying hydrological modeling errors through a mixture of normal distributions. Journal of Hydrology, 332, 303-315.

Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular Simulations.

PubMed

Takada, Shoji; Kanada, Ryo; Tan, Cheng; Terakawa, Tsuyoshi; Li, Wenfei; Kenzaki, Hiroo

2015-12-15

Due to hierarchic nature of biomolecular systems, their computational modeling calls for multiscale approaches, in which coarse-grained (CG) simulations are used to address long-time dynamics of large systems. Here, we review recent developments and applications of CG modeling methods, focusing on our methods primarily for proteins, DNA, and their complexes. These methods have been implemented in the CG biomolecular simulator, CafeMol. Our CG model has resolution such that ∼10 non-hydrogen atoms are grouped into one CG particle on average. For proteins, each amino acid is represented by one CG particle. For DNA, one nucleotide is simplified by three CG particles, representing sugar, phosphate, and base. The protein modeling is based on the idea that proteins have a globally funnel-like energy landscape, which is encoded in the structure-based potential energy function. We first describe two representative minimal models of proteins, called the elastic network model and the classic Go̅ model. We then present a more elaborate protein model, which extends the minimal model to incorporate sequence and context dependent local flexibility and nonlocal contacts. For DNA, we describe a model developed by de Pablo's group that was tuned to well reproduce sequence-dependent structural and thermodynamic experimental data for single- and double-stranded DNAs. Protein-DNA interactions are modeled either by the structure-based term for specific cases or by electrostatic and excluded volume terms for nonspecific cases. We also discuss the time scale mapping in CG molecular dynamics simulations. While the apparent single time step of our CGMD is about 10 times larger than that in the fully atomistic molecular dynamics for small-scale dynamics, large-scale motions can be further accelerated by two-orders of magnitude with the use of CG model and a low friction constant in Langevin dynamics. Next, we present four examples of applications. First, the classic Go̅ model was used to emulate one ATP cycle of a molecular motor, kinesin. Second, nonspecific protein-DNA binding was studied by a combination of elaborate protein and DNA models. Third, a transcription factor, p53, that contains highly fluctuating regions was simulated on two perpendicularly arranged DNA segments, addressing intersegmental transfer of p53. Fourth, we simulated structural dynamics of dinucleosomes connected by a linker DNA finding distinct types of internucleosome docking and salt-concentration-dependent compaction. Finally, we discuss many of limitations in the current approaches and future directions. Especially, more accurate electrostatic treatment and a phospholipid model that matches our CG resolutions are of immediate importance.

Understanding the Effect of Grain Boundary Character on Dynamic Recrystallization in Stainless Steel 316L

NASA Astrophysics Data System (ADS)

Beck, Megan; Morse, Michael; Corolewski, Caleb; Fritchman, Koyuki; Stifter, Chris; Poole, Callum; Hurley, Michael; Frary, Megan

2017-08-01

Dynamic recrystallization (DRX) occurs during high-temperature deformation in metals and alloys with low to medium stacking fault energies. Previous simulations and experimental research have shown the effect of temperature and grain size on DRX behavior, but not the effect of the grain boundary character distribution. To investigate the effects of the distribution of grain boundary types, experimental testing was performed on stainless steel 316L specimens with different initial special boundary fractions (SBF). This work was completed in conjunction with computer simulations that used a modified Monte Carlo method which allowed for the addition of anisotropic grain boundary energies using orientation data from electron backscatter diffraction (EBSD). The correlation of the experimental and simulation work allows for a better understanding of how the input parameters in the simulations correspond to what occurs experimentally. Results from both simulations and experiments showed that a higher fraction of so-called "special" boundaries ( e.g., Σ3 twin boundaries) delayed the onset of recrystallization to larger strains and that it is energetically favorable for nuclei to form on triple junctions without these so-called "special" boundaries.

Enumerating Substituted Benzene Isomers of Tree-Like Chemical Graphs.

PubMed

Li, Jinghui; Nagamochi, Hiroshi; Akutsu, Tatsuya

2018-01-01

Enumeration of chemical structures is useful for drug design, which is one of the main targets of computational biology and bioinformatics. A chemical graph with no other cycles than benzene rings is called tree-like, and becomes a tree possibly with multiple edges if we contract each benzene ring into a single virtual atom of valence 6. All tree-like chemical graphs with a given tree representation are called the substituted benzene isomers of . When we replace each virtual atom in with a benzene ring to obtain a substituted benzene isomer, distinct isomers of are caused by the difference in arrangements of atom groups around a benzene ring. In this paper, we propose an efficient algorithm that enumerates all substituted benzene isomers of a given tree representation . Our algorithm first counts the number of all the isomers of the tree representation by a dynamic programming method. To enumerate all the isomers, for each , our algorithm then generates the th isomer by backtracking the counting phase of the dynamic programming. We also implemented our algorithm for computational experiments.

Review of Modelling Techniques for In Vivo Muscle Force Estimation in the Lower Extremities during Strength Training

PubMed Central

Schellenberg, Florian; Oberhofer, Katja; Taylor, William R.

2015-01-01

Background. Knowledge of the musculoskeletal loading conditions during strength training is essential for performance monitoring, injury prevention, rehabilitation, and training design. However, measuring muscle forces during exercise performance as a primary determinant of training efficacy and safety has remained challenging. Methods. In this paper we review existing computational techniques to determine muscle forces in the lower limbs during strength exercises in vivo and discuss their potential for uptake into sports training and rehabilitation. Results. Muscle forces during exercise performance have almost exclusively been analysed using so-called forward dynamics simulations, inverse dynamics techniques, or alternative methods. Musculoskeletal models based on forward dynamics analyses have led to considerable new insights into muscular coordination, strength, and power during dynamic ballistic movement activities, resulting in, for example, improved techniques for optimal performance of the squat jump, while quasi-static inverse dynamics optimisation and EMG-driven modelling have helped to provide an understanding of low-speed exercises. Conclusion. The present review introduces the different computational techniques and outlines their advantages and disadvantages for the informed usage by nonexperts. With sufficient validation and widespread application, muscle force calculations during strength exercises in vivo are expected to provide biomechanically based evidence for clinicians and therapists to evaluate and improve training guidelines. PMID:26417378

Change detection in the dynamics of an intracellular protein synthesis model using nonlinear Kalman filtering.

PubMed

Rigatos, Gerasimos G; Rigatou, Efthymia G; Djida, Jean Daniel

2015-10-01

A method for early diagnosis of parametric changes in intracellular protein synthesis models (e.g. the p53 protein - mdm2 inhibitor model) is developed with the use of a nonlinear Kalman Filtering approach (Derivative-free nonlinear Kalman Filter) and of statistical change detection methods. The intracellular protein synthesis dynamic model is described by a set of coupled nonlinear differential equations. It is shown that such a dynamical system satisfies differential flatness properties and this allows to transform it, through a change of variables (diffeomorphism), to the so-called linear canonical form. For the linearized equivalent of the dynamical system, state estimation can be performed using the Kalman Filter recursion. Moreover, by applying an inverse transformation based on the previous diffeomorphism it becomes also possible to obtain estimates of the state variables of the initial nonlinear model. By comparing the output of the Kalman Filter (which is assumed to correspond to the undistorted dynamical model) with measurements obtained from the monitored protein synthesis system, a sequence of differences (residuals) is obtained. The statistical processing of the residuals with the use of x2 change detection tests, can provide indication within specific confidence intervals about parametric changes in the considered biological system and consequently indications about the appearance of specific diseases (e.g. malignancies).

The human dynamic clamp as a paradigm for social interaction.

PubMed

Dumas, Guillaume; de Guzman, Gonzalo C; Tognoli, Emmanuelle; Kelso, J A Scott

2014-09-02

Social neuroscience has called for new experimental paradigms aimed toward real-time interactions. A distinctive feature of interactions is mutual information exchange: One member of a pair changes in response to the other while simultaneously producing actions that alter the other. Combining mathematical and neurophysiological methods, we introduce a paradigm called the human dynamic clamp (HDC), to directly manipulate the interaction or coupling between a human and a surrogate constructed to behave like a human. Inspired by the dynamic clamp used so productively in cellular neuroscience, the HDC allows a person to interact in real time with a virtual partner itself driven by well-established models of coordination dynamics. People coordinate hand movements with the visually observed movements of a virtual hand, the parameters of which depend on input from the subject's own movements. We demonstrate that HDC can be extended to cover a broad repertoire of human behavior, including rhythmic and discrete movements, adaptation to changes of pacing, and behavioral skill learning as specified by a virtual "teacher." We propose HDC as a general paradigm, best implemented when empirically verified theoretical or mathematical models have been developed in a particular scientific field. The HDC paradigm is powerful because it provides an opportunity to explore parameter ranges and perturbations that are not easily accessible in ordinary human interactions. The HDC not only enables to test the veracity of theoretical models, it also illuminates features that are not always apparent in real-time human social interactions and the brain correlates thereof.

Plug-and-play inference for disease dynamics: measles in large and small populations as a case study

PubMed Central

He, Daihai; Ionides, Edward L.; King, Aaron A.

2010-01-01

Statistical inference for mechanistic models of partially observed dynamic systems is an active area of research. Most existing inference methods place substantial restrictions upon the form of models that can be fitted and hence upon the nature of the scientific hypotheses that can be entertained and the data that can be used to evaluate them. In contrast, the so-called plug-and-play methods require only simulations from a model and are thus free of such restrictions. We show the utility of the plug-and-play approach in the context of an investigation of measles transmission dynamics. Our novel methodology enables us to ask and answer questions that previous analyses have been unable to address. Specifically, we demonstrate that plug-and-play methods permit the development of a modelling and inference framework applicable to data from both large and small populations. We thereby obtain novel insights into the nature of heterogeneity in mixing and comment on the importance of including extra-demographic stochasticity as a means of dealing with environmental stochasticity and model misspecification. Our approach is readily applicable to many other epidemiological and ecological systems. PMID:19535416

Photonic jet μ-etching: from static to dynamic process

NASA Astrophysics Data System (ADS)

Abdurrochman, A.; Lecler, S.; Zelgowski, J.; Mermet, F.; Fontaine, J.; Tumbelaka, B. Y.

2017-05-01

Photonic jet etching is a direct-laser etching method applying photonic jet phenomenon to concentrate the laser beam onto the proceeded material. We call photonic jet the phenomenon of the localized sub-wavelength propagative beam generated at the shadow-side surfaces of micro-scale dielectric cylinders or spheres, when they are illuminated by an electromagnetic plane-wave or laser beam. This concentration has made possible the laser to yield sub-μ etching marks, despite the laser was a near-infrared with nano-second pulses sources. We will present these achievements from the beginning when some spherical glasses were used for static etching to dynamic etching using an optical fiber with a semi-elliptical tip.

Collective phase description of oscillatory convection

NASA Astrophysics Data System (ADS)

Kawamura, Yoji; Nakao, Hiroya

2013-12-01

We formulate a theory for the collective phase description of oscillatory convection in Hele-Shaw cells. It enables us to describe the dynamics of the oscillatory convection by a single degree of freedom which we call the collective phase. The theory can be considered as a phase reduction method for limit-cycle solutions in infinite-dimensional dynamical systems, namely, stable time-periodic solutions to partial differential equations, representing the oscillatory convection. We derive the phase sensitivity function, which quantifies the phase response of the oscillatory convection to weak perturbations applied at each spatial point, and analyze the phase synchronization between two weakly coupled Hele-Shaw cells exhibiting oscillatory convection on the basis of the derived phase equations.

Stochastic optimal control of ultradiffusion processes with application to dynamic portfolio management

NASA Astrophysics Data System (ADS)

Marcozzi, Michael D.

2008-12-01

We consider theoretical and approximation aspects of the stochastic optimal control of ultradiffusion processes in the context of a prototype model for the selling price of a European call option. Within a continuous-time framework, the dynamic management of a portfolio of assets is effected through continuous or point control, activation costs, and phase delay. The performance index is derived from the unique weak variational solution to the ultraparabolic Hamilton-Jacobi equation; the value function is the optimal realization of the performance index relative to all feasible portfolios. An approximation procedure based upon a temporal box scheme/finite element method is analyzed; numerical examples are presented in order to demonstrate the viability of the approach.

Dynamics of flexible bodies in tree topology - A computer oriented approach

NASA Technical Reports Server (NTRS)

Singh, R. P.; Vandervoort, R. J.; Likins, P. W.

1984-01-01

An approach suited for automatic generation of the equations of motion for large mechanical systems (i.e., large space structures, mechanisms, robots, etc.) is presented. The system topology is restricted to a tree configuration. The tree is defined as an arbitrary set of rigid and flexible bodies connected by hinges characterizing relative translations and rotations of two adjoining bodies. The equations of motion are derived via Kane's method. The resulting equation set is of minimum dimension. Dynamical equations are imbedded in a computer program called TREETOPS. Extensive control simulation capability is built in the TREETOPS program. The simulation is driven by an interactive set-up program resulting in an easy to use analysis tool.

Dynamic and Transient Performance of Turbofan/Turboshaft Convertible Engine With Variable Inlet Guide Vanes

NASA Technical Reports Server (NTRS)

McArdle, Jack G.; Barth, Richard L.; Wenzel, Leon M.; Biesiadny, Thomas J.

1996-01-01

A convertible engine called the CEST TF34, using the variable inlet guide vane method of power change, was tested on an outdoor stand at the NASA Lewis Research Center with a waterbrake dynamometer for the shaft load. A new digital electronic system, in conjunction with a modified standard TF34 hydromechanical fuel control, kept engine operation stable and safely within limits. All planned testing was completed successfully. Steady-state performance and acoustic characteristics were reported previously and are referenced. This report presents results of transient and dynamic tests. The transient tests measured engine response to several rapid changes in thrust and torque commands at constant fan (shaft) speed. Limited results from dynamic tests using the pseudorandom binary noise technique are also presented. Performance of the waterbrake dynamometer is discussed in an appendix.

Note: "Lock-in accelerometry" to follow sink dynamics in shaken granular matter.

PubMed

Sánchez-Colina, G; Alonso-Llanes, L; Martínez, E; Batista-Leyva, A J; Clement, C; Fliedner, C; Toussaint, R; Altshuler, E

2014-12-01

Understanding the penetration dynamics of intruders in granular beds is relevant not only for fundamental physics, but also for geophysical processes and construction on sediments or granular soils in areas potentially affected by earthquakes. While the penetration of intruders in two dimensional (2D) laboratory granular beds can be followed using video recording, this is useless in three dimensional (3D) beds of non-transparent materials such as common sand. Here, we propose a method to quantify the sink dynamics of an intruder into laterally shaken granular beds based on the temporal correlations between the signals from a reference accelerometer fixed to the shaken granular bed, and a probe accelerometer deployed inside the intruder. Due to its analogy with the working principle of a lock-in amplifier, we call this technique lock-in accelerometry.

Exploring the Dynamics of Cell Processes through Simulations of Fluorescence Microscopy Experiments

PubMed Central

Angiolini, Juan; Plachta, Nicolas; Mocskos, Esteban; Levi, Valeria

2015-01-01

Fluorescence correlation spectroscopy (FCS) methods are powerful tools for unveiling the dynamical organization of cells. For simple cases, such as molecules passively moving in a homogeneous media, FCS analysis yields analytical functions that can be fitted to the experimental data to recover the phenomenological rate parameters. Unfortunately, many dynamical processes in cells do not follow these simple models, and in many instances it is not possible to obtain an analytical function through a theoretical analysis of a more complex model. In such cases, experimental analysis can be combined with Monte Carlo simulations to aid in interpretation of the data. In response to this need, we developed a method called FERNET (Fluorescence Emission Recipes and Numerical routines Toolkit) based on Monte Carlo simulations and the MCell-Blender platform, which was designed to treat the reaction-diffusion problem under realistic scenarios. This method enables us to set complex geometries of the simulation space, distribute molecules among different compartments, and define interspecies reactions with selected kinetic constants, diffusion coefficients, and species brightness. We apply this method to simulate single- and multiple-point FCS, photon-counting histogram analysis, raster image correlation spectroscopy, and two-color fluorescence cross-correlation spectroscopy. We believe that this new program could be very useful for predicting and understanding the output of fluorescence microscopy experiments. PMID:26039162

Perception and Haptic Rendering of Friction Moments.

PubMed

Kawasaki, H; Ohtuka, Y; Koide, S; Mouri, T

2011-01-01

This paper considers moments due to friction forces on the human fingertip. A computational technique called the friction moment arc method is presented. The method computes the static and/or dynamic friction moment independent of a friction force calculation. In addition, a new finger holder to display friction moment is presented. This device incorporates a small brushless motor and disk, and connects the human's finger to an interface finger of the five-fingered haptic interface robot HIRO II. Subjects' perception of friction moment while wearing the finger holder, as well as perceptions during object manipulation in a virtual reality environment, were evaluated experimentally.

The coupling technique: A two-wave acoustic method for the study of dislocation dynamics

NASA Astrophysics Data System (ADS)

Gremaud, G.; Bujard, M.; Benoit, W.

1987-03-01

Progress in the study of dislocation dynamics has been achieved using a two-wave acoustic method, which has been called the coupling technique. In this method, the attenuation α and the velocity v of ultrasonic waves are measured in a sample submitted simultaneously to a harmonic stress σ of low frequency. Closed curves Δα(σ) and Δv/v(σ) are drawn during each cycle of the applied stress. The shapes of these curves and their evolution are characteristic of each dislocation motion mechanism which is activated by the low-frequency applied stress. For this reason, the closed curves Δα(σ) and Δv/v(σ) can be considered as signatures of the interaction mechanism which controls the low-frequency dislocation motion. In this paper, the concept of signature is presented and explained with some experimental examples. It will also be shown that theoretical models can be developed which explain very well the experimental results.

Graph-based analysis of kinetics on multidimensional potential-energy surfaces.

PubMed

Okushima, T; Niiyama, T; Ikeda, K S; Shimizu, Y

2009-09-01

The aim of this paper is twofold: one is to give a detailed description of an alternative graph-based analysis method, which we call saddle connectivity graph, for analyzing the global topography and the dynamical properties of many-dimensional potential-energy landscapes and the other is to give examples of applications of this method in the analysis of the kinetics of realistic systems. A Dijkstra-type shortest path algorithm is proposed to extract dynamically dominant transition pathways by kinetically defining transition costs. The applicability of this approach is first confirmed by an illustrative example of a low-dimensional random potential. We then show that a coarse-graining procedure tailored for saddle connectivity graphs can be used to obtain the kinetic properties of 13- and 38-atom Lennard-Jones clusters. The coarse-graining method not only reduces the complexity of the graphs, but also, with iterative use, reveals a self-similar hierarchical structure in these clusters. We also propose that the self-similarity is common to many-atom Lennard-Jones clusters.

Methods of sequential estimation for determining initial data in numerical weather prediction. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Cohn, S. E.

1982-01-01

Numerical weather prediction (NWP) is an initial-value problem for a system of nonlinear differential equations, in which initial values are known incompletely and inaccurately. Observational data available at the initial time must therefore be supplemented by data available prior to the initial time, a problem known as meteorological data assimilation. A further complication in NWP is that solutions of the governing equations evolve on two different time scales, a fast one and a slow one, whereas fast scale motions in the atmosphere are not reliably observed. This leads to the so called initialization problem: initial values must be constrained to result in a slowly evolving forecast. The theory of estimation of stochastic dynamic systems provides a natural approach to such problems. For linear stochastic dynamic models, the Kalman-Bucy (KB) sequential filter is the optimal data assimilation method, for linear models, the optimal combined data assimilation-initialization method is a modified version of the KB filter.

Simultaneous regularization method for the determination of radius distributions from experimental multiangle correlation functions

NASA Astrophysics Data System (ADS)

Buttgereit, R.; Roths, T.; Honerkamp, J.; Aberle, L. B.

2001-10-01

Dynamic light scattering experiments have become a powerful tool in order to investigate the dynamical properties of complex fluids. In many applications in both soft matter research and industry so-called ``real world'' systems are subject of great interest. Here, the dilution of the investigated system often cannot be changed without getting measurement artifacts, so that one often has to deal with highly concentrated and turbid media. The investigation of such systems requires techniques that suppress the influence of multiple scattering, e.g., cross correlation techniques. However, measurements at turbid as well as highly diluted media lead to data with low signal-to-noise ratio, which complicates data analysis and leads to unreliable results. In this article a multiangle regularization method is discussed, which copes with the difficulties arising from such samples and enhances enormously the quality of the estimated solution. In order to demonstrate the efficiency of this multiangle regularization method we applied it to cross correlation functions measured at highly turbid samples.

Chaotic dynamics of flexible Euler-Bernoulli beams

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

Awrejcewicz, J., E-mail: awrejcew@p.lodz.pl; Krysko, A. V., E-mail: anton.krysko@gmail.com; Kutepov, I. E., E-mail: iekutepov@gmail.com

2013-12-15

Mathematical modeling and analysis of spatio-temporal chaotic dynamics of flexible simple and curved Euler-Bernoulli beams are carried out. The Kármán-type geometric non-linearity is considered. Algorithms reducing partial differential equations which govern the dynamics of studied objects and associated boundary value problems are reduced to the Cauchy problem through both Finite Difference Method with the approximation of O(c{sup 2}) and Finite Element Method. The obtained Cauchy problem is solved via the fourth and sixth-order Runge-Kutta methods. Validity and reliability of the results are rigorously discussed. Analysis of the chaotic dynamics of flexible Euler-Bernoulli beams for a series of boundary conditions ismore » carried out with the help of the qualitative theory of differential equations. We analyze time histories, phase and modal portraits, autocorrelation functions, the Poincaré and pseudo-Poincaré maps, signs of the first four Lyapunov exponents, as well as the compression factor of the phase volume of an attractor. A novel scenario of transition from periodicity to chaos is obtained, and a transition from chaos to hyper-chaos is illustrated. In particular, we study and explain the phenomenon of transition from symmetric to asymmetric vibrations. Vibration-type charts are given regarding two control parameters: amplitude q{sub 0} and frequency ω{sub p} of the uniformly distributed periodic excitation. Furthermore, we detected and illustrated how the so called temporal-space chaos is developed following the transition from regular to chaotic system dynamics.« less

Methods For Self-Organizing Software

DOEpatents

Bouchard, Ann M.; Osbourn, Gordon C.

2005-10-18

A method for dynamically self-assembling and executing software is provided, containing machines that self-assemble execution sequences and data structures. In addition to ordered functions calls (found commonly in other software methods), mutual selective bonding between bonding sites of machines actuates one or more of the bonding machines. Two or more machines can be virtually isolated by a construct, called an encapsulant, containing a population of machines and potentially other encapsulants that can only bond with each other. A hierarchical software structure can be created using nested encapsulants. Multi-threading is implemented by populations of machines in different encapsulants that are interacting concurrently. Machines and encapsulants can move in and out of other encapsulants, thereby changing the functionality. Bonding between machines' sites can be deterministic or stochastic with bonding triggering a sequence of actions that can be implemented by each machine. A self-assembled execution sequence occurs as a sequence of stochastic binding between machines followed by their deterministic actuation. It is the sequence of bonding of machines that determines the execution sequence, so that the sequence of instructions need not be contiguous in memory.

Understanding dislocation mechanics at the mesoscale using phase field dislocation dynamics

PubMed Central

Hunter, A.

2016-01-01

In this paper, we discuss the formulation, recent developments and findings obtained from a mesoscale mechanics technique called phase field dislocation dynamics (PFDD). We begin by presenting recent advancements made in modelling face-centred cubic materials, such as integration with atomic-scale simulations to account for partial dislocations. We discuss calculations that help in understanding grain size effects on transitions from full to partial dislocation-mediated slip behaviour and deformation twinning. Finally, we present recent extensions of the PFDD framework to alternative crystal structures, such as body-centred cubic metals, and two-phase materials, including free surfaces, voids and bi-metallic crystals. With several examples we demonstrate that the PFDD model is a powerful and versatile method that can bridge the length and time scales between atomistic and continuum-scale methods, providing a much needed understanding of deformation mechanisms in the mesoscale regime. PMID:27002063

Modelling crystal plasticity by 3D dislocation dynamics and the finite element method: The Discrete-Continuous Model revisited

NASA Astrophysics Data System (ADS)

Vattré, A.; Devincre, B.; Feyel, F.; Gatti, R.; Groh, S.; Jamond, O.; Roos, A.

2014-02-01

A unified model coupling 3D dislocation dynamics (DD) simulations with the finite element (FE) method is revisited. The so-called Discrete-Continuous Model (DCM) aims to predict plastic flow at the (sub-)micron length scale of materials with complex boundary conditions. The evolution of the dislocation microstructure and the short-range dislocation-dislocation interactions are calculated with a DD code. The long-range mechanical fields due to the dislocations are calculated by a FE code, taking into account the boundary conditions. The coupling procedure is based on eigenstrain theory, and the precise manner in which the plastic slip, i.e. the dislocation glide as calculated by the DD code, is transferred to the integration points of the FE mesh is described in full detail. Several test cases are presented, and the DCM is applied to plastic flow in a single-crystal Nickel-based superalloy.

Penalty dynamic programming algorithm for dim targets detection in sensor systems.

PubMed

Huang, Dayu; Xue, Anke; Guo, Yunfei

2012-01-01

In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations.

Parametric spectro-temporal analyzer (PASTA) for real-time optical spectrum observation

NASA Astrophysics Data System (ADS)

Zhang, Chi; Xu, Jianbing; Chui, P. C.; Wong, Kenneth K. Y.

2013-06-01

Real-time optical spectrum analysis is an essential tool in observing ultrafast phenomena, such as the dynamic monitoring of spectrum evolution. However, conventional method such as optical spectrum analyzers disperse the spectrum in space and allocate it in time sequence by mechanical rotation of a grating, so are incapable of operating at high speed. A more recent method all-optically stretches the spectrum in time domain, but is limited by the allowable input condition. In view of these constraints, here we present a real-time spectrum analyzer called parametric spectro-temporal analyzer (PASTA), which is based on the time-lens focusing mechanism. It achieves a frame rate as high as 100 MHz and accommodates various input conditions. As a proof of concept and also for the first time, we verify its applications in observing the dynamic spectrum of a Fourier domain mode-locked laser, and the spectrum evolution of a laser cavity during its stabilizing process.

Simultaneous Aerodynamic and Structural Design Optimization (SASDO) for a 3-D Wing

NASA Technical Reports Server (NTRS)

Gumbert, Clyde R.; Hou, Gene J.-W.; Newman, Perry A.

2001-01-01

The formulation and implementation of an optimization method called Simultaneous Aerodynamic and Structural Design Optimization (SASDO) is shown as an extension of the Simultaneous Aerodynamic Analysis and Design Optimization (SAADO) method. It is extended by the inclusion of structure element sizing parameters as design variables and Finite Element Method (FEM) analysis responses as constraints. The method aims to reduce the computational expense. incurred in performing shape and sizing optimization using state-of-the-art Computational Fluid Dynamics (CFD) flow analysis, FEM structural analysis and sensitivity analysis tools. SASDO is applied to a simple. isolated, 3-D wing in inviscid flow. Results show that the method finds the saine local optimum as a conventional optimization method with some reduction in the computational cost and without significant modifications; to the analysis tools.

Robust Flutter Analysis for Aeroservoelastic Systems

NASA Astrophysics Data System (ADS)

Kotikalpudi, Aditya

The dynamics of a flexible air vehicle are typically described using an aeroservoelastic model which accounts for interaction between aerodynamics, structural dynamics, rigid body dynamics and control laws. These subsystems can be individually modeled using a theoretical approach and experimental data from various ground tests can be combined into them. For instance, a combination of linear finite element modeling and data from ground vibration tests may be used to obtain a validated structural model. Similarly, an aerodynamic model can be obtained using computational fluid dynamics or simple panel methods and partially updated using limited data from wind tunnel tests. In all cases, the models obtained for these subsystems have a degree of uncertainty owing to inherent assumptions in the theory and errors in experimental data. Suitable uncertain models that account for these uncertainties can be built to study the impact of these modeling errors on the ability to predict dynamic instabilities known as flutter. This thesis addresses the methods used for modeling rigid body dynamics, structural dynamics and unsteady aerodynamics of a blended wing design called the Body Freedom Flutter vehicle. It discusses the procedure used to incorporate data from a wide range of ground based experiments in the form of model uncertainties within these subsystems. Finally, it provides the mathematical tools for carrying out flutter analysis and sensitivity analysis which account for these model uncertainties. These analyses are carried out for both open loop and controller in the loop (closed loop) cases.

Dynamic grid refinement for partial differential equations on parallel computers

NASA Technical Reports Server (NTRS)

Mccormick, S.; Quinlan, D.

1989-01-01

The fast adaptive composite grid method (FAC) is an algorithm that uses various levels of uniform grids to provide adaptive resolution and fast solution of PDEs. An asynchronous version of FAC, called AFAC, that completely eliminates the bottleneck to parallelism is presented. This paper describes the advantage that this algorithm has in adaptive refinement for moving singularities on multiprocessor computers. This work is applicable to the parallel solution of two- and three-dimensional shock tracking problems.

Low-Rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging.

PubMed

Ravishankar, Saiprasad; Moore, Brian E; Nadakuditi, Raj Rao; Fessler, Jeffrey A

2017-05-01

Sparsity-based approaches have been popular in many applications in image processing and imaging. Compressed sensing exploits the sparsity of images in a transform domain or dictionary to improve image recovery fromundersampledmeasurements. In the context of inverse problems in dynamic imaging, recent research has demonstrated the promise of sparsity and low-rank techniques. For example, the patches of the underlying data are modeled as sparse in an adaptive dictionary domain, and the resulting image and dictionary estimation from undersampled measurements is called dictionary-blind compressed sensing, or the dynamic image sequence is modeled as a sum of low-rank and sparse (in some transform domain) components (L+S model) that are estimated from limited measurements. In this work, we investigate a data-adaptive extension of the L+S model, dubbed LASSI, where the temporal image sequence is decomposed into a low-rank component and a component whose spatiotemporal (3D) patches are sparse in some adaptive dictionary domain. We investigate various formulations and efficient methods for jointly estimating the underlying dynamic signal components and the spatiotemporal dictionary from limited measurements. We also obtain efficient sparsity penalized dictionary-blind compressed sensing methods as special cases of our LASSI approaches. Our numerical experiments demonstrate the promising performance of LASSI schemes for dynamicmagnetic resonance image reconstruction from limited k-t space data compared to recent methods such as k-t SLR and L+S, and compared to the proposed dictionary-blind compressed sensing method.

Dynamic Multiple-Threshold Call Admission Control Based on Optimized Genetic Algorithm in Wireless/Mobile Networks

NASA Astrophysics Data System (ADS)

Wang, Shengling; Cui, Yong; Koodli, Rajeev; Hou, Yibin; Huang, Zhangqin

Due to the dynamics of topology and resources, Call Admission Control (CAC) plays a significant role for increasing resource utilization ratio and guaranteeing users' QoS requirements in wireless/mobile networks. In this paper, a dynamic multi-threshold CAC scheme is proposed to serve multi-class service in a wireless/mobile network. The thresholds are renewed at the beginning of each time interval to react to the changing mobility rate and network load. To find suitable thresholds, a reward-penalty model is designed, which provides different priorities between different service classes and call types through different reward/penalty policies according to network load and average call arrival rate. To speed up the running time of CAC, an Optimized Genetic Algorithm (OGA) is presented, whose components such as encoding, population initialization, fitness function and mutation etc., are all optimized in terms of the traits of the CAC problem. The simulation demonstrates that the proposed CAC scheme outperforms the similar schemes, which means the optimization is realized. Finally, the simulation shows the efficiency of OGA.

Neural-tree call admission controller for ATM networks

NASA Astrophysics Data System (ADS)

Rughooputh, Harry C. S.

1999-03-01

Asynchronous Transfer Mode (ATM) has been recommended by ITU-T as the transport method for broadband integrated services digital networks. In high-speed ATM networks different types of multimedia traffic streams with widely varying traffic characteristics and Quality of Service (QoS) are asynchronously multiplexed on transmission links and switched without window flow control as found in X.25. In such an environment, a traffic control scheme is required to manage the required QoS of each class individually. To meet the QoS requirements, Bandwidth Allocation and Call Admission Control (CAC) in ATM networks must be able to adapt gracefully to the dynamic behavior of traffic and the time-varying nature of the network condition. In this paper, a Neural Network approach for CAC is proposed. The call admission problem is addressed by designing controllers based on Neural Tree Networks. Simulations reveal that the proposed scheme is not only simple but it also offers faster response than conventional neural/neuro-fuzzy controllers.

G-index: A new metric to describe dynamic refractive index effects in HPLC absorbance detection.

PubMed

Kraiczek, Karsten G; Rozing, Gerard P; Zengerle, Roland

2018-09-01

High performance liquid chromatography (HPLC) with a solvent gradient and absorbance detection is one of the most widely used methods in analytical chemistry. The observed absorbance baseline is affected by the changes in the refractive index (RI) of the mobile phase. Near the limited of detection, this complicates peak quantitation. The general aspects of these RI-induced apparent absorbance effects are discussed. Two different detectors with fundamentally different optics and flow cell concepts, a variable-wavelength detector equipped with a conventional flow cell and a diode-array detector equipped with a liquid core waveguide flow cell, are compared with respect to their RI behavior. A simple method to separate static - partly unavoidable - RI effects from dynamic RI effects is presented. It is shown that the dynamic RI behavior of an absorbance detector can be well described using a single, relatively easy-to-determine metric called the G-index. The G-index is typically in the order of a few seconds and its sign depends on the optical flow cell concept. Copyright © 2018 Elsevier B.V. All rights reserved.

RTL validation methodology on high complexity wireless microcontroller using OVM technique for fast time to market

NASA Astrophysics Data System (ADS)

Zhafirah Muhammad, Nurul; Harun, A.; Hambali, N. A. M. A.; Murad, S. A. Z.; Mohyar, S. N.; Isa, M. N.; Jambek, AB

2017-11-01

Increased demand in internet of thing (IOT) application based has inadvertently forced the move towards higher complexity of integrated circuit supporting SoC. Such spontaneous increased in complexity poses unequivocal complicated validation strategies. Hence, the complexity allows researchers to come out with various exceptional methodologies in order to overcome this problem. This in essence brings about the discovery of dynamic verification, formal verification and hybrid techniques. In reserve, it is very important to discover bugs at infancy of verification process in (SoC) in order to reduce time consuming and fast time to market for the system. Ergo, in this paper we are focusing on the methodology of verification that can be done at Register Transfer Level of SoC based on the AMBA bus design. On top of that, the discovery of others verification method called Open Verification Methodology (OVM) brings out an easier way in RTL validation methodology neither as the replacement for the traditional method yet as an effort for fast time to market for the system. Thus, the method called OVM is proposed in this paper as the verification method for larger design to avert the disclosure of the bottleneck in validation platform.

Red Lesion Detection Using Dynamic Shape Features for Diabetic Retinopathy Screening.

PubMed

Seoud, Lama; Hurtut, Thomas; Chelbi, Jihed; Cheriet, Farida; Langlois, J M Pierre

2016-04-01

The development of an automatic telemedicine system for computer-aided screening and grading of diabetic retinopathy depends on reliable detection of retinal lesions in fundus images. In this paper, a novel method for automatic detection of both microaneurysms and hemorrhages in color fundus images is described and validated. The main contribution is a new set of shape features, called Dynamic Shape Features, that do not require precise segmentation of the regions to be classified. These features represent the evolution of the shape during image flooding and allow to discriminate between lesions and vessel segments. The method is validated per-lesion and per-image using six databases, four of which are publicly available. It proves to be robust with respect to variability in image resolution, quality and acquisition system. On the Retinopathy Online Challenge's database, the method achieves a FROC score of 0.420 which ranks it fourth. On the Messidor database, when detecting images with diabetic retinopathy, the proposed method achieves an area under the ROC curve of 0.899, comparable to the score of human experts, and it outperforms state-of-the-art approaches.

Accurate acceleration of kinetic Monte Carlo simulations through the modification of rate constants.

PubMed

Chatterjee, Abhijit; Voter, Arthur F

2010-05-21

We present a novel computational algorithm called the accelerated superbasin kinetic Monte Carlo (AS-KMC) method that enables a more efficient study of rare-event dynamics than the standard KMC method while maintaining control over the error. In AS-KMC, the rate constants for processes that are observed many times are lowered during the course of a simulation. As a result, rare processes are observed more frequently than in KMC and the time progresses faster. We first derive error estimates for AS-KMC when the rate constants are modified. These error estimates are next employed to develop a procedure for lowering process rates with control over the maximum error. Finally, numerical calculations are performed to demonstrate that the AS-KMC method captures the correct dynamics, while providing significant CPU savings over KMC in most cases. We show that the AS-KMC method can be employed with any KMC model, even when no time scale separation is present (although in such cases no computational speed-up is observed), without requiring the knowledge of various time scales present in the system.

Mobile Phone Call Data as a Regional Socio-Economic Proxy Indicator

PubMed Central

Šćepanović, Sanja; Mishkovski, Igor; Hui, Pan; Nurminen, Jukka K.; Ylä-Jääski, Antti

2015-01-01

The advent of publishing anonymized call detail records opens the door for temporal and spatial human dynamics studies. Such studies, besides being useful for creating universal models for mobility patterns, could be also used for creating new socio-economic proxy indicators that will not rely only on the local or state institutions. In this paper, from the frequency of calls at different times of the day, in different small regional units (sub-prefectures) in Côte d'Ivoire, we infer users' home and work sub-prefectures. This division of users enables us to analyze different mobility and calling patterns for the different regions. We then compare how those patterns correlate to the data from other sources, such as: news for particular events in the given period, census data, economic activity, poverty index, power plants and energy grid data. Our results show high correlation in many of the cases revealing the diversity of socio-economic insights that can be inferred using only mobile phone call data. The methods and the results may be particularly relevant to policy-makers engaged in poverty reduction initiatives as they can provide an affordable tool in the context of resource-constrained developing economies, such as Côte d'Ivoire's. PMID:25897957

Transport induced by mean-eddy interaction: I. Theory, and relation to Lagrangian lobe dynamics

NASA Astrophysics Data System (ADS)

Ide, Kayo; Wiggins, Stephen

2015-02-01

In this paper we develop a method for the estimation of Transport Induced by the Mean-Eddy interaction (TIME) in two-dimensional unsteady flows. The method is based on the dynamical systems approach to fluid transport and can be viewed as a hybrid combination of Lagrangian and Eulerian methods. The (Eulerian) boundaries across which we consider (Lagrangian) transport are kinematically defined by appropriately chosen streamlines of the mean flow. By evaluating the impact of the mean-eddy interaction on transport, the TIME method can be used as a diagnostic tool for transport processes that occur during a specified time interval along a specified boundary segment. We introduce two types of TIME functions: one that quantifies the accumulation of flow properties and another that measures the displacement of the transport geometry. The spatial geometry of transport is described by the so-called pseudo-lobes, and temporal evolution of transport by their dynamics. In the case where the TIME functions are evaluated along a separatrix, the pseudo-lobes have a relationship to the lobes of Lagrangian transport theory. In fact, one of the TIME functions is identical to the Melnikov function that is used to measure the distance, at leading order in a small parameter, between the two invariant manifolds that define the Lagrangian lobes. We contrast the similarities and differences between the TIME and Lagrangian lobe dynamics in detail. An application of the TIME method is carried out for inter-gyre transport in the wind-driven oceanic circulation model and a comparison with the Lagrangian transport theory is made.

An interactive graphics program to retrieve, display, compare, manipulate, curve fit, difference and cross plot wind tunnel data

NASA Technical Reports Server (NTRS)

Elliott, R. D.; Werner, N. M.; Baker, W. M.

1975-01-01

The Aerodynamic Data Analysis and Integration System (ADAIS), developed as a highly interactive computer graphics program capable of manipulating large quantities of data such that addressable elements of a data base can be called up for graphic display, compared, curve fit, stored, retrieved, differenced, etc., was described. The general nature of the system is evidenced by the fact that limited usage has already occurred with data bases consisting of thermodynamic, basic loads, and flight dynamics data. Productivity using ADAIS of five times that for conventional manual methods of wind tunnel data analysis is routinely achieved. In wind tunnel data analysis, data from one or more runs of a particular test may be called up and displayed along with data from one or more runs of a different test. Curves may be faired through the data points by any of four methods, including cubic spline and least squares polynomial fit up to seventh order.

Time Dependent Tomography of the Solar Corona in Three Spatial Dimensions

NASA Astrophysics Data System (ADS)

Butala, M. D.; Frazin, R. A.; Kamalabadi, F.

2006-12-01

The combination of the soon to be launched STEREO mission with SOHO will provide scientists with three simultaneous space-borne views of the Sun. The increase in available measurements will reduce the data acquisition time necessary to obtain 3D coronal electron density (N_e) estimates from coronagraph images using a technique called solar rotational tomography (SRT). However, the data acquisition period will still be long enough for the corona to dynamically evolve, requiring time dependent solar tomography. The Kalman filter (KF) would seem to be an ideal computational method for time dependent SRT. Unfortunately, the KF scales poorly with problem size and is, as a result, inapplicable. A Monte Carlo approximation to the KF called the localized ensemble Kalman filter was developed for massive applications and has the promise of making the time dependent estimation of the 3D coronal N_e possible. We present simulations showing that this method will make time dependent tomography in three spatial dimensions computationally feasible.

Dynamic optimization of distributed biological systems using robust and efficient numerical techniques.

PubMed

Vilas, Carlos; Balsa-Canto, Eva; García, Maria-Sonia G; Banga, Julio R; Alonso, Antonio A

2012-07-02

Systems biology allows the analysis of biological systems behavior under different conditions through in silico experimentation. The possibility of perturbing biological systems in different manners calls for the design of perturbations to achieve particular goals. Examples would include, the design of a chemical stimulation to maximize the amplitude of a given cellular signal or to achieve a desired pattern in pattern formation systems, etc. Such design problems can be mathematically formulated as dynamic optimization problems which are particularly challenging when the system is described by partial differential equations.This work addresses the numerical solution of such dynamic optimization problems for spatially distributed biological systems. The usual nonlinear and large scale nature of the mathematical models related to this class of systems and the presence of constraints on the optimization problems, impose a number of difficulties, such as the presence of suboptimal solutions, which call for robust and efficient numerical techniques. Here, the use of a control vector parameterization approach combined with efficient and robust hybrid global optimization methods and a reduced order model methodology is proposed. The capabilities of this strategy are illustrated considering the solution of a two challenging problems: bacterial chemotaxis and the FitzHugh-Nagumo model. In the process of chemotaxis the objective was to efficiently compute the time-varying optimal concentration of chemotractant in one of the spatial boundaries in order to achieve predefined cell distribution profiles. Results are in agreement with those previously published in the literature. The FitzHugh-Nagumo problem is also efficiently solved and it illustrates very well how dynamic optimization may be used to force a system to evolve from an undesired to a desired pattern with a reduced number of actuators. The presented methodology can be used for the efficient dynamic optimization of generic distributed biological systems.

Multiscale simulations of patchy particle systems combining Molecular Dynamics, Path Sampling and Green's Function Reaction Dynamics

NASA Astrophysics Data System (ADS)

Bolhuis, Peter

Important reaction-diffusion processes, such as biochemical networks in living cells, or self-assembling soft matter, span many orders in length and time scales. In these systems, the reactants' spatial dynamics at mesoscopic length and time scales of microns and seconds is coupled to the reactions between the molecules at microscopic length and time scales of nanometers and milliseconds. This wide range of length and time scales makes these systems notoriously difficult to simulate. While mean-field rate equations cannot describe such processes, the mesoscopic Green's Function Reaction Dynamics (GFRD) method enables efficient simulation at the particle level provided the microscopic dynamics can be integrated out. Yet, many processes exhibit non-trivial microscopic dynamics that can qualitatively change the macroscopic behavior, calling for an atomistic, microscopic description. The recently developed multiscale Molecular Dynamics Green's Function Reaction Dynamics (MD-GFRD) approach combines GFRD for simulating the system at the mesocopic scale where particles are far apart, with microscopic Molecular (or Brownian) Dynamics, for simulating the system at the microscopic scale where reactants are in close proximity. The association and dissociation of particles are treated with rare event path sampling techniques. I will illustrate the efficiency of this method for patchy particle systems. Replacing the microscopic regime with a Markov State Model avoids the microscopic regime completely. The MSM is then pre-computed using advanced path-sampling techniques such as multistate transition interface sampling. I illustrate this approach on patchy particle systems that show multiple modes of binding. MD-GFRD is generic, and can be used to efficiently simulate reaction-diffusion systems at the particle level, including the orientational dynamics, opening up the possibility for large-scale simulations of e.g. protein signaling networks.

An ontology-based nurse call management system (oNCS) with probabilistic priority assessment

PubMed Central

2011-01-01

Background The current, place-oriented nurse call systems are very static. A patient can only make calls with a button which is fixed to a wall of a room. Moreover, the system does not take into account various factors specific to a situation. In the future, there will be an evolution to a mobile button for each patient so that they can walk around freely and still make calls. The system would become person-oriented and the available context information should be taken into account to assign the correct nurse to a call. The aim of this research is (1) the design of a software platform that supports the transition to mobile and wireless nurse call buttons in hospitals and residential care and (2) the design of a sophisticated nurse call algorithm. This algorithm dynamically adapts to the situation at hand by taking the profile information of staff members and patients into account. Additionally, the priority of a call probabilistically depends on the risk factors, assigned to a patient. Methods The ontology-based Nurse Call System (oNCS) was developed as an extension of a Context-Aware Service Platform. An ontology is used to manage the profile information. Rules implement the novel nurse call algorithm that takes all this information into account. Probabilistic reasoning algorithms are designed to determine the priority of a call based on the risk factors of the patient. Results The oNCS system is evaluated through a prototype implementation and simulations, based on a detailed dataset obtained from Ghent University Hospital. The arrival times of nurses at the location of a call, the workload distribution of calls amongst nurses and the assignment of priorities to calls are compared for the oNCS system and the current, place-oriented nurse call system. Additionally, the performance of the system is discussed. Conclusions The execution time of the nurse call algorithm is on average 50.333 ms. Moreover, the oNCS system significantly improves the assignment of nurses to calls. Calls generally have a nurse present faster and the workload-distribution amongst the nurses improves. PMID:21294860

Time-resolved investigations of the non-thermal ablation process of graphite induced by femtosecond laser pulses

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

Kalupka, C., E-mail: christian.kalupka@llt.rwth-aachen.de; Finger, J.; Reininghaus, M.

2016-04-21

We report on the in-situ analysis of the ablation dynamics of the, so-called, laser induced non-thermal ablation process of graphite. A highly oriented pyrolytic graphite is excited by femtosecond laser pulses with fluences below the classic thermal ablation threshold. The ablation dynamics are investigated by axial pump-probe reflection measurements, transversal pump-probe shadowgraphy, and time-resolved transversal emission photography. The combination of the applied analysis methods allows for a continuous and detailed time-resolved observation of the non-thermal ablation dynamics from several picoseconds up to 180 ns. Formation of large, μm-sized particles takes place within the first 3.5 ns after irradiation. The following propagation ofmore » ablation products and the shock wave front are tracked by transversal shadowgraphy up to 16 ns. The comparison of ablation dynamics of different fluences by emission photography reveals thermal ablation products even for non-thermal fluences.« less

AMA- and RWE- Based Adaptive Kalman Filter for Denoising Fiber Optic Gyroscope Drift Signal

PubMed Central

Yang, Gongliu; Liu, Yuanyuan; Li, Ming; Song, Shunguang

2015-01-01

An improved double-factor adaptive Kalman filter called AMA-RWE-DFAKF is proposed to denoise fiber optic gyroscope (FOG) drift signal in both static and dynamic conditions. The first factor is Kalman gain updated by random weighting estimation (RWE) of the covariance matrix of innovation sequence at any time to ensure the lowest noise level of output, but the inertia of KF response increases in dynamic condition. To decrease the inertia, the second factor is the covariance matrix of predicted state vector adjusted by RWE only when discontinuities are detected by adaptive moving average (AMA).The AMA-RWE-DFAKF is applied for denoising FOG static and dynamic signals, its performance is compared with conventional KF (CKF), RWE-based adaptive KF with gain correction (RWE-AKFG), AMA- and RWE- based dual mode adaptive KF (AMA-RWE-DMAKF). Results of Allan variance on static signal and root mean square error (RMSE) on dynamic signal show that this proposed algorithm outperforms all the considered methods in denoising FOG signal. PMID:26512665

AMA- and RWE- Based Adaptive Kalman Filter for Denoising Fiber Optic Gyroscope Drift Signal.

PubMed

Yang, Gongliu; Liu, Yuanyuan; Li, Ming; Song, Shunguang

2015-10-23

An improved double-factor adaptive Kalman filter called AMA-RWE-DFAKF is proposed to denoise fiber optic gyroscope (FOG) drift signal in both static and dynamic conditions. The first factor is Kalman gain updated by random weighting estimation (RWE) of the covariance matrix of innovation sequence at any time to ensure the lowest noise level of output, but the inertia of KF response increases in dynamic condition. To decrease the inertia, the second factor is the covariance matrix of predicted state vector adjusted by RWE only when discontinuities are detected by adaptive moving average (AMA).The AMA-RWE-DFAKF is applied for denoising FOG static and dynamic signals, its performance is compared with conventional KF (CKF), RWE-based adaptive KF with gain correction (RWE-AKFG), AMA- and RWE- based dual mode adaptive KF (AMA-RWE-DMAKF). Results of Allan variance on static signal and root mean square error (RMSE) on dynamic signal show that this proposed algorithm outperforms all the considered methods in denoising FOG signal.

Dynamically stable multiply quantized vortices in dilute Bose-Einstein condensates

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

Huhtamaeki, J. A. M.; Virtanen, S. M. M.; Moettoenen, M.

2006-12-15

Multiquantum vortices in dilute atomic Bose-Einstein condensates confined in long cigar-shaped traps are known to be both energetically and dynamically unstable. They tend to split into single-quantum vortices even in the ultralow temperature limit with vanishingly weak dissipation, which has also been confirmed in the recent experiments [Y. Shin et al., Phys. Rev. Lett. 93, 160406 (2004)] utilizing the so-called topological phase engineering method to create multiquantum vortices. We study the stability properties of multiquantum vortices in different trap geometries by solving the Bogoliubov excitation spectra for such states. We find that there are regions in the trap asymmetry andmore » condensate interaction strength plane in which the splitting instability of multiquantum vortices is suppressed, and hence they are dynamically stable. For example, the doubly quantized vortex can be made dynamically stable even in spherical traps within a wide range of interaction strength values. We expect that this suppression of vortex-splitting instability can be experimentally verified.« less

Connection forces in deformable multibody dynamics

NASA Technical Reports Server (NTRS)

Shabana, A. A.; Chang, C. W.

1989-01-01

In the dynamic formulation of holonomic and nonholonomic systems based on D'Alembert-Lagrange equation, the forces of constraints are maintained in the dynamic equations by introducing auxiliary variables, called Lagrange multipliers. This approach introduces a set of generalized reaction forces associated with the system generalized coordinates. Different sets of variables can be used as generalized coordinates and accordingly, the generalized reactions associated with these generalized coordinates may not be the actual reaction forces at the joints. In rigid body dynamics, the generalized reaction forces and the actual reaction forces at the joints represent equipollent systems of forces since they produce the same total forces and moments at and about any point on the rigid body. This is not, however, the case in deformable body analyses wherein the generalized reaction forces depend on the system generalized reference and elastic coordinates. In this paper, a method for determining the actual reaction forces at the joints from the generalized reaction forces in deformable multibody systems is presented.

Dynamic contrast optical coherence tomography images transit time and quantifies microvascular plasma volume and flow in the retina and choriocapillaris

PubMed Central

Merkle, Conrad W.; Leahy, Conor; Srinivasan, Vivek J.

2016-01-01

Despite the prevalence of optical imaging techniques to measure hemodynamics in large retinal vessels, quantitative measurements of retinal capillary and choroidal hemodynamics have traditionally been challenging. Here, a new imaging technique called dynamic contrast optical coherence tomography (DyC-OCT) is applied in the rat eye to study microvascular blood flow in individual retinal and choroidal layers in vivo. DyC-OCT is based on imaging the transit of an intravascular tracer dynamically as it passes through the field-of-view. Hemodynamic parameters can be determined through quantitative analysis of tracer kinetics. In addition to enabling depth-resolved transit time, volume, and flow measurements, the injected tracer also enhances OCT angiograms and enables clear visualization of the choriocapillaris, particularly when combined with a post-processing method for vessel enhancement. DyC-OCT complements conventional OCT angiography through quantification of tracer dynamics, similar to fluorescence angiography, but with the important added benefit of laminar resolution. PMID:27867732

Dynamic contrast optical coherence tomography images transit time and quantifies microvascular plasma volume and flow in the retina and choriocapillaris.

PubMed

Merkle, Conrad W; Leahy, Conor; Srinivasan, Vivek J

2016-10-01

Despite the prevalence of optical imaging techniques to measure hemodynamics in large retinal vessels, quantitative measurements of retinal capillary and choroidal hemodynamics have traditionally been challenging. Here, a new imaging technique called dynamic contrast optical coherence tomography (DyC-OCT) is applied in the rat eye to study microvascular blood flow in individual retinal and choroidal layers in vivo . DyC-OCT is based on imaging the transit of an intravascular tracer dynamically as it passes through the field-of-view. Hemodynamic parameters can be determined through quantitative analysis of tracer kinetics. In addition to enabling depth-resolved transit time, volume, and flow measurements, the injected tracer also enhances OCT angiograms and enables clear visualization of the choriocapillaris, particularly when combined with a post-processing method for vessel enhancement. DyC-OCT complements conventional OCT angiography through quantification of tracer dynamics, similar to fluorescence angiography, but with the important added benefit of laminar resolution.

Dynamical Causal Modeling from a Quantum Dynamical Perspective

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

Demiralp, Emre; Demiralp, Metin

Recent research suggests that any set of first order linear vector ODEs can be converted to a set of specific vector ODEs adhering to what we have called ''Quantum Harmonical Form (QHF)''. QHF has been developed using a virtual quantum multi harmonic oscillator system where mass and force constants are considered to be time variant and the Hamiltonian is defined as a conic structure over positions and momenta to conserve the Hermiticity. As described in previous works, the conversion to QHF requires the matrix coefficient of the first set of ODEs to be a normal matrix. In this paper, thismore » limitation is circumvented using a space extension approach expanding the potential applicability of this method. Overall, conversion to QHF allows the investigation of a set of ODEs using mathematical tools available to the investigation of the physical concepts underlying quantum harmonic oscillators. The utility of QHF in the context of dynamical systems and dynamical causal modeling in behavioral and cognitive neuroscience is briefly discussed.« less

A CLASS OF RECONSTRUCTED DISCONTINUOUS GALERKIN METHODS IN COMPUTATIONAL FLUID DYNAMICS

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

Hong Luo; Yidong Xia; Robert Nourgaliev

2011-05-01

A class of reconstructed discontinuous Galerkin (DG) methods is presented to solve compressible flow problems on arbitrary grids. The idea is to combine the efficiency of the reconstruction methods in finite volume methods and the accuracy of the DG methods to obtain a better numerical algorithm in computational fluid dynamics. The beauty of the resulting reconstructed discontinuous Galerkin (RDG) methods is that they provide a unified formulation for both finite volume and DG methods, and contain both classical finite volume and standard DG methods as two special cases of the RDG methods, and thus allow for a direct efficiency comparison.more » Both Green-Gauss and least-squares reconstruction methods and a least-squares recovery method are presented to obtain a quadratic polynomial representation of the underlying linear discontinuous Galerkin solution on each cell via a so-called in-cell reconstruction process. The devised in-cell reconstruction is aimed to augment the accuracy of the discontinuous Galerkin method by increasing the order of the underlying polynomial solution. These three reconstructed discontinuous Galerkin methods are used to compute a variety of compressible flow problems on arbitrary meshes to assess their accuracy. The numerical experiments demonstrate that all three reconstructed discontinuous Galerkin methods can significantly improve the accuracy of the underlying second-order DG method, although the least-squares reconstructed DG method provides the best performance in terms of both accuracy, efficiency, and robustness.« less

Interpolating moving least-squares methods for fitting potential energy surfaces: using classical trajectories to explore configuration space.

PubMed

Dawes, Richard; Passalacqua, Alessio; Wagner, Albert F; Sewell, Thomas D; Minkoff, Michael; Thompson, Donald L

2009-04-14

We develop two approaches for growing a fitted potential energy surface (PES) by the interpolating moving least-squares (IMLS) technique using classical trajectories. We illustrate both approaches by calculating nitrous acid (HONO) cis-->trans isomerization trajectories under the control of ab initio forces from low-level HF/cc-pVDZ electronic structure calculations. In this illustrative example, as few as 300 ab initio energy/gradient calculations are required to converge the isomerization rate constant at a fixed energy to approximately 10%. Neither approach requires any preliminary electronic structure calculations or initial approximate representation of the PES (beyond information required for trajectory initial conditions). Hessians are not required. Both approaches rely on the fitting error estimation properties of IMLS fits. The first approach, called IMLS-accelerated direct dynamics, propagates individual trajectories directly with no preliminary exploratory trajectories. The PES is grown "on the fly" with the computation of new ab initio data only when a fitting error estimate exceeds a prescribed tight tolerance. The second approach, called dynamics-driven IMLS fitting, uses relatively inexpensive exploratory trajectories to both determine and fit the dynamically accessible configuration space. Once exploratory trajectories no longer find configurations with fitting error estimates higher than the designated accuracy, the IMLS fit is considered to be complete and usable in classical trajectory calculations or other applications.

Crew exploration vehicle (CEV) attitude control using a neural-immunology/memory network

NASA Astrophysics Data System (ADS)

Weng, Liguo; Xia, Min; Wang, Wei; Liu, Qingshan

2015-01-01

This paper addresses the problem of the crew exploration vehicle (CEV) attitude control. CEVs are NASA's next-generation human spaceflight vehicles, and they use reaction control system (RCS) jet engines for attitude adjustment, which calls for control algorithms for firing the small propulsion engines mounted on vehicles. In this work, the resultant CEV dynamics combines both actuation and attitude dynamics. Therefore, it is highly nonlinear and even coupled with significant uncertainties. To cope with this situation, a neural-immunology/memory network is proposed. It is inspired by the human memory and immune systems. The control network does not rely on precise system dynamics information. Furthermore, the overall control scheme has a simple structure and demands much less computation as compared with most existing methods, making it attractive for real-time implementation. The effectiveness of this approach is also verified via simulation.

Using directed information for influence discovery in interconnected dynamical systems

NASA Astrophysics Data System (ADS)

Rao, Arvind; Hero, Alfred O.; States, David J.; Engel, James Douglas

2008-08-01

Structure discovery in non-linear dynamical systems is an important and challenging problem that arises in various applications such as computational neuroscience, econometrics, and biological network discovery. Each of these systems have multiple interacting variables and the key problem is the inference of the underlying structure of the systems (which variables are connected to which others) based on the output observations (such as multiple time trajectories of the variables). Since such applications demand the inference of directed relationships among variables in these non-linear systems, current methods that have a linear assumption on structure or yield undirected variable dependencies are insufficient. Hence, in this work, we present a methodology for structure discovery using an information-theoretic metric called directed time information (DTI). Using both synthetic dynamical systems as well as true biological datasets (kidney development and T-cell data), we demonstrate the utility of DTI in such problems.

Inferring Biological Structures from Super-Resolution Single Molecule Images Using Generative Models

PubMed Central

Maji, Suvrajit; Bruchez, Marcel P.

2012-01-01

Localization-based super resolution imaging is presently limited by sampling requirements for dynamic measurements of biological structures. Generating an image requires serial acquisition of individual molecular positions at sufficient density to define a biological structure, increasing the acquisition time. Efficient analysis of biological structures from sparse localization data could substantially improve the dynamic imaging capabilities of these methods. Using a feature extraction technique called the Hough Transform simple biological structures are identified from both simulated and real localization data. We demonstrate that these generative models can efficiently infer biological structures in the data from far fewer localizations than are required for complete spatial sampling. Analysis at partial data densities revealed efficient recovery of clathrin vesicle size distributions and microtubule orientation angles with as little as 10% of the localization data. This approach significantly increases the temporal resolution for dynamic imaging and provides quantitatively useful biological information. PMID:22629348

PLUM: Parallel Load Balancing for Adaptive Unstructured Meshes

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Biswas, Rupak; Saini, Subhash (Technical Monitor)

1998-01-01

Mesh adaption is a powerful tool for efficient unstructured-grid computations but causes load imbalance among processors on a parallel machine. We present a novel method called PLUM to dynamically balance the processor workloads with a global view. This paper presents the implementation and integration of all major components within our dynamic load balancing strategy for adaptive grid calculations. Mesh adaption, repartitioning, processor assignment, and remapping are critical components of the framework that must be accomplished rapidly and efficiently so as not to cause a significant overhead to the numerical simulation. A data redistribution model is also presented that predicts the remapping cost on the SP2. This model is required to determine whether the gain from a balanced workload distribution offsets the cost of data movement. Results presented in this paper demonstrate that PLUM is an effective dynamic load balancing strategy which remains viable on a large number of processors.

Special Features of Galactic Dynamics

NASA Astrophysics Data System (ADS)

Efthymiopoulos, Christos; Voglis, Nikos; Kalapotharakos, Constantinos

This is an introductory article to some basic notions and currently open problems of galactic dynamics. The focus is on topics mostly relevant to the so-called `new methods' of celestial mechanics or Hamiltonian dynamics, as applied to the ellipsoidal components of galaxies, i.e., to the elliptical galaxies and to the dark halos and bulges of disk galaxies. Traditional topics such as Jeans theorem, the role of a `third integral' of motion, Nekhoroshev theory, violent relaxation, and the statistical mechanics of collisionless stellar systems are first discussed. The emphasis is on modern extrapolations of these old topics. Recent results from orbital and global dynamical studies of galaxies are then shortly reviewed. The role of various families of orbits in supporting self-consistency, as well as the role of chaos in galaxies, are stressed. A description is then given of the main numerical techniques of integration of the N-body problem in the framework of stellar dynamics and of the results obtained via N-Body experiments. A final topic is the secular evolution and self-organization of galactic systems.

Dynamic Modeling of Solar Dynamic Components and Systems

NASA Technical Reports Server (NTRS)

Hochstein, John I.; Korakianitis, T.

1992-01-01

The purpose of this grant was to support NASA in modeling efforts to predict the transient dynamic and thermodynamic response of the space station solar dynamic power generation system. In order to meet the initial schedule requirement of providing results in time to support installation of the system as part of the initial phase of space station, early efforts were executed with alacrity and often in parallel. Initially, methods to predict the transient response of a Rankine as well as a Brayton cycle were developed. Review of preliminary design concepts led NASA to select a regenerative gas-turbine cycle using a helium-xenon mixture as the working fluid and, from that point forward, the modeling effort focused exclusively on that system. Although initial project planning called for a three year period of performance, revised NASA schedules moved system installation to later and later phases of station deployment. Eventually, NASA selected to halt development of the solar dynamic power generation system for space station and to reduce support for this project to two-thirds of the original level.

Free-Swinging Failure Tolerance for Robotic Manipulators

NASA Technical Reports Server (NTRS)

English, James

1997-01-01

Under this GSRP fellowship, software-based failure-tolerance techniques were developed for robotic manipulators. The focus was on failures characterized by the loss of actuator torque at a joint, called free-swinging failures. The research results spanned many aspects of the free-swinging failure-tolerance problem, from preparing for an expected failure to discovery of postfailure capabilities to establishing efficient methods to realize those capabilities. Developed algorithms were verified using computer-based dynamic simulations, and these were further verified using hardware experiments at Johnson Space Center.

A Localized Ensemble Kalman Smoother

NASA Technical Reports Server (NTRS)

Butala, Mark D.

2012-01-01

Numerous geophysical inverse problems prove difficult because the available measurements are indirectly related to the underlying unknown dynamic state and the physics governing the system may involve imperfect models or unobserved parameters. Data assimilation addresses these difficulties by combining the measurements and physical knowledge. The main challenge in such problems usually involves their high dimensionality and the standard statistical methods prove computationally intractable. This paper develops and addresses the theoretical convergence of a new high-dimensional Monte-Carlo approach called the localized ensemble Kalman smoother.

[Body language group: depersonalization and repersonalization using make-up].

PubMed

Quidu, M; Tabary, C

1981-04-01

Make up was used as a support by a corporal expression group which met two hours a week during three months. This method call particularly for tact and sight, the importance of these factors being well known to attain the elaboration and the integration of body scheme. In a recreative, therefore reassuring context, reinforced by the group phenomenon, the dynamism of gesture and relationship extends far beyond the features. The trends of make-up during the sessions and themes based on mimesis allowed to measure progress.

The human dynamic clamp as a paradigm for social interaction

PubMed Central

Dumas, Guillaume; de Guzman, Gonzalo C.; Tognoli, Emmanuelle; Kelso, J. A. Scott

2014-01-01

Social neuroscience has called for new experimental paradigms aimed toward real-time interactions. A distinctive feature of interactions is mutual information exchange: One member of a pair changes in response to the other while simultaneously producing actions that alter the other. Combining mathematical and neurophysiological methods, we introduce a paradigm called the human dynamic clamp (HDC), to directly manipulate the interaction or coupling between a human and a surrogate constructed to behave like a human. Inspired by the dynamic clamp used so productively in cellular neuroscience, the HDC allows a person to interact in real time with a virtual partner itself driven by well-established models of coordination dynamics. People coordinate hand movements with the visually observed movements of a virtual hand, the parameters of which depend on input from the subject’s own movements. We demonstrate that HDC can be extended to cover a broad repertoire of human behavior, including rhythmic and discrete movements, adaptation to changes of pacing, and behavioral skill learning as specified by a virtual “teacher.” We propose HDC as a general paradigm, best implemented when empirically verified theoretical or mathematical models have been developed in a particular scientific field. The HDC paradigm is powerful because it provides an opportunity to explore parameter ranges and perturbations that are not easily accessible in ordinary human interactions. The HDC not only enables to test the veracity of theoretical models, it also illuminates features that are not always apparent in real-time human social interactions and the brain correlates thereof. PMID:25114256

Absence of effects of an in-plane magnetic field in a quasi-two-dimensional electron system

NASA Astrophysics Data System (ADS)

Brandt, F. T.; Sánchez-Monroy, J. A.

2018-03-01

The dynamics of a quasi-two-dimensional electron system (q2DES) in the presence of a tilted magnetic field is reconsidered employing the thin-layer method. We derive the effective equations for relativistic and nonrelativistic q2DESs. Through a perturbative expansion, we show that while the magnetic length is much greater than the confinement width, the in-plane magnetic field only affects the particle dynamics through the spin. Therefore, effects due to an in-plane magnetic vector potential reported previously in the literature for 2D quantum rings, 2D quantum dots and graphene are fictitious. In particular, the so-called pseudo chiral magnetic effect recently proposed in graphene is not realistic.

Molecular Dynamic Simulation of Water Vapor and Determination of Diffusion Characteristics in the Pore

NASA Astrophysics Data System (ADS)

Nikonov, Eduard G.; Pavluš, Miron; Popovičová, Mária

2018-02-01

One of the varieties of pores, often found in natural or artificial building materials, are the so-called blind pores of dead-end or saccate type. Three-dimensional model of such kind of pore has been developed in this work. This model has been used for simulation of water vapor interaction with individual pore by molecular dynamics in combination with the diffusion equation method. Special investigations have been done to find dependencies between thermostats implementations and conservation of thermodynamic and statistical values of water vapor - pore system. The two types of evolution of water - pore system have been investigated: drying and wetting of the pore. Full research of diffusion coefficient, diffusion velocity and other diffusion parameters has been made.

Collective phase description of oscillatory convection

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

Kawamura, Yoji, E-mail: ykawamura@jamstec.go.jp; Nakao, Hiroya

We formulate a theory for the collective phase description of oscillatory convection in Hele-Shaw cells. It enables us to describe the dynamics of the oscillatory convection by a single degree of freedom which we call the collective phase. The theory can be considered as a phase reduction method for limit-cycle solutions in infinite-dimensional dynamical systems, namely, stable time-periodic solutions to partial differential equations, representing the oscillatory convection. We derive the phase sensitivity function, which quantifies the phase response of the oscillatory convection to weak perturbations applied at each spatial point, and analyze the phase synchronization between two weakly coupled Hele-Shawmore » cells exhibiting oscillatory convection on the basis of the derived phase equations.« less

Terminal Model Of Newtonian Dynamics

NASA Technical Reports Server (NTRS)

Zak, Michail

1994-01-01

Paper presents study of theory of Newtonian dynamics of terminal attractors and repellers, focusing on issues of reversibility vs. irreversibility and deterministic evolution vs. probabilistic or chaotic evolution of dynamic systems. Theory developed called "terminal dynamics" emphasizes difference between it and classical Newtonian dynamics. Also holds promise for explaining irreversibility, unpredictability, probabilistic behavior, and chaos in turbulent flows, in thermodynamic phenomena, and in other dynamic phenomena and systems.

Malware Analysis Using Visualized Image Matrices

PubMed Central

Im, Eul Gyu

2014-01-01

This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively. PMID:25133202

Joint state and parameter estimation of the hemodynamic model by particle smoother expectation maximization method

NASA Astrophysics Data System (ADS)

Aslan, Serdar; Taylan Cemgil, Ali; Akın, Ata

2016-08-01

Objective. In this paper, we aimed for the robust estimation of the parameters and states of the hemodynamic model by using blood oxygen level dependent signal. Approach. In the fMRI literature, there are only a few successful methods that are able to make a joint estimation of the states and parameters of the hemodynamic model. In this paper, we implemented a maximum likelihood based method called the particle smoother expectation maximization (PSEM) algorithm for the joint state and parameter estimation. Main results. Former sequential Monte Carlo methods were only reliable in the hemodynamic state estimates. They were claimed to outperform the local linearization (LL) filter and the extended Kalman filter (EKF). The PSEM algorithm is compared with the most successful method called square-root cubature Kalman smoother (SCKS) for both state and parameter estimation. SCKS was found to be better than the dynamic expectation maximization (DEM) algorithm, which was shown to be a better estimator than EKF, LL and particle filters. Significance. PSEM was more accurate than SCKS for both the state and the parameter estimation. Hence, PSEM seems to be the most accurate method for the system identification and state estimation for the hemodynamic model inversion literature. This paper do not compare its results with Tikhonov-regularized Newton—CKF (TNF-CKF), a recent robust method which works in filtering sense.

An information theory framework for dynamic functional domain connectivity.

PubMed

Vergara, Victor M; Miller, Robyn; Calhoun, Vince

2017-06-01

Dynamic functional network connectivity (dFNC) analyzes time evolution of coherent activity in the brain. In this technique dynamic changes are considered for the whole brain. This paper proposes an information theory framework to measure information flowing among subsets of functional networks call functional domains. Our method aims at estimating bits of information contained and shared among domains. The succession of dynamic functional states is estimated at the domain level. Information quantity is based on the probabilities of observing each dynamic state. Mutual information measurement is then obtained from probabilities across domains. Thus, we named this value the cross domain mutual information (CDMI). Strong CDMIs were observed in relation to the subcortical domain. Domains related to sensorial input, motor control and cerebellum form another CDMI cluster. Information flow among other domains was seldom found. Other methods of dynamic connectivity focus on whole brain dFNC matrices. In the current framework, information theory is applied to states estimated from pairs of multi-network functional domains. In this context, we apply information theory to measure information flow across functional domains. Identified CDMI clusters point to known information pathways in the basal ganglia and also among areas of sensorial input, patterns found in static functional connectivity. In contrast, CDMI across brain areas of higher level cognitive processing follow a different pattern that indicates scarce information sharing. These findings show that employing information theory to formally measured information flow through brain domains reveals additional features of functional connectivity. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimating varying coefficients for partial differential equation models.

PubMed

Zhang, Xinyu; Cao, Jiguo; Carroll, Raymond J

2017-09-01

Partial differential equations (PDEs) are used to model complex dynamical systems in multiple dimensions, and their parameters often have important scientific interpretations. In some applications, PDE parameters are not constant but can change depending on the values of covariates, a feature that we call varying coefficients. We propose a parameter cascading method to estimate varying coefficients in PDE models from noisy data. Our estimates of the varying coefficients are shown to be consistent and asymptotically normally distributed. The performance of our method is evaluated by a simulation study and by an empirical study estimating three varying coefficients in a PDE model arising from LIDAR data. © 2017, The International Biometric Society.

An alternative to unstructured grids for computing gas dynamic flows around arbitrarily complex two-dimensional bodies

NASA Technical Reports Server (NTRS)

Quirk, James J.

1992-01-01

In this paper we describe an approach for dealing with arbitrary complex, two dimensional geometries, the so-called cartesian boundary method. Conceptually, the cartesian boundary method is quite simple. Solid bodies blank out areas of a background, cartesian mesh, and the resultant cut cells are singled out for special attention. However, there are several obstacles that must be overcome in order to achieve a practical scheme. We present a general strategy that overcomes these obstacles, together with some details of our successful conversion of an adaptive mesh algorithm from a body-fitted code to a cartesian boundary code.

The New Maia Detector System: Methods For High Definition Trace Element Imaging Of Natural Material

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

Ryan, C. G.; School of Physics, University of Melbourne, Parkville VIC; CODES Centre of Excellence, University of Tasmania, Hobart TAS

2010-04-06

Motivated by the need for megapixel high definition trace element imaging to capture intricate detail in natural material, together with faster acquisition and improved counting statistics in elemental imaging, a large energy-dispersive detector array called Maia has been developed by CSIRO and BNL for SXRF imaging on the XFM beamline at the Australian Synchrotron. A 96 detector prototype demonstrated the capacity of the system for real-time deconvolution of complex spectral data using an embedded implementation of the Dynamic Analysis method and acquiring highly detailed images up to 77 M pixels spanning large areas of complex mineral sample sections.

The New Maia Detector System: Methods For High Definition Trace Element Imaging Of Natural Material

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

Ryan, C.G.; Siddons, D.P.; Kirkham, R.

2010-05-25

Motivated by the need for megapixel high definition trace element imaging to capture intricate detail in natural material, together with faster acquisition and improved counting statistics in elemental imaging, a large energy-dispersive detector array called Maia has been developed by CSIRO and BNL for SXRF imaging on the XFM beamline at the Australian Synchrotron. A 96 detector prototype demonstrated the capacity of the system for real-time deconvolution of complex spectral data using an embedded implementation of the Dynamic Analysis method and acquiring highly detailed images up to 77 M pixels spanning large areas of complex mineral sample sections.

Application of the Hilbert space average method on heat conduction models.

PubMed

Michel, Mathias; Gemmer, Jochen; Mahler, Günter

2006-01-01

We analyze closed one-dimensional chains of weakly coupled many level systems, by means of the so-called Hilbert space average method (HAM). Subject to some concrete conditions on the Hamiltonian of the system, our theory predicts energy diffusion with respect to a coarse-grained description for almost all initial states. Close to the respective equilibrium, we investigate this behavior in terms of heat transport and derive the heat conduction coefficient. Thus, we are able to show that both heat (energy) diffusive behavior as well as Fourier's law follows from and is compatible with a reversible Schrödinger dynamics on the complete level of description.

Numerical computations of the dynamics of fluidic membranes and vesicles

NASA Astrophysics Data System (ADS)

Barrett, John W.; Garcke, Harald; Nürnberg, Robert

2015-11-01

Vesicles and many biological membranes are made of two monolayers of lipid molecules and form closed lipid bilayers. The dynamical behavior of vesicles is very complex and a variety of forms and shapes appear. Lipid bilayers can be considered as a surface fluid and hence the governing equations for the evolution include the surface (Navier-)Stokes equations, which in particular take the membrane viscosity into account. The evolution is driven by forces stemming from the curvature elasticity of the membrane. In addition, the surface fluid equations are coupled to bulk (Navier-)Stokes equations. We introduce a parametric finite-element method to solve this complex free boundary problem and present the first three-dimensional numerical computations based on the full (Navier-)Stokes system for several different scenarios. For example, the effects of the membrane viscosity, spontaneous curvature, and area difference elasticity (ADE) are studied. In particular, it turns out, that even in the case of no viscosity contrast between the bulk fluids, the tank treading to tumbling transition can be obtained by increasing the membrane viscosity. Besides the classical tank treading and tumbling motions, another mode (called the transition mode in this paper, but originally called the vacillating-breathing mode and subsequently also called trembling, transition, and swinging mode) separating these classical modes appears and is studied by us numerically. We also study how features of equilibrium shapes in the ADE and spontaneous curvature models, like budding behavior or starfish forms, behave in a shear flow.

Volumetric MRI of the lungs during forced expiration.

PubMed

Berman, Benjamin P; Pandey, Abhishek; Li, Zhitao; Jeffries, Lindsie; Trouard, Theodore P; Oliva, Isabel; Cortopassi, Felipe; Martin, Diego R; Altbach, Maria I; Bilgin, Ali

2016-06-01

Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides spatial information but is challenging due to large movement over a short time. The purpose of this work is to provide a solution to lung imaging during forced expiration using accelerated magnetic resonance imaging. The method uses radial golden angle stack-of-stars gradient echo acquisition and compressed sensing reconstruction. A technique for dynamic three-dimensional imaging of the lungs from highly undersampled data is developed and tested on six subjects. This method takes advantage of image sparsity, both spatially and temporally, including the use of reference frames called bookends. Sparsity, with respect to total variation, and residual from the bookends, enables reconstruction from an extremely limited amount of data. Dynamic three-dimensional images can be captured at sub-150 ms temporal resolution, using only three (or less) acquired radial lines per slice per timepoint. The images have a spatial resolution of 4.6×4.6×10 mm. Lung volume calculations based on image segmentation are compared to those from simultaneously acquired spirometer measurements. Dynamic lung imaging during forced expiration is made possible by compressed sensing accelerated dynamic three-dimensional radial magnetic resonance imaging. Magn Reson Med 75:2295-2302, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Modeling repetitive motions using structured light.

PubMed

Xu, Yi; Aliaga, Daniel G

2010-01-01

Obtaining models of dynamic 3D objects is an important part of content generation for computer graphics. Numerous methods have been extended from static scenarios to model dynamic scenes. If the states or poses of the dynamic object repeat often during a sequence (but not necessarily periodically), we call such a repetitive motion. There are many objects, such as toys, machines, and humans, undergoing repetitive motions. Our key observation is that when a motion-state repeats, we can sample the scene under the same motion state again but using a different set of parameters; thus, providing more information of each motion state. This enables robustly acquiring dense 3D information difficult for objects with repetitive motions using only simple hardware. After the motion sequence, we group temporally disjoint observations of the same motion state together and produce a smooth space-time reconstruction of the scene. Effectively, the dynamic scene modeling problem is converted to a series of static scene reconstructions, which are easier to tackle. The varying sampling parameters can be, for example, structured-light patterns, illumination directions, and viewpoints resulting in different modeling techniques. Based on this observation, we present an image-based motion-state framework and demonstrate our paradigm using either a synchronized or an unsynchronized structured-light acquisition method.

A mesoscopic bridging scale method for fluids and coupling dissipative particle dynamics with continuum finite element method

PubMed Central

Kojic, Milos; Filipovic, Nenad; Tsuda, Akira

2012-01-01

A multiscale procedure to couple a mesoscale discrete particle model and a macroscale continuum model of incompressible fluid flow is proposed in this study. We call this procedure the mesoscopic bridging scale (MBS) method since it is developed on the basis of the bridging scale method for coupling molecular dynamics and finite element models [G.J. Wagner, W.K. Liu, Coupling of atomistic and continuum simulations using a bridging scale decomposition, J. Comput. Phys. 190 (2003) 249–274]. We derive the governing equations of the MBS method and show that the differential equations of motion of the mesoscale discrete particle model and finite element (FE) model are only coupled through the force terms. Based on this coupling, we express the finite element equations which rely on the Navier–Stokes and continuity equations, in a way that the internal nodal FE forces are evaluated using viscous stresses from the mesoscale model. The dissipative particle dynamics (DPD) method for the discrete particle mesoscale model is employed. The entire fluid domain is divided into a local domain and a global domain. Fluid flow in the local domain is modeled with both DPD and FE method, while fluid flow in the global domain is modeled by the FE method only. The MBS method is suitable for modeling complex (colloidal) fluid flows, where continuum methods are sufficiently accurate only in the large fluid domain, while small, local regions of particular interest require detailed modeling by mesoscopic discrete particles. Solved examples – simple Poiseuille and driven cavity flows illustrate the applicability of the proposed MBS method. PMID:23814322

Angular dependence of multiangle dynamic light scattering for particle size distribution inversion using a self-adapting regularization algorithm

NASA Astrophysics Data System (ADS)

Li, Lei; Yu, Long; Yang, Kecheng; Li, Wei; Li, Kai; Xia, Min

2018-04-01

The multiangle dynamic light scattering (MDLS) technique can better estimate particle size distributions (PSDs) than single-angle dynamic light scattering. However, determining the inversion range, angular weighting coefficients, and scattering angle combination is difficult but fundamental to the reconstruction for both unimodal and multimodal distributions. In this paper, we propose a self-adapting regularization method called the wavelet iterative recursion nonnegative Tikhonov-Phillips-Twomey (WIRNNT-PT) algorithm. This algorithm combines a wavelet multiscale strategy with an appropriate inversion method and could self-adaptively optimize several noteworthy issues containing the choices of the weighting coefficients, the inversion range and the optimal inversion method from two regularization algorithms for estimating the PSD from MDLS measurements. In addition, the angular dependence of the MDLS for estimating the PSDs of polymeric latexes is thoroughly analyzed. The dependence of the results on the number and range of measurement angles was analyzed in depth to identify the optimal scattering angle combination. Numerical simulations and experimental results for unimodal and multimodal distributions are presented to demonstrate both the validity of the WIRNNT-PT algorithm and the angular dependence of MDLS and show that the proposed algorithm with a six-angle analysis in the 30-130° range can be satisfactorily applied to retrieve PSDs from MDLS measurements.

Characterization and Dynamic Behavior of Wild Yeast during Spontaneous Wine Fermentation in Steel Tanks and Amphorae

PubMed Central

Díaz, Cecilia; Molina, Ana María; Nähring, Jörg; Fischer, Rainer

2013-01-01

We studied the dynamic behavior of wild yeasts during spontaneous wine fermentation at a winery in the Valais region of Switzerland. Wild yeasts in the winery environment were characterized using a PCR-RFLP method. Up to 11 different yeast species were isolated from the vineyard air, whereas only seven were recovered from the grapes surface. We initially investigated a cultureindependent method in pilot-scale steel fermentation tanks and found a greater diversity of yeasts in the musts from two red grape varieties compared to three white grape varieties. We found that the yeasts Metschnikowia pulcherrima, Rhodotorula mucilaginosa, Pichia kluyveri, P. membranifaciens and Saccharomyces cerevisiae remained active at the end of the fermentation. We also studied the dynamic behavior of yeasts in Qvevris for the first time using a novel, highlysensitive quantitative real-time PCR method. We found that non-Saccharomyces yeasts were present during the entire fermentation process, with R. mucilaginosa and P. anomala the most prominent species. We studied the relationship between the predominance of different species and the output of the fermentation process. We identified so-called spoilage yeasts in all the fermentations, but high levels of acetic acid accumulated only in those fermentations with an extended lag phase. PMID:23738327

Quasi-coarse-grained dynamics: modelling of metallic materials at mesoscales

NASA Astrophysics Data System (ADS)

Dongare, Avinash M.

2014-12-01

A computationally efficient modelling method called quasi-coarse-grained dynamics (QCGD) is developed to expand the capabilities of molecular dynamics (MD) simulations to model behaviour of metallic materials at the mesoscales. This mesoscale method is based on solving the equations of motion for a chosen set of representative atoms from an atomistic microstructure and using scaling relationships for the atomic-scale interatomic potentials in MD simulations to define the interactions between representative atoms. The scaling relationships retain the atomic-scale degrees of freedom and therefore energetics of the representative atoms as would be predicted in MD simulations. The total energetics of the system is retained by scaling the energetics and the atomic-scale degrees of freedom of these representative atoms to account for the missing atoms in the microstructure. This scaling of the energetics renders improved time steps for the QCGD simulations. The success of the QCGD method is demonstrated by the prediction of the structural energetics, high-temperature thermodynamics, deformation behaviour of interfaces, phase transformation behaviour, plastic deformation behaviour, heat generation during plastic deformation, as well as the wave propagation behaviour, as would be predicted using MD simulations for a reduced number of representative atoms. The reduced number of atoms and the improved time steps enables the modelling of metallic materials at the mesoscale in extreme environments.

Transport induced by mean-eddy interaction: II. Analysis of transport processes

NASA Astrophysics Data System (ADS)

Ide, Kayo; Wiggins, Stephen

2015-03-01

We present a framework for the analysis of transport processes resulting from the mean-eddy interaction in a flow. The framework is based on the Transport Induced by the Mean-Eddy Interaction (TIME) method presented in a companion paper (Ide and Wiggins, 2014) [1]. The TIME method estimates the (Lagrangian) transport across stationary (Eulerian) boundaries defined by chosen streamlines of the mean flow. Our framework proceeds after first carrying out a sequence of preparatory steps that link the flow dynamics to the transport processes. This includes the construction of the so-called "instantaneous flux" as the Hovmöller diagram. Transport processes are studied by linking the signals of the instantaneous flux field to the dynamical variability of the flow. This linkage also reveals how the variability of the flow contributes to the transport. The spatio-temporal analysis of the flux diagram can be used to assess the efficiency of the variability in transport processes. We apply the method to the double-gyre ocean circulation model in the situation where the Rossby-wave mode dominates the dynamic variability. The spatio-temporal analysis shows that the inter-gyre transport is controlled by the circulating eddy vortices in the fast eastward jet region, whereas the basin-scale Rossby waves have very little impact.

Overview of Single-Molecule Speckle (SiMS) Microscopy and Its Electroporation-Based Version with Efficient Labeling and Improved Spatiotemporal Resolution.

PubMed

Yamashiro, Sawako; Watanabe, Naoki

2017-07-06

Live-cell single-molecule imaging was introduced more than a decade ago, and has provided critical information on remodeling of the actin cytoskeleton, the motion of plasma membrane proteins, and dynamics of molecular motor proteins. Actin remodeling has been the best target for this approach because actin and its associated proteins stop diffusing when assembled, allowing visualization of single-molecules of fluorescently-labeled proteins in a state specific manner. The approach based on this simple principle is called Single-Molecule Speckle (SiMS) microscopy. For instance, spatiotemporal regulation of actin polymerization and lifetime distribution of actin filaments can be monitored directly by tracking actin SiMS. In combination with fluorescently labeled probes of various actin regulators, SiMS microscopy has contributed to clarifying the processes underlying recycling, motion and remodeling of the live-cell actin network. Recently, we introduced an electroporation-based method called eSiMS microscopy, with high efficiency, easiness and improved spatiotemporal precision. In this review, we describe the application of live-cell single-molecule imaging to cellular actin dynamics and discuss the advantages of eSiMS microscopy over previous SiMS microscopy.

A new method for solving routing and wavelength assignment problems under inaccurate routing information in optical networks with conversion capability

NASA Astrophysics Data System (ADS)

Luo, Yanting; Zhang, Yongjun; Gu, Wanyi

2009-11-01

In large dynamic networks it is extremely difficult to maintain accurate routing information on all network nodes. The existing studies have illustrated the impact of imprecise state information on the performance of dynamic routing and wavelength assignment (RWA) algorithms. An algorithm called Bypass Based Optical Routing (BBOR) proposed by Xavier Masip-Bruin et al can reduce the effects of having inaccurate routing information in networks operating under the wavelength-continuity constraint. Then they extended the BBOR mechanism (for convenience it's called EBBOR mechanism below) to be applied to the networks with sparse and limited wavelength conversion. But it only considers the characteristic of wavelength conversion in the step of computing the bypass-paths so that its performance may decline with increasing the degree of wavelength translation (this concept will be explained in the section of introduction again). We will demonstrate the issue through theoretical analysis and introduce a novel algorithm which modifies both the lightpath selection and the bypass-paths computation in comparison to EBBOR algorithm. Simulations show that the Modified EBBOR (MEBBOR) algorithm improves the blocking performance significantly in optical networks with Conversion Capability.

Mistletoe Berry Outline Mapping with a Path Curve Function and Recording the Circadian Rhythm of Their Phenotypic Shape Change

PubMed Central

Derbidge, Renatus; Baumgartner, Stephan; Heusser, Peter

2016-01-01

This paper presents a discovery: the change of the outline shape of mistletoe (Viscum album ssp. album) berries in vivo and in situ during ripening. It was found that a plant organ that is usually considered to merely increase in size actually changes shape in a specific rhythmic fashion. We introduce a new approach to chronobiological research on a macro-phenotypic scale to trace changes over long periods of time (with a resolution from hours to months) by using a dynamic form-determining parameter called Lambda (λ). λ is known in projective geometry as a measure for pertinent features of the outline shapes of egg-like forms, so called path curves. Ascertained circadian changes of form were analyzed for their correlation with environmental factors such as light, temperature, and other weather influences. Certain weather conditions such as sky cover, i.e., sunshine minutes per hour, have an impact on the amplitude of the daily change in form. The present paper suggests a possible supplement to established methods in chronobiology, as in this case the dynamic of form-change becomes a measurable feature, displaying a convincing accordance between mathematical rule and plant shape. PMID:27933073

High-efficiency non-uniformity correction for wide dynamic linear infrared radiometry system

NASA Astrophysics Data System (ADS)

Li, Zhou; Yu, Yi; Tian, Qi-Jie; Chang, Song-Tao; He, Feng-Yun; Yin, Yan-He; Qiao, Yan-Feng

2017-09-01

Several different integration times are always set for a wide dynamic linear and continuous variable integration time infrared radiometry system, therefore, traditional calibration-based non-uniformity correction (NUC) are usually conducted one by one, and furthermore, several calibration sources required, consequently makes calibration and process of NUC time-consuming. In this paper, the difference of NUC coefficients between different integration times have been discussed, and then a novel NUC method called high-efficiency NUC, which combines the traditional calibration-based non-uniformity correction, has been proposed. It obtains the correction coefficients of all integration times in whole linear dynamic rangesonly by recording three different images of a standard blackbody. Firstly, mathematical procedure of the proposed non-uniformity correction method is validated and then its performance is demonstrated by a 400 mm diameter ground-based infrared radiometry system. Experimental results show that the mean value of Normalized Root Mean Square (NRMS) is reduced from 3.78% to 0.24% by the proposed method. In addition, the results at 4 ms and 70 °C prove that this method has a higher accuracy compared with traditional calibration-based NUC. In the meantime, at other integration time and temperature there is still a good correction effect. Moreover, it greatly reduces the number of correction time and temperature sampling point, and is characterized by good real-time performance and suitable for field measurement.

Correlating contact line capillarity and dynamic contact angle hysteresis in surfactant-nanoparticle based complex fluids

NASA Astrophysics Data System (ADS)

Harikrishnan, A. R.; Dhar, Purbarun; Agnihotri, Prabhat K.; Gedupudi, Sateesh; Das, Sarit K.

2018-04-01

Dynamic wettability and contact angle hysteresis can be correlated to shed insight onto any solid-liquid interaction. Complex fluids are capable of altering the expected hysteresis and dynamic wetting behavior due to interfacial interactions. We report the effect of capillary number on the dynamic advancing and receding contact angles of surfactant-based nanocolloidal solutions on hydrophilic, near hydrophobic, and superhydrophobic surfaces by performing forced wetting and de-wetting experiments by employing the embedded needle method. A segregated study is performed to infer the contributing effects of the constituents and effects of particle morphology. The static contact angle hysteresis is found to be a function of particle and surfactant concentrations and greatly depends on the nature of the morphology of the particles. An order of estimate of line energy and a dynamic flow parameter called spreading factor and the transient variations of these parameters are explored which sheds light on the dynamics of contact line movement and response to perturbation of three-phase contact. The Cox-Voinov-Tanner law was found to hold for hydrophilic and a weak dependency on superhydrophobic surfaces with capillary number, and even for the complex fluids, with a varying degree of dependency for different fluids.

The SOBANE risk management strategy and the Déparis method for the participatory screening of the risks.

PubMed

Malchaire, J B

2004-08-01

The first section of the document describes a risk-prevention strategy, called SOBANE, in four levels: screening, observation, analysis and expertise. The aim is to make risk prevention faster, more cost effective, and more effective in coordinating the contributions of the workers themselves, their management, the internal and external occupational health (OH) practitioners and the experts. These four levels are: screening, where the risk factors are detected by the workers and their management, and obvious solutions are implemented; observation, where the remaining problems are studied in more detail, one by one, and the reasons and the solutions are discussed in detail; analysis, where, when necessary, an OH practitioner is called upon to carry out appropriate measurements to develop specific solutions; expertise, where, in very sophisticated and rare cases, the assistance of an expert is called upon to solve a particular problem. The method for the participatory screening of the risks (in French: Dépistage Participatif des Risques), Déparis, is proposed for the first level screening of the SOBANE strategy. The work situation is systematically reviewed and all the aspects conditioning the easiness, the effectiveness and the satisfaction at work are discussed, in search of practical prevention measures. The points to be studied more in detail at level 2, observation, are identified. The method is carried out during a meeting of key workers and technical staff. The method proves to be simple, sparing in time and means and playing a significant role in the development of a dynamic plan of risk management and of a culture of dialogue in the company.

Timing matters: sonar call groups facilitate target localization in bats.

PubMed

Kothari, Ninad B; Wohlgemuth, Melville J; Hulgard, Katrine; Surlykke, Annemarie; Moss, Cynthia F

2014-01-01

To successfully negotiate a cluttered environment, an echolocating bat must control the timing of motor behaviors in response to dynamic sensory information. Here we detail the big brown bat's adaptive temporal control over sonar call production for tracking prey, moving predictably or unpredictably, under different experimental conditions. We studied the adaptive control of vocal-motor behaviors in free-flying big brown bats, Eptesicus fuscus, as they captured tethered and free-flying insects, in open and cluttered environments. We also studied adaptive sonar behavior in bats trained to track moving targets from a resting position. In each of these experiments, bats adjusted the features of their calls to separate target and clutter. Under many task conditions, flying bats produced prominent sonar sound groups identified as clusters of echolocation pulses with relatively stable intervals, surrounded by longer pulse intervals. In experiments where bats tracked approaching targets from a resting position, bats also produced sonar sound groups, and the prevalence of these sonar sound groups increased when motion of the target was unpredictable. We hypothesize that sonar sound groups produced during flight, and the sonar call doublets produced by a bat tracking a target from a resting position, help the animal resolve dynamic target location and represent the echo scene in greater detail. Collectively, our data reveal adaptive temporal control over sonar call production that allows the bat to negotiate a complex and dynamic environment.

Timing matters: sonar call groups facilitate target localization in bats

PubMed Central

Kothari, Ninad B.; Wohlgemuth, Melville J.; Hulgard, Katrine; Surlykke, Annemarie; Moss, Cynthia F.

2014-01-01

To successfully negotiate a cluttered environment, an echolocating bat must control the timing of motor behaviors in response to dynamic sensory information. Here we detail the big brown bat's adaptive temporal control over sonar call production for tracking prey, moving predictably or unpredictably, under different experimental conditions. We studied the adaptive control of vocal-motor behaviors in free-flying big brown bats, Eptesicus fuscus, as they captured tethered and free-flying insects, in open and cluttered environments. We also studied adaptive sonar behavior in bats trained to track moving targets from a resting position. In each of these experiments, bats adjusted the features of their calls to separate target and clutter. Under many task conditions, flying bats produced prominent sonar sound groups identified as clusters of echolocation pulses with relatively stable intervals, surrounded by longer pulse intervals. In experiments where bats tracked approaching targets from a resting position, bats also produced sonar sound groups, and the prevalence of these sonar sound groups increased when motion of the target was unpredictable. We hypothesize that sonar sound groups produced during flight, and the sonar call doublets produced by a bat tracking a target from a resting position, help the animal resolve dynamic target location and represent the echo scene in greater detail. Collectively, our data reveal adaptive temporal control over sonar call production that allows the bat to negotiate a complex and dynamic environment. PMID:24860509

Simultaneous Genotype Calling and Haplotype Phasing Improves Genotype Accuracy and Reduces False-Positive Associations for Genome-wide Association Studies

PubMed Central

Browning, Brian L.; Yu, Zhaoxia

2009-01-01

We present a novel method for simultaneous genotype calling and haplotype-phase inference. Our method employs the computationally efficient BEAGLE haplotype-frequency model, which can be applied to large-scale studies with millions of markers and thousands of samples. We compare genotype calls made with our method to genotype calls made with the BIRDSEED, CHIAMO, GenCall, and ILLUMINUS genotype-calling methods, using genotype data from the Illumina 550K and Affymetrix 500K arrays. We show that our method has higher genotype-call accuracy and yields fewer uncalled genotypes than competing methods. We perform single-marker analysis of data from the Wellcome Trust Case Control Consortium bipolar disorder and type 2 diabetes studies. For bipolar disorder, the genotype calls in the original study yield 25 markers with apparent false-positive association with bipolar disorder at a p < 10−7 significance level, whereas genotype calls made with our method yield no associated markers at this significance threshold. Conversely, for markers with replicated association with type 2 diabetes, there is good concordance between genotype calls used in the original study and calls made by our method. Results from single-marker and haplotypic analysis of our method's genotype calls for the bipolar disorder study indicate that our method is highly effective at eliminating genotyping artifacts that cause false-positive associations in genome-wide association studies. Our new genotype-calling methods are implemented in the BEAGLE and BEAGLECALL software packages. PMID:19931040

Exploring Protein Dynamics Space: The Dynasome as the Missing Link between Protein Structure and Function

PubMed Central

Hensen, Ulf; Meyer, Tim; Haas, Jürgen; Rex, René; Vriend, Gert; Grubmüller, Helmut

2012-01-01

Proteins are usually described and classified according to amino acid sequence, structure or function. Here, we develop a minimally biased scheme to compare and classify proteins according to their internal mobility patterns. This approach is based on the notion that proteins not only fold into recurring structural motifs but might also be carrying out only a limited set of recurring mobility motifs. The complete set of these patterns, which we tentatively call the dynasome, spans a multi-dimensional space with axes, the dynasome descriptors, characterizing different aspects of protein dynamics. The unique dynamic fingerprint of each protein is represented as a vector in the dynasome space. The difference between any two vectors, consequently, gives a reliable measure of the difference between the corresponding protein dynamics. We characterize the properties of the dynasome by comparing the dynamics fingerprints obtained from molecular dynamics simulations of 112 proteins but our approach is, in principle, not restricted to any specific source of data of protein dynamics. We conclude that: 1. the dynasome consists of a continuum of proteins, rather than well separated classes. 2. For the majority of proteins we observe strong correlations between structure and dynamics. 3. Proteins with similar function carry out similar dynamics, which suggests a new method to improve protein function annotation based on protein dynamics. PMID:22606222

TADSim: Discrete Event-based Performance Prediction for Temperature Accelerated Dynamics

DOE PAGES

Mniszewski, Susan M.; Junghans, Christoph; Voter, Arthur F.; ...

2015-04-16

Next-generation high-performance computing will require more scalable and flexible performance prediction tools to evaluate software--hardware co-design choices relevant to scientific applications and hardware architectures. Here, we present a new class of tools called application simulators—parameterized fast-running proxies of large-scale scientific applications using parallel discrete event simulation. Parameterized choices for the algorithmic method and hardware options provide a rich space for design exploration and allow us to quickly find well-performing software--hardware combinations. We demonstrate our approach with a TADSim simulator that models the temperature-accelerated dynamics (TAD) method, an algorithmically complex and parameter-rich member of the accelerated molecular dynamics (AMD) family ofmore » molecular dynamics methods. The essence of the TAD application is captured without the computational expense and resource usage of the full code. We accomplish this by identifying the time-intensive elements, quantifying algorithm steps in terms of those elements, abstracting them out, and replacing them by the passage of time. We use TADSim to quickly characterize the runtime performance and algorithmic behavior for the otherwise long-running simulation code. We extend TADSim to model algorithm extensions, such as speculative spawning of the compute-bound stages, and predict performance improvements without having to implement such a method. Validation against the actual TAD code shows close agreement for the evolution of an example physical system, a silver surface. Finally, focused parameter scans have allowed us to study algorithm parameter choices over far more scenarios than would be possible with the actual simulation. This has led to interesting performance-related insights and suggested extensions.« less

Molecular dynamics simulation of nonlinear spectroscopies of intermolecular motions in liquid water.

PubMed

Yagasaki, Takuma; Saito, Shinji

2009-09-15

Water is the most extensively studied of liquids because of both its ubiquity and its anomalous thermodynamic and dynamic properties. The properties of water are dominated by hydrogen bonds and hydrogen bond network rearrangements. Fundamental information on the dynamics of liquid water has been provided by linear infrared (IR), Raman, and neutron-scattering experiments; molecular dynamics simulations have also provided insights. Recently developed higher-order nonlinear spectroscopies open new windows into the study of the hydrogen bond dynamics of liquid water. For example, the vibrational lifetimes of stretches and a bend, intramolecular features of water dynamics, can be accurately measured and are found to be on the femtosecond time scale at room temperature. Higher-order nonlinear spectroscopy is expressed by a multitime correlation function, whereas traditional linear spectroscopy is given by a one-time correlation function. Thus, nonlinear spectroscopy yields more detailed information on the dynamics of condensed media than linear spectroscopy. In this Account, we describe the theoretical background and methods for calculating higher order nonlinear spectroscopy; equilibrium and nonequilibrium molecular dynamics simulations, and a combination of both, are used. We also present the intermolecular dynamics of liquid water revealed by fifth-order two-dimensional (2D) Raman spectroscopy and third-order IR spectroscopy. 2D Raman spectroscopy is sensitive to couplings between modes; the calculated 2D Raman signal of liquid water shows large anharmonicity in the translational motion and strong coupling between the translational and librational motions. Third-order IR spectroscopy makes it possible to examine the time-dependent couplings. The 2D IR spectra and three-pulse photon echo peak shift show the fast frequency modulation of the librational motion. A significant effect of the translational motion on the fast frequency modulation of the librational motion is elucidated by introducing the "translation-free" molecular dynamics simulation. The isotropic pump-probe signal and the polarization anisotropy decay show fast transfer of the librational energy to the surrounding water molecules, followed by relaxation to the hot ground state. These theoretical methods do not require frequently used assumptions and can thus be called ab initio methods; together with multidimensional nonlinear spectroscopies, they provide powerful methods for examining the inter- and intramolecular details of water dynamics.

A parallel algorithm for multi-level logic synthesis using the transduction method. M.S. Thesis

NASA Technical Reports Server (NTRS)

Lim, Chieng-Fai

1991-01-01

The Transduction Method has been shown to be a powerful tool in the optimization of multilevel networks. Many tools such as the SYLON synthesis system (X90), (CM89), (LM90) have been developed based on this method. A parallel implementation is presented of SYLON-XTRANS (XM89) on an eight processor Encore Multimax shared memory multiprocessor. It minimizes multilevel networks consisting of simple gates through parallel pruning, gate substitution, gate merging, generalized gate substitution, and gate input reduction. This implementation, called Parallel TRANSduction (PTRANS), also uses partitioning to break large circuits up and performs inter- and intra-partition dynamic load balancing. With this, good speedups and high processor efficiencies are achievable without sacrificing the resulting circuit quality.

The linguistic and interactional factors impacting recognition and dispatch in emergency calls for out-of-hospital cardiac arrest: a mixed-method linguistic analysis study protocol.

PubMed

Riou, Marine; Ball, Stephen; Williams, Teresa A; Whiteside, Austin; O'Halloran, Kay L; Bray, Janet; Perkins, Gavin D; Cameron, Peter; Fatovich, Daniel M; Inoue, Madoka; Bailey, Paul; Brink, Deon; Smith, Karen; Della, Phillip; Finn, Judith

2017-07-09

Emergency telephone calls placed by bystanders are crucial to the recognition of out-of-hospital cardiac arrest (OHCA), fast ambulance dispatch and initiation of early basic life support. Clear and efficient communication between caller and call-taker is essential to this time-critical emergency, yet few studies have investigated the impact that linguistic factors may have on the nature of the interaction and the resulting trajectory of the call. This research aims to provide a better understanding of communication factors impacting on the accuracy and timeliness of ambulance dispatch. A dataset of OHCA calls and their corresponding metadata will be analysed from an interdisciplinary perspective, combining linguistic analysis and health services research. The calls will be transcribed and coded for linguistic and interactional variables and then used to answer a series of research questions about the recognition of OHCA and the delivery of basic life-support instructions to bystanders. Linguistic analysis of calls will provide a deeper understanding of the interactional dynamics between caller and call-taker which may affect recognition and dispatch for OHCA. Findings from this research will translate into recommendations for modifications of the protocols for ambulance dispatch and provide directions for further research. The study has been approved by the Curtin University Human Research Ethics Committee (HR128/2013) and the St John Ambulance Western Australia Research Advisory Group. Findings will be published in peer-reviewed journals and communicated to key audiences, including ambulance dispatch professionals. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A 2-1-1 Research Collaboration

PubMed Central

Eddens, Katherine S.; Alcaraz, Kassandra I.; Kreuter, Matthew W.; Rath, Suchitra; Greer, Regina

2012-01-01

Background 2-1-1 serves as a lifeline in times of crises. These crises often cause a spike in call volume that can challenge 2-1-1’s ability to meet their service quality standards. For researchers gathering data through 2-1-1s, a sudden increase in call volume might reduce accrual as 2-1-1 has less time to administer study protocols. Research activities imbedded in 2-1-1 systems may directly affect 2-1-1 service quality indicators. Purpose Using data from a 2-1-1 research collaboration, this paper examines the impact of crises on call volume to 2-1-1, how call volume affects research participant accrual through 2-1-1, and how research recruitment efforts affect 2-1-1 service quality indicators. Methods t-tests were used to examine the effect of call volume on research participant accrual. Linear and logistic regressions were used to examine the effect of research participant accrual on 2-1-1 service quality indicators. Data were collected June 2010–December 2011; data were analyzed in 2012. Results Findings from this collaboration suggest that crises causing spikes in call volume adversely affect 2-1-1 service quality indicators as well as accrual of research participants. Administering a brief (2–3 minute) health risk assessment did not negatively affect service quality, but administering a longer (15–18 minute) survey had a modest adverse effect on these indicators. Conclusions In 2-1-1 research collaborations, both partners need to understand the dynamic relationship between call volume, research accrual, and service quality, and adjust expectations accordingly. If research goals include administering a longer survey, increased staffing of 2-1-1 call centers may be needed to avoid compromising service quality. PMID:23157769

Dynamic pressure sensitivity determination with Mach number method

NASA Astrophysics Data System (ADS)

Sarraf, Christophe; Damion, Jean-Pierre

2018-05-01

Measurements of pressure in fast transient conditions are often performed even if the dynamic characteristic of the transducer are not traceable to international standards. Moreover, the question of a primary standard in dynamic pressure is still open, especially for gaseous applications. The question is to improve dynamic standards in order to respond to expressed industrial needs. In this paper, the method proposed in the EMRP IND09 ‘Dynamic’ project, which can be called the ‘ideal shock tube method’, is compared with the ‘collective standard method’ currently used in the Laboratoire de Métrologie Dynamique (LNE/ENSAM). The input is a step of pressure generated by a shock tube. The transducer is a piezoelectric pressure sensor. With the ‘ideal shock tube method’ the sensitivity of a pressure sensor is first determined dynamically. This method requires a shock tube implemented with piezoelectric shock wave detectors. The measurement of the Mach number in the tube allows an evaluation of the incident pressure amplitude of a step using a theoretical 1D model of the shock tube. Heat transfer, other actual effects and effects of the shock tube imperfections are not taken into account. The amplitude of the pressure step is then used to determine the sensitivity in dynamic conditions. The second method uses a frequency bandwidth comparison to determine pressure at frequencies from quasi-static conditions, traceable to static pressure standards, to higher frequencies (up to 10 kHz). The measurand is also a step of pressure generated by a supposed ideal shock tube or a fast-opening device. The results are provided as a transfer function with an uncertainty budget assigned to a frequency range, also deliverable frequency by frequency. The largest uncertainty in the bandwidth of comparison is used to trace the final pressure step level measured in dynamic conditions, owing that this pressure is not measurable in a steady state on a shock tube. A reference sensor thereby calibrated can be used in a comparison measurement process. At high frequencies the most important component of the uncertainty in this method is due to actual shock tube complex effects not already functionalized nowadays or thought not to be functionalized in this kind of direct method. After a brief review of both methods and a brief review of the determination of the transfer function of pressure transducers, and the budget of associated uncertainty for the dynamic calibration of a pressure transducer in gas, this paper presents a comparison of the results obtained with the ‘ideal shock tube’ and the ‘collective standard’ methods.

On the Inference of Functional Circadian Networks Using Granger Causality

PubMed Central

Pourzanjani, Arya; Herzog, Erik D.; Petzold, Linda R.

2015-01-01

Being able to infer one way direct connections in an oscillatory network such as the suprachiastmatic nucleus (SCN) of the mammalian brain using time series data is difficult but crucial to understanding network dynamics. Although techniques have been developed for inferring networks from time series data, there have been no attempts to adapt these techniques to infer directional connections in oscillatory time series, while accurately distinguishing between direct and indirect connections. In this paper an adaptation of Granger Causality is proposed that allows for inference of circadian networks and oscillatory networks in general called Adaptive Frequency Granger Causality (AFGC). Additionally, an extension of this method is proposed to infer networks with large numbers of cells called LASSO AFGC. The method was validated using simulated data from several different networks. For the smaller networks the method was able to identify all one way direct connections without identifying connections that were not present. For larger networks of up to twenty cells the method shows excellent performance in identifying true and false connections; this is quantified by an area-under-the-curve (AUC) 96.88%. We note that this method like other Granger Causality-based methods, is based on the detection of high frequency signals propagating between cell traces. Thus it requires a relatively high sampling rate and a network that can propagate high frequency signals. PMID:26413748

Physics of Traffic Flow

NASA Astrophysics Data System (ADS)

Davis, L. C.

2015-03-01

The Texas A&M Transportation Institute estimated that traffic congestion cost the United States 121 billion in 2011 (the latest data available). The cost is due to wasted time and fuel. In addition to accidents and road construction, factors contributing to congestion include large demand, instability of high-density free flow and selfish behavior of drivers, which produces self-organized traffic bottlenecks. Extensive data collected on instrumented highways in various countries have led to a better understanding of traffic dynamics. From these measurements, Boris Kerner and colleagues developed a new theory called three-phase theory. They identified three major phases of flow observed in the data: free flow, synchronous flow and wide moving jams. The intermediate phase is called synchronous because vehicles in different lanes tend to have similar velocities. This congested phase, characterized by lower velocities yet modestly high throughput, frequently occurs near on-ramps and lane reductions. At present there are only two widely used methods of congestion mitigation: ramp metering and the display of current travel-time information to drivers. To find more effective methods to reduce congestion, researchers perform large-scale simulations using models based on the new theories. An algorithm has been proposed to realize Wardrop equilibria with real-time route information. Such equilibria have equal travel time on alternative routes between a given origin and destination. An active area of current research is the dynamics of connected vehicles, which communicate wirelessly with other vehicles and the surrounding infrastructure. These systems show great promise for improving traffic flow and safety.

Real-time decay of a highly excited charge carrier in the one-dimensional Holstein model

NASA Astrophysics Data System (ADS)

Dorfner, F.; Vidmar, L.; Brockt, C.; Jeckelmann, E.; Heidrich-Meisner, F.

2015-03-01

We study the real-time dynamics of a highly excited charge carrier coupled to quantum phonons via a Holstein-type electron-phonon coupling. This is a prototypical example for the nonequilibrium dynamics in an interacting many-body system where excess energy is transferred from electronic to phononic degrees of freedom. We use diagonalization in a limited functional space (LFS) to study the nonequilibrium dynamics on a finite one-dimensional chain. This method agrees with exact diagonalization and the time-evolving block-decimation method, in both the relaxation regime and the long-time stationary state, and among these three methods it is the most efficient and versatile one for this problem. We perform a comprehensive analysis of the time evolution by calculating the electron, phonon and electron-phonon coupling energies, and the electronic momentum distribution function. The numerical results are compared to analytical solutions for short times, for a small hopping amplitude and for a weak electron-phonon coupling. In the latter case, the relaxation dynamics obtained from the Boltzmann equation agrees very well with the LFS data. We also study the time dependence of the eigenstates of the single-site reduced density matrix, which defines the so-called optimal phonon modes. We discuss their structure in nonequilibrium and the distribution of their weights. Our analysis shows that the structure of optimal phonon modes contains very useful information for the interpretation of the numerical data.

Quantum dynamics of light-driven chiral molecular motors.

PubMed

Yamaki, Masahiro; Nakayama, Shin-ichiro; Hoki, Kunihito; Kono, Hirohiko; Fujimura, Yuichi

2009-03-21

The results of theoretical studies on quantum dynamics of light-driven molecular motors with internal rotation are presented. Characteristic features of chiral motors driven by a non-helical, linearly polarized electric field of light are explained on the basis of symmetry argument. The rotational potential of the chiral motor is characterized by a ratchet form. The asymmetric potential determines the directional motion: the rotational direction is toward the gentle slope of the asymmetric potential. This direction is called the intuitive direction. To confirm the unidirectional rotational motion, results of quantum dynamical calculations of randomly-oriented molecular motors are presented. A theoretical design of the smallest light-driven molecular machine is presented. The smallest chiral molecular machine has an optically driven engine and a running propeller on its body. The mechanisms of transmission of driving forces from the engine to the propeller are elucidated by using a quantum dynamical treatment. The results provide a principle for control of optically-driven molecular bevel gears. Temperature effects are discussed using the density operator formalism. An effective method for ultrafast control of rotational motions in any desired direction is presented with the help of a quantum control theory. In this method, visible or UV light pulses are applied to drive the motor via an electronic excited state. A method for driving a large molecular motor consisting of an aromatic hydrocarbon is presented. The molecular motor is operated by interactions between the induced dipole of the molecular motor and the electric field of light pulses.

Impact of Soil Moisture Dynamics on ASAR Observed Backscatters and its Spatial Variability over the Upstream of the Heihe River Basin, China

NASA Astrophysics Data System (ADS)

Wang, Shuguo

2013-01-01

The so called change detection method is a promising way to acquire soil moisture (SM) dynamics dependent on time series of radar backscatter (σ0) observations. The current study is a preceded step for using this method to carry out SM inversion at basin scale, in order to investigate the applicability of the change detection method in the Heihe River Basin, and to inspect the sensitivity of SAR signals to soil moisture variations. At the meantime, a prior knowledge of SM dynamics and land heterogeneities that may contribute to backscatter observations can be obtained. The impact of land surface states on spatial and temporal σ0 variability measured by ASAR has been evaluated in the upstream of the Heihe River Basin, which was one of the foci experimental areas (FEAs) in Watershed Allied Telemetry Experimental Research (WATER). Based on the in situ measurements provided by an automatic meteorological station (AMS) established at the A’rou site and time series of ASAR observations focused on a 1 km2 area, the relationships between the temporal dynamics of σ0 with in situ SM variations, and land heterogeneities of the study area according to the characteristics of spatial variability of σ0, were identified. The in situ measurements of soil moisture and temperature show a very clear seasonal freeze/thaw cycle in the study site. The temporal σ0 evolvement is basically coherent with ground measurements.

Theoretical Sum Frequency Generation Spectroscopy of Peptides

PubMed Central

2015-01-01

Vibrational sum frequency generation (SFG) has become a very promising technique for the study of proteins at interfaces, and it has been applied to important systems such as anti-microbial peptides, ion channel proteins, and human islet amyloid polypeptide. Moreover, so-called “chiral” SFG techniques, which rely on polarization combinations that generate strong signals primarily for chiral molecules, have proven to be particularly discriminatory of protein secondary structure. In this work, we present a theoretical strategy for calculating protein amide I SFG spectra by combining line-shape theory with molecular dynamics simulations. We then apply this method to three model peptides, demonstrating the existence of a significant chiral SFG signal for peptides with chiral centers, and providing a framework for interpreting the results on the basis of the dependence of the SFG signal on the peptide orientation. We also examine the importance of dynamical and coupling effects. Finally, we suggest a simple method for determining a chromophore’s orientation relative to the surface using ratios of experimental heterodyne-detected signals with different polarizations, and test this method using theoretical spectra. PMID:25203677

Live CLEM imaging to analyze nuclear structures at high resolution.

PubMed

Haraguchi, Tokuko; Osakada, Hiroko; Koujin, Takako

2015-01-01

Fluorescence microscopy (FM) and electron microscopy (EM) are powerful tools for observing molecular components in cells. FM can provide temporal information about cellular proteins and structures in living cells. EM provides nanometer resolution images of cellular structures in fixed cells. We have combined FM and EM to develop a new method of correlative light and electron microscopy (CLEM), called "Live CLEM." In this method, the dynamic behavior of specific molecules of interest is first observed in living cells using fluorescence microscopy (FM) and then cellular structures in the same cell are observed using electron microscopy (EM). Following image acquisition, FM and EM images are compared to enable the fluorescent images to be correlated with the high-resolution images of cellular structures obtained using EM. As this method enables analysis of dynamic events involving specific molecules of interest in the context of specific cellular structures at high resolution, it is useful for the study of nuclear structures including nuclear bodies. Here we describe Live CLEM that can be applied to the study of nuclear structures in mammalian cells.

OPTIMIZING THROUGH CO-EVOLUTIONARY AVALANCHES

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

S. BOETTCHER; A. PERCUS

2000-08-01

We explore a new general-purpose heuristic for finding high-quality solutions to hard optimization problems. The method, called extremal optimization, is inspired by ''self-organized critically,'' a concept introduced to describe emergent complexity in many physical systems. In contrast to Genetic Algorithms which operate on an entire ''gene-pool'' of possible solutions, extremal optimization successively replaces extremely undesirable elements of a sub-optimal solution with new, random ones. Large fluctuations, called ''avalanches,'' ensue that efficiently explore many local optima. Drawing upon models used to simulate far-from-equilibrium dynamics, extremal optimization complements approximation methods inspired by equilibrium statistical physics, such as simulated annealing. With only onemore » adjustable parameter, its performance has proved competitive with more elaborate methods, especially near phase transitions. Those phase transitions are found in the parameter space of most optimization problems, and have recently been conjectured to be the origin of some of the hardest instances in computational complexity. We will demonstrate how extremal optimization can be implemented for a variety of combinatorial optimization problems. We believe that extremal optimization will be a useful tool in the investigation of phase transitions in combinatorial optimization problems, hence valuable in elucidating the origin of computational complexity.« less

The Dynamics of Chemical Reactions: Atomistic Visualizations of Organic Reactions, and Homage to van 't Hoff.

PubMed

Yang, Zhongyue; Houk, K N

2018-03-15

Jacobus Henricus van 't Hoff was the first Nobel Laureate in Chemistry. He pioneered in the study of chemical dynamics, which referred at that time to chemical kinetics and thermodynamics. The term has evolved in modern times to refer to the exploration of chemical transformations in a time-resolved fashion. Chemical dynamics has been driven by the development of molecular dynamics trajectory simulations, which provide atomic visualization of chemical processes and illuminate how dynamic effects influence chemical reactivity and selectivity. In homage to the legend of van 't Hoff, we review the development of the chemical dynamics of organic reactions, our area of research. We then discuss our trajectory simulations of pericyclic reactions, and our development of dynamic criteria for concerted and stepwise reaction mechanisms. We also describe a method that we call environment-perturbed transition state sampling, which enables trajectory simulations in condensed-media using quantum mechanics and molecular mechanics (QM/MM). We apply the method to reactions in solvent and in enzyme. Jacobus Henricus van 't Hoff (1852, Rotterdam-1911, Berlin) received the Nobel Prize for Chemistry in 1901 "in recognition of the extraordinary services he has rendered by the discovery of the laws of chemical dynamics and osmotic pressure in solutions". van 't Hoff was born the Netherlands, and earned his doctorate in Utrecht in 1874. In 1896 he moved to Berlin, where he was offered a position with more research and less teaching. van 't Hoff is considered one of the founders of physical chemistry. A key step in establishing this new field was the start of Zeitschrift für Physikalische Chemie in 1887. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Effective Group Dynamics: Theories and Practices.

ERIC Educational Resources Information Center

Murk, Peter J.

Using a brief experiential group activity called "Choosing a Color Exercise" as an introductory measure, this paper explains the basics of group dynamics and reviews the major theoretical relationships between the group's structure, the dynamics of maintenance and task behaviors, and effective individual performances. The types of functional and…

The difference between a dynamic and mechanical approach to stroke treatment.

PubMed

Helgason, Cathy M

2007-06-01

The current classification of stroke is based on causation, also called pathogenesis, and relies on binary logic faithful to the Aristotelian tradition. Accordingly, a pathology is or is not the cause of the stroke, is considered independent of others, and is the target for treatment. It is the subject for large double-blind randomized clinical therapeutic trials. The scientific view behind clinical trials is the fundamental concept that information is statistical, and causation is determined by probabilities. Therefore, the cause and effect relation will be determined by probability-theory-based statistics. This is the basis of evidence-based medicine, which calls for the results of such trials to be the basis for physician decisions regarding diagnosis and treatment. However, there are problems with the methodology behind evidence-based medicine. Calculations using probability-theory-based statistics regarding cause and effect are performed within an automatic system where there are known inputs and outputs. This method of research provides a framework of certainty with no surprise elements or outcomes. However, it is not a system or method that will come up with previously unknown variables, concepts, or universal principles; it is not a method that will give a new outcome; and it is not a method that allows for creativity, expertise, or new insight for problem solving.

Videogrammetry Using Projected Circular Targets: Proof-of-Concept Test

NASA Technical Reports Server (NTRS)

Pappa, Richard S.; Black, Jonathan T.

2003-01-01

Videogrammetry is the science of calculating 3D object coordinates as a function of time from image sequences. It expands the method of photogrammetry to multiple time steps enabling the object to be characterized dynamically. Photogrammetry achieves the greatest accuracy with high contrast, solid-colored, circular targets. The high contrast is most often effected using retro-reflective targets attached to the measurement article. Knowledge of the location of each target allows those points to be tracked in a sequence of images, thus yielding dynamic characterization of the overall object. For ultra-lightweight and inflatable gossamer structures (e.g. solar sails, inflatable antennae, sun shields, etc.) where it may be desirable to avoid physically attaching retro-targets, a high-density grid of projected circular targets - called dot projection - is a viable alternative. Over time the object changes shape or position independently of the dots. Dynamic behavior, such as deployment or vibration, can be characterized by tracking the overall 3D shape of the object instead of tracking specific object points. To develop this method, an oscillating rigid object was measured using both retroreflective targets and dot projection. This paper details these tests, compares the results, and discusses the overall accuracy of dot projection videogrammetry.

Videogrammetry Using Projected Circular Targets: Proof-of-Concept Test

NASA Technical Reports Server (NTRS)

Black, Jonathan T.; Pappa, Richard S.

2003-01-01

Videogrammetry is the science of calculating 3D object coordinates as a function of time from image sequences. It expands the method of photogrammetry to multiple time steps enabling the object to be characterized dynamically. Photogrammetry achieves the greatest accuracy with high contrast, solid-colored circular targets. The high contrast is most often effected using retro-reflective targets attached to the measurement article. Knowledge of the location of each target allows those points to be tracked in a sequence of images, thus yielding dynamic characterization of the overall object. For ultra-lightweight and inflatable gossamer structures (e.g. solar sails, inflatable antennae, sun shields, etc.) where it may be desirable to avoid physically attaching retro-targets, a high-density grid of projected circular targets - called dot projection - is a viable alternative. Over time the object changes shape or position independently of the dots. Dynamic behavior, such as deployment or vibration, can be characterized by tracking the overall 3D shape of the object instead of tracking specific object points. To develop this method, an oscillating rigid object was measured using both retro- reflective targets and dot projection. This paper details these tests, compares the results, and discusses the overall accuracy of dot projection videogrammetry.

Tracking urban human activity from mobile phone calling patterns

PubMed Central

Ghosh, Asim; Bhattacharya, Kunal; Dunbar, Robin I. M.; Kaski, Kimmo

2017-01-01

Timings of human activities are marked by circadian clocks which in turn are entrained to different environmental signals. In an urban environment the presence of artificial lighting and various social cues tend to disrupt the natural entrainment with the sunlight. However, it is not completely understood to what extent this is the case. Here we exploit the large-scale data analysis techniques to study the mobile phone calling activity of people in large cities to infer the dynamics of urban daily rhythms. From the calling patterns of about 1,000,000 users spread over different cities but lying inside the same time-zone, we show that the onset and termination of the calling activity synchronizes with the east-west progression of the sun. We also find that the onset and termination of the calling activity of users follows a yearly dynamics, varying across seasons, and that its timings are entrained to solar midnight. Furthermore, we show that the average mid-sleep time of people living in urban areas depends on the age and gender of each cohort as a result of biological and social factors. PMID:29161270

Tracking urban human activity from mobile phone calling patterns.

PubMed

Monsivais, Daniel; Ghosh, Asim; Bhattacharya, Kunal; Dunbar, Robin I M; Kaski, Kimmo

2017-11-01

Timings of human activities are marked by circadian clocks which in turn are entrained to different environmental signals. In an urban environment the presence of artificial lighting and various social cues tend to disrupt the natural entrainment with the sunlight. However, it is not completely understood to what extent this is the case. Here we exploit the large-scale data analysis techniques to study the mobile phone calling activity of people in large cities to infer the dynamics of urban daily rhythms. From the calling patterns of about 1,000,000 users spread over different cities but lying inside the same time-zone, we show that the onset and termination of the calling activity synchronizes with the east-west progression of the sun. We also find that the onset and termination of the calling activity of users follows a yearly dynamics, varying across seasons, and that its timings are entrained to solar midnight. Furthermore, we show that the average mid-sleep time of people living in urban areas depends on the age and gender of each cohort as a result of biological and social factors.

Flight dynamics analysis and simulation of heavy lift airships. Volume 5: Programmer's manual

NASA Technical Reports Server (NTRS)

Ringland, R. F.; Tischler, M. B.; Jex, H. R.; Emmen, R. D.; Ashkenas, I. L.

1982-01-01

The Programmer's Manual contains explanations of the logic embodied in the various program modules, a dictionary of program variables, a subroutine listing, subroutine/common block/cross reference listing, and a calling/called subroutine cross reference listing.

Shock simulations of a single-site coarse-grain RDX model using the dissipative particle dynamics method with reactivity

NASA Astrophysics Data System (ADS)

Sellers, Michael S.; Lísal, Martin; Schweigert, Igor; Larentzos, James P.; Brennan, John K.

2017-01-01

In discrete particle simulations, when an atomistic model is coarse-grained, a tradeoff is made: a boost in computational speed for a reduction in accuracy. The Dissipative Particle Dynamics (DPD) methods help to recover lost accuracy of the viscous and thermal properties, while giving back a relatively small amount of computational speed. Since its initial development for polymers, one of the most notable extensions of DPD has been the introduction of chemical reactivity, called DPD-RX. In 2007, Maillet, Soulard, and Stoltz introduced implicit chemical reactivity in DPD through the concept of particle reactors and simulated the decomposition of liquid nitromethane. We present an extended and generalized version of the DPD-RX method, and have applied it to solid hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX). Demonstration simulations of reacting RDX are performed under shock conditions using a recently developed single-site coarse-grain model and a reduced RDX decomposition mechanism. A description of the methods used to simulate RDX and its transition to hot product gases within DPD-RX is presented. Additionally, we discuss several examples of the effect of shock speed and microstructure on the corresponding material chemistry.

A discrete geometric approach for simulating the dynamics of thin viscous threads

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

Audoly, B., E-mail: audoly@lmm.jussieu.fr; Clauvelin, N.; Brun, P.-T.

We present a numerical model for the dynamics of thin viscous threads based on a discrete, Lagrangian formulation of the smooth equations. The model makes use of a condensed set of coordinates, called the centerline/spin representation: the kinematic constraints linking the centerline's tangent to the orientation of the material frame is used to eliminate two out of three degrees of freedom associated with rotations. Based on a description of twist inspired from discrete differential geometry and from variational principles, we build a full-fledged discrete viscous thread model, which includes in particular a discrete representation of the internal viscous stress. Consistencymore » of the discrete model with the classical, smooth equations for thin threads is established formally. Our numerical method is validated against reference solutions for steady coiling. The method makes it possible to simulate the unsteady behavior of thin viscous threads in a robust and efficient way, including the combined effects of inertia, stretching, bending, twisting, large rotations and surface tension.« less

Burstiness and tie activation strategies in time-varying social networks.

PubMed

Ubaldi, Enrico; Vezzani, Alessandro; Karsai, Márton; Perra, Nicola; Burioni, Raffaella

2017-04-13

The recent developments in the field of social networks shifted the focus from static to dynamical representations, calling for new methods for their analysis and modelling. Observations in real social systems identified two main mechanisms that play a primary role in networks' evolution and influence ongoing spreading processes: the strategies individuals adopt when selecting between new or old social ties, and the bursty nature of the social activity setting the pace of these choices. We introduce a time-varying network model accounting both for ties selection and burstiness and we analytically study its phase diagram. The interplay of the two effects is non trivial and, interestingly, the effects of burstiness might be suppressed in regimes where individuals exhibit a strong preference towards previously activated ties. The results are tested against numerical simulations and compared with two empirical datasets with very good agreement. Consequently, the framework provides a principled method to classify the temporal features of real networks, and thus yields new insights to elucidate the effects of social dynamics on spreading processes.

Long-term stable time integration scheme for dynamic analysis of planar geometrically exact Timoshenko beams

NASA Astrophysics Data System (ADS)

Nguyen, Tien Long; Sansour, Carlo; Hjiaj, Mohammed

2017-05-01

In this paper, an energy-momentum method for geometrically exact Timoshenko-type beam is proposed. The classical time integration schemes in dynamics are known to exhibit instability in the non-linear regime. The so-called Timoshenko-type beam with the use of rotational degree of freedom leads to simpler strain relations and simpler expressions of the inertial terms as compared to the well known Bernoulli-type model. The treatment of the Bernoulli-model has been recently addressed by the authors. In this present work, we extend our approach of using the strain rates to define the strain fields to in-plane geometrically exact Timoshenko-type beams. The large rotational degrees of freedom are exactly computed. The well-known enhanced strain method is used to avoid locking phenomena. Conservation of energy, momentum and angular momentum is proved formally and numerically. The excellent performance of the formulation will be demonstrated through a range of examples.

Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems

PubMed Central

Huang, Dayu; Xue, Anke; Guo, Yunfei

2012-01-01

In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations. PMID:22666074

Generalized Predictive Control of Dynamic Systems with Rigid-Body Modes

NASA Technical Reports Server (NTRS)

Kvaternik, Raymond G.

2013-01-01

Numerical simulations to assess the effectiveness of Generalized Predictive Control (GPC) for active control of dynamic systems having rigid-body modes are presented. GPC is a linear, time-invariant, multi-input/multi-output predictive control method that uses an ARX model to characterize the system and to design the controller. Although the method can accommodate both embedded (implicit) and explicit feedforward paths for incorporation of disturbance effects, only the case of embedded feedforward in which the disturbances are assumed to be unknown is considered here. Results from numerical simulations using mathematical models of both a free-free three-degree-of-freedom mass-spring-dashpot system and the XV-15 tiltrotor research aircraft are presented. In regulation mode operation, which calls for zero system response in the presence of disturbances, the simulations showed reductions of nearly 100%. In tracking mode operations, where the system is commanded to follow a specified path, the GPC controllers produced the desired responses, even in the presence of disturbances.

Burstiness and tie activation strategies in time-varying social networks

NASA Astrophysics Data System (ADS)

Ubaldi, Enrico; Vezzani, Alessandro; Karsai, Márton; Perra, Nicola; Burioni, Raffaella

2017-04-01

The recent developments in the field of social networks shifted the focus from static to dynamical representations, calling for new methods for their analysis and modelling. Observations in real social systems identified two main mechanisms that play a primary role in networks’ evolution and influence ongoing spreading processes: the strategies individuals adopt when selecting between new or old social ties, and the bursty nature of the social activity setting the pace of these choices. We introduce a time-varying network model accounting both for ties selection and burstiness and we analytically study its phase diagram. The interplay of the two effects is non trivial and, interestingly, the effects of burstiness might be suppressed in regimes where individuals exhibit a strong preference towards previously activated ties. The results are tested against numerical simulations and compared with two empirical datasets with very good agreement. Consequently, the framework provides a principled method to classify the temporal features of real networks, and thus yields new insights to elucidate the effects of social dynamics on spreading processes.

Active control of panel vibrations induced by boundary-layer flow

NASA Technical Reports Server (NTRS)

Chow, Pao-Liu

1991-01-01

Some problems in active control of panel vibration excited by a boundary layer flow over a flat plate are studied. In the first phase of the study, the optimal control problem of vibrating elastic panel induced by a fluid dynamical loading was studied. For a simply supported rectangular plate, the vibration control problem can be analyzed by a modal analysis. The control objective is to minimize the total cost functional, which is the sum of a vibrational energy and the control cost. By means of the modal expansion, the dynamical equation for the plate and the cost functional are reduced to a system of ordinary differential equations and the cost functions for the modes. For the linear elastic plate, the modes become uncoupled. The control of each modal amplitude reduces to the so-called linear regulator problem in control theory. Such problems can then be solved by the method of adjoint state. The optimality system of equations was solved numerically by a shooting method. The results are summarized.

Numerical simulation of water hammer in low pressurized pipe: comparison of SimHydraulics and Lax-Wendroff method with experiment

NASA Astrophysics Data System (ADS)

Himr, D.

2013-04-01

Article describes simulation of unsteady flow during water hammer with two programs, which use different numerical approaches to solve ordinary one dimensional differential equations describing the dynamics of hydraulic elements and pipes. First one is Matlab-Simulink-SimHydraulics, which is a commercial software developed to solve the dynamics of general hydraulic systems. It defines them with block elements. The other software is called HYDRA and it is based on the Lax-Wendrff numerical method, which serves as a tool to solve the momentum and continuity equations. This program was developed in Matlab by Brno University of Technology. Experimental measurements were performed on a simple test rig, which consists of an elastic pipe with strong damping connecting two reservoirs. Water hammer is induced with fast closing the valve. Physical properties of liquid and pipe elasticity parameters were considered in both simulations, which are in very good agreement and differences in comparison with experimental data are minimal.

Pbar Beam Stacking in the Recycler by Longitudinal Phase-space Coating

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

Bhat, C. M.

2013-08-06

Barrier rf buckets have brought about new challenges in longitudinal beam dynamics of charged particle beams in synchrotrons and at the same time led to many new remarkable prospects in beam handling. In this paper, I describe a novel beam stacking scheme for synchrotrons using barrier buckets without any emittance dilution to the beam. First I discuss the general principle of the method, called longitudinal phase-space coating. Multi-particle beam dynamics simulations of the scheme applied to the Recycler, convincingly validates the concepts and feasibility of the method. Then I demonstrate the technique experimentally in the Recycler and also use itmore » in operation. A spin-off of this scheme is its usefulness in mapping the incoherent synchrotron tune spectrum of the beam particles in barrier buckets and producing a clean hollow beam in longitudinal phase space. Both of which are described here in detail with illustrations. The beam stacking scheme presented here is the first of its kind.« less

Automatic Selection of Order Parameters in the Analysis of Large Scale Molecular Dynamics Simulations.

PubMed

Sultan, Mohammad M; Kiss, Gert; Shukla, Diwakar; Pande, Vijay S

2014-12-09

Given the large number of crystal structures and NMR ensembles that have been solved to date, classical molecular dynamics (MD) simulations have become powerful tools in the atomistic study of the kinetics and thermodynamics of biomolecular systems on ever increasing time scales. By virtue of the high-dimensional conformational state space that is explored, the interpretation of large-scale simulations faces difficulties not unlike those in the big data community. We address this challenge by introducing a method called clustering based feature selection (CB-FS) that employs a posterior analysis approach. It combines supervised machine learning (SML) and feature selection with Markov state models to automatically identify the relevant degrees of freedom that separate conformational states. We highlight the utility of the method in the evaluation of large-scale simulations and show that it can be used for the rapid and automated identification of relevant order parameters involved in the functional transitions of two exemplary cell-signaling proteins central to human disease states.

Hidden attractors in dynamical systems

NASA Astrophysics Data System (ADS)

Dudkowski, Dawid; Jafari, Sajad; Kapitaniak, Tomasz; Kuznetsov, Nikolay V.; Leonov, Gennady A.; Prasad, Awadhesh

2016-06-01

Complex dynamical systems, ranging from the climate, ecosystems to financial markets and engineering applications typically have many coexisting attractors. This property of the system is called multistability. The final state, i.e., the attractor on which the multistable system evolves strongly depends on the initial conditions. Additionally, such systems are very sensitive towards noise and system parameters so a sudden shift to a contrasting regime may occur. To understand the dynamics of these systems one has to identify all possible attractors and their basins of attraction. Recently, it has been shown that multistability is connected with the occurrence of unpredictable attractors which have been called hidden attractors. The basins of attraction of the hidden attractors do not touch unstable fixed points (if exists) and are located far away from such points. Numerical localization of the hidden attractors is not straightforward since there are no transient processes leading to them from the neighborhoods of unstable fixed points and one has to use the special analytical-numerical procedures. From the viewpoint of applications, the identification of hidden attractors is the major issue. The knowledge about the emergence and properties of hidden attractors can increase the likelihood that the system will remain on the most desirable attractor and reduce the risk of the sudden jump to undesired behavior. We review the most representative examples of hidden attractors, discuss their theoretical properties and experimental observations. We also describe numerical methods which allow identification of the hidden attractors.

The Dynamics of Perception and Action

ERIC Educational Resources Information Center

Warren, William H.

2006-01-01

How might one account for the organization in behavior without attributing it to an internal control structure? The present article develops a theoretical framework called behavioral dynamics that integrates an information-based approach to perception with a dynamical systems approach to action. For a given task, the agent and its environment are…

Power-rate synchronization of coupled genetic oscillators with unbounded time-varying delay.

PubMed

Alofi, Abdulaziz; Ren, Fengli; Al-Mazrooei, Abdullah; Elaiw, Ahmed; Cao, Jinde

2015-10-01

In this paper, a new synchronization problem for the collective dynamics among genetic oscillators with unbounded time-varying delay is investigated. The dynamical system under consideration consists of an array of linearly coupled identical genetic oscillators with each oscillators having unbounded time-delays. A new concept called power-rate synchronization, which is different from both the asymptotical synchronization and the exponential synchronization, is put forward to facilitate handling the unbounded time-varying delays. By using a combination of the Lyapunov functional method, matrix inequality techniques and properties of Kronecker product, we derive several sufficient conditions that ensure the coupled genetic oscillators to be power-rate synchronized. The criteria obtained in this paper are in the form of matrix inequalities. Illustrative example is presented to show the effectiveness of the obtained results.

Guided SAR image despeckling with probabilistic non local weights

NASA Astrophysics Data System (ADS)

Gokul, Jithin; Nair, Madhu S.; Rajan, Jeny

2017-12-01

SAR images are generally corrupted by granular disturbances called speckle, which makes visual analysis and detail extraction a difficult task. Non Local despeckling techniques with probabilistic similarity has been a recent trend in SAR despeckling. To achieve effective speckle suppression without compromising detail preservation, we propose an improvement for the existing Generalized Guided Filter with Bayesian Non-Local Means (GGF-BNLM) method. The proposed method (Guided SAR Image Despeckling with Probabilistic Non Local Weights) replaces parametric constants based on heuristics in GGF-BNLM method with dynamically derived values based on the image statistics for weight computation. Proposed changes make GGF-BNLM method adaptive and as a result, significant improvement is achieved in terms of performance. Experimental analysis on SAR images shows excellent speckle reduction without compromising feature preservation when compared to GGF-BNLM method. Results are also compared with other state-of-the-art and classic SAR depseckling techniques to demonstrate the effectiveness of the proposed method.

Modal identification of structures by a novel approach based on FDD-wavelet method

NASA Astrophysics Data System (ADS)

Tarinejad, Reza; Damadipour, Majid

2014-02-01

An important application of system identification in structural dynamics is the determination of natural frequencies, mode shapes and damping ratios during operation which can then be used for calibrating numerical models. In this paper, the combination of two advanced methods of Operational Modal Analysis (OMA) called Frequency Domain Decomposition (FDD) and Continuous Wavelet Transform (CWT) based on novel cyclic averaging of correlation functions (CACF) technique are used for identification of dynamic properties. By using this technique, the autocorrelation of averaged correlation functions is used instead of original signals. Integration of FDD and CWT methods is used to overcome their deficiency and take advantage of the unique capabilities of these methods. The FDD method is able to accurately estimate the natural frequencies and mode shapes of structures in the frequency domain. On the other hand, the CWT method is in the time-frequency domain for decomposition of a signal at different frequencies and determines the damping coefficients. In this paper, a new formulation applied to the wavelet transform of the averaged correlation function of an ambient response is proposed. This application causes to accurate estimation of damping ratios from weak (noise) or strong (earthquake) vibrations and long or short duration record. For this purpose, the modified Morlet wavelet having two free parameters is used. The optimum values of these two parameters are obtained by employing a technique which minimizes the entropy of the wavelet coefficients matrix. The capabilities of the novel FDD-Wavelet method in the system identification of various dynamic systems with regular or irregular distribution of mass and stiffness are illustrated. This combined approach is superior to classic methods and yields results that agree well with the exact solutions of the numerical models.

SVAS3: Strain Vector Aided Sensorization of Soft Structures.

PubMed

Culha, Utku; Nurzaman, Surya G; Clemens, Frank; Iida, Fumiya

2014-07-17

Soft material structures exhibit high deformability and conformability which can be useful for many engineering applications such as robots adapting to unstructured and dynamic environments. However, the fact that they have almost infinite degrees of freedom challenges conventional sensory systems and sensorization approaches due to the difficulties in adapting to soft structure deformations. In this paper, we address this challenge by proposing a novel method which designs flexible sensor morphologies to sense soft material deformations by using a functional material called conductive thermoplastic elastomer (CTPE). This model-based design method, called Strain Vector Aided Sensorization of Soft Structures (SVAS3), provides a simulation platform which analyzes soft body deformations and automatically finds suitable locations for CTPE-based strain gauge sensors to gather strain information which best characterizes the deformation. Our chosen sensor material CTPE exhibits a set of unique behaviors in terms of strain length electrical conductivity, elasticity, and shape adaptability, allowing us to flexibly design sensor morphology that can best capture strain distributions in a given soft structure. We evaluate the performance of our approach by both simulated and real-world experiments and discuss the potential and limitations.

Dynamics on Networks of Manifolds

NASA Astrophysics Data System (ADS)

DeVille, Lee; Lerman, Eugene

2015-03-01

We propose a precise definition of a continuous time dynamical system made up of interacting open subsystems. The interconnections of subsystems are coded by directed graphs. We prove that the appropriate maps of graphs called graph fibrations give rise to maps of dynamical systems. Consequently surjective graph fibrations give rise to invariant subsystems and injective graph fibrations give rise to projections of dynamical systems.

Data-driven reverse engineering of signaling pathways using ensembles of dynamic models.

PubMed

Henriques, David; Villaverde, Alejandro F; Rocha, Miguel; Saez-Rodriguez, Julio; Banga, Julio R

2017-02-01

Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models), which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks): it builds dynamic (based on ordinary differential equation) models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training). For this task, SELDOM's ensemble prediction is not only consistently better than predictions from individual models, but also often outperforms the state of the art represented by the methods used in the HPN-DREAM challenge.

Data-driven reverse engineering of signaling pathways using ensembles of dynamic models

PubMed Central

Henriques, David; Villaverde, Alejandro F.; Banga, Julio R.

2017-01-01

Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models), which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks): it builds dynamic (based on ordinary differential equation) models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training). For this task, SELDOM’s ensemble prediction is not only consistently better than predictions from individual models, but also often outperforms the state of the art represented by the methods used in the HPN-DREAM challenge. PMID:28166222

Soil Moisture Dynamics Under Corn, Soybean, and Perennial Kura Clover

USDA-ARS?s Scientific Manuscript database

Rising global food and energy consumption call for increased agricultural production, whereas rising concerns for environmental quality call for farming systems with more favorable environmental impacts. Improved understanding and management of plant-soil water interactions are central to meeting th...

Crossfit analysis: a novel method to characterize the dynamics of induced plant responses.

PubMed

Jansen, Jeroen J; van Dam, Nicole M; Hoefsloot, Huub C J; Smilde, Age K

2009-12-16

Many plant species show induced responses that protect them against exogenous attacks. These responses involve the production of many different bioactive compounds. Plant species belonging to the Brassicaceae family produce defensive glucosinolates, which may greatly influence their favorable nutritional properties for humans. Each responding compound may have its own dynamic profile and metabolic relationships with other compounds. The chemical background of the induced response is therefore highly complex and may therefore not reveal all the properties of the response in any single model. This study therefore aims to describe the dynamics of the glucosinolate response, measured at three time points after induction in a feral Brassica, by a three-faceted approach, based on Principal Component Analysis. First the large-scale aspects of the response are described in a 'global model' and then each time-point in the experiment is individually described in 'local models' that focus on phenomena that occur at specific moments in time. Although each local model describes the variation among the plants at one time-point as well as possible, the response dynamics are lost. Therefore a novel method called the 'Crossfit' is described that links the local models of different time-points to each other. Each element of the described analysis approach reveals different aspects of the response. The crossfit shows that smaller dynamic changes may occur in the response that are overlooked by global models, as illustrated by the analysis of a metabolic profiling dataset of the same samples.

Crossfit analysis: a novel method to characterize the dynamics of induced plant responses

PubMed Central

2009-01-01

Background Many plant species show induced responses that protect them against exogenous attacks. These responses involve the production of many different bioactive compounds. Plant species belonging to the Brassicaceae family produce defensive glucosinolates, which may greatly influence their favorable nutritional properties for humans. Each responding compound may have its own dynamic profile and metabolic relationships with other compounds. The chemical background of the induced response is therefore highly complex and may therefore not reveal all the properties of the response in any single model. Results This study therefore aims to describe the dynamics of the glucosinolate response, measured at three time points after induction in a feral Brassica, by a three-faceted approach, based on Principal Component Analysis. First the large-scale aspects of the response are described in a 'global model' and then each time-point in the experiment is individually described in 'local models' that focus on phenomena that occur at specific moments in time. Although each local model describes the variation among the plants at one time-point as well as possible, the response dynamics are lost. Therefore a novel method called the 'Crossfit' is described that links the local models of different time-points to each other. Conclusions Each element of the described analysis approach reveals different aspects of the response. The crossfit shows that smaller dynamic changes may occur in the response that are overlooked by global models, as illustrated by the analysis of a metabolic profiling dataset of the same samples. PMID:20015363

Generating high-speed dynamic running gaits in a quadruped robot using an evolutionary search.

PubMed

Krasny, Darren P; Orin, David E

2004-08-01

Over the past several decades, there has been a considerable interest in investigating high-speed dynamic gaits for legged robots. While much research has been published, both in the biomechanics and engineering fields regarding the analysis of these gaits, no single study has adequately characterized the dynamics of high-speed running as can be achieved in a realistic, yet simple, robotic system. The goal of this paper is to find the most energy-efficient, natural, and unconstrained gallop that can be achieved using a simulated quadrupedal robot with articulated legs, asymmetric mass distribution, and compliant legs. For comparison purposes, we also implement the bound and canter. The model used here is planar, although we will show that it captures much of the predominant dynamic characteristics observed in animals. While it is not our goal to prove anything about biological locomotion, the dynamic similarities between the gaits we produce and those found in animals does indicate a similar underlying dynamic mechanism. Thus, we will show that achieving natural, efficient high-speed locomotion is possible even with a fairly simple robotic system. To generate the high-speed gaits, we use an efficient evolutionary algorithm called set-based stochastic optimization. This algorithm finds open-loop control parameters to generate periodic trajectories for the body. Several alternative methods are tested to generate periodic trajectories for the legs. The combined solutions found by the evolutionary search and the periodic-leg methods, over a range of speeds up to 10.0 m/s, reveal "biological" characteristics that are emergent properties of the underlying gaits.

Quantifying socio-economic indicators in developing countries from mobile phone communication data: applications to Côte d’Ivoire

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

Mao, Huina; Shuai, Xin; Ahn, Yong -Yeol

The widespread adoption of mobile devices that record the communications, social relations, and movements of billions of individuals in great detail presents unique opportunities for the study of social structures and human dynamics at very large scales. This is particularly the case for developing countries where social and economic data can be hard to obtain and is often too sparse for real-time analytics. In this paper, we leverage mobile call log data from Côte d’Ivoire to analyze the relations between its nation-wide communications network and the socio-economic dynamics of its regional economies. We introduce the CallRank indicator to quantify themore » relative importance of an area on the basis of call records, and show that a region’s ratio of in- and out-going calls can predict its income level. We detect a communication divide between rich and poor regions of Côte d’Ivoire, which corresponds to existing socio-economic data. Our results demonstrate the potential of mobile communication data to monitor the economic development and social dynamics of low-income developing countries in the absence of extensive econometric and social data. Finally, our work may support efforts to stimulate sustainable economic development and to reduce poverty and inequality.« less

Quantifying socio-economic indicators in developing countries from mobile phone communication data: applications to Côte d’Ivoire

DOE PAGES

Mao, Huina; Shuai, Xin; Ahn, Yong -Yeol; ...

2015-10-13

The widespread adoption of mobile devices that record the communications, social relations, and movements of billions of individuals in great detail presents unique opportunities for the study of social structures and human dynamics at very large scales. This is particularly the case for developing countries where social and economic data can be hard to obtain and is often too sparse for real-time analytics. In this paper, we leverage mobile call log data from Côte d’Ivoire to analyze the relations between its nation-wide communications network and the socio-economic dynamics of its regional economies. We introduce the CallRank indicator to quantify themore » relative importance of an area on the basis of call records, and show that a region’s ratio of in- and out-going calls can predict its income level. We detect a communication divide between rich and poor regions of Côte d’Ivoire, which corresponds to existing socio-economic data. Our results demonstrate the potential of mobile communication data to monitor the economic development and social dynamics of low-income developing countries in the absence of extensive econometric and social data. Finally, our work may support efforts to stimulate sustainable economic development and to reduce poverty and inequality.« less

Dynamic malware analysis using IntroVirt: a modified hypervisor-based system

NASA Astrophysics Data System (ADS)

White, Joshua S.; Pape, Stephen R.; Meily, Adam T.; Gloo, Richard M.

2013-05-01

In this paper, we present a system for Dynamic Malware Analysis which incorporates the use of IntroVirt™. IntroVirt is an introspective hypervisor architecture and infrastructure that supports advanced analysis techniques for stealth-malwareanalysis. This system allows for complete guest monitoring and interaction, including the manipulation and blocking of system calls. IntroVirt is capable of bypassing virtual machine detection capabilities of even the most sophisticated malware, by spoofing returns to system call responses. Additional fuzzing capabilities can be employed to detect both malware vulnerabilities and polymorphism.

EC86-33385-002

NASA Image and Video Library

1986-02-27

This photograph shows a modified General Dynamics AFTI/F-111A Aardvark in flight with supercritical mission adaptive wings (MAW) installed. With the phasing out of the TACT program came a renewed effort by the Air Force Flight Dynamics Laboratory to extend supercritical wing technology to a higher level of performance. In the early 1980s the supercritical wing on the F-111A aircraft was replaced with a wing built by Boeing Aircraft Company System called a “mission adaptive wing” (MAW), and a joint NASA and Air Force program called Advanced Fighter Technology Integration (AFTI) was born.

Free-Swinging Failure Tolerance for Robotic Manipulators. Degree awarded by Purdue Univ.

NASA Technical Reports Server (NTRS)

English, James

1997-01-01

Under this GSRP fellowship, software-based failure-tolerance techniques were developed for robotic manipulators. The focus was on failures characterized by the loss of actuator torque at a joint, called free-swinging failures. The research results spanned many aspects of the free-swinging failure-tolerance problem, from preparing for an expected failure to discovery of postfailure capabilities to establishing efficient methods to realize those capabilities. Developed algorithms were verified using computer-based dynamic simulations, and these were further verified using hardware experiments at Johnson Space Center.

Defect inspection using a time-domain mode decomposition technique

NASA Astrophysics Data System (ADS)

Zhu, Jinlong; Goddard, Lynford L.

2018-03-01

In this paper, we propose a technique called time-varying frequency scanning (TVFS) to meet the challenges in killer defect inspection. The proposed technique enables the dynamic monitoring of defects by checking the hopping in the instantaneous frequency data and the classification of defect types by comparing the difference in frequencies. The TVFS technique utilizes the bidimensional empirical mode decomposition (BEMD) method to separate the defect information from the sea of system errors. This significantly improve the signal-to-noise ratio (SNR) and moreover, it potentially enables reference-free defect inspection.

Stability properties of a general class of nonlinear dynamical systems

NASA Astrophysics Data System (ADS)

Gléria, I. M.; Figueiredo, A.; Rocha Filho, T. M.

2001-05-01

We establish sufficient conditions for the boundedness of the trajectories and the stability of the fixed points in a class of general nonlinear systems, the so-called quasi-polynomial vector fields, with the help of a natural embedding of such systems in a family of generalized Lotka-Volterra (LV) equations. A purely algebraic procedure is developed to determine such conditions. We apply our method to obtain new results for LV systems, by a reparametrization in time variable, and to study general nonlinear vector fields, originally far from the LV format.

Clustangles: An Open Library for Clustering Angular Data.

PubMed

Sargsyan, Karen; Hua, Yun Hao; Lim, Carmay

2015-08-24

Dihedral angles are good descriptors of the numerous conformations visited by large, flexible systems, but their analysis requires directional statistics. A single package including the various multivariate statistical methods for angular data that accounts for the distinct topology of such data does not exist. Here, we present a lightweight standalone, operating-system independent package called Clustangles to fill this gap. Clustangles will be useful in analyzing the ever-increasing number of structures in the Protein Data Bank and clustering the copious conformations from increasingly long molecular dynamics simulations.

Relaxation dynamics of internal segments of DNA chains in nanochannels

NASA Astrophysics Data System (ADS)

Jain, Aashish; Muralidhar, Abhiram; Dorfman, Kevin; Dorfman Group Team

We will present relaxation dynamics of internal segments of a DNA chain confined in nanochannel. The results have direct application in genome mapping technology, where long DNA molecules containing sequence-specific fluorescent probes are passed through an array of nanochannels to linearize them, and then the distances between these probes (the so-called ``DNA barcode'') are measured. The relaxation dynamics of internal segments set the experimental error due to dynamic fluctuations. We developed a multi-scale simulation algorithm, combining a Pruned-Enriched Rosenbluth Method (PERM) simulation of a discrete wormlike chain model with hard spheres with Brownian dynamics (BD) simulations of a bead-spring chain. Realistic parameters such as the bead friction coefficient and spring force law parameters are obtained from PERM simulations and then mapped onto the bead-spring model. The BD simulations are carried out to obtain the extension autocorrelation functions of various segments, which furnish their relaxation times. Interestingly, we find that (i) corner segments relax faster than the center segments and (ii) relaxation times of corner segments do not depend on the contour length of DNA chain, whereas the relaxation times of center segments increase linearly with DNA chain size.

Förster resonance energy transfer as a tool to study photoreceptor biology

PubMed Central

Hovan, Stephanie C.; Howell, Scott; Park, Paul S.-H.

2010-01-01

Vision is initiated in photoreceptor cells of the retina by a set of biochemical events called phototransduction. These events occur via coordinated dynamic processes that include changes in secondary messenger concentrations, conformational changes and post-translational modifications of signaling proteins, and protein-protein interactions between signaling partners. A complete description of the orchestration of these dynamic processes is still unavailable. Described in this work is the first step in the development of tools combining fluorescent protein technology, Förster resonance energy transfer (FRET), and transgenic animals that have the potential to reveal important molecular insights about the dynamic processes occurring in photoreceptor cells. We characterize the fluorescent proteins SCFP3A and SYFP2 for use as a donor-acceptor pair in FRET assays, which will facilitate the visualization of dynamic processes in living cells. We also demonstrate the targeted expression of these fluorescent proteins to the rod photoreceptor cells of Xenopus laevis, and describe a general method for detecting FRET in these cells. The general approaches described here can address numerous types of questions related to phototransduction and photoreceptor biology by providing a platform to visualize dynamic processes in molecular detail within a native context. PMID:21198205

Advances in the mechanical modeling of filamentous actin and its cross-linked networks on multiple scales.

PubMed

Unterberger, Michael J; Holzapfel, Gerhard A

2014-11-01

The protein actin is a part of the cytoskeleton and, therefore, responsible for the mechanical properties of the cells. Starting with the single molecule up to the final structure, actin creates a hierarchical structure of several levels exhibiting a remarkable behavior. The hierarchy spans several length scales and limitations in computational power; therefore, there is a call for different mechanical modeling approaches for the different scales. On the molecular level, we may consider each atom in molecular dynamics simulations. Actin forms filaments by combining the molecules into a double helix. In a model, we replace molecular subdomains using coarse-graining methods, allowing the investigation of larger systems of several atoms. These models on the nanoscale inform continuum mechanical models of large filaments, which are based on worm-like chain models for polymers. Assemblies of actin filaments are connected with cross-linker proteins. Models with discrete filaments, so-called Mikado models, allow us to investigate the dependence of the properties of networks on the parameters of the constituents. Microstructurally motivated continuum models of the networks provide insights into larger systems containing cross-linked actin networks. Modeling of such systems helps to gain insight into the processes on such small scales. On the other hand, they call for verification and hence trigger the improvement of established experiments and the development of new methods.

Generalized-active-space pair-density functional theory: an efficient method to study large, strongly correlated, conjugated systems.

PubMed

Ghosh, Soumen; Cramer, Christopher J; Truhlar, Donald G; Gagliardi, Laura

2017-04-01

Predicting ground- and excited-state properties of open-shell organic molecules by electronic structure theory can be challenging because an accurate treatment has to correctly describe both static and dynamic electron correlation. Strongly correlated systems, i.e. , systems with near-degeneracy correlation effects, are particularly troublesome. Multiconfigurational wave function methods based on an active space are adequate in principle, but it is impractical to capture most of the dynamic correlation in these methods for systems characterized by many active electrons. We recently developed a new method called multiconfiguration pair-density functional theory (MC-PDFT), that combines the advantages of wave function theory and density functional theory to provide a more practical treatment of strongly correlated systems. Here we present calculations of the singlet-triplet gaps in oligoacenes ranging from naphthalene to dodecacene. Calculations were performed for unprecedently large orbitally optimized active spaces of 50 electrons in 50 orbitals, and we test a range of active spaces and active space partitions, including four kinds of frontier orbital partitions. We show that MC-PDFT can predict the singlet-triplet splittings for oligoacenes consistent with the best available and much more expensive methods, and indeed MC-PDFT may constitute the benchmark against which those other models should be compared, given the absence of experimental data.

Dynamic frame resizing with convolutional neural network for efficient video compression

NASA Astrophysics Data System (ADS)

Kim, Jaehwan; Park, Youngo; Choi, Kwang Pyo; Lee, JongSeok; Jeon, Sunyoung; Park, JeongHoon

2017-09-01

In the past, video codecs such as vc-1 and H.263 used a technique to encode reduced-resolution video and restore original resolution from the decoder for improvement of coding efficiency. The techniques of vc-1 and H.263 Annex Q are called dynamic frame resizing and reduced-resolution update mode, respectively. However, these techniques have not been widely used due to limited performance improvements that operate well only under specific conditions. In this paper, video frame resizing (reduced/restore) technique based on machine learning is proposed for improvement of coding efficiency. The proposed method features video of low resolution made by convolutional neural network (CNN) in encoder and reconstruction of original resolution using CNN in decoder. The proposed method shows improved subjective performance over all the high resolution videos which are dominantly consumed recently. In order to assess subjective quality of the proposed method, Video Multi-method Assessment Fusion (VMAF) which showed high reliability among many subjective measurement tools was used as subjective metric. Moreover, to assess general performance, diverse bitrates are tested. Experimental results showed that BD-rate based on VMAF was improved by about 51% compare to conventional HEVC. Especially, VMAF values were significantly improved in low bitrate. Also, when the method is subjectively tested, it had better subjective visual quality in similar bit rate.

Automatic classification of killer whale vocalizations using dynamic time warping.

PubMed

Brown, Judith C; Miller, Patrick J O

2007-08-01

A set of killer whale sounds from Marineland were recently classified automatically [Brown et al., J. Acoust. Soc. Am. 119, EL34-EL40 (2006)] into call types using dynamic time warping (DTW), multidimensional scaling, and kmeans clustering to give near-perfect agreement with a perceptual classification. Here the effectiveness of four DTW algorithms on a larger and much more challenging set of calls by Northern Resident whales will be examined, with each call consisting of two independently modulated pitch contours and having considerable overlap in contours for several of the perceptual call types. Classification results are given for each of the four algorithms for the low frequency contour (LFC), the high frequency contour (HFC), their derivatives, and weighted sums of the distances corresponding to LFC with HFC, LFC with its derivative, and HFC with its derivative. The best agreement with the perceptual classification was 90% attained by the Sakoe-Chiba algorithm for the low frequency contours alone.

A CFD Approach to Modeling Spacecraft Fuel Slosh

NASA Technical Reports Server (NTRS)

Marsell, Brandon; Gangadharan, Sathya; Chatman, Yadira; Sudermann, James; Schlee, Keith; Ristow, James E.

2009-01-01

Energy dissipation and resonant coupling from sloshing fuel in spacecraft fuel tanks is a problem that occurs in the design of many spacecraft. In the case of a spin stabilized spacecraft, this energy dissipation can cause a growth in the spacecrafts' nutation (wobble) that may lead to disastrous consequences for the mission. Even in non-spinning spacecraft, coupling between the spacecraft or upper stage flight control system and an unanticipated slosh resonance can result in catastrophe. By using a Computational Fluid Dynamics (CFD) solver such as Fluent, a model for this fuel slosh can be created. The accuracy of the model must be tested by comparing its results to an experimental test case. Such a model will allow for the variation of many different parameters such as fluid viscosity and gravitational field, yielding a deeper understanding of spacecraft slosh dynamics. In order to gain a better understanding of the dynamics behind sloshing fluids, the Launch Services Program (LSP) at the NASA Kennedy Space Center (KSC) is interested in finding ways to better model this behavior. Thanks to past research, a state-of-the-art fuel slosh research facility was designed and fabricated at Embry Riddle Aeronautical University (ERAU). This test facility has produced interesting results and a fairly reliable parameter estimation process to predict the necessary values that accurately characterize a mechanical pendulum analog model. The current study at ERAU uses a different approach to model the free surface sloshing of liquid in a spherical tank using Computational Fluid Dynamics (CFD) methods. Using a software package called Fluent, a model was created to simulate the sloshing motion of the propellant. This finite volume program uses a technique called the Volume of Fluid (VOF) method to model the interaction between two fluids [4]. For the case of free surface slosh, the two fluids are the propellant and air. As the fuel sloshes around in the tank, it naturally displaces the air. Using the conservation of mass, momentum, and energy equations, as well as the VOF equations, one can predict the behavior of the sloshing fluid and calculate the forces, pressure gradients, and velocity field for the entire liquid as a function of time.

Statistical inference of dynamic resting-state functional connectivity using hierarchical observation modeling.

PubMed

Sojoudi, Alireza; Goodyear, Bradley G

2016-12-01

Spontaneous fluctuations of blood-oxygenation level-dependent functional magnetic resonance imaging (BOLD fMRI) signals are highly synchronous between brain regions that serve similar functions. This provides a means to investigate functional networks; however, most analysis techniques assume functional connections are constant over time. This may be problematic in the case of neurological disease, where functional connections may be highly variable. Recently, several methods have been proposed to determine moment-to-moment changes in the strength of functional connections over an imaging session (so called dynamic connectivity). Here a novel analysis framework based on a hierarchical observation modeling approach was proposed, to permit statistical inference of the presence of dynamic connectivity. A two-level linear model composed of overlapping sliding windows of fMRI signals, incorporating the fact that overlapping windows are not independent was described. To test this approach, datasets were synthesized whereby functional connectivity was either constant (significant or insignificant) or modulated by an external input. The method successfully determines the statistical significance of a functional connection in phase with the modulation, and it exhibits greater sensitivity and specificity in detecting regions with variable connectivity, when compared with sliding-window correlation analysis. For real data, this technique possesses greater reproducibility and provides a more discriminative estimate of dynamic connectivity than sliding-window correlation analysis. Hum Brain Mapp 37:4566-4580, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

QAARM: quasi-anharmonic autoregressive model reveals molecular recognition pathways in ubiquitin

PubMed Central

Savol, Andrej J.; Burger, Virginia M.; Agarwal, Pratul K.; Ramanathan, Arvind; Chennubhotla, Chakra S.

2011-01-01

Motivation: Molecular dynamics (MD) simulations have dramatically improved the atomistic understanding of protein motions, energetics and function. These growing datasets have necessitated a corresponding emphasis on trajectory analysis methods for characterizing simulation data, particularly since functional protein motions and transitions are often rare and/or intricate events. Observing that such events give rise to long-tailed spatial distributions, we recently developed a higher-order statistics based dimensionality reduction method, called quasi-anharmonic analysis (QAA), for identifying biophysically-relevant reaction coordinates and substates within MD simulations. Further characterization of conformation space should consider the temporal dynamics specific to each identified substate. Results: Our model uses hierarchical clustering to learn energetically coherent substates and dynamic modes of motion from a 0.5 μs ubiqutin simulation. Autoregressive (AR) modeling within and between states enables a compact and generative description of the conformational landscape as it relates to functional transitions between binding poses. Lacking a predictive component, QAA is extended here within a general AR model appreciative of the trajectory's temporal dependencies and the specific, local dynamics accessible to a protein within identified energy wells. These metastable states and their transition rates are extracted within a QAA-derived subspace using hierarchical Markov clustering to provide parameter sets for the second-order AR model. We show the learned model can be extrapolated to synthesize trajectories of arbitrary length. Contact: ramanathana@ornl.gov; chakracs@pitt.edu PMID:21685101

Bayesian B-spline mapping for dynamic quantitative traits.

PubMed

Xing, Jun; Li, Jiahan; Yang, Runqing; Zhou, Xiaojing; Xu, Shizhong

2012-04-01

Owing to their ability and flexibility to describe individual gene expression at different time points, random regression (RR) analyses have become a popular procedure for the genetic analysis of dynamic traits whose phenotypes are collected over time. Specifically, when modelling the dynamic patterns of gene expressions in the RR framework, B-splines have been proved successful as an alternative to orthogonal polynomials. In the so-called Bayesian B-spline quantitative trait locus (QTL) mapping, B-splines are used to characterize the patterns of QTL effects and individual-specific time-dependent environmental errors over time, and the Bayesian shrinkage estimation method is employed to estimate model parameters. Extensive simulations demonstrate that (1) in terms of statistical power, Bayesian B-spline mapping outperforms the interval mapping based on the maximum likelihood; (2) for the simulated dataset with complicated growth curve simulated by B-splines, Legendre polynomial-based Bayesian mapping is not capable of identifying the designed QTLs accurately, even when higher-order Legendre polynomials are considered and (3) for the simulated dataset using Legendre polynomials, the Bayesian B-spline mapping can find the same QTLs as those identified by Legendre polynomial analysis. All simulation results support the necessity and flexibility of B-spline in Bayesian mapping of dynamic traits. The proposed method is also applied to a real dataset, where QTLs controlling the growth trajectory of stem diameters in Populus are located.

Extracting protein dynamics information from overlapped NMR signals using relaxation dispersion difference NMR spectroscopy.

PubMed

Konuma, Tsuyoshi; Harada, Erisa; Sugase, Kenji

2015-12-01

Protein dynamics plays important roles in many biological events, such as ligand binding and enzyme reactions. NMR is mostly used for investigating such protein dynamics in a site-specific manner. Recently, NMR has been actively applied to large proteins and intrinsically disordered proteins, which are attractive research targets. However, signal overlap, which is often observed for such proteins, hampers accurate analysis of NMR data. In this study, we have developed a new methodology called relaxation dispersion difference that can extract conformational exchange parameters from overlapped NMR signals measured using relaxation dispersion spectroscopy. In relaxation dispersion measurements, the signal intensities of fluctuating residues vary according to the Carr-Purcell-Meiboon-Gill pulsing interval, whereas those of non-fluctuating residues are constant. Therefore, subtraction of each relaxation dispersion spectrum from that with the highest signal intensities, measured at the shortest pulsing interval, leaves only the signals of the fluctuating residues. This is the principle of the relaxation dispersion difference method. This new method enabled us to extract exchange parameters from overlapped signals of heme oxygenase-1, which is a relatively large protein. The results indicate that the structural flexibility of a kink in the heme-binding site is important for efficient heme binding. Relaxation dispersion difference requires neither selectively labeled samples nor modification of pulse programs; thus it will have wide applications in protein dynamics analysis.

Social Dynamics in the Preschool

ERIC Educational Resources Information Center

Martin, Carol Lynn; Fabes, Richard A.; Hanish, Laura D.; Hollenstein, Tom

2005-01-01

In this paper, we consider how concepts from dynamic systems (such as attractors, repellors, and self-organization) can be applied to the study of young children's peer relationships. We also consider how these concepts can be used to explore basic issues involving early peer processes. We use the dynamical systems approach called state space grid…

Dynamic simulation of train derailments

DOT National Transportation Integrated Search

2006-11-05

This paper describes a planar rigid-body model to examine the gross motions of rail cars in a train derailment. The model is implemented using a commercial software package called ADAMS (Automatic Dynamic Analysis of Mechanical Systems). The results ...

An Introduction to Intelligent Networks

DTIC Science & Technology

1994-02-01

customers in particular) to "specify a different geographic location for the call to terminate at. depending on the location of the calling customer ...corporate and military alike), with the promise also that they support affordable and dynamic reconfiguration. For example, as a domestic customer . I... relationship has an SCP serving a distribution of SSP elements to pnride wupport for calls that invoke IN functionality. And is in turn coatrolied and

Microtubule catastrophe and rescue.

PubMed

Gardner, Melissa K; Zanic, Marija; Howard, Jonathon

2013-02-01

Microtubules are long cylindrical polymers composed of tubulin subunits. In cells, microtubules play an essential role in architecture and motility. For example, microtubules give shape to cells, serve as intracellular transport tracks, and act as key elements in important cellular structures such as axonemes and mitotic spindles. To accomplish these varied functions, networks of microtubules in cells are very dynamic, continuously remodeling through stochastic length fluctuations at the ends of individual microtubules. The dynamic behavior at the end of an individual microtubule is termed 'dynamic instability'. This behavior manifests itself by periods of persistent microtubule growth interrupted by occasional switching to rapid shrinkage (called microtubule 'catastrophe'), and then by switching back from shrinkage to growth (called microtubule 'rescue'). In this review, we summarize recent findings which provide new insights into the mechanisms of microtubule catastrophe and rescue, and discuss the impact of these findings in regards to the role of microtubule dynamics inside of cells. Copyright © 2012 Elsevier Ltd. All rights reserved.

Group cohesion in foraging meerkats: follow the moving 'vocal hot spot'.

PubMed

Gall, Gabriella E C; Manser, Marta B

2017-04-01

Group coordination, when 'on the move' or when visibility is low, is a challenge faced by many social living animals. While some animals manage to maintain cohesion solely through visual contact, the mechanism of group cohesion through other modes of communication, a necessity when visual contact is reduced, is not yet understood. Meerkats ( Suricata suricatta ), a small, social carnivore, forage as a cohesive group while moving continuously. While foraging, they frequently emit 'close calls', soft close-range contact calls. Variations in their call rates based on their local environment, coupled with individual movement, produce a dynamic acoustic landscape with a moving 'vocal hotspot' of the highest calling activity. We investigated whether meerkats follow such a vocal hotspot by playing back close calls of multiple individuals to foraging meerkats from the front and back edge of the group simultaneously. These two artificially induced vocal hotspots caused the group to spatially elongate and split into two subgroups. We conclude that meerkats use the emergent dynamic call pattern of the group to adjust their movement direction and maintain cohesion. Our study describes a highly flexible mechanism for the maintenance of group cohesion through vocal communication, for mobile species in habitats with low visibility and where movement decisions need to be adjusted continuously to changing environmental conditions.

The density-matrix renormalization group: a short introduction.

PubMed

Schollwöck, Ulrich

2011-07-13

The density-matrix renormalization group (DMRG) method has established itself over the last decade as the leading method for the simulation of the statics and dynamics of one-dimensional strongly correlated quantum lattice systems. The DMRG is a method that shares features of a renormalization group procedure (which here generates a flow in the space of reduced density operators) and of a variational method that operates on a highly interesting class of quantum states, so-called matrix product states (MPSs). The DMRG method is presented here entirely in the MPS language. While the DMRG generally fails in larger two-dimensional systems, the MPS picture suggests a straightforward generalization to higher dimensions in the framework of tensor network states. The resulting algorithms, however, suffer from difficulties absent in one dimension, apart from a much more unfavourable efficiency, such that their ultimate success remains far from clear at the moment.

Efficient Fluid Dynamic Design Optimization Using Cartesian Grids

NASA Technical Reports Server (NTRS)

Dadone, A.; Grossman, B.; Sellers, Bill (Technical Monitor)

2004-01-01

This report is subdivided in three parts. The first one reviews a new approach to the computation of inviscid flows using Cartesian grid methods. The crux of the method is the curvature-corrected symmetry technique (CCST) developed by the present authors for body-fitted grids. The method introduces ghost cells near the boundaries whose values are developed from an assumed flow-field model in vicinity of the wall consisting of a vortex flow, which satisfies the normal momentum equation and the non-penetration condition. The CCST boundary condition was shown to be substantially more accurate than traditional boundary condition approaches. This improved boundary condition is adapted to a Cartesian mesh formulation, which we call the Ghost Body-Cell Method (GBCM). In this approach, all cell centers exterior to the body are computed with fluxes at the four surrounding cell edges. There is no need for special treatment corresponding to cut cells which complicate other Cartesian mesh methods.

Simultaneous Aerodynamic Analysis and Design Optimization (SAADO) for a 3-D Flexible Wing

NASA Technical Reports Server (NTRS)

Gumbert, Clyde R.; Hou, Gene J.-W.

2001-01-01

The formulation and implementation of an optimization method called Simultaneous Aerodynamic Analysis and Design Optimization (SAADO) are extended from single discipline analysis (aerodynamics only) to multidisciplinary analysis - in this case, static aero-structural analysis - and applied to a simple 3-D wing problem. The method aims to reduce the computational expense incurred in performing shape optimization using state-of-the-art Computational Fluid Dynamics (CFD) flow analysis, Finite Element Method (FEM) structural analysis and sensitivity analysis tools. Results for this small problem show that the method reaches the same local optimum as conventional optimization. However, unlike its application to the win,, (single discipline analysis), the method. as I implemented here, may not show significant reduction in the computational cost. Similar reductions were seen in the two-design-variable (DV) problem results but not in the 8-DV results given here.

Energy landscape analysis of neuroimaging data

NASA Astrophysics Data System (ADS)

Ezaki, Takahiro; Watanabe, Takamitsu; Ohzeki, Masayuki; Masuda, Naoki

2017-05-01

Computational neuroscience models have been used for understanding neural dynamics in the brain and how they may be altered when physiological or other conditions change. We review and develop a data-driven approach to neuroimaging data called the energy landscape analysis. The methods are rooted in statistical physics theory, in particular the Ising model, also known as the (pairwise) maximum entropy model and Boltzmann machine. The methods have been applied to fitting electrophysiological data in neuroscience for a decade, but their use in neuroimaging data is still in its infancy. We first review the methods and discuss some algorithms and technical aspects. Then, we apply the methods to functional magnetic resonance imaging data recorded from healthy individuals to inspect the relationship between the accuracy of fitting, the size of the brain system to be analysed and the data length. This article is part of the themed issue `Mathematical methods in medicine: neuroscience, cardiology and pathology'.

Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis.

PubMed

Tashkova, Katerina; Korošec, Peter; Silc, Jurij; Todorovski, Ljupčo; Džeroski, Sašo

2011-10-11

We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and artificial data, for all observability scenarios considered, and for all amounts of noise added to the artificial data. In sum, the meta-heuristic methods considered are suitable for estimating the parameters in the ODE model of the dynamics of endocytosis under a range of conditions: With the model and conditions being representative of parameter estimation tasks in ODE models of biochemical systems, our results clearly highlight the promise of bio-inspired meta-heuristic methods for parameter estimation in dynamic system models within system biology.

Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis

PubMed Central

2011-01-01

Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and artificial data, for all observability scenarios considered, and for all amounts of noise added to the artificial data. In sum, the meta-heuristic methods considered are suitable for estimating the parameters in the ODE model of the dynamics of endocytosis under a range of conditions: With the model and conditions being representative of parameter estimation tasks in ODE models of biochemical systems, our results clearly highlight the promise of bio-inspired meta-heuristic methods for parameter estimation in dynamic system models within system biology. PMID:21989196

Multilevel relaxation phenomena and population trapping

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

Hioe, F.T.

1991-11-01

This final report summarizes the main results of our work supported by DOE since 1982. A list of 45 publications supported by this DOE Grant is attached at the end of this report. The use and exploitation of the SU(N) dynamic symmetry to the study of the dynamics of laser-atom interaction was the starting point of our research work under this DOE Grant, and is our most original contribution to the field of quantum electrodynamics. Many results of general and special interests have been derived and developed from this starting point and the following is a summary of them: (1)more » We have introduced a set of simple relations based on the principle of unitary invariance which has proved to be useful for the study of the dynamics of a quantum system involving coupling. (2) We have found various specific conditions under which (a) we may have trapped population, or (b) we may send laser pulses through a multilevel atomic medium without attenuation. (3) We have found a remarkably efficient method for optimal state selective multiphoton population transfer, that employs two or more spatially overlapping lasers arranged in an unconventional sequence which we called counterintuitive''. A recent suggestion by Profs. P. Marte, P. Zoller and J.L. Hall to use this counterintuitive method for atomic beam deflections promises to make this remarkably effective procedure to become an important method in atomic interferometry.« less

A Multi-Cycle Q-Modulation for Dynamic Optimization of Inductive Links.

PubMed

Lee, Byunghun; Yeon, Pyungwoo; Ghovanloo, Maysam

2016-08-01

This paper presents a new method, called multi-cycle Q-modulation, which can be used in wireless power transmission (WPT) to modulate the quality factor (Q) of the receiver (Rx) coil and dynamically optimize the load impedance to maximize the power transfer efficiency (PTE) in two-coil links. A key advantage of the proposed method is that it can be easily implemented using off-the-shelf components without requiring fast switching at or above the carrier frequency, which is more suitable for integrated circuit design. Moreover, the proposed technique does not need any sophisticated synchronization between the power carrier and Q-modulation switching pulses. The multi-cycle Q-modulation is analyzed theoretically by a lumped circuit model, and verified in simulation and measurement using an off-the-shelf prototype. Automatic resonance tuning (ART) in the Rx, combined with multi-cycle Q-modulation helped maximizing PTE of the inductive link dynamically in the presence of environmental and loading variations, which can otherwise significantly degrade the PTE in multi-coil settings. In the prototype conventional 2-coil link, the proposed method increased the power amplifier (PA) plus inductive link efficiency from 4.8% to 16.5% at ( R L = 1 kΩ, d 23 = 3 cm), and from 23% to 28.2% at ( R L = 100 Ω, d 23 = 3 cm) after 11% change in the resonance capacitance, while delivering 168.1 mW to the load (PDL).

Three pillars for achieving quantum mechanical molecular dynamics simulations of huge systems: Divide-and-conquer, density-functional tight-binding, and massively parallel computation.

PubMed

Nishizawa, Hiroaki; Nishimura, Yoshifumi; Kobayashi, Masato; Irle, Stephan; Nakai, Hiromi

2016-08-05

The linear-scaling divide-and-conquer (DC) quantum chemical methodology is applied to the density-functional tight-binding (DFTB) theory to develop a massively parallel program that achieves on-the-fly molecular reaction dynamics simulations of huge systems from scratch. The functions to perform large scale geometry optimization and molecular dynamics with DC-DFTB potential energy surface are implemented to the program called DC-DFTB-K. A novel interpolation-based algorithm is developed for parallelizing the determination of the Fermi level in the DC method. The performance of the DC-DFTB-K program is assessed using a laboratory computer and the K computer. Numerical tests show the high efficiency of the DC-DFTB-K program, a single-point energy gradient calculation of a one-million-atom system is completed within 60 s using 7290 nodes of the K computer. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Dynamics of asteroid family halos constrained by spin/shape models

NASA Astrophysics Data System (ADS)

Broz, Miroslav

2016-10-01

A number of asteroid families cannot be identified solely on the basis of the Hierarchical Clustering Method (HCM), because they have additional 'former' members in the surroundings which constitute a so called halo (e.g. Broz & Morbidelli 2013). They are usually mixed up with the background population which has to be taken into account too.Luckily, new photometric observations allow to derive new spin/shape models, which serve as independent constraints for dynamical models. For example, a recent census of the Eos family shows 43 core and 27 halo asteroids (including background) with known spin orientations.To this point, we present a complex spin-orbital model which includes full N-body dynamics and consequently accounts for all mean-motion, secular, or three-body gravitational resonances, the Yarkovsky drift, YORP effect, collisional reorientations and also spin-orbital interactions. These are especially important for the Koronis family. In this project, we make use of data from the DAMIT database and ProjectSoft Blue Eye 600 observatory.

Conceptual Design Optimization of an Augmented Stability Aircraft Incorporating Dynamic Response Performance Constraints

NASA Technical Reports Server (NTRS)

Welstead, Jason

2014-01-01

This research focused on incorporating stability and control into a multidisciplinary de- sign optimization on a Boeing 737-class advanced concept called the D8.2b. A new method of evaluating the aircraft handling performance using quantitative evaluation of the sys- tem to disturbances, including perturbations, continuous turbulence, and discrete gusts, is presented. A multidisciplinary design optimization was performed using the D8.2b transport air- craft concept. The con guration was optimized for minimum fuel burn using a design range of 3,000 nautical miles. Optimization cases were run using xed tail volume coecients, static trim constraints, and static trim and dynamic response constraints. A Cessna 182T model was used to test the various dynamic analysis components, ensuring the analysis was behaving as expected. Results of the optimizations show that including stability and con- trol in the design process drastically alters the optimal design, indicating that stability and control should be included in conceptual design to avoid system level penalties later in the design process.

Optimal subinterval selection approach for power system transient stability simulation

DOE PAGES

Kim, Soobae; Overbye, Thomas J.

2015-10-21

Power system transient stability analysis requires an appropriate integration time step to avoid numerical instability as well as to reduce computational demands. For fast system dynamics, which vary more rapidly than what the time step covers, a fraction of the time step, called a subinterval, is used. However, the optimal value of this subinterval is not easily determined because the analysis of the system dynamics might be required. This selection is usually made from engineering experiences, and perhaps trial and error. This paper proposes an optimal subinterval selection approach for power system transient stability analysis, which is based on modalmore » analysis using a single machine infinite bus (SMIB) system. Fast system dynamics are identified with the modal analysis and the SMIB system is used focusing on fast local modes. An appropriate subinterval time step from the proposed approach can reduce computational burden and achieve accurate simulation responses as well. As a result, the performance of the proposed method is demonstrated with the GSO 37-bus system.« less

Neural dynamic programming and its application to control systems

NASA Astrophysics Data System (ADS)

Seong, Chang-Yun

There are few general practical feedback control methods for nonlinear MIMO (multi-input-multi-output) systems, although such methods exist for their linear counterparts. Neural Dynamic Programming (NDP) is proposed as a practical design method of optimal feedback controllers for nonlinear MIMO systems. NDP is an offspring of both neural networks and optimal control theory. In optimal control theory, the optimal solution to any nonlinear MIMO control problem may be obtained from the Hamilton-Jacobi-Bellman equation (HJB) or the Euler-Lagrange equations (EL). The two sets of equations provide the same solution in different forms: EL leads to a sequence of optimal control vectors, called Feedforward Optimal Control (FOC); HJB yields a nonlinear optimal feedback controller, called Dynamic Programming (DP). DP produces an optimal solution that can reject disturbances and uncertainties as a result of feedback. Unfortunately, computation and storage requirements associated with DP solutions can be problematic, especially for high-order nonlinear systems. This dissertation presents an approximate technique for solving the DP problem based on neural network techniques that provides many of the performance benefits (e.g., optimality and feedback) of DP and benefits from the numerical properties of neural networks. We formulate neural networks to approximate optimal feedback solutions whose existence DP justifies. We show the conditions under which NDP closely approximates the optimal solution. Finally, we introduce the learning operator characterizing the learning process of the neural network in searching the optimal solution. The analysis of the learning operator provides not only a fundamental understanding of the learning process in neural networks but also useful guidelines for selecting the number of weights of the neural network. As a result, NDP finds---with a reasonable amount of computation and storage---the optimal feedback solutions to nonlinear MIMO control problems that would be very difficult to solve with DP. NDP was demonstrated on several applications such as the lateral autopilot logic for a Boeing 747, the minimum fuel control of a double-integrator plant with bounded control, the backward steering of a two-trailer truck, and the set-point control of a two-link robot arm.

A parallel Discrete Element Method to model collisions between non-convex particles

NASA Astrophysics Data System (ADS)

Rakotonirina, Andriarimina Daniel; Delenne, Jean-Yves; Wachs, Anthony

2017-06-01

In many dry granular and suspension flow configurations, particles can be highly non-spherical. It is now well established in the literature that particle shape affects the flow dynamics or the microstructure of the particles assembly in assorted ways as e.g. compacity of packed bed or heap, dilation under shear, resistance to shear, momentum transfer between translational and angular motions, ability to form arches and block the flow. In this talk, we suggest an accurate and efficient way to model collisions between particles of (almost) arbitrary shape. For that purpose, we develop a Discrete Element Method (DEM) combined with a soft particle contact model. The collision detection algorithm handles contacts between bodies of various shape and size. For nonconvex bodies, our strategy is based on decomposing a non-convex body into a set of convex ones. Therefore, our novel method can be called "glued-convex method" (in the sense clumping convex bodies together), as an extension of the popular "glued-spheres" method, and is implemented in our own granular dynamics code Grains3D. Since the whole problem is solved explicitly, our fully-MPI parallelized code Grains3D exhibits a very high scalability when dynamic load balancing is not required. In particular, simulations on up to a few thousands cores in configurations involving up to a few tens of millions of particles can readily be performed. We apply our enhanced numerical model to (i) the collapse of a granular column made of convex particles and (i) the microstructure of a heap of non-convex particles in a cylindrical reactor.

StreamMap: Smooth Dynamic Visualization of High-Density Streaming Points.

PubMed

Li, Chenhui; Baciu, George; Han, Yu

2018-03-01

Interactive visualization of streaming points for real-time scatterplots and linear blending of correlation patterns is increasingly becoming the dominant mode of visual analytics for both big data and streaming data from active sensors and broadcasting media. To better visualize and interact with inter-stream patterns, it is generally necessary to smooth out gaps or distortions in the streaming data. Previous approaches either animate the points directly or present a sampled static heat-map. We propose a new approach, called StreamMap, to smoothly blend high-density streaming points and create a visual flow that emphasizes the density pattern distributions. In essence, we present three new contributions for the visualization of high-density streaming points. The first contribution is a density-based method called super kernel density estimation that aggregates streaming points using an adaptive kernel to solve the overlapping problem. The second contribution is a robust density morphing algorithm that generates several smooth intermediate frames for a given pair of frames. The third contribution is a trend representation design that can help convey the flow directions of the streaming points. The experimental results on three datasets demonstrate the effectiveness of StreamMap when dynamic visualization and visual analysis of trend patterns on streaming points are required.

Dynamic Rupture Modeling in Three Dimensions on Unstructured Meshes Using a Discontinuous Galerkin Method

NASA Astrophysics Data System (ADS)

Pelties, C.; Käser, M.

2010-12-01

We will present recent developments concerning the extensions of the ADER-DG method to solve three dimensional dynamic rupture problems on unstructured tetrahedral meshes. The simulation of earthquake rupture dynamics and seismic wave propagation using a discontinuous Galerkin (DG) method in 2D was recently presented by J. de la Puente et al. (2009). A considerable feature of this study regarding spontaneous rupture problems was the combination of the DG scheme and a time integration method using Arbitrarily high-order DERivatives (ADER) to provide high accuracy in space and time with the discretization on unstructured meshes. In the resulting discrete velocity-stress formulation of the elastic wave equations variables are naturally discontinuous at the interfaces between elements. The so-called Riemann problem can then be solved to obtain well defined values of the variables at the discontinuity itself. This is in particular valid for the fault at which a certain friction law has to be evaluated. Hence, the fault’s geometry is honored by the computational mesh. This way, complex fault planes can be modeled adequately with small elements while fast mesh coarsening is possible with increasing distance from the fault. Due to the strict locality of the scheme using only direct neighbor communication, excellent parallel behavior can be observed. A further advantage of the scheme is that it avoids spurious high-frequency contributions in the slip rate spectra and therefore does not require artificial Kelvin-Voigt damping or filtering of synthetic seismograms. In order to test the accuracy of the ADER-DG method the Southern California Earthquake Center (SCEC) benchmark for spontaneous rupture simulations was employed. Reference: J. de la Puente, J.-P. Ampuero, and M. Käser (2009), Dynamic rupture modeling on unstructured meshes using a discontinuous Galerkin method, JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 114, B10302, doi:10.1029/2008JB006271

Maximum caliber inference of nonequilibrium processes

NASA Astrophysics Data System (ADS)

Otten, Moritz; Stock, Gerhard

2010-07-01

Thirty years ago, Jaynes suggested a general theoretical approach to nonequilibrium statistical mechanics, called maximum caliber (MaxCal) [Annu. Rev. Phys. Chem. 31, 579 (1980)]. MaxCal is a variational principle for dynamics in the same spirit that maximum entropy is a variational principle for equilibrium statistical mechanics. Motivated by the success of maximum entropy inference methods for equilibrium problems, in this work the MaxCal formulation is applied to the inference of nonequilibrium processes. That is, given some time-dependent observables of a dynamical process, one constructs a model that reproduces these input data and moreover, predicts the underlying dynamics of the system. For example, the observables could be some time-resolved measurements of the folding of a protein, which are described by a few-state model of the free energy landscape of the system. MaxCal then calculates the probabilities of an ensemble of trajectories such that on average the data are reproduced. From this probability distribution, any dynamical quantity of the system can be calculated, including population probabilities, fluxes, or waiting time distributions. After briefly reviewing the formalism, the practical numerical implementation of MaxCal in the case of an inference problem is discussed. Adopting various few-state models of increasing complexity, it is demonstrated that the MaxCal principle indeed works as a practical method of inference: The scheme is fairly robust and yields correct results as long as the input data are sufficient. As the method is unbiased and general, it can deal with any kind of time dependency such as oscillatory transients and multitime decays.

Dynamics in the Fitness-Income plane: Brazilian states vs World countries

PubMed Central

Operti, Felipe G.; Pugliese, Emanuele; Andrade, José S.; Pietronero, Luciano

2018-01-01

In this paper we introduce a novel algorithm, called Exogenous Fitness, to calculate the Fitness of subnational entities and we apply it to the states of Brazil. In the last decade, several indices were introduced to measure the competitiveness of countries by looking at the complexity of their export basket. Tacchella et al (2012) developed a non-monetary metric called Fitness. In this paper, after an overview about Brazil as a whole and the comparison with the other BRIC countries, we introduce a new methodology based on the Fitness algorithm, called Exogenous Fitness. Combining the results with the Gross Domestic Product per capita (GDPp), we look at the dynamics of the Brazilian states in the Fitness-Income plane. Two regimes are distinguishable: one with high predictability and the other with low predictability, showing a deep analogy with the heterogeneous dynamics of the World countries. Furthermore, we compare the ranking of the Brazilian states according to the Exogenous Fitness with the ranking obtained through two other techniques, namely Endogenous Fitness and Economic Complexity Index. PMID:29874265

Dynamics in the Fitness-Income plane: Brazilian states vs World countries.

PubMed

Operti, Felipe G; Pugliese, Emanuele; Andrade, José S; Pietronero, Luciano; Gabrielli, Andrea

2018-01-01

In this paper we introduce a novel algorithm, called Exogenous Fitness, to calculate the Fitness of subnational entities and we apply it to the states of Brazil. In the last decade, several indices were introduced to measure the competitiveness of countries by looking at the complexity of their export basket. Tacchella et al (2012) developed a non-monetary metric called Fitness. In this paper, after an overview about Brazil as a whole and the comparison with the other BRIC countries, we introduce a new methodology based on the Fitness algorithm, called Exogenous Fitness. Combining the results with the Gross Domestic Product per capita (GDPp), we look at the dynamics of the Brazilian states in the Fitness-Income plane. Two regimes are distinguishable: one with high predictability and the other with low predictability, showing a deep analogy with the heterogeneous dynamics of the World countries. Furthermore, we compare the ranking of the Brazilian states according to the Exogenous Fitness with the ranking obtained through two other techniques, namely Endogenous Fitness and Economic Complexity Index.

Systems configured to distribute a telephone call, communication systems, communication methods and methods of routing a telephone call to a service representative

DOEpatents

Harris, Scott H.; Johnson, Joel A.; Neiswanger, Jeffery R.; Twitchell, Kevin E.

2004-03-09

The present invention includes systems configured to distribute a telephone call, communication systems, communication methods and methods of routing a telephone call to a customer service representative. In one embodiment of the invention, a system configured to distribute a telephone call within a network includes a distributor adapted to connect with a telephone system, the distributor being configured to connect a telephone call using the telephone system and output the telephone call and associated data of the telephone call; and a plurality of customer service representative terminals connected with the distributor and a selected customer service representative terminal being configured to receive the telephone call and the associated data, the distributor and the selected customer service representative terminal being configured to synchronize, application of the telephone call and associated data from the distributor to the selected customer service representative terminal.

Agent-based traffic management and reinforcement learning in congested intersection network.

DOT National Transportation Integrated Search

2012-08-01

This study evaluates the performance of traffic control systems based on reinforcement learning (RL), also called approximate dynamic programming (ADP). Two algorithms have been selected for testing: 1) Q-learning and 2) approximate dynamic programmi...

A dynamic system matching technique for improving the accuracy of MEMS gyroscopes

NASA Astrophysics Data System (ADS)

Stubberud, Peter A.; Stubberud, Stephen C.; Stubberud, Allen R.

2014-12-01

A classical MEMS gyro transforms angular rates into electrical values through Euler's equations of angular rotation. Production models of a MEMS gyroscope will have manufacturing errors in the coefficients of the differential equations. The output signal of a production gyroscope will be corrupted by noise, with a major component of the noise due to the manufacturing errors. As is the case of the components in an analog electronic circuit, one way of controlling the variability of a subsystem is to impose extremely tight control on the manufacturing process so that the coefficient values are within some specified bounds. This can be expensive and may even be impossible as is the case in certain applications of micro-electromechanical (MEMS) sensors. In a recent paper [2], the authors introduced a method for combining the measurements from several nominally equal MEMS gyroscopes using a technique based on a concept from electronic circuit design called dynamic element matching [1]. Because the method in this paper deals with systems rather than elements, it is called a dynamic system matching technique (DSMT). The DSMT generates a single output by randomly switching the outputs of several, nominally identical, MEMS gyros in and out of the switch output. This has the effect of 'spreading the spectrum' of the noise caused by the coefficient errors generated in the manufacture of the individual gyros. A filter can then be used to eliminate that part of the spread spectrum that is outside the pass band of the gyro. A heuristic analysis in that paper argues that the DSMT can be used to control the effects of the random coefficient variations. In a follow-on paper [4], a simulation of a DSMT indicated that the heuristics were consistent. In this paper, analytic expressions of the DSMT noise are developed which confirm that the earlier conclusions are valid. These expressions include the various DSMT design parameters and, therefore, can be used as design tools for DSMT systems.

A dynamic system matching technique for improving the accuracy of MEMS gyroscopes

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

Stubberud, Peter A., E-mail: stubber@ee.unlv.edu; Stubberud, Stephen C., E-mail: scstubberud@ieee.org; Stubberud, Allen R., E-mail: stubberud@att.net

A classical MEMS gyro transforms angular rates into electrical values through Euler's equations of angular rotation. Production models of a MEMS gyroscope will have manufacturing errors in the coefficients of the differential equations. The output signal of a production gyroscope will be corrupted by noise, with a major component of the noise due to the manufacturing errors. As is the case of the components in an analog electronic circuit, one way of controlling the variability of a subsystem is to impose extremely tight control on the manufacturing process so that the coefficient values are within some specified bounds. This canmore » be expensive and may even be impossible as is the case in certain applications of micro-electromechanical (MEMS) sensors. In a recent paper [2], the authors introduced a method for combining the measurements from several nominally equal MEMS gyroscopes using a technique based on a concept from electronic circuit design called dynamic element matching [1]. Because the method in this paper deals with systems rather than elements, it is called a dynamic system matching technique (DSMT). The DSMT generates a single output by randomly switching the outputs of several, nominally identical, MEMS gyros in and out of the switch output. This has the effect of 'spreading the spectrum' of the noise caused by the coefficient errors generated in the manufacture of the individual gyros. A filter can then be used to eliminate that part of the spread spectrum that is outside the pass band of the gyro. A heuristic analysis in that paper argues that the DSMT can be used to control the effects of the random coefficient variations. In a follow-on paper [4], a simulation of a DSMT indicated that the heuristics were consistent. In this paper, analytic expressions of the DSMT noise are developed which confirm that the earlier conclusions are valid. These expressions include the various DSMT design parameters and, therefore, can be used as design tools for DSMT systems.« less

Nonlinear Boltzmann equation for the homogeneous isotropic case: Some improvements to deterministic methods and applications to relaxation towards local equilibrium

NASA Astrophysics Data System (ADS)

Asinari, P.

2011-03-01

Boltzmann equation is one the most powerful paradigms for explaining transport phenomena in fluids. Since early fifties, it received a lot of attention due to aerodynamic requirements for high altitude vehicles, vacuum technology requirements and nowadays, micro-electro-mechanical systems (MEMs). Because of the intrinsic mathematical complexity of the problem, Boltzmann himself started his work by considering first the case when the distribution function does not depend on space (homogeneous case), but only on time and the magnitude of the molecular velocity (isotropic collisional integral). The interest with regards to the homogeneous isotropic Boltzmann equation goes beyond simple dilute gases. In the so-called econophysics, a Boltzmann type model is sometimes introduced for studying the distribution of wealth in a simple market. Another recent application of the homogeneous isotropic Boltzmann equation is given by opinion formation modeling in quantitative sociology, also called socio-dynamics or sociophysics. The present work [1] aims to improve the deterministic method for solving homogenous isotropic Boltzmann equation proposed by Aristov [2] by two ideas: (a) the homogeneous isotropic problem is reformulated first in terms of particle kinetic energy (this allows one to ensure exact particle number and energy conservation during microscopic collisions) and (b) a DVM-like correction (where DVM stands for Discrete Velocity Model) is adopted for improving the relaxation rates (this allows one to satisfy exactly the conservation laws at macroscopic level, which is particularly important for describing the late dynamics in the relaxation towards the equilibrium).

Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time-to-event in presence of censoring and competing risks.

PubMed

Blanche, Paul; Proust-Lima, Cécile; Loubère, Lucie; Berr, Claudine; Dartigues, Jean-François; Jacqmin-Gadda, Hélène

2015-03-01

Thanks to the growing interest in personalized medicine, joint modeling of longitudinal marker and time-to-event data has recently started to be used to derive dynamic individual risk predictions. Individual predictions are called dynamic because they are updated when information on the subject's health profile grows with time. We focus in this work on statistical methods for quantifying and comparing dynamic predictive accuracy of this kind of prognostic models, accounting for right censoring and possibly competing events. Dynamic area under the ROC curve (AUC) and Brier Score (BS) are used to quantify predictive accuracy. Nonparametric inverse probability of censoring weighting is used to estimate dynamic curves of AUC and BS as functions of the time at which predictions are made. Asymptotic results are established and both pointwise confidence intervals and simultaneous confidence bands are derived. Tests are also proposed to compare the dynamic prediction accuracy curves of two prognostic models. The finite sample behavior of the inference procedures is assessed via simulations. We apply the proposed methodology to compare various prediction models using repeated measures of two psychometric tests to predict dementia in the elderly, accounting for the competing risk of death. Models are estimated on the French Paquid cohort and predictive accuracies are evaluated and compared on the French Three-City cohort. © 2014, The International Biometric Society.

Geocenter motion estimated from GRACE orbits: The impact of F10.7 solar flux

NASA Astrophysics Data System (ADS)

Tseng, Tzu-Pang; Hwang, Cheinway; Sośnica, Krzysztof; Kuo, Chung-Yen; Liu, Ya-Chi; Yeh, Wen-Hao

2017-06-01

We assess the impact of orbit modeling on the origin offsets between GRACE kinematic and reduced-dynamic orbits. The origin of the kinematic orbit is the center of IGS network (CN), whereas the origin of the reduced-dynamic orbit is assumed to be the center of mass of the Earth (CM). Theoretically, the origin offset between these two orbits is associated with the geocenter motion. However, the dynamic property of the reduced-dynamic orbit is highly related to orbit parameterizations. The assessment of the F10.7 impact on the geocenter motion is implemented by using different orbit parameterization setups in the reduced-dynamic method. We generate two types of reduced-dynamic orbits using 15 and 240 empirical parameters per day from 2005 to 2012. The empirical parameter used in Bernese GNSS Software is called piece-wise constant empirical acceleration (PCA) and is mainly to absorb the non-gravitational forces mostly related to the atmospheric drag and solar radiation pressure. The differences between kinematic and dynamic orbits can serve as a measurement for geocenter. The RMS value of the geocenter measurement in the 15-PCA case is approximately 3.5 cm and approximately 2 cm in the 240-PCA case. The correlation between the orbit difference and F10.7 is about 0.90 in the 15-PCA case and -0.10 to 0 in the 240-PCA case. This implies that the reduced-dynamic orbit modeled with 240 PCAs absorbs the F10.7 variation, which aliases to the 15-PCA orbit solution. The annual amplitudes of the geocenter motion are 3.1, 3.1 and 2.5 mm in the 15-PCA case, compared to 0.9, 2.0 and 1.3 mm in the 240-PCA case in the X, Y and Z components, respectively. The 15-PCA solution is thus closer to the geocenter motions derived from other space-geodetic techniques. The proposed method is limited to the parameterizations in the reduced-dynamic approach.

Can investor sentiment be used to predict the stock price? Dynamic analysis based on China stock market

NASA Astrophysics Data System (ADS)

Guo, Kun; Sun, Yi; Qian, Xin

2017-03-01

With the development of the social network, the interaction between investors in stock market became more fast and convenient. Thus, investor sentiment which can influence their investment decisions may be quickly spread and magnified through the network, and to a certain extent the stock market can be affected. This paper collected the user comments data from a popular professional social networking site of China stock market called Xueqiu, then the investor sentiment data can be obtained through semantic analysis. The dynamic analysis on relationship between investor sentiment and stock market is proposed based on Thermal Optimal Path (TOP) method. The results show that the sentiment data was not always leading over stock market price, and it can be used to predict the stock price only when the stock has high investor attention.

Dynamic test input generation for multiple-fault isolation

NASA Technical Reports Server (NTRS)

Schaefer, Phil

1990-01-01

Recent work is Causal Reasoning has provided practical techniques for multiple fault diagnosis. These techniques provide a hypothesis/measurement diagnosis cycle. Using probabilistic methods, they choose the best measurements to make, then update fault hypotheses in response. For many applications such as computers and spacecraft, few measurement points may be accessible, or values may change quickly as the system under diagnosis operates. In these cases, a hypothesis/measurement cycle is insufficient. A technique is presented for a hypothesis/test-input/measurement diagnosis cycle. In contrast to generating tests a priori for determining device functionality, it dynamically generates tests in response to current knowledge about fault probabilities. It is shown how the mathematics previously used for measurement specification can be applied to the test input generation process. An example from an efficient implementation called Multi-Purpose Causal (MPC) is presented.

Scaling analysis of heart beat fluctuations data and its relationship with cyclic alternating pattern data during sleep

NASA Astrophysics Data System (ADS)

de León-Lomelí, R.; Murguía, J. S.; Chouvarda, I.; Méndez, M. O.; González-Galván, E.; Alba, A.

2016-01-01

During sleep there exists a nonlinear dynamic phenomenon, which is called cyclic alternating pattern. This phenomenon is generated in the brain and is composed of a series of events of short duration known as A-phases. It has been shown that A-phases can be found in other physiological systems such as the cardiovascular. However, there is no evidence that shows the temporal influence of the A-phases with the cardiovascular system. For this purpose, we consider the scaling method known as detrended fluctuation analysis (DFA). The analysis was carried out in well sleepers and insomnia people, and the numerical results show an increment in the scaling parameter for the insomnia subjects compared with the normal ones. In addition, the results of the heart dynamics suggests a persistent behavior toward the 1/f-noise.

Introduction to the focus issue: fifty years of chaos: applied and theoretical.

PubMed

Hikihara, Takashi; Holmes, Philip; Kambe, Tsutomu; Rega, Giuseppe

2012-12-01

The discovery of deterministic chaos in the late nineteenth century, its subsequent study, and the development of mathematical and computational methods for its analysis have substantially influenced the sciences. Chaos is, however, only one phenomenon in the larger area of dynamical systems theory. This Focus Issue collects 13 papers, from authors and research groups representing the mathematical, physical, and biological sciences, that were presented at a symposium held at Kyoto University from November 28 to December 2, 2011. The symposium, sponsored by the International Union of Theoretical and Applied Mechanics, was called 50 Years of Chaos: Applied and Theoretical. Following some historical remarks to provide a background for the last 50 years, and for chaos, this Introduction surveys the papers and identifies some common themes that appear in them and in the theory of dynamical systems.

Coherent structures: Comments on mechanisms

NASA Technical Reports Server (NTRS)

Hunt, J. C. R.

1987-01-01

There is now overwhelming evidence that in most turbulent flows there exist regions moving with the flow where the velocity and vorticity have a characteristic structure. These regions are called coherent structures because within them the large-scale distributions of velocity and/or vorticity remain coherent even as these structures move through the flow and interact with other structures. Since the flow enters and leaves the bounding surfaces of these structures, a useful definition for coherent structures is that they are open volumes with distinctive large-scale vorticity distributions. Possible fruitful directions for the study of the dynamics of coherent structures are suggested. Most coherent structures research to data was concentrated on measurement and kinematical analysis; there is now a welcome move to examine the dynamics of coherent structures, by a variety of different methods. A few of them will be described.

Individual killer whale vocal variation during intra-group behavioral dynamics

NASA Astrophysics Data System (ADS)

Grebner, Dawn M.

The scientific goal of this dissertation was to carefully study the signal structure of killer whale communications and vocal complexity and link them to behavioral circumstances. The overall objective of this research sought to provide insight into killer whale call content and usage which may be conveying information to conspecifics in order to maintain group cohesion. Data were collected in the summers of 2006 and 2007 in Johnstone Strait, British Columbia. For both individuals and small groups, vocalizations were isolated using a triangular hydrophone array and the behavioral movement patterns were captured by a theodolite and video camera positioned on a cliff overlooking the hyrophone locations. This dissertation is divided into four analysis chapters. In Chapter 3, discriminant analysis was used to validate the four N04 call subtypes which were originally parsed due to variations in slope segments. The first two functions of the discriminant analysis explained 97% of the variability. Most of the variability for the N04 call was found in the front convex and the terminal portions of the call, while very little variability was found in the center region of the call. This research revealed that individual killer whales produced multiple subtypes of the N04 call. No correlations of behaviors to acoustic parameters obtained were found. The aim of the Chapter 4 was to determine if killer whale calling behavior varied prior to and after the animals had joined. Pulsed call rates were found to be greater pre- compared to post-joining events. Two-way vocal exchanges were more common occurring 74% of the time during pre-joining events. In Chapter 5, initiated and first response to calls varied between age/sex class groups when mothers were separated from an offspring. Solo mothers and calves initiated pulsed calls more often than they responded. Most of the no vocal responses were due to mothers who were foraging. Finally, observations of the frequency split in N04 calls discussed in Chapter 6 showed that the higher frequency component (HFC) was always associated with sideband 7 (SB7) of the lower frequency component (LFC). Insight into Northern Resident killer whale intra-group vocal dynamics would aid our understanding of vocal behaviors of many other marine mammal species that rely on vocal exchanges for prey capture, group movement or survival. This is the first study to focus on killer whale vocal content and usage as it pertains to intra-group dynamics for (1) mother and offspring separations and (2) for all individuals prior to joining events, as well as (3) individual usage in a diverging pulsed call. It is also the first time the N04 call has been parsed into subtypes.

A New Engine for Schools: The Flexible Scheduling Paradigm

ERIC Educational Resources Information Center

Snyder, Yaakov; Herer, Yale T.; Moore, Michael

2012-01-01

We present a new approach for the organization of schools, which we call the flexible scheduling paradigm (FSP). FSP improves student learning by dynamically redeploying teachers and other pedagogical resources to provide students with customized learning conditions over shorter time periods called "mini-terms" instead of semesters or years. By…

Anticipatory Neurofuzzy Control

NASA Technical Reports Server (NTRS)

Mccullough, Claire L.

1994-01-01

Technique of feedback control, called "anticipatory neurofuzzy control," developed for use in controlling flexible structures and other dynamic systems for which mathematical models of dynamics poorly known or unknown. Superior ability to act during operation to compensate for, and adapt to, errors in mathematical model of dynamics, changes in dynamics, and noise. Also offers advantage of reduced computing time. Hybrid of two older fuzzy-logic control techniques: standard fuzzy control and predictive fuzzy control.

Is alarm calling risky? Marmots avoid calling from risky places.

PubMed

Collier, Travis C; Blumstein, Daniel T; Girod, Lewis; Taylor, Charles E

2010-12-01

Alarm calling is common in many species. A prevalent assumption is that calling puts the vocalizing individual at increased risk of predation. If calling is indeed costly, we need special explanations for its evolution and maintenance. In some, but not all species, callers vocalize away from safety and thus may be exposed to an increased risk of predation. However, for species that emit bouts with one or a few calls, it is often difficult to identify the caller and find the precise location where a call was produced. We analyzed the spatial dynamics of yellow-bellied marmot (Marmota flaviventris) alarm calling using an acoustic localization system to determine the location from which calls were emitted. Marmots almost always called from positions close to the safety of their burrows, and, if they produced more than one alarm call, tended to end their calling bouts closer to safety than they started them. These results suggest that for this species, potential increased predation risk from alarm calling is greatly mitigated and indeed calling may have limited predation costs.

Is alarm calling risky? Marmots avoid calling from risky places

PubMed Central

Collier, Travis C.; Blumstein, Daniel T.; Girod, Lewis; Taylor, Charles E.

2010-01-01

Alarm calling is common in many species. A prevalent assumption is that calling puts the vocalizing individual at increased risk of predation. If calling is indeed costly, we need special explanations for its evolution and maintenance. In some, but not all species, callers vocalize away from safety and thus may be exposed to an increased risk of predation. However, for species that emit bouts with one or a few calls, it is often difficult to identify the caller and find the precise location where a call was produced. We analyzed the spatial dynamics of yellow-bellied marmot (Marmota flaviventris) alarm calling using an acoustic localization system to determine the location from which calls were emitted. Marmots almost always called from positions close to the safety of their burrows, and, if they produced more than one alarm call, tended to end their calling bouts closer to safety than they started them. These results suggest that for this species, potential increased predation risk from alarm calling is greatly mitigated and indeed calling may have limited predation costs. PMID:21116460

Evaluation of Kirkwood-Buff integrals via finite size scaling: a large scale molecular dynamics study

NASA Astrophysics Data System (ADS)

Dednam, W.; Botha, A. E.

2015-01-01

Solvation of bio-molecules in water is severely affected by the presence of co-solvent within the hydration shell of the solute structure. Furthermore, since solute molecules can range from small molecules, such as methane, to very large protein structures, it is imperative to understand the detailed structure-function relationship on the microscopic level. For example, it is useful know the conformational transitions that occur in protein structures. Although such an understanding can be obtained through large-scale molecular dynamic simulations, it is often the case that such simulations would require excessively large simulation times. In this context, Kirkwood-Buff theory, which connects the microscopic pair-wise molecular distributions to global thermodynamic properties, together with the recently developed technique, called finite size scaling, may provide a better method to reduce system sizes, and hence also the computational times. In this paper, we present molecular dynamics trial simulations of biologically relevant low-concentration solvents, solvated by aqueous co-solvent solutions. In particular we compare two different methods of calculating the relevant Kirkwood-Buff integrals. The first (traditional) method computes running integrals over the radial distribution functions, which must be obtained from large system-size NVT or NpT simulations. The second, newer method, employs finite size scaling to obtain the Kirkwood-Buff integrals directly by counting the particle number fluctuations in small, open sub-volumes embedded within a larger reservoir that can be well approximated by a much smaller simulation cell. In agreement with previous studies, which made a similar comparison for aqueous co-solvent solutions, without the additional solvent, we conclude that the finite size scaling method is also applicable to the present case, since it can produce computationally more efficient results which are equivalent to the more costly radial distribution function method.

Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data

NASA Astrophysics Data System (ADS)

Pathak, Jaideep; Lu, Zhixin; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

2017-12-01

We use recent advances in the machine learning area known as "reservoir computing" to formulate a method for model-free estimation from data of the Lyapunov exponents of a chaotic process. The technique uses a limited time series of measurements as input to a high-dimensional dynamical system called a "reservoir." After the reservoir's response to the data is recorded, linear regression is used to learn a large set of parameters, called the "output weights." The learned output weights are then used to form a modified autonomous reservoir designed to be capable of producing an arbitrarily long time series whose ergodic properties approximate those of the input signal. When successful, we say that the autonomous reservoir reproduces the attractor's "climate." Since the reservoir equations and output weights are known, we can compute the derivatives needed to determine the Lyapunov exponents of the autonomous reservoir, which we then use as estimates of the Lyapunov exponents for the original input generating system. We illustrate the effectiveness of our technique with two examples, the Lorenz system and the Kuramoto-Sivashinsky (KS) equation. In the case of the KS equation, we note that the high dimensional nature of the system and the large number of Lyapunov exponents yield a challenging test of our method, which we find the method successfully passes.

Potential energy surface fitting by a statistically localized, permutationally invariant, local interpolating moving least squares method for the many-body potential: Method and application to N{sub 4}

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

Bender, Jason D.; Doraiswamy, Sriram; Candler, Graham V., E-mail: truhlar@umn.edu, E-mail: candler@aem.umn.edu

2014-02-07

Fitting potential energy surfaces to analytic forms is an important first step for efficient molecular dynamics simulations. Here, we present an improved version of the local interpolating moving least squares method (L-IMLS) for such fitting. Our method has three key improvements. First, pairwise interactions are modeled separately from many-body interactions. Second, permutational invariance is incorporated in the basis functions, using permutationally invariant polynomials in Morse variables, and in the weight functions. Third, computational cost is reduced by statistical localization, in which we statistically correlate the cutoff radius with data point density. We motivate our discussion in this paper with amore » review of global and local least-squares-based fitting methods in one dimension. Then, we develop our method in six dimensions, and we note that it allows the analytic evaluation of gradients, a feature that is important for molecular dynamics. The approach, which we call statistically localized, permutationally invariant, local interpolating moving least squares fitting of the many-body potential (SL-PI-L-IMLS-MP, or, more simply, L-IMLS-G2), is used to fit a potential energy surface to an electronic structure dataset for N{sub 4}. We discuss its performance on the dataset and give directions for further research, including applications to trajectory calculations.« less

On Numerical Heating

NASA Astrophysics Data System (ADS)

Liou, Meng-Sing

2013-11-01

The development of computational fluid dynamics over the last few decades has yielded enormous successes and capabilities that are being routinely employed today; however there remain some open problems to be properly resolved. One example is the so-called overheating problem, which can arise in two very different scenarios, from either colliding or receding streams. Common in both is a localized, numerically over-predicted temperature. Von Neumann reported the former, a compressive overheating, nearly 70 years ago and numerically smeared the temperature peak by introducing artificial diffusion. However, the latter is unphysical in an expansive (rarefying) situation; it still dogs every method known to the author. We will present a study aiming at resolving this overheating problem and we find that: (1) the entropy increase is one-to-one linked to the increase in the temperature rise and (2) the overheating is inevitable in the current computational fluid dynamics framework in practice. Finally we will show a simple hybrid method that fundamentally cures the overheating problem in a rarefying flow, but also retains the property of accurate shock capturing. Moreover, this remedy (enhancement of current numerical methods) can be included easily in the present Eulerian codes. This work is performed under NASA's Fundamental Aeronautics Program.

Integration of Human Reliability Analysis Models into the Simulation-Based Framework for the Risk-Informed Safety Margin Characterization Toolkit

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

Boring, Ronald; Mandelli, Diego; Rasmussen, Martin

2016-06-01

This report presents an application of a computation-based human reliability analysis (HRA) framework called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER). HUNTER has been developed not as a standalone HRA method but rather as framework that ties together different HRA methods to model dynamic risk of human activities as part of an overall probabilistic risk assessment (PRA). While we have adopted particular methods to build an initial model, the HUNTER framework is meant to be intrinsically flexible to new pieces that achieve particular modeling goals. In the present report, the HUNTER implementation has the following goals: •more » Integration with a high fidelity thermal-hydraulic model capable of modeling nuclear power plant behaviors and transients • Consideration of a PRA context • Incorporation of a solid psychological basis for operator performance • Demonstration of a functional dynamic model of a plant upset condition and appropriate operator response This report outlines these efforts and presents the case study of a station blackout scenario to demonstrate the various modules developed to date under the HUNTER research umbrella.« less

Network structure of multivariate time series.

PubMed

Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

2015-10-21

Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

Detection of baleen whales on an ocean-bottom seismometer array in the Lau Basin

NASA Astrophysics Data System (ADS)

Brodie, D.; Dunn, R.

2011-12-01

Long-term deployment of ocean-bottom seismometer arrays provides a unique opportunity for identifying and tracking whales in a manner not usually possible in biological studies. Large baleen whales emit low frequency (>5Hz) sounds called 'calls' or 'songs' that can be detected on either the hydrophone or vertical channel of the instrument at distances in excess of 50 km. The calls are distinct to individual species and even geographical groups among species, and are thought to serve a variety of purposes. Distinct repeating calls can be automatically identified using matched-filter processing, and whales can be located in a manner similar to that of earthquakes. Many baleen whale species are endangered, and little is known about their geographic distribution, population dynamics, and basic behaviors. The Lau back-arc basin, a tectonically active, elongated basin bounded by volcanic shallows, lies in the southwestern Pacific Ocean between Fiji and Tonga. Although whales are known to exist around Fiji and Tonga, little is understood about the population dynamics and migration patterns throughout the basin. Twenty-nine broadband ocean-bottom seismometers deployed in the basin recorded data for approximately ten months during the years 2009-2010. To date, four species of whales have been identified in the data: Blue (one call type), Humpback (two call types, including long-lasting 'songs'), Bryde's (one call type), and Fin whales (three call types). Three as-yet-unknown call types have also been identified. After the calls were identified, idealized spectrograms of the known calls were matched against the entire data set using an auto-detection algorithm. The auto-detection output provides the number of calls and times of year when each call type was recorded. Based on the results, whales migrate seasonally through the basin with some overlapping of species. Initial results also indicate that different species of whales are more common in some parts of the basin than others, suggesting preferences in water depth and distance to land. In future work, whales will be tracked through the basin using call localization information to illustrate migration patterns of the various species.

Nonequilibrium hypersonic flows simulations with asymptotic-preserving Monte Carlo methods

NASA Astrophysics Data System (ADS)

Ren, Wei; Liu, Hong; Jin, Shi

2014-12-01

In the rarefied gas dynamics, the DSMC method is one of the most popular numerical tools. It performs satisfactorily in simulating hypersonic flows surrounding re-entry vehicles and micro-/nano- flows. However, the computational cost is expensive, especially when Kn → 0. Even for flows in the near-continuum regime, pure DSMC simulations require a number of computational efforts for most cases. Albeit several DSMC/NS hybrid methods are proposed to deal with this, those methods still suffer from the boundary treatment, which may cause nonphysical solutions. Filbet and Jin [1] proposed a framework of new numerical methods of Boltzmann equation, called asymptotic preserving schemes, whose computational costs are affordable as Kn → 0. Recently, Ren et al. [2] realized the AP schemes with Monte Carlo methods (AP-DSMC), which have better performance than counterpart methods. In this paper, AP-DSMC is applied in simulating nonequilibrium hypersonic flows. Several numerical results are computed and analyzed to study the efficiency and capability of capturing complicated flow characteristics.

Control of water distribution networks with dynamic DMA topology using strictly feasible sequential convex programming

NASA Astrophysics Data System (ADS)

Wright, Robert; Abraham, Edo; Parpas, Panos; Stoianov, Ivan

2015-12-01

The operation of water distribution networks (WDN) with a dynamic topology is a recently pioneered approach for the advanced management of District Metered Areas (DMAs) that integrates novel developments in hydraulic modeling, monitoring, optimization, and control. A common practice for leakage management is the sectorization of WDNs into small zones, called DMAs, by permanently closing isolation valves. This facilitates water companies to identify bursts and estimate leakage levels by measuring the inlet flow for each DMA. However, by permanently closing valves, a number of problems have been created including reduced resilience to failure and suboptimal pressure management. By introducing a dynamic topology to these zones, these disadvantages can be eliminated while still retaining the DMA structure for leakage monitoring. In this paper, a novel optimization method based on sequential convex programming (SCP) is outlined for the control of a dynamic topology with the objective of reducing average zone pressure (AZP). A key attribute for control optimization is reliable convergence. To achieve this, the SCP method we propose guarantees that each optimization step is strictly feasible, resulting in improved convergence properties. By using a null space algorithm for hydraulic analyses, the computations required are also significantly reduced. The optimized control is actuated on a real WDN operated with a dynamic topology. This unique experimental program incorporates a number of technologies set up with the objective of investigating pioneering developments in WDN management. Preliminary results indicate AZP reductions for a dynamic topology of up to 6.5% over optimally controlled fixed topology DMAs. This article was corrected on 12 JAN 2016. See the end of the full text for details.

Mode Reduction and Upscaling of Reactive Transport Under Incomplete Mixing

NASA Astrophysics Data System (ADS)

Lester, D. R.; Bandopadhyay, A.; Dentz, M.; Le Borgne, T.

2016-12-01

Upscaling of chemical reactions in partially-mixed fluid environments is a challenging problem due to the detailed interactions between inherently nonlinear reaction kinetics and complex spatio-temporal concentration distributions under incomplete mixing. We address this challenge via the development of an order reduction method for the advection-diffusion-reaction equation (ADRE) via projection of the reaction kinetics onto a small number N of leading eigenmodes of the advection-diffusion operator (the so-called "strange eigenmodes" of the flow) as an N-by-N nonlinear system, whilst mixing dynamics only are projected onto the remaining modes. For simple kinetics and moderate Péclet and Damkhöler numbers, this approach yields analytic solutions for the concentration mean, evolving spatio-temporal distribution and PDF in terms of the well-mixed reaction kinetics and mixing dynamics. For more complex kinetics or large Péclet or Damkhöler numbers only a small number of modes are required to accurately quantify the mixing and reaction dynamics in terms of the concentration field and PDF, facilitating greatly simplified approximation and analysis of reactive transport. Approximate solutions of this low-order nonlinear system provide quantiative predictions of the evolving concentration PDF. We demonstrate application of this method to a simple random flow and various mass-action reaction kinetics.

Object-oriented design and implementation of CFDLab: a computer-assisted learning tool for fluid dynamics using dual reciprocity boundary element methodology

NASA Astrophysics Data System (ADS)

Friedrich, J.

1999-08-01

As lecturers, our main concern and goal is to develop more attractive and efficient ways of communicating up-to-date scientific knowledge to our students and facilitate an in-depth understanding of physical phenomena. Computer-based instruction is very promising to help both teachers and learners in their difficult task, which involves complex cognitive psychological processes. This complexity is reflected in high demands on the design and implementation methods used to create computer-assisted learning (CAL) programs. Due to their concepts, flexibility, maintainability and extended library resources, object-oriented modeling techniques are very suitable to produce this type of pedagogical tool. Computational fluid dynamics (CFD) enjoys not only a growing importance in today's research, but is also very powerful for teaching and learning fluid dynamics. For this purpose, an educational PC program for university level called 'CFDLab 1.1' for Windows™ was developed with an interactive graphical user interface (GUI) for multitasking and point-and-click operations. It uses the dual reciprocity boundary element method as a versatile numerical scheme, allowing to handle a variety of relevant governing equations in two dimensions on personal computers due to its simple pre- and postprocessing including 2D Laplace, Poisson, diffusion, transient convection-diffusion.

Development and application of dynamic hybrid multi-region inventory analysis for macro-level environmental policy analysis: a case study on climate policy in Taiwan.

PubMed

Chao, Chia-Wei; Heijungs, Reinout; Ma, Hwong-wen

2013-03-19

We develop a novel inventory method called Dynamic Hybrid Multi-Region Inventory analysis (DHMRI), which integrates the EEMRIOA and Integrated Hybrid LCA and applies time-dependent environmental intervention information for inventory analysis. Consequently, DHMRI is able to quantify the change in the environmental footprint caused by a specific policy while taking structural changes and technological dynamics into consideration. DHMRI is applied to assess the change in the total CO2 emissions associated with the total final demand caused by the climate policy in Taiwan to demonstrate the practicality of this novel method. The evaluation reveals that the implementation of mitigation measures included in the existing climate policy, such as an enhancement in energy efficiency, promotion of renewable energy, and limitation of the growth of energy-intensive industries, will lead to a 28% increase in the total CO2 emissions and that the main driver is the export-oriented electronics industry. Moreover, a major increase in the total emissions is predicted to occur in Southeast Asia and China. The observations from the case study reveal that DHMRI is capable of overcoming the limitations of existing assessment tools at macro-level evaluation of environmental policies.

Crystal Nucleation in Liquids: Open Questions and Future Challenges in Molecular Dynamics Simulations

PubMed Central

2016-01-01

The nucleation of crystals in liquids is one of nature’s most ubiquitous phenomena, playing an important role in areas such as climate change and the production of drugs. As the early stages of nucleation involve exceedingly small time and length scales, atomistic computer simulations can provide unique insights into the microscopic aspects of crystallization. In this review, we take stock of the numerous molecular dynamics simulations that, in the past few decades, have unraveled crucial aspects of crystal nucleation in liquids. We put into context the theoretical framework of classical nucleation theory and the state-of-the-art computational methods by reviewing simulations of such processes as ice nucleation and the crystallization of molecules in solutions. We shall see that molecular dynamics simulations have provided key insights into diverse nucleation scenarios, ranging from colloidal particles to natural gas hydrates, and that, as a result, the general applicability of classical nucleation theory has been repeatedly called into question. We have attempted to identify the most pressing open questions in the field. We believe that, by improving (i) existing interatomic potentials and (ii) currently available enhanced sampling methods, the community can move toward accurate investigations of realistic systems of practical interest, thus bringing simulations a step closer to experiments. PMID:27228560

Applying graph partitioning methods in measurement-based dynamic load balancing

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

Bhatele, Abhinav; Fourestier, Sebastien; Menon, Harshitha

Load imbalance leads to an increasing waste of resources as an application is scaled to more and more processors. Achieving the best parallel efficiency for a program requires optimal load balancing which is a NP-hard problem. However, finding near-optimal solutions to this problem for complex computational science and engineering applications is becoming increasingly important. Charm++, a migratable objects based programming model, provides a measurement-based dynamic load balancing framework. This framework instruments and then migrates over-decomposed objects to balance computational load and communication at runtime. This paper explores the use of graph partitioning algorithms, traditionally used for partitioning physical domains/meshes, formore » measurement-based dynamic load balancing of parallel applications. In particular, we present repartitioning methods developed in a graph partitioning toolbox called SCOTCH that consider the previous mapping to minimize migration costs. We also discuss a new imbalance reduction algorithm for graphs with irregular load distributions. We compare several load balancing algorithms using microbenchmarks on Intrepid and Ranger and evaluate the effect of communication, number of cores and number of objects on the benefit achieved from load balancing. New algorithms developed in SCOTCH lead to better performance compared to the METIS partitioners for several cases, both in terms of the application execution time and fewer number of objects migrated.« less

Crystal Nucleation in Liquids: Open Questions and Future Challenges in Molecular Dynamics Simulations.

PubMed

Sosso, Gabriele C; Chen, Ji; Cox, Stephen J; Fitzner, Martin; Pedevilla, Philipp; Zen, Andrea; Michaelides, Angelos

2016-06-22

The nucleation of crystals in liquids is one of nature's most ubiquitous phenomena, playing an important role in areas such as climate change and the production of drugs. As the early stages of nucleation involve exceedingly small time and length scales, atomistic computer simulations can provide unique insights into the microscopic aspects of crystallization. In this review, we take stock of the numerous molecular dynamics simulations that, in the past few decades, have unraveled crucial aspects of crystal nucleation in liquids. We put into context the theoretical framework of classical nucleation theory and the state-of-the-art computational methods by reviewing simulations of such processes as ice nucleation and the crystallization of molecules in solutions. We shall see that molecular dynamics simulations have provided key insights into diverse nucleation scenarios, ranging from colloidal particles to natural gas hydrates, and that, as a result, the general applicability of classical nucleation theory has been repeatedly called into question. We have attempted to identify the most pressing open questions in the field. We believe that, by improving (i) existing interatomic potentials and (ii) currently available enhanced sampling methods, the community can move toward accurate investigations of realistic systems of practical interest, thus bringing simulations a step closer to experiments.

Parallel/Vector Integration Methods for Dynamical Astronomy

NASA Astrophysics Data System (ADS)

Fukushima, T.

Progress of parallel/vector computers has driven us to develop suitable numerical integrators utilizing their computational power to the full extent while being independent on the size of system to be integrated. Unfortunately, the parallel version of Runge-Kutta type integrators are known to be not so efficient. Recently we developed a parallel version of the extrapolation method (Ito and Fukushima 1997), which allows variable timesteps and still gives an acceleration factor of 3-4 for general problems. While the vector-mode usage of Picard-Chebyshev method (Fukushima 1997a, 1997b) will lead the acceleration factor of order of 1000 for smooth problems such as planetary/satellites orbit integration. The success of multiple-correction PECE mode of time-symmetric implicit Hermitian integrator (Kokubo 1998) seems to enlighten Milankar's so-called "pipelined predictor corrector method", which is expected to lead an acceleration factor of 3-4. We will review these directions and discuss future prospects.

3D sensor placement strategy using the full-range pheromone ant colony system

NASA Astrophysics Data System (ADS)

Shuo, Feng; Jingqing, Jia

2016-07-01

An optimized sensor placement strategy will be extremely beneficial to ensure the safety and cost reduction considerations of structural health monitoring (SHM) systems. The sensors must be placed such that important dynamic information is obtained and the number of sensors is minimized. The practice is to select individual sensor directions by several 1D sensor methods and the triaxial sensors are placed in these directions for monitoring. However, this may lead to non-optimal placement of many triaxial sensors. In this paper, a new method, called FRPACS, is proposed based on the ant colony system (ACS) to solve the optimal placement of triaxial sensors. The triaxial sensors are placed as single units in an optimal fashion. And then the new method is compared with other algorithms using Dalian North Bridge. The computational precision and iteration efficiency of the FRPACS has been greatly improved compared with the original ACS and EFI method.

LCAMP: Location Constrained Approximate Message Passing for Compressed Sensing MRI

PubMed Central

Sung, Kyunghyun; Daniel, Bruce L; Hargreaves, Brian A

2016-01-01

Iterative thresholding methods have been extensively studied as faster alternatives to convex optimization methods for solving large-sized problems in compressed sensing. A novel iterative thresholding method called LCAMP (Location Constrained Approximate Message Passing) is presented for reducing computational complexity and improving reconstruction accuracy when a nonzero location (or sparse support) constraint can be obtained from view shared images. LCAMP modifies the existing approximate message passing algorithm by replacing the thresholding stage with a location constraint, which avoids adjusting regularization parameters or thresholding levels. This work is first compared with other conventional reconstruction methods using random 1D signals and then applied to dynamic contrast-enhanced breast MRI to demonstrate the excellent reconstruction accuracy (less than 2% absolute difference) and low computation time (5 - 10 seconds using Matlab) with highly undersampled 3D data (244 × 128 × 48; overall reduction factor = 10). PMID:23042658

Optimization of the launcher ascent trajectory leading to the global optimum without any initialization: the breakthrough of the Hamilton-Jacobi-Bellman approach

NASA Astrophysics Data System (ADS)

Bourgeois, E.; Bokanowski, O.; Zidani, H.; Désilles, A.

2018-06-01

The resolution of the launcher ascent trajectory problem by the so-called Hamilton-Jacobi-Bellman (HJB) approach, relying on the Dynamic Programming Principle, has been investigated. The method gives a global optimum and does not need any initialization procedure. Despite these advantages, this approach is seldom used because of the dicculties of computing the solution of the HJB equation for high dimension problems. The present study shows that an eccient resolution is found. An illustration of the method is proposed on a heavy class launcher, for a typical GEO (Geostationary Earth Orbit) mission. This study has been performed in the frame of the Centre National d'Etudes Spatiales (CNES) Launchers Research & Technology Program.

High-performance multiprocessor architecture for a 3-D lattice gas model

NASA Technical Reports Server (NTRS)

Lee, F.; Flynn, M.; Morf, M.

1991-01-01

The lattice gas method has recently emerged as a promising discrete particle simulation method in areas such as fluid dynamics. We present a very high-performance scalable multiprocessor architecture, called ALGE, proposed for the simulation of a realistic 3-D lattice gas model, Henon's 24-bit FCHC isometric model. Each of these VLSI processors is as powerful as a CRAY-2 for this application. ALGE is scalable in the sense that it achieves linear speedup for both fixed and increasing problem sizes with more processors. The core computation of a lattice gas model consists of many repetitions of two alternating phases: particle collision and propagation. Functional decomposition by symmetry group and virtual move are the respective keys to efficient implementation of collision and propagation.

Shock Simulations of Single-Site Coarse-Grain RDX using the Dissipative Particle Dynamics Method with Reactivity

NASA Astrophysics Data System (ADS)

Sellers, Michael; Lisal, Martin; Schweigert, Igor; Larentzos, James; Brennan, John

2015-06-01

In discrete particle simulations, when an atomistic model is coarse-grained, a trade-off is made: a boost in computational speed for a reduction in accuracy. Dissipative Particle Dynamics (DPD) methods help to recover accuracy in viscous and thermal properties, while giving back a small amount of computational speed. One of the most notable extensions of DPD has been the introduction of chemical reactivity, called DPD-RX. Today, pairing the current evolution of DPD-RX with a coarse-grained potential and its chemical decomposition reactions allows for the simulation of the shock behavior of energetic materials at a timescale faster than an atomistic counterpart. In 2007, Maillet et al. introduced implicit chemical reactivity in DPD through the concept of particle reactors and simulated the decomposition of liquid nitromethane. We have recently extended the DPD-RX method and have applied it to solid hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) under shock conditions using a recently developed single-site coarse-grain model and a reduced RDX decomposition mechanism. A description of the methods used to simulate RDX and its tranition to hot product gases within DPD-RX will be presented. Additionally, examples of the effect of microstructure on shock behavior will be shown. Approved for public release. Distribution is unlimited.

An extinction/reignition dynamic method for turbulent combustion

NASA Astrophysics Data System (ADS)

Knaus, Robert; Pantano, Carlos

2011-11-01

Quasi-randomly distributed locations of high strain in turbulent combustion can cause a nonpremixed or partially premixed flame to develop local regions of extinction called ``flame holes''. The presence and extent of these holes can increase certain pollutants and reduce the amount of fuel burned. Accurately modeling the dynamics of these interacting regions can improve the accuracy of combustion simulations by effectively incorporating finite-rate chemistry effects. In the proposed method, the flame hole state is characterized by a progress variable that nominally exists on the stoichiometric surface. The evolution of this field is governed by a partial-differential equation embedded in the time-dependent two-manifold of the flame surface. This equation includes advection, propagation, and flame hole formation (flame hole healing or collapse is accounted by propagation naturally). We present a computational algorithm that solves this equation by embedding it in the usual three-dimensional space. A piece-wise parabolic WENO scheme combined with a compression algorithm are used to evolve the flame hole progress variable. A key aspect of the method is the extension of the surface data to the three-dimensional space in an efficient manner. We present results of this method applied to canonical turbulent combusting flows where the flame holes interact and describe their statistics.

Theory of buttressed marine ice sheet dynamics and its application to the assessment of tipping-point conditions

NASA Astrophysics Data System (ADS)

Pegler, S.

2017-12-01

Understanding the fate of the West Antarctic Ice Sheet is constrained by difficulties of resolving the buttressing effect of ice shelves and its dynamic response to grounding-line migration. This effect may be responsible for protecting a large majority of outlet glaciers in Antarctica against surging into the ocean. I present a theoretical methodology for assessing the positions and stability of grounding lines that incorporates closed-form, dynamic descriptions of ice-shelf buttressing and extensional (stretching) viscous stresses. The method is applied to assess the conditions for grounding-line tipping points. Such points are shown to produce abrupt `cliff-edge' transitions to runaway retreat, representing the so-called marine ice sheet instability. Depending on the bed profile, melt and calving rates, a tipping point can either lie very near to a local maximum in the bed topography or potentially far upstream of it, along a reverse bed. The model predictions for both wide and narrow embayments are validated by numerical simulations and laboratory experiments. A case study of Pine Island Glacier indicates the possibility for long-term stabilisation, with the analytical method affording an extensive exploration of scenarios. The theory also elucidates a mode of grounding-line migration controlled entirely by the determinants of the ice-shelf buttressing force, with a loss of sensitivity to basal conditions, contrasting with the conclusion from one-dimensional theory that the ice shelf is irrelevant. The results provide an interpretive framework for understanding grounding-line dynamics, its coupling with ice-shelf dynamics, an efficient exploration of parameter variation, and a complement to large-scale simulation.

INTRODUCING CAFein, A NEW COMPUTATIONAL TOOL FOR STELLAR PULSATIONS AND DYNAMIC TIDES

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

Valsecchi, F.; Farr, W. M.; Willems, B.

2013-08-10

Here we present CAFein, a new computational tool for investigating radiative dissipation of dynamic tides in close binaries and of non-adiabatic, non-radial stellar oscillations in isolated stars in the linear regime. For the latter, CAFein computes the non-adiabatic eigenfrequencies and eigenfunctions of detailed stellar models. The code is based on the so-called Riccati method, a numerical algorithm that has been successfully applied to a variety of stellar pulsators, and which does not suffer from the major drawbacks of commonly used shooting and relaxation schemes. Here we present an extension of the Riccati method to investigate dynamic tides in close binaries.more » We demonstrate CAFein's capabilities as a stellar pulsation code both in the adiabatic and non-adiabatic regimes, by reproducing previously published eigenfrequencies of a polytrope, and by successfully identifying the unstable modes of a stellar model in the {beta} Cephei/SPB region of the Hertzsprung-Russell diagram. Finally, we verify CAFein's behavior in the dynamic tides regime by investigating the effects of dynamic tides on the eigenfunctions and orbital and spin evolution of massive main sequence stars in eccentric binaries, and of hot Jupiter host stars. The plethora of asteroseismic data provided by NASA's Kepler satellite, some of which include the direct detection of tidally excited stellar oscillations, make CAFein quite timely. Furthermore, the increasing number of observed short-period detached double white dwarfs (WDs) and the observed orbital decay in the tightest of such binaries open up a new possibility of investigating WD interiors through the effects of tides on their orbital evolution.« less

Quantifying time-of-flight-resolved optical field dynamics in turbid media with interferometric near-infrared spectroscopy (iNIRS) (Conference Presentation)

NASA Astrophysics Data System (ADS)

Borycki, Dawid; Kholiqov, Oybek; Zhou, Wenjun; Srinivasan, Vivek J.

2017-03-01

Sensing and imaging methods based on the dynamic scattering of coherent light, including laser speckle, laser Doppler, and diffuse correlation spectroscopy quantify scatterer motion using light intensity (speckle) fluctuations. The underlying optical field autocorrelation (OFA), rather than being measured directly, is typically inferred from the intensity autocorrelation (IA) through the Siegert relationship, by assuming that the scattered field obeys Gaussian statistics. In this work, we demonstrate interferometric near-infrared spectroscopy (iNIRS) for measurement of time-of-flight (TOF) resolved field and intensity autocorrelations in fluid tissue phantoms and in vivo. In phantoms, we find a breakdown of the Siegert relationship for short times-of-flight due to a contribution from static paths whose optical field does not decorrelate over experimental time scales, and demonstrate that eliminating such paths by polarization gating restores the validity of the Siegert relationship. Inspired by these results, we developed a method, called correlation gating, for separating the OFA into static and dynamic components. Correlation gating enables more precise quantification of tissue dynamics. To prove this, we show that iNIRS and correlation gating can be applied to measure cerebral hemodynamics of the nude mouse in vivo using dynamically scattered (ergodic) paths and not static (non-ergodic) paths, which may not be impacted by blood. More generally, correlation gating, in conjunction with TOF resolution, enables more precise separation of diffuse and non-diffusive contributions to OFA than is possible with TOF resolution alone. Finally, we show that direct measurements of OFA are statistically more efficient than indirect measurements based on IA.

Calls reveal population structure of blue whales across the southeast Indian Ocean and the southwest Pacific Ocean.

PubMed

Balcazar, Naysa E; Tripovich, Joy S; Klinck, Holger; Nieukirk, Sharon L; Mellinger, David K; Dziak, Robert P; Rogers, Tracey L

2015-11-24

For effective species management, understanding population structure and distribution is critical. However, quantifying population structure is not always straightforward. Within the Southern Hemisphere, the blue whale ( Balaenoptera musculus ) complex is extremely diverse but difficult to study. Using automated detector methods, we identified "acoustic populations" of whales producing region-specific call types. We examined blue whale call types in passive acoustic data at sites spanning over 7,370 km across the southeast Indian Ocean and southwest Pacific Ocean (SWPO) from 2009 to 2012. In the absence of genetic resolution, these acoustic populations offer unique information about the blue whale population complex. We found that the Australian continent acts as a geographic boundary, separating Australia and New Zealand blue whale acoustic populations at the junction of the Indian and Pacific Ocean basins. We located blue whales in previously undocumented locations, including the far SWPO, in the Tasman Sea off the east coast of Australia, and along the Lau Basin near Tonga. Our understanding of population dynamics across this broad scale has significant implications to recovery and conservation management for this endangered species, at a regional and global scale.

Geometrical analysis of the LiCN vibrational dynamics: a stability geometrical indicator.

PubMed

Vergel, A; Benito, R M; Losada, J C; Borondo, F

2014-02-01

The vibrational dynamics of the LiNC/LiCN molecular system is examined making use of the Riemannian geometry. Stability and chaoticity are analyzed, in this context, by means of the Jacobi-Levi-Civita equations, derived from the Jacobi metric, and its solutions. A dynamical indicator, called stability geometrical indicator, is introduced in order to ascertain the dynamical characteristics of stability and chaos in the molecule under study.

Multiobjective Resource-Constrained Project Scheduling with a Time-Varying Number of Tasks

PubMed Central

Abello, Manuel Blanco

2014-01-01

In resource-constrained project scheduling (RCPS) problems, ongoing tasks are restricted to utilizing a fixed number of resources. This paper investigates a dynamic version of the RCPS problem where the number of tasks varies in time. Our previous work investigated a technique called mapping of task IDs for centroid-based approach with random immigrants (McBAR) that was used to solve the dynamic problem. However, the solution-searching ability of McBAR was investigated over only a few instances of the dynamic problem. As a consequence, only a small number of characteristics of McBAR, under the dynamics of the RCPS problem, were found. Further, only a few techniques were compared to McBAR with respect to its solution-searching ability for solving the dynamic problem. In this paper, (a) the significance of the subalgorithms of McBAR is investigated by comparing McBAR to several other techniques; and (b) the scope of investigation in the previous work is extended. In particular, McBAR is compared to a technique called, Estimation Distribution Algorithm (EDA). As with McBAR, EDA is applied to solve the dynamic problem, an application that is unique in the literature. PMID:24883398

Hard versus soft dynamics for adsorption-desorption kinetics: Exact results in one-dimension.

PubMed

Manzi, S J; Huespe, V J; Belardinelli, R E; Pereyra, V D

2009-11-01

The adsorption-desorption kinetics is discussed in the framework of the kinetic lattice-gas model. The master equation formalism has been introduced to describe the evolution of the system, where the transition probabilities are written as an expansion of the occupation configurations of all neighboring sites. Since the detailed balance principle determines half of the coefficients that arise from the expansion, it is necessary to introduce ad hoc, a dynamic scheme to get the rest of them. Three schemes of the so-called hard dynamics, in which the probability of transition from single site cannot be factored into a part which depends only on the interaction energy and one that only depends on the field energy, and five schemes of the so-called soft dynamics, in which this factorization is possible, were introduced for this purpose. It is observed that for the hard dynamic schemes, the equilibrium and nonequilibrium observables, such as adsorption isotherms, sticking coefficients, and thermal desorption spectra, have a normal or physical sustainable behavior. While for the soft dynamics schemes, with the exception of the transition state theory, the equilibrium and nonequilibrium observables have several problems. Some of them can be regarded as abnormal behavior.

Permutation invariant polynomial neural network approach to fitting potential energy surfaces. II. Four-atom systems

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

Li, Jun; Jiang, Bin; Guo, Hua, E-mail: hguo@unm.edu

2013-11-28

A rigorous, general, and simple method to fit global and permutation invariant potential energy surfaces (PESs) using neural networks (NNs) is discussed. This so-called permutation invariant polynomial neural network (PIP-NN) method imposes permutation symmetry by using in its input a set of symmetry functions based on PIPs. For systems with more than three atoms, it is shown that the number of symmetry functions in the input vector needs to be larger than the number of internal coordinates in order to include both the primary and secondary invariant polynomials. This PIP-NN method is successfully demonstrated in three atom-triatomic reactive systems, resultingmore » in full-dimensional global PESs with average errors on the order of meV. These PESs are used in full-dimensional quantum dynamical calculations.« less

Application of Canonical Effective Methods to Background-Independent Theories

NASA Astrophysics Data System (ADS)

Buyukcam, Umut

Effective formalisms play an important role in analyzing phenomena above some given length scale when complete theories are not accessible. In diverse exotic but physically important cases, the usual path-integral techniques used in a standard Quantum Field Theory approach seldom serve as adequate tools. This thesis exposes a new effective method for quantum systems, called the Canonical Effective Method, which owns particularly wide applicability in backgroundindependent theories as in the case of gravitational phenomena. The central purpose of this work is to employ these techniques to obtain semi-classical dynamics from canonical quantum gravity theories. Application to non-associative quantum mechanics is developed and testable results are obtained. Types of non-associative algebras relevant for magnetic-monopole systems are discussed. Possible modifications of hypersurface deformation algebra and the emergence of effective space-times are presented. iii.

The NASA/Industry Design Analysis Methods for Vibrations (DAMVIBS) Program - A government overview. [of rotorcraft technology development using finite element method

NASA Technical Reports Server (NTRS)

Kvaternik, Raymond G.

1992-01-01

An overview is presented of government contributions to the program called Design Analysis Methods for Vibrations (DAMV) which attempted to develop finite-element-based analyses of rotorcraft vibrations. NASA initiated the program with a finite-element modeling program for the CH-47D tandem-rotor helicopter. The DAMV program emphasized four areas including: airframe finite-element modeling, difficult components studies, coupled rotor-airframe vibrations, and airframe structural optimization. Key accomplishments of the program include industrywide standards for modeling metal and composite airframes, improved industrial designs for vibrations, and the identification of critical structural contributors to airframe vibratory responses. The program also demonstrated the value of incorporating secondary modeling details to improving correlation, and the findings provide the basis for an improved finite-element-based dynamics design-analysis capability.

Robust and Cost-Efficient Communication Based on SNMP in Mobile Networks

NASA Astrophysics Data System (ADS)

Ryu, Sang-Hoon; Baik, Doo-Kwon

A main challenge in the design of this mobile network is the development of dynamic routing protocols that can efficiently find routes between two communicating nodes. Multimedia streaming services are receiving considerable interest in the mobile network business. An entire mobile network may change its point of attachment to the Internet. The mobile network is operated by a basic specification to support network mobility called Network Mobility (NEMO) Basic Support. However, NEMO basic Support mechanism has some problem in continuous communication. In this paper, we propose robust and cost-efficient algorithm. And we simulate proposed method and conclude some remarks.

PARS: a web server for the prediction of Protein Allosteric and Regulatory Sites.

PubMed

Panjkovich, Alejandro; Daura, Xavier

2014-05-01

The regulation of protein activity is a key aspect of life at the molecular level. Unveiling its details is thus crucial to understanding signalling and metabolic pathways. The most common and powerful mechanism of protein-function regulation is allostery, which has been increasingly calling the attention of medicinal chemists due to its potential for the discovery of novel therapeutics. In this context, PARS is a simple and fast method that queries protein dynamics and structural conservation to identify pockets on a protein structure that may exert a regulatory effect on the binding of a small-molecule ligand.

CONTIN XPCS: Software for Inverse Transform Analysis of X-Ray Photon Correlation Spectroscopy Dynamics

PubMed Central

Narayanan, Suresh; Zhang, Fan; Kuzmenko, Ivan; Ilavsky, Jan

2018-01-01

X-ray photon correlation spectroscopy (XPCS) and dynamic light scattering (DLS) both reveal dynamics using coherent scattering, but X-rays permit investigating of dynamics in a much more diverse array of materials. Heterogeneous dynamics occur in many such materials, and we showed how classic tools employed in analysis of heterogeneous DLS dynamics extend to XPCS, revealing additional information that conventional Kohlrausch exponential fitting obscures. This work presents the software implementation of inverse transform analysis of XPCS data called CONTIN XPCS, an extension of traditional CONTIN that accommodates dynamics encountered in equilibrium XPCS measurements. PMID:29875507

CONTIN XPCS: Software for Inverse Transform Analysis of X-Ray Photon Correlation Spectroscopy Dynamics.

PubMed

Andrews, Ross N; Narayanan, Suresh; Zhang, Fan; Kuzmenko, Ivan; Ilavsky, Jan

2018-02-01

X-ray photon correlation spectroscopy (XPCS) and dynamic light scattering (DLS) both reveal dynamics using coherent scattering, but X-rays permit investigating of dynamics in a much more diverse array of materials. Heterogeneous dynamics occur in many such materials, and we showed how classic tools employed in analysis of heterogeneous DLS dynamics extend to XPCS, revealing additional information that conventional Kohlrausch exponential fitting obscures. This work presents the software implementation of inverse transform analysis of XPCS data called CONTIN XPCS, an extension of traditional CONTIN that accommodates dynamics encountered in equilibrium XPCS measurements.

Solar Potential Analysis and Integration of the Time-Dependent Simulation Results for Semantic 3d City Models Using Dynamizers

NASA Astrophysics Data System (ADS)

Chaturvedi, K.; Willenborg, B.; Sindram, M.; Kolbe, T. H.

2017-10-01

Semantic 3D city models play an important role in solving complex real-world problems and are being adopted by many cities around the world. A wide range of application and simulation scenarios directly benefit from the adoption of international standards such as CityGML. However, most of the simulations involve properties, whose values vary with respect to time, and the current generation semantic 3D city models do not support time-dependent properties explicitly. In this paper, the details of solar potential simulations are provided operating on the CityGML standard, assessing and estimating solar energy production for the roofs and facades of the 3D building objects in different ways. Furthermore, the paper demonstrates how the time-dependent simulation results are better-represented inline within 3D city models utilizing the so-called Dynamizer concept. This concept not only allows representing the simulation results in standardized ways, but also delivers a method to enhance static city models by such dynamic property values making the city models truly dynamic. The dynamizer concept has been implemented as an Application Domain Extension of the CityGML standard within the OGC Future City Pilot Phase 1. The results are given in this paper.

Review of Modelling Techniques for In Vivo Muscle Force Estimation in the Lower Extremities during Strength Training.

PubMed

Schellenberg, Florian; Oberhofer, Katja; Taylor, William R; Lorenzetti, Silvio

2015-01-01

Knowledge of the musculoskeletal loading conditions during strength training is essential for performance monitoring, injury prevention, rehabilitation, and training design. However, measuring muscle forces during exercise performance as a primary determinant of training efficacy and safety has remained challenging. In this paper we review existing computational techniques to determine muscle forces in the lower limbs during strength exercises in vivo and discuss their potential for uptake into sports training and rehabilitation. Muscle forces during exercise performance have almost exclusively been analysed using so-called forward dynamics simulations, inverse dynamics techniques, or alternative methods. Musculoskeletal models based on forward dynamics analyses have led to considerable new insights into muscular coordination, strength, and power during dynamic ballistic movement activities, resulting in, for example, improved techniques for optimal performance of the squat jump, while quasi-static inverse dynamics optimisation and EMG-driven modelling have helped to provide an understanding of low-speed exercises. The present review introduces the different computational techniques and outlines their advantages and disadvantages for the informed usage by nonexperts. With sufficient validation and widespread application, muscle force calculations during strength exercises in vivo are expected to provide biomechanically based evidence for clinicians and therapists to evaluate and improve training guidelines.

Effect of Intercalated Water on Potassium Ion Transport through Kv1.2 Channels Studied via On-the-Fly Free-Energy Parametrization.

PubMed

Paz, S Alexis; Maragliano, Luca; Abrams, Cameron F

2018-05-08

We introduce a two-dimensional version of the method called on-the-fly free energy parametrization (OTFP) to reconstruct free-energy surfaces using Molecular Dynamics simulations, which we name OTFP-2D. We first test the new method by reconstructing the well-known dihedral angles free energy surface of solvated alanine dipeptide. Then, we use it to investigate the process of K + ions translocation inside the Kv1.2 channel. By comparing a series of two-dimensional free energy surfaces for ion movement calculated with different conditions on the intercalated water molecules, we first recapitulate the widely accepted knock-on mechanism for ion translocation and then confirm that permeation occurs with water molecules alternated among the ions, in accordance with the latest experimental findings. From a methodological standpoint, our new OTFP-2D algorithm demonstrates the excellent sampling acceleration of temperature-accelerated molecular dynamics and the ability to efficiently compute 2D free-energy surfaces. It will therefore be useful in large variety complex biomacromolecular simulations.

Zombie states for description of structure and dynamics of multi-electron systems

NASA Astrophysics Data System (ADS)

Shalashilin, Dmitrii V.

2018-05-01

Canonical Coherent States (CSs) of Harmonic Oscillator have been extensively used as a basis in a number of computational methods of quantum dynamics. However, generalising such techniques for fermionic systems is difficult because Fermionic Coherent States (FCSs) require complicated algebra of Grassmann numbers not well suited for numerical calculations. This paper introduces a coherent antisymmetrised superposition of "dead" and "alive" electronic states called here Zombie State (ZS), which can be used in a manner of FCSs but without Grassmann algebra. Instead, for Zombie States, a very simple sign-changing rule is used in the definition of creation and annihilation operators. Then, calculation of electronic structure Hamiltonian matrix elements between two ZSs becomes very simple and a straightforward technique for time propagation of fermionic wave functions can be developed. By analogy with the existing methods based on Canonical Coherent States of Harmonic Oscillator, fermionic wave functions can be propagated using a set of randomly selected Zombie States as a basis. As a proof of principles, the proposed Coupled Zombie States approach is tested on a simple example showing that the technique is exact.

Calculation of the X-Ray emission K and L 2,3 bands of metallic magnesium and aluminum with allowance for multielectron effects

NASA Astrophysics Data System (ADS)

Ovcharenko, R. E.; Tupitsyn, I. I.; Savinov, E. P.; Voloshina, E. N.; Dedkov, Yu. S.; Shulakov, A. S.

2014-01-01

A procedure is proposed to calculate the shape of the characteristic X-ray emission bands of metals with allowance for multielectron effects. The effects of the dynamic screening of a core vacancy by conduction electrons and the Auger effect in the valence band are taken into account. The dynamic screening of a core vacancy, which is known to be called the MND (Mahan-Nozeieres-De Dominics) effect, is taken into account by an ab initio band calculation of crystals using the PAW (projected augmented waves) method. The Auger effect is taken into account by a semiempirical method using the approximation of a quadratic dependence of the level width in the valence band on the difference between the level energy and the Fermi energy. The proposed calculation procedure is used to describe the X-ray emission K and L 2,3 bands of metallic magnesium and aluminum crystals. The calculated spectra agree well with the experimental bands both near the Fermi level and in the low-energy part of the spectra in all cases.

Experimental Verification of Sparse Aperture Mask for Low Order Wavefront Sensing

NASA Astrophysics Data System (ADS)

Subedi, Hari; Kasdin, N. Jeremy

2017-01-01

To directly image exoplanets, future space-based missions are equipped with coronagraphs which manipulate the diffraction of starlight and create regions of high contrast called dark holes. Theoretically, coronagraphs can be designed to achieve the high level of contrast required to image exoplanets, which are billions of times dimmer than their host stars, however the aberrations caused by optical imperfections and thermal fluctuations cause the degradation of contrast in the dark holes. Focal plane wavefront control (FPWC) algorithms using deformable mirrors (DMs) are used to mitigate the quasi-static aberrations caused by optical imperfections. Although the FPWC methods correct the quasi-static aberrations, they are blind to dynamic errors caused by telescope jitter and thermal fluctuations. At Princeton's High Contrast Imaging Lab we have developed a new technique that integrates a sparse aperture mask with the coronagraph to estimate these low-order dynamic wavefront errors. This poster shows the effectiveness of a SAM Low-Order Wavefront Sensor in estimating and correcting these errors via simulation and experiment and compares the results to other methods, such as the Zernike Wavefront Sensor planned for WFIRST.

Remotely measuring populations during a crisis by overlaying two data sources

PubMed Central

Bharti, Nita; Lu, Xin; Bengtsson, Linus; Wetter, Erik; Tatem, Andrew J.

2015-01-01

Background Societal instability and crises can cause rapid, large-scale movements. These movements are poorly understood and difficult to measure but strongly impact health. Data on these movements are important for planning response efforts. We retrospectively analyzed movement patterns surrounding a 2010 humanitarian crisis caused by internal political conflict in Côte d'Ivoire using two different methods. Methods We used two remote measures, nighttime lights satellite imagery and anonymized mobile phone call detail records, to assess average population sizes as well as dynamic population changes. These data sources detect movements across different spatial and temporal scales. Results The two data sources showed strong agreement in average measures of population sizes. Because the spatiotemporal resolution of the data sources differed, we were able to obtain measurements on long- and short-term dynamic elements of populations at different points throughout the crisis. Conclusions Using complementary, remote data sources to measure movement shows promise for future use in humanitarian crises. We conclude with challenges of remotely measuring movement and provide suggestions for future research and methodological developments. PMID:25733558

Object-Oriented Control System Design Using On-Line Training of Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Rubaai, Ahmed

1997-01-01

This report deals with the object-oriented model development of a neuro-controller design for permanent magnet (PM) dc motor drives. The system under study is described as a collection of interacting objects. Each object module describes the object behaviors, called methods. The characteristics of the object are included in its variables. The knowledge of the object exists within its variables, and the performance is determined by its methods. This structure maps well to the real world objects that comprise the system being modeled. A dynamic learning architecture that possesses the capabilities of simultaneous on-line identification and control is incorporated to enforce constraints on connections and control the dynamics of the motor. The control action is implemented "on-line", in "real time" in such a way that the predicted trajectory follows a specified reference model. A design example of controlling a PM dc motor drive on-line shows the effectiveness of the design tool. This will therefore be very useful in aerospace applications. It is expected to provide an innovative and noval software model for the rocket engine numerical simulator executive.

High-order computational fluid dynamics tools for aircraft design

PubMed Central

Wang, Z. J.

2014-01-01

Most forecasts predict an annual airline traffic growth rate between 4.5 and 5% in the foreseeable future. To sustain that growth, the environmental impact of aircraft cannot be ignored. Future aircraft must have much better fuel economy, dramatically less greenhouse gas emissions and noise, in addition to better performance. Many technical breakthroughs must take place to achieve the aggressive environmental goals set up by governments in North America and Europe. One of these breakthroughs will be physics-based, highly accurate and efficient computational fluid dynamics and aeroacoustics tools capable of predicting complex flows over the entire flight envelope and through an aircraft engine, and computing aircraft noise. Some of these flows are dominated by unsteady vortices of disparate scales, often highly turbulent, and they call for higher-order methods. As these tools will be integral components of a multi-disciplinary optimization environment, they must be efficient to impact design. Ultimately, the accuracy, efficiency, robustness, scalability and geometric flexibility will determine which methods will be adopted in the design process. This article explores these aspects and identifies pacing items. PMID:25024419

Beluga whale, Delphinapterus leucas, vocalizations from the Churchill River, Manitoba, Canada.

PubMed

Chmelnitsky, Elly G; Ferguson, Steven H

2012-06-01

Classification of animal vocalizations is often done by a human observer using aural and visual analysis but more efficient, automated methods have also been utilized to reduce bias and increase reproducibility. Beluga whale, Delphinapterus leucas, calls were described from recordings collected in the summers of 2006-2008, in the Churchill River, Manitoba. Calls (n=706) were classified based on aural and visual analysis, and call characteristics were measured; calls were separated into 453 whistles (64.2%; 22 types), 183 pulsed∕noisy calls (25.9%; 15 types), and 70 combined calls (9.9%; seven types). Measured parameters varied within each call type but less variation existed in pulsed and noisy call types and some combined call types than in whistles. A more efficient and repeatable hierarchical clustering method was applied to 200 randomly chosen whistles using six call characteristics as variables; twelve groups were identified. Call characteristics varied less in cluster analysis groups than in whistle types described by visual and aural analysis and results were similar to the whistle contours described. This study provided the first description of beluga calls in Hudson Bay and using two methods provides more robust interpretations and an assessment of appropriate methods for future studies.

Complex dynamics in the Leslie-Gower type of the food chain system with multiple delays

NASA Astrophysics Data System (ADS)

Guo, Lei; Song, Zi-Gen; Xu, Jian

2014-08-01

In this paper, we present a Leslie-Gower type of food chain system composed of three species, which are resource, consumer, and predator, respectively. The digestion time delays corresponding to consumer-eat-resource and predator-eat-consumer are introduced for more realistic consideration. It is called the resource digestion delay (RDD) and consumer digestion delay (CDD) for simplicity. Analyzing the corresponding characteristic equation, the stabilities of the boundary and interior equilibrium points are studied. The food chain system exhibits the species coexistence for the small values of digestion delays. Large RDD/CDD may destabilize the species coexistence and induce the system dynamic into recurrent bloom or system collapse. Further, the present of multiple delays can control species population into the stable coexistence. To investigate the effect of time delays on the recurrent bloom of species population, the Hopf bifurcation and periodic solution are investigated in detail in terms of the central manifold reduction and normal form method. Finally, numerical simulations are performed to display some complex dynamics, which include multiple periodic solution and chaos motion for the different values of system parameters. The system dynamic behavior evolves into the chaos motion by employing the period-doubling bifurcation.

A Comparison of Three Random Number Generators for Aircraft Dynamic Modeling Applications

NASA Technical Reports Server (NTRS)

Grauer, Jared A.

2017-01-01

Three random number generators, which produce Gaussian white noise sequences, were compared to assess their suitability in aircraft dynamic modeling applications. The first generator considered was the MATLAB (registered) implementation of the Mersenne-Twister algorithm. The second generator was a website called Random.org, which processes atmospheric noise measured using radios to create the random numbers. The third generator was based on synthesis of the Fourier series, where the random number sequences are constructed from prescribed amplitude and phase spectra. A total of 200 sequences, each having 601 random numbers, for each generator were collected and analyzed in terms of the mean, variance, normality, autocorrelation, and power spectral density. These sequences were then applied to two problems in aircraft dynamic modeling, namely estimating stability and control derivatives from simulated onboard sensor data, and simulating flight in atmospheric turbulence. In general, each random number generator had good performance and is well-suited for aircraft dynamic modeling applications. Specific strengths and weaknesses of each generator are discussed. For Monte Carlo simulation, the Fourier synthesis method is recommended because it most accurately and consistently approximated Gaussian white noise and can be implemented with reasonable computational effort.

Development of a Probabilistic Dynamic Synthesis Method for the Analysis of Nondeterministic Structures

NASA Technical Reports Server (NTRS)

Brown, A. M.

1998-01-01

Accounting for the statistical geometric and material variability of structures in analysis has been a topic of considerable research for the last 30 years. The determination of quantifiable measures of statistical probability of a desired response variable, such as natural frequency, maximum displacement, or stress, to replace experience-based "safety factors" has been a primary goal of these studies. There are, however, several problems associated with their satisfactory application to realistic structures, such as bladed disks in turbomachinery. These include the accurate definition of the input random variables (rv's), the large size of the finite element models frequently used to simulate these structures, which makes even a single deterministic analysis expensive, and accurate generation of the cumulative distribution function (CDF) necessary to obtain the probability of the desired response variables. The research presented here applies a methodology called probabilistic dynamic synthesis (PDS) to solve these problems. The PDS method uses dynamic characteristics of substructures measured from modal test as the input rv's, rather than "primitive" rv's such as material or geometric uncertainties. These dynamic characteristics, which are the free-free eigenvalues, eigenvectors, and residual flexibility (RF), are readily measured and for many substructures, a reasonable sample set of these measurements can be obtained. The statistics for these rv's accurately account for the entire random character of the substructure. Using the RF method of component mode synthesis, these dynamic characteristics are used to generate reduced-size sample models of the substructures, which are then coupled to form system models. These sample models are used to obtain the CDF of the response variable by either applying Monte Carlo simulation or by generating data points for use in the response surface reliability method, which can perform the probabilistic analysis with an order of magnitude less computational effort. Both free- and forced-response analyses have been performed, and the results indicate that, while there is considerable room for improvement, the method produces usable and more representative solutions for the design of realistic structures with a substantial savings in computer time.

SVAS3: Strain Vector Aided Sensorization of Soft Structures

PubMed Central

Culha, Utku; Nurzaman, Surya G.; Clemens, Frank; Iida, Fumiya

2014-01-01

Soft material structures exhibit high deformability and conformability which can be useful for many engineering applications such as robots adapting to unstructured and dynamic environments. However, the fact that they have almost infinite degrees of freedom challenges conventional sensory systems and sensorization approaches due to the difficulties in adapting to soft structure deformations. In this paper, we address this challenge by proposing a novel method which designs flexible sensor morphologies to sense soft material deformations by using a functional material called conductive thermoplastic elastomer (CTPE). This model-based design method, called Strain Vector Aided Sensorization of Soft Structures (SVAS3), provides a simulation platform which analyzes soft body deformations and automatically finds suitable locations for CTPE-based strain gauge sensors to gather strain information which best characterizes the deformation. Our chosen sensor material CTPE exhibits a set of unique behaviors in terms of strain length electrical conductivity, elasticity, and shape adaptability, allowing us to flexibly design sensor morphology that can best capture strain distributions in a given soft structure. We evaluate the performance of our approach by both simulated and real-world experiments and discuss the potential and limitations. PMID:25036332

The accuracy of ab initio calculations without ab initio calculations for charged systems: Kriging predictions of atomistic properties for ions in aqueous solutions

NASA Astrophysics Data System (ADS)

Di Pasquale, Nicodemo; Davie, Stuart J.; Popelier, Paul L. A.

2018-06-01

Using the machine learning method kriging, we predict the energies of atoms in ion-water clusters, consisting of either Cl- or Na+ surrounded by a number of water molecules (i.e., without Na+Cl- interaction). These atomic energies are calculated following the topological energy partitioning method called Interacting Quantum Atoms (IQAs). Kriging predicts atomic properties (in this case IQA energies) by a model that has been trained over a small set of geometries with known property values. The results presented here are part of the development of an advanced type of force field, called FFLUX, which offers quantum mechanical information to molecular dynamics simulations without the limiting computational cost of ab initio calculations. The results reported for the prediction of the IQA components of the energy in the test set exhibit an accuracy of a few kJ/mol, corresponding to an average error of less than 5%, even when a large cluster of water molecules surrounding an ion is considered. Ions represent an important chemical system and this work shows that they can be correctly taken into account in the framework of the FFLUX force field.

A framework for the assessment of the spatial and temporal patterns of threatened coastal delphinids

NASA Astrophysics Data System (ADS)

Wang, Jingzhen; Yang, Yingting; Yang, Feng; Li, Yuelin; Li, Lianjie; Lin, Derun; He, Tangtian; Liang, Bo; Zhang, Tao; Lin, Yao; Li, Ping; Liu, Wenhua

2016-01-01

The massively accelerated biodiversity loss rate in the Anthropocene calls for an efficient and effective way to identify the spatial and temporal dynamics of endangered species. To this end, we developed a useful identification framework based on a case study of locally endangered Sousa chinensis by combining both LEK (local ecological knowledge) evaluation and regional boat-based survey methods. Our study investigated the basic ecological information of Sousa chinensis in the estuaries of eastern Guangdong that had previously been neglected, which could guide the future study and conservation. Based on the statistical testing of reported spatial and temporal dolphins sighting data from fishermen and the ecological monitoring analyses, including sighting rate, site fidelity and residence time estimations, some of the current Sousa chinensis units are likely to be geographically isolated and critically endangered, which calls for much greater conservation efforts. Given the accelerated population extinction rate and increasing budgetary constraints, our survey pattern can be applied in a timely and economically acceptable manner to the spatial and temporal assessment of other threatened coastal delphinids, particularly when population distributions are on a large scale and traditional sampling methods are difficult to implement.

A framework for the assessment of the spatial and temporal patterns of threatened coastal delphinids.

PubMed

Wang, Jingzhen; Yang, Yingting; Yang, Feng; Li, Yuelin; Li, Lianjie; Lin, Derun; He, Tangtian; Liang, Bo; Zhang, Tao; Lin, Yao; Li, Ping; Liu, Wenhua

2016-01-25

The massively accelerated biodiversity loss rate in the Anthropocene calls for an efficient and effective way to identify the spatial and temporal dynamics of endangered species. To this end, we developed a useful identification framework based on a case study of locally endangered Sousa chinensis by combining both LEK (local ecological knowledge) evaluation and regional boat-based survey methods. Our study investigated the basic ecological information of Sousa chinensis in the estuaries of eastern Guangdong that had previously been neglected, which could guide the future study and conservation. Based on the statistical testing of reported spatial and temporal dolphins sighting data from fishermen and the ecological monitoring analyses, including sighting rate, site fidelity and residence time estimations, some of the current Sousa chinensis units are likely to be geographically isolated and critically endangered, which calls for much greater conservation efforts. Given the accelerated population extinction rate and increasing budgetary constraints, our survey pattern can be applied in a timely and economically acceptable manner to the spatial and temporal assessment of other threatened coastal delphinids, particularly when population distributions are on a large scale and traditional sampling methods are difficult to implement.

Development of Quadratic Programming Algorithm Based on Interior Point Method with Estimation Mechanism of Active Constraints

NASA Astrophysics Data System (ADS)

Hashimoto, Hiroyuki; Takaguchi, Yusuke; Nakamura, Shizuka

Instability of calculation process and increase of calculation time caused by increasing size of continuous optimization problem remain the major issues to be solved to apply the technique to practical industrial systems. This paper proposes an enhanced quadratic programming algorithm based on interior point method mainly for improvement of calculation stability. The proposed method has dynamic estimation mechanism of active constraints on variables, which fixes the variables getting closer to the upper/lower limit on them and afterwards releases the fixed ones as needed during the optimization process. It is considered as algorithm-level integration of the solution strategy of active-set method into the interior point method framework. We describe some numerical results on commonly-used bench-mark problems called “CUTEr” to show the effectiveness of the proposed method. Furthermore, the test results on large-sized ELD problem (Economic Load Dispatching problems in electric power supply scheduling) are also described as a practical industrial application.

WEAKLY SYNCHRYRONIZED SUBPOPULATION DYNAMICS IN WISCONSIN FROGS AND TOADS

EPA Science Inventory

Spatial synchrony in population dynamics is a topic of increasing interest in basic and applied ecology. We used data from 18 years of frog and toad calling surveys conducted throughout Wisconsin to determine the level of intraspecific synchrony among survey sites, and the relat...

Correlations induced by depressing synapses in critically self-organized networks with quenched dynamics

NASA Astrophysics Data System (ADS)

Campos, João Guilherme Ferreira; Costa, Ariadne de Andrade; Copelli, Mauro; Kinouchi, Osame

2017-04-01

In a recent work, mean-field analysis and computer simulations were employed to analyze critical self-organization in networks of excitable cellular automata where randomly chosen synapses in the network were depressed after each spike (the so-called annealed dynamics). Calculations agree with simulations of the annealed version, showing that the nominal branching ratio σ converges to unity in the thermodynamic limit, as expected of a self-organized critical system. However, the question remains whether the same results apply to the biological case where only the synapses of firing neurons are depressed (the so-called quenched dynamics). We show that simulations of the quenched model yield significant deviations from σ =1 due to spatial correlations. However, the model is shown to be critical, as the largest eigenvalue of the synaptic matrix approaches unity in the thermodynamic limit, that is, λc=1 . We also study the finite size effects near the critical state as a function of the parameters of the synaptic dynamics.

X-38 Experimental Controls Laws

NASA Technical Reports Server (NTRS)

Munday, Steve; Estes, Jay; Bordano, Aldo J.

2000-01-01

X-38 Experimental Control Laws X-38 is a NASA JSC/DFRC experimental flight test program developing a series of prototypes for an International Space Station (ISS) Crew Return Vehicle, often called an ISS "lifeboat." X- 38 Vehicle 132 Free Flight 3, currently scheduled for the end of this month, will be the first flight test of a modem FCS architecture called Multi-Application Control-Honeywell (MACH), originally developed by the Honeywell Technology Center. MACH wraps classical P&I outer attitude loops around a modem dynamic inversion attitude rate loop. The dynamic inversion process requires that the flight computer have an onboard aircraft model of expected vehicle dynamics based upon the aerodynamic database. Dynamic inversion is computationally intensive, so some timing modifications were made to implement MACH on the slower flight computers of the subsonic test vehicles. In addition to linear stability margin analyses and high fidelity 6-DOF simulation, hardware-in-the-loop testing is used to verify the implementation of MACH and its robustness to aerodynamic and environmental uncertainties and disturbances.

Dynamics and thermodynamics of open chemical networks

NASA Astrophysics Data System (ADS)

Esposito, Massimiliano

Open chemical networks (OCN) are large sets of coupled chemical reactions where some of the species are chemostated (i.e. continuously restored from the environment). Cell metabolism is a notable example of OCN. Two results will be presented. First, dissipation in OCN operating in nonequilibrium steady-states strongly depends on the network topology (algebraic properties of the stoichiometric matrix). An application to oligosaccharides exchange dynamics performed by so-called D-enzymes will be provided. Second, at low concentration the dissipation of OCN is in general inaccurately predicted by deterministic dynamics (i.e. nonlinear rate equations for the species concentrations). In this case a description in terms of the chemical master equation is necessary. A notable exception is provided by so-called deficiency zero networks, i.e. chemical networks with no hidden cycles present in the graph of reactant complexes.

The Role of Electronic Excitations on Chemical Reaction Dynamics at Metal, Semiconductor and Nanoparticle Surfaces

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

Tully, John C.

Chemical reactions are often facilitated and steered when carried out on solid surfaces, essential for applications such as heterogeneous catalysis, solar energy conversion, corrosion, materials processing, and many others. A critical factor that can determine the rates and pathways of chemical reactions at surfaces is the efficiency and specificity of energy transfer; how fast does energy move around and where does it go? For reactions on insulator surfaces energy transfer generally moves in and out of vibrations of the adsorbed molecule and the underlying substrate. By contrast, on metal surfaces, metallic nanoparticles and semiconductors, another pathway for energy flow opensmore » up, excitation and de-excitation of electrons. This so-called “nonadiabatic” mechanism often dominates the transfer of energy and can directly impact the course of a chemical reaction. Conventional computational methods such as molecular dynamics simulation do not account for this nonadiabatic behavior. The current DOE-BES funded project has focused on developing the underlying theoretical foundation and the computational methodology for the prediction of nonadiabatic chemical reaction dynamics at surfaces. The research has successfully opened up new methodology and new applications for molecular simulation. In particular, over the last three years, the “Electronic Friction” theory, pioneered by the PI, has now been developed into a stable and accurate computational method that is sufficiently practical to allow first principles “on-the-fly” simulation of chemical reaction dynamics at metal surfaces.« less

Individuality and stability in male songs of cao vit gibbons (Nomascus nasutus) with potential to monitor population dynamics.

PubMed

Feng, Jun-Juan; Cui, Liang-Wei; Ma, Chang-Yong; Fei, Han-Lan; Fan, Peng-Fei

2014-01-01

Vocal individuality and stability has been used to conduct population surveys, monitor population dynamics, and detect dispersal patterns in avian studies. To our knowledge, it has never been used in these kinds of studies among primates. The cao vit gibbon is a critically endangered species with only one small population living in a karst forest along China-Vietnam border. Due to the difficult karst terrain, an international border, long life history, and similarity in male morphology, detailed monitoring of population dynamics and dispersal patterns are not possible using traditional observation methods. In this paper, we test individuality and stability in male songs of cao vit gibbons. We then discuss the possibility of using vocal individuality for population surveys and monitoring population dynamics and dispersal patterns. Significant individuality of vocalization was detected in all 9 males, and the correct rate of individual identification yielded by discriminant function analysis using a subset of variables was satisfactory (>90%). Vocal stability over 2-6 years was also documented in 4 males. Several characters of cao vit gibbons allowed long-term population monitoring using vocal recordings in both China and Vietnam: 1) regular loud calls, 2) strong individuality and stability in male songs, 3) stable territories, and 4) long male tenure. During the course of this research, we also observed one male replacement (confirmed by vocal analysis). This time- and labor-saving method might be the most effective way to detect dispersal patterns in this transboundary population.

A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data From Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects.

PubMed

Doborjeh, Maryam Gholami; Wang, Grace Y; Kasabov, Nikola K; Kydd, Robert; Russell, Bruce

2016-09-01

This paper introduces a method utilizing spiking neural networks (SNN) for learning, classification, and comparative analysis of brain data. As a case study, the method was applied to electroencephalography (EEG) data collected during a GO/NOGO cognitive task performed by untreated opiate addicts, those undergoing methadone maintenance treatment (MMT) for opiate dependence and a healthy control group. the method is based on an SNN architecture called NeuCube, trained on spatiotemporal EEG data. NeuCube was used to classify EEG data across subject groups and across GO versus NOGO trials, but also facilitated a deeper comparative analysis of the dynamic brain processes. This analysis results in a better understanding of human brain functioning across subject groups when performing a cognitive task. In terms of the EEG data classification, a NeuCube model obtained better results (the maximum obtained accuracy: 90.91%) when compared with traditional statistical and artificial intelligence methods (the maximum obtained accuracy: 50.55%). more importantly, new information about the effects of MMT on cognitive brain functions is revealed through the analysis of the SNN model connectivity and its dynamics. this paper presented a new method for EEG data modeling and revealed new knowledge on brain functions associated with mental activity which is different from the brain activity observed in a resting state of the same subjects.

Generalized-active-space pair-density functional theory: an efficient method to study large, strongly correlated, conjugated systems

DOE PAGES

Ghosh, Soumen; Cramer, Christopher J.; Truhlar, Donald G.; ...

2017-01-19

Predicting ground- and excited-state properties of open-shell organic molecules by electronic structure theory can be challenging because an accurate treatment has to correctly describe both static and dynamic electron correlation. Strongly correlated systems, i.e., systems with near-degeneracy correlation effects, are particularly troublesome. Multiconfigurational wave function methods based on an active space are adequate in principle, but it is impractical to capture most of the dynamic correlation in these methods for systems characterized by many active electrons. Here, we recently developed a new method called multiconfiguration pair-density functional theory (MC-PDFT), that combines the advantages of wave function theory and density functionalmore » theory to provide a more practical treatment of strongly correlated systems. Here we present calculations of the singlet–triplet gaps in oligoacenes ranging from naphthalene to dodecacene. Calculations were performed for unprecedently large orbitally optimized active spaces of 50 electrons in 50 orbitals, and we test a range of active spaces and active space partitions, including four kinds of frontier orbital partitions. We show that MC-PDFT can predict the singlet–triplet splittings for oligoacenes consistent with the best available and much more expensive methods, and indeed MC-PDFT may constitute the benchmark against which those other models should be compared, given the absence of experimental data.« less

Generalized-active-space pair-density functional theory: an efficient method to study large, strongly correlated, conjugated systems

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

Ghosh, Soumen; Cramer, Christopher J.; Truhlar, Donald G.

Predicting ground- and excited-state properties of open-shell organic molecules by electronic structure theory can be challenging because an accurate treatment has to correctly describe both static and dynamic electron correlation. Strongly correlated systems, i.e., systems with near-degeneracy correlation effects, are particularly troublesome. Multiconfigurational wave function methods based on an active space are adequate in principle, but it is impractical to capture most of the dynamic correlation in these methods for systems characterized by many active electrons. Here, we recently developed a new method called multiconfiguration pair-density functional theory (MC-PDFT), that combines the advantages of wave function theory and density functionalmore » theory to provide a more practical treatment of strongly correlated systems. Here we present calculations of the singlet–triplet gaps in oligoacenes ranging from naphthalene to dodecacene. Calculations were performed for unprecedently large orbitally optimized active spaces of 50 electrons in 50 orbitals, and we test a range of active spaces and active space partitions, including four kinds of frontier orbital partitions. We show that MC-PDFT can predict the singlet–triplet splittings for oligoacenes consistent with the best available and much more expensive methods, and indeed MC-PDFT may constitute the benchmark against which those other models should be compared, given the absence of experimental data.« less

Gradient-based multiconfiguration Shepard interpolation for generating potential energy surfaces for polyatomic reactions.

PubMed

Tishchenko, Oksana; Truhlar, Donald G

2010-02-28

This paper describes and illustrates a way to construct multidimensional representations of reactive potential energy surfaces (PESs) by a multiconfiguration Shepard interpolation (MCSI) method based only on gradient information, that is, without using any Hessian information from electronic structure calculations. MCSI, which is called multiconfiguration molecular mechanics (MCMM) in previous articles, is a semiautomated method designed for constructing full-dimensional PESs for subsequent dynamics calculations (classical trajectories, full quantum dynamics, or variational transition state theory with multidimensional tunneling). The MCSI method is based on Shepard interpolation of Taylor series expansions of the coupling term of a 2 x 2 electronically diabatic Hamiltonian matrix with the diagonal elements representing nonreactive analytical PESs for reactants and products. In contrast to the previously developed method, these expansions are truncated in the present version at the first order, and, therefore, no input of electronic structure Hessians is required. The accuracy of the interpolated energies is evaluated for two test reactions, namely, the reaction OH+H(2)-->H(2)O+H and the hydrogen atom abstraction from a model of alpha-tocopherol by methyl radical. The latter reaction involves 38 atoms and a 108-dimensional PES. The mean unsigned errors averaged over a wide range of representative nuclear configurations (corresponding to an energy range of 19.5 kcal/mol in the former case and 32 kcal/mol in the latter) are found to be within 1 kcal/mol for both reactions, based on 13 gradients in one case and 11 in the other. The gradient-based MCMM method can be applied for efficient representations of multidimensional PESs in cases where analytical electronic structure Hessians are too expensive or unavailable, and it provides new opportunities to employ high-level electronic structure calculations for dynamics at an affordable cost.

Multilevel relaxation phenomena and population trapping. Final report, July 1, 1984--June 30, 1991

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

Hioe, F.T.

1991-11-01

This final report summarizes the main results of our work supported by DOE since 1982. A list of 45 publications supported by this DOE Grant is attached at the end of this report. The use and exploitation of the SU(N) dynamic symmetry to the study of the dynamics of laser-atom interaction was the starting point of our research work under this DOE Grant, and is our most original contribution to the field of quantum electrodynamics. Many results of general and special interests have been derived and developed from this starting point and the following is a summary of them: (1)more » We have introduced a set of simple relations based on the principle of unitary invariance which has proved to be useful for the study of the dynamics of a quantum system involving coupling. (2) We have found various specific conditions under which (a) we may have trapped population, or (b) we may send laser pulses through a multilevel atomic medium without attenuation. (3) We have found a remarkably efficient method for optimal state selective multiphoton population transfer, that employs two or more spatially overlapping lasers arranged in an unconventional sequence which we called ``counterintuitive``. A recent suggestion by Profs. P. Marte, P. Zoller and J.L. Hall to use this counterintuitive method for atomic beam deflections promises to make this remarkably effective procedure to become an important method in atomic interferometry.« less

Economic Model Predictive Control of Bihormonal Artificial Pancreas System Based on Switching Control and Dynamic R-parameter.

PubMed

Tang, Fengna; Wang, Youqing

2017-11-01

Blood glucose (BG) regulation is a long-term task for people with diabetes. In recent years, more and more researchers have attempted to achieve automated regulation of BG using automatic control algorithms, called the artificial pancreas (AP) system. In clinical practice, it is equally important to guarantee the treatment effect and reduce the treatment costs. The main motivation of this study is to reduce the cure burden. The dynamic R-parameter economic model predictive control (R-EMPC) is chosen to regulate the delivery rates of exogenous hormones (insulin and glucagon). It uses particle swarm optimization (PSO) to optimize the economic cost function and the switching logic between insulin delivery and glucagon delivery is designed based on switching control theory. The proposed method is first tested on the standard subject; the result is compared with the switching PID and the switching MPC. The effect of the dynamic R-parameter on improving the control performance is illustrated by comparing the results of the EMPC and the R-EMPC. Finally, the robustness tests on meal change (size and timing), hormone sensitivity (insulin and glucagon), and subject variability are performed. All results show that the proposed method can improve the control performance and reduce the economic costs. The simulation results verify the effectiveness of the proposed algorithm on improving the tracking performance, enhancing robustness, and reducing economic costs. The method proposed in this study owns great worth in practical application.

Identifying self-interstitials of bcc and fcc crystals in molecular dynamics

NASA Astrophysics Data System (ADS)

Bukkuru, S.; Bhardwaj, U.; Warrier, M.; Rao, A. D. P.; Valsakumar, M. C.

2017-02-01

Identification of self-interstitials in molecular dynamics (MD) simulations is of critical importance. There exist several criteria for identifying the self-interstitial. Most of the existing methods use an assumed cut-off value for the displacement of an atom from its lattice position to identify the self-interstitial. The results obtained are affected by the chosen cut-off value. Moreover, these chosen cut-off values are independent of temperature. We have developed a novel unsupervised learning algorithm called Max-Space Clustering (MSC) to identify an appropriate cut-off value and its dependence on temperature. This method is compared with some widely used methods such as effective sphere (ES) method and nearest neighbor sphere (NNS) method. The cut-off radius obtained using our method shows a linear variation with temperature. The value of cut-off radius and its temperature dependence is derived for five bcc (Cr, Fe, Mo, Nb, W) and six fcc (Ag, Au, Cu, Ni, Pd, Pt) crystals. It is seen that the ratio of the cut-off values "r" to the lattice constant "a" lies between 0.23 and 0.3 at 300 K and this ratio is on an average smaller for the fcc crystals. Collision cascade simulations are carried out for Primary knock-on Atom (PKA) energies of 5 keV in Fe (at 300 K and 1000 K) and W (at 300 K and 2500 K) and the results are compared using the various methods.

EC86-33385-04

NASA Image and Video Library

1986-03-27

This photograph shows a modified General Dynamics AFTI/F-111A Aardvark with supercritical mission adaptive wings (MAW) installed. The AFTI/F111A is seen banking towards Rodgers Dry Lake and Edwards Air Force Base. With the phasing out of the TACT program came a renewed effort by the Air Force Flight Dynamics Laboratory to extend supercritical wing technology to a higher level of performance. In the early 1980s the supercritical wing on the F-111A aircraft was replaced with a wing built by Boeing Aircraft Company System called a “mission adaptive wing” (MAW), and a joint NASA and Air Force program called Advanced Fighter Technology Integration (AFTI) was born.

Unstructured Adaptive Grid Computations on an Array of SMPs

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Pramanick, Ira; Sohn, Andrew; Simon, Horst D.

1996-01-01

Dynamic load balancing is necessary for parallel adaptive methods to solve unsteady CFD problems on unstructured grids. We have presented such a dynamic load balancing framework called JOVE, in this paper. Results on a four-POWERnode POWER CHALLENGEarray demonstrated that load balancing gives significant performance improvements over no load balancing for such adaptive computations. The parallel speedup of JOVE, implemented using MPI on the POWER CHALLENCEarray, was significant, being as high as 31 for 32 processors. An implementation of JOVE that exploits 'an array of SMPS' architecture was also studied; this hybrid JOVE outperformed flat JOVE by up to 28% on the meshes and adaption models tested. With large, realistic meshes and actual flow-solver and adaption phases incorporated into JOVE, hybrid JOVE can be expected to yield significant advantage over flat JOVE, especially as the number of processors is increased, thus demonstrating the scalability of an array of SMPs architecture.

Chaotic vortex filaments in a Bose–Einstein condensate and in superfluid helium

NASA Astrophysics Data System (ADS)

Nemirovskii, S. K.

2018-05-01

A statement of the quantum turbulence problem in both a Bose–Einstein condensate (BEC) and superfluid helium is formulated. In superfluid helium use is made of a so-called vortex filament method, in which quantum vortices are represented by stringlike objects, i.e. vortex lines. The dynamics of the vortex lines is determined by deterministic equations of motion, supplemented by random reconnections. Unlike He II, the laws of the dynamics of quantum vortices in BEC are based on the nonlinear Schrödinger equation. This makes it possible to obtain a microscopic description of the collision of vortices, the structure of a vortex filament, etc. A comparative analysis of these complementary approaches is carried out. It is shown that there are some features that do not automatically transfer the results obtained for BEC to vortices in He II and vice versa.

Reversible Vector Ratchet Effect in Skyrmion Systems

NASA Astrophysics Data System (ADS)

Ma, Xiaoyu; Reichhardt, Charles; Reichhardt, Cynthia

Magnetic skyrmions are topological non-trivial spin textures found in several magnetic materials. Since their motion can be controlled using ultralow current densities, skyrmions are appealing for potential applications in spintronics as information carriers and processing devices. In this work, we studied the collective transport properties of driven skyrmions based on a particle-like model with molecular dynamics (MD) simulation. Our results show that ac driven skyrmions interacting with an asymmetric substrate provide a realization of a new class of ratchet system, which we call a vector ratchet, that arises due to the effect of the Magnus term on the skyrmion dynamics. In a vector ratchet, the dc motion induced by the ac drive can be described as a vector that can be rotated up to 360 degrees relative to the substrate asymmetry direction. This could represent a new method for controlling skyrmion motion for spintronic applications.

Open Systems with Error Bounds: Spin-Boson Model with Spectral Density Variations.

PubMed

Mascherpa, F; Smirne, A; Huelga, S F; Plenio, M B

2017-03-10

In the study of open quantum systems, one of the most common ways to describe environmental effects on the reduced dynamics is through the spectral density. However, in many models this object cannot be computed from first principles and needs to be inferred on phenomenological grounds or fitted to experimental data. Consequently, some uncertainty regarding its form and parameters is unavoidable; this in turn calls into question the accuracy of any theoretical predictions based on a given spectral density. Here, we focus on the spin-boson model as a prototypical open quantum system, find two error bounds on predicted expectation values in terms of the spectral density variation considered, and state a sufficient condition for the strongest one to apply. We further demonstrate an application of our result, by bounding the error brought about by the approximations involved in the hierarchical equations of motion resolution method for spin-boson dynamics.

MVL spatiotemporal analysis for model intercomparison in EPS: application to the DEMETER multi-model ensemble

NASA Astrophysics Data System (ADS)

Fernández, J.; Primo, C.; Cofiño, A. S.; Gutiérrez, J. M.; Rodríguez, M. A.

2009-08-01

In a recent paper, Gutiérrez et al. (Nonlinear Process Geophys 15(1):109-114, 2008) introduced a new characterization of spatiotemporal error growth—the so called mean-variance logarithmic (MVL) diagram—and applied it to study ensemble prediction systems (EPS); in particular, they analyzed single-model ensembles obtained by perturbing the initial conditions. In the present work, the MVL diagram is applied to multi-model ensembles analyzing also the effect of model formulation differences. To this aim, the MVL diagram is systematically applied to the multi-model ensemble produced in the EU-funded DEMETER project. It is shown that the shared building blocks (atmospheric and ocean components) impose similar dynamics among different models and, thus, contribute to poorly sampling the model formulation uncertainty. This dynamical similarity should be taken into account, at least as a pre-screening process, before applying any objective weighting method.

Space Satellite Dynamics with Applications to Sunlight Pressure Attitude Control. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Stuck, B. W.

1972-01-01

A research program into three aspects of space satellite dynamics was carried out. First, a four-dimensional space-time formulation of Newtonian mechanics is developed. This theory allows a new physical interpretation of the conservation theorems of mechanics first derived rigorously by Noether. Second, a new concept for estimating the three angles which specify the orientation in space of a rigid body is presented. Two separate methods for implementing this concept are discussed, one based on direction cosines, the other on quaternions. Two examples are discussed: constant orientation in space, and constant rate of change of the three angles with time. Third, two synchronous equatorial orbit communication satellite designs which use sunlight pressure to control their attitude are analyzed. Each design is equipped with large reflecting surfaces, called solar sails, which can be canted in different directions to generate torques to correct pointing errors.

TQ-bifurcations in discrete dynamical systems: Analysis of qualitative rearrangements of the oscillation mode

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

Makarenko, A. V., E-mail: avm.science@mail.ru

A new class of bifurcations is defined in discrete dynamical systems, and methods for their diagnostics and the analysis of their properties are presented. The TQ-bifurcations considered are implemented in discrete mappings and are related to the qualitative rearrangement of the shape of trajectories in an extended space of states. Within the demonstration of the main capabilities of the toolkit, an analysis is carried out of a logistic mapping in a domain to the right of the period-doubling limit point. Five critical values of the parameter are found for which the geometric structure of the trajectories of the mapping experiencesmore » a qualitative rearrangement. In addition, an analysis is carried out of the so-called “trace map,” which arises in the problems of quantum-mechanical description of various properties of discrete crystalline and quasicrystalline lattices.« less

Don't Fear Optimality: Sampling for Probabilistic-Logic Sequence Models

NASA Astrophysics Data System (ADS)

Thon, Ingo

One of the current challenges in artificial intelligence is modeling dynamic environments that change due to the actions or activities undertaken by people or agents. The task of inferring hidden states, e.g. the activities or intentions of people, based on observations is called filtering. Standard probabilistic models such as Dynamic Bayesian Networks are able to solve this task efficiently using approximative methods such as particle filters. However, these models do not support logical or relational representations. The key contribution of this paper is the upgrade of a particle filter algorithm for use with a probabilistic logical representation through the definition of a proposal distribution. The performance of the algorithm depends largely on how well this distribution fits the target distribution. We adopt the idea of logical compilation into Binary Decision Diagrams for sampling. This allows us to use the optimal proposal distribution which is normally prohibitively slow.

Uncertainty Quantification in Aeroelasticity

NASA Astrophysics Data System (ADS)

Beran, Philip; Stanford, Bret; Schrock, Christopher

2017-01-01

Physical interactions between a fluid and structure, potentially manifested as self-sustained or divergent oscillations, can be sensitive to many parameters whose values are uncertain. Of interest here are aircraft aeroelastic interactions, which must be accounted for in aircraft certification and design. Deterministic prediction of these aeroelastic behaviors can be difficult owing to physical and computational complexity. New challenges are introduced when physical parameters and elements of the modeling process are uncertain. By viewing aeroelasticity through a nondeterministic prism, where key quantities are assumed stochastic, one may gain insights into how to reduce system uncertainty, increase system robustness, and maintain aeroelastic safety. This article reviews uncertainty quantification in aeroelasticity using traditional analytical techniques not reliant on computational fluid dynamics; compares and contrasts this work with emerging methods based on computational fluid dynamics, which target richer physics; and reviews the state of the art in aeroelastic optimization under uncertainty. Barriers to continued progress, for example, the so-called curse of dimensionality, are discussed.

The Wonderful World of Active Many-Particle Systems

NASA Astrophysics Data System (ADS)

Helbing, Dirk

Since the subject of traffic dynamics has captured the interest of physicists, many astonishing effects have been revealed and explained. Some of the questions now understood are the following: Why are vehicles sometimes stopped by so-called ``phantom traffic jams'', although they all like to drive fast? What are the mechanisms behind stop-and-go traffic? Why are there several different kinds of congestion, and how are they related? Why do most traffic jams occur considerably before the road capacity is reached? Can a temporary reduction of the traffic volume cause a lasting traffic jam? Why do pedestrians moving in opposite directions normally organize in lanes, while nervous crowds are ``freezing by heating''? Why do panicking pedestrians produce dangerous deadlocks? All these questions have been answered by applying and extending methods from statistical physics and non-linear dynamics to self-driven many-particle systems.

Ant Colony Optimization With Local Search for Dynamic Traveling Salesman Problems.

PubMed

Mavrovouniotis, Michalis; Muller, Felipe M; Yang, Shengxiang

2016-06-13

For a dynamic traveling salesman problem (DTSP), the weights (or traveling times) between two cities (or nodes) may be subject to changes. Ant colony optimization (ACO) algorithms have proved to be powerful methods to tackle such problems due to their adaptation capabilities. It has been shown that the integration of local search operators can significantly improve the performance of ACO. In this paper, a memetic ACO algorithm, where a local search operator (called unstring and string) is integrated into ACO, is proposed to address DTSPs. The best solution from ACO is passed to the local search operator, which removes and inserts cities in such a way that improves the solution quality. The proposed memetic ACO algorithm is designed to address both symmetric and asymmetric DTSPs. The experimental results show the efficiency of the proposed memetic algorithm for addressing DTSPs in comparison with other state-of-the-art algorithms.

Computational strategies in the dynamic simulation of constrained flexible MBS

NASA Technical Reports Server (NTRS)

Amirouche, F. M. L.; Xie, M.

1993-01-01

This research focuses on the computational dynamics of flexible constrained multibody systems. At first a recursive mapping formulation of the kinematical expressions in a minimum dimension as well as the matrix representation of the equations of motion are presented. The method employs Kane's equation, FEM, and concepts of continuum mechanics. The generalized active forces are extended to include the effects of high temperature conditions, such as creep, thermal stress, and elastic-plastic deformation. The time variant constraint relations for rolling/contact conditions between two flexible bodies are also studied. The constraints for validation of MBS simulation of gear meshing contact using a modified Timoshenko beam theory are also presented. The last part deals with minimization of vibration/deformation of the elastic beam in multibody systems making use of time variant boundary conditions. The above methodologies and computational procedures developed are being implemented in a program called DYAMUS.

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

Biyikli, Emre; To, Albert C., E-mail: albertto@pitt.edu

Atomistic/continuum coupling methods combine accurate atomistic methods and efficient continuum methods to simulate the behavior of highly ordered crystalline systems. Coupled methods utilize the advantages of both approaches to simulate systems at a lower computational cost, while retaining the accuracy associated with atomistic methods. Many concurrent atomistic/continuum coupling methods have been proposed in the past; however, their true computational efficiency has not been demonstrated. The present work presents an efficient implementation of a concurrent coupling method called the Multiresolution Molecular Mechanics (MMM) for serial, parallel, and adaptive analysis. First, we present the features of the software implemented along with themore » associated technologies. The scalability of the software implementation is demonstrated, and the competing effects of multiscale modeling and parallelization are discussed. Then, the algorithms contributing to the efficiency of the software are presented. These include algorithms for eliminating latent ghost atoms from calculations and measurement-based dynamic balancing of parallel workload. The efficiency improvements made by these algorithms are demonstrated by benchmark tests. The efficiency of the software is found to be on par with LAMMPS, a state-of-the-art Molecular Dynamics (MD) simulation code, when performing full atomistic simulations. Speed-up of the MMM method is shown to be directly proportional to the reduction of the number of the atoms visited in force computation. Finally, an adaptive MMM analysis on a nanoindentation problem, containing over a million atoms, is performed, yielding an improvement of 6.3–8.5 times in efficiency, over the full atomistic MD method. For the first time, the efficiency of a concurrent atomistic/continuum coupling method is comprehensively investigated and demonstrated.« less

Multiresolution molecular mechanics: Implementation and efficiency

NASA Astrophysics Data System (ADS)

Biyikli, Emre; To, Albert C.

2017-01-01

Atomistic/continuum coupling methods combine accurate atomistic methods and efficient continuum methods to simulate the behavior of highly ordered crystalline systems. Coupled methods utilize the advantages of both approaches to simulate systems at a lower computational cost, while retaining the accuracy associated with atomistic methods. Many concurrent atomistic/continuum coupling methods have been proposed in the past; however, their true computational efficiency has not been demonstrated. The present work presents an efficient implementation of a concurrent coupling method called the Multiresolution Molecular Mechanics (MMM) for serial, parallel, and adaptive analysis. First, we present the features of the software implemented along with the associated technologies. The scalability of the software implementation is demonstrated, and the competing effects of multiscale modeling and parallelization are discussed. Then, the algorithms contributing to the efficiency of the software are presented. These include algorithms for eliminating latent ghost atoms from calculations and measurement-based dynamic balancing of parallel workload. The efficiency improvements made by these algorithms are demonstrated by benchmark tests. The efficiency of the software is found to be on par with LAMMPS, a state-of-the-art Molecular Dynamics (MD) simulation code, when performing full atomistic simulations. Speed-up of the MMM method is shown to be directly proportional to the reduction of the number of the atoms visited in force computation. Finally, an adaptive MMM analysis on a nanoindentation problem, containing over a million atoms, is performed, yielding an improvement of 6.3-8.5 times in efficiency, over the full atomistic MD method. For the first time, the efficiency of a concurrent atomistic/continuum coupling method is comprehensively investigated and demonstrated.

The Complex Case of Fear and Safe Space

ERIC Educational Resources Information Center

Stengel, Barbara S.

2010-01-01

Here I shine light on the concept of and call for safe space and on the implicit argument that seems to undergird both the concept and the call, complicating and problematizing the taken for granted view of this issue with the goal of revealing a more complex dynamic worthy of interpretive attention when determining educational response. I…

Data assimilation method based on the constraints of confidence region

NASA Astrophysics Data System (ADS)

Li, Yong; Li, Siming; Sheng, Yao; Wang, Luheng

2018-03-01

The ensemble Kalman filter (EnKF) is a distinguished data assimilation method that is widely used and studied in various fields including methodology and oceanography. However, due to the limited sample size or imprecise dynamics model, it is usually easy for the forecast error variance to be underestimated, which further leads to the phenomenon of filter divergence. Additionally, the assimilation results of the initial stage are poor if the initial condition settings differ greatly from the true initial state. To address these problems, the variance inflation procedure is usually adopted. In this paper, we propose a new method based on the constraints of a confidence region constructed by the observations, called EnCR, to estimate the inflation parameter of the forecast error variance of the EnKF method. In the new method, the state estimate is more robust to both the inaccurate forecast models and initial condition settings. The new method is compared with other adaptive data assimilation methods in the Lorenz-63 and Lorenz-96 models under various model parameter settings. The simulation results show that the new method performs better than the competing methods.

New method for distance-based close following safety indicator.

PubMed

Sharizli, A A; Rahizar, R; Karim, M R; Saifizul, A A

2015-01-01

The increase in the number of fatalities caused by road accidents involving heavy vehicles every year has raised the level of concern and awareness on road safety in developing countries like Malaysia. Changes in the vehicle dynamic characteristics such as gross vehicle weight, travel speed, and vehicle classification will affect a heavy vehicle's braking performance and its ability to stop safely in emergency situations. As such, the aim of this study is to establish a more realistic new distance-based safety indicator called the minimum safe distance gap (MSDG), which incorporates vehicle classification (VC), speed, and gross vehicle weight (GVW). Commercial multibody dynamics simulation software was used to generate braking distance data for various heavy vehicle classes under various loads and speeds. By applying nonlinear regression analysis to the simulation results, a mathematical expression of MSDG has been established. The results show that MSDG is dynamically changed according to GVW, VC, and speed. It is envisaged that this new distance-based safety indicator would provide a more realistic depiction of the real traffic situation for safety analysis.

Experimental and analytical investigation of inertial propulsion mechanisms and motion simulation of rigid multi-body mechanical systems

NASA Astrophysics Data System (ADS)

Almesallmy, Mohammed

Methodologies are developed for dynamic analysis of mechanical systems with emphasis on inertial propulsion systems. This work adopted the Lagrangian methodology. Lagrangian methodology is the most efficient classical computational technique, which we call Equations of Motion Code (EOMC). The EOMC is applied to several simple dynamic mechanical systems for easier understanding of the method and to aid other investigators in developing equations of motion of any dynamic system. In addition, it is applied to a rigid multibody system, such as Thomson IPS [Thomson 1986]. Furthermore, a simple symbolic algorithm is developed using Maple software, which can be used to convert any nonlinear n-order ordinary differential equation (ODE) systems into 1st-order ODE system in ready format to be used in Matlab software. A side issue, but equally important, we have started corresponding with the U.S. Patent office to persuade them that patent applications, claiming gross linear motion based on inertial propulsion systems should be automatically rejected. The precedent is rejection of patent applications involving perpetual motion machines.

Amoeba-inspired nanoarchitectonic computing implemented using electrical Brownian ratchets.

PubMed

Aono, M; Kasai, S; Kim, S-J; Wakabayashi, M; Miwa, H; Naruse, M

2015-06-12

In this study, we extracted the essential spatiotemporal dynamics that allow an amoeboid organism to solve a computationally demanding problem and adapt to its environment, thereby proposing a nature-inspired nanoarchitectonic computing system, which we implemented using a network of nanowire devices called 'electrical Brownian ratchets (EBRs)'. By utilizing the fluctuations generated from thermal energy in nanowire devices, we used our system to solve the satisfiability problem, which is a highly complex combinatorial problem related to a wide variety of practical applications. We evaluated the dependency of the solution search speed on its exploration parameter, which characterizes the fluctuation intensity of EBRs, using a simulation model of our system called 'AmoebaSAT-Brownian'. We found that AmoebaSAT-Brownian enhanced the solution searching speed dramatically when we imposed some constraints on the fluctuations in its time series and it outperformed a well-known stochastic local search method. These results suggest a new computing paradigm, which may allow high-speed problem solving to be implemented by interacting nanoscale devices with low power consumption.

Turnover of Lipidated LC3 and Autophagic Cargoes in Mammalian Cells.

PubMed

Rodríguez-Arribas, M; Yakhine-Diop, S M S; González-Polo, R A; Niso-Santano, M; Fuentes, J M

2017-01-01

Macroautophagy (usually referred to as autophagy) is the most important degradation system in mammalian cells. It is responsible for the elimination of protein aggregates, organelles, and other cellular content. During autophagy, these materials (i.e., cargo) must be engulfed by a double-membrane structure called an autophagosome, which delivers the cargo to the lysosome to complete its degradation. Autophagy is a very dynamic pathway called autophagic flux. The process involves all the steps that are implicated in cargo degradation from autophagosome formation. There are several techniques to monitor autophagic flux. Among them, the method most used experimentally to assess autophagy is the detection of LC3 protein processing and p62 degradation by Western blotting. In this chapter, we provide a detailed and straightforward protocol for this purpose in cultured mammalian cells, including a brief set of notes concerning problems associated with the Western-blotting detection of LC3 and p62. © 2017 Elsevier Inc. All rights reserved.

Dynamical Systems Approaches to Emotional Development

ERIC Educational Resources Information Center

Camras, Linda A.; Witherington, David C.

2005-01-01

Within the last 20 years, transitions in the conceptualization of emotion and its development have given rise to calls for an explanatory framework that captures emotional development in all its organizational complexity and variability. Recent attempts have been made to couch emotional development in terms of a dynamical systems approach through…

AN INDICATOR OF FOREST DYNAMICS USING A SHIFTING LANDSCAPE MOSAIC

EPA Science Inventory

The composition of a landscape is a fundamental indicator in land-cover pattern assessments. The objective of this paper was to evaluate a landscape composition indicator called ‘landscape mosaic’ as a framework for interpreting land-cover dynamics over a 9-year period in a 360,...

Functional hoarseness in children: short-term play therapy with family dynamic counseling as therapy of choice.

PubMed

Kollbrunner, Jürg; Seifert, Eberhard

2013-09-01

Children with nonorganic voice disorders (NVDs) are treated mainly using direct voice therapy techniques such as the accent method or glottal attack changes and indirect methods such as vocal hygiene and voice education. However, both approaches tackle only the symptoms and not etiological factors in the family dynamics and therefore often enjoy little success. The aim of the "Bernese Brief Dynamic Intervention" (BBDI) for children with NVD was to extend the effectiveness of pediatric voice therapies with a psychosomatic concept combining short-term play therapy with the child and family dynamic counseling of the parents. This study compares the therapeutic changes in three groups where different procedures were used, before intervention and 1 year afterward: counseling of parents (one to two consultations; n = 24), Brief Dynamic Intervention on the lines of the BBDI (three to five play therapy sessions with the child plus two to four sessions with the parents; n = 20), and traditional voice therapy (n = 22). A Voice Questionnaire for Parents developed by us with 59 questions to be answered on a four-point Likert scale was used to measure the change. According to the parents' assessment, a significant improvement in voice quality was achieved in all three methods. Counseling of parents (A) appears to have led parents to give their child more latitude, for example, they stopped nagging the child or demanding that he/she should behave strictly by the rules. After BBDI (B), the mothers were more responsive to their children's wishes and the children were more relaxed and their speech became livelier. At home, they called out to them less often at a distance, which probably improved parent-child dialog. Traditional voice therapy (C) seems to have had a positive effect on the children's social competence. BBDI seems to have the deepest, widest, and therefore probably the most enduring therapeutic effect on children with NVD. Copyright © 2013 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

Time-dependent theoretical treatments of the dynamics of electrons and nuclei in molecular systems

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

Deumens, E.; Diz, A.; Longo, R.

1994-07-01

An overview is presented of methods for time-dependent treatments of molecules as systems of electrons and nuclei. The theoretical details of these methods are reviewed and contrasted in the light of a recently developed time-dependent method called electron-nuclear dynamics. Electron-nuclear dynamics (END) is a formulation of the complete dynamics of electrons and nuclei of a molecular system that eliminates the necessity of constructing potential-energy surfaces. Because of its general formulation, it encompasses many aspects found in other formulations and can serve as a didactic device for clarifying many of the principles and approximations relevant in time-dependent treatments of molecular systems.more » The END equations are derived from the time-dependent variational principle applied to a chosen family of efficiently parametrized approximate state vectors. A detailed analysis of the END equations is given for the case of a single-determinantal state for the electrons and a classical treatment of the nuclei. The approach leads to a simple formulation of the fully nonlinear time-dependent Hartree-Fock theory including nuclear dynamics. The nonlinear END equations with the [ital ab] [ital initio] Coulomb Hamiltonian have been implemented at this level of theory in a computer program, ENDyne, and have been shown feasible for the study of small molecular systems. Implementation of the Austin Model 1 semiempirical Hamiltonian is discussed as a route to large molecular systems. The linearized END equations at this level of theory are shown to lead to the random-phase approximation for the coupled system of electrons and nuclei. The qualitative features of the general nonlinear solution are analyzed using the results of the linearized equations as a first approximation. Some specific applications of END are presented, and the comparison with experiment and other theoretical approaches is discussed.« less

Optimization,Modeling, and Control: Applications to Klystron Designing and Hepatitis C Virus Dynamics

NASA Astrophysics Data System (ADS)

Lankford, George Bernard

In this dissertation, we address applying mathematical and numerical techniques in the fields of high energy physics and biomedical sciences. The first portion of this thesis presents a method for optimizing the design of klystron circuits. A klystron is an electron beam tube lined with cavities that emit resonant frequencies to velocity modulate electrons that pass through the tube. Radio frequencies (RF) inserted in the klystron are amplified due to the velocity modulation of the electrons. The routine described in this work automates the selection of cavity positions, resonant frequencies, quality factors, and other circuit parameters to maximize the efficiency with required gain. The method is based on deterministic sampling methods. We will describe the procedure and give several examples for both narrow and wide band klystrons, using the klystron codes AJDISK (Java) and TESLA (Python). The rest of the dissertation is dedicated to developing, calibrating and using a mathematical model for hepatitis C dynamics with triple drug combination therapy. Groundbreaking new drugs, called direct acting antivirals, have been introduced recently to fight off chronic hepatitis C virus infection. The model we introduce is for hepatitis C dynamics treated with the direct acting antiviral drug, telaprevir, along with traditional interferon and ribavirin treatments to understand how this therapy affects the viral load of patients exhibiting different types of response. We use sensitivity and identifiability techniques to determine which parameters can be best estimated from viral load data. We use these estimations to give patient-specific fits of the model to partial viral response, end-of-treatment response, and breakthrough patients. We will then revise the model to incorporate an immune response dynamic to more accurately describe the dynamics. Finally, we will implement a suboptimal control to acquire a drug treatment regimen that will alleviate the systemic cost associated with constant drug treatment.

Temporal networks

NASA Astrophysics Data System (ADS)

Holme, Petter; Saramäki, Jari

2012-10-01

A great variety of systems in nature, society and technology-from the web of sexual contacts to the Internet, from the nervous system to power grids-can be modeled as graphs of vertices coupled by edges. The network structure, describing how the graph is wired, helps us understand, predict and optimize the behavior of dynamical systems. In many cases, however, the edges are not continuously active. As an example, in networks of communication via e-mail, text messages, or phone calls, edges represent sequences of instantaneous or practically instantaneous contacts. In some cases, edges are active for non-negligible periods of time: e.g., the proximity patterns of inpatients at hospitals can be represented by a graph where an edge between two individuals is on throughout the time they are at the same ward. Like network topology, the temporal structure of edge activations can affect dynamics of systems interacting through the network, from disease contagion on the network of patients to information diffusion over an e-mail network. In this review, we present the emergent field of temporal networks, and discuss methods for analyzing topological and temporal structure and models for elucidating their relation to the behavior of dynamical systems. In the light of traditional network theory, one can see this framework as moving the information of when things happen from the dynamical system on the network, to the network itself. Since fundamental properties, such as the transitivity of edges, do not necessarily hold in temporal networks, many of these methods need to be quite different from those for static networks. The study of temporal networks is very interdisciplinary in nature. Reflecting this, even the object of study has many names-temporal graphs, evolving graphs, time-varying graphs, time-aggregated graphs, time-stamped graphs, dynamic networks, dynamic graphs, dynamical graphs, and so on. This review covers different fields where temporal graphs are considered, but does not attempt to unify related terminology-rather, we want to make papers readable across disciplines.

Estimating Atomic Contributions to Hydration and Binding Using Free Energy Perturbation.

PubMed

Irwin, Benedict W J; Huggins, David J

2018-06-12

We present a general method called atom-wise free energy perturbation (AFEP), which extends a conventional molecular dynamics free energy perturbation (FEP) simulation to give the contribution to a free energy change from each atom. AFEP is derived from an expansion of the Zwanzig equation used in the exponential averaging method by defining that the system total energy can be partitioned into contributions from each atom. A partitioning method is assumed and used to group terms in the expansion to correspond to individual atoms. AFEP is applied to six example free energy changes to demonstrate the method. Firstly, the hydration free energies of methane, methanol, methylamine, methanethiol, and caffeine in water. AFEP highlights the atoms in the molecules that interact favorably or unfavorably with water. Finally AFEP is applied to the binding free energy of human immunodeficiency virus type 1 protease to lopinavir, and AFEP reveals the contribution of each atom to the binding free energy, indicating candidate areas of the molecule to improve to produce a more strongly binding inhibitor. FEP gives a single value for the free energy change and is already a very useful method. AFEP gives a free energy change for each "part" of the system being simulated, where part can mean individual atoms, chemical groups, amino acids, or larger partitions depending on what the user is trying to measure. This method should have various applications in molecular dynamics studies of physical, chemical, or biochemical phenomena, specifically in the field of computational drug discovery.

Multi-spectral fiber spectroscopy in 0,4-16μm range for biomedical applications(Conference Presentation)

NASA Astrophysics Data System (ADS)

Artyushenko, Viacheslav

2017-02-01

Various biomedical applications of fiber optics in a broad spectral range 0,4-16μm span from endoscopic imaging and Photo Dynamic Diagnostics (PDD) to laser power delivery for minimal invasive laser surgery, tissue coagulation and welding, Photo Dynamic Therapy (PDT), etc. Present review will highlight the latest results in advanced fiber solutions for a precise tissue diagnostics and control of some therapy methods - for so called "theranostic". Spectral fiber sensing for label free analysis of tissue composition helps to differentiate malignant and normal tissue to secure minimal invasive, but complete tumor removal or treatment. All key methods of Raman, fluorescence, diffuse reflection & MIR-absorption spectroscopy will be compared when used for the same spot of tissue - to select the most specific, sensitive and accurate method or to combine them for the synergy enhanced effect. The most informative spectral features for distinct organs/ tumor can be used to design special fiber sensors to be developed for portable and low cost applications with modern IT-features. Examples of multi-spectral tissue diagnostics promising for the future clinical applications will be presented to enable reduced mortality from cancer in the future. Translation of described methods into clinical practice will be discussed in comparison with the other method of optical diagnostics which should enhance modern medicine by less invasive, more precise and more effective methods of therapy to be fused with in-vivo diagnostics sensors & systems.

Quantification of Asian Dust Plume Seasonal Dynamics and Regional Features

NASA Technical Reports Server (NTRS)

Goetz, Michael

2011-01-01

Dust is but one of many aerosols that are analyzed at the Jet Propulsion Laboratory in Pasadena. The purpose of this paper is to describe the process in analyzing and digitizing dust within a source region to better explain the work achieved by my internship. This paper will go over how to view collected data by Multi-angle Imaging SpectroRadiometer (MISR) [1] and the procedure of downloading data to be analyzed. With this data, one can digitize dust plumes using two methods called plume lines and plume polygons with the help of the software MISR INteractive eXplorer (MINX)[3]; thus, the theory of MINX's[3] algorithm and these methods are discussed in detail. Research was gathered from these techniques and emphasis is also focused on the obtained data and results.

Optical imaging through dynamic turbid media using the Fourier-domain shower-curtain effect

PubMed Central

Edrei, Eitan; Scarcelli, Giuliano

2016-01-01

Several phenomena have been recently exploited to circumvent scattering and have succeeded in imaging or focusing light through turbid layers. However, the requirement for the turbid medium to be steady during the imaging process remains a fundamental limitation of these methods. Here we introduce an optical imaging modality that overcomes this challenge by taking advantage of the so-called shower-curtain effect, adapted to the spatial-frequency domain via speckle correlography. We present high resolution imaging of objects hidden behind millimeter-thick tissue or dense lens cataracts. We demonstrate our imaging technique to be insensitive to rapid medium movements (> 5 m/s) beyond any biologically-relevant motion. Furthermore, we show this method can be extended to several contrast mechanisms and imaging configurations. PMID:27347498