Feedforward-feedback hybrid control for magnetic shape memory alloy actuators based on the Krasnosel'skii-Pokrovskii model.

PubMed

Zhou, Miaolei; Zhang, Qi; Wang, Jingyuan

2014-01-01

As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system.

The influence of averaging and noisy decision strategies on the recognition memory ROC.

PubMed

Malmberg, Kenneth J; Xu, Jing

2006-02-01

Many single- and dual-process models of recognition memory predict that the ratings and remember-know receiver operating characteristics (ROCs) are the same, but Rotello, Macmillan, and Reeder (2004) reported that the slopes of the remember-know and ratings z-transformed ROCs (zROCs) are different The authors show that averaging introduces nonlinearities to the form of the zROC and that ratings and remember-know zROCs are indistinguishable when constructed in a conventional manner. The authors show, further, that some nonoptimal decision strategies have a distinctive, nonlinear effect on the form of the single-process continuous-state zROC. The conclusion is that many factors having nothing to do with the nature of recognition memory can affect the shape of zROCs, and that therefore, the shape of the zROC does not, alone, characterize different memory models.

INDIRECT INTELLIGENT SLIDING MODE CONTROL OF A SHAPE MEMORY ALLOY ACTUATED FLEXIBLE BEAM USING HYSTERETIC RECURRENT NEURAL NETWORKS.

PubMed

Hannen, Jennifer C; Crews, John H; Buckner, Gregory D

2012-08-01

This paper introduces an indirect intelligent sliding mode controller (IISMC) for shape memory alloy (SMA) actuators, specifically a flexible beam deflected by a single offset SMA tendon. The controller manipulates applied voltage, which alters SMA tendon temperature to track reference bending angles. A hysteretic recurrent neural network (HRNN) captures the nonlinear, hysteretic relationship between SMA temperature and bending angle. The variable structure control strategy provides robustness to model uncertainties and parameter variations, while effectively compensating for system nonlinearities, achieving superior tracking compared to an optimized PI controller.

An NN-Based SRD Decomposition Algorithm and Its Application in Nonlinear Compensation

PubMed Central

Yan, Honghang; Deng, Fang; Sun, Jian; Chen, Jie

2014-01-01

In this study, a neural network-based square root of descending (SRD) order decomposition algorithm for compensating for nonlinear data generated by sensors is presented. The study aims at exploring the optimized decomposition of data 1.00,0.00,0.00 and minimizing the computational complexity and memory space of the training process. A linear decomposition algorithm, which automatically finds the optimal decomposition of N subparts and reduces the training time to 1N and memory cost to 1N, has been implemented on nonlinear data obtained from an encoder. Particular focus is given to the theoretical access of estimating the numbers of hidden nodes and the precision of varying the decomposition method. Numerical experiments are designed to evaluate the effect of this algorithm. Moreover, a designed device for angular sensor calibration is presented. We conduct an experiment that samples the data of an encoder and compensates for the nonlinearity of the encoder to testify this novel algorithm. PMID:25232912

Nonlinear waves in reaction-diffusion systems: The effect of transport memory

NASA Astrophysics Data System (ADS)

Manne, K. K.; Hurd, A. J.; Kenkre, V. M.

2000-04-01

Motivated by the problem of determining stress distributions in granular materials, we study the effect of finite transport correlation times on the propagation of nonlinear wave fronts in reaction-diffusion systems. We obtain results such as the possibility of spatial oscillations in the wave-front shape for certain values of the system parameters and high enough wave-front speeds. We also generalize earlier known results concerning the minimum wave-front speed and shape-speed relationships stemming from the finiteness of the correlation times. Analytic investigations are made possible by a piecewise linear representation of the nonlinearity.

Effect of Alzheimer's disease risk and protective factors on cognitive trajectories in subjective memory complainers.

PubMed

Teipel, Stefan J; Cavedo, Enrica; Lista, Simone; Habert, Marie-Odile; Potier, Marie-Claude; Grothe, Michel J; Epelbaum, Stephane; Sambati, Luisa; Gagliardi, Geoffroy; Toschi, Nicola; Greicius, Michael; Dubois, Bruno; Hampel, Harald

2018-05-21

Cognitive change in people at risk of Alzheimer's disease (AD) such as subjective memory complainers is highly variable across individuals. We used latent class growth modeling to identify distinct classes of nonlinear trajectories of cognitive change over 2 years follow-up from 265 subjective memory complainers individuals (age 70 years and older) of the INSIGHT-preAD cohort. We determined the effect of cortical amyloid load, hippocampus and basal forebrain volumes, and education on the cognitive trajectory classes. Latent class growth modeling identified distinct nonlinear cognitive trajectories. Education was associated with higher performing trajectories, whereas global amyloid load and basal forebrain atrophy were associated with lower performing trajectories. Distinct classes of cognitive trajectories were associated with risk and protective factors of AD. These associations support the notion that the identified cognitive trajectories reflect different risk for AD that may be useful for selecting high-risk individuals for intervention trials. Copyright © 2018. Published by Elsevier Inc.

Internal filament modulation in low-dielectric gap design for built-in selector-less resistive switching memory application

NASA Astrophysics Data System (ADS)

Chen, Ying-Chen; Lin, Chih-Yang; Huang, Hui-Chun; Kim, Sungjun; Fowler, Burt; Chang, Yao-Feng; Wu, Xiaohan; Xu, Gaobo; Chang, Ting-Chang; Lee, Jack C.

2018-02-01

Sneak path current is a severe hindrance for the application of high-density resistive random-access memory (RRAM) array designs. In this work, we demonstrate nonlinear (NL) resistive switching characteristics of a HfO x /SiO x -based stacking structure as a realization for selector-less RRAM devices. The NL characteristic was obtained and designed by optimizing the internal filament location with a low effective dielectric constant in the HfO x /SiO x structure. The stacking HfO x /SiO x -based RRAM device as the one-resistor-only memory cell is applicable without needing an additional selector device to solve the sneak path issue with a switching voltage of ~1 V, which is desirable for low-power operating in built-in nonlinearity crossbar array configurations.

New non-linear model of groundwater recharge: Inclusion of memory, heterogeneity and visco-elasticity

NASA Astrophysics Data System (ADS)

Spannenberg, Jescica; Atangana, Abdon; Vermeulen, P. D.

2017-09-01

Fractional differentiation has adequate use for investigating real world scenarios related to geological formations associated with elasticity, heterogeneity, viscoelasticity, and the memory effect. Since groundwater systems exist in these geological formations, modelling groundwater recharge as a real world scenario is a challenging task to do because existing recharge estimation methods are governed by linear equations which make use of constant field parameters. This is inadequate because in reality these parameters are a function of both space and time. This study therefore concentrates on modifying the recharge equation governing the EARTH model, by application of the Eton approach. Accordingly, this paper presents a modified equation which is non-linear, and accounts for parameters in a way that it is a function of both space and time. To be more specific, herein, recharge and drainage resistance which are parameters within the equation, became a function of both space and time. Additionally, the study entailed solving the non-linear equation using an iterative method as well as numerical solutions by means of the Crank-Nicolson scheme. The numerical solutions were used alongside the Riemann-Liouville, Caputo-Fabrizio, and Atangana-Baleanu derivatives, so that account was taken for elasticity, heterogeneity, viscoelasticity, and the memory effect. In essence, this paper presents a more adequate model for recharge estimation.

Genetically determined interaction between the dopamine transporter and the D2 receptor on prefronto-striatal activity and volume in humans.

PubMed

Bertolino, Alessandro; Fazio, Leonardo; Di Giorgio, Annabella; Blasi, Giuseppe; Romano, Raffaella; Taurisano, Paolo; Caforio, Grazia; Sinibaldi, Lorenzo; Ursini, Gianluca; Popolizio, Teresa; Tirotta, Emanuele; Papp, Audrey; Dallapiccola, Bruno; Borrelli, Emiliana; Sadee, Wolfgang

2009-01-28

Dopamine modulation of neuronal activity during memory tasks identifies a nonlinear inverted-U shaped function. Both the dopamine transporter (DAT) and dopamine D(2) receptors (encoded by DRD(2)) critically regulate dopamine signaling in the striatum and in prefrontal cortex during memory. Moreover, in vitro studies have demonstrated that DAT and D(2) proteins reciprocally regulate each other presynaptically. Therefore, we have evaluated the genetic interaction between a DRD(2) polymorphism (rs1076560) causing reduced presynaptic D(2) receptor expression and the DAT 3'-VNTR variant (affecting DAT expression) in a large sample of healthy subjects undergoing blood oxygenation level-dependent (BOLD)-functional magnetic resonance imaging (MRI) during memory tasks and structural MRI. Results indicated a significant DRD(2)/DAT interaction in prefrontal cortex and striatum BOLD activity during both working memory and encoding of recognition memory. The differential effect on BOLD activity of the DAT variant was mostly manifest in the context of the DRD(2) allele associated with lower presynaptic expression. Similar results were also evident for gray matter volume in caudate. These interactions describe a nonlinear relationship between compound genotypes and brain activity or gray matter volume. Complementary data from striatal protein extracts from wild-type and D(2) knock-out animals (D2R(-/-)) indicate that DAT and D(2) proteins interact in vivo. Together, our results demonstrate that the interaction between genetic variants in DRD(2) and DAT critically modulates the nonlinear relationship between dopamine and neuronal activity during memory processing.

Analysis of intelligent hinged shell structures: deployable deformation and shape memory effect

NASA Astrophysics Data System (ADS)

Shi, Guang-Hui; Yang, Qing-Sheng; He, X. Q.

2013-12-01

Shape memory polymers (SMPs) are a class of intelligent materials with the ability to recover their initial shape from a temporarily fixable state when subjected to external stimuli. In this work, the thermo-mechanical behavior of a deployable SMP-based hinged structure is modeled by the finite element method using a 3D constitutive model with shape memory effect. The influences of hinge structure parameters on the nonlinear loading process are investigated. The total shape memory of the processes the hinged structure goes through, including loading at high temperature, decreasing temperature with load carrying, unloading at low temperature and recovering the initial shape with increasing temperature, are illustrated. Numerical results show that the present constitutive theory and the finite element method can effectively predict the complicated thermo-mechanical deformation behavior and shape memory effect of SMP-based hinged shell structures.

Efficient L1 regularization-based reconstruction for fluorescent molecular tomography using restarted nonlinear conjugate gradient.

PubMed

Shi, Junwei; Zhang, Bin; Liu, Fei; Luo, Jianwen; Bai, Jing

2013-09-15

For the ill-posed fluorescent molecular tomography (FMT) inverse problem, the L1 regularization can protect the high-frequency information like edges while effectively reduce the image noise. However, the state-of-the-art L1 regularization-based algorithms for FMT reconstruction are expensive in memory, especially for large-scale problems. An efficient L1 regularization-based reconstruction algorithm based on nonlinear conjugate gradient with restarted strategy is proposed to increase the computational speed with low memory consumption. The reconstruction results from phantom experiments demonstrate that the proposed algorithm can obtain high spatial resolution and high signal-to-noise ratio, as well as high localization accuracy for fluorescence targets.

The consentaneous model of the financial markets exhibiting spurious nature of long-range memory

NASA Astrophysics Data System (ADS)

Gontis, V.; Kononovicius, A.

2018-09-01

It is widely accepted that there is strong persistence in the volatility of financial time series. The origin of the observed persistence, or long-range memory, is still an open problem as the observed phenomenon could be a spurious effect. Earlier we have proposed the consentaneous model of the financial markets based on the non-linear stochastic differential equations. The consentaneous model successfully reproduces empirical probability and power spectral densities of volatility. This approach is qualitatively different from models built using fractional Brownian motion. In this contribution we investigate burst and inter-burst duration statistics of volatility in the financial markets employing the consentaneous model. Our analysis provides an evidence that empirical statistical properties of burst and inter-burst duration can be explained by non-linear stochastic differential equations driving the volatility in the financial markets. This serves as an strong argument that long-range memory in finance can have spurious nature.

All-optical clocked flip-flops and random access memory cells using the nonlinear polarization rotation effect of low-polarization-dependent semiconductor optical amplifiers

NASA Astrophysics Data System (ADS)

Wang, Yongjun; Liu, Xinyu; Tian, Qinghua; Wang, Lina; Xin, Xiangjun

2018-03-01

Basic configurations of various all-optical clocked flip-flops (FFs) and optical random access memory (RAM) based on the nonlinear polarization rotation (NPR) effect of low-polarization-dependent semiconductor optical amplifiers (SOA) are proposed. As the constituent elements, all-optical logic gates and all-optical SR latches are constructed by taking advantage of the SOA's NPR switch. Different all-optical FFs (AOFFs), including SR-, D-, T-, and JK-types as well as an optical RAM cell were obtained by the combination of the proposed all-optical SR latches and logic gates. The effectiveness of the proposed schemes were verified by simulation results and demonstrated by a D-FF and 1-bit RAM cell experimental system. The proposed all-optical clocked FFs and RAM cell are significant to all-optical signal processing.

An extended macro model accounting for acceleration changes with memory and numerical tests

NASA Astrophysics Data System (ADS)

Cheng, Rongjun; Ge, Hongxia; Sun, Fengxin; Wang, Jufeng

2018-09-01

Considering effect of acceleration changes with memory, an improved continuum model of traffic flow is proposed in this paper. By applying the linear stability theory, we derived the new model's linear stability condition. Through nonlinear analysis, the KdV-Burgers equation is derived to describe the propagating behavior of traffic density wave near the neutral stability line. Numerical simulation is carried out to study the extended traffic flow model, which explores how acceleration changes with memory affected each car's velocity, density and fuel consumption and exhaust emissions. Numerical results demonstrate that acceleration changes with memory have significant negative effect on dynamic characteristic of traffic flow. Furthermore, research results verify that the effect of acceleration changes with memory will deteriorate the stability of traffic flow and increase cars' total fuel consumptions and emissions during the whole evolution of small perturbation.

My Experience with Ti-Ni-Based and Ti-Based Shape Memory Alloys

NASA Astrophysics Data System (ADS)

Miyazaki, Shuichi

2017-12-01

The present author has been studying shape memory alloys including Cu-Al-Ni, Ti-Ni-based, and Ni-free Ti-based alloys since 1979. This paper reviews the present author's research results for the latter two materials since 1981. The topics on the Ti-Ni-based alloys include the achievement of superelasticity in Ti-Ni alloys through understanding of the role of microstructures consisting of dislocations and precipitates, followed by the contribution to the development of application market of shape memory effect and superelasticity, characterization of the R-phase and monoclinic martensitic transformations, clarification of the basic characteristics of fatigue properties, development of sputter-deposited shape memory thin films and fabrication of prototypes of microactuators utilizing thin films, development of high temperature shape memory alloys, and so on. The topics of Ni-free Ti-based shape memory alloys include the characterization of the orthorhombic phase martensitic transformation and related shape memory effect and superelasticity, the effects of texture, omega phase and adding elements on the martensitic transformation and shape memory properties, clarification of the unique effects of oxygen addition to induce non-linear large elasticity, Invar effect and heating-induced martensitic transformation, and so on.

An extended continuum model considering optimal velocity change with memory and numerical tests

NASA Astrophysics Data System (ADS)

Qingtao, Zhai; Hongxia, Ge; Rongjun, Cheng

2018-01-01

In this paper, an extended continuum model of traffic flow is proposed with the consideration of optimal velocity changes with memory. The new model's stability condition and KdV-Burgers equation considering the optimal velocities change with memory are deduced through linear stability theory and nonlinear analysis, respectively. Numerical simulation is carried out to study the extended continuum model, which explores how optimal velocity changes with memory affected velocity, density and energy consumption. Numerical results show that when considering the effects of optimal velocity changes with memory, the traffic jams can be suppressed efficiently. Both the memory step and sensitivity parameters of optimal velocity changes with memory will enhance the stability of traffic flow efficiently. Furthermore, numerical results demonstrates that the effect of optimal velocity changes with memory can avoid the disadvantage of historical information, which increases the stability of traffic flow on road, and so it improve the traffic flow stability and minimize cars' energy consumptions.

Spin memory effect for compact binaries in the post-Newtonian approximation

NASA Astrophysics Data System (ADS)

Nichols, David A.

2017-04-01

The spin memory effect is a recently predicted relativistic phenomenon in asymptotically flat spacetimes that become nonradiative infinitely far in the past and future. Between these early and late times, the magnetic-parity part of the time integral of the gravitational-wave strain can undergo a nonzero change; this difference is the spin memory effect. Families of freely falling observers around an isolated source can measure this effect, in principle, and fluxes of angular momentum per unit solid angle (or changes in superspin charges) generate the effect. The spin memory effect had not been computed explicitly for astrophysical sources of gravitational waves, such as compact binaries. In this paper, we compute the spin memory in terms of a set of radiative multipole moments of the gravitational-wave strain. The result of this calculation allows us to establish the following results about the spin memory: (i) We find that the accumulation of the spin memory behaves in a qualitatively different way from that of the displacement memory effect for nonspinning, quasicircular compact binaries in the post-Newtonian approximation: the spin memory undergoes a large secular growth over the duration of the inspiral, whereas for the displacement effect this increase is small. (ii) The rate at which the spin memory grows is equivalent to a nonlinear, but nonoscillatory and nonhereditary effect in the gravitational waveform that had been previously calculated for nonspinning, quasicircular compact binaries. (iii) This rate of buildup of the spin memory could potentially be detected by future gravitational-wave detectors by carefully combining the measured waveforms from hundreds of gravitational-wave detections of compact binaries.

Super non-linear RRAM with ultra-low power for 3D vertical nano-crossbar arrays.

PubMed

Luo, Qing; Xu, Xiaoxin; Liu, Hongtao; Lv, Hangbing; Gong, Tiancheng; Long, Shibing; Liu, Qi; Sun, Haitao; Banerjee, Writam; Li, Ling; Gao, Jianfeng; Lu, Nianduan; Liu, Ming

2016-08-25

Vertical crossbar arrays provide a cost-effective approach for high density three-dimensional (3D) integration of resistive random access memory. However, an individual selector device is not allowed to be integrated with the memory cell separately. The development of V-RRAM has impeded the lack of satisfactory self-selective cells. In this study, we have developed a high performance bilayer self-selective device using HfO2 as the memory switching layer and a mixed ionic and electron conductor as the selective layer. The device exhibits high non-linearity (>10(3)) and ultra-low half-select leakage (<0.1 pA). A four layer vertical crossbar array was successfully demonstrated based on the developed self-selective device. High uniformity, ultra-low leakage, sub-nA operation, self-compliance, and excellent read/write disturbance immunity were achieved. The robust array level performance shows attractive potential for low power and high density 3D data storage applications.

Nonlinear density wave investigation for an extended car-following model considering driver’s memory and jerk

NASA Astrophysics Data System (ADS)

Jin, Zhizhan; Li, Zhipeng; Cheng, Rongjun; Ge, Hongxia

2018-01-01

Based on the two velocity difference model (TVDM), an extended car-following model is developed to investigate the effect of driver’s memory and jerk on traffic flow in this paper. By using linear stability analysis, the stability conditions are derived. And through nonlinear analysis, the time-dependent Ginzburg-Landau (TDGL) equation and the modified Korteweg-de Vries (mKdV) equation are obtained, respectively. The mKdV equation is constructed to describe the traffic behavior near the critical point. The evolution of traffic congestion and the corresponding energy consumption are discussed. Numerical simulations show that the improved model is found not only to enhance the stability of traffic flow, but also to depress the energy consumption, which are consistent with the theoretical analysis.

Sparse distributed memory: understanding the speed and robustness of expert memory

PubMed Central

Brogliato, Marcelo S.; Chada, Daniel M.; Linhares, Alexandre

2014-01-01

How can experts, sometimes in exacting detail, almost immediately and very precisely recall memory items from a vast repertoire? The problem in which we will be interested concerns models of theoretical neuroscience that could explain the speed and robustness of an expert's recollection. The approach is based on Sparse Distributed Memory, which has been shown to be plausible, both in a neuroscientific and in a psychological manner, in a number of ways. A crucial characteristic concerns the limits of human recollection, the “tip-of-tongue” memory event—which is found at a non-linearity in the model. We expand the theoretical framework, deriving an optimization formula to solve this non-linearity. Numerical results demonstrate how the higher frequency of rehearsal, through work or study, immediately increases the robustness and speed associated with expert memory. PMID:24808842

Thermomechanical behavior of a two-way shape memory composite actuator

NASA Astrophysics Data System (ADS)

Ge, Qi; Westbrook, Kristofer K.; Mather, Patrick T.; Dunn, Martin L.; Qi, H. Jerry

2013-05-01

Shape memory polymers (SMPs) are a class of smart materials that can fix a temporary shape and recover to their permanent (original) shape in response to an environmental stimulus such as heat, electricity, or irradiation, among others. Most SMPs developed in the past can only demonstrate the so-called one-way shape memory effect; i.e., one programming step can only yield one shape memory cycle. Recently, one of the authors (Mather) developed a SMP that exhibits both one-way shape memory (1W-SM) and two-way shape memory (2W-SM) effects (with the assistance of an external load). This SMP was further used to develop a free-standing composite actuator with a nonlinear reversible actuation under thermal cycling. In this paper, a theoretical model for the PCO SMP based composite actuator was developed to investigate its thermomechanical behavior and the mechanisms for the observed phenomena during the actuation cycles, and to provide insight into how to improve the design.

Nonlinear optical memory for manipulation of orbital angular momentum of light.

PubMed

de Oliveira, R A; Borba, G C; Martins, W S; Barreiro, S; Felinto, D; Tabosa, J W R

2015-11-01

We report on the demonstration of a nonlinear optical memory (NOM) for storage and on-demand manipulation of orbital angular momentum (OAM) of light via higher-order nonlinear processes in cold cesium atoms. A spatially resolved phase-matching technique is used to select each order of the nonlinear susceptibility associated, respectively, with time-delayed four-, six-, and eight-wave mixing processes. For a specific configuration of the stored OAM of the incident beams, we demonstrated that the OAM of the retrieved beam can be manipulated according to the order of the nonlinear process chosen by the operator for reading out the NOM. This demonstration indicates new pathways for applications in classical and quantum information processing where OAM of light is used to encode optical information.

Blind identification of nonlinear models with non-Gaussian inputs

NASA Astrophysics Data System (ADS)

Prakriya, Shankar; Pasupathy, Subbarayan; Hatzinakos, Dimitrios

1995-12-01

Some methods are proposed for the blind identification of finite-order discrete-time nonlinear models with non-Gaussian circular inputs. The nonlinear models consist of two finite memory linear time invariant (LTI) filters separated by a zero-memory nonlinearity (ZMNL) of the polynomial type (the LTI-ZMNL-LTI models). The linear subsystems are allowed to be of non-minimum phase (NMP). The methods base their estimates of the impulse responses on slices of the N plus 1th order polyspectra of the output sequence. It is shown that the identification of LTI-ZMNL systems requires only a 1-D moment or polyspectral slice. The coefficients of the ZMNL are not estimated, and need not be known. The order of the nonlinearity can, in theory, be estimated from the received signal. These methods possess several noise and interference suppression characteristics, and have applications in modeling nonlinearly amplified QAM/QPSK signals in digital satellite and microwave communications.

Method and system for training dynamic nonlinear adaptive filters which have embedded memory

NASA Technical Reports Server (NTRS)

Rabinowitz, Matthew (Inventor)

2002-01-01

Described herein is a method and system for training nonlinear adaptive filters (or neural networks) which have embedded memory. Such memory can arise in a multi-layer finite impulse response (FIR) architecture, or an infinite impulse response (IIR) architecture. We focus on filter architectures with separate linear dynamic components and static nonlinear components. Such filters can be structured so as to restrict their degrees of computational freedom based on a priori knowledge about the dynamic operation to be emulated. The method is detailed for an FIR architecture which consists of linear FIR filters together with nonlinear generalized single layer subnets. For the IIR case, we extend the methodology to a general nonlinear architecture which uses feedback. For these dynamic architectures, we describe how one can apply optimization techniques which make updates closer to the Newton direction than those of a steepest descent method, such as backpropagation. We detail a novel adaptive modified Gauss-Newton optimization technique, which uses an adaptive learning rate to determine both the magnitude and direction of update steps. For a wide range of adaptive filtering applications, the new training algorithm converges faster and to a smaller value of cost than both steepest-descent methods such as backpropagation-through-time, and standard quasi-Newton methods. We apply the algorithm to modeling the inverse of a nonlinear dynamic tracking system 5, as well as a nonlinear amplifier 6.

A review on shape memory alloys with applications to morphing aircraft

NASA Astrophysics Data System (ADS)

Barbarino, S.; Saavedra Flores, E. I.; Ajaj, R. M.; Dayyani, I.; Friswell, M. I.

2014-06-01

Shape memory alloys (SMAs) are a unique class of metallic materials with the ability to recover their original shape at certain characteristic temperatures (shape memory effect), even under high applied loads and large inelastic deformations, or to undergo large strains without plastic deformation or failure (super-elasticity). In this review, we describe the main features of SMAs, their constitutive models and their properties. We also review the fatigue behavior of SMAs and some methods adopted to remove or reduce its undesirable effects. SMAs have been used in a wide variety of applications in different fields. In this review, we focus on the use of shape memory alloys in the context of morphing aircraft, with particular emphasis on variable twist and camber, and also on actuation bandwidth and reduction of power consumption. These applications prove particularly challenging because novel configurations are adopted to maximize integration and effectiveness of SMAs, which play the role of an actuator (using the shape memory effect), often combined with structural, load-carrying capabilities. Iterative and multi-disciplinary modeling is therefore necessary due to the fluid-structure interaction combined with the nonlinear behavior of SMAs.

Modeling dynamic acousto-elastic testing experiments: validation and perspectives.

PubMed

Gliozzi, A S; Scalerandi, M

2014-10-01

Materials possessing micro-inhomogeneities often display a nonlinear response to mechanical solicitations, which is sensitive to the confining pressure acting on the sample. Dynamic acoustoelastic testing allows measurement of the instantaneous variations in the elastic modulus due to the change of the dynamic pressure induced by a low-frequency wave. This paper shows that a Preisach-Mayergoyz space based hysteretic multi-state elastic model provides an explanation for experimental observations in consolidated granular media and predicts memory and nonlinear effects comparable to those measured in rocks.

Parametric analysis and temperature effect of deployable hinged shells using shape memory polymers

NASA Astrophysics Data System (ADS)

Tao, Ran; Yang, Qing-Sheng; He, Xiao-Qiao; Liew, Kim-Meow

2016-11-01

Shape memory polymers (SMPs) are a class of intelligent materials, which are defined by their capacity to store a temporary shape and recover an original shape. In this work, the shape memory effect of SMP deployable hinged shell is simulated by using compiled user defined material subroutine (UMAT) subroutine of ABAQUS. Variations of bending moment and strain energy of the hinged shells with different temperatures and structural parameters in the loading process are given. The effects of the parameters and temperature on the nonlinear deformation process are emphasized. The entire thermodynamic cycle of SMP deployable hinged shell includes loading at high temperature, load carrying with cooling, unloading at low temperature and recovering the original shape with heating. The results show that the complicated thermo-mechanical deformation and shape memory effect of SMP deployable hinge are influenced by the structural parameters and temperature. The design ability of SMP smart hinged structures in practical application is prospected.

Inverse halftoning via robust nonlinear filtering

NASA Astrophysics Data System (ADS)

Shen, Mei-Yin; Kuo, C.-C. Jay

1999-10-01

A new blind inverse halftoning algorithm based on a nonlinear filtering technique of low computational complexity and low memory requirement is proposed in this research. It is called blind since we do not require the knowledge of the halftone kernel. The proposed scheme performs nonlinear filtering in conjunction with edge enhancement to improve the quality of an inverse halftoned image. Distinct features of the proposed approach include: efficiently smoothing halftone patterns in large homogeneous areas, additional edge enhancement capability to recover the edge quality and an excellent PSNR performance with only local integer operations and a small memory buffer.

On the predictability of extreme events in records with linear and nonlinear long-range memory: Efficiency and noise robustness

NASA Astrophysics Data System (ADS)

Bogachev, Mikhail I.; Bunde, Armin

2011-06-01

We study the predictability of extreme events in records with linear and nonlinear long-range memory in the presence of additive white noise using two different approaches: (i) the precursory pattern recognition technique (PRT) that exploits solely the information about short-term precursors, and (ii) the return interval approach (RIA) that exploits long-range memory incorporated in the elapsed time after the last extreme event. We find that the PRT always performs better when only linear memory is present. In the presence of nonlinear memory, both methods demonstrate comparable efficiency in the absence of white noise. When additional white noise is present in the record (which is the case in most observational records), the efficiency of the PRT decreases monotonously with increasing noise level. In contrast, the RIA shows an abrupt transition between a phase of low level noise where the prediction is as good as in the absence of noise, and a phase of high level noise where the prediction becomes poor. In the phase of low and intermediate noise the RIA predicts considerably better than the PRT, which explains our recent findings in physiological and financial records.

CSOLNP: Numerical Optimization Engine for Solving Non-linearly Constrained Problems.

PubMed

Zahery, Mahsa; Maes, Hermine H; Neale, Michael C

2017-08-01

We introduce the optimizer CSOLNP, which is a C++ implementation of the R package RSOLNP (Ghalanos & Theussl, 2012, Rsolnp: General non-linear optimization using augmented Lagrange multiplier method. R package version, 1) alongside some improvements. CSOLNP solves non-linearly constrained optimization problems using a Sequential Quadratic Programming (SQP) algorithm. CSOLNP, NPSOL (a very popular implementation of SQP method in FORTRAN (Gill et al., 1986, User's guide for NPSOL (version 4.0): A Fortran package for nonlinear programming (No. SOL-86-2). Stanford, CA: Stanford University Systems Optimization Laboratory), and SLSQP (another SQP implementation available as part of the NLOPT collection (Johnson, 2014, The NLopt nonlinear-optimization package. Retrieved from http://ab-initio.mit.edu/nlopt)) are three optimizers available in OpenMx package. These optimizers are compared in terms of runtimes, final objective values, and memory consumption. A Monte Carlo analysis of the performance of the optimizers was performed on ordinal and continuous models with five variables and one or two factors. While the relative difference between the objective values is less than 0.5%, CSOLNP is in general faster than NPSOL and SLSQP for ordinal analysis. As for continuous data, none of the optimizers performs consistently faster than the others. In terms of memory usage, we used Valgrind's heap profiler tool, called Massif, on one-factor threshold models. CSOLNP and NPSOL consume the same amount of memory, while SLSQP uses 71 MB more memory than the other two optimizers.

6 DOF Nonlinear AUV Simulation Toolbox

DTIC Science & Technology

1997-01-01

is to supply a flexible 3D -simulation platform for motion visualization, in-lab debugging and testing of mission-specific strategies as well as those...Explorer are modular designed [Smith] in order to cut time and cost for vehicle recontlguration. A flexible 3D -simulation platform is desired to... 3D models. Current implemented modules include a nonlinear dynamic model for the OEX, shared memory and semaphore manager tools, shared memory monitor

Rapid solution of large-scale systems of equations

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.

1994-01-01

The analysis and design of complex aerospace structures requires the rapid solution of large systems of linear and nonlinear equations, eigenvalue extraction for buckling, vibration and flutter modes, structural optimization and design sensitivity calculation. Computers with multiple processors and vector capabilities can offer substantial computational advantages over traditional scalar computer for these analyses. These computers fall into two categories: shared memory computers and distributed memory computers. This presentation covers general-purpose, highly efficient algorithms for generation/assembly or element matrices, solution of systems of linear and nonlinear equations, eigenvalue and design sensitivity analysis and optimization. All algorithms are coded in FORTRAN for shared memory computers and many are adapted to distributed memory computers. The capability and numerical performance of these algorithms will be addressed.

Total recall in distributive associative memories

NASA Technical Reports Server (NTRS)

Danforth, Douglas G.

1991-01-01

Iterative error correction of asymptotically large associative memories is equivalent to a one-step learning rule. This rule is the inverse of the activation function of the memory. Spectral representations of nonlinear activation functions are used to obtain the inverse in closed form for Sparse Distributed Memory, Selected-Coordinate Design, and Radial Basis Functions.

A Formal Model of Capacity Limits in Working Memory

ERIC Educational Resources Information Center

Oberauer, Klaus; Kliegl, Reinhold

2006-01-01

A mathematical model of working-memory capacity limits is proposed on the key assumption of mutual interference between items in working memory. Interference is assumed to arise from overwriting of features shared by these items. The model was fit to time-accuracy data of memory-updating tasks from four experiments using nonlinear mixed effect…

Hybrid associative memory using an incoherent correlation system

NASA Astrophysics Data System (ADS)

Taniguchi, Masaki; Ichioka, Yoshiki; Matsuoka, Katsunori

1990-10-01

A hybrid heteroassociative memory is presented that uses an incoherent system in which two correlators and a nonlinear element form a nonlinear feedback system. This system can recall any pattern from an input pattern without cross-talk or ghosts by properly designing a pair of filters installed in the correlators. Experiments on a simple hybrid system were performed to ensure the operation of the system and to demonstrate the usefulness of this proposed system.

Realization of synaptic learning and memory functions in Y2O3 based memristive device fabricated by dual ion beam sputtering

NASA Astrophysics Data System (ADS)

Das, Mangal; Kumar, Amitesh; Singh, Rohit; Than Htay, Myo; Mukherjee, Shaibal

2018-02-01

Single synaptic device with inherent learning and memory functions is demonstrated based on a forming-free amorphous Y2O3 (yttria) memristor fabricated by dual ion beam sputtering system. Synaptic functions such as nonlinear transmission characteristics, long-term plasticity, short-term plasticity and ‘learning behavior (LB)’ are achieved using a single synaptic device based on cost-effective metal-insulator-semiconductor (MIS) structure. An ‘LB’ function is demonstrated, for the first time in the literature, for a yttria based memristor, which bears a resemblance to certain memory functions of biological systems. The realization of key synaptic functions in a cost-effective MIS structure would promote much cheaper synapse for artificial neural network.

Detection of weak signals in memory thermal baths.

PubMed

Jiménez-Aquino, J I; Velasco, R M; Romero-Bastida, M

2014-11-01

The nonlinear relaxation time and the statistics of the first passage time distribution in connection with the quasideterministic approach are used to detect weak signals in the decay process of the unstable state of a Brownian particle embedded in memory thermal baths. The study is performed in the overdamped approximation of a generalized Langevin equation characterized by an exponential decay in the friction memory kernel. A detection criterion for each time scale is studied: The first one is referred to as the receiver output, which is given as a function of the nonlinear relaxation time, and the second one is related to the statistics of the first passage time distribution.

Selector-free resistive switching memory cell based on BiFeO3 nano-island showing high resistance ratio and nonlinearity factor

PubMed Central

Jeon, Ji Hoon; Joo, Ho-Young; Kim, Young-Min; Lee, Duk Hyun; Kim, Jin-Soo; Kim, Yeon Soo; Choi, Taekjib; Park, Bae Ho

2016-01-01

Highly nonlinear bistable current-voltage (I–V) characteristics are necessary in order to realize high density resistive random access memory (ReRAM) devices that are compatible with cross-point stack structures. Up to now, such I–V characteristics have been achieved by introducing complex device structures consisting of selection elements (selectors) and memory elements which are connected in series. In this study, we report bipolar resistive switching (RS) behaviours of nano-crystalline BiFeO3 (BFO) nano-islands grown on Nb-doped SrTiO3 substrates, with large ON/OFF ratio of 4,420. In addition, the BFO nano-islands exhibit asymmetric I–V characteristics with high nonlinearity factor of 1,100 in a low resistance state. Such selector-free RS behaviours are enabled by the mosaic structures and pinned downward ferroelectric polarization in the BFO nano-islands. The high resistance ratio and nonlinearity factor suggest that our BFO nano-islands can be extended to an N × N array of N = 3,740 corresponding to ~107 bits. Therefore, our BFO nano-island showing both high resistance ratio and nonlinearity factor offers a simple and promising building block of high density ReRAM. PMID:27001415

WARP3D-Release 10.8: Dynamic Nonlinear Analysis of Solids using a Preconditioned Conjugate Gradient Software Architecture

NASA Technical Reports Server (NTRS)

Koppenhoefer, Kyle C.; Gullerud, Arne S.; Ruggieri, Claudio; Dodds, Robert H., Jr.; Healy, Brian E.

1998-01-01

This report describes theoretical background material and commands necessary to use the WARP3D finite element code. WARP3D is under continuing development as a research code for the solution of very large-scale, 3-D solid models subjected to static and dynamic loads. Specific features in the code oriented toward the investigation of ductile fracture in metals include a robust finite strain formulation, a general J-integral computation facility (with inertia, face loading), an element extinction facility to model crack growth, nonlinear material models including viscoplastic effects, and the Gurson-Tver-gaard dilatant plasticity model for void growth. The nonlinear, dynamic equilibrium equations are solved using an incremental-iterative, implicit formulation with full Newton iterations to eliminate residual nodal forces. The history integration of the nonlinear equations of motion is accomplished with Newmarks Beta method. A central feature of WARP3D involves the use of a linear-preconditioned conjugate gradient (LPCG) solver implemented in an element-by-element format to replace a conventional direct linear equation solver. This software architecture dramatically reduces both the memory requirements and CPU time for very large, nonlinear solid models since formation of the assembled (dynamic) stiffness matrix is avoided. Analyses thus exhibit the numerical stability for large time (load) steps provided by the implicit formulation coupled with the low memory requirements characteristic of an explicit code. In addition to the much lower memory requirements of the LPCG solver, the CPU time required for solution of the linear equations during each Newton iteration is generally one-half or less of the CPU time required for a traditional direct solver. All other computational aspects of the code (element stiffnesses, element strains, stress updating, element internal forces) are implemented in the element-by- element, blocked architecture. This greatly improves vectorization of the code on uni-processor hardware and enables straightforward parallel-vector processing of element blocks on multi-processor hardware.

Agent based reasoning for the non-linear stochastic models of long-range memory

NASA Astrophysics Data System (ADS)

Kononovicius, A.; Gontis, V.

2012-02-01

We extend Kirman's model by introducing variable event time scale. The proposed flexible time scale is equivalent to the variable trading activity observed in financial markets. Stochastic version of the extended Kirman's agent based model is compared to the non-linear stochastic models of long-range memory in financial markets. The agent based model providing matching macroscopic description serves as a microscopic reasoning of the earlier proposed stochastic model exhibiting power law statistics.

Grain size effects on stability of nonlinear vibration with nanocrystalline NiTi shape memory alloy

NASA Astrophysics Data System (ADS)

Xia, Minglu; Sun, Qingping

2017-10-01

Grain size effects on stability of thermomechanical responses for a nonlinear torsional vibration system with nanocrystalline superelastic NiTi bar are investigated in the frequency and amplitude domains. NiTi bars with average grain size from 10 nm to 100 nm are fabricated through cold-rolling and subsequent annealing. Thermomechanical responses of the NiTi bar as a softening nonlinear damping spring in the torsional vibration system are obtained by synchronised acquisition of rotational angle and temperature under external sinusoidal excitation. It is shown that nonlinearity and damping capacity of the NiTi bar decrease as average grain size of the material is reduced below 100 nm. Therefore jump phenomena of thermomechanical responses become less significant or even vanish and the vibration system becomes more stable. The work in this paper provides a solid experimental base for manipulating the undesired jump phenomena of thermomechanical responses and stabilising the mechanical vibration system through grain refinement of NiTi SMA.

Nano-cone resistive memory for ultralow power operation.

PubMed

Kim, Sungjun; Jung, Sunghun; Kim, Min-Hwi; Kim, Tae-Hyeon; Bang, Suhyun; Cho, Seongjae; Park, Byung-Gook

2017-03-24

SiN x -based nano-structure resistive memory is fabricated by fully silicon CMOS compatible process integration including particularly designed anisotropic etching for the construction of a nano-cone silicon bottom electrode (BE). Bipolar resistive switching characteristics have significantly reduced switching current and voltage and are demonstrated in a nano-cone BE structure, as compared with those in a flat BE one. We have verified by systematic device simulations that the main cause of reduction in the performance parameters is the high electric field being more effectively concentrated at the tip of the cone-shaped BE. The greatly improved nonlinearity of the nano-cone resistive memory cell will be beneficial in the ultra-high-density crossbar array.

General stability of memory-type thermoelastic Timoshenko beam acting on shear force

NASA Astrophysics Data System (ADS)

Apalara, Tijani A.

2018-03-01

In this paper, we consider a linear thermoelastic Timoshenko system with memory effects where the thermoelastic coupling is acting on shear force under Neumann-Dirichlet-Dirichlet boundary conditions. The same system with fully Dirichlet boundary conditions was considered by Messaoudi and Fareh (Nonlinear Anal TMA 74(18):6895-6906, 2011, Acta Math Sci 33(1):23-40, 2013), but they obtained a general stability result which depends on the speeds of wave propagation. In our case, we obtained a general stability result irrespective of the wave speeds of the system.

A comparison of several methods of solving nonlinear regression groundwater flow problems

USGS Publications Warehouse

Cooley, Richard L.

1985-01-01

Computational efficiency and computer memory requirements for four methods of minimizing functions were compared for four test nonlinear-regression steady state groundwater flow problems. The fastest methods were the Marquardt and quasi-linearization methods, which required almost identical computer times and numbers of iterations; the next fastest was the quasi-Newton method, and last was the Fletcher-Reeves method, which did not converge in 100 iterations for two of the problems. The fastest method per iteration was the Fletcher-Reeves method, and this was followed closely by the quasi-Newton method. The Marquardt and quasi-linearization methods were slower. For all four methods the speed per iteration was directly related to the number of parameters in the model. However, this effect was much more pronounced for the Marquardt and quasi-linearization methods than for the other two. Hence the quasi-Newton (and perhaps Fletcher-Reeves) method might be more efficient than either the Marquardt or quasi-linearization methods if the number of parameters in a particular model were large, although this remains to be proven. The Marquardt method required somewhat less central memory than the quasi-linearization metilod for three of the four problems. For all four problems the quasi-Newton method required roughly two thirds to three quarters of the memory required by the Marquardt method, and the Fletcher-Reeves method required slightly less memory than the quasi-Newton method. Memory requirements were not excessive for any of the four methods.

Emergence, evolution, and control of multistability in a hybrid topological quantum/classical system.

PubMed

Wang, Guanglei; Xu, Hongya; Lai, Ying-Cheng

2018-03-01

We present a novel class of nonlinear dynamical systems-a hybrid of relativistic quantum and classical systems and demonstrate that multistability is ubiquitous. A representative setting is coupled systems of a topological insulator and an insulating ferromagnet, where the former possesses an insulating bulk with topologically protected, dissipationless, and conducting surface electronic states governed by the relativistic quantum Dirac Hamiltonian and the latter is described by the nonlinear classical evolution of its magnetization vector. The interactions between the two are essentially the spin transfer torque from the topological insulator to the ferromagnet and the local proximity induced exchange coupling in the opposite direction. The hybrid system exhibits a rich variety of nonlinear dynamical phenomena besides multistability such as bifurcations, chaos, and phase synchronization. The degree of multistability can be controlled by an external voltage. In the case of two coexisting states, the system is effectively binary, opening a door to exploitation for developing spintronic memory devices. Because of the dissipationless and spin-momentum locking nature of the surface currents of the topological insulator, little power is needed for generating a significant current, making the system appealing for potential applications in next generation of low power memory devices.

Emergence, evolution, and control of multistability in a hybrid topological quantum/classical system

NASA Astrophysics Data System (ADS)

Wang, Guanglei; Xu, Hongya; Lai, Ying-Cheng

2018-03-01

We present a novel class of nonlinear dynamical systems—a hybrid of relativistic quantum and classical systems and demonstrate that multistability is ubiquitous. A representative setting is coupled systems of a topological insulator and an insulating ferromagnet, where the former possesses an insulating bulk with topologically protected, dissipationless, and conducting surface electronic states governed by the relativistic quantum Dirac Hamiltonian and the latter is described by the nonlinear classical evolution of its magnetization vector. The interactions between the two are essentially the spin transfer torque from the topological insulator to the ferromagnet and the local proximity induced exchange coupling in the opposite direction. The hybrid system exhibits a rich variety of nonlinear dynamical phenomena besides multistability such as bifurcations, chaos, and phase synchronization. The degree of multistability can be controlled by an external voltage. In the case of two coexisting states, the system is effectively binary, opening a door to exploitation for developing spintronic memory devices. Because of the dissipationless and spin-momentum locking nature of the surface currents of the topological insulator, little power is needed for generating a significant current, making the system appealing for potential applications in next generation of low power memory devices.

Traveling wavefront solutions to nonlinear reaction-diffusion-convection equations

NASA Astrophysics Data System (ADS)

Indekeu, Joseph O.; Smets, Ruben

2017-08-01

Physically motivated modified Fisher equations are studied in which nonlinear convection and nonlinear diffusion is allowed for besides the usual growth and spread of a population. It is pointed out that in a large variety of cases separable functions in the form of exponentially decaying sharp wavefronts solve the differential equation exactly provided a co-moving point source or sink is active at the wavefront. The velocity dispersion and front steepness may differ from those of some previously studied exact smooth traveling wave solutions. For an extension of the reaction-diffusion-convection equation, featuring a memory effect in the form of a maturity delay for growth and spread, also smooth exact wavefront solutions are obtained. The stability of the solutions is verified analytically and numerically.

An ensemble Kalman filter for statistical estimation of physics constrained nonlinear regression models

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

Harlim, John, E-mail: jharlim@psu.edu; Mahdi, Adam, E-mail: amahdi@ncsu.edu; Majda, Andrew J., E-mail: jonjon@cims.nyu.edu

2014-01-15

A central issue in contemporary science is the development of nonlinear data driven statistical–dynamical models for time series of noisy partial observations from nature or a complex model. It has been established recently that ad-hoc quadratic multi-level regression models can have finite-time blow-up of statistical solutions and/or pathological behavior of their invariant measure. Recently, a new class of physics constrained nonlinear regression models were developed to ameliorate this pathological behavior. Here a new finite ensemble Kalman filtering algorithm is developed for estimating the state, the linear and nonlinear model coefficients, the model and the observation noise covariances from available partialmore » noisy observations of the state. Several stringent tests and applications of the method are developed here. In the most complex application, the perfect model has 57 degrees of freedom involving a zonal (east–west) jet, two topographic Rossby waves, and 54 nonlinearly interacting Rossby waves; the perfect model has significant non-Gaussian statistics in the zonal jet with blocked and unblocked regimes and a non-Gaussian skewed distribution due to interaction with the other 56 modes. We only observe the zonal jet contaminated by noise and apply the ensemble filter algorithm for estimation. Numerically, we find that a three dimensional nonlinear stochastic model with one level of memory mimics the statistical effect of the other 56 modes on the zonal jet in an accurate fashion, including the skew non-Gaussian distribution and autocorrelation decay. On the other hand, a similar stochastic model with zero memory levels fails to capture the crucial non-Gaussian behavior of the zonal jet from the perfect 57-mode model.« less

Ferroelectric polarization induces electronic nonlinearity in ion-doped conducting polymers

PubMed Central

Fabiano, Simone; Sani, Negar; Kawahara, Jun; Kergoat, Loïg; Nissa, Josefin; Engquist, Isak; Crispin, Xavier; Berggren, Magnus

2017-01-01

Poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) is an organic mixed ion-electron conducting polymer. The PEDOT phase transports holes and is redox-active, whereas the PSS phase transports ions. When PEDOT is redox-switched between its semiconducting and conducting state, the electronic and optical properties of its bulk are controlled. Therefore, it is appealing to use this transition in electrochemical devices and to integrate those into large-scale circuits, such as display or memory matrices. Addressability and memory functionality of individual devices, within these matrices, are typically achieved by nonlinear current-voltage characteristics and bistability—functions that can potentially be offered by the semiconductor-conductor transition of redox polymers. However, low conductivity of the semiconducting state and poor bistability, due to self-discharge, make fast operation and memory retention impossible. We report that a ferroelectric polymer layer, coated along the counter electrode, can control the redox state of PEDOT. The polarization switching characteristics of the ferroelectric polymer, which take place as the coercive field is overcome, introduce desired nonlinearity and bistability in devices that maintain PEDOT in its highly conducting and fast-operating regime. Memory functionality and addressability are demonstrated in ferro-electrochromic display pixels and ferro-electrochemical transistors. PMID:28695197

The Longitudinal Trajectory of Default Mode Network Connectivity in Healthy Older Adults Varies As a Function of Age and Is Associated with Changes in Episodic Memory and Processing Speed.

PubMed

Staffaroni, Adam M; Brown, Jesse A; Casaletto, Kaitlin B; Elahi, Fanny M; Deng, Jersey; Neuhaus, John; Cobigo, Yann; Mumford, Paige S; Walters, Samantha; Saloner, Rowan; Karydas, Anna; Coppola, Giovanni; Rosen, Howie J; Miller, Bruce L; Seeley, William W; Kramer, Joel H

2018-03-14

The default mode network (DMN) supports memory functioning and may be sensitive to preclinical Alzheimer's pathology. Little is known, however, about the longitudinal trajectory of this network's intrinsic functional connectivity (FC). In this study, we evaluated longitudinal FC in 111 cognitively normal older human adults (ages 49-87, 46 women/65 men), 92 of whom had at least three task-free fMRI scans ( n = 353 total scans). Whole-brain FC and three DMN subnetworks were assessed: (1) within-DMN, (2) between anterior and posterior DMN, and (3) between medial temporal lobe network and posterior DMN. Linear mixed-effects models demonstrated significant baseline age × time interactions, indicating a nonlinear trajectory. There was a trend toward increasing FC between ages 50-66 and significantly accelerating declines after age 74. A similar interaction was observed for whole-brain FC. APOE status did not predict baseline connectivity or change in connectivity. After adjusting for network volume, changes in within-DMN connectivity were specifically associated with changes in episodic memory and processing speed but not working memory or executive functions. The relationship with processing speed was attenuated after covarying for white matter hyperintensities (WMH) and whole-brain FC, whereas within-DMN connectivity remained associated with memory above and beyond WMH and whole-brain FC. Whole-brain and DMN FC exhibit a nonlinear trajectory, with more rapid declines in older age and possibly increases in connectivity early in the aging process. Within-DMN connectivity is a marker of episodic memory performance even among cognitively healthy older adults. SIGNIFICANCE STATEMENT Default mode network and whole-brain connectivity, measured using task-free fMRI, changed nonlinearly as a function of age, with some suggestion of early increases in connectivity. For the first time, longitudinal changes in DMN connectivity were shown to correlate with changes in episodic memory, whereas volume changes in relevant brain regions did not. This relationship was not accounted for by white matter hyperintensities or mean whole-brain connectivity. Functional connectivity may be an early biomarker of changes in aging but should be used with caution given its nonmonotonic nature, which could complicate interpretation. Future studies investigating longitudinal network changes should consider whole-brain changes in connectivity. Copyright © 2018 the authors 0270-6474/18/382810-09$15.00/0.

Influence of mechanically-induced dilatation on the shape memory behavior of amorphous polymers at large deformation

NASA Astrophysics Data System (ADS)

Hanzon, Drew W.; Lu, Haibao; Yakacki, Christopher M.; Yu, Kai

2018-01-01

In this study, we explore the influence of mechanically-induced dilatation on the thermomechanical and shape memory behavior of amorphous shape memory polymers (SMPs) at large deformation. The uniaxial tension, glass transition, stress relaxation and free recovery behaviors are examined with different strain levels (up to 340% engineering strain). A multi-branched constitutive model that incorporates dilatational effects on the polymer relaxation time is established and applied to assist in discussions and understand the nonlinear viscoelastic behaviors of SMPs. It is shown that the volumetric dilatation results in an SMP network with lower viscosity, faster relaxation, and lower Tg. The influence of the dilatational effect on the thermomechanical behaviors is significant when the polymers are subject to large deformation or in a high viscosity state. The dilation also increases the free recovery rate of SMP at a given recovery temperature. Even though the tested SMPs are far beyond their linear viscoelastic region when a large programming strain is applied, the free recovery behavior still follows the time-temperature superposition (TTSP) if the dilatational effect is considered during the transformation of time scales; however, if the programming strain is different, TTSP fails in predicting the recovery behavior of SMPs because the network has different entropy state and driving force during shape recovery. Since most soft active polymers are subject to large deformation in practice, this study provides a theoretical basis to better understand their nonlinear viscoelastic behaviors, and optimize their performance in engineering applications.

Persistence and long-term memories of daily maximum and minimum temperatures in southern South America

NASA Astrophysics Data System (ADS)

Naumann, Gustavo; Vargas, Walter M.; Minetti, Juan L.

2011-10-01

The persistence and long-term memories in daily maximum and minimum temperature series during the instrumental period in southern South America were analysed. Here, we found a markedly seasonal pattern both for short- and long-term memories that can lead to enhanced predictability on intraseasonal timescales. In addition, well-defined spatial patterns of these properties were found in the region. Throughout the entire region, the strongest dependence was observed in autumn and early winter. In the Patagonia region only, the temperatures exhibited more memory during the spring. In general, these elements indicate that nonlinear interactions exist between the annual cycles of temperature and its anomalies. Knowledge of the spatiotemporal behaviour of these long-term memories can be used in the building of stochastic models that only use persistence. It is possible to propose two objective forecast models based on linear interactions associated with persistence and one that allows for the use of information from nonlinear interactions that are manifested in the form of forerunners.

A waveguide frequency converter connecting rubidium-based quantum memories to the telecom C-band.

PubMed

Albrecht, Boris; Farrera, Pau; Fernandez-Gonzalvo, Xavier; Cristiani, Matteo; de Riedmatten, Hugues

2014-02-27

Coherently converting the frequency and temporal waveform of single and entangled photons will be crucial to interconnect the various elements of future quantum information networks. Of particular importance is the quantum frequency conversion of photons emitted by material systems able to store quantum information, so-called quantum memories. There have been significant efforts to implement quantum frequency conversion using nonlinear crystals, with non-classical light from broadband photon-pair sources and solid-state emitters. However, solid state quantum frequency conversion has not yet been achieved with long-lived optical quantum memories. Here we demonstrate an ultra-low-noise solid state photonic quantum interface suitable for connecting quantum memories based on atomic ensembles to the telecommunication fibre network. The interface is based on an integrated-waveguide nonlinear device. We convert heralded single photons at 780 nm from a rubidium-based quantum memory to the telecommunication wavelength of 1,552 nm, showing significant non-classical correlations between the converted photon and the heralding signal.

Complex magnetic behaviour and evidence of a superspin glass state in the binary intermetallic compound Er5Pd2

NASA Astrophysics Data System (ADS)

Sharma, Mohit K.; Yadav, Kavita; Mukherjee, K.

2018-05-01

The binary intermetallic compound Er5Pd2 has been investigated using dc and ac magnetic susceptibilities, magnetic memory effect, isothermal magnetization, non-linear dc susceptibility, heat capacity and magnetocaloric effect studies. Interestingly, even though the compound does not show geometrical frustration it undergoes glassy magnetic phase transition below 17.2 K. Investigation of dc magnetization and heat capacity data divulged absence of long-ranged magnetic ordering. Through the magnetic memory effect, time dependent magnetization and ac susceptibility studies it was revealed that the compound undergoes glass-like freezing below 17.2 K. Analysis of frequency dependence of this transition temperature through scaling and Arrhenius law; along with the Mydosh parameter indicate, that the dynamics in Er5Pd2 are due to the presence of strongly interacting superspins rather than individual spins. This phase transition was further investigated by non-linear dc susceptibility and was characterized by static critical exponents γ and δ. Our results indicate that this compound shows the signature of superspin glass at low temperature. Additionally, both conventional and inverse magnetocaloric effect was observed with a large value of magnetic entropy change and relative cooling power. Our results suggest that Er5Pd2 can be classified as a superspin glass system with large magnetocaloric effect.

A new analysis of the Fornberg-Whitham equation pertaining to a fractional derivative with Mittag-Leffler-type kernel

NASA Astrophysics Data System (ADS)

Kumar, Devendra; Singh, Jagdev; Baleanu, Dumitru

2018-02-01

The mathematical model of breaking of non-linear dispersive water waves with memory effect is very important in mathematical physics. In the present article, we examine a novel fractional extension of the non-linear Fornberg-Whitham equation occurring in wave breaking. We consider the most recent theory of differentiation involving the non-singular kernel based on the extended Mittag-Leffler-type function to modify the Fornberg-Whitham equation. We examine the existence of the solution of the non-linear Fornberg-Whitham equation of fractional order. Further, we show the uniqueness of the solution. We obtain the numerical solution of the new arbitrary order model of the non-linear Fornberg-Whitham equation with the aid of the Laplace decomposition technique. The numerical outcomes are displayed in the form of graphs and tables. The results indicate that the Laplace decomposition algorithm is a very user-friendly and reliable scheme for handling such type of non-linear problems of fractional order.

Numerical solution methods for viscoelastic orthotropic materials

NASA Technical Reports Server (NTRS)

Gramoll, K. C.; Dillard, D. A.; Brinson, H. F.

1988-01-01

Numerical solution methods for viscoelastic orthotropic materials, specifically fiber reinforced composite materials, are examined. The methods include classical lamination theory using time increments, direction solution of the Volterra Integral, Zienkiewicz's linear Prony series method, and a new method called Nonlinear Differential Equation Method (NDEM) which uses a nonlinear Prony series. The criteria used for comparison of the various methods include the stability of the solution technique, time step size stability, computer solution time length, and computer memory storage. The Volterra Integral allowed the implementation of higher order solution techniques but had difficulties solving singular and weakly singular compliance function. The Zienkiewicz solution technique, which requires the viscoelastic response to be modeled by a Prony series, works well for linear viscoelastic isotropic materials and small time steps. The new method, NDEM, uses a modified Prony series which allows nonlinear stress effects to be included and can be used with orthotropic nonlinear viscoelastic materials. The NDEM technique is shown to be accurate and stable for both linear and nonlinear conditions with minimal computer time.

A Nonlinear Model for Hippocampal Cognitive Prosthesis: Memory Facilitation by Hippocampal Ensemble Stimulation

PubMed Central

Hampson, Robert E.; Song, Dong; Chan, Rosa H.M.; Sweatt, Andrew J.; Riley, Mitchell R.; Gerhardt, Gregory A.; Shin, Dae C.; Marmarelis, Vasilis Z.; Berger, Theodore W.; Deadwyler, Samuel A.

2012-01-01

Collaborative investigations have characterized how multineuron hippocampal ensembles encode memory necessary for subsequent successful performance by rodents in a delayed nonmatch to sample (DNMS) task and utilized that information to provide the basis for a memory prosthesis to enhance performance. By employing a unique nonlinear dynamic multi-input/multi-output (MIMO) model, developed and adapted to hippocampal neural ensemble firing patterns derived from simultaneous recorded CA1 and CA3 activity, it was possible to extract information encoded in the sample phase necessary for successful performance in the nonmatch phase of the task. The extension of this MIMO model to online delivery of electrical stimulation delivered to the same recording loci that mimicked successful CA1 firing patterns, provided the means to increase levels of performance on a trial-by-trial basis. Inclusion of several control procedures provides evidence for the specificity of effective MIMO model generated patterns of electrical stimulation. Increased utility of the MIMO model as a prosthesis device was exhibited by the demonstration of cumulative increases in DNMS task performance with repeated MIMO stimulation over many sessions on both stimulation and nonstimulation trials, suggesting overall system modification with continued exposure. Results reported here are compatible with and extend prior demonstrations and further support the candidacy of the MIMO model as an effective cortical prosthesis. PMID:22438334

Effect of in vitro degradation of poly(D,L-lactide)/beta-tricalcium composite on its shape-memory properties.

PubMed

Zheng, Xiaotong; Zhou, Shaobing; Yu, Xiongjun; Li, Xiaohong; Feng, Bo; Qu, Shuxin; Weng, Jie

2008-07-01

The in vitro degradation characteristic and shape-memory properties of poly(D,L-lactide) (PDLLA)/beta-tricalcium phosphate (beta-TCP) composites were investigated because of their wide application in biomedical fields. In this article, PDLLA and crystalline beta-TCP were compounded and interesting shape-memory behaviors of the composite were first investigated. Then, in vitro degradation of the PDLLA/beta-TCP composites with weight ratios of 1:1, 2:1, and 3:1 was performed in phosphate buffer saline solution (PBS) (154 mM, pH 7.4) at 37 degrees C. The effect of in vitro degradation time for PDLLA/beta-TCP composites on shape-memory properties was studied by scanning electron microscopy, differential scanning calorimetry, gel permeation chromatography, X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The changes of structural morphology, glass transition temperature (T(g)), molecular weight, and weight loss of composites matrix and pH change of degradation medium indicated that shape-memory effects at different degradation time were nonlinearly influenced because of the breaking down of polymer chain and the formation of degradation products. Furthermore, the results from XRD and FTIR implied that the degradation products, for example, hydroxyapatite (HA), calcium hydrogen phosphate (CaHPO(4)), and calcium pyrophosphate (Ca(2)P(2)O(7)) phases also had some effects on shape-memory properties during the degradation. 2007 Wiley Periodicals, Inc.

Transfer Functions Via Laplace- And Fourier-Borel Transforms

NASA Technical Reports Server (NTRS)

Can, Sumer; Unal, Aynur

1991-01-01

Approach to solution of nonlinear ordinary differential equations involves transfer functions based on recently-introduced Laplace-Borel and Fourier-Borel transforms. Main theorem gives transform of response of nonlinear system as Cauchy product of transfer function and transform of input function of system, together with memory effects. Used to determine responses of electrical circuits containing variable inductances or resistances. Also possibility of doing all noncommutative algebra on computers in such symbolic programming languages as Macsyma, Reduce, PL1, or Lisp. Process of solution organized and possibly simplified by algebraic manipulations reducing integrals in solutions to known or tabulated forms.

Can observations look back to the beginning of inflation?

NASA Astrophysics Data System (ADS)

Wetterich, C.

2016-03-01

The cosmic microwave background can measure the inflaton potential only if inflation lasts sufficiently long before the time of horizon crossing of observable fluctuations, such that non-linear effects in the time evolution of Green's functions lead to a loss of memory of initial conditions for the ultraviolet tail of the spectrum. Within a derivative expansion of the quantum effective action for an interacting scalar field we discuss the most general solution for the correlation function, including arbitrary pure and mixed quantum states. In this approximation no loss of memory occurs - cosmic microwave observations see the initial spectrum at the beginning of inflation, processed only mildly by the scale-violating effects at horizon crossing induced by the inflaton potential.

Nonlinear degradation of a visible-light communication link: A Volterra-series approach

NASA Astrophysics Data System (ADS)

Kamalakis, Thomas; Dede, Georgia

2018-06-01

Visible light communications can be used to provide illumination and data communication at the same time. In this paper, a reverse-engineering approach is presented for assessing the impact of nonlinear signal distortion in visible light communication links. The approach is based on the Volterra series expansion and has the advantage of accurately accounting for memory effects in contrast to the static nonlinear models that are popular in the literature. Volterra kernels describe the end-to-end system response and can be inferred from measurements. Consequently, this approach does not rely on any particular physical models and assumptions regarding the individual link components. We provide the necessary framework for estimating the nonlinear distortion on the symbol estimates of a discrete multitone modulated link. Various design aspects such as waveform clipping and predistortion are also incorporated in the analysis. Using this framework, the nonlinear signal-to-interference is calculated for the system at hand. It is shown that at high signal amplitudes, the nonlinear signal-to-interference can be less than 25 dB.

Nonlinear machine learning and design of reconfigurable digital colloids.

PubMed

Long, Andrew W; Phillips, Carolyn L; Jankowksi, Eric; Ferguson, Andrew L

2016-09-14

Digital colloids, a cluster of freely rotating "halo" particles tethered to the surface of a central particle, were recently proposed as ultra-high density memory elements for information storage. Rational design of these digital colloids for memory storage applications requires a quantitative understanding of the thermodynamic and kinetic stability of the configurational states within which information is stored. We apply nonlinear machine learning to Brownian dynamics simulations of these digital colloids to extract the low-dimensional intrinsic manifold governing digital colloid morphology, thermodynamics, and kinetics. By modulating the relative size ratio between halo particles and central particles, we investigate the size-dependent configurational stability and transition kinetics for the 2-state tetrahedral (N = 4) and 30-state octahedral (N = 6) digital colloids. We demonstrate the use of this framework to guide the rational design of a memory storage element to hold a block of text that trades off the competing design criteria of memory addressability and volatility.

Nonlinear space charge dynamics in mixed ionic-electronic conductors: Resistive switching and ferroelectric-like hysteresis of electromechanical response

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

Morozovska, Anna N.; Morozovsky, Nicholas V.; Eliseev, Eugene A.

We performed self-consistent modelling of nonlinear electrotransport and electromechanical response of thin films of mixed ionic-electronic conductors (MIEC) allowing for steric effects of mobile charged defects (ions, protons, or vacancies), electron degeneration, and Vegard stresses. We establish correlations between the features of the nonlinear space-charge dynamics, current-voltage, and bending-voltage curves for different types of the film electrodes. A pronounced ferroelectric-like hysteresis of the bending-voltage loops and current maxima on the double hysteresis current-voltage loops appear for the electron-transport electrodes. The double hysteresis loop with pronounced humps indicates a memristor-type resistive switching. The switching occurs due to the strong nonlinear couplingmore » between the electronic and ionic subsystems. A sharp meta-stable maximum of the electron density appears near one open electrode and moves to another one during the periodic change of applied voltage. Our results can explain the nonlinear nature and correlation of electrical and mechanical memory effects in thin MIEC films. The analytical expression proving that the electrically induced bending of MIEC films can be detected by interferometric methods is derived.« less

Seismic waveform inversion best practices: regional, global and exploration test cases

NASA Astrophysics Data System (ADS)

Modrak, Ryan; Tromp, Jeroen

2016-09-01

Reaching the global minimum of a waveform misfit function requires careful choices about the nonlinear optimization, preconditioning and regularization methods underlying an inversion. Because waveform inversion problems are susceptible to erratic convergence associated with strong nonlinearity, one or two test cases are not enough to reliably inform such decisions. We identify best practices, instead, using four seismic near-surface problems, one regional problem and two global problems. To make meaningful quantitative comparisons between methods, we carry out hundreds of inversions, varying one aspect of the implementation at a time. Comparing nonlinear optimization algorithms, we find that limited-memory BFGS provides computational savings over nonlinear conjugate gradient methods in a wide range of test cases. Comparing preconditioners, we show that a new diagonal scaling derived from the adjoint of the forward operator provides better performance than two conventional preconditioning schemes. Comparing regularization strategies, we find that projection, convolution, Tikhonov regularization and total variation regularization are effective in different contexts. Besides questions of one strategy or another, reliability and efficiency in waveform inversion depend on close numerical attention and care. Implementation details involving the line search and restart conditions have a strong effect on computational cost, regardless of the chosen nonlinear optimization algorithm.

Optoelectronic associative memory

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin (Inventor)

1993-01-01

An associative optical memory including an input spatial light modulator (SLM) in the form of an edge enhanced liquid crystal light valve (LCLV) and a pair of memory SLM's in the form of liquid crystal televisions (LCTV's) forms a matrix array of an input image which is cross correlated with a matrix array of stored images. The correlation product is detected and nonlinearly amplified to illuminate a replica of the stored image array to select the stored image correlating with the input image. The LCLV is edge enhanced by reducing the bias frequency and voltage and rotating its orientation. The edge enhancement and nonlinearity of the photodetection improves the orthogonality of the stored image. The illumination of the replicate stored image provides a clean stored image, uncontaminated by the image comparison process.

Modeling the action-potential-sensitive nonlinear-optical response of myelinated nerve fibers and short-term memory

NASA Astrophysics Data System (ADS)

Shneider, M. N.; Voronin, A. A.; Zheltikov, A. M.

2011-11-01

The Goldman-Albus treatment of the action-potential dynamics is combined with a phenomenological description of molecular hyperpolarizabilities into a closed-form model of the action-potential-sensitive second-harmonic response of myelinated nerve fibers with nodes of Ranvier. This response is shown to be sensitive to nerve demyelination, thus enabling an optical diagnosis of various demyelinating diseases, including multiple sclerosis. The model is applied to examine the nonlinear-optical response of a three-neuron reverberating circuit—the basic element of short-term memory.

NDRAM: nonlinear dynamic recurrent associative memory for learning bipolar and nonbipolar correlated patterns.

PubMed

Chartier, Sylvain; Proulx, Robert

2005-11-01

This paper presents a new unsupervised attractor neural network, which, contrary to optimal linear associative memory models, is able to develop nonbipolar attractors as well as bipolar attractors. Moreover, the model is able to develop less spurious attractors and has a better recall performance under random noise than any other Hopfield type neural network. Those performances are obtained by a simple Hebbian/anti-Hebbian online learning rule that directly incorporates feedback from a specific nonlinear transmission rule. Several computer simulations show the model's distinguishing properties.

Entanglement distillation for quantum communication network with atomic-ensemble memories.

PubMed

Li, Tao; Yang, Guo-Jian; Deng, Fu-Guo

2014-10-06

Atomic ensembles are effective memory nodes for quantum communication network due to the long coherence time and the collective enhancement effect for the nonlinear interaction between an ensemble and a photon. Here we investigate the possibility of achieving the entanglement distillation for nonlocal atomic ensembles by the input-output process of a single photon as a result of cavity quantum electrodynamics. We give an optimal entanglement concentration protocol (ECP) for two-atomic-ensemble systems in a partially entangled pure state with known parameters and an efficient ECP for the systems in an unknown partially entangled pure state with a nondestructive parity-check detector (PCD). For the systems in a mixed entangled state, we introduce an entanglement purification protocol with PCDs. These entanglement distillation protocols have high fidelity and efficiency with current experimental techniques, and they are useful for quantum communication network with atomic-ensemble memories.

Spurious cross-frequency amplitude-amplitude coupling in nonstationary, nonlinear signals

NASA Astrophysics Data System (ADS)

Yeh, Chien-Hung; Lo, Men-Tzung; Hu, Kun

2016-07-01

Recent studies of brain activities show that cross-frequency coupling (CFC) plays an important role in memory and learning. Many measures have been proposed to investigate the CFC phenomenon, including the correlation between the amplitude envelopes of two brain waves at different frequencies - cross-frequency amplitude-amplitude coupling (AAC). In this short communication, we describe how nonstationary, nonlinear oscillatory signals may produce spurious cross-frequency AAC. Utilizing the empirical mode decomposition, we also propose a new method for assessment of AAC that can potentially reduce the effects of nonlinearity and nonstationarity and, thus, help to avoid the detection of artificial AACs. We compare the performances of this new method and the traditional Fourier-based AAC method. We also discuss the strategies to identify potential spurious AACs.

When high working memory capacity is and is not beneficial for predicting nonlinear processes.

PubMed

Fischer, Helen; Holt, Daniel V

2017-04-01

Predicting the development of dynamic processes is vital in many areas of life. Previous findings are inconclusive as to whether higher working memory capacity (WMC) is always associated with using more accurate prediction strategies, or whether higher WMC can also be associated with using overly complex strategies that do not improve accuracy. In this study, participants predicted a range of systematically varied nonlinear processes based on exponential functions where prediction accuracy could or could not be enhanced using well-calibrated rules. Results indicate that higher WMC participants seem to rely more on well-calibrated strategies, leading to more accurate predictions for processes with highly nonlinear trajectories in the prediction region. Predictions of lower WMC participants, in contrast, point toward an increased use of simple exemplar-based prediction strategies, which perform just as well as more complex strategies when the prediction region is approximately linear. These results imply that with respect to predicting dynamic processes, working memory capacity limits are not generally a strength or a weakness, but that this depends on the process to be predicted.

Quantum associative memory with linear and non-linear algorithms for the diagnosis of some tropical diseases.

PubMed

Tchapet Njafa, J-P; Nana Engo, S G

2018-01-01

This paper presents the QAMDiagnos, a model of Quantum Associative Memory (QAM) that can be a helpful tool for medical staff without experience or laboratory facilities, for the diagnosis of four tropical diseases (malaria, typhoid fever, yellow fever and dengue) which have several similar signs and symptoms. The memory can distinguish a single infection from a polyinfection. Our model is a combination of the improved versions of the original linear quantum retrieving algorithm proposed by Ventura and the non-linear quantum search algorithm of Abrams and Lloyd. From the given simulation results, it appears that the efficiency of recognition is good when particular signs and symptoms of a disease are inserted given that the linear algorithm is the main algorithm. The non-linear algorithm helps confirm or correct the diagnosis or give some advice to the medical staff for the treatment. So, our QAMDiagnos that has a friendly graphical user interface for desktop and smart-phone is a sensitive and a low-cost diagnostic tool that enables rapid and accurate diagnosis of four tropical diseases. Copyright © 2017 Elsevier Ltd. All rights reserved.

Electrically-controlled nonlinear switching and multi-level storage characteristics in WOx film-based memory cells

NASA Astrophysics Data System (ADS)

Duan, W. J.; Wang, J. B.; Zhong, X. L.

2018-05-01

Resistive switching random access memory (RRAM) is considered as a promising candidate for the next generation memory due to its scalability, high integration density and non-volatile storage characteristics. Here, the multiple electrical characteristics in Pt/WOx/Pt cells are investigated. Both of the nonlinear switching and multi-level storage can be achieved by setting different compliance current in the same cell. The correlations among the current, time and temperature are analyzed by using contours and 3D surfaces. The switching mechanism is explained in terms of the formation and rupture of conductive filament which is related to oxygen vacancies. The experimental results show that the non-stoichiometric WOx film-based device offers a feasible way for the applications of oxide-based RRAMs.

Programmable, reversible and repeatable wrinkling of shape memory polymer thin films on elastomeric substrates for smart adhesion.

PubMed

Wang, Yu; Xiao, Jianliang

2017-08-09

Programmable, reversible and repeatable wrinkling of shape memory polymer (SMP) thin films on elastomeric polydimethylsiloxane (PDMS) substrates is realized, by utilizing the heat responsive shape memory effect of SMPs. The dependencies of wrinkle wavelength and amplitude on program strain and SMP film thickness are shown to agree with the established nonlinear buckling theory. The wrinkling is reversible, as the wrinkled SMP thin film can be recovered to the flat state by heating up the bilayer system. The programming cycle between wrinkle and flat is repeatable, and different program strains can be used in different programming cycles to induce different surface morphologies. Enabled by the programmable, reversible and repeatable SMP film wrinkling on PDMS, smart, programmable surface adhesion with large tuning range is demonstrated.

Optimal sixteenth order convergent method based on quasi-Hermite interpolation for computing roots.

PubMed

Zafar, Fiza; Hussain, Nawab; Fatimah, Zirwah; Kharal, Athar

2014-01-01

We have given a four-step, multipoint iterative method without memory for solving nonlinear equations. The method is constructed by using quasi-Hermite interpolation and has order of convergence sixteen. As this method requires four function evaluations and one derivative evaluation at each step, it is optimal in the sense of the Kung and Traub conjecture. The comparisons are given with some other newly developed sixteenth-order methods. Interval Newton's method is also used for finding the enough accurate initial approximations. Some figures show the enclosure of finitely many zeroes of nonlinear equations in an interval. Basins of attractions show the effectiveness of the method.

Cascadable all-optical inverter based on a nonlinear vertical-cavity semiconductor optical amplifier.

PubMed

Zhang, Haijiang; Wen, Pengyue; Esener, Sadik

2007-07-01

We report, for the first time to our knowledge, the operation of a cascadable, low-optical-switching-power(~10 microW) small-area (~100 microm(2)) high-speed (80 ps fall time) all-optical inverter. This inverter employs cross-gain modulation, polarization gain anisotropy, and highly nonlinear gain characteristics of an electrically pumped vertical-cavity semiconductor optical amplifier (VCSOA). The measured transfer characteristics of such an optical inverter resemble those of standard electronic metal-oxide semiconductor field-effect transistor-based inverters exhibiting high noise margin and high extinction ratio (~9.3 dB), making VCSOAs an ideal building block for all-optical logic and memory.

Inter-synaptic learning of combination rules in a cortical network model

PubMed Central

Lavigne, Frédéric; Avnaïm, Francis; Dumercy, Laurent

2014-01-01

Selecting responses in working memory while processing combinations of stimuli depends strongly on their relations stored in long-term memory. However, the learning of XOR-like combinations of stimuli and responses according to complex rules raises the issue of the non-linear separability of the responses within the space of stimuli. One proposed solution is to add neurons that perform a stage of non-linear processing between the stimuli and responses, at the cost of increasing the network size. Based on the non-linear integration of synaptic inputs within dendritic compartments, we propose here an inter-synaptic (IS) learning algorithm that determines the probability of potentiating/depressing each synapse as a function of the co-activity of the other synapses within the same dendrite. The IS learning is effective with random connectivity and without either a priori wiring or additional neurons. Our results show that IS learning generates efficacy values that are sufficient for the processing of XOR-like combinations, on the basis of the sole correlational structure of the stimuli and responses. We analyze the types of dendrites involved in terms of the number of synapses from pre-synaptic neurons coding for the stimuli and responses. The synaptic efficacy values obtained show that different dendrites specialize in the detection of different combinations of stimuli. The resulting behavior of the cortical network model is analyzed as a function of inter-synaptic vs. Hebbian learning. Combinatorial priming effects show that the retrospective activity of neurons coding for the stimuli trigger XOR-like combination-selective prospective activity of neurons coding for the expected response. The synergistic effects of inter-synaptic learning and of mixed-coding neurons are simulated. The results show that, although each mechanism is sufficient by itself, their combined effects improve the performance of the network. PMID:25221529

The simulation of the non-Markovian behaviour of a two-level system

NASA Astrophysics Data System (ADS)

Semina, I.; Petruccione, F.

2016-05-01

Non-Markovian relaxation dynamics of a two-level system is studied with the help of the non-linear stochastic Schrödinger equation with coloured Ornstein-Uhlenbeck noise. This stochastic Schrödinger equation is investigated numerically with an adapted Platen scheme. It is shown, that the memory effects have a significant impact to the dynamics of the system.

Large Deflection of Ideal Pseudo-Elastic Shape Memory Alloy Cantilever Beam

NASA Astrophysics Data System (ADS)

Cui, Shitang; Hu, Liming; Yan, Jun

This paper deals with the large deflections of pseudo-elastic shape memory alloy cantilever beams subjected to a concentrated load at the free end. Because of the large deflections, geometry nonlinearity arises and this analysis employs the nonlinear bending theory. The exact expression of curvature is used in the moment-curvature relationship. As a vertical force at the tip of cantilever, curvature and bending moment distribution expressions are deduced. The curvature changed distinctly when the surface material undergoes phase transformation. The length of phase transformation region was affected greatly with the force at the free end.

Nonlinear model for an optical read-only-memory disk readout channel based on an edge-spread function.

PubMed

Kobayashi, Seiji

2002-05-10

A point-spread function (PSF) is commonly used as a model of an optical disk readout channel. However, the model given by the PSF does not contain the quadratic distortion generated by the photo-detection process. We introduce a model for calculating an approximation of the quadratic component of a signal. We show that this model can be further simplified when a read-only-memory (ROM) disk is assumed. We introduce an edge-spread function by which a simple nonlinear model of an optical ROM disk readout channel is created.

Identification of multivariable nonlinear systems in the presence of colored noises using iterative hierarchical least squares algorithm.

PubMed

Jafari, Masoumeh; Salimifard, Maryam; Dehghani, Maryam

2014-07-01

This paper presents an efficient method for identification of nonlinear Multi-Input Multi-Output (MIMO) systems in the presence of colored noises. The method studies the multivariable nonlinear Hammerstein and Wiener models, in which, the nonlinear memory-less block is approximated based on arbitrary vector-based basis functions. The linear time-invariant (LTI) block is modeled by an autoregressive moving average with exogenous (ARMAX) model which can effectively describe the moving average noises as well as the autoregressive and the exogenous dynamics. According to the multivariable nature of the system, a pseudo-linear-in-the-parameter model is obtained which includes two different kinds of unknown parameters, a vector and a matrix. Therefore, the standard least squares algorithm cannot be applied directly. To overcome this problem, a Hierarchical Least Squares Iterative (HLSI) algorithm is used to simultaneously estimate the vector and the matrix of unknown parameters as well as the noises. The efficiency of the proposed identification approaches are investigated through three nonlinear MIMO case studies. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Signal and noise extraction from analog memory elements for neuromorphic computing.

PubMed

Gong, N; Idé, T; Kim, S; Boybat, I; Sebastian, A; Narayanan, V; Ando, T

2018-05-29

Dense crossbar arrays of non-volatile memory (NVM) can potentially enable massively parallel and highly energy-efficient neuromorphic computing systems. The key requirements for the NVM elements are continuous (analog-like) conductance tuning capability and switching symmetry with acceptable noise levels. However, most NVM devices show non-linear and asymmetric switching behaviors. Such non-linear behaviors render separation of signal and noise extremely difficult with conventional characterization techniques. In this study, we establish a practical methodology based on Gaussian process regression to address this issue. The methodology is agnostic to switching mechanisms and applicable to various NVM devices. We show tradeoff between switching symmetry and signal-to-noise ratio for HfO 2 -based resistive random access memory. Then, we characterize 1000 phase-change memory devices based on Ge 2 Sb 2 Te 5 and separate total variability into device-to-device variability and inherent randomness from individual devices. These results highlight the usefulness of our methodology to realize ideal NVM devices for neuromorphic computing.

Influence of magnet eddy current on magnetization characteristics of variable flux memory machine

NASA Astrophysics Data System (ADS)

Yang, Hui; Lin, Heyun; Zhu, Z. Q.; Lyu, Shukang

2018-05-01

In this paper, the magnet eddy current characteristics of a newly developed variable flux memory machine (VFMM) is investigated. Firstly, the machine structure, non-linear hysteresis characteristics and eddy current modeling of low coercive force magnet are described, respectively. Besides, the PM eddy current behaviors when applying the demagnetizing current pulses are unveiled and investigated. The mismatch of the required demagnetization currents between the cases with or without considering the magnet eddy current is identified. In addition, the influences of the magnet eddy current on the demagnetization effect of VFMM are analyzed. Finally, a prototype is manufactured and tested to verify the theoretical analyses.

Tracking Control of Shape-Memory-Alloy Actuators Based on Self-Sensing Feedback and Inverse Hysteresis Compensation

PubMed Central

Liu, Shu-Hung; Huang, Tse-Shih; Yen, Jia-Yush

2010-01-01

Shape memory alloys (SMAs) offer a high power-to-weight ratio, large recovery strain, and low driving voltages, and have thus attracted considerable research attention. The difficulty of controlling SMA actuators arises from their highly nonlinear hysteresis and temperature dependence. This paper describes a combination of self-sensing and model-based control, where the model includes both the major and minor hysteresis loops as well as the thermodynamics effects. The self-sensing algorithm uses only the power width modulation (PWM) signal and requires no heavy equipment. The method can achieve high-accuracy servo control and is especially suitable for miniaturized applications. PMID:22315530

Long memory and volatility clustering: Is the empirical evidence consistent across stock markets?

NASA Astrophysics Data System (ADS)

Bentes, Sónia R.; Menezes, Rui; Mendes, Diana A.

2008-06-01

Long memory and volatility clustering are two stylized facts frequently related to financial markets. Traditionally, these phenomena have been studied based on conditionally heteroscedastic models like ARCH, GARCH, IGARCH and FIGARCH, inter alia. One advantage of these models is their ability to capture nonlinear dynamics. Another interesting manner to study the volatility phenomenon is by using measures based on the concept of entropy. In this paper we investigate the long memory and volatility clustering for the SP 500, NASDAQ 100 and Stoxx 50 indexes in order to compare the US and European Markets. Additionally, we compare the results from conditionally heteroscedastic models with those from the entropy measures. In the latter, we examine Shannon entropy, Renyi entropy and Tsallis entropy. The results corroborate the previous evidence of nonlinear dynamics in the time series considered.

We should be using nonlinear indices when relating heart-rate dynamics to cognition and mood

PubMed Central

Young, Hayley; Benton, David

2015-01-01

Both heart rate (HR) and brain functioning involve the integrated output of a multitude of regulatory mechanisms, that are not quantified adequately by linear approximations such as means and standard deviations. It was therefore considered whether non-linear measures of HR complexity are more strongly associated with cognition and mood. Whilst resting, the inter-beat (R-R) time series of twenty-one males and twenty-four females were measured for five minutes. The data were summarised using time, frequency and nonlinear complexity measures. Attention, memory, reaction times, mood and cortisol levels were assessed. Nonlinear HR indices captured additional information, enabling a greater percentage of the variance in behaviour to be explained. On occasions non-linear indices were related to aspects for behaviour, for example focused attention and cortisol production, when time or frequency indices were not. These effects were sexually dimorphic with HR complexity being more strongly associated with the behaviour of females. It was concluded that nonlinear rather than linear methods of summarizing the HR times series offers a novel way of relating brain functioning and behaviour. It should be considered whether non-linear measures of HR complexity can be used as a biomarker of the integrated functioning of the brain. PMID:26565560

Novel procedure for characterizing nonlinear systems with memory: 2017 update

NASA Astrophysics Data System (ADS)

Nuttall, Albert H.; Katz, Richard A.; Hughes, Derke R.; Koch, Robert M.

2017-05-01

The present article discusses novel improvements in nonlinear signal processing made by the prime algorithm developer, Dr. Albert H. Nuttall and co-authors, a consortium of research scientists from the Naval Undersea Warfare Center Division, Newport, RI. The algorithm, called the Nuttall-Wiener-Volterra or 'NWV' algorithm is named for its principal contributors [1], [2],[ 3] . The NWV algorithm significantly reduces the computational workload for characterizing nonlinear systems with memory. Following this formulation, two measurement waveforms are required in order to characterize a specified nonlinear system under consideration: (1) an excitation input waveform, x(t) (the transmitted signal); and, (2) a response output waveform, z(t) (the received signal). Given these two measurement waveforms for a given propagation channel, a 'kernel' or 'channel response', h= [h0,h1,h2,h3] between the two measurement points, is computed via a least squares approach that optimizes modeled kernel values by performing a best fit between measured response z(t) and a modeled response y(t). New techniques significantly diminish the exponential growth of the number of computed kernel coefficients at second and third order and alleviate the Curse of Dimensionality (COD) in order to realize practical nonlinear solutions of scientific and engineering interest.

Boosted Schwarzschild metrics from a Kerr–Schild perspective

NASA Astrophysics Data System (ADS)

Mädler, Thomas; Winicour, Jeffrey

2018-02-01

The Kerr–Schild version of the Schwarzschild metric contains a Minkowski background which provides a definition of a boosted black hole. There are two Kerr–Schild versions corresponding to ingoing or outgoing principle null directions. We show that the two corresponding Minkowski backgrounds and their associated boosts have an unexpected difference. We analyze this difference and discuss the implications in the nonlinear regime for the gravitational memory effect resulting from the ejection of massive particles from an isolated system. We show that the nonlinear effect agrees with the linearized result based upon the retarded Green function only if the velocity of the ejected particle corresponds to a boost symmetry of the ingoing Minkowski background. A boost with respect to the outgoing Minkowski background is inconsistent with the absence of ingoing radiation from past null infinity.

Nonlinearities in the exchange rates returns and volatility

NASA Astrophysics Data System (ADS)

Díaz, Andrés Fernández; Grau-Carles, Pilar; Mangas, Lorenzo Escot

2002-12-01

Recent findings of nonlinearities in financial assets can be the product of contamination produced by shifts in the distribution of the data. Using the BDS and Kaplan tests it is shown that, some of the nonlinearities found in foreign exchange rate returns, can be the product of shifts in variance while other do not. Also, the behavior of the volatility is studied, showing that the ARFIMA modeling is able to capture long memory, but, depending on the proxy used for the volatility, is not always able to capture all the nonlinearities of the data

Constitutive modeling of glassy shape memory polymers

NASA Astrophysics Data System (ADS)

Khanolkar, Mahesh

The aim of this research is to develop constitutive models for non-linear materials. Here, issues related for developing constitutive model for glassy shape memory polymers are addressed in detail. Shape memory polymers are novel material that can be easily formed into complex shapes, retaining memory of their original shape even after undergoing large deformations. The temporary shape is stable and return to the original shape is triggered by a suitable mechanism such heating the polymer above a transition temperature. Glassy shape memory polymers are called glassy because the temporary shape is fixed by the formation of a glassy solid, while return to the original shape is due to the melting of this glassy phase. The constitutive model has been developed to capture the thermo-mechanical behavior of glassy shape memory polymers using elements of nonlinear mechanics and polymer physics. The key feature of this framework is that a body can exist stress free in numerous natural configurations, the underlying natural configuration of the body changing during the process, with the response of the body being elastic from these evolving natural configurations. The aim of this research is to formulate a constitutive model for glassy shape memory polymers (GSMP) which takes in to account the fact that the stress-strain response depends on thermal expansion of polymers. The model developed is for the original amorphous phase, the temporary glassy phase and transition between these phases. The glass transition process has been modeled using a framework that was developed recently for studying crystallization in polymers and is based on the theory of multiple natural configurations. Using the same frame work, the melting of the glassy phase to capture the return of the polymer to its original shape is also modeled. The effect of nanoreinforcement on the response of shape memory polymers (GSMP) is studied and a model is developed. In addition to modeling and solving boundary value problems for GSMP's, problems of importance for CSMP, specifically a shape memory cycle (Torsion of a Cylinder) is solved using the developed crystallizable shape memory polymer model. To solve complex boundary value problems in realistic geometries a user material subroutine (UMAT) for GSMP model has been developed for use in conjunction with the commercial finite element software ABAQUS. The accuracy of the UMAT has been verified by testing it against problems for which the results are known.

Study of electrical conductivity and memory switching in the zinc-vanadium-phosphate glasses

NASA Astrophysics Data System (ADS)

Mirzayi, M.; Hekmatshoar, M. H.

2013-07-01

Vanadium zinc phosphate glasses were prepared by the conventional melt quenching technique and effect of V2O5 concentration on d.c. conductivity of prepared samples were investigated. X-ray diffraction patterns confirmed the glassy character of the samples. The d.c. conductivity increased with increase in V2O5 content. Results showed that activation energy has a single value in the investigated range of temperature, which can be explained in accordance with Mott small pollaron hopping model. I-V characteristics at high electric field showed that switching in these glasses was memory type. The threshold field of switching was found to decrease with increase in V2O5 content. Non-linear behavior and switching phenomenon was explained by Pool-Frenkel effect and thermal model.

Memory persistency and nonlinearity in daily mean dew point across India

NASA Astrophysics Data System (ADS)

Ray, Rajdeep; Khondekar, Mofazzal Hossain; Ghosh, Koushik; Bhattacharjee, Anup Kumar

2016-04-01

Enterprising endeavour has been taken in this work to realize and estimate the persistence in memory of the daily mean dew point time series obtained from seven different weather stations viz. Kolkata, Chennai (Madras), New Delhi, Mumbai (Bombay), Bhopal, Agartala and Ahmedabad representing different geographical zones in India. Hurst exponent values reveal an anti-persistent behaviour of these dew point series. To affirm the Hurst exponent values, five different scaling methods have been used and the corresponding results are compared to synthesize a finer and reliable conclusion out of it. The present analysis also bespeaks that the variation in daily mean dew point is governed by a non-stationary process with stationary increments. The delay vector variance (DVV) method has been exploited to investigate nonlinearity, and the present calculation confirms the presence of deterministic nonlinear profile in the daily mean dew point time series of the seven stations.

Hippocampal CA3-dentate gyrus volume uniquely linked to improvement in associative memory from childhood to adulthood.

PubMed

Daugherty, Ana M; Flinn, Robert; Ofen, Noa

2017-06-01

Associative memory develops into adulthood and critically depends on the hippocampus. The hippocampus is a complex structure composed of subfields that are functionally-distinct, and anterior-posterior divisions along the length of the hippocampal horizontal axis that may also differ by cognitive correlates. Although each of these aspects has been considered independently, here we evaluate their relative contributions as correlates of age-related improvement in memory. Volumes of hippocampal subfields (subiculum, CA1-2, CA3-dentate gyrus) and anterior-posterior divisions (hippocampal head, body, tail) were manually segmented from high-resolution images in a sample of healthy participants (age 8-25 years). Adults had smaller CA3-dentate gyrus volume as compared to children, which accounted for 67% of the indirect effect of age predicting better associative memory via hippocampal volumes. Whereas hippocampal body volume demonstrated non-linear age differences, larger hippocampal body volume was weakly related to better associative memory only when accounting for the mutual correlation with subfields measured within that region. Thus, typical development of associative memory was largely explained by age-related differences in CA3-dentate gyrus. Copyright © 2017 Elsevier Inc. All rights reserved.

Hippocampal CA3-dentate gyrus volume uniquely linked to improvement in associative memory from childhood to adulthood

PubMed Central

Daugherty, Ana M.; Flinn, Robert; Ofen, Noa

2017-01-01

Associative memory develops into adulthood and critically depends on the hippocampus. The hippocampus is a complex structure composed of subfields that are functionally-distinct, and anterior-posterior divisions along the length of the hippocampal horizontal axis that may also differ by cognitive correlates. Although each of these aspects has been considered independently, here we evaluate their relative contributions as correlates of age-related improvement in memory. Volumes of hippocampal subfields (subiculum, CA1-2, CA3-dentate gyrus) and anterior-posterior divisions (hippocampal head, body, tail) were manually segmented from high-resolution proton density-weighted images in a sample of healthy participants (age 8–25 years). Adults had smaller CA3-dentate gyrus volume as compared to children, which accounted for 67% of the indirect effect of age predicting better associative memory via hippocampal volumes. Whereas hippocampal body volume demonstrated non-linear age differences, larger hippocampal body volume was weakly related to better associative memory only when accounting for the mutual correlation with subfields measured within that region. Thus, typical development of associative memory was largely explained by age-related differences in CA3-dentate gyrus. PMID:28342999

The application of nonlinear programming and collocation to optimal aeroassisted orbital transfers

NASA Astrophysics Data System (ADS)

Shi, Y. Y.; Nelson, R. L.; Young, D. H.; Gill, P. E.; Murray, W.; Saunders, M. A.

1992-01-01

Sequential quadratic programming (SQP) and collocation of the differential equations of motion were applied to optimal aeroassisted orbital transfers. The Optimal Trajectory by Implicit Simulation (OTIS) computer program codes with updated nonlinear programming code (NZSOL) were used as a testbed for the SQP nonlinear programming (NLP) algorithms. The state-of-the-art sparse SQP method is considered to be effective for solving large problems with a sparse matrix. Sparse optimizers are characterized in terms of memory requirements and computational efficiency. For the OTIS problems, less than 10 percent of the Jacobian matrix elements are nonzero. The SQP method encompasses two phases: finding an initial feasible point by minimizing the sum of infeasibilities and minimizing the quadratic objective function within the feasible region. The orbital transfer problem under consideration involves the transfer from a high energy orbit to a low energy orbit.

Symmetry Breaking of Counter-Propagating Light in a Nonlinear Resonator.

PubMed

Del Bino, Leonardo; Silver, Jonathan M; Stebbings, Sarah L; Del'Haye, Pascal

2017-02-21

Spontaneous symmetry breaking is a concept of fundamental importance in many areas of physics, underpinning such diverse phenomena as ferromagnetism, superconductivity, superfluidity and the Higgs mechanism. Here we demonstrate nonreciprocity and spontaneous symmetry breaking between counter-propagating light in dielectric microresonators. The symmetry breaking corresponds to a resonance frequency splitting that allows only one of two counter-propagating (but otherwise identical) states of light to circulate in the resonator. Equivalently, this effect can be seen as the collapse of standing waves and transition to travelling waves within the resonator. We present theoretical calculations to show that the symmetry breaking is induced by Kerr-nonlinearity-mediated interaction between the counter-propagating light. Our findings pave the way for a variety of applications including optically controllable circulators and isolators, all-optical switching, nonlinear-enhanced rotation sensing, optical flip-flops for photonic memories as well as exceptionally sensitive power and refractive index sensors.

Symmetry Breaking of Counter-Propagating Light in a Nonlinear Resonator

PubMed Central

Del Bino, Leonardo; Silver, Jonathan M.; Stebbings, Sarah L.; Del'Haye, Pascal

2017-01-01

Spontaneous symmetry breaking is a concept of fundamental importance in many areas of physics, underpinning such diverse phenomena as ferromagnetism, superconductivity, superfluidity and the Higgs mechanism. Here we demonstrate nonreciprocity and spontaneous symmetry breaking between counter-propagating light in dielectric microresonators. The symmetry breaking corresponds to a resonance frequency splitting that allows only one of two counter-propagating (but otherwise identical) states of light to circulate in the resonator. Equivalently, this effect can be seen as the collapse of standing waves and transition to travelling waves within the resonator. We present theoretical calculations to show that the symmetry breaking is induced by Kerr-nonlinearity-mediated interaction between the counter-propagating light. Our findings pave the way for a variety of applications including optically controllable circulators and isolators, all-optical switching, nonlinear-enhanced rotation sensing, optical flip-flops for photonic memories as well as exceptionally sensitive power and refractive index sensors. PMID:28220865

Chaotic Oscillations of Second Order Linear Hyperbolic Equations with Nonlinear Boundary Conditions: A Factorizable but Noncommutative Case

NASA Astrophysics Data System (ADS)

Li, Liangliang; Huang, Yu; Chen, Goong; Huang, Tingwen

If a second order linear hyperbolic partial differential equation in one-space dimension can be factorized as a product of two first order operators and if the two first order operators commute, with one boundary condition being the van der Pol type and the other being linear, one can establish the occurrence of chaos when the parameters enter a certain regime [Chen et al., 2014]. However, if the commutativity of the two first order operators fails to hold, then the treatment in [Chen et al., 2014] no longer works and significant new challenges arise in determining nonlinear boundary conditions that engenders chaos. In this paper, we show that by incorporating a linear memory effect, a nonlinear van der Pol boundary condition can cause chaotic oscillations when the parameter enters a certain regime. Numerical simulations illustrating chaotic oscillations are also presented.

Sensitive periods in fear learning and memory.

PubMed

King, Elizabeth C; Pattwell, Siobhan S; Glatt, Charles E; Lee, Francis S

2014-01-01

Adolescence represents a uniquely sensitive developmental stage in the transition from childhood to adulthood. During this transition, neuronal circuits are particularly susceptible to modification by experience. In addition, adolescence is a stage in which the incidence of anxiety disorders peaks in humans and over 75% of adults with fear-related disorders met diagnostic criteria as children and adolescents. While postnatal critical periods of plasticity for primary sensory processes, such as in the visual system are well established, less is known about potential critical or sensitive periods for fear learning and memory. Here, we review the non-linear developmental aspects of fear learning and memory during a transition period into and out of adolescence. We also review the literature on the non-linear development of GABAergic neurotransmission, a key regulator of critical period plasticity. We provide a model that may inform improved treatment strategies for children and adolescents with fear-related disorders.

Sensitive periods in fear learning and memory

PubMed Central

King, Elizabeth C.; Pattwell, Siobhan S.; Glatt, Charles E.; Lee, Francis S.

2015-01-01

Adolescence represents a uniquely sensitive developmental stage in the transition from childhood to adulthood. During this transition, neuronal circuits are particularly susceptible to modification by experience. In addition, adolescence is a stage in which the incidence of anxiety disorders peaks in humans and over 75% of adults with fear-related disorders met diagnostic criteria as children and adolescents. While postnatal critical periods of plasticity for primary sensory processes, such as in the visual system are well established, less is known about potential critical or sensitive periods for fear learning and memory. Here, we review the nonlinear developmental aspects of fear learning and memory during a transition period into and out of adolescence. We also review the literature on the non-linear development of GABAergic neurotransmission, a key regulator of critical period plasticity. We provide a model that may inform improved treatment strategies for children and adolescents with fear-related disorders. PMID:23611461

Nonlinear Developmental trajectory of fear learning and memory

PubMed Central

King, Elizabeth C.; Pattwell, Siobhan S.; Sun, Alice; Glatt, Charles E.; Lee, Francis S.

2013-01-01

The transition into and out of adolescence represents a unique developmental period during which neuronal circuits are particularly susceptible to modification by experience. Adolescence is associated with an increased incidence of anxiety disorders in humans,1–3 and an estimated 75% of adults with fear-related disorders met diagnostic criteria as children and adolescents.4,5 Conserved neural circuitry between rodents and humans has facilitated neurodevelopmental studies of behavioral and molecular processes associated with fear learning and memory, which lie at the heart of many anxiety disorders. Here, we review the non-linear developmental aspects of fear learning and memory during a transition period into and out of adolescence and provide a discussion of the molecular mechanisms that may underlie these alterations in behavior. We provide a model that may help to inform novel treatment strategies for children and adolescents with fear-related disorders. PMID:24176014

Modeling of long-range memory processes with inverse cubic distributions by the nonlinear stochastic differential equations

NASA Astrophysics Data System (ADS)

Kaulakys, B.; Alaburda, M.; Ruseckas, J.

2016-05-01

A well-known fact in the financial markets is the so-called ‘inverse cubic law’ of the cumulative distributions of the long-range memory fluctuations of market indicators such as a number of events of trades, trading volume and the logarithmic price change. We propose the nonlinear stochastic differential equation (SDE) giving both the power-law behavior of the power spectral density and the long-range dependent inverse cubic law of the cumulative distribution. This is achieved using the suggestion that when the market evolves from calm to violent behavior there is a decrease of the delay time of multiplicative feedback of the system in comparison to the driving noise correlation time. This results in a transition from the Itô to the Stratonovich sense of the SDE and yields a long-range memory process.

TiO2-based memristors and ReRAM: materials, mechanisms and models (a review)

NASA Astrophysics Data System (ADS)

Gale, Ella

2014-10-01

The memristor is the fundamental nonlinear circuit element, with uses in computing and computer memory. Resistive Random Access Memory (ReRAM) is a resistive switching memory proposed as a non-volatile memory. In this review we shall summarize the state of the art for these closely-related fields, concentrating on titanium dioxide, the well-utilized and archetypal material for both. We shall cover material properties, switching mechanisms and models to demonstrate what ReRAM and memristor scientists can learn from each other and examine the outlook for these technologies.

Nonlinear Hysteretic Torsional Waves

NASA Astrophysics Data System (ADS)

Cabaret, J.; Béquin, P.; Theocharis, G.; Andreev, V.; Gusev, V. E.; Tournat, V.

2015-07-01

We theoretically study and experimentally report the propagation of nonlinear hysteretic torsional pulses in a vertical granular chain made of cm-scale, self-hanged magnetic beads. As predicted by contact mechanics, the torsional coupling between two beads is found to be nonlinear hysteretic. This results in a nonlinear pulse distortion essentially different from the distortion predicted by classical nonlinearities and in a complex dynamic response depending on the history of the wave particle angular velocity. Both are consistent with the predictions of purely hysteretic nonlinear elasticity and the Preisach-Mayergoyz hysteresis model, providing the opportunity to study the phenomenon of nonlinear dynamic hysteresis in the absence of other types of material nonlinearities. The proposed configuration reveals a plethora of interesting phenomena including giant amplitude-dependent attenuation, short-term memory, as well as dispersive properties. Thus, it could find interesting applications in nonlinear wave control devices such as strong amplitude-dependent filters.

Dynamic-Data Driven Modeling of Uncertainties and 3D Effects of Porous Shape Memory Alloys

DTIC Science & Technology

2014-02-03

takes longer since cooling is required. In fact, five to ten times longer is common. Porous SMAs using an appropriately cold liquid is one of the...deploying solar panels, space station component joining, vehicular docking, and numerous Mars rover components. On airplanes or drones, jet engine...Presho, G. Li. Generalized multiscale finite element methods. Nonlinear elliptic equations, Communication in Computational Physics, 15 (2014), pp

Insight into the Effects of Reinforcement Shape on Achieving Continuous Martensite Transformation in Phase Transforming Matrix Composites

NASA Astrophysics Data System (ADS)

Zhang, Xudong; Ren, Junqiang; Wang, Xiaofei; Zong, Hongxiang; Cui, Lishan; Ding, Xiangdong

2017-12-01

A continuous martensite transformation is indispensable for achieving large linear superelasticity and low modulus in phase transforming metal-based composites. However, determining how to accurately condition the residual martensite in a shape memory alloy matrix though the reinforcement shape to achieve continuous martensite transformation has been a challenge. Here, we take the finite element method to perform a comparative study of the effects of nanoinclusion shape on the interaction and martensite phase transformation in this new composite. Two typical samples are compared: one reinforced by metallic nanowires and the other by nanoparticles. We find that the residual martensite within the shape memory alloy matrix after a pretreatment can be tailored by the reinforcement shape. In particular, our results show that the shape memory alloy matrix can retain enough residual martensite phases to achieve continuous martensite transformation in the subsequent loading when the aspect ratio of nanoreinforcement is larger than 20. In contrast, the composites reinforced with spherical or low aspect ratio reinforcement show a typical nonlinear superelasticity as a result of a low stress transfer-induced discontinuous martensite transformation within the shape memory alloy matrix.

Resistive and Capacitive Memory Effects in Oxide Insulator/ Oxide Conductor Hetero-Structures

NASA Astrophysics Data System (ADS)

Meyer, Rene; Miao, Maosheng; Wu, Jian; Chevallier, Christophe

2013-03-01

We report resistive and capacitive memory effects observed in oxide insulator/ oxide conductor hetero-structures. Electronic transport properties of Pt/ZrO2/PCMO/Pt structures with ZrO2 thicknesses ranging from 20A to 40A are studied before and after applying short voltage pulses of positive and negative polarity for set and reset operation. As processed devices display a non-linear IV characteristic which we attribute to trap assisted tunneling through the ZrO2 tunnel oxide. Current scaling with electrode area and tunnel oxide thickness confirms uniform conduction. The set/reset operation cause an up/down shift of the IV characteristic indicating that the conduction mechanism of both states is still dominated by tunneling. A change in the resistance is associated with a capacitance change of the device. An exponential relation between program voltages and set times is found. A model based on electric field mediated non-linear transport of oxygen ions across the ZrO2/PCMO interface is proposed. The change in the tunnel current is explained by ionic charge transfer between tunnel oxide and conductive metal oxide changing both tunnel barrier height and PCMO conductivity. DFT techniques are employed to explain the conductivity change in the PCMO interfacial layer observed through capacitance measurements.

Pulse width modulation-based temperature tracking for feedback control of a shape memory alloy actuator.

PubMed

Ayvali, Elif; Desai, Jaydev P

2014-04-01

This work presents a temperature-feedback approach to control the radius of curvature of an arc-shaped shape memory alloy (SMA) wire. The nonlinear properties of the SMA such as phase transformation and its dependence on temperature and stress make SMA actuators difficult to control. Tracking a desired trajectory is more challenging than controlling just the position of the SMA actuator since the desired path is continuously changing. Consequently, tracking the desired strain directly or tracking the parameters such as temperature and electrical resistance that are related to strain with a model is a challenging task. Temperature-feedback is an attractive approach when direct measurement of strain is not practical. Pulse width modulation (PWM) is an effective method for SMA actuation and it can be used along with a compensator to control the temperature of the SMA. Using the constitutive model of the SMA, the desired temperature profile can be obtained for a given strain trajectory. A PWM-based nonlinear PID controller with a feed-forward heat transfer model is proposed to use temperature-feedback for tracking a desired temperature trajectory. The proposed controller is used during the heating phase of the SMA actuator. The controller proves to be effective in tracking step-wise and continuous trajectories.

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.

Coexistence of high performance resistance and capacitance memory based on multilayered metal-oxide structures

PubMed Central

Yan, Z. B.; Liu, J. -M.

2013-01-01

The Au/DyMnO3/Nb:SrTiO3/Au stack was demonstrated to be not only a high performance memristor but also a good memcapacitor. The switching time is below 10 ns, the retention is longer than 105 s, and the change ratio of resistance (or capacitance) is larger than 100 over the 108 switching cycles. Moreover, this stack has a broad range of intermediate states that are tunable by the operating voltages. It is indicated that the memory effects originate from the Nb:SrTiO3/Au junction where the barrier profile is electrically modulated. The serial connected Au/DyMnO3/Nb:SrTiO3 stack behaves as a high nonlinear resistor paralleling with a capacitor, which raises the capacitance change ratio and enhances the memory stability of the device. PMID:23963467

Regenerative memory in time-delayed neuromorphic photonic resonators

NASA Astrophysics Data System (ADS)

Romeira, B.; Avó, R.; Figueiredo, José M. L.; Barland, S.; Javaloyes, J.

2016-01-01

We investigate a photonic regenerative memory based upon a neuromorphic oscillator with a delayed self-feedback (autaptic) connection. We disclose the existence of a unique temporal response characteristic of localized structures enabling an ideal support for bits in an optical buffer memory for storage and reshaping of data information. We link our experimental implementation, based upon a nanoscale nonlinear resonant tunneling diode driving a laser, to the paradigm of neuronal activity, the FitzHugh-Nagumo model with delayed feedback. This proof-of-concept photonic regenerative memory might constitute a building block for a new class of neuron-inspired photonic memories that can handle high bit-rate optical signals.

Dynamic phenotypic restructuring of the CD4 and CD8 T-cell subsets with age in healthy humans: a compartmental model analysis.

PubMed

Jackola, D R; Hallgren, H M

1998-11-16

In healthy humans, phenotypic restructuring occurs with age within the CD3+ T-lymphocyte complement. This is characterized by a non-linear decrease of the percentage of 'naive' (CD45RA+) cells and a corresponding non-linear increase of the percentage of 'memory' (CD45R0+) cells among both the CD4+ and CD8+ T-cell subsets. We devised a simple compartmental model to study the age-dependent kinetics of phenotypic restructuring. We also derived differential equations whose parameters determined yearly gains minus losses of the percentage and absolute numbers of circulating naive cells, yearly gains minus losses of the percentage and absolute numbers of circulating memory cells, and the yearly rate of conversion of naive to memory cells. Solutions of these evaluative differential equations demonstrate the following: (1) the memory cell complement 'resides' within its compartment for a longer time than the naive cell complement within its compartment for both CD4 and CD8 cells; (2) the average, annual 'turnover rate' is the same for CD4 and CD8 naive cells. In contrast, the average, annual 'turnover rate' for memory CD8 cells is 1.5 times that of memory CD4 cells; (3) the average, annual conversion rate of CD4 naive cells to memory cells is twice that of the CD8 conversion rate; (4) a transition in dynamic restructuring occurs during the third decade of life that is due to these differences in turnover and conversion rates, between and from naive to memory cells.

Task-switching cost and repetition priming: two overlooked confounds in the first-set procedure of the Sternberg paradigm and how they affect memory set-size effects.

PubMed

Jou, Jerwen

2014-10-01

Subjects performed Sternberg-type memory recognition tasks (Sternberg paradigm) in four experiments. Category-instance names were used as learning and testing materials. Sternberg's original experiments demonstrated a linear relation between reaction time (RT) and memory-set size (MSS). A few later studies found no relation, and other studies found a nonlinear relation (logarithmic) between the two variables. These deviations were used as evidence undermining Sternberg's serial scan theory. This study identified two confounding variables in the fixed-set procedure of the paradigm (where multiple probes are presented at test for a learned memory set) that could generate a MSS RT function that was either flat or logarithmic rather than linearly increasing. These two confounding variables were task-switching cost and repetition priming. The former factor worked against smaller memory sets and in favour of larger sets whereas the latter factor worked in the opposite way. Results demonstrated that a null or a logarithmic RT-to-MSS relation could be the artefact of the combined effects of these two variables. The Sternberg paradigm has been used widely in memory research, and a thorough understanding of the subtle methodological pitfalls is crucial. It is suggested that a varied-set procedure (where only one probe is presented at test for a learned memory set) is a more contamination-free procedure for measuring the MSS effects, and that if a fixed-set procedure is used, it is worthwhile examining the RT function of the very first trials across the MSSs, which are presumably relatively free of contamination by the subsequent trials.

The retention and disruption of color information in human short-term visual memory.

PubMed

Nemes, Vanda A; Parry, Neil R A; Whitaker, David; McKeefry, Declan J

2012-01-27

Previous studies have demonstrated that the retention of information in short-term visual perceptual memory can be disrupted by the presentation of masking stimuli during interstimulus intervals (ISIs) in delayed discrimination tasks (S. Magnussen & W. W. Greenlee, 1999). We have exploited this effect in order to determine to what extent short-term perceptual memory is selective for stimulus color. We employed a delayed hue discrimination paradigm to measure the fidelity with which color information was retained in short-term memory. The task required 5 color normal observers to discriminate between spatially non-overlapping colored reference and test stimuli that were temporally separated by an ISI of 5 s. The points of subjective equality (PSEs) on the resultant psychometric matching functions provided an index of performance. Measurements were made in the presence and absence of mask stimuli presented during the ISI, which varied in hue around the equiluminant plane in DKL color space. For all reference stimuli, we found a consistent mask-induced, hue-dependent shift in PSE compared to the "no mask" conditions. These shifts were found to be tuned in color space, only occurring for a range of mask hues that fell within bandwidths of 29-37 deg. Outside this range, masking stimuli had little or no effect on measured PSEs. The results demonstrate that memory masking for color exhibits selectivity similar to that which has already been demonstrated for other visual attributes. The relatively narrow tuning of these interference effects suggests that short-term perceptual memory for color is based on higher order, non-linear color coding. © ARVO

Mixed memory, (non) Hurst effect, and maximum entropy of rainfall in the tropical Andes

NASA Astrophysics Data System (ADS)

Poveda, Germán

2011-02-01

Diverse linear and nonlinear statistical parameters of rainfall under aggregation in time and the kind of temporal memory are investigated. Data sets from the Andes of Colombia at different resolutions (15 min and 1-h), and record lengths (21 months and 8-40 years) are used. A mixture of two timescales is found in the autocorrelation and autoinformation functions, with short-term memory holding for time lags less than 15-30 min, and long-term memory onwards. Consistently, rainfall variance exhibits different temporal scaling regimes separated at 15-30 min and 24 h. Tests for the Hurst effect evidence the frailty of the R/ S approach in discerning the kind of memory in high resolution rainfall, whereas rigorous statistical tests for short-memory processes do reject the existence of the Hurst effect. Rainfall information entropy grows as a power law of aggregation time, S( T) ˜ Tβ with < β> = 0.51, up to a timescale, TMaxEnt (70-202 h), at which entropy saturates, with β = 0 onwards. Maximum entropy is reached through a dynamic Generalized Pareto distribution, consistently with the maximum information-entropy principle for heavy-tailed random variables, and with its asymptotically infinitely divisible property. The dynamics towards the limit distribution is quantified. Tsallis q-entropies also exhibit power laws with T, such that Sq( T) ˜ Tβ( q) , with β( q) ⩽ 0 for q ⩽ 0, and β( q) ≃ 0.5 for q ⩾ 1. No clear patterns are found in the geographic distribution within and among the statistical parameters studied, confirming the strong variability of tropical Andean rainfall.

A complexity theory model in science education problem solving: random walks for working memory and mental capacity.

PubMed

Stamovlasis, Dimitrios; Tsaparlis, Georgios

2003-07-01

The present study examines the role of limited human channel capacity from a science education perspective. A model of science problem solving has been previously validated by applying concepts and tools of complexity theory (the working memory, random walk method). The method correlated the subjects' rank-order achievement scores in organic-synthesis chemistry problems with the subjects' working memory capacity. In this work, we apply the same nonlinear approach to a different data set, taken from chemical-equilibrium problem solving. In contrast to the organic-synthesis problems, these problems are algorithmic, require numerical calculations, and have a complex logical structure. As a result, these problems cause deviations from the model, and affect the pattern observed with the nonlinear method. In addition to Baddeley's working memory capacity, the Pascual-Leone's mental (M-) capacity is examined by the same random-walk method. As the complexity of the problem increases, the fractal dimension of the working memory random walk demonstrates a sudden drop, while the fractal dimension of the M-capacity random walk decreases in a linear fashion. A review of the basic features of the two capacities and their relation is included. The method and findings have consequences for problem solving not only in chemistry and science education, but also in other disciplines.

Dynamic linkages among the gold market, US dollar and crude oil market

NASA Astrophysics Data System (ADS)

Mo, Bin; Nie, He; Jiang, Yonghong

2018-02-01

This paper aims to examine the dynamic linkages among the gold market, US dollar and crude oil market. The analysis also delves more deeply into the effect of the global financial crisis on the short-term relationship. We use fractional cointegration to analyze the long-term memory feature of these volatility processes to investigate whether they are tied through a common long-term equilibrium. The DCC-MGARCH model is employed to investigate the time-varying long-term linkages among these markets. The Krystou-Labys non-linear asymmetric Granger causality method is used to examine the effect of the financial crisis. We find that (i) there is clearly a long-term dependence among these markets; (ii) the dynamic gold-oil relationship is always positive and the oil-dollar relationship is always negative; and (iii) after the crisis, we can observe evidence of a positive non-linear causal relationship from gold to US dollar and US dollar to crude oil, and a negative non-linear causal relationship from US dollar to gold. Investors who want to construct their optimal portfolios and policymakers who aim to make effective macroeconomic policies should take these findings into account.

A general nonlinear magnetomechanical model for ferromagnetic materials under a constant weak magnetic field

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

Shi, Pengpeng; Zheng, Xiaojing, E-mail: xjzheng@xidian.edu.cn; Jin, Ke

2016-04-14

Weak magnetic nondestructive testing (e.g., metal magnetic memory method) concerns the magnetization variation of ferromagnetic materials due to its applied load and a weak magnetic surrounding them. One key issue on these nondestructive technologies is the magnetomechanical effect for quantitative evaluation of magnetization state from stress–strain condition. A representative phenomenological model has been proposed to explain the magnetomechanical effect by Jiles in 1995. However, the Jiles' model has some deficiencies in quantification, for instance, there is a visible difference between theoretical prediction and experimental measurements on stress–magnetization curve, especially in the compression case. Based on the thermodynamic relations and themore » approach law of irreversible magnetization, a nonlinear coupled model is proposed to improve the quantitative evaluation of the magnetomechanical effect. Excellent agreement has been achieved between the predictions from the present model and previous experimental results. In comparison with Jiles' model, the prediction accuracy is improved greatly by the present model, particularly for the compression case. A detailed study has also been performed to reveal the effects of initial magnetization status, cyclic loading, and demagnetization factor on the magnetomechanical effect. Our theoretical model reveals that the stable weak magnetic signals of nondestructive testing after multiple cyclic loads are attributed to the first few cycles eliminating most of the irreversible magnetization. Remarkably, the existence of demagnetization field can weaken magnetomechanical effect, therefore, significantly reduces the testing capability. This theoretical model can be adopted to quantitatively analyze magnetic memory signals, and then can be applied in weak magnetic nondestructive testing.« less

Dynamic learning from adaptive neural network control of a class of nonaffine nonlinear systems.

PubMed

Dai, Shi-Lu; Wang, Cong; Wang, Min

2014-01-01

This paper studies the problem of learning from adaptive neural network (NN) control of a class of nonaffine nonlinear systems in uncertain dynamic environments. In the control design process, a stable adaptive NN tracking control design technique is proposed for the nonaffine nonlinear systems with a mild assumption by combining a filtered tracking error with the implicit function theorem, input-to-state stability, and the small-gain theorem. The proposed stable control design technique not only overcomes the difficulty in controlling nonaffine nonlinear systems but also relaxes constraint conditions of the considered systems. In the learning process, the partial persistent excitation (PE) condition of radial basis function NNs is satisfied during tracking control to a recurrent reference trajectory. Under the PE condition and an appropriate state transformation, the proposed adaptive NN control is shown to be capable of acquiring knowledge on the implicit desired control input dynamics in the stable control process and of storing the learned knowledge in memory. Subsequently, an NN learning control design technique that effectively exploits the learned knowledge without re-adapting to the controller parameters is proposed to achieve closed-loop stability and improved control performance. Simulation studies are performed to demonstrate the effectiveness of the proposed design techniques.

Sensitivity to Mental Effort and Test-Retest Reliability of Heart Rate Variability Measures in Healthy Seniors

PubMed Central

Mukherjee, Shalini; Yadav, Rajeev; Yung, Iris; Zajdel, Daniel P.; Oken, Barry S.

2011-01-01

Objectives To determine 1) whether heart rate variability (HRV) was a sensitive and reliable measure in mental effort tasks carried out by healthy seniors and 2) whether non-linear approaches to HRV analysis, in addition to traditional time and frequency domain approaches were useful to study such effects. Methods Forty healthy seniors performed two visual working memory tasks requiring different levels of mental effort, while ECG was recorded. They underwent the same tasks and recordings two weeks later. Traditional and 13 non-linear indices of HRV including Poincaré, entropy and detrended fluctuation analysis (DFA) were determined. Results Time domain (especially mean R-R interval/RRI), frequency domain and, among nonlinear parameters- Poincaré and DFA were the most reliable indices. Mean RRI, time domain and Poincaré were also the most sensitive to different mental effort task loads and had the largest effect size. Conclusions Overall, linear measures were the most sensitive and reliable indices to mental effort. In non-linear measures, Poincaré was the most reliable and sensitive, suggesting possible usefulness as an independent marker in cognitive function tasks in healthy seniors. Significance A large number of HRV parameters was both reliable as well as sensitive indices of mental effort, although the simple linear methods were the most sensitive. PMID:21459665

Wavelet-based associative memory

NASA Astrophysics Data System (ADS)

Jones, Katharine J.

2004-04-01

Faces provide important characteristics of a person"s identification. In security checks, face recognition still remains the method in continuous use despite other approaches (i.e. fingerprints, voice recognition, pupil contraction, DNA scanners). With an associative memory, the output data is recalled directly using the input data. This can be achieved with a Nonlinear Holographic Associative Memory (NHAM). This approach can also distinguish between strongly correlated images and images that are partially or totally enclosed by others. Adaptive wavelet lifting has been used for Content-Based Image Retrieval. In this paper, adaptive wavelet lifting will be applied to face recognition to achieve an associative memory.

More memory under evolutionary learning may lead to chaos

NASA Astrophysics Data System (ADS)

Diks, Cees; Hommes, Cars; Zeppini, Paolo

2013-02-01

We show that an increase of memory of past strategy performance in a simple agent-based innovation model, with agents switching between costly innovation and cheap imitation, can be quantitatively stabilising while at the same time qualitatively destabilising. As memory in the fitness measure increases, the amplitude of price fluctuations decreases, but at the same time a bifurcation route to chaos may arise. The core mechanism leading to the chaotic behaviour in this model with strategy switching is that the map obtained for the system with memory is a convex combination of an increasing linear function and a decreasing non-linear function.

Noise stabilization of self-organized memories.

PubMed

Povinelli, M L; Coppersmith, S N; Kadanoff, L P; Nagel, S R; Venkataramani, S C

1999-05-01

We investigate a nonlinear dynamical system which "remembers" preselected values of a system parameter. The deterministic version of the system can encode many parameter values during a transient period, but in the limit of long times, almost all of them are forgotten. Here we show that a certain type of stochastic noise can stabilize multiple memories, enabling many parameter values to be encoded permanently. We present analytic results that provide insight both into the memory formation and into the noise-induced memory stabilization. The relevance of our results to experiments on the charge-density wave material NbSe3 is discussed.

Bandlimited computerized improvements in characterization of nonlinear systems with memory

NASA Astrophysics Data System (ADS)

Nuttall, Albert H.; Katz, Richard A.; Hughes, Derke R.; Koch, Robert M.

2016-05-01

The present article discusses some inroads in nonlinear signal processing made by the prime algorithm developer, Dr. Albert H. Nuttall and co-authors, a consortium of research scientists from the Naval Undersea Warfare Center Division, Newport, RI. The algorithm, called the Nuttall-Wiener-Volterra 'NWV' algorithm is named for its principal contributors [1], [2],[ 3] over many years of developmental research. The NWV algorithm significantly reduces the computational workload for characterizing nonlinear systems with memory. Following this formulation, two measurement waveforms on the system are required in order to characterize a specified nonlinear system under consideration: (1) an excitation input waveform, x(t) (the transmitted signal); and, (2) a response output waveform, z(t) (the received signal). Given these two measurement waveforms for a given propagation channel, a 'kernel' or 'channel response', h= [h0,h1,h2,h3] between the two measurement points, is computed via a least squares approach that optimizes modeled kernel values by performing a best fit between measured response z(t) and a modeled response y(t). New techniques significantly diminish the exponential growth of the number of computed kernel coefficients at second and third order in order to combat and reasonably alleviate the curse of dimensionality.

A Dual Super-Element Domain Decomposition Approach for Parallel Nonlinear Finite Element Analysis

NASA Astrophysics Data System (ADS)

Jokhio, G. A.; Izzuddin, B. A.

2015-05-01

This article presents a new domain decomposition method for nonlinear finite element analysis introducing the concept of dual partition super-elements. The method extends ideas from the displacement frame method and is ideally suited for parallel nonlinear static/dynamic analysis of structural systems. In the new method, domain decomposition is realized by replacing one or more subdomains in a "parent system," each with a placeholder super-element, where the subdomains are processed separately as "child partitions," each wrapped by a dual super-element along the partition boundary. The analysis of the overall system, including the satisfaction of equilibrium and compatibility at all partition boundaries, is realized through direct communication between all pairs of placeholder and dual super-elements. The proposed method has particular advantages for matrix solution methods based on the frontal scheme, and can be readily implemented for existing finite element analysis programs to achieve parallelization on distributed memory systems with minimal intervention, thus overcoming memory bottlenecks typically faced in the analysis of large-scale problems. Several examples are presented in this article which demonstrate the computational benefits of the proposed parallel domain decomposition approach and its applicability to the nonlinear structural analysis of realistic structural systems.

A vacancy-modulated self-selective resistive switching memory with pronounced nonlinear behavior

NASA Astrophysics Data System (ADS)

Ma, Haili; Feng, Jie; Gao, Tian; Zhu, Xi

2017-12-01

In this study, we report a self-selective (nonlinear) resistive switching memory cell, with high on-state half-bias nonlinearity of 650, sub-μA operating current, and high On/Off ratios above 100×. Regarding the cell structure, a thermal oxidized HfO x layer in combination with a sputtered Ta2O5 layer was configured as an active stack, with Pt and Hf as top and bottom electrodes, respectively. The Ta2O5 acts as a selective layer as well as a series resistor, which could make the resistive switching happened in HfO x layer. Through the analysis of the physicochemical properties and electrical conduction mechanisms at each state, a vacancy-modulated resistance switching model was proposed to explain the switching behavior. The conductivity of HfO x layer was changed by polarity-dependent drift of the oxygen vacancy ( V o), resulting in an electron hopping distance change during switching. With the help of Ta2O5 selective layer, high nonlinearity observed in low resistance state. The proposed material stack shows a promising prospect to act as a self-selective cell for 3D vertical RRAM application.

Engineering non-linear resonator mode interactions in circuit QED by continuous driving: Manipulation of a photonic quantum memory

NASA Astrophysics Data System (ADS)

Reagor, Matthew; Pfaff, Wolfgang; Heeres, Reinier; Ofek, Nissim; Chou, Kevin; Blumoff, Jacob; Leghtas, Zaki; Touzard, Steven; Sliwa, Katrina; Holland, Eric; Albert, Victor V.; Frunzio, Luigi; Devoret, Michel H.; Jiang, Liang; Schoelkopf, Robert J.

2015-03-01

Recent advances in circuit QED have shown great potential for using microwave resonators as quantum memories. In particular, it is possible to encode the state of a quantum bit in non-classical photonic states inside a high-Q linear resonator. An outstanding challenge is to perform controlled operations on such a photonic state. We demonstrate experimentally how a continuous drive on a transmon qubit coupled to a high-Q storage resonator can be used to induce non-linear dynamics of the resonator. Tailoring the drive properties allows us to cancel or enhance non-linearities in the system such that we can manipulate the state stored in the cavity. This approach can be used to either counteract undesirable evolution due to the bare Hamiltonian of the system or, ultimately, to perform logical operations on the state encoded in the cavity field. Our method provides a promising pathway towards performing universal control for quantum states stored in high-coherence resonators in the circuit QED platform.

Experimental Results and Issues on Equalization for Nonlinear Memory Channel: Pre-Cursor Enhanced Ram-DFE Canceler

NASA Technical Reports Server (NTRS)

Yuan, Lu; LeBlanc, James

1998-01-01

This thesis investigates the effects of the High Power Amplifier (HPA) and the filters over a satellite or telemetry channel. The Volterra series expression is presented for the nonlinear channel with memory, and the algorithm is based on the finite-state machine model. A RAM-based algorithm operating on the receiver side, Pre-cursor Enhanced RAM-FSE Canceler (PERC) is developed. A high order modulation scheme , 16-QAM is used for simulation, the results show that PERC provides an efficient and reliable method to transmit data on the bandlimited nonlinear channel. The contribution of PERC algorithm is that it includes both pre-cursors and post-cursors as the RAM address lines, and suggests a new way to make decision on the pre-addresses. Compared with the RAM-DFE structure that only includes post- addresses, the BER versus Eb/NO performance of PERC is substantially enhanced. Experiments are performed for PERC algorithms with different parameters on AWGN channels, and the results are compared and analyzed. The investigation of this thesis includes software simulation and hardware verification. Hardware is setup to collect actual TWT data. Simulation on both the software-generated data and the real-world data are performed. Practical limitations are considered for the hardware collected data. Simulation results verified the reliability of the PERC algorithm. This work was conducted at NMSU in the Center for Space Telemetering and Telecommunications Systems in the Klipsch School of Electrical and Computer Engineering Department.

Control of an innovative super-capacitor-powered shape-memory-alloy actuated accumulator for blowout preventer

NASA Astrophysics Data System (ADS)

Chen, Jian; Li, Peng; Song, Gangbing; Ren, Zhang

2017-01-01

The design of a super-capacitor-powered shape-memory-alloy (SMA) actuated accumulator for blowout preventer (BOP) presented in this paper featured several advantages over conventional hydraulic accumulators including instant large current drive, quick system response and elimination of need for the pressure conduits. However, the mechanical design introduced two challenges, the nonlinear nature of SMA actuators and the varying voltage provided by a super capacitor, for control system design. A cerebellar model articulation controller (CMAC) feedforward plus PID controller was developed with the aim of compensation for these adverse effects. Experiments were conducted on a scaled down model and experimental results show that precision control can be achieved with the proposed configurations and algorithms.

Simulation program of nonlinearities applied to telecommunication systems

NASA Technical Reports Server (NTRS)

Thomas, C.

1979-01-01

In any satellite communication system, the problems of distorsion created by nonlinear devices or systems must be considered. The subject of this paper is the use of the Fast Fourier Transform (F.F.T.) in the prediction of the intermodulation performance of amplifiers, mixers, filters. A nonlinear memory-less model is chosen to simulate amplitude and phase nonlinearities of the device in the simulation program written in FORTRAN 4. The experimentally observed nonlinearity parameters of a low noise 3.7-4.2 GHz amplifier are related to the gain and phase coefficients of Fourier Service Series. The measured results are compared with those calculated from the simulation in the cases where the input signal is composed of two, three carriers and noise power density.

Nonlinear responses within the medial prefrontal cortex reveal when specific implicit information influences economic decision making.

PubMed

Deppe, Michael; Schwindt, Wolfram; Kugel, Harald; Plassmann, Hilke; Kenning, Peter

2005-04-01

The authors used functional magnetic resonance imaging (fMRI) to investigate how individual economic decisions are influenced by implicit memory contributions. Twenty-two participants were asked to make binary decisions between different brands of sensorily nearly undistinguishable consumer goods. Changes of brain activity comparing decisions in the presence or absence of a specific target brand were detected by fMRI. Only when the tar get brand was the participant's favorite one did the authors find reduced activation in the dorsolateral prefrontal, posterior parietal, and occipital cortices and the left premotor area (Brodmann areas [BA] 9, 46, 7/19, and 6). Simultaneously, activity was increased in the inferior precuneus and posterior cingulate (BA 7), right superior frontal gyrus (BA 10), right supramarginal gyrus (BA 40), and, most pronounced, in the ventromedial prefrontal cortex (BA 10). For products mainly distinguishable by brand information, the authors revealed a nonlinear winner-take-all effect for a participant's favorite brand characterized, on one hand, by reduced activation in brain areas associated with working memory and reasoning and, on the other hand, increased activation in areas involved in processing of emotions and self-reflections during decision making.

Potential implementation of reservoir computing models based on magnetic skyrmions

NASA Astrophysics Data System (ADS)

Bourianoff, George; Pinna, Daniele; Sitte, Matthias; Everschor-Sitte, Karin

2018-05-01

Reservoir Computing is a type of recursive neural network commonly used for recognizing and predicting spatio-temporal events relying on a complex hierarchy of nested feedback loops to generate a memory functionality. The Reservoir Computing paradigm does not require any knowledge of the reservoir topology or node weights for training purposes and can therefore utilize naturally existing networks formed by a wide variety of physical processes. Most efforts to implement reservoir computing prior to this have focused on utilizing memristor techniques to implement recursive neural networks. This paper examines the potential of magnetic skyrmion fabrics and the complex current patterns which form in them as an attractive physical instantiation for Reservoir Computing. We argue that their nonlinear dynamical interplay resulting from anisotropic magnetoresistance and spin-torque effects allows for an effective and energy efficient nonlinear processing of spatial temporal events with the aim of event recognition and prediction.

Towards representation of a perceptual color manifold using associative memory for color constancy.

PubMed

Seow, Ming-Jung; Asari, Vijayan K

2009-01-01

In this paper, we propose the concept of a manifold of color perception through empirical observation that the center-surround properties of images in a perceptually similar environment define a manifold in the high dimensional space. Such a manifold representation can be learned using a novel recurrent neural network based learning algorithm. Unlike the conventional recurrent neural network model in which the memory is stored in an attractive fixed point at discrete locations in the state space, the dynamics of the proposed learning algorithm represent memory as a nonlinear line of attraction. The region of convergence around the nonlinear line is defined by the statistical characteristics of the training data. This learned manifold can then be used as a basis for color correction of the images having different color perception to the learned color perception. Experimental results show that the proposed recurrent neural network learning algorithm is capable of color balance the lighting variations in images captured in different environments successfully.

Thermodynamic restrictions on the constitutive equations of electromagnetic theory

NASA Technical Reports Server (NTRS)

Coleman, B. D.; Dill, E. H.

1971-01-01

Thermodynamics second law restrictions on constitutive equations of electromagnetic theory for nonlinear materials with long-range gradually fading memory, considering dissipation principle consequences

Dosage-dependent non-linear effect of L-dopa on human motor cortex plasticity.

PubMed

Monte-Silva, Katia; Liebetanz, David; Grundey, Jessica; Paulus, Walter; Nitsche, Michael A

2010-09-15

The neuromodulator dopamine affects learning and memory formation and their likely physiological correlates, long-term depression and potentiation, in animals and humans. It is known from animal experiments that dopamine exerts a dosage-dependent, inverted U-shaped effect on these functions. However, this has not been explored in humans so far. In order to reveal a non-linear dose-dependent effect of dopamine on cortical plasticity in humans, we explored the impact of 25, 100 and 200 mg of L-dopa on transcranial direct current (tDCS)-induced plasticity in twelve healthy human subjects. The primary motor cortex served as a model system, and plasticity was monitored by motor evoked potential amplitudes elicited by transcranial magnetic stimulation. As compared to placebo medication, low and high dosages of L-dopa abolished facilitatory as well as inhibitory plasticity, whereas the medium dosage prolonged inhibitory plasticity, and turned facilitatory plasticity into inhibition. Thus the results show clear non-linear, dosage-dependent effects of dopamine on both facilitatory and inhibitory plasticity, and support the assumption of the importance of a specific dosage of dopamine optimally suited to improve plasticity. This might be important for the therapeutic application of dopaminergic agents, especially for rehabilitative purposes, and explain some opposing results in former studies.

The Effects of Home-Based Cognitive Training on Verbal Working Memory and Language Comprehension in Older Adulthood

PubMed Central

Payne, Brennan R.; Stine-Morrow, Elizabeth A. L.

2017-01-01

Effective language understanding is crucial to maintaining cognitive abilities and learning new information through adulthood. However, age-related declines in working memory (WM) have a robust negative influence on multiple aspects of language comprehension and use, potentially limiting communicative competence. In the current study (N = 41), we examined the effects of a novel home-based computerized cognitive training program targeting verbal WM on changes in verbal WM and language comprehension in healthy older adults relative to an active component-control group. Participants in the WM training group showed non-linear improvements in performance on trained verbal WM tasks. Relative to the active control group, WM training participants also showed improvements on untrained verbal WM tasks and selective improvements across untrained dimensions of language, including sentence memory, verbal fluency, and comprehension of syntactically ambiguous sentences. Though the current study is preliminary in nature, it does provide initial promising evidence that WM training may influence components of language comprehension in adulthood and suggests that home-based training of WM may be a viable option for probing the scope and limits of cognitive plasticity in older adults. PMID:28848421

The Effects of Home-Based Cognitive Training on Verbal Working Memory and Language Comprehension in Older Adulthood.

PubMed

Payne, Brennan R; Stine-Morrow, Elizabeth A L

2017-01-01

Effective language understanding is crucial to maintaining cognitive abilities and learning new information through adulthood. However, age-related declines in working memory (WM) have a robust negative influence on multiple aspects of language comprehension and use, potentially limiting communicative competence. In the current study ( N = 41), we examined the effects of a novel home-based computerized cognitive training program targeting verbal WM on changes in verbal WM and language comprehension in healthy older adults relative to an active component-control group. Participants in the WM training group showed non-linear improvements in performance on trained verbal WM tasks. Relative to the active control group, WM training participants also showed improvements on untrained verbal WM tasks and selective improvements across untrained dimensions of language, including sentence memory, verbal fluency, and comprehension of syntactically ambiguous sentences. Though the current study is preliminary in nature, it does provide initial promising evidence that WM training may influence components of language comprehension in adulthood and suggests that home-based training of WM may be a viable option for probing the scope and limits of cognitive plasticity in older adults.

The Influence of Metacognitive Skills on Learners' Memory of Information in a Hypermedia Environment

ERIC Educational Resources Information Center

Schwartz, Neil H.; Andersen, Christopher; Hong, Namsoo; Howard, Bruce; McGee, Steven

2004-01-01

Twenty-eight students (aged 9 to 17) freely explored a science Web site structured either in an outline (linear) format or "puzzle" (non-linear) format for 2.5 hours. Subjects then engaged in tasks involving locational memory and informational recall. The results indicate that presence of metacognitive skills was a necessary but not sufficient…

Global similarity predicts dissociation of classification and recognition: evidence questioning the implicit-explicit learning distinction in amnesia.

PubMed

Jamieson, Randall K; Holmes, Signy; Mewhort, D J K

2010-11-01

Dissociation of classification and recognition in amnesia is widely taken to imply 2 functional systems: an implicit procedural-learning system that is spared in amnesia and an explicit episodic-learning system that is compromised. We argue that both tasks reflect the global similarity of probes to memory. In classification, subjects sort unstudied grammatical exemplars from lures, whereas in recognition, they sort studied grammatical exemplars from lures. Hence, global similarity is necessarily greater in recognition than in classification. Moreover, a grammatical exemplar's similarity to studied exemplars is a nonlinear function of the integrity of the data in memory. Assuming that data integrity is better for control subjects than for subjects with amnesia, the nonlinear relation combined with the advantage for recognition over classification predicts the dissociation of recognition and classification. To illustrate the dissociation of recognition and classification in healthy undergraduates, we manipulated study time to vary the integrity of the data in memory and brought the dissociation under experimental control. We argue that the dissociation reflects a general cost in memory rather than a selective impairment of separate procedural and episodic systems. (c) 2010 APA, all rights reserved

Potential of minicomputer/array-processor system for nonlinear finite-element analysis

NASA Technical Reports Server (NTRS)

Strohkorb, G. A.; Noor, A. K.

1983-01-01

The potential of using a minicomputer/array-processor system for the efficient solution of large-scale, nonlinear, finite-element problems is studied. A Prime 750 is used as the host computer, and a software simulator residing on the Prime is employed to assess the performance of the Floating Point Systems AP-120B array processor. Major hardware characteristics of the system such as virtual memory and parallel and pipeline processing are reviewed, and the interplay between various hardware components is examined. Effective use of the minicomputer/array-processor system for nonlinear analysis requires the following: (1) proper selection of the computational procedure and the capability to vectorize the numerical algorithms; (2) reduction of input-output operations; and (3) overlapping host and array-processor operations. A detailed discussion is given of techniques to accomplish each of these tasks. Two benchmark problems with 1715 and 3230 degrees of freedom, respectively, are selected to measure the anticipated gain in speed obtained by using the proposed algorithms on the array processor.

A boost of confidence: The role of the ventromedial prefrontal cortex in memory, decision-making, and schemas.

PubMed

Hebscher, Melissa; Gilboa, Asaf

2016-09-01

The ventromedial prefrontal cortex (vmPFC) has been implicated in a wide array of functions across multiple domains. In this review, we focus on the vmPFC's involvement in mediating strategic aspects of memory retrieval, memory-related schema functions, and decision-making. We suggest that vmPFC generates a confidence signal that informs decisions and memory-guided behaviour. Confidence is central to these seemingly diverse functions: (1) Strategic retrieval: lesions to the vmPFC impair an early, automatic, and intuitive monitoring process ("feeling of rightness"; FOR) often associated with confabulation (spontaneous reporting of erroneous memories). Critically, confabulators typically demonstrate high levels of confidence in their false memories, suggesting that faulty monitoring following vmPFC damage may lead to indiscriminate confidence signals. (2) Memory schemas: the vmPFC is critically involved in instantiating and maintaining contextually relevant schemas, broadly defined as higher level knowledge structures that encapsulate lower level representational elements. The correspondence between memory retrieval cues and these activated schemas leads to FOR monitoring. Stronger, more elaborate schemas produce stronger FOR and influence confidence in the veracity of memory candidates. (3) Finally, we review evidence on the vmPFC's role in decision-making, extending this role to decision-making during memory retrieval. During non-mnemonic and mnemonic decision-making the vmPFC automatically encodes confidence. Confidence signal in the vmPFC is revealed as a non-linear relationship between a first-order monitoring assessment and second-order action or choice. Attempting to integrate the multiple functions of the vmPFC, we propose a posterior-anterior organizational principle for this region. More posterior vmPFC regions are involved in earlier, automatic, subjective, and contextually sensitive functions, while more anterior regions are involved in controlled actions based on these earlier functions. Confidence signals reflect the non-linear relationship between first-order, posterior-mediated and second-order, anterior-mediated processes and are represented along the entire axis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Academician Nikolai Nikolaevich Bogolyubov (for the 100th anniversary of his birth)

NASA Astrophysics Data System (ADS)

Martynyuk, A. A.; Mishchenko, E. F.; Samoilenko, A. M.; Sukhanov, A. D.

2009-07-01

This paper is dedicated to the memory of N. N. Bogolyubov in recognition of his towering stature in nonlinear mechanics and theoretical physics, his remarkable many-sided genius, and the originality and depth of his contribution to the world's science. The paper briefly describes Bogolyubov's achievements in nonlinear mechanics, classical statistical physics, theory of superconductivity, quantum field theory, and strong interaction theory

Numerical Analysis of Modeling Based on Improved Elman Neural Network

PubMed Central

Jie, Shao

2014-01-01

A modeling based on the improved Elman neural network (IENN) is proposed to analyze the nonlinear circuits with the memory effect. The hidden layer neurons are activated by a group of Chebyshev orthogonal basis functions instead of sigmoid functions in this model. The error curves of the sum of squared error (SSE) varying with the number of hidden neurons and the iteration step are studied to determine the number of the hidden layer neurons. Simulation results of the half-bridge class-D power amplifier (CDPA) with two-tone signal and broadband signals as input have shown that the proposed behavioral modeling can reconstruct the system of CDPAs accurately and depict the memory effect of CDPAs well. Compared with Volterra-Laguerre (VL) model, Chebyshev neural network (CNN) model, and basic Elman neural network (BENN) model, the proposed model has better performance. PMID:25054172

Buy three but get only two: the smallest effect in a 2 × 2 ANOVA is always uninterpretable.

PubMed

Garcia-Marques, Leonel; Garcia-Marques, Teresa; Brauer, Markus

2014-12-01

Loftus (Memory & Cognition 6:312-319, 1978) distinguished between interpretable and uninterpretable interactions. Uninterpretable interactions are ambiguous, because they may be due to two additive main effects (no interaction) and a nonlinear relationship between the (latent) outcome variable and its indicator. Interpretable interactions can only be due to the presence of a true interactive effect in the outcome variable, regardless of the relationship that it establishes with its indicator. In the present article, we first show that same problem can arise when an unmeasured mediator has a nonlinear effect on the measured outcome variable. Then we integrate Loftus's arguments with a seemingly contradictory approach to interactions suggested by Rosnow and Rosenthal (Psychological Bulletin 105:143-146, 1989). We show that entire data patterns, not just interaction effects alone, produce interpretable or noninterpretable interactions. Next, we show that the same problem of interpretability can apply to main effects. Lastly, we give concrete advice on what researchers can do to generate data patterns that provide unambiguous evidence for hypothesized interactions.

Self-consistent modelling of electrochemical strain microscopy in mixed ionic-electronic conductors: Nonlinear and dynamic regimes

DOE PAGES

Varenyk, O. V.; Silibin, M. V.; Kiselev, Dmitri A.; ...

2015-08-19

The frequency dependent Electrochemical Strain Microscopy (ESM) response of mixed ionic-electronic conductors is analyzed within the framework of Fermi-Dirac statistics and the Vegard law, accounting for steric effects from mobile donors. The emergence of dynamic charge waves and nonlinear deformation of the surface in response to bias applied to the tip-surface junction is numerically explored. The 2D maps of the strain and concentration distributions across the mixed ionic-electronic conductor and bias-induced surface displacements are calculated. Furthermore, the obtained numerical results can be applied to quantify the ESM response of Li-based solid electrolytes, materials with resistive switching, and electroactive ferroelectric polymers,more » which are of potential interest for flexible and high-density non-volatile memory devices.« less

Self-consistent modelling of electrochemical strain microscopy in mixed ionic-electronic conductors: Nonlinear and dynamic regimes

NASA Astrophysics Data System (ADS)

Varenyk, O. V.; Silibin, M. V.; Kiselev, D. A.; Eliseev, E. A.; Kalinin, S. V.; Morozovska, A. N.

2015-08-01

The frequency dependent Electrochemical Strain Microscopy (ESM) response of mixed ionic-electronic conductors is analyzed within the framework of Fermi-Dirac statistics and the Vegard law, accounting for steric effects from mobile donors. The emergence of dynamic charge waves and nonlinear deformation of the surface in response to bias applied to the tip-surface junction is numerically explored. The 2D maps of the strain and concentration distributions across the mixed ionic-electronic conductor and bias-induced surface displacements are calculated. The obtained numerical results can be applied to quantify the ESM response of Li-based solid electrolytes, materials with resistive switching, and electroactive ferroelectric polymers, which are of potential interest for flexible and high-density non-volatile memory devices.

An efficient interior-point algorithm with new non-monotone line search filter method for nonlinear constrained programming

NASA Astrophysics Data System (ADS)

Wang, Liwei; Liu, Xinggao; Zhang, Zeyin

2017-02-01

An efficient primal-dual interior-point algorithm using a new non-monotone line search filter method is presented for nonlinear constrained programming, which is widely applied in engineering optimization. The new non-monotone line search technique is introduced to lead to relaxed step acceptance conditions and improved convergence performance. It can also avoid the choice of the upper bound on the memory, which brings obvious disadvantages to traditional techniques. Under mild assumptions, the global convergence of the new non-monotone line search filter method is analysed, and fast local convergence is ensured by second order corrections. The proposed algorithm is applied to the classical alkylation process optimization problem and the results illustrate its effectiveness. Some comprehensive comparisons to existing methods are also presented.

Photonic single nonlinear-delay dynamical node for information processing

NASA Astrophysics Data System (ADS)

Ortín, Silvia; San-Martín, Daniel; Pesquera, Luis; Gutiérrez, José Manuel

2012-06-01

An electro-optical system with a delay loop based on semiconductor lasers is investigated for information processing by performing numerical simulations. This system can replace a complex network of many nonlinear elements for the implementation of Reservoir Computing. We show that a single nonlinear-delay dynamical system has the basic properties to perform as reservoir: short-term memory and separation property. The computing performance of this system is evaluated for two prediction tasks: Lorenz chaotic time series and nonlinear auto-regressive moving average (NARMA) model. We sweep the parameters of the system to find the best performance. The results achieved for the Lorenz and the NARMA-10 tasks are comparable to those obtained by other machine learning methods.

Thermodynamic Model of Spatial Memory

NASA Astrophysics Data System (ADS)

Kaufman, Miron; Allen, P.

1998-03-01

We develop and test a thermodynamic model of spatial memory. Our model is an application of statistical thermodynamics to cognitive science. It is related to applications of the statistical mechanics framework in parallel distributed processes research. Our macroscopic model allows us to evaluate an entropy associated with spatial memory tasks. We find that older adults exhibit higher levels of entropy than younger adults. Thurstone's Law of Categorical Judgment, according to which the discriminal processes along the psychological continuum produced by presentations of a single stimulus are normally distributed, is explained by using a Hooke spring model of spatial memory. We have also analyzed a nonlinear modification of the ideal spring model of spatial memory. This work is supported by NIH/NIA grant AG09282-06.

Explicit time integration of finite element models on a vectorized, concurrent computer with shared memory

NASA Technical Reports Server (NTRS)

Gilbertsen, Noreen D.; Belytschko, Ted

1990-01-01

The implementation of a nonlinear explicit program on a vectorized, concurrent computer with shared memory is described and studied. The conflict between vectorization and concurrency is described and some guidelines are given for optimal block sizes. Several example problems are summarized to illustrate the types of speed-ups which can be achieved by reprogramming as compared to compiler optimization.

Nonlinear Associations between Plasma Cholesterol Levels and Neuropsychological Function

PubMed Central

Wendell, Carrington R.; Zonderman, Alan B.; Katzel, Leslie I.; Rosenberger, William F.; Plamadeala, Victoria V.; Hosey, Megan M.; Waldstein, Shari R.

2016-01-01

Objective Although both high and low levels of total and low-density lipoprotein (LDL) cholesterol have been associated with poor neuropsychological function, little research has examined nonlinear effects. We examined quadratic relations of cholesterol to performance on a comprehensive neuropsychological battery. Method Participants were 190 older adults (53% men, ages 54–83) free of major medical, neurologic, and psychiatric disease. Measures of fasting plasma total and high-density lipoprotein (HDL) cholesterol were assayed, and LDL cholesterol was calculated. Participants completed neuropsychological measures of attention, executive function, memory, visuospatial judgment, and manual speed/dexterity. Multiple regression analyses examined cholesterol levels as quadratic predictors of each measure of cognitive performance, with age (dichotomized as <70 vs. 70+) as an effect modifier. Results A significant quadratic effect of total cholesterol2 × age was identified for Logical Memory II (b=−.0013, p=.039), such that the 70+ group performed best at high and low levels of total cholesterol than at mid-range total cholesterol (U-shaped), and the <70 group performed worse at high and low levels of total cholesterol than at mid-range total cholesterol (inverted U-shape). Similarly, significant U- and J-shaped effects of LDL cholesterol2 × age were identified for Visual Reproduction II (b=−.0020, p=.026) and log of Trails B (b=.0001, p=.044). Quadratic associations between HDL cholesterol and cognitive performance were nonsignificant. Conclusions Results indicate differential associations between cholesterol and neuropsychological function across different ages and domains of function. High and low total and LDL cholesterol may confer both risk and benefit for suboptimal cognitive function at different ages. PMID:27280580

Quantification of Load Dependent Brain Activity in Parametric N-Back Working Memory Tasks using Pseudo-continuous Arterial Spin Labeling (pCASL) Perfusion Imaging.

PubMed

Zou, Qihong; Gu, Hong; Wang, Danny J J; Gao, Jia-Hong; Yang, Yihong

2011-04-01

Brain activation and deactivation induced by N-back working memory tasks and their load effects have been extensively investigated using positron emission tomography (PET) and blood-oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI). However, the underlying mechanisms of BOLD fMRI are still not completely understood and PET imaging requires injection of radioactive tracers. In this study, a pseudo-continuous arterial spin labeling (pCASL) perfusion imaging technique was used to quantify cerebral blood flow (CBF), a well understood physiological index reflective of cerebral metabolism, in N-back working memory tasks. Using pCASL, we systematically investigated brain activation and deactivation induced by the N-back working memory tasks and further studied the load effects on brain activity based on quantitative CBF. Our data show increased CBF in the fronto-parietal cortices, thalamus, caudate, and cerebellar regions, and decreased CBF in the posterior cingulate cortex and medial prefrontal cortex, during the working memory tasks. Most of the activated/deactivated brain regions show an approximately linear relationship between CBF and task loads (0, 1, 2 and 3 back), although several regions show non-linear relationships (quadratic and cubic). The CBF-based spatial patterns of brain activation/deactivation and load effects from this study agree well with those obtained from BOLD fMRI and PET techniques. These results demonstrate the feasibility of ASL techniques to quantify human brain activity during high cognitive tasks, suggesting its potential application to assessing the mechanisms of cognitive deficits in neuropsychiatric and neurological disorders.

Nonlinear magnetoacoustic wave propagation with chemical reactions

NASA Astrophysics Data System (ADS)

Margulies, Timothy Scott

2002-11-01

The magnetoacoustic problem with an application to sound wave propagation through electrically conducting fluids such as the ocean in the Earth's magnetic field, liquid metals, or plasmas has been addressed taking into account several simultaneous chemical reactions. Using continuum balance equations for the total mass, linear momentum, energy; as well as Maxwell's electrodynamic equations, a nonlinear beam equation has been developed to generalize the Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation for a fluid with linear viscosity but nonlinear and diffraction effects. Thermodynamic parameters are used and not tailored to only an adiabatic fluid case. The chemical kinetic equations build on a relaxing media approach presented, for example, by K. Naugolnukh and L. Ostrovsky [Nonlinear Wave Processes in Acoustics (Cambridge Univ. Press, Cambridge, 1998)] for a linearized single reaction and thermodynamic pressure equation of state. Approximations for large and small relaxation times and for magnetohydrodynamic parameters [Korsunskii, Sov. Phys. Acoust. 36 (1990)] are examined. Additionally, Cattaneo's equation for heat conduction and its generalization for a memory process rather than a Fourier's law are taken into account. It was introduced for the heat flux depends on the temperature gradient at an earlier time to generate heat pulses of finite speed.

Quantum memories: emerging applications and recent advances

NASA Astrophysics Data System (ADS)

Heshami, Khabat; England, Duncan G.; Humphreys, Peter C.; Bustard, Philip J.; Acosta, Victor M.; Nunn, Joshua; Sussman, Benjamin J.

2016-11-01

Quantum light-matter interfaces are at the heart of photonic quantum technologies. Quantum memories for photons, where non-classical states of photons are mapped onto stationary matter states and preserved for subsequent retrieval, are technical realizations enabled by exquisite control over interactions between light and matter. The ability of quantum memories to synchronize probabilistic events makes them a key component in quantum repeaters and quantum computation based on linear optics. This critical feature has motivated many groups to dedicate theoretical and experimental research to develop quantum memory devices. In recent years, exciting new applications, and more advanced developments of quantum memories, have proliferated. In this review, we outline some of the emerging applications of quantum memories in optical signal processing, quantum computation and non-linear optics. We review recent experimental and theoretical developments, and their impacts on more advanced photonic quantum technologies based on quantum memories.

One bipolar transistor selector - One resistive random access memory device for cross bar memory array

NASA Astrophysics Data System (ADS)

Aluguri, R.; Kumar, D.; Simanjuntak, F. M.; Tseng, T.-Y.

2017-09-01

A bipolar transistor selector was connected in series with a resistive switching memory device to study its memory characteristics for its application in cross bar array memory. The metal oxide based p-n-p bipolar transistor selector indicated good selectivity of about 104 with high retention and long endurance showing its usefulness in cross bar RRAM devices. Zener tunneling is found to be the main conduction phenomena for obtaining high selectivity. 1BT-1R device demonstrated good memory characteristics with non-linearity of 2 orders, selectivity of about 2 orders and long retention characteristics of more than 105 sec. One bit-line pull-up scheme shows that a 650 kb cross bar array made with this 1BT1R devices works well with more than 10 % read margin proving its ability in future memory technology application.

Quantum memories: emerging applications and recent advances.

PubMed

Heshami, Khabat; England, Duncan G; Humphreys, Peter C; Bustard, Philip J; Acosta, Victor M; Nunn, Joshua; Sussman, Benjamin J

2016-11-12

Quantum light-matter interfaces are at the heart of photonic quantum technologies. Quantum memories for photons, where non-classical states of photons are mapped onto stationary matter states and preserved for subsequent retrieval, are technical realizations enabled by exquisite control over interactions between light and matter. The ability of quantum memories to synchronize probabilistic events makes them a key component in quantum repeaters and quantum computation based on linear optics. This critical feature has motivated many groups to dedicate theoretical and experimental research to develop quantum memory devices. In recent years, exciting new applications, and more advanced developments of quantum memories, have proliferated. In this review, we outline some of the emerging applications of quantum memories in optical signal processing, quantum computation and non-linear optics. We review recent experimental and theoretical developments, and their impacts on more advanced photonic quantum technologies based on quantum memories.

Quantum memories: emerging applications and recent advances

PubMed Central

Heshami, Khabat; England, Duncan G.; Humphreys, Peter C.; Bustard, Philip J.; Acosta, Victor M.; Nunn, Joshua; Sussman, Benjamin J.

2016-01-01

Quantum light–matter interfaces are at the heart of photonic quantum technologies. Quantum memories for photons, where non-classical states of photons are mapped onto stationary matter states and preserved for subsequent retrieval, are technical realizations enabled by exquisite control over interactions between light and matter. The ability of quantum memories to synchronize probabilistic events makes them a key component in quantum repeaters and quantum computation based on linear optics. This critical feature has motivated many groups to dedicate theoretical and experimental research to develop quantum memory devices. In recent years, exciting new applications, and more advanced developments of quantum memories, have proliferated. In this review, we outline some of the emerging applications of quantum memories in optical signal processing, quantum computation and non-linear optics. We review recent experimental and theoretical developments, and their impacts on more advanced photonic quantum technologies based on quantum memories. PMID:27695198

Tunneling Electroresistance Effect with Diode Characteristic for Cross-Point Memory.

PubMed

Lee, Hong-Sub; Park, Hyung-Ho

2016-06-22

Cross-point memory architecture (CPMA) by using memristors has attracted considerable attention because of its high-density integration. However, a common and significant drawback of the CPMA is related to crosstalk issues between cells by sneak currents. This study demonstrated the sneak current free resistive switching characteristic of a ferroelectric tunnel diode (FTD) memristor for a CPMA by utilizing a novel concept of a ferroelectric quadrangle and triangle barrier switch. A FTD of Au/BaTiO3 (5 nm)/Nb-doped SrTiO3 (100) was used to obtain a desirable memristive effect for the CPMA. The FTD could reversibly change the shape of the ferroelectric potential from a quadrangle to a triangle. The effect included high nonlinearity and diode characteristics. It was derived from utilizing different sequences of carrier transport mechanisms such as the direct tunneling current, Fowler-Nordheim tunneling, and thermionic emission. The FTD memristor demonstrated the feasibility of sneak current-free high-density CPMA.

On the Existence of a Free Boundary for a Class of Reaction-Diffusion Systems.

DTIC Science & Technology

1982-02-01

I. Diaz. "Soluciones con soporte compacto para alguno. problemas semilineales". Collect. Math. 30 (1979), 141-179. -26- [121 J. I. Diaz. Tecnica de ...supersoluciones locales para problemas estacionarios no lineales: applicacion al estudio de flujoe subsonicos. Memory of the Real Academia de Ciencias...nonlinearity, nonlinear boundary conditions, dead core set, chemical reactions Work Unit Number I - Applied Analysis (1) Seccion de Matematicas

A multistate pH-triggered nonlinear optical switch.

PubMed

Castet, Frédéric; Champagne, Benoît; Pina, Fernando; Rodriguez, Vincent

2014-08-04

By using hyper-Rayleigh scattering experiments and quantum-chemical calculations, we demonstrate that nonlinear optics can be used to probe unequivocally, within a non-destructive process, the multiple electronic states that are activated upon pH- and light-triggered transformations of the 4'-hydroxyflavylium ion. These results open new perspectives in the design of molecular-scale high-density optical memory. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Sensitivity to mental effort and test-retest reliability of heart rate variability measures in healthy seniors.

PubMed

Mukherjee, Shalini; Yadav, Rajeev; Yung, Iris; Zajdel, Daniel P; Oken, Barry S

2011-10-01

To determine (1) whether heart rate variability (HRV) was a sensitive and reliable measure in mental effort tasks carried out by healthy seniors and (2) whether non-linear approaches to HRV analysis, in addition to traditional time and frequency domain approaches were useful to study such effects. Forty healthy seniors performed two visual working memory tasks requiring different levels of mental effort, while ECG was recorded. They underwent the same tasks and recordings 2 weeks later. Traditional and 13 non-linear indices of HRV including Poincaré, entropy and detrended fluctuation analysis (DFA) were determined. Time domain, especially mean R-R interval (RRI), frequency domain and, among non-linear parameters - Poincaré and DFA were the most reliable indices. Mean RRI, time domain and Poincaré were also the most sensitive to different mental effort task loads and had the largest effect size. Overall, linear measures were the most sensitive and reliable indices to mental effort. In non-linear measures, Poincaré was the most reliable and sensitive, suggesting possible usefulness as an independent marker in cognitive function tasks in healthy seniors. A large number of HRV parameters was both reliable as well as sensitive indices of mental effort, although the simple linear methods were the most sensitive. Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Super Nonlinear Electrodeposition-Diffusion-Controlled Thin-Film Selector.

PubMed

Ji, Xinglong; Song, Li; He, Wei; Huang, Kejie; Yan, Zhiyuan; Zhong, Shuai; Zhang, Yishu; Zhao, Rong

2018-03-28

Selector elements with high nonlinearity are an indispensable part in constructing high density, large-scale, 3D stackable emerging nonvolatile memory and neuromorphic network. Although significant efforts have been devoted to developing novel thin-film selectors, it remains a great challenge in achieving good switching performance in the selectors to satisfy the stringent electrical criteria of diverse memory elements. In this work, we utilized high-defect-density chalcogenide glass (Ge 2 Sb 2 Te 5 ) in conjunction with high mobility Ag element (Ag-GST) to achieve a super nonlinear selective switching. A novel electrodeposition-diffusion dynamic selector based on Ag-GST exhibits superior selecting performance including excellent nonlinearity (<5 mV/dev), ultra-low leakage (<10 fA), and bidirectional operation. With the solid microstructure evidence and dynamic analyses, we attributed the selective switching to the competition between the electrodeposition and diffusion of Ag atoms in the glassy GST matrix under electric field. A switching model is proposed, and the in-depth understanding of the selective switching mechanism offers an insight of switching dynamics for the electrodeposition-diffusion-controlled thin-film selector. This work opens a new direction of selector designs by combining high mobility elements and high-defect-density chalcogenide glasses, which can be extended to other materials with similar properties.

Chaotic vibrations of the duffing system with fractional damping

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

Syta, Arkadiusz; Litak, Grzegorz; Lenci, Stefano

2014-03-15

We examined the Duffing system with a fractional damping term. Calculating the basins of attraction, we demonstrate a broad spectrum of non-linear behaviour connected with sensitivity to the initial conditions and chaos. To quantify dynamical response of the system, we propose the statistical 0-1 test as well as the maximal Lyapunov exponent; the application of the latter encounter a few difficulties because of the memory effect due to the fractional derivative. The results are confirmed by bifurcation diagrams, phase portraits, and Poincaré sections.

Information processing via physical soft body

PubMed Central

Nakajima, Kohei; Hauser, Helmut; Li, Tao; Pfeifer, Rolf

2015-01-01

Soft machines have recently gained prominence due to their inherent softness and the resulting safety and resilience in applications. However, these machines also have disadvantages, as they respond with complex body dynamics when stimulated. These dynamics exhibit a variety of properties, including nonlinearity, memory, and potentially infinitely many degrees of freedom, which are often difficult to control. Here, we demonstrate that these seemingly undesirable properties can in fact be assets that can be exploited for real-time computation. Using body dynamics generated from a soft silicone arm, we show that they can be employed to emulate desired nonlinear dynamical systems. First, by using benchmark tasks, we demonstrate that the nonlinearity and memory within the body dynamics can increase the computational performance. Second, we characterize our system’s computational capability by comparing its task performance with a standard machine learning technique and identify its range of validity and limitation. Our results suggest that soft bodies are not only impressive in their deformability and flexibility but can also be potentially used as computational resources on top and for free. PMID:26014748

Theory and modeling of atmospheric turbulence, part 1

NASA Technical Reports Server (NTRS)

1984-01-01

The cascade transfer which is the only function to describe the mode coupling as the result of the nonlinear hydrodynamic state of turbulence is discussed. A kinetic theory combined with a scaling procedure was developed. The transfer function governs the non-linear mode coupling in strong turbulence. The master equation is consistent with the hydrodynamical system that describes the microdynamic state of turbulence and has the advantages to be homogeneous and have fewer nonlinear terms. The modes are scaled into groups to decipher the governing transport processes and statistical characteristics. An equation of vorticity transport describes the microdynamic state of two dimensional, isotropic and homogeneous, geostrophic turbulence. The equation of evolution of the macrovorticity is derived from group scaling in the form of the Fokker-Planck equation with memory. The microdynamic state of turbulence is transformed into the Liouville equation to derive the kinetic equation of the singlet distribution in turbulence. The collision integral contains a memory, which is analyzed with pair collision and the multiple collision. Two other kinetic equations are developed in parallel for the propagator and the transition probability for the interaction among the groups.

Two-dimensional signal processing using a morphological filter for holographic memory

NASA Astrophysics Data System (ADS)

Kondo, Yo; Shigaki, Yusuke; Yamamoto, Manabu

2012-03-01

Today, along with the wider use of high-speed information networks and multimedia, it is increasingly necessary to have higher-density and higher-transfer-rate storage devices. Therefore, research and development into holographic memories with three-dimensional storage areas is being carried out to realize next-generation large-capacity memories. However, in holographic memories, interference between bits, which affect the detection characteristics, occurs as a result of aberrations such as the deviation of a wavefront in an optical system. In this study, we pay particular attention to the nonlinear factors that cause bit errors, where filters with a Volterra equalizer and the morphologies are investigated as a means of signal processing.

Chaotic patterns of autonomic activity during hypnotic recall.

PubMed

Bob, Petr; Siroka, Ivana; Susta, Marek

2009-01-01

Chaotic neural dynamics likely emerge in cognitive processes and may present time periods that are extremely sensitive to influences affecting the neural system. Recent findings suggest that this sensitivity may increase during retrieval of stressful emotional experiences reflecting underlying mechanism related to consolidation of traumatic memories. In this context, hypnotic recall of anxiety memories in 10 patients, simultaneously with ECG measurement was performed. The same measurement was performed during control cognitive task in 8 anxiety patients and 22 healthy controls. Nonlinear data analysis of ECG records indicates significant increase in the degree of chaos during retrieval of stressful memory in all the patients. The results suggest a role of chaotic neural dynamics during processing of anxiety-related stressful memories.

Unraveling complex nonlinear elastic behaviors in rocks using dynamic acousto-elasticity

NASA Astrophysics Data System (ADS)

Riviere, J.; Guyer, R.; Renaud, G.; TenCate, J. A.; Johnson, P. A.

2012-12-01

In comparison with standard nonlinear ultrasonic methods like frequency mixing or resonance based measurements that allow one to extract average, bulk variations of modulus and attenuation versus strain level, dynamic acousto-elasticity (DAE) allows to obtain the elastic behavior over the entire dynamic cycle, detailing the full nonlinear behavior under tension and compression, including hysteresis and memory effects. This method consists of exciting a sample in Bulk-mode resonance at strains of 10-7 to 10-5 and simultaneously probing with a sequence of high frequency, low amplitude pulses. Time of flight and amplitudes of these pulses, respectively related to nonlinear elastic and dissipative parameters, can be plotted versus vibration strain level. Despite complex nonlinear signatures obtained for most rocks, it can be shown that for low strain amplitude (< 10-6), the nonlinear classical theory issued from a Taylor decomposition can explain the harmonic content. For higher strain, harmonic content becomes richer and the material exhibits more hysteretic behaviors, i.e. strain rate dependencies. Such observations have been made in the past (e.g., Pasqualini et al., JGR 2007), but not with the extreme detail of elasticity provided by DAE. Previous quasi-static measurements made in Berea sandstone (Claytor et al, GRL 2009), show that the hysteretic behavior disappears when the protocol is performed at a very low strain-rate (static limit). Therefore, future work will aim at linking quasi-static and dynamic observations, i.e. the frequency or strain-rate dependence, in order to understand underlying physical phenomena.

An efficient nonlinear finite-difference approach in the computational modeling of the dynamics of a nonlinear diffusion-reaction equation in microbial ecology.

PubMed

Macías-Díaz, J E; Macías, Siegfried; Medina-Ramírez, I E

2013-12-01

In this manuscript, we present a computational model to approximate the solutions of a partial differential equation which describes the growth dynamics of microbial films. The numerical technique reported in this work is an explicit, nonlinear finite-difference methodology which is computationally implemented using Newton's method. Our scheme is compared numerically against an implicit, linear finite-difference discretization of the same partial differential equation, whose computer coding requires an implementation of the stabilized bi-conjugate gradient method. Our numerical results evince that the nonlinear approach results in a more efficient approximation to the solutions of the biofilm model considered, and demands less computer memory. Moreover, the positivity of initial profiles is preserved in the practice by the nonlinear scheme proposed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Resistive Switching of Ta2O5-Based Self-Rectifying Vertical-Type Resistive Switching Memory

NASA Astrophysics Data System (ADS)

Ryu, Sungyeon; Kim, Seong Keun; Choi, Byung Joon

2018-01-01

To efficiently increase the capacity of resistive switching random-access memory (RRAM) while maintaining the same area, a vertical structure similar to a vertical NAND flash structure is needed. In addition, the sneak-path current through the half-selected neighboring memory cell should be mitigated by integrating a selector device with each RRAM cell. In this study, an integrated vertical-type RRAM cell and selector device was fabricated and characterized. Ta2O5 as the switching layer and TaOxNy as the selector layer were used to preliminarily study the feasibility of such an integrated device. To make the side contact of the bottom electrode with active layers, a thick Al2O3 insulating layer was placed between the Pt bottom electrode and the Ta2O5/TaOxNy stacks. Resistive switching phenomena were observed under relatively low currents (below 10 μA) in this vertical-type RRAM device. The TaOxNy layer acted as a nonlinear resistor with moderate nonlinearity. Its low-resistance-state and high-resistance-state were well retained up to 1000 s.

A stress-induced phase transition model for semi-crystallize shape memory polymer

NASA Astrophysics Data System (ADS)

Guo, Xiaogang; Zhou, Bo; Liu, Liwu; Liu, Yanju; Leng, Jinsong

2014-03-01

The developments of constitutive models for shape memory polymer (SMP) have been motivated by its increasing applications. During cooling or heating process, the phase transition which is a continuous time-dependent process happens in semi-crystallize SMP and the various individual phases form at different temperature and in different configuration. Then, the transformation between these phases occurred and shape memory effect will emerge. In addition, stress applied on SMP is an important factor for crystal melting during phase transition. In this theory, an ideal phase transition model considering stress or pre-strain is the key to describe the behaviors of shape memory effect. So a normal distributed model was established in this research to characterize the volume fraction of each phase in SMP during phase transition. Generally, the experiment results are partly backward (in heating process) or forward (in cooling process) compared with the ideal situation considering delay effect during phase transition. So, a correction on the normal distributed model is needed. Furthermore, a nonlinear relationship between stress and phase transition temperature Tg is also taken into account for establishing an accurately normal distributed phase transition model. Finally, the constitutive model which taking the stress as an influence factor on phase transition was also established. Compared with the other expressions, this new-type model possesses less parameter and is more accurate. For the sake of verifying the rationality and accuracy of new phase transition and constitutive model, the comparisons between the simulated and experimental results were carried out.

Co-rotational thermo-mechanically coupled multi-field framework and finite element for the large displacement analysis of multi-layered shape memory alloy beam-like structures

NASA Astrophysics Data System (ADS)

Solomou, Alexandros G.; Machairas, Theodoros T.; Karakalas, Anargyros A.; Saravanos, Dimitris A.

2017-06-01

A thermo-mechanically coupled finite element (FE) for the simulation of multi-layered shape memory alloy (SMA) beams admitting large displacements and rotations (LDRs) is developed to capture the geometrically nonlinear effects which are present in many SMA applications. A generalized multi-field beam theory implementing a SMA constitutive model based on small strain theory, thermo-mechanically coupled governing equations and multi-field kinematic hypotheses combining first order shear deformation assumptions with a sixth order polynomial temperature field through the thickness of the beam section are extended to admit LDRs. The co-rotational formulation is adopted, where the motion of the beam is decomposed to rigid body motion and relative small deformation in the local frame. A new generalized multi-layered SMA FE is formulated. The nonlinear transient spatial discretized equations of motion of the SMA structure are synthesized and solved using the Newton-Raphson method combined with an implicit time integration scheme. Correlations of models incorporating the present beam FE with respective results of models incorporating plane stress SMA FEs, demonstrate excellent agreement of the predicted LDRs response, temperature and phase transformation fields, as well as, significant gains in computational time.

Parallel Newton-Krylov-Schwarz algorithms for the transonic full potential equation

NASA Technical Reports Server (NTRS)

Cai, Xiao-Chuan; Gropp, William D.; Keyes, David E.; Melvin, Robin G.; Young, David P.

1996-01-01

We study parallel two-level overlapping Schwarz algorithms for solving nonlinear finite element problems, in particular, for the full potential equation of aerodynamics discretized in two dimensions with bilinear elements. The overall algorithm, Newton-Krylov-Schwarz (NKS), employs an inexact finite-difference Newton method and a Krylov space iterative method, with a two-level overlapping Schwarz method as a preconditioner. We demonstrate that NKS, combined with a density upwinding continuation strategy for problems with weak shocks, is robust and, economical for this class of mixed elliptic-hyperbolic nonlinear partial differential equations, with proper specification of several parameters. We study upwinding parameters, inner convergence tolerance, coarse grid density, subdomain overlap, and the level of fill-in in the incomplete factorization, and report their effect on numerical convergence rate, overall execution time, and parallel efficiency on a distributed-memory parallel computer.

A Nonlinear Functional Differential Equation in Banach Space with Applications to Materials with Fading Memory.

DTIC Science & Technology

1982-08-01

memory can be interpreted * mathematically as a smoothness requirement for Y. Following Coleman and Noll [ 4,5 ], we introduce an influence function , intended...to characterize the rate at which memory fades, and construct an LP-type space of admissible strain histories, using the influence function as a...that f h(s)fw(s)I ds < c, 0 equipped with the norm* given by (1.8) IwIl h = w(o)l + f h(s)w(s) 2d 0 We refer to h as an influence function and to the

Nonlinear changes in brain activity during continuous word repetition: an event-related multiparametric functional MR imaging study.

PubMed

Hagenbeek, R E; Rombouts, S A R B; Veltman, D J; Van Strien, J W; Witter, M P; Scheltens, P; Barkhof, F

2007-10-01

Changes in brain activation as a function of continuous multiparametric word recognition have not been studied before by using functional MR imaging (fMRI), to our knowledge. Our aim was to identify linear changes in brain activation and, what is more interesting, nonlinear changes in brain activation as a function of extended word repetition. Fifteen healthy young right-handed individuals participated in this study. An event-related extended continuous word-recognition task with 30 target words was used to study the parametric effect of word recognition on brain activation. Word-recognition-related brain activation was studied as a function of 9 word repetitions. fMRI data were analyzed with a general linear model with regressors for linearly changing signal intensity and nonlinearly changing signal intensity, according to group average reaction time (RT) and individual RTs. A network generally associated with episodic memory recognition showed either constant or linearly decreasing brain activation as a function of word repetition. Furthermore, both anterior and posterior cingulate cortices and the left middle frontal gyrus followed the nonlinear curve of the group RT, whereas the anterior cingulate cortex was also associated with individual RT. Linear alteration in brain activation as a function of word repetition explained most changes in blood oxygen level-dependent signal intensity. Using a hierarchically orthogonalized model, we found evidence for nonlinear activation associated with both group and individual RTs.

Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets

NASA Astrophysics Data System (ADS)

Gontis, V.; Kononovicius, A.

2017-10-01

We address the problem of long-range memory in the financial markets. There are two conceptually different ways to reproduce power-law decay of auto-correlation function: using fractional Brownian motion as well as non-linear stochastic differential equations. In this contribution we address this problem by analyzing empirical return and trading activity time series from the Forex. From the empirical time series we obtain probability density functions of burst and inter-burst duration. Our analysis reveals that the power-law exponents of the obtained probability density functions are close to 3 / 2, which is a characteristic feature of the one-dimensional stochastic processes. This is in a good agreement with earlier proposed model of absolute return based on the non-linear stochastic differential equations derived from the agent-based herding model.

Low-Complexity Discriminative Feature Selection From EEG Before and After Short-Term Memory Task.

PubMed

Behzadfar, Neda; Firoozabadi, S Mohammad P; Badie, Kambiz

2016-10-01

A reliable and unobtrusive quantification of changes in cortical activity during short-term memory task can be used to evaluate the efficacy of interfaces and to provide real-time user-state information. In this article, we investigate changes in electroencephalogram signals in short-term memory with respect to the baseline activity. The electroencephalogram signals have been analyzed using 9 linear and nonlinear/dynamic measures. We applied statistical Wilcoxon examination and Davis-Bouldian criterion to select optimal discriminative features. The results show that among the features, the permutation entropy significantly increased in frontal lobe and the occipital second lower alpha band activity decreased during memory task. These 2 features reflect the same mental task; however, their correlation with memory task varies in different intervals. In conclusion, it is suggested that the combination of the 2 features would improve the performance of memory based neurofeedback systems. © EEG and Clinical Neuroscience Society (ECNS) 2016.

Fast prediction of pulsed nonlinear acoustic fields from clinically relevant sources using Time-Averaged Wave Envelope approach: comparison of numerical simulations and experimental results

PubMed Central

Wójcik, J.; Kujawska, T.; Nowicki, A.; Lewin, P.A.

2008-01-01

The primary goal of this work was to verify experimentally the applicability of the recently introduced Time-Averaged Wave Envelope (TAWE) method [1] as a tool for fast prediction of four dimensional (4D) pulsed nonlinear pressure fields from arbitrarily shaped acoustic sources in attenuating media. The experiments were performed in water at the fundamental frequency of 2.8 MHz for spherically focused (focal length F = 80 mm) square (20 × 20 mm) and rectangular (10 × 25 mm) sources similar to those used in the design of 1D linear arrays operating with ultrasonic imaging systems. The experimental results obtained with 10-cycle tone bursts at three different excitation levels corresponding to linear, moderately nonlinear and highly nonlinear propagation conditions (0.045, 0.225 and 0.45 MPa on-source pressure amplitude, respectively) were compared with those yielded using the TAWE approach [1]. The comparison of the experimental results and numerical simulations has shown that the TAWE approach is well suited to predict (to within ± 1 dB) both the spatial-temporal and spatial-spectral pressure variations in the pulsed nonlinear acoustic beams. The obtained results indicated that implementation of the TAWE approach enabled shortening of computation time in comparison with the time needed for prediction of the full 4D pulsed nonlinear acoustic fields using a conventional (Fourier-series) approach [2]. The reduction in computation time depends on several parameters, including the source geometry, dimensions, fundamental resonance frequency, excitation level as well as the strength of the medium nonlinearity. For the non-axisymmetric focused transducers mentioned above and excited by a tone burst corresponding to moderately nonlinear and highly nonlinear conditions the execution time of computations was 3 and 12 hours, respectively, when using a 1.5 GHz clock frequency, 32-bit processor PC laptop with 2 GB RAM memory, only. Such prediction of the full 4D pulsed field is not possible when using conventional, Fourier-series scheme as it would require increasing the RAM memory by at least 2 orders of magnitude. PMID:18474387

Interplay of non-Markov and internal friction effects in the barrier crossing kinetics of biopolymers: insights from an analytically solvable model.

PubMed

Makarov, Dmitrii E

2013-01-07

Conformational rearrangements in biomolecules (such as protein folding or enzyme-ligand binding) are often interpreted in terms of low-dimensional models of barrier crossing such as Kramers' theory. Dimensionality reduction, however, entails memory effects; as a result, the effective frictional drag force along the reaction coordinate nontrivially depends on the time scale of the transition. Moreover, when both solvent and "internal" friction effects are important, their interplay results in a highly nonlinear dependence of the effective friction on solvent viscosity that is not captured by common phenomenological models of barrier crossing. Here, these effects are illustrated using an analytically solvable toy model of an unstructured polymer chain involved in an inter- or intramolecular transition. The transition rate is calculated using the Grote-Hynes and Langer theories, which--unlike Kramers' theory--account for memory. The resulting effective frictional force exerted by the polymer along the reaction coordinate can be rationalized in terms of the effective number of monomers engaged in the transition. Faster transitions (relative to the polymer reconfiguration time scale) involve fewer monomers and, correspondingly, lower friction forces, because the polymer chain does not have enough time to reconfigure in response to the transition.

Asymmetric Memory Circuit Would Resist Soft Errors

NASA Technical Reports Server (NTRS)

Buehler, Martin G.; Perlman, Marvin

1990-01-01

Some nonlinear error-correcting codes more efficient in presence of asymmetry. Combination of circuit-design and coding concepts expected to make integrated-circuit random-access memories more resistant to "soft" errors (temporary bit errors, also called "single-event upsets" due to ionizing radiation). Integrated circuit of new type made deliberately more susceptible to one kind of bit error than to other, and associated error-correcting code adapted to exploit this asymmetry in error probabilities.

Large conditional single-photon cross-phase modulation

NASA Astrophysics Data System (ADS)

Beck, Kristin; Hosseini, Mahdi; Duan, Yiheng; Vuletic, Vladan

2016-05-01

Deterministic optical quantum logic requires a nonlinear quantum process that alters the phase of a quantum optical state by π through interaction with only one photon. Here, we demonstrate a large conditional cross-phase modulation between a signal field, stored inside an atomic quantum memory, and a control photon that traverses a high-finesse optical cavity containing the atomic memory. This approach avoids fundamental limitations associated with multimode effects for traveling optical photons. We measure a conditional cross-phase shift of up to π / 3 between the retrieved signal and control photons, and confirm deterministic entanglement between the signal and control modes by extracting a positive concurrence. With a moderate improvement in cavity finesse, our system can reach a coherent phase shift of p at low loss, enabling deterministic and universal photonic quantum logic. Preprint: arXiv:1512.02166 [quant-ph

Numerical Study of the Plasticity-Induced Stabilization Effect on Martensitic Transformations in Shape Memory Alloys

NASA Astrophysics Data System (ADS)

Junker, Philipp; Hempel, Philipp

2017-12-01

It is well known that plastic deformations in shape memory alloys stabilize the martensitic phase. Furthermore, the knowledge concerning the plastic state is crucial for a reliable sustainability analysis of construction parts. Numerical simulations serve as a tool for the realistic investigation of the complex interactions between phase transformations and plastic deformations. To account also for irreversible deformations, we expand an energy-based material model by including a non-linear isotropic hardening plasticity model. An implementation of this material model into commercial finite element programs, e.g., Abaqus, offers the opportunity to analyze entire structural components at low costs and fast computation times. Along with the theoretical derivation and expansion of the model, several simulation results for various boundary value problems are presented and interpreted for improved construction designing.

Nonlinear associations between plasma cholesterol levels and neuropsychological function.

PubMed

Wendell, Carrington R; Zonderman, Alan B; Katzel, Leslie I; Rosenberger, William F; Plamadeala, Victoria V; Hosey, Megan M; Waldstein, Shari R

2016-11-01

Although both high and low levels of total and low-density lipoprotein (LDL) cholesterol have been associated with poor neuropsychological function, little research has examined nonlinear effects. We examined quadratic relations of cholesterol to performance on a comprehensive neuropsychological battery. Participants were 190 older adults (53% men, ages 54-83) free of major medical, neurologic, and psychiatric disease. Measures of fasting plasma total and high-density lipoprotein (HDL) cholesterol were assayed, and LDL cholesterol was calculated. Participants completed neuropsychological measures of attention, executive function, memory, visuospatial judgment, and manual speed and dexterity. Multiple regression analyses examined cholesterol levels as quadratic predictors of each measure of cognitive performance, with age (dichotomized as <70 vs. 70+) as an effect modifier. A significant quadratic effect of Total Cholesterol² × Age was identified for Logical Memory II ( b = -.0013, p = .039), such that the 70+ group performed best at high and low levels of total cholesterol than at midrange total cholesterol (U-shaped) and the <70 group performed worse at high and low levels of total cholesterol than at midrange total cholesterol (inverted U shape). Similarly, significant U- and J-shaped effects of LDL Cholesterol² × Age were identified for Visual Reproduction II ( b = -.0020, p = .026) and log of the Trail Making Test, Part B (b = .0001, p = .044). Quadratic associations between HDL cholesterol and cognitive performance were nonsignificant. Results indicate differential associations between cholesterol and neuropsychological function across different ages and domains of function. High and low total and LDL cholesterol may confer both risk and benefit for suboptimal cognitive function at different ages. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A practically unconditionally gradient stable scheme for the N-component Cahn-Hilliard system

NASA Astrophysics Data System (ADS)

Lee, Hyun Geun; Choi, Jeong-Whan; Kim, Junseok

2012-02-01

We present a practically unconditionally gradient stable conservative nonlinear numerical scheme for the N-component Cahn-Hilliard system modeling the phase separation of an N-component mixture. The scheme is based on a nonlinear splitting method and is solved by an efficient and accurate nonlinear multigrid method. The scheme allows us to convert the N-component Cahn-Hilliard system into a system of N-1 binary Cahn-Hilliard equations and significantly reduces the required computer memory and CPU time. We observe that our numerical solutions are consistent with the linear stability analysis results. We also demonstrate the efficiency of the proposed scheme with various numerical experiments.

V.A.Robsman: Nonlinear Testing and Building Industry

NASA Astrophysics Data System (ADS)

Rudenko, Oleg V.

2006-05-01

This talk is devoted to the memory of outstanding scientist and engineer Vadim A. Robsman who died in January 2005. Dr.Robsman was the Honored Builder of Russia. He developed and applied new methods of nondestructive testing of buildings, bridges, power plants and other building units. At the same time, he published works on fundamental problems of acoustics and nonlinear dynamics. In particular, he suggested a new equation of the 4-th order continuing the series of basic equations of nonlinear wave theory (Burgers Eq.: 2-nd order, Korteveg - de Vries Eq.: 3-rd order) and found exact solutions for high-intensity waves in scattering media.

Generalized Weierstrass-Mandelbrot Function Model for Actual Stocks Markets Indexes with Nonlinear Characteristics

NASA Astrophysics Data System (ADS)

Zhang, L.; Yu, C.; Sun, J. Q.

2015-03-01

It is difficult to simulate the dynamical behavior of actual financial markets indexes effectively, especially when they have nonlinear characteristics. So it is significant to propose a mathematical model with these characteristics. In this paper, we investigate a generalized Weierstrass-Mandelbrot function (WMF) model with two nonlinear characteristics: fractal dimension D where 2 > D > 1.5 and Hurst exponent (H) where 1 > H > 0.5 firstly. And then we study the dynamical behavior of H for WMF as D and the spectrum of the time series γ change in three-dimensional space, respectively. Because WMF and the actual stock market indexes have two common features: fractal behavior using fractal dimension and long memory effect by Hurst exponent, we study the relationship between WMF and the actual stock market indexes. We choose a random value of γ and fixed value of D for WMF to simulate the S&P 500 indexes at different time ranges. As shown in the simulation results of three-dimensional space, we find that γ is important in WMF model and different γ may have the same effect for the nonlinearity of WMF. Then we calculate the skewness and kurtosis of actual Daily S&P 500 index in different time ranges which can be used to choose the value of γ. Based on these results, we choose appropriate γ, D and initial value into WMF to simulate Daily S&P 500 indexes. Using the fit line method in two-dimensional space for the simulated values, we find that the generalized WMF model is effective for simulating different actual stock market indexes in different time ranges. It may be useful for understanding the dynamical behavior of many different financial markets.

Implementation of software-based sensor linearization algorithms on low-cost microcontrollers.

PubMed

Erdem, Hamit

2010-10-01

Nonlinear sensors and microcontrollers are used in many embedded system designs. As the input-output characteristic of most sensors is nonlinear in nature, obtaining data from a nonlinear sensor by using an integer microcontroller has always been a design challenge. This paper discusses the implementation of six software-based sensor linearization algorithms for low-cost microcontrollers. The comparative study of the linearization algorithms is performed by using a nonlinear optical distance-measuring sensor. The performance of the algorithms is examined with respect to memory space usage, linearization accuracy and algorithm execution time. The implementation and comparison results can be used for selection of a linearization algorithm based on the sensor transfer function, expected linearization accuracy and microcontroller capacity. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Automated diagnosis of autism: in search of a mathematical marker.

PubMed

Bhat, Shreya; Acharya, U Rajendra; Adeli, Hojjat; Bairy, G Muralidhar; Adeli, Amir

2014-01-01

Autism is a type of neurodevelopmental disorder affecting the memory, behavior, emotion, learning ability, and communication of an individual. An early detection of the abnormality, due to irregular processing in the brain, can be achieved using electroencephalograms (EEG). The variations in the EEG signals cannot be deciphered by mere visual inspection. Computer-aided diagnostic tools can be used to recognize the subtle and invisible information present in the irregular EEG pattern and diagnose autism. This paper presents a state-of-the-art review of automated EEG-based diagnosis of autism. Various time domain, frequency domain, time-frequency domain, and nonlinear dynamics for the analysis of autistic EEG signals are described briefly. A focus of the review is the use of nonlinear dynamics and chaos theory to discover the mathematical biomarkers for the diagnosis of the autism analogous to biological markers. A combination of the time-frequency and nonlinear dynamic analysis is the most effective approach to characterize the nonstationary and chaotic physiological signals for the automated EEG-based diagnosis of autism spectrum disorder (ASD). The features extracted using these nonlinear methods can be used as mathematical markers to detect the early stage of autism and aid the clinicians in their diagnosis. This will expedite the administration of appropriate therapies to treat the disorder.

Real-time tumor motion estimation using respiratory surrogate via memory-based learning

NASA Astrophysics Data System (ADS)

Li, Ruijiang; Lewis, John H.; Berbeco, Ross I.; Xing, Lei

2012-08-01

Respiratory tumor motion is a major challenge in radiation therapy for thoracic and abdominal cancers. Effective motion management requires an accurate knowledge of the real-time tumor motion. External respiration monitoring devices (optical, etc) provide a noninvasive, non-ionizing, low-cost and practical approach to obtain the respiratory signal. Due to the highly complex and nonlinear relations between tumor and surrogate motion, its ultimate success hinges on the ability to accurately infer the tumor motion from respiratory surrogates. Given their widespread use in the clinic, such a method is critically needed. We propose to use a powerful memory-based learning method to find the complex relations between tumor motion and respiratory surrogates. The method first stores the training data in memory and then finds relevant data to answer a particular query. Nearby data points are assigned high relevance (or weights) and conversely distant data are assigned low relevance. By fitting relatively simple models to local patches instead of fitting one single global model, it is able to capture highly nonlinear and complex relations between the internal tumor motion and external surrogates accurately. Due to the local nature of weighting functions, the method is inherently robust to outliers in the training data. Moreover, both training and adapting to new data are performed almost instantaneously with memory-based learning, making it suitable for dynamically following variable internal/external relations. We evaluated the method using respiratory motion data from 11 patients. The data set consists of simultaneous measurement of 3D tumor motion and 1D abdominal surface (used as the surrogate signal in this study). There are a total of 171 respiratory traces, with an average peak-to-peak amplitude of ∼15 mm and average duration of ∼115 s per trace. Given only 5 s (roughly one breath) pretreatment training data, the method achieved an average 3D error of 1.5 mm and 95th percentile error of 3.4 mm on unseen test data. The average 3D error was further reduced to 1.4 mm when the model was tuned to its optimal setting for each respiratory trace. In one trace where a few outliers are present in the training data, the proposed method achieved an error reduction of as much as ∼50% compared with the best linear model (1.0 mm versus 2.1 mm). The memory-based learning technique is able to accurately capture the highly complex and nonlinear relations between tumor and surrogate motion in an efficient manner (a few milliseconds per estimate). Furthermore, the algorithm is particularly suitable to handle situations where the training data are contaminated by large errors or outliers. These desirable properties make it an ideal candidate for accurate and robust tumor gating/tracking using respiratory surrogates.

Nonlinear Thermoelastic Model for SMAs and SMA Hybrid Composites

NASA Technical Reports Server (NTRS)

Turner, Travis L.

2004-01-01

A constitutive mathematical model has been developed that predicts the nonlinear thermomechanical behaviors of shape-memory-alloys (SMAs) and of shape-memory-alloy hybrid composite (SMAHC) structures, which are composite-material structures that contain embedded SMA actuators. SMAHC structures have been investigated for their potential utility in a variety of applications in which there are requirements for static or dynamic control of the shapes of structures, control of the thermoelastic responses of structures, or control of noise and vibrations. The present model overcomes deficiencies of prior, overly simplistic or qualitative models that have proven ineffective or intractable for engineering of SMAHC structures. The model is sophisticated enough to capture the essential features of the mechanics of SMAHC structures yet simple enough to accommodate input from fundamental engineering measurements and is in a form that is amenable to implementation in general-purpose structural analysis environments.

On the form of ROCs constructed from confidence ratings.

PubMed

Malmberg, Kenneth J

2002-03-01

A classical question for memory researchers is whether memories vary in an all-or-nothing, discrete manner (e.g., stored vs. not stored, recalled vs. not recalled), or whether they vary along a continuous dimension (e.g., strength, similarity, or familiarity). For yes-no classification tasks, continuous- and discrete-state models predict nonlinear and linear receiver operating characteristics (ROCs), respectively (D. M. Green & J. A. Swets, 1966; N. A. Macmillan & C. D. Creelman, 1991). Recently, several authors have assumed that these predictions are generalizable to confidence ratings tasks (J. Qin, C. L. Raye, M. K. Johnson, & K. J. Mitchell, 2001; S. D. Slotnick, S. A. Klein, C. S. Dodson, & A. P. Shimamura, 2000, and A. P. Yonelinas, 1999). This assumption is shown to be unwarranted by showing that discrete-state ratings models predict both linear and nonlinear ROCs. The critical factor determining the form of the discrete-state ROC is the response strategy adopted by the classifier.

Reformulation of time-convolutionless mode-coupling theory near the glass transition

NASA Astrophysics Data System (ADS)

Tokuyama, Michio

2017-10-01

The time-convolutionless mode-coupling theory (TMCT) recently proposed is reformulated under the condition that one of two approximations, which have been used to formulate the original TMCT in addition to the MCT approximations done on a derivation of nonlinear memory function in terms of the intermediate-scattering function, is not employed because it causes unphysical results for intermediate times. The improved TMCT equation is then derived consistently under another approximation. It is first checked that the ergodic to non-ergodic transition obtained by a new equation is exactly the same as that obtained by an old one because the long-time dynamics of both equations coincides with each other. However, it is emphasized that a difference between them appears in the intermediate-time dynamics of physical quantities. Such a difference is explored numerically in the dynamics of a non-Gaussian parameter by employing the Percus-Yevick static structure factor to calculate the nonlinear memory function.

Spatial light modulators and applications III; Proceedings of the Meeting, San Diego, CA, Aug. 7, 8, 1989

NASA Astrophysics Data System (ADS)

Efron, Uzi

Recent advances in the technology and applications of spatial light modulators (SLMs) are discussed in review essays by leading experts. Topics addressed include materials for SLMs, SLM devices and device technology, applications to optical data processing, and applications to artificial neural networks. Particular attention is given to nonlinear optical polymers, liquid crystals, magnetooptic SLMs, multiple-quantum-well SLMs, deformable-mirror SLMs, three-dimensional optical memories, applications of photorefractive devices to optical computing, photonic neurocomputers and learning machines, holographic associative memories, SLMs as parallel memories for optoelectronic neural networks, and coherent-optics implementations of neural-network models.

Spatial light modulators and applications III; Proceedings of the Meeting, San Diego, CA, Aug. 7, 8, 1989

NASA Technical Reports Server (NTRS)

Efron, Uzi (Editor)

1990-01-01

Recent advances in the technology and applications of spatial light modulators (SLMs) are discussed in review essays by leading experts. Topics addressed include materials for SLMs, SLM devices and device technology, applications to optical data processing, and applications to artificial neural networks. Particular attention is given to nonlinear optical polymers, liquid crystals, magnetooptic SLMs, multiple-quantum-well SLMs, deformable-mirror SLMs, three-dimensional optical memories, applications of photorefractive devices to optical computing, photonic neurocomputers and learning machines, holographic associative memories, SLMs as parallel memories for optoelectronic neural networks, and coherent-optics implementations of neural-network models.

Persistent Memory in Single Node Delay-Coupled Reservoir Computing.

PubMed

Kovac, André David; Koall, Maximilian; Pipa, Gordon; Toutounji, Hazem

2016-01-01

Delays are ubiquitous in biological systems, ranging from genetic regulatory networks and synaptic conductances, to predator/pray population interactions. The evidence is mounting, not only to the presence of delays as physical constraints in signal propagation speed, but also to their functional role in providing dynamical diversity to the systems that comprise them. The latter observation in biological systems inspired the recent development of a computational architecture that harnesses this dynamical diversity, by delay-coupling a single nonlinear element to itself. This architecture is a particular realization of Reservoir Computing, where stimuli are injected into the system in time rather than in space as is the case with classical recurrent neural network realizations. This architecture also exhibits an internal memory which fades in time, an important prerequisite to the functioning of any reservoir computing device. However, fading memory is also a limitation to any computation that requires persistent storage. In order to overcome this limitation, the current work introduces an extended version to the single node Delay-Coupled Reservoir, that is based on trained linear feedback. We show by numerical simulations that adding task-specific linear feedback to the single node Delay-Coupled Reservoir extends the class of solvable tasks to those that require nonfading memory. We demonstrate, through several case studies, the ability of the extended system to carry out complex nonlinear computations that depend on past information, whereas the computational power of the system with fading memory alone quickly deteriorates. Our findings provide the theoretical basis for future physical realizations of a biologically-inspired ultrafast computing device with extended functionality.

Persistent Memory in Single Node Delay-Coupled Reservoir Computing

PubMed Central

Pipa, Gordon; Toutounji, Hazem

2016-01-01

Delays are ubiquitous in biological systems, ranging from genetic regulatory networks and synaptic conductances, to predator/pray population interactions. The evidence is mounting, not only to the presence of delays as physical constraints in signal propagation speed, but also to their functional role in providing dynamical diversity to the systems that comprise them. The latter observation in biological systems inspired the recent development of a computational architecture that harnesses this dynamical diversity, by delay-coupling a single nonlinear element to itself. This architecture is a particular realization of Reservoir Computing, where stimuli are injected into the system in time rather than in space as is the case with classical recurrent neural network realizations. This architecture also exhibits an internal memory which fades in time, an important prerequisite to the functioning of any reservoir computing device. However, fading memory is also a limitation to any computation that requires persistent storage. In order to overcome this limitation, the current work introduces an extended version to the single node Delay-Coupled Reservoir, that is based on trained linear feedback. We show by numerical simulations that adding task-specific linear feedback to the single node Delay-Coupled Reservoir extends the class of solvable tasks to those that require nonfading memory. We demonstrate, through several case studies, the ability of the extended system to carry out complex nonlinear computations that depend on past information, whereas the computational power of the system with fading memory alone quickly deteriorates. Our findings provide the theoretical basis for future physical realizations of a biologically-inspired ultrafast computing device with extended functionality. PMID:27783690

Hierarchically Parallelized Constrained Nonlinear Solvers with Automated Substructuring

NASA Technical Reports Server (NTRS)

Padovan, Joe; Kwang, Abel

1994-01-01

This paper develops a parallelizable multilevel multiple constrained nonlinear equation solver. The substructuring process is automated to yield appropriately balanced partitioning of each succeeding level. Due to the generality of the procedure,_sequential, as well as partially and fully parallel environments can be handled. This includes both single and multiprocessor assignment per individual partition. Several benchmark examples are presented. These illustrate the robustness of the procedure as well as its capability to yield significant reductions in memory utilization and calculational effort due both to updating and inversion.

Femtojoule-scale all-optical latching and modulation via cavity nonlinear optics.

PubMed

Kwon, Yeong-Dae; Armen, Michael A; Mabuchi, Hideo

2013-11-15

We experimentally characterize Hopf bifurcation phenomena at femtojoule energy scales in a multiatom cavity quantum electrodynamical (cavity QED) system and demonstrate how such behaviors can be exploited in the design of all-optical memory and modulation devices. The data are analyzed by using a semiclassical model that explicitly treats heterogeneous coupling of atoms to the cavity mode. Our results highlight the interest of cavity QED systems for ultralow power photonic signal processing as well as for fundamental studies of mesoscopic nonlinear dynamics.

A modeling framework for deriving the structural and functional architecture of a short-term memory microcircuit.

PubMed

Fisher, Dimitry; Olasagasti, Itsaso; Tank, David W; Aksay, Emre R F; Goldman, Mark S

2013-09-04

Although many studies have identified neural correlates of memory, relatively little is known about the circuit properties connecting single-neuron physiology to behavior. Here we developed a modeling framework to bridge this gap and identify circuit interactions capable of maintaining short-term memory. Unlike typical studies that construct a phenomenological model and test whether it reproduces select aspects of neuronal data, we directly fit the synaptic connectivity of an oculomotor memory circuit to a broad range of anatomical, electrophysiological, and behavioral data. Simultaneous fits to all data, combined with sensitivity analyses, revealed complementary roles of synaptic and neuronal recruitment thresholds in providing the nonlinear interactions required to generate the observed circuit behavior. This work provides a methodology for identifying the cellular and synaptic mechanisms underlying short-term memory and demonstrates how the anatomical structure of a circuit may belie its functional organization. Copyright © 2013 Elsevier Inc. All rights reserved.

A nonlinear HP-type complementary resistive switch

NASA Astrophysics Data System (ADS)

Radtke, Paul K.; Schimansky-Geier, Lutz

2016-05-01

Resistive Switching (RS) is the change in resistance of a dielectric under the influence of an external current or electric field. This change is non-volatile, and the basis of both the memristor and resistive random access memory. In the latter, high integration densities favor the anti-serial combination of two RS-elements to a single cell, termed the complementary resistive switch (CRS). Motivated by the irregular shape of the filament protruding into the device, we suggest a nonlinearity in the resistance-interpolation function, characterized by a single parameter p. Thereby the original HP-memristor is expanded upon. We numerically simulate and analytically solve this model. Further, the nonlinearity allows for its application to the CRS.

Performance comparison of attitude determination, attitude estimation, and nonlinear observers algorithms

NASA Astrophysics Data System (ADS)

MOHAMMED, M. A. SI; BOUSSADIA, H.; BELLAR, A.; ADNANE, A.

2017-01-01

This paper presents a brief synthesis and useful performance analysis of different attitude filtering algorithms (attitude determination algorithms, attitude estimation algorithms, and nonlinear observers) applied to Low Earth Orbit Satellite in terms of accuracy, convergence time, amount of memory, and computation time. This latter is calculated in two ways, using a personal computer and also using On-board computer 750 (OBC 750) that is being used in many SSTL Earth observation missions. The use of this comparative study could be an aided design tool to the designer to choose from an attitude determination or attitude estimation or attitude observer algorithms. The simulation results clearly indicate that the nonlinear Observer is the more logical choice.

Overcoming learning barriers through knowledge management.

PubMed

Dror, Itiel E; Makany, Tamas; Kemp, Jonathan

2011-02-01

The ability to learn highly depends on how knowledge is managed. Specifically, different techniques for note-taking utilize different cognitive processes and strategies. In this paper, we compared dyslexic and control participants when using linear and non-linear note-taking. All our participants were professionals working in the banking and financial sector. We examined comprehension, accuracy, mental imagery & complexity, metacognition, and memory. We found that participants with dyslexia, when using a non-linear note-taking technique outperformed the control group using linear note-taking and matched the performance of the control group using non-linear note-taking. These findings emphasize how different knowledge management techniques can avoid some of the barriers to learners. Copyright © 2010 John Wiley & Sons, Ltd.

Aging selectively impairs recollection in recognition memory for pictures: Evidence from modeling and ROC curves

PubMed Central

Howard, Marc W.; Bessette-Symons, Brandy; Zhang, Yaofei; Hoyer, William J.

2006-01-01

Younger and older adults were tested on recognition memory for pictures. The Yonelinas high threshold (YHT) model, a formal implementation of two-process theory, fit the response distribution data of both younger and older adults significantly better than a normal unequal variance signal detection model. Consistent with this finding, non-linear zROC curves were obtained for both groups. Estimates of recollection from the YHT model were significantly higher for younger than older adults. This deficit was not a consequence of a general decline in memory; older adults showed comparable overall accuracy and in fact a non-significant increase in their familiarity scores. Implications of these results for theories of recognition memory and the mnemonic deficit associated with aging are discussed. PMID:16594795

Preferential selection based on strategy persistence and memory promotes cooperation in evolutionary prisoner's dilemma games

NASA Astrophysics Data System (ADS)

Liu, Yuanming; Huang, Changwei; Dai, Qionglin

2018-06-01

Strategy imitation plays a crucial role in evolutionary dynamics when we investigate the spontaneous emergence of cooperation under the framework of evolutionary game theory. Generally, when an individual updates his strategy, he needs to choose a role model whom he will learn from. In previous studies, individuals choose role models randomly from their neighbors. In recent works, researchers have considered that individuals choose role models according to neighbors' attractiveness characterized by the present network topology or historical payoffs. Here, we associate an individual's attractiveness with the strategy persistence, which characterizes how frequently he changes his strategy. We introduce a preferential parameter α to describe the nonlinear correlation between the selection probability and the strategy persistence and the memory length of individuals M into the evolutionary games. We investigate the effects of α and M on cooperation. Our results show that cooperation could be promoted when α > 0 and at the same time M > 1, which corresponds to the situation that individuals are inclined to select their neighbors with relatively higher persistence levels during the evolution. Moreover, we find that the cooperation level could reach the maximum at an optimal memory length when α > 0. Our work sheds light on how to promote cooperation through preferential selection based on strategy persistence and a limited memory length.

Hepatitis C virus Broadly Neutralizing Monoclonal Antibodies Isolated 25 Years after Spontaneous Clearance.

PubMed

Merat, Sabrina J; Molenkamp, Richard; Wagner, Koen; Koekkoek, Sylvie M; van de Berg, Dorien; Yasuda, Etsuko; Böhne, Martino; Claassen, Yvonne B; Grady, Bart P; Prins, Maria; Bakker, Arjen Q; de Jong, Menno D; Spits, Hergen; Schinkel, Janke; Beaumont, Tim

2016-01-01

Hepatitis C virus (HCV) is world-wide a major cause of liver related morbidity and mortality. No vaccine is available to prevent HCV infection. To design an effective vaccine, understanding immunity against HCV is necessary. The memory B cell repertoire was characterized from an intravenous drug user who spontaneously cleared HCV infection 25 years ago. CD27+IgG+ memory B cells were immortalized using BCL6 and Bcl-xL. These immortalized B cells were used to study antibody-mediated immunity against the HCV E1E2 glycoproteins. Five E1E2 broadly reactive antibodies were isolated: 3 antibodies showed potent neutralization of genotype 1 to 4 using HCV pseudotyped particles, whereas the other 2 antibodies neutralized genotype 1, 2 and 3 or 1 and 2 only. All antibodies recognized non-linear epitopes on E2. Finally, except for antibody AT12-011, which recognized an epitope consisting of antigenic domain C /AR2 and AR5, all other four antibodies recognized epitope II and domain B. These data show that a subject, who spontaneously cleared HCV infection 25 years ago, still has circulating memory B cells that are able to secrete broadly neutralizing antibodies. Presence of such memory B cells strengthens the argument for undertaking the development of an HCV vaccine.

Manipulation of optical-pulse-imprinted memory in a Λ system

NASA Astrophysics Data System (ADS)

Gutiérrez-Cuevas, Rodrigo; Eberly, Joseph H.

2015-09-01

We examine coherent memory manipulation in a Λ -type medium, using the second-order solution presented by Groves, Clader, and Eberly [J. Phys. B: At. Mol. Opt. Phys. 46, 224005 (2013), 10.1088/0953-4075/46/22/224005] as a guide. The analytical solution obtained using the Darboux transformation and a nonlinear superposition principle describes complicated soliton-pulse dynamics which, by an appropriate choice of parameters, can be simplified to a well-defined sequence of pulses interacting with the medium. In this report, this solution is reviewed and put to test by means of a series of numerical simulations, encompassing all the parameter space and adding the effects of homogeneous broadening due to spontaneous emission. We find that even though the decohered results deviate from the analytical prediction they do follow a similar trend that could be used as a guide for future experiments.

Estimation of Transformation Temperatures in Ti-Ni-Pd Shape Memory Alloys

NASA Astrophysics Data System (ADS)

Narayana, P. L.; Kim, Seong-Woong; Hong, Jae-Keun; Reddy, N. S.; Yeom, Jong-Taek

2018-03-01

The present study focused on estimating the complex nonlinear relationship between the composition and phase transformation temperatures of Ti-Ni-Pd shape memory alloys by artificial neural networks (ANN). The ANN models were developed by using the experimental data of Ti-Ni-Pd alloys. It was found that the predictions are in good agreement with the trained and unseen test data of existing alloys. The developed model was able to simulate new virtual alloys to quantitatively estimate the effect of Ti, Ni, and Pd on transformation temperatures. The transformation temperature behavior of these virtual alloys is validated by conducting new experiments on the Ti-rich thin film that was deposited using multi target sputtering equipment. The transformation behavior of the film was measured by varying the composition with the help of aging treatment. The predicted trend of transformational temperatures was explained with the help of experimental results.

Large conditional single-photon cross-phase modulation

PubMed Central

Hosseini, Mahdi; Duan, Yiheng; Vuletić, Vladan

2016-01-01

Deterministic optical quantum logic requires a nonlinear quantum process that alters the phase of a quantum optical state by π through interaction with only one photon. Here, we demonstrate a large conditional cross-phase modulation between a signal field, stored inside an atomic quantum memory, and a control photon that traverses a high-finesse optical cavity containing the atomic memory. This approach avoids fundamental limitations associated with multimode effects for traveling optical photons. We measure a conditional cross-phase shift of π/6 (and up to π/3 by postselection on photons that remain in the system longer than average) between the retrieved signal and control photons, and confirm deterministic entanglement between the signal and control modes by extracting a positive concurrence. By upgrading to a state-of-the-art cavity, our system can reach a coherent phase shift of π at low loss, enabling deterministic and universal photonic quantum logic. PMID:27519798

Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks.

PubMed

Vlachas, Pantelis R; Byeon, Wonmin; Wan, Zhong Y; Sapsis, Themistoklis P; Koumoutsakos, Petros

2018-05-01

We introduce a data-driven forecasting method for high-dimensional chaotic systems using long short-term memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high-dimensional dynamical systems in their reduced order space and are shown to be an effective set of nonlinear approximators of their attractor. We demonstrate the forecasting performance of the LSTM and compare it with Gaussian processes (GPs) in time series obtained from the Lorenz 96 system, the Kuramoto-Sivashinsky equation and a prototype climate model. The LSTM networks outperform the GPs in short-term forecasting accuracy in all applications considered. A hybrid architecture, extending the LSTM with a mean stochastic model (MSM-LSTM), is proposed to ensure convergence to the invariant measure. This novel hybrid method is fully data-driven and extends the forecasting capabilities of LSTM networks.

Study of chromatic adaptation using memory color matches, Part II: colored illuminants.

PubMed

Smet, Kevin A G; Zhai, Qiyan; Luo, Ming R; Hanselaer, Peter

2017-04-03

In a previous paper, 12 corresponding color data sets were derived for 4 neutral illuminants using the long-term memory colours of five familiar objects. The data were used to test several linear (one-step and two-step von Kries, RLAB) and nonlinear (Hunt and Nayatani) chromatic adaptation transforms (CAT). This paper extends that study to a total of 156 corresponding color sets by including 9 more colored illuminants: 2 with low and 2 with high correlated color temperatures as well as 5 representing high chroma adaptive conditions. As in the previous study, a two-step von Kries transform whereby the degree of adaptation D is optimized to minimize the DEu'v' prediction errors outperformed all other tested models for both memory color and literature corresponding color sets, whereby prediction errors were lower for the memory color set. Most of the transforms tested, except the two- and one-step von Kries models with optimized D, showed large errors for corresponding color subsets that contained non-neutral adaptive conditions as all of them tended to overestimate the effective degree of adaptation in this study. An analysis of the impact of the sensor space primaries in which the adaptation is performed was found to have little impact compared to that of model choice. Finally, the effective degree of adaptation for the 13 illumination conditions (4 neutral + 9 colored) was successfully modelled using a bivariate Gaussian in a Macleod-Boyton like chromaticity diagram.

Quadratic Hadamard Memories II. Adaptive Stochastic Content. Addressable Memory

DTIC Science & Technology

1990-07-01

No. 6429 Issued by Army Missile Command Under Contract # DAAH1-88-C-0887 D T IC Technical Report #2 E LEC SlD Approved for public release...integrate the N coupled nonlinear 0 differential equations, something I cannot do. In the proportional region these equations d 5 can be integrated in spite...is summed, but Uav a is not. Indices are used as follows. i, j, and k denote components in input space. a, b, c, d , and p denote components in the

Adaptive filtering with the self-organizing map: a performance comparison.

PubMed

Barreto, Guilherme A; Souza, Luís Gustavo M

2006-01-01

In this paper we provide an in-depth evaluation of the SOM as a feasible tool for nonlinear adaptive filtering. A comprehensive survey of existing SOM-based and related architectures for learning input-output mappings is carried out and the application of these architectures to nonlinear adaptive filtering is formulated. Then, we introduce two simple procedures for building RBF-based nonlinear filters using the Vector-Quantized Temporal Associative Memory (VQTAM), a recently proposed method for learning dynamical input-output mappings using the SOM. The aforementioned SOM-based adaptive filters are compared with standard FIR/LMS and FIR/LMS-Newton linear transversal filters, as well as with powerful MLP-based filters in nonlinear channel equalization and inverse modeling tasks. The obtained results in both tasks indicate that SOM-based filters can consistently outperform powerful MLP-based ones.

Improved multi-level capability in Si3N4-based resistive switching memory using continuous gradual reset switching

NASA Astrophysics Data System (ADS)

Kim, Sungjun; Park, Byung-Gook

2017-01-01

In this letter, we compare three different types of reset switching behavior in a bipolar resistive random-access memory (RRAM) system that is housed in a Ni/Si3N4/Si structure. The abrupt, step-like gradual and continuous gradual reset transitions are largely determined by the low-resistance state (LRS). For abrupt reset switching, the large conducting path shows ohmic behavior or has a weak nonlinear current-voltage (I-V) characteristics in the LRS. For gradual switching, including both the step-like and continuous reset types, trap-assisted direct tunneling is dominant in the low-voltage regime, while trap-assisted Fowler-Nordheim tunneling is dominant in the high-voltage regime, thus causing nonlinear I-V characteristics. More importantly, we evaluate the multi-level capabilities of the two different gradual switching types, including both step-like and continuous reset behavior, using identical and incremental voltage conditions. Finer control of the conductance level with good uniformity is achieved in continuous gradual reset switching when compared to that in step-like gradual reset switching. For continuous reset switching, a single conducting path, which initially has a tunneling gap, gradually responds to pulses with even and identical amplitudes, while for step-like reset switching, the multiple conducting paths only respond to incremental pulses to obtain effective multi-level states.

Group-kinetic theory of turbulence

NASA Technical Reports Server (NTRS)

Tchen, C. M.

1986-01-01

The two phases are governed by two coupled systems of Navier-Stokes equations. The couplings are nonlinear. These equations describe the microdynamical state of turbulence, and are transformed into a master equation. By scaling, a kinetic hierarchy is generated in the form of groups, representing the spectral evolution, the diffusivity and the relaxation. The loss of memory in formulating the relaxation yields the closure. The network of sub-distributions that participates in the relaxation is simulated by a self-consistent porous medium, so that the average effect on the diffusivity is to make it approach equilibrium. The kinetic equation of turbulence is derived. The method of moments reverts it to the continuum. The equation of spectral evolution is obtained and the transport properties are calculated. In inertia turbulence, the Kolmogoroff law for weak coupling and the spectrum for the strong coupling are found. As the fluid analog, the nonlinear Schrodinger equation has a driving force in the form of emission of solitons by velocity fluctuations, and is used to describe the microdynamical state of turbulence. In order for the emission together with the modulation to participate in the transport processes, the non-homogeneous Schrodinger equation is transformed into a homogeneous master equation. By group-scaling, the master equation is decomposed into a system of transport equations, replacing the Bogoliubov system of equations of many-particle distributions. It is in the relaxation that the memory is lost when the ensemble of higher-order distributions is simulated by an effective porous medium. The closure is thus found. The kinetic equation is derived and transformed into the equation of spectral flow.

Macroscopic models for shape memory alloy characterization and design

NASA Astrophysics Data System (ADS)

Massad, Jordan Elias

Shape memory alloys (SMAs) are being considered for a number of high performance applications, such as deformable aircraft wings, earthquake-resistant structures, and microdevices, due to their capability to achieve very high work densities, produce large deformations, and generate high stresses. In general, the material behavior of SMAs is nonlinear and hysteresic. To achieve the full potential of SMA actuators, it is necessary to develop models that characterize the nonlinearities and hysteresis inherent in the constituent materials. Additionally, the design of SMA actuators necessitates the development of control algorithms based on those models. We develop two models that quantify the nonlinearities and hysteresis inherent to SMAs, each in formulations suitable for subsequent control design. In the first model, we employ domain theory to quantify SMA behavior under isothermal conditions. The model involves a single first-order, nonlinear ordinary differential equation and requires as few as seven parameters that are identifiable from measurements. We develop the second model using the Muller-Achenbach-Seelecke framework where a transition state theory of nonequilibrium processes is used to derive rate laws for the evolution of material phase fractions. The fully thermomechanical model predicts rate-dependent, polycrystalline SMA behavior, and it accommodates heat transfer issues pertinent to thin-film SMAs. Furthermore, the model admits a low-order formulation and has a small number of parameters which can be readily identified using attributes of measured data. We illustrate aspects of both models through comparison with experimental bulk and thin-film SMA data.

Stability analysis for stochastic BAM nonlinear neural network with delays

NASA Astrophysics Data System (ADS)

Lv, Z. W.; Shu, H. S.; Wei, G. L.

2008-02-01

In this paper, stochastic bidirectional associative memory neural networks with constant or time-varying delays is considered. Based on a Lyapunov-Krasovskii functional and the stochastic stability analysis theory, we derive several sufficient conditions in order to guarantee the global asymptotically stable in the mean square. Our investigation shows that the stochastic bidirectional associative memory neural networks are globally asymptotically stable in the mean square if there are solutions to some linear matrix inequalities(LMIs). Hence, the global asymptotic stability of the stochastic bidirectional associative memory neural networks can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed global asymptotic stability criteria.

Optical computing, optical memory, and SBIRs at Foster-Miller

NASA Astrophysics Data System (ADS)

Domash, Lawrence H.

1994-03-01

A desktop design and manufacturing system for binary diffractive elements, MacBEEP, was developed with the optical researcher in mind. Optical processing systems for specialized tasks such as cellular automation computation and fractal measurement were constructed. A new family of switchable holograms has enabled several applications for control of laser beams in optical memories. New spatial light modulators and optical logic elements have been demonstrated based on a more manufacturable semiconductor technology. Novel synthetic and polymeric nonlinear materials for optical storage are under development in an integrated memory architecture. SBIR programs enable creative contributions from smaller companies, both product oriented and technology oriented, and support advances that might not otherwise be developed.

A Hippocampal Cognitive Prosthesis: Multi-Input, Multi-Output Nonlinear Modeling and VLSI Implementation

PubMed Central

Berger, Theodore W.; Song, Dong; Chan, Rosa H. M.; Marmarelis, Vasilis Z.; LaCoss, Jeff; Wills, Jack; Hampson, Robert E.; Deadwyler, Sam A.; Granacki, John J.

2012-01-01

This paper describes the development of a cognitive prosthesis designed to restore the ability to form new long-term memories typically lost after damage to the hippocampus. The animal model used is delayed nonmatch-to-sample (DNMS) behavior in the rat, and the “core” of the prosthesis is a biomimetic multi-input/multi-output (MIMO) nonlinear model that provides the capability for predicting spatio-temporal spike train output of hippocampus (CA1) based on spatio-temporal spike train inputs recorded presynaptically to CA1 (e.g., CA3). We demonstrate the capability of the MIMO model for highly accurate predictions of CA1 coded memories that can be made on a single-trial basis and in real-time. When hippocampal CA1 function is blocked and long-term memory formation is lost, successful DNMS behavior also is abolished. However, when MIMO model predictions are used to reinstate CA1 memory-related activity by driving spatio-temporal electrical stimulation of hippocampal output to mimic the patterns of activity observed in control conditions, successful DNMS behavior is restored. We also outline the design in very-large-scale integration for a hardware implementation of a 16-input, 16-output MIMO model, along with spike sorting, amplification, and other functions necessary for a total system, when coupled together with electrode arrays to record extracellularly from populations of hippocampal neurons, that can serve as a cognitive prosthesis in behaving animals. PMID:22438335

Adaptive learning in complex reproducing kernel Hilbert spaces employing Wirtinger's subgradients.

PubMed

Bouboulis, Pantelis; Slavakis, Konstantinos; Theodoridis, Sergios

2012-03-01

This paper presents a wide framework for non-linear online supervised learning tasks in the context of complex valued signal processing. The (complex) input data are mapped into a complex reproducing kernel Hilbert space (RKHS), where the learning phase is taking place. Both pure complex kernels and real kernels (via the complexification trick) can be employed. Moreover, any convex, continuous and not necessarily differentiable function can be used to measure the loss between the output of the specific system and the desired response. The only requirement is the subgradient of the adopted loss function to be available in an analytic form. In order to derive analytically the subgradients, the principles of the (recently developed) Wirtinger's calculus in complex RKHS are exploited. Furthermore, both linear and widely linear (in RKHS) estimation filters are considered. To cope with the problem of increasing memory requirements, which is present in almost all online schemes in RKHS, the sparsification scheme, based on projection onto closed balls, has been adopted. We demonstrate the effectiveness of the proposed framework in a non-linear channel identification task, a non-linear channel equalization problem and a quadrature phase shift keying equalization scheme, using both circular and non circular synthetic signal sources.

Stochastic Erosion of Fractal Structure in Nonlinear Dynamical Systems

NASA Astrophysics Data System (ADS)

Agarwal, S.; Wettlaufer, J. S.

2014-12-01

We analyze the effects of stochastic noise on the Lorenz-63 model in the chaotic regime to demonstrate a set of general issues arising in the interpretation of data from nonlinear dynamical systems typical in geophysics. The model is forced using both additive and multiplicative, white and colored noise and it is shown that, through a suitable choice of the noise intensity, both additive and multiplicative noise can produce similar dynamics. We use a recently developed measure, histogram distance, to show the similarity between the dynamics produced by additive and multiplicative forcing. This phenomenon, in a nonlinear fractal structure with chaotic dynamics can be explained by understanding how noise affects the Unstable Periodic Orbits (UPOs) of the system. For delta-correlated noise, the UPOs erode the fractal structure. In the presence of memory in the noise forcing, the time scale of the noise starts to interact with the period of some UPO and, depending on the noise intensity, stochastic resonance may be observed. This also explains the mixing in dissipative dynamical systems in presence of white noise; as the fractal structure is smoothed, the decay of correlations is enhanced, and hence the rate of mixing increases with noise intensity.

Time-local equation for exact time-dependent optimized effective potential in time-dependent density functional theory

NASA Astrophysics Data System (ADS)

Liao, Sheng-Lun; Ho, Tak-San; Rabitz, Herschel; Chu, Shih-I.

2017-04-01

Solving and analyzing the exact time-dependent optimized effective potential (TDOEP) integral equation has been a longstanding challenge due to its highly nonlinear and nonlocal nature. To meet the challenge, we derive an exact time-local TDOEP equation that admits a unique real-time solution in terms of time-dependent Kohn-Sham orbitals and effective memory orbitals. For illustration, the dipole evolution dynamics of a one-dimension-model chain of hydrogen atoms is numerically evaluated and examined to demonstrate the utility of the proposed time-local formulation. Importantly, it is shown that the zero-force theorem, violated by the time-dependent Krieger-Li-Iafrate approximation, is fulfilled in the current TDOEP framework. This work was partially supported by DOE.

Closing the Loop for Memory Prostheses: Detecting the Role of Hippocampal Neural Ensembles Using Nonlinear Models

PubMed Central

Hampson, Robert E.; Song, Dong; Chan, Rosa H.M.; Sweatt, Andrew J.; Riley, Mitchell R.; Goonawardena, Anushka V.; Marmarelis, Vasilis Z.; Gerhardt, Greg A.; Berger, Theodore W.; Deadwyler, Sam A.

2012-01-01

A major factor involved in providing closed loop feedback for control of neural function is to understand how neural ensembles encode online information critical to the final behavioral endpoint. This issue was directly assessed in rats performing a short-term delay memory task in which successful encoding of task information is dependent upon specific spatiotemporal firing patterns recorded from ensembles of CA3 and CA1 hippocampal neurons. Such patterns, extracted by a specially designed nonlinear multi-input multi-output (MIMO) nonlinear mathematical model, were used to predict successful performance online via a closed loop paradigm which regulated trial difficulty (time of retention) as a function of the “strength” of stimulus encoding. The significance of the MIMO model as a neural prosthesis has been demonstrated by substituting trains of electrical stimulation pulses to mimic these same ensemble firing patterns. This feature was used repeatedly to vary “normal” encoding as a means of understanding how neural ensembles can be “tuned” to mimic the inherent process of selecting codes of different strength and functional specificity. The capacity to enhance and tune hippocampal encoding via MIMO model detection and insertion of critical ensemble firing patterns shown here provides the basis for possible extension to other disrupted brain circuitry. PMID:22498704

Modification of 2-D Time-Domain Shallow Water Wave Equation using Asymptotic Expansion Method

NASA Astrophysics Data System (ADS)

Khairuman, Teuku; Nasruddin, MN; Tulus; Ramli, Marwan

2018-01-01

Generally, research on the tsunami wave propagation model can be conducted by using a linear model of shallow water theory, where a non-linear side on high order is ignored. In line with research on the investigation of the tsunami waves, the Boussinesq equation model underwent a change aimed to obtain an improved quality of the dispersion relation and non-linearity by increasing the order to be higher. To solve non-linear sides at high order is used a asymptotic expansion method. This method can be used to solve non linear partial differential equations. In the present work, we found that this method needs much computational time and memory with the increase of the number of elements.

Interaction of solitons with a string of coupled quantum dots

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

Kumar, Vijendra, E-mail: vsmedphysics@gmail.com; Swami, O. P., E-mail: omg1789@gmail.com; Nagar, A. K., E-mail: ajaya.nagar@gmail.com

2016-05-06

In this paper, we develop a theory for discrete solitons interaction with a string of coupled quantum dots in view of the local field effects. Discrete nonlinear Schrodinger (DNLS) equations are used to describe the dynamics of the string. Numerical calculations are carried out and results are analyzed with the help of matlab software. With the help of numerical solutions we demonstrate that in the quantum dots string, Rabi oscillations (RO) are self trapped into stable bright Rabi solitons. The Rabi oscillations in different types of nanostructures have potential applications to the elements of quantum logic and quantum memory.

Systematic construction and control of stereo nerve vision network in intelligent manufacturing

NASA Astrophysics Data System (ADS)

Liu, Hua; Wang, Helong; Guo, Chunjie; Ding, Quanxin; Zhou, Liwei

2017-10-01

A system method of constructing stereo vision by using neural network is proposed, and the operation and control mechanism in actual operation are proposed. This method makes effective use of the neural network in learning and memory function, by after training with samples. Moreover, the neural network can learn the nonlinear relationship in the stereoscopic vision system and the internal and external orientation elements. These considerations are Worthy of attention, which includes limited constraints, the scientific of critical group, the operating speed and the operability in technical aspects. The results support our theoretical forecast.

Harmonic analysis of spacecraft power systems using a personal computer

NASA Technical Reports Server (NTRS)

Williamson, Frank; Sheble, Gerald B.

1989-01-01

The effects that nonlinear devices such as ac/dc converters, HVDC transmission links, and motor drives have on spacecraft power systems are discussed. The nonsinusoidal currents, along with the corresponding voltages, are calculated by a harmonic power flow which decouples and solves for each harmonic component individually using an iterative Newton-Raphson algorithm. The sparsity of the harmonic equations and the overall Jacobian matrix is used to an advantage in terms of saving computer memory space and in terms of reducing computation time. The algorithm could also be modified to analyze each harmonic separately instead of all at the same time.

Assessing the dream-lag effect for REM and NREM stage 2 dreams.

PubMed

Blagrove, Mark; Fouquet, Nathalie C; Henley-Einion, Josephine A; Pace-Schott, Edward F; Davies, Anna C; Neuschaffer, Jennifer L; Turnbull, Oliver H

2011-01-01

This study investigates evidence, from dream reports, for memory consolidation during sleep. It is well-known that events and memories from waking life can be incorporated into dreams. These incorporations can be a literal replication of what occurred in waking life, or, more often, they can be partial or indirect. Two types of temporal relationship have been found to characterize the time of occurrence of a daytime event and the reappearance or incorporation of its features in a dream. These temporal relationships are referred to as the day-residue or immediate incorporation effect, where there is the reappearance of features from events occurring on the immediately preceding day, and the dream-lag effect, where there is the reappearance of features from events occurring 5-7 days prior to the dream. Previous work on the dream-lag effect has used spontaneous home recalled dream reports, which can be from Rapid Eye Movement Sleep (REM) and from non-Rapid Eye Movement Sleep (NREM). This study addresses whether the dream-lag effect occurs only for REM sleep dreams, or for both REM and NREM stage 2 (N2) dreams. 20 participants kept a daily diary for over a week before sleeping in the sleep laboratory for 2 nights. REM and N2 dreams collected in the laboratory were transcribed and each participant rated the level of correspondence between every dream report and every diary record. The dream-lag effect was found for REM but not N2 dreams. Further analysis indicated that this result was not due to N2 dream reports being shorter, in terms of number of words, than the REM dream reports. These results provide evidence for a 7-day sleep-dependent non-linear memory consolidation process that is specific to REM sleep, and accord with proposals for the importance of REM sleep to emotional memory consolidation.

Assessing the Dream-Lag Effect for REM and NREM Stage 2 Dreams

PubMed Central

Blagrove, Mark; Fouquet, Nathalie C.; Henley-Einion, Josephine A.; Pace-Schott, Edward F.; Davies, Anna C.; Neuschaffer, Jennifer L.; Turnbull, Oliver H.

2011-01-01

This study investigates evidence, from dream reports, for memory consolidation during sleep. It is well-known that events and memories from waking life can be incorporated into dreams. These incorporations can be a literal replication of what occurred in waking life, or, more often, they can be partial or indirect. Two types of temporal relationship have been found to characterize the time of occurrence of a daytime event and the reappearance or incorporation of its features in a dream. These temporal relationships are referred to as the day-residue or immediate incorporation effect, where there is the reappearance of features from events occurring on the immediately preceding day, and the dream-lag effect, where there is the reappearance of features from events occurring 5–7 days prior to the dream. Previous work on the dream-lag effect has used spontaneous home recalled dream reports, which can be from Rapid Eye Movement Sleep (REM) and from non-Rapid Eye Movement Sleep (NREM). This study addresses whether the dream-lag effect occurs only for REM sleep dreams, or for both REM and NREM stage 2 (N2) dreams. 20 participants kept a daily diary for over a week before sleeping in the sleep laboratory for 2 nights. REM and N2 dreams collected in the laboratory were transcribed and each participant rated the level of correspondence between every dream report and every diary record. The dream-lag effect was found for REM but not N2 dreams. Further analysis indicated that this result was not due to N2 dream reports being shorter, in terms of number of words, than the REM dream reports. These results provide evidence for a 7-day sleep-dependent non-linear memory consolidation process that is specific to REM sleep, and accord with proposals for the importance of REM sleep to emotional memory consolidation. PMID:22046336

A Unified Dynamic Model for Learning, Replay, and Sharp-Wave/Ripples.

PubMed

Jahnke, Sven; Timme, Marc; Memmesheimer, Raoul-Martin

2015-12-09

Hippocampal activity is fundamental for episodic memory formation and consolidation. During phases of rest and sleep, it exhibits sharp-wave/ripple (SPW/R) complexes, which are short episodes of increased activity with superimposed high-frequency oscillations. Simultaneously, spike sequences reflecting previous behavior, such as traversed trajectories in space, are replayed. Whereas these phenomena are thought to be crucial for the formation and consolidation of episodic memory, their neurophysiological mechanisms are not well understood. Here we present a unified model showing how experience may be stored and thereafter replayed in association with SPW/Rs. We propose that replay and SPW/Rs are tightly interconnected as they mutually generate and support each other. The underlying mechanism is based on the nonlinear dendritic computation attributable to dendritic sodium spikes that have been prominently found in the hippocampal regions CA1 and CA3, where SPW/Rs and replay are also generated. Besides assigning SPW/Rs a crucial role for replay and thus memory processing, the proposed mechanism also explains their characteristic features, such as the oscillation frequency and the overall wave form. The results shed a new light on the dynamical aspects of hippocampal circuit learning. During phases of rest and sleep, the hippocampus, the "memory center" of the brain, generates intermittent patterns of strongly increased overall activity with high-frequency oscillations, the so-called sharp-wave/ripples. We investigate their role in learning and memory processing. They occur together with replay of activity sequences reflecting previous behavior. Developing a unifying computational model, we propose that both phenomena are tightly linked, by mutually generating and supporting each other. The underlying mechanism depends on nonlinear amplification of synchronous inputs that has been prominently found in the hippocampus. Besides assigning sharp-wave/ripples a crucial role for replay generation and thus memory processing, the proposed mechanism also explains their characteristic features, such as the oscillation frequency and the overall wave form. Copyright © 2015 the authors 0270-6474/15/3516236-23$15.00/0.

Nicolaas Bloembergen as a scientist and a mentor

NASA Astrophysics Data System (ADS)

Liu, Jia-Ming

2018-03-01

Nicolaas Bloembergen made rich contributions to nuclear magnetic resonance, masers and lasers, nonlinear optics and ultrafast laser-matter interactions. The Nobel laureate sadly passed away on 5 September 2017. Here are my memories of my Harvard mentor, a remarkable person and a wonderful scientist.

Blind equalization with criterion with memory nonlinearity

NASA Astrophysics Data System (ADS)

Chen, Yuanjie; Nikias, Chrysostomos L.; Proakis, John G.

1992-06-01

Blind equalization methods usually combat the linear distortion caused by a nonideal channel via a transversal filter, without resorting to the a priori known training sequences. We introduce a new criterion with memory nonlinearity (CRIMNO) for the blind equalization problem. The basic idea of this criterion is to augment the Godard [or constant modulus algorithm (CMA)] cost function with additional terms that penalize the autocorrelations of the equalizer outputs. Several variations of the CRIMNO algorithms are derived, with the variations dependent on (1) whether the empirical averages or the single point estimates are used to approximate the expectations, (2) whether the recent or the delayed equalizer coefficients are used, and (3) whether the weights applied to the autocorrelation terms are fixed or are allowed to adapt. Simulation experiments show that the CRIMNO algorithm, and especially its adaptive weight version, exhibits faster convergence speed than the Godard (or CMA) algorithm. Extensions of the CRIMNO criterion to accommodate the case of correlated inputs to the channel are also presented.

Solution of large nonlinear quasistatic structural mechanics problems on distributed-memory multiprocessor computers

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

Blanford, M.

1997-12-31

Most commercially-available quasistatic finite element programs assemble element stiffnesses into a global stiffness matrix, then use a direct linear equation solver to obtain nodal displacements. However, for large problems (greater than a few hundred thousand degrees of freedom), the memory size and computation time required for this approach becomes prohibitive. Moreover, direct solution does not lend itself to the parallel processing needed for today`s multiprocessor systems. This talk gives an overview of the iterative solution strategy of JAS3D, the nonlinear large-deformation quasistatic finite element program. Because its architecture is derived from an explicit transient-dynamics code, it does not ever assemblemore » a global stiffness matrix. The author describes the approach he used to implement the solver on multiprocessor computers, and shows examples of problems run on hundreds of processors and more than a million degrees of freedom. Finally, he describes some of the work he is presently doing to address the challenges of iterative convergence for ill-conditioned problems.« less

Tracking Control of a Magnetic Shape Memory Actuator Using an Inverse Preisach Model with Modified Fuzzy Sliding Mode Control.

PubMed

Lin, Jhih-Hong; Chiang, Mao-Hsiung

2016-08-25

Magnetic shape memory (MSM) alloys are a new class of smart materials with extraordinary strains up to 12% and frequencies in the range of 1 to 2 kHz. The MSM actuator is a potential device which can achieve high performance electromagnetic actuation by using the properties of MSM alloys. However, significant non-linear hysteresis behavior is a significant barrier to control the MSM actuator. In this paper, the Preisach model was used, by capturing experiments from different input signals and output responses, to model the hysteresis of MSM actuator, and the inverse Preisach model, as a feedforward control, provided compensational signals to the MSM actuator to linearize the hysteresis non-linearity. The control strategy for path tracking combined the hysteresis compensator and the modified fuzzy sliding mode control (MFSMC) which served as a path controller. Based on the experimental results, it was verified that a tracking error in the order of micrometers was achieved.

Tracking Control of a Magnetic Shape Memory Actuator Using an Inverse Preisach Model with Modified Fuzzy Sliding Mode Control

PubMed Central

Lin, Jhih-Hong; Chiang, Mao-Hsiung

2016-01-01

Magnetic shape memory (MSM) alloys are a new class of smart materials with extraordinary strains up to 12% and frequencies in the range of 1 to 2 kHz. The MSM actuator is a potential device which can achieve high performance electromagnetic actuation by using the properties of MSM alloys. However, significant non-linear hysteresis behavior is a significant barrier to control the MSM actuator. In this paper, the Preisach model was used, by capturing experiments from different input signals and output responses, to model the hysteresis of MSM actuator, and the inverse Preisach model, as a feedforward control, provided compensational signals to the MSM actuator to linearize the hysteresis non-linearity. The control strategy for path tracking combined the hysteresis compensator and the modified fuzzy sliding mode control (MFSMC) which served as a path controller. Based on the experimental results, it was verified that a tracking error in the order of micrometers was achieved. PMID:27571081

From non-linear magnetoacoustics and spin reorientation transition to magnetoelectric micro/nano-systems

NASA Astrophysics Data System (ADS)

Tiercelin, Nicolas; Preobrazhensky, Vladimir; BouMatar, Olivier; Talbi, Abdelkrim; Giordano, Stefano; Dusch, Yannick; Klimov, Alexey; Mathurin, Théo.; Elmazria, Omar; Hehn, Michel; Pernod, Philippe

2017-09-01

The interaction of a strongly nonlinear spin system with a crystalline lattice through magnetoelastic coupling results in significant modifications of the acoustic properties of magnetic materials, especially in the vicinity of magnetic instabilities associated with the spin-reorientation transition (SRT). The magnetoelastic coupling transfers the critical properties of the magnetic subsystem to the elastic one, which leads to a strong decrease of the sound velocity in the vicinity of the SRT, and allows a large control over acoustic nonlinearities. The general principles of the non-linear magneto-acoustics (NMA) will be introduced and illustrated in `bulk' applications such as acoustic wave phase conjugation, multi-phonon coupling, explosive instability of magneto-elastic vibrations, etc. The concept of the SRT coupled to magnetoelastic interaction has been transferred into nanostructured magnetoelastic multilayers with uni-axial anisotropy. The high sensitivity and the non-linear properties have been demonstrated in cantilever type actuators, and phenomena such as magneto-mechanical RF demodulation have been observed. The combination of the magnetic layers with piezoelectric materials also led to stress-mediated magnetoelectric (ME) composites with high ME coefficients, thanks to the SRT. The magnetoacoustic effects of the SRT have also been studied for surface acoustic waves propagating in the magnetoelastic layers and found to be promising for highly sensitive magnetic field sensors working at room temperature. On the other hand, mechanical stress is a very efficient way to control the magnetic subsystem. The principle of a very energy efficient stress-mediated magnetoelectric writing and reading in a magnetic memory is described.

Creation of long-term coherent optical memory via controlled nonlinear interactions in Bose-Einstein condensates.

PubMed

Zhang, Rui; Garner, Sean R; Hau, Lene Vestergaard

2009-12-04

A Bose-Einstein condensate confined in an optical dipole trap is used to generate long-term coherent memory for light, and storage times of more than 1 s are observed. Phase coherence of the condensate as well as controlled manipulations of elastic and inelastic atomic scattering processes are utilized to increase the storage fidelity by several orders of magnitude over previous schemes. The results have important applications for creation of long-distance quantum networks and for generation of entangled states of light and matter.

Giant and universal magnetoelectric coupling in soft materials and concomitant ramifications for materials science and biology

NASA Astrophysics Data System (ADS)

Liu, Liping; Sharma, Pradeep

2013-10-01

Magnetoelectric coupling—the ability of a material to magnetize upon application of an electric field and, conversely, to polarize under the action of a magnetic field—is rare and restricted to a rather small set of exotic hard crystalline materials. Intense research activity has recently ensued on materials development, fundamental scientific issues, and applications related to this phenomenon. This tantalizing property, if present in adequate strength at room temperature, can be used to pave the way for next-generation memory devices such as miniature magnetic random access memories and multiple state memory bits, sensors, energy harvesting, spintronics, among others. In this Rapid Communication, we prove the existence of an overlooked strain mediated nonlinear mechanism that can be used to universally induce the giant magnetoelectric effect in all (sufficiently) soft dielectric materials. For soft polymer foams—which, for instance, may be used in stretchable electronics—we predict room-temperature magnetoelectric coefficients that are comparable to the best known (hard) composite materials created. We also argue, based on a simple quantitative model, that magnetoreception in some biological contexts (e.g., birds) most likely utilizes this very mechanism.

Applications of Shape Memory Alloys for Neurology and Neuromuscular Rehabilitation

PubMed Central

Pittaccio, Simone; Garavaglia, Lorenzo; Ceriotti, Carlo; Passaretti, Francesca

2015-01-01

Shape memory alloys (SMAs) are a very promising class of metallic materials that display interesting nonlinear properties, such as pseudoelasticity (PE), shape memory effect (SME) and damping capacity, due to high mechanical hysteresis and internal friction. Our group has applied SMA in the field of neuromuscular rehabilitation, designing some new devices based on the mentioned SMA properties: in particular, a new type of orthosis for spastic limb repositioning, which allows residual voluntary movement of the impaired limb and has no predetermined final target position, but follows and supports muscular elongation in a dynamic and compliant way. Considering patients in the sub-acute phase after a neurological lesion, and possibly bedridden, the paper presents a mobiliser for the ankle joint, which is designed exploiting the SME to provide passive exercise to the paretic lower limb. Two different SMA-based applications in the field of neuroscience are then presented, a guide and a limb mobiliser specially designed to be compatible with diagnostic instrumentations that impose rigid constraints in terms of electromagnetic compatibility and noise distortion. Finally, the paper discusses possible uses of these materials in the treatment of movement disorders, such as dystonia or hyperkinesia, where their dynamic characteristics can be advantageous. PMID:26023790

Complex dynamics of semantic memory access in reading.

PubMed

Baggio, Giosué; Fonseca, André

2012-02-07

Understanding a word in context relies on a cascade of perceptual and conceptual processes, starting with modality-specific input decoding, and leading to the unification of the word's meaning into a discourse model. One critical cognitive event, turning a sensory stimulus into a meaningful linguistic sign, is the access of a semantic representation from memory. Little is known about the changes that activating a word's meaning brings about in cortical dynamics. We recorded the electroencephalogram (EEG) while participants read sentences that could contain a contextually unexpected word, such as 'cold' in 'In July it is very cold outside'. We reconstructed trajectories in phase space from single-trial EEG time series, and we applied three nonlinear measures of predictability and complexity to each side of the semantic access boundary, estimated as the onset time of the N400 effect evoked by critical words. Relative to controls, unexpected words were associated with larger prediction errors preceding the onset of the N400. Accessing the meaning of such words produced a phase transition to lower entropy states, in which cortical processing becomes more predictable and more regular. Our study sheds new light on the dynamics of information flow through interfaces between sensory and memory systems during language processing.

Electrochromic conductive polymer fuses for hybrid organic/inorganic semiconductor memories

NASA Astrophysics Data System (ADS)

Möller, Sven; Forrest, Stephen R.; Perlov, Craig; Jackson, Warren; Taussig, Carl

2003-12-01

We demonstrate a nonvolatile, write-once-read-many-times (WORM) memory device employing a hybrid organic/inorganic semiconductor architecture consisting of thin film p-i-n silicon diode on a stainless steel substrate integrated in series with a conductive polymer fuse. The nonlinearity of the silicon diodes enables a passive matrix memory architecture, while the conductive polyethylenedioxythiophene:polystyrene sulfonic acid polymer serves as a reliable switch with fuse-like behavior for data storage. The polymer can be switched at ˜2 μs, resulting in a permanent decrease of conductivity of the memory pixel by up to a factor of 103. The switching mechanism is primarily due to a current and thermally dependent redox reaction in the polymer, limited by the double injection of both holes and electrons. The switched device performance does not degrade after many thousand read cycles in ambient at room temperature. Our results suggest that low cost, organic/inorganic WORM memories are feasible for light weight, high density, robust, and fast archival storage applications.

Dynamical principles in neuroscience

NASA Astrophysics Data System (ADS)

Rabinovich, Mikhail I.; Varona, Pablo; Selverston, Allen I.; Abarbanel, Henry D. I.

2006-10-01

Dynamical modeling of neural systems and brain functions has a history of success over the last half century. This includes, for example, the explanation and prediction of some features of neural rhythmic behaviors. Many interesting dynamical models of learning and memory based on physiological experiments have been suggested over the last two decades. Dynamical models even of consciousness now exist. Usually these models and results are based on traditional approaches and paradigms of nonlinear dynamics including dynamical chaos. Neural systems are, however, an unusual subject for nonlinear dynamics for several reasons: (i) Even the simplest neural network, with only a few neurons and synaptic connections, has an enormous number of variables and control parameters. These make neural systems adaptive and flexible, and are critical to their biological function. (ii) In contrast to traditional physical systems described by well-known basic principles, first principles governing the dynamics of neural systems are unknown. (iii) Many different neural systems exhibit similar dynamics despite having different architectures and different levels of complexity. (iv) The network architecture and connection strengths are usually not known in detail and therefore the dynamical analysis must, in some sense, be probabilistic. (v) Since nervous systems are able to organize behavior based on sensory inputs, the dynamical modeling of these systems has to explain the transformation of temporal information into combinatorial or combinatorial-temporal codes, and vice versa, for memory and recognition. In this review these problems are discussed in the context of addressing the stimulating questions: What can neuroscience learn from nonlinear dynamics, and what can nonlinear dynamics learn from neuroscience?

Dynamical principles in neuroscience

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

Rabinovich, Mikhail I.; Varona, Pablo; Selverston, Allen I.

Dynamical modeling of neural systems and brain functions has a history of success over the last half century. This includes, for example, the explanation and prediction of some features of neural rhythmic behaviors. Many interesting dynamical models of learning and memory based on physiological experiments have been suggested over the last two decades. Dynamical models even of consciousness now exist. Usually these models and results are based on traditional approaches and paradigms of nonlinear dynamics including dynamical chaos. Neural systems are, however, an unusual subject for nonlinear dynamics for several reasons: (i) Even the simplest neural network, with only amore » few neurons and synaptic connections, has an enormous number of variables and control parameters. These make neural systems adaptive and flexible, and are critical to their biological function. (ii) In contrast to traditional physical systems described by well-known basic principles, first principles governing the dynamics of neural systems are unknown. (iii) Many different neural systems exhibit similar dynamics despite having different architectures and different levels of complexity. (iv) The network architecture and connection strengths are usually not known in detail and therefore the dynamical analysis must, in some sense, be probabilistic. (v) Since nervous systems are able to organize behavior based on sensory inputs, the dynamical modeling of these systems has to explain the transformation of temporal information into combinatorial or combinatorial-temporal codes, and vice versa, for memory and recognition. In this review these problems are discussed in the context of addressing the stimulating questions: What can neuroscience learn from nonlinear dynamics, and what can nonlinear dynamics learn from neuroscience?.« less

Machine Learning-based discovery of closures for reduced models of dynamical systems

NASA Astrophysics Data System (ADS)

Pan, Shaowu; Duraisamy, Karthik

2017-11-01

Despite the successful application of machine learning (ML) in fields such as image processing and speech recognition, only a few attempts has been made toward employing ML to represent the dynamics of complex physical systems. Previous attempts mostly focus on parameter calibration or data-driven augmentation of existing models. In this work we present a ML framework to discover closure terms in reduced models of dynamical systems and provide insights into potential problems associated with data-driven modeling. Based on exact closure models for linear system, we propose a general linear closure framework from viewpoint of optimization. The framework is based on trapezoidal approximation of convolution term. Hyperparameters that need to be determined include temporal length of memory effect, number of sampling points, and dimensions of hidden states. To circumvent the explicit specification of memory effect, a general framework inspired from neural networks is also proposed. We conduct both a priori and posteriori evaluations of the resulting model on a number of non-linear dynamical systems. This work was supported in part by AFOSR under the project ``LES Modeling of Non-local effects using Statistical Coarse-graining'' with Dr. Jean-Luc Cambier as the technical monitor.

Exploiting short-term memory in soft body dynamics as a computational resource

PubMed Central

Nakajima, K.; Li, T.; Hauser, H.; Pfeifer, R.

2014-01-01

Soft materials are not only highly deformable, but they also possess rich and diverse body dynamics. Soft body dynamics exhibit a variety of properties, including nonlinearity, elasticity and potentially infinitely many degrees of freedom. Here, we demonstrate that such soft body dynamics can be employed to conduct certain types of computation. Using body dynamics generated from a soft silicone arm, we show that they can be exploited to emulate functions that require memory and to embed robust closed-loop control into the arm. Our results suggest that soft body dynamics have a short-term memory and can serve as a computational resource. This finding paves the way towards exploiting passive body dynamics for control of a large class of underactuated systems. PMID:25185579

Three-dimensional optical memory systems based on photochromic materials: polarization control of two-color data writing and the possibility of nondestructive data reading

NASA Astrophysics Data System (ADS)

Akimov, D. A.; Fedotov, Andrei B.; Koroteev, Nikolai I.; Magnitskii, S. A.; Naumov, A. N.; Sidorov-Biryukov, Dmitri A.; Sokoluk, N. T.; Zheltikov, Alexei M.

1998-04-01

The possibilities of optimizing data writing and reading in devices of 3D optical memory using photochromic materials are discussed. We quantitatively analyze linear and nonlinear optical properties of induline spiropyran molecules, which allows us to estimate the efficiency of using such materials for implementing 3D optical-memory devices. It is demonstrated that, with an appropriate choice of polarization vectors of laser beams, one can considerably improve the efficiency of two-photon writing in photochromic materials. The problem of reading the data stored in a photochromic material is analyzed. The possibilities of data reading methods with the use of fluorescence and four-photon techniques are compared.

A Little Goes a Long Way: Low Working Memory Load Is Associated with Optimal Distractor Inhibition and Increased Vagal Control under Anxiety.

PubMed

Spangler, Derek P; Friedman, Bruce H

2017-01-01

Anxiety impairs both inhibition of distraction and attentional focus. It is unclear whether these impairments are reduced or exacerbated when loading working memory with non-affective information. Cardiac vagal control has been related to top-down regulation of anxiety; therefore, vagal control may reflect load-related inhibition of distraction under anxiety. The present study examined whether: (1) the enhancing and impairing effects of load on inhibition exist together in a non-linear function, (2) there is a similar association between inhibition and concurrent vagal control under anxiety. During anxiogenic threat-of-noise, 116 subjects maintained a digit series of varying lengths (0, 2, 4, and 6 digits) while completing a visual flanker task. The task was broken into four blocks, with a baseline period preceding each. Electrocardiography was acquired throughout to quantify vagal control as high-frequency heart rate variability (HRV). There were significant quadratic relations of working memory load to flanker performance and to HRV, but no associations between HRV and performance. Results indicate that low load was associated with relatively better inhibition and increased HRV. These findings suggest that attentional performance under anxiety depends on the availability of working memory resources, which might be reflected by vagal control. These results have implications for treating anxiety disorders, in which regulation of anxiety can be optimized for attentional focus.

Relation between acute and long-term cognitive decline after surgery: Influence of metabolic syndrome.

PubMed

Gambús, P L; Trocóniz, I F; Feng, X; Gimenez-Milá, M; Mellado, R; Degos, V; Vacas, S; Maze, M

2015-11-01

The relationship between persistent postoperative cognitive decline and the more common acute variety remains unknown; using data acquired in preclinical studies of postoperative cognitive decline we attempted to characterize this relationship. Low capacity runner (LCR) rats, which have all the features of the metabolic syndrome, were compared postoperatively with high capacity runner (HCR) rats for memory, assessed by trace fear conditioning (TFC) on the 7th postoperative day, and learning and memory (probe trial [PT]) assessed by the Morris water-maze (MWM) at 3 months postoperatively. Rate of learning (AL) data from the MWM test, were estimated by non-linear mixed effects modeling. The individual rat's TFC result at postoperative day (POD) 7 was correlated with its AL and PT from the MWM data sets at postoperative day POD 90. A single exponential decay model best described AL in the MWM with LCR and surgery (LCR-SURG) being the only significant covariates; first order AL rate constant was 0.07 s(-1) in LCR-SURG and 0.16s(-1) in the remaining groups (p<0.05). TFC was significantly correlated with both AL (R=0.74; p<0.0001) and PT (R=0.49; p<0.01). Severity of memory decline at 1 week after surgery presaged long-lasting deteriorations in learning and memory. Copyright © 2015 Elsevier Inc. All rights reserved.

A Little Goes a Long Way: Low Working Memory Load Is Associated with Optimal Distractor Inhibition and Increased Vagal Control under Anxiety

PubMed Central

Spangler, Derek P.; Friedman, Bruce H.

2017-01-01

Anxiety impairs both inhibition of distraction and attentional focus. It is unclear whether these impairments are reduced or exacerbated when loading working memory with non-affective information. Cardiac vagal control has been related to top–down regulation of anxiety; therefore, vagal control may reflect load-related inhibition of distraction under anxiety. The present study examined whether: (1) the enhancing and impairing effects of load on inhibition exist together in a non-linear function, (2) there is a similar association between inhibition and concurrent vagal control under anxiety. During anxiogenic threat-of-noise, 116 subjects maintained a digit series of varying lengths (0, 2, 4, and 6 digits) while completing a visual flanker task. The task was broken into four blocks, with a baseline period preceding each. Electrocardiography was acquired throughout to quantify vagal control as high-frequency heart rate variability (HRV). There were significant quadratic relations of working memory load to flanker performance and to HRV, but no associations between HRV and performance. Results indicate that low load was associated with relatively better inhibition and increased HRV. These findings suggest that attentional performance under anxiety depends on the availability of working memory resources, which might be reflected by vagal control. These results have implications for treating anxiety disorders, in which regulation of anxiety can be optimized for attentional focus. PMID:28217091

Christodoulou Memory of GW150914 - Prospects of Detection in LIGO and Future Detectors

NASA Astrophysics Data System (ADS)

Johnson, Aaron; Kapadia, Shasvath; Kennefick, Daniel

2017-01-01

The event GW150914 produced strains of the order 10-21 in the two instruments comprising the Laser Interferometric Gravitational Wave Observatory (LIGO). The event has been interpreted as originating in a coalescing black hole binary, with individual components of about 30 solar masses each. A striking aspect of the coalescence deduced from the signal is the emission of 3 solar masses of energy in the oscillating gravitational wave. Theory predicts a DC component of the gravitational signal associated with the emission of such large amounts of gravitational wave energy known as the Christodoulou memory. The memory, as a non-linear component of the signal, is expected to be an order of magnitude smaller than the amplitude of the primary AC component of the gravitational waves. We discuss the prospects of detecting the Christodoulou memory in similar future signals, both with LIGO and with other detectors, including future space-based instruments.

Static analysis of C-shape SMA middle ear prosthesis

NASA Astrophysics Data System (ADS)

Latalski, Jarosław; Rusinek, Rafał

2017-08-01

Shape memory alloys are a family of metals with the ability to change specimen shape depending on their temperature. This unique property is useful in many areas of mechanical and biomechanical engineering. A new half-ring middle ear prosthesis design made of a shape memory alloy, that is undergoing initial clinical tests, is investigated in this research paper. The analytical model of the studied structure made of nonlinear constitutive material is solved to identify the temperature-dependent stiffness characteristics of the proposed design on the basis of the Crotti-Engesser theorem. The final integral expression for the element deflection is highly complex, thus the solution has to be computed numerically. The final results show the proposed shape memory C-shape element to behave linearly in the analysed range of loadings and temperatures. This is an important observation that significantly simplifies the analysis of the prototype structure and opens wide perspectives for further possible applications of shape memory alloys.

Semantic priming increases word frequency judgments: Evidence for the role of memory strength in frequency estimation.

PubMed

Woltz, Dan J; Gardner, Michael K

2015-09-01

Previous research has demonstrated a systematic, nonlinear relationship between word frequency judgments and values from word frequency norms. This relationship could reflect a perceptual process similar to that found in the psychophysics literature for a variety of sensory phenomena. Alternatively, it could reflect memory strength differences that are expected for words of varying levels of prior exposure. Two experiments tested the memory strength explanation by semantically priming words prior to frequency judgments. Exposure to related word meanings produced a small but measurable increase in target word frequency ratings. Repetition but not semantic priming had a greater impact on low compared to high frequency words. These findings are consistent with a memory strength view of frequency judgments that assumes a distributed network with lexical and semantic levels of representation. Copyright © 2015 Elsevier B.V. All rights reserved.

MRI-leukoaraiosis thresholds and the phenotypic expression of dementia

PubMed Central

Mitchell, Sandra M.; Brumback, Babette; Tanner, Jared J.; Schmalfuss, Ilona; Lamar, Melissa; Giovannetti, Tania; Heilman, Kenneth M.; Libon, David J.

2012-01-01

Objective: To examine the concept of leukoaraiosis thresholds on working memory, visuoconstruction, memory, and language in dementia. Methods: A consecutive series of 83 individuals with insidious onset/progressive dementia clinically diagnosed with Alzheimer disease (AD) or small vessel vascular dementia (VaD) completed neuropsychological measures assessing working memory, visuoconstruction, episodic memory, and language. A clinical MRI scan was used to quantify leukoaraiosis, total white matter, hippocampus, lacune, and intracranial volume. We performed analyses to detect the lowest level of leukoaraiosis associated with impairment on the neuropsychological measures. Results: Leukoaraiosis ranged from 0.63% to 23.74% of participants' white matter. Leukoaraiosis explained a significant amount of variance in working memory performance when it involved 3% or more of the white matter with curve estimations showing the relationship to be nonlinear in nature. Greater leukoaraiosis (13%) was implicated for impairment in visuoconstruction. Relationships between leukoaraiosis, episodic memory, and language measures were linear or flat. Conclusions: Leukoaraiosis involves specific threshold points for working memory and visuoconstructional tests in AD/VaD spectrum dementia. These data underscore the need to better understand the threshold at which leukoaraiosis affects and alters the phenotypic expression in insidious onset dementia syndromes. PMID:22843264

Human memory manipulated: dissociating factors contributing to MTL activity, an fMRI study.

PubMed

Pustina, Dorian; Gizewski, Elke; Forsting, Michael; Daum, Irene; Suchan, Boris

2012-04-01

Memory processes are mainly studied with subjective rating procedures. We used a morphing procedure to objectively manipulate the similarity of target stimuli. While undergoing functional magnetic resonance imaging, nineteen subjects performed a encoding and recognition task on face and scene stimuli, varying the degree of manipulation of previously studied targets at 0%, 20%, 40% or 60%. Analyses were performed with parametric modulations for objective stimulus status (morphing level), subjective memory (confidence rating), and reaction times (RTs). Results showed that medial temporal lobe (MTL) activity can be best explained by a combination of subjective and objective factors. Memory success is associated with activity modulation in the hippocampus both for faces and for scenes. Memory failures correlated with lower hippocampal activity for scenes, but not for faces. Activity changed during retrieval on similar areas activated during encoding. There was a considerable impact of RTs on memory-related areas. Objective perceptual identity correlated with activity in the left MTL, while subjective memory experience correlated with activity in the right MTL for both types of material. Overall, the results indicate that MTL activity is heterogeneous, showing both linear and non-linear activity, depending on the factor analyzed. Copyright © 2011 Elsevier B.V. All rights reserved.

Encoding mechano-memories in filamentous-actin networks

NASA Astrophysics Data System (ADS)

Majumdar, Sayantan; Foucard, Louis; Levine, Alex; Gardel, Margaret L.

History-dependent adaptation is a central feature of learning and memory. Incorporating such features into `adaptable materials' that can modify their mechanical properties in response to external cues, remains an outstanding challenge in materials science. Here, we study a novel mechanism of mechano-memory in cross-linked F-actin networks, the essential determinants of the mechanical behavior of eukaryotic cells. We find that the non-linear mechanical response of such networks can be reversibly programmed through induction of mechano-memories. In particular, the direction, magnitude, and duration of previously applied shear stresses can be encoded into the network architecture. The `memory' of the forcing history is long-lived, but it can be erased by force applied in the opposite direction. These results demonstrate that F-actin networks can encode analog read-write mechano-memories which can be used for adaptation to mechanical stimuli. We further show that the mechano-memory arises from changes in the nematic order of the constituent filaments. Our results suggest a new mechanism of mechanical sensing in eukaryotic cells and provide a strategy for designing a novel class of materials. S.M. acknowledges U. Chicago MRSEC for support through a Kadanoff-Rice fellowship.

Dendritic nonlinearities reduce network size requirements and mediate ON and OFF states of persistent activity in a PFC microcircuit model.

PubMed

Papoutsi, Athanasia; Sidiropoulou, Kyriaki; Poirazi, Panayiota

2014-07-01

Technological advances have unraveled the existence of small clusters of co-active neurons in the neocortex. The functional implications of these microcircuits are in large part unexplored. Using a heavily constrained biophysical model of a L5 PFC microcircuit, we recently showed that these structures act as tunable modules of persistent activity, the cellular correlate of working memory. Here, we investigate the mechanisms that underlie persistent activity emergence (ON) and termination (OFF) and search for the minimum network size required for expressing these states within physiological regimes. We show that (a) NMDA-mediated dendritic spikes gate the induction of persistent firing in the microcircuit. (b) The minimum network size required for persistent activity induction is inversely proportional to the synaptic drive of each excitatory neuron. (c) Relaxation of connectivity and synaptic delay constraints eliminates the gating effect of NMDA spikes, albeit at a cost of much larger networks. (d) Persistent activity termination by increased inhibition depends on the strength of the synaptic input and is negatively modulated by dADP. (e) Slow synaptic mechanisms and network activity contain predictive information regarding the ability of a given stimulus to turn ON and/or OFF persistent firing in the microcircuit model. Overall, this study zooms out from dendrites to cell assemblies and suggests a tight interaction between dendritic non-linearities and network properties (size/connectivity) that may facilitate the short-memory function of the PFC.

Constitutive modeling and control of 1D smart composite structures

NASA Astrophysics Data System (ADS)

Briggs, Jonathan P.; Ostrowski, James P.; Ponte-Castaneda, Pedro

1998-07-01

Homogenization techniques for determining effective properties of composite materials may provide advantages for control of stiffness and strain in systems using hysteretic smart actuators embedded in a soft matrix. In this paper, a homogenized model of a 1D composite structure comprised of shape memory alloys and a rubber-like matrix is presented. With proportional and proportional/integral feedback, using current as the input state and global strain as an error state, implementation scenarios include the use of tractions on the boundaries and a nonlinear constitutive law for the matrix. The result is a simple model which captures the nonlinear behavior of the smart composite material system and is amenable to experiments with various control paradigms. The success of this approach in the context of the 1D model suggests that the homogenization method may prove useful in investigating control of more general smart structures. Applications of such materials could include active rehabilitation aids, e.g. wrist braces, as well as swimming/undulating robots, or adaptive molds for manufacturing processes.

Linearized Programming of Memristors for Artificial Neuro-Sensor Signal Processing

PubMed Central

Yang, Changju; Kim, Hyongsuk

2016-01-01

A linearized programming method of memristor-based neural weights is proposed. Memristor is known as an ideal element to implement a neural synapse due to its embedded functions of analog memory and analog multiplication. Its resistance variation with a voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is proposed. The anti-serial architecture is composed of two memristors with opposite polarities. It linearizes the variation of memristance due to complimentary actions of two memristors. For programming a memristor, additional memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and memristor bridge synapse which is built with two sets of anti-serial memristor architecture is taken as an application example of the proposed method. Simulations are performed with memristors of both linear drift model and nonlinear model. PMID:27548186

Linearized Programming of Memristors for Artificial Neuro-Sensor Signal Processing.

PubMed

Yang, Changju; Kim, Hyongsuk

2016-08-19

A linearized programming method of memristor-based neural weights is proposed. Memristor is known as an ideal element to implement a neural synapse due to its embedded functions of analog memory and analog multiplication. Its resistance variation with a voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is proposed. The anti-serial architecture is composed of two memristors with opposite polarities. It linearizes the variation of memristance due to complimentary actions of two memristors. For programming a memristor, additional memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and memristor bridge synapse which is built with two sets of anti-serial memristor architecture is taken as an application example of the proposed method. Simulations are performed with memristors of both linear drift model and nonlinear model.

Local interaction simulation approach to modelling nonclassical, nonlinear elastic behavior in solids.

PubMed

Scalerandi, Marco; Agostini, Valentina; Delsanto, Pier Paolo; Van Den Abeele, Koen; Johnson, Paul A

2003-06-01

Recent studies show that a broad category of materials share "nonclassical" nonlinear elastic behavior much different from "classical" (Landau-type) nonlinearity. Manifestations of "nonclassical" nonlinearity include stress-strain hysteresis and discrete memory in quasistatic experiments, and specific dependencies of the harmonic amplitudes with respect to the drive amplitude in dynamic wave experiments, which are remarkably different from those predicted by the classical theory. These materials have in common soft "bond" elements, where the elastic nonlinearity originates, contained in hard matter (e.g., a rock sample). The bond system normally comprises a small fraction of the total material volume, and can be localized (e.g., a crack in a solid) or distributed, as in a rock. In this paper a model is presented in which the soft elements are treated as hysteretic or reversible elastic units connected in a one-dimensional lattice to elastic elements (grains), which make up the hard matrix. Calculations are performed in the framework of the local interaction simulation approach (LISA). Experimental observations are well predicted by the model, which is now ready both for basic investigations about the physical origins of nonlinear elasticity and for applications to material damage diagnostics.

Time domain nonlinear SMA damper force identification approach and its numerical validation

NASA Astrophysics Data System (ADS)

Xin, Lulu; Xu, Bin; He, Jia

2012-04-01

Most of the currently available vibration-based identification approaches for structural damage detection are based on eigenvalues and/or eigenvectors extracted from vibration measurements and, strictly speaking, are only suitable for linear system. However, the initiation and development of damage in engineering structures under severe dynamic loadings are typical nonlinear procedure. Studies on the identification of restoring force which is a direct indicator of the extent of the nonlinearity have received increasing attention in recent years. In this study, a date-based time domain identification approach for general nonlinear system was developed. The applied excitation and the corresponding response time series of the structure were used for identification by means of standard least-square techniques and a power series polynomial model (PSPM) which was utilized to model the nonlinear restoring force (NRF). The feasibility and robustness of the proposed approach was verified by a 2 degree-of-freedoms (DOFs) lumped mass numerical model equipped with a shape memory ally (SMA) damper mimicking nonlinear behavior. The results show that the proposed data-based time domain method is capable of identifying the NRF in engineering structures without any assumptions on the mass distribution and the topology of the structure, and provides a promising way for damage detection in the presence of structural nonlinearities.

Nonlinear dynamical model of human gait

NASA Astrophysics Data System (ADS)

West, Bruce J.; Scafetta, Nicola

2003-05-01

We present a nonlinear dynamical model of the human gait control system in a variety of gait regimes. The stride-interval time series in normal human gait is characterized by slightly multifractal fluctuations. The fractal nature of the fluctuations becomes more pronounced under both an increase and decrease in the average gait. Moreover, the long-range memory in these fluctuations is lost when the gait is keyed on a metronome. Human locomotion is controlled by a network of neurons capable of producing a correlated syncopated output. The central nervous system is coupled to the motocontrol system, and together they control the locomotion of the gait cycle itself. The metronomic gait is simulated by a forced nonlinear oscillator with a periodic external force associated with the conscious act of walking in a particular way.

Volterra series based blind equalization for nonlinear distortions in short reach optical CAP system

NASA Astrophysics Data System (ADS)

Tao, Li; Tan, Hui; Fang, Chonghua; Chi, Nan

2016-12-01

In this paper, we propose a blind Volterra series based nonlinear equalization (VNLE) with low complexity for the nonlinear distortion mitigation in short reach optical carrierless amplitude and phase (CAP) modulation system. The principle of the blind VNLE is presented and the performance of its blind adaptive algorithms including the modified cascaded multi-mode algorithm (MCMMA) and direct detection LMS (DD-LMS) are investigated experimentally. Compared to the conventional VNLE using training symbols before demodulation, it is performed after matched filtering and downsampling, so shorter memory length is required but similar performance improvement is observed. About 1 dB improvement is observed at BER of 3.8×10-3 for 40 Gb/s CAP32 signal over 40 km standard single mode fiber.

Simulation of noisy dynamical system by Deep Learning

NASA Astrophysics Data System (ADS)

Yeo, Kyongmin

2017-11-01

Deep learning has attracted huge attention due to its powerful representation capability. However, most of the studies on deep learning have been focused on visual analytics or language modeling and the capability of the deep learning in modeling dynamical systems is not well understood. In this study, we use a recurrent neural network to model noisy nonlinear dynamical systems. In particular, we use a long short-term memory (LSTM) network, which constructs internal nonlinear dynamics systems. We propose a cross-entropy loss with spatial ridge regularization to learn a non-stationary conditional probability distribution from a noisy nonlinear dynamical system. A Monte Carlo procedure to perform time-marching simulations by using the LSTM is presented. The behavior of the LSTM is studied by using noisy, forced Van der Pol oscillator and Ikeda equation.

On structure-exploiting trust-region regularized nonlinear least squares algorithms for neural-network learning.

PubMed

Mizutani, Eiji; Demmel, James W

2003-01-01

This paper briefly introduces our numerical linear algebra approaches for solving structured nonlinear least squares problems arising from 'multiple-output' neural-network (NN) models. Our algorithms feature trust-region regularization, and exploit sparsity of either the 'block-angular' residual Jacobian matrix or the 'block-arrow' Gauss-Newton Hessian (or Fisher information matrix in statistical sense) depending on problem scale so as to render a large class of NN-learning algorithms 'efficient' in both memory and operation costs. Using a relatively large real-world nonlinear regression application, we shall explain algorithmic strengths and weaknesses, analyzing simulation results obtained by both direct and iterative trust-region algorithms with two distinct NN models: 'multilayer perceptrons' (MLP) and 'complementary mixtures of MLP-experts' (or neuro-fuzzy modular networks).

Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall.

PubMed

Hampson, Robert E; Song, Dong; Robinson, Brian S; Fetterhoff, Dustin; Dakos, Alexander S; Roeder, Brent M; She, Xiwei; Wicks, Robert T; Witcher, Mark R; Couture, Daniel E; Laxton, Adrian W; Munger-Clary, Heidi; Popli, Gautam; Sollman, Myriam J; Whitlow, Christopher T; Marmarelis, Vasilis Z; Berger, Theodore W; Deadwyler, Sam A

2018-06-01

We demonstrate here the first successful implementation in humans of a proof-of-concept system for restoring and improving memory function via facilitation of memory encoding using the patient's own hippocampal spatiotemporal neural codes for memory. Memory in humans is subject to disruption by drugs, disease and brain injury, yet previous attempts to restore or rescue memory function in humans typically involved only nonspecific, modulation of brain areas and neural systems related to memory retrieval. We have constructed a model of processes by which the hippocampus encodes memory items via spatiotemporal firing of neural ensembles that underlie the successful encoding of short-term memory. A nonlinear multi-input, multi-output (MIMO) model of hippocampal CA3 and CA1 neural firing is computed that predicts activation patterns of CA1 neurons during the encoding (sample) phase of a delayed match-to-sample (DMS) human short-term memory task. MIMO model-derived electrical stimulation delivered to the same CA1 locations during the sample phase of DMS trials facilitated short-term/working memory by 37% during the task. Longer term memory retention was also tested in the same human subjects with a delayed recognition (DR) task that utilized images from the DMS task, along with images that were not from the task. Across the subjects, the stimulated trials exhibited significant improvement (35%) in both short-term and long-term retention of visual information. These results demonstrate the facilitation of memory encoding which is an important feature for the construction of an implantable neural prosthetic to improve human memory.

Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall

NASA Astrophysics Data System (ADS)

Hampson, Robert E.; Song, Dong; Robinson, Brian S.; Fetterhoff, Dustin; Dakos, Alexander S.; Roeder, Brent M.; She, Xiwei; Wicks, Robert T.; Witcher, Mark R.; Couture, Daniel E.; Laxton, Adrian W.; Munger-Clary, Heidi; Popli, Gautam; Sollman, Myriam J.; Whitlow, Christopher T.; Marmarelis, Vasilis Z.; Berger, Theodore W.; Deadwyler, Sam A.

2018-06-01

Objective. We demonstrate here the first successful implementation in humans of a proof-of-concept system for restoring and improving memory function via facilitation of memory encoding using the patient’s own hippocampal spatiotemporal neural codes for memory. Memory in humans is subject to disruption by drugs, disease and brain injury, yet previous attempts to restore or rescue memory function in humans typically involved only nonspecific, modulation of brain areas and neural systems related to memory retrieval. Approach. We have constructed a model of processes by which the hippocampus encodes memory items via spatiotemporal firing of neural ensembles that underlie the successful encoding of short-term memory. A nonlinear multi-input, multi-output (MIMO) model of hippocampal CA3 and CA1 neural firing is computed that predicts activation patterns of CA1 neurons during the encoding (sample) phase of a delayed match-to-sample (DMS) human short-term memory task. Main results. MIMO model-derived electrical stimulation delivered to the same CA1 locations during the sample phase of DMS trials facilitated short-term/working memory by 37% during the task. Longer term memory retention was also tested in the same human subjects with a delayed recognition (DR) task that utilized images from the DMS task, along with images that were not from the task. Across the subjects, the stimulated trials exhibited significant improvement (35%) in both short-term and long-term retention of visual information. Significance. These results demonstrate the facilitation of memory encoding which is an important feature for the construction of an implantable neural prosthetic to improve human memory.

Behavioral modeling and digital compensation of nonlinearity in DFB lasers for multi-band directly modulated radio-over-fiber systems

NASA Astrophysics Data System (ADS)

Li, Jianqiang; Yin, Chunjing; Chen, Hao; Yin, Feifei; Dai, Yitang; Xu, Kun

2014-11-01

The envisioned C-RAN concept in wireless communication sector replies on distributed antenna systems (DAS) which consist of a central unit (CU), multiple remote antenna units (RAUs) and the fronthaul links between them. As the legacy and emerging wireless communication standards will coexist for a long time, the fronthaul links are preferred to carry multi-band multi-standard wireless signals. Directly-modulated radio-over-fiber (ROF) links can serve as a lowcost option to make fronthaul connections conveying multi-band wireless signals. However, directly-modulated radioover- fiber (ROF) systems often suffer from inherent nonlinearities from directly-modulated lasers. Unlike ROF systems working at the single-band mode, the modulation nonlinearities in multi-band ROF systems can result in both in-band and cross-band nonlinear distortions. In order to address this issue, we have recently investigated the multi-band nonlinear behavior of directly-modulated DFB lasers based on multi-dimensional memory polynomial model. Based on this model, an efficient multi-dimensional baseband digital predistortion technique was developed and experimentally demonstrated for linearization of multi-band directly-modulated ROF systems.

Generalized Nonlinear Yule Models

NASA Astrophysics Data System (ADS)

Lansky, Petr; Polito, Federico; Sacerdote, Laura

2016-11-01

With the aim of considering models related to random graphs growth exhibiting persistent memory, we propose a fractional nonlinear modification of the classical Yule model often studied in the context of macroevolution. Here the model is analyzed and interpreted in the framework of the development of networks such as the World Wide Web. Nonlinearity is introduced by replacing the linear birth process governing the growth of the in-links of each specific webpage with a fractional nonlinear birth process with completely general birth rates. Among the main results we derive the explicit distribution of the number of in-links of a webpage chosen uniformly at random recognizing the contribution to the asymptotics and the finite time correction. The mean value of the latter distribution is also calculated explicitly in the most general case. Furthermore, in order to show the usefulness of our results, we particularize them in the case of specific birth rates giving rise to a saturating behaviour, a property that is often observed in nature. The further specialization to the non-fractional case allows us to extend the Yule model accounting for a nonlinear growth.

Nonlinear analyses of composite aerospace structures in sonic fatigue

NASA Technical Reports Server (NTRS)

Mei, Chuh

1993-01-01

This report summarizes the semiannual research progress, accomplishments, and future plans performed under the NASA Langley Research Center Grant No. NAG-1-1358. The primary research effort of this project is the development of analytical methods for the prediction of nonlinear random response of composite aerospace structures subjected to combined acoustic and thermal loads. The progress, accomplishments, and future plates on four sonic fatigue research topics are described. The sonic fatigue design and passive control of random response of shape memory alloy hybrid composites presented in section 4, which is suited especially for HSCT, is a new initiative.

Organization of the 1999 Integrated Photonics Research Topical Meeting Held at Fess Parker’s Doubletree Resort, Santa Barbara, California on 19-21 Jul 1999

DTIC Science & Technology

2000-02-29

ArF laser of 6.4eV as photon energy. The irradiation was carried out with an energy density of 100mJ/cm2 per pulse and a pulse repetition of 10...soliton lasers , optical ring memories, femtosecond stretched- pulse lasers , and nonlinear loop filters will be described, (p. 2) 9:00am (Plenary) RMA2...stretched- pulse lasers , and nonlinear loop filters will be described. RMA2-1 / 3 Challenges and opportunities in Photonic Integration M.K. Smit

Nonlinear analyses of composite aerospace structures in sonic fatigue

NASA Astrophysics Data System (ADS)

Mei, Chuh

1993-06-01

This report summarizes the semiannual research progress, accomplishments, and future plans performed under the NASA Langley Research Center Grant No. NAG-1-1358. The primary research effort of this project is the development of analytical methods for the prediction of nonlinear random response of composite aerospace structures subjected to combined acoustic and thermal loads. The progress, accomplishments, and future plates on four sonic fatigue research topics are described. The sonic fatigue design and passive control of random response of shape memory alloy hybrid composites presented in section 4, which is suited especially for HSCT, is a new initiative.

A new methodology for automated diagnosis of mild cognitive impairment (MCI) using magnetoencephalography (MEG).

PubMed

Amezquita-Sanchez, Juan P; Adeli, Anahita; Adeli, Hojjat

2016-05-15

Mild cognitive impairment (MCI) is a cognitive disorder characterized by memory impairment, greater than expected by age. A new methodology is presented to identify MCI patients during a working memory task using MEG signals. The methodology consists of four steps: In step 1, the complete ensemble empirical mode decomposition (CEEMD) is used to decompose the MEG signal into a set of adaptive sub-bands according to its contained frequency information. In step 2, a nonlinear dynamics measure based on permutation entropy (PE) analysis is employed to analyze the sub-bands and detect features to be used for MCI detection. In step 3, an analysis of variation (ANOVA) is used for feature selection. In step 4, the enhanced probabilistic neural network (EPNN) classifier is applied to the selected features to distinguish between MCI and healthy patients. The usefulness and effectiveness of the proposed methodology are validated using the sensed MEG data obtained experimentally from 18 MCI and 19 control patients. Copyright © 2016 Elsevier B.V. All rights reserved.

Information Cost, Memory Length and Market Instability.

PubMed

Diks, Cees; Li, Xindan; Wu, Chengyao

2018-07-01

In this article, we study the instability of a stock market with a modified version of Diks and Dindo's (2008) model where the market is characterized by nonlinear interactions between informed traders and uninformed traders. In the interaction of heterogeneous agents, we replace the replicator dynamics for the fractions by logistic strategy switching. This modification makes the model more suitable for describing realistic price dynamics, as well as more robust with respect to parameter changes. One goal of our paper is to use this model to explore if the arrival of new information (news) and investor behavior have an effect on market instability. A second, related, goal is to study the way markets absorb new information, especially when the market is unstable and the price is far from being fully informative. We find that the dynamics become locally unstable and prices may deviate far from the fundamental price, routing to chaos through bifurcation, with increasing information costs or decreasing memory length of the uninformed traders.

On a model of electromagnetic field propagation in ferroelectric media

NASA Astrophysics Data System (ADS)

Picard, Rainer

2007-04-01

The Maxwell system in an anisotropic, inhomogeneous medium with non-linear memory effect produced by a Maxwell type system for the polarization is investigated under low regularity assumptions on data and domain. The particular form of memory in the system is motivated by a model for electromagnetic wave propagation in ferromagnetic materials suggested by Greenberg, MacCamy and Coffman [J.M. Greenberg, R.C. MacCamy, C.V. Coffman, On the long-time behavior of ferroelectric systems, Phys. D 134 (1999) 362-383]. To avoid unnecessary regularity requirements the problem is approached as a system of space-time operator equation in the framework of extrapolation spaces (Sobolev lattices), a theoretical framework developed in [R. Picard, Evolution equations as space-time operator equations, Math. Anal. Appl. 173 (2) (1993) 436-458; R. Picard, Evolution equations as operator equations in lattices of Hilbert spaces, Glasnik Mat. 35 (2000) 111-136]. A solution theory for a large class of ferromagnetic materials confined to an arbitrary open set (with suitably generalized boundary conditions) is obtained.

Recent progress in tungsten oxides based memristors and their neuromorphological applications

NASA Astrophysics Data System (ADS)

Qu, Bo; Younis, Adnan; Chu, Dewei

2016-09-01

The advance in conventional silicon based semiconductor industry is now becoming indeterminacy as it still along the road of Moore's Law and concomitant problems associated with it are the emergence of a number of practical issues such as short channel effect. In terms of memory applications, it is generally believed that transistors based memory devices will approach to their scaling limits up to 2018. Therefore, one of the most prominent challenges today in semiconductor industry is the need of a new memory technology which is able to combine the best characterises of current devices. The resistive switching memories which are regarded as "memristors" thus gain great attentions thanks to their specific nonlinear electrical properties. More importantly, their behaviour resembles with the transmission characteristic of synapse in biology. Therefore, the research of synapses biomimetic devices based on memristor will certainly bring a great research prospect in studying synapse emulation as well as building artificial neural networks. Tungsten oxides (WO x ) exhibits many essential characteristics as a great candidate for memristive devices including: accredited endurance (over 105 cycles), stoichiometric flexibility, complimentary metal-oxide-semiconductor (CMOS) process compatibility and configurable properties including non-volatile rectification, memorization and learning functions. Herein, recent progress on Tungsten oxide based materials and its associating memory devices had been reviewed. The possible implementation of this material as a bio-inspired artificial synapse is also highlighted. The penultimate section summaries the current research progress for tungsten oxide based biological synapses and end up with several proposals that have been suggested for possible future developments.

Spatial abilities across the adult life span.

PubMed

Borella, Erika; Meneghetti, Chiara; Ronconi, Lucia; De Beni, Rossana

2014-02-01

The study investigates age-related effects across the adult life span on spatial abilities (testing subabilities based on a distinction between spatial visualization, mental rotation, and perspective taking) and spatial self-assessments. The sample consisted of 454 participants (223 women and 231 men) from 20 to 91 years of age. Results showed nonlinear age-related effects for spatial visualization and perspective taking but linear effects for mental rotation; few or no age-related effects were found for spatial self-assessments. Working memory accounted for only a small proportion of the variance in all spatial tasks and had no effect on spatial self-assessments. Overall, our findings suggest that the influence of age on spatial skills across the adult life span is considerable, but the effects of age change as a function of the spatial task considered, and the effect on spatial self-assessment is more marginal.

Statistical mechanics of neocortical interactions: A scaling paradigm applied to electroencephalography

NASA Astrophysics Data System (ADS)

Ingber, Lester

1991-09-01

A series of papers has developed a statistical mechanics of neocortical interactions (SMNI), deriving aggregate behavior of experimentally observed columns of neurons from statistical electrical-chemical properties of synaptic interactions. While not useful to yield insights at the single-neuron level, SMNI has demonstrated its capability in describing large-scale properties of short-term memory and electroencephalographic (EEG) systematics. The necessity of including nonlinear and stochastic structures in this development has been stressed. In this paper, a more stringent test is placed on SMNI: The algebraic and numerical algorithms previously developed in this and similar systems are brought to bear to fit large sets of EEG and evoked-potential data being collected to investigate genetic predispositions to alcoholism and to extract brain ``signatures'' of short-term memory. Using the numerical algorithm of very fast simulated reannealing, it is demonstrated that SMNI can indeed fit these data within experimentally observed ranges of its underlying neuronal-synaptic parameters, and the quantitative modeling results are used to examine physical neocortical mechanisms to discriminate high-risk and low-risk populations genetically predisposed to alcoholism. Since this study is a control to span relatively long time epochs, similar to earlier attempts to establish such correlations, this discrimination is inconclusive because of other neuronal activity which can mask such effects. However, the SMNI model is shown to be consistent with EEG data during selective attention tasks and with neocortical mechanisms describing short-term memory previously published using this approach. This paper explicitly identifies similar nonlinear stochastic mechanisms of interaction at the microscopic-neuronal, mesoscopic-columnar, and macroscopic-regional scales of neocortical interactions. These results give strong quantitative support for an accurate intuitive picture, portraying neocortical interactions as having common algebraic or physics mechanisms that scale across quite disparate spatial scales and functional or behavioral phenomena, i.e., describing interactions among neurons, columns of neurons, and regional masses of neurons.

Quantum state detection and state preparation based on cavity-enhanced nonlinear interaction of atoms with single photon

NASA Astrophysics Data System (ADS)

Hosseini, Mahdi

Our ability to engineer quantum states of light and matter has significantly advanced over the past two decades, resulting in the production of both Gaussian and non-Gaussian optical states. The resulting tailored quantum states enable quantum technologies such as quantum optical communication, quantum sensing as well as quantum photonic computation. The strong nonlinear light-atom interaction is the key to deterministic quantum state preparation and quantum photonic processing. One route to enhancing the usually weak nonlinear light-atom interactions is to approach the regime of cavity quantum electrodynamics (cQED) interaction by means of high finesse optical resonators. I present results from the MIT experiment of large conditional cross-phase modulation between a signal photon, stored inside an atomic quantum memory, and a control photon that traverses a high-finesse optical cavity containing the atomic memory. I also present a scheme to probabilistically change the amplitude and phase of a signal photon qubit to, in principle, arbitrary values by postselection on a control photon that has interacted with that state. Notably, small changes of the control photon polarization measurement basis by few degrees can substantially change the amplitude and phase of the signal state. Finally, I present our ongoing effort at Purdue to realize similar peculiar quantum phenomena at the single photon level on chip scale photonic systems.

Developmental Change in the Influence of Domain-General Abilities and Domain-Specific Knowledge on Mathematics Achievement: An Eight-Year Longitudinal Study

PubMed Central

Geary, David C.; Nicholas, Alan; Li, Yaoran; Sun, Jianguo

2016-01-01

The contributions of domain-general abilities and domain-specific knowledge to subsequent mathematics achievement were longitudinally assessed (n = 167) through 8th grade. First grade intelligence and working memory and prior grade reading achievement indexed domain-general effects and domain-specific effects were indexed by prior grade mathematics achievement and mathematical cognition measures of prior grade number knowledge, addition skills, and fraction knowledge. Use of functional data analysis enabled grade-by-grade estimation of overall domain-general and domain-specific effects on subsequent mathematics achievement, the relative importance of individual domain-general and domain-specific variables on this achievement, and linear and non-linear across-grade estimates of these effects. The overall importance of domain-general abilities for subsequent achievement was stable across grades, with working memory emerging as the most important domain-general ability in later grades. The importance of prior mathematical competencies on subsequent mathematics achievement increased across grades, with number knowledge and arithmetic skills critical in all grades and fraction knowledge in later grades. Overall, domain-general abilities were more important than domain-specific knowledge for mathematics learning in early grades but general abilities and domain-specific knowledge were equally important in later grades. PMID:28781382

Theory of nonlinear, distortive phenomena in solids: Martensitic, crack, and multiscale structures-phenomenology and physics. Progress summary, 1991--1994

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

Sethna, J.P.; Krumhansl, J.A.

1994-08-01

We have identified tweed precursors to martensitic phase transformations as a spin glass phase due to composition variations, and used simulations and exact replica theory predictions to predict diffraction peaks and model phase diagrams, and provide real space data for comparison to transmission electron micrograph images. We have used symmetry principles to derive the crack growth laws for mixed-mode brittle fracture, explaining the results for two-dimensional fracture and deriving the growth laws in three dimensions. We have used recent advances in dynamical critical phenomena to study hysteresis in disordered systems, explaining the return-point-memory effect, predicting distributions for Barkhausen noise, andmore » elucidating the transition from athermal to burst behavior in martensites. From a nonlinear lattice-dynamical model of a first-order transition using simulations, finite-size scaling, and transfer matrix methods, it is shown that heterophase transformation precursors cannot occur in a pure homogeneous system, thus emphasizing the role of disorder in real materials. Full integration of nonlinear Landau-Ginzburg continuum theory with experimental neutron-scattering data and first-principles calculations has been carried out to compute semi-quantitative values of the energy and thickness of twin boundaries in InTl and FePd martensites.« less

LINEAR - DERIVATION AND DEFINITION OF A LINEAR AIRCRAFT MODEL

NASA Technical Reports Server (NTRS)

Duke, E. L.

1994-01-01

The Derivation and Definition of a Linear Model program, LINEAR, provides the user with a powerful and flexible tool for the linearization of aircraft aerodynamic models. LINEAR was developed to provide a standard, documented, and verified tool to derive linear models for aircraft stability analysis and control law design. Linear system models define the aircraft system in the neighborhood of an analysis point and are determined by the linearization of the nonlinear equations defining vehicle dynamics and sensors. LINEAR numerically determines a linear system model using nonlinear equations of motion and a user supplied linear or nonlinear aerodynamic model. The nonlinear equations of motion used are six-degree-of-freedom equations with stationary atmosphere and flat, nonrotating earth assumptions. LINEAR is capable of extracting both linearized engine effects, such as net thrust, torque, and gyroscopic effects and including these effects in the linear system model. The point at which this linear model is defined is determined either by completely specifying the state and control variables, or by specifying an analysis point on a trajectory and directing the program to determine the control variables and the remaining state variables. The system model determined by LINEAR consists of matrices for both the state and observation equations. The program has been designed to provide easy selection of state, control, and observation variables to be used in a particular model. Thus, the order of the system model is completely under user control. Further, the program provides the flexibility of allowing alternate formulations of both the state and observation equations. Data describing the aircraft and the test case is input to the program through a terminal or formatted data files. All data can be modified interactively from case to case. The aerodynamic model can be defined in two ways: a set of nondimensional stability and control derivatives for the flight point of interest, or a full non-linear aerodynamic model as used in simulations. LINEAR is written in FORTRAN and has been implemented on a DEC VAX computer operating under VMS with a virtual memory requirement of approximately 296K of 8 bit bytes. Both an interactive and batch version are included. LINEAR was developed in 1988.

Statistical mechanics of neocortical interactions. Derivation of short-term-memory capacity

NASA Astrophysics Data System (ADS)

Ingber, Lester

1984-06-01

A theory developed by the author to describe macroscopic neocortical interactions demonstrates that empirical values of chemical and electrical parameters of synaptic interactions establish several minima of the path-integral Lagrangian as a function of excitatory and inhibitory columnar firings. The number of possible minima, their time scales of hysteresis and probable reverberations, and their nearest-neighbor columnar interactions are all consistent with well-established empirical rules of human short-term memory. Thus, aspects of conscious experience are derived from neuronal firing patterns, using modern methods of nonlinear nonequilibrium statistical mechanics to develop realistic explicit synaptic interactions.

Position, scale, and rotation invariant holographic associative memory

NASA Astrophysics Data System (ADS)

Fielding, Kenneth H.; Rogers, Steven K.; Kabrisky, Matthew; Mills, James P.

1989-08-01

This paper describes the development and characterization of a holographic associative memory (HAM) system that is able to recall stored objects whose inputs were changed in position, scale, and rotation. The HAM is based on the single iteration model described by Owechko et al. (1987); however, the system described uses a self-pumped BaTiO3 phase conjugate mirror, rather than a degenerate four-wave mixing proposed by Owechko and his coworkers. The HAM system can store objects in a position, scale, and rotation invariant feature space. The angularly multiplexed diffuse Fourier transform holograms of the HAM feature space are characterized as the memory unit; distorted input objects are correlated with the hologram, and the nonlinear phase conjugate mirror reduces cross-correlation noise and provides object discrimination. Applications of the HAM system are presented.

Scale-free networks as an epiphenomenon of memory

NASA Astrophysics Data System (ADS)

Caravelli, F.; Hamma, A.; Di Ventra, M.

2015-01-01

Many realistic networks are scale free, with small characteristic path lengths, high clustering, and power law in their degree distribution. They can be obtained by dynamical networks in which a preferential attachment process takes place. However, this mechanism is non-local, in the sense that it requires knowledge of the whole graph in order for the graph to be updated. Instead, if preferential attachment and realistic networks occur in physical systems, these features need to emerge from a local model. In this paper, we propose a local model and show that a possible ingredient (which is often underrated) for obtaining scale-free networks with local rules is memory. Such a model can be realised in solid-state circuits, using non-linear passive elements with memory such as memristors, and thus can be tested experimentally.

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

Chacón, L., E-mail: chacon@lanl.gov; Chen, G.; Knoll, D.A.

We review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLOmore » approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.« less

Multiscale high-order/low-order (HOLO) algorithms and applications

NASA Astrophysics Data System (ADS)

Chacón, L.; Chen, G.; Knoll, D. A.; Newman, C.; Park, H.; Taitano, W.; Willert, J. A.; Womeldorff, G.

2017-02-01

We review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.

Initial Alignment of Large Azimuth Misalignment Angles in SINS Based on Adaptive UPF

PubMed Central

Sun, Jin; Xu, Xiao-Su; Liu, Yi-Ting; Zhang, Tao; Li, Yao

2015-01-01

The case of large azimuth misalignment angles in a strapdown inertial navigation system (SINS) is analyzed, and a method of using the adaptive UPF for the initial alignment is proposed. The filter is based on the idea of a strong tracking filter; through the introduction of the attenuation memory factor to effectively enhance the corrections of the current information residual error on the system, it reduces the influence on the system due to the system simplification, and the uncertainty of noise statistical properties to a certain extent; meanwhile, the UPF particle degradation phenomenon is better overcome. Finally, two kinds of non-linear filters, UPF and adaptive UPF, are adopted in the initial alignment of large azimuth misalignment angles in SINS, and the filtering effects of the two kinds of nonlinear filter on the initial alignment were compared by simulation and turntable experiments. The simulation and turntable experiment results show that the speed and precision of the initial alignment using adaptive UPF for a large azimuth misalignment angle in SINS under the circumstance that the statistical properties of the system noise are certain or not have been improved to some extent. PMID:26334277

3-D Forward modeling of Induced Polarization Effects of Transient Electromagnetic Method

NASA Astrophysics Data System (ADS)

Wu, Y.; Ji, Y.; Guan, S.; Li, D.; Wang, A.

2017-12-01

In transient electromagnetic (TEM) detection, Induced polarization (IP) effects are so important that they cannot be ignored. The authors simulate the three-dimensional (3-D) induced polarization effects in time-domain directly by applying the finite-difference time-domain method (FDTD) based on Cole-Cole model. Due to the frequency dispersion characteristics of the electrical conductivity, the computations of convolution in the generalized Ohm's law of fractional order system makes the forward modeling particularly complicated. Firstly, we propose a method to approximate the fractional order function of Cole-Cole model using a lower order rational transfer function based on error minimum theory in the frequency domain. In this section, two auxiliary variables are introduced to transform nonlinear least square fitting problem of the fractional order system into a linear programming problem, thus avoiding having to solve a system of equations and nonlinear problems. Secondly, the time-domain expression of Cole-Cole model is obtained by using Inverse Laplace transform. Then, for the calculation of Ohm's law, we propose an e-index auxiliary equation of conductivity to transform the convolution to non-convolution integral; in this section, the trapezoid rule is applied to compute the integral. We then substitute the recursion equation into Maxwell's equations to derive the iterative equations of electromagnetic field using the FDTD method. Finally, we finish the stimulation of 3-D model and evaluate polarization parameters. The results are compared with those obtained from the digital filtering solution of the analytical equation in the homogeneous half space, as well as with the 3-D model results from the auxiliary ordinary differential equation method (ADE). Good agreements are obtained across the three methods. In terms of the 3-D model, the proposed method has higher efficiency and lower memory requirements as execution times and memory usage were reduced by 20% compared with ADE method.

Study of chromatic adaptation using memory color matches, Part I: neutral illuminants.

PubMed

Smet, Kevin A G; Zhai, Qiyan; Luo, Ming R; Hanselaer, Peter

2017-04-03

Twelve corresponding color data sets have been obtained using the long-term memory colors of familiar objects as target stimuli. Data were collected for familiar objects with neutral, red, yellow, green and blue hues under 4 approximately neutral illumination conditions on or near the blackbody locus. The advantages of the memory color matching method are discussed in light of other more traditional asymmetric matching techniques. Results were compared to eight corresponding color data sets available in literature. The corresponding color data was used to test several linear (von Kries, RLAB, etc.) and nonlinear (Hunt & Nayatani) chromatic adaptation transforms (CAT). It was found that a simple two-step von Kries, whereby the degree of adaptation D is optimized to minimize the DEu'v' prediction errors, outperformed all other tested models for both memory color and literature corresponding color sets, whereby prediction errors were lower for the memory color sets. The predictive errors were substantially smaller than the standard uncertainty on the average observer and were comparable to what are considered just-noticeable-differences in the CIE u'v' chromaticity diagram, supporting the use of memory color based internal references to study chromatic adaptation mechanisms.

Memory and pattern storage in neural networks with activity dependent synapses

NASA Astrophysics Data System (ADS)

Mejias, J. F.; Torres, J. J.

2009-01-01

We present recently obtained results on the influence of the interplay between several activity dependent synaptic mechanisms, such as short-term depression and facilitation, on the maximum memory storage capacity in an attractor neural network [1]. In contrast with the case of synaptic depression, which drastically reduces the capacity of the network to store and retrieve activity patterns [2], synaptic facilitation is able to enhance the memory capacity in different situations. In particular, we find that a convenient balance between depression and facilitation can enhance the memory capacity, reaching maximal values similar to those obtained with static synapses, that is, without activity-dependent processes. We also argue, employing simple arguments, that this level of balance is compatible with experimental data recorded from some cortical areas, where depression and facilitation may play an important role for both memory-oriented tasks and information processing. We conclude that depressing synapses with a certain level of facilitation allow to recover the good retrieval properties of networks with static synapses while maintaining the nonlinear properties of dynamic synapses, convenient for information processing and coding.

A low switching voltage organic-on-inorganic heterojunction memory element utilizing a conductive polymer fuse on a doped silicon substrate

NASA Astrophysics Data System (ADS)

Smith, Shawn; Forrest, Stephen R.

2004-06-01

We present a simple, nonvolatile, write-once-read-many-times (WORM) memory device utilizing an organic-on-inorganic heterojunction (OI-HJ) diode with a conductive polymer fuse consisting of polyethylene dioxythiophene:polysterene sulfonic acid (PEDOT:PSS) forming one side of the rectifying junction. Current transients are used to change the fuse from a conducting to a nonconducting state to record a logical "1" or "0", while the nonlinearity of the OI-HJ allows for passive matrix memory addressing. The device switches at 2 and 4 V for 50 nm thick PEDOT:PSS films on p-type Si and n-type Si, respectively. This is significantly lower than the switching voltage used in PEDOT:PSS/p-i-n Si memory elements [J. Appl Phys. 94, 7811 (2003)]. The switching results in a permanent reduction of forward-bias current by approximately five orders of magnitude. These results suggest that the OI-HJ structure has potential for use in low-cost passive matrix WORM memories for archival storage applications.

All oxide semiconductor-based bidirectional vertical p-n-p selectors for 3D stackable crossbar-array electronics

PubMed Central

Bae, Yoon Cheol; Lee, Ah Rahm; Baek, Gwang Ho; Chung, Je Bock; Kim, Tae Yoon; Park, Jea Gun; Hong, Jin Pyo

2015-01-01

Three-dimensional (3D) stackable memory devices including nano-scaled crossbar array are central for the realization of high-density non-volatile memory electronics. However, an essential sneak path issue affecting device performance in crossbar array remains a bottleneck and a grand challenge. Therefore, a suitable bidirectional selector as a two-way switch is required to facilitate a major breakthrough in the 3D crossbar array memory devices. Here, we show the excellent selectivity of all oxide p-/n-type semiconductor-based p-n-p open-based bipolar junction transistors as selectors in crossbar memory array. We report that bidirectional nonlinear characteristics of oxide p-n-p junctions can be highly enhanced by manipulating p-/n-type oxide semiconductor characteristics. We also propose an associated Zener tunneling mechanism that explains the unique features of our p-n-p selector. Our experimental findings are further extended to confirm the profound functionality of oxide p-n-p selectors integrated with several bipolar resistive switching memory elements working as storage nodes. PMID:26289565

Navigation and Comprehension of Digital Expository Texts: Hypertext Structure, Previous Domain Knowledge, and Working Memory Capacity

ERIC Educational Resources Information Center

Burin, Debora I.; Barreyro, Juan P.; Saux, Gastón; Irrazábal, Natalia C.

2015-01-01

Introduction: In contemporary information societies, reading digital text has become pervasive. One of the most distinctive features of digital texts is their internal connections via hyperlinks, resulting in non-linear hypertexts. Hypertext structure and previous knowledge affect navigation and comprehension of digital expository texts. From the…

Does money matter in inflation forecasting?

NASA Astrophysics Data System (ADS)

Binner, J. M.; Tino, P.; Tepper, J.; Anderson, R.; Jones, B.; Kendall, G.

2010-11-01

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two nonlinear techniques, namely, recurrent neural networks and kernel recursive least squares regression-techniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naïve random walk model. The best models were nonlinear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. Beyond its economic findings, our study is in the tradition of physicists’ long-standing interest in the interconnections among statistical mechanics, neural networks, and related nonparametric statistical methods, and suggests potential avenues of extension for such studies.

Light-induced pyroelectric effect as an effective approach for ultrafast ultraviolet nanosensing

NASA Astrophysics Data System (ADS)

Wang, Zhaona; Yu, Ruomeng; Pan, Caofeng; Li, Zhaoling; Yang, Jin; Yi, Fang; Wang, Zhong Lin

2015-09-01

Zinc oxide is potentially a useful material for ultraviolet detectors; however, a relatively long response time hinders practical implementation. Here by designing and fabricating a self-powered ZnO/perovskite-heterostructured ultraviolet photodetector, the pyroelectric effect, induced in wurtzite ZnO nanowires on ultraviolet illumination, has been utilized as an effective approach for high-performance photon sensing. The response time is improved from 5.4 s to 53 μs at the rising edge, and 8.9 s to 63 μs at the falling edge, with an enhancement of five orders in magnitudes. The specific detectivity and the responsivity are both enhanced by 322%. This work provides a novel design to achieve ultrafast ultraviolet sensing at room temperature via light-self-induced pyroelectric effect. The newly designed ultrafast self-powered ultraviolet nanosensors may find promising applications in ultrafast optics, nonlinear optics, optothermal detections, computational memories and biocompatible optoelectronic probes.

Nonlinear analysis of pupillary dynamics.

PubMed

Onorati, Francesco; Mainardi, Luca Tommaso; Sirca, Fabiola; Russo, Vincenzo; Barbieri, Riccardo

2016-02-01

Pupil size reflects autonomic response to different environmental and behavioral stimuli, and its dynamics have been linked to other autonomic correlates such as cardiac and respiratory rhythms. The aim of this study is to assess the nonlinear characteristics of pupil size of 25 normal subjects who participated in a psychophysiological experimental protocol with four experimental conditions, namely “baseline”, “anger”, “joy”, and “sadness”. Nonlinear measures, such as sample entropy, correlation dimension, and largest Lyapunov exponent, were computed on reconstructed signals of spontaneous fluctuations of pupil dilation. Nonparametric statistical tests were performed on surrogate data to verify that the nonlinear measures are an intrinsic characteristic of the signals. We then developed and applied a piecewise linear regression model to detrended fluctuation analysis (DFA). Two joinpoints and three scaling intervals were identified: slope α0, at slow time scales, represents a persistent nonstationary long-range correlation, whereas α1 and α2, at middle and fast time scales, respectively, represent long-range power-law correlations, similarly to DFA applied to heart rate variability signals. Of the computed complexity measures, α0 showed statistically significant differences among experimental conditions (p<0.001). Our results suggest that (a) pupil size at constant light condition is characterized by nonlinear dynamics, (b) three well-defined and distinct long-memory processes exist at different time scales, and (c) autonomic stimulation is partially reflected in nonlinear dynamics. (c) autonomic stimulation is partially reflected in nonlinear dynamics.

Correlation between piezoresponse nonlinearity and hysteresis in ferroelectric crystals at nanoscale

DOE PAGES

Kalinin, Sergei V.; Jesse, Stephen; Yang, Yaodong; ...

2016-04-27

Here, the nonlinear response of a ferroic to external fields has been studied for decades, garnering interest for both understanding fundamental physics, as well as technological applications such as memory devices. Yet, the behavior of ferroelectrics at mesoscopic regimes remains poorly understood, and the scale limits of theories developed for macroscopic regimes are not well tested experimentally. Here, we test the link between piezo-nonlinearity and local piezoelectric strain hysteresis, via AC-field dependent measurements in conjunction with first order reversal curve (FORC) measurements on (K,Na)NbO 3 crystals with band-excitation piezoelectric force microscopy. The correlation coefficient between nonlinearity amplitude and the FORCmore » of the polarization switching shows a clear decrease in correlation with increasing AC bias, suggesting the impact of domain wall clamping on the DC measurement case. Further, correlation of polynomial fitting terms from the nonlinear measurements with the hysteresis loop area reveals that the largest correlations are reserved for the quadratic terms, which is expected for irreversible domain wall motion contributions that impact both piezoelectric behavior as well as minor loop formation. These confirm the link between local piezoelectric nonlinearity, domain wall motion and minor loop formation, and suggest that existing theories (such as Preisach) are applicable at these length scales, with associated implications for future nanoscale devices.« less

How memory of direct animal interactions can lead to territorial pattern formation.

PubMed

Potts, Jonathan R; Lewis, Mark A

2016-05-01

Mechanistic home range analysis (MHRA) is a highly effective tool for understanding spacing patterns of animal populations. It has hitherto focused on populations where animals defend their territories by communicating indirectly, e.g. via scent marks. However, many animal populations defend their territories using direct interactions, such as ritualized aggression. To enable application of MHRA to such populations, we construct a model of direct territorial interactions, using linear stability analysis and energy methods to understand when territorial patterns may form. We show that spatial memory of past interactions is vital for pattern formation, as is memory of 'safe' places, where the animal has visited but not suffered recent territorial encounters. Additionally, the spatial range over which animals make decisions to move is key to understanding the size and shape of their resulting territories. Analysis using energy methods, on a simplified version of our system, shows that stability in the nonlinear system corresponds well to predictions of linear analysis. We also uncover a hysteresis in the process of territory formation, so that formation may depend crucially on initial space-use. Our analysis, in one dimension and two dimensions, provides mathematical groundwork required for extending MHRA to situations where territories are defended by direct encounters. © 2016 The Author(s).

Complex dynamics of semantic memory access in reading

PubMed Central

Baggio, Giosué; Fonseca, André

2012-01-01

Understanding a word in context relies on a cascade of perceptual and conceptual processes, starting with modality-specific input decoding, and leading to the unification of the word's meaning into a discourse model. One critical cognitive event, turning a sensory stimulus into a meaningful linguistic sign, is the access of a semantic representation from memory. Little is known about the changes that activating a word's meaning brings about in cortical dynamics. We recorded the electroencephalogram (EEG) while participants read sentences that could contain a contextually unexpected word, such as ‘cold’ in ‘In July it is very cold outside’. We reconstructed trajectories in phase space from single-trial EEG time series, and we applied three nonlinear measures of predictability and complexity to each side of the semantic access boundary, estimated as the onset time of the N400 effect evoked by critical words. Relative to controls, unexpected words were associated with larger prediction errors preceding the onset of the N400. Accessing the meaning of such words produced a phase transition to lower entropy states, in which cortical processing becomes more predictable and more regular. Our study sheds new light on the dynamics of information flow through interfaces between sensory and memory systems during language processing. PMID:21715401

Behavior of the shape memory alloy NiTi during one-dimensional shock loading

NASA Astrophysics Data System (ADS)

Millett, J. C. F.; Bourne, N. K.; Gray, G. T., III

2002-09-01

The response of alloys based on the intermetallic compound NiTi to high-strain-rate and shock loading conditions has recently attracted attention. In particular, similarities between it, and other shape memory materials such as the alloy U-6%Nb in the propagation of the plastic wave in Taylor cylinders are of significant interest. In this article, the Hugoniot is measured using multiple manganin stress gauges, either embedded between plates of the NiTi alloy, or supported with blocks of polymethylmethacrylate. In this way, the shock stress, shock velocity, and details of the shock wave profile have been gathered. An inflection at lower stresses has been found in the Hugoniot curve (stress-particle velocity), and has been ascribed to the martensitic phase transformation that is characteristic of the shape memory effect in this alloy. In a similar way, the variation of shock velocity with particle velocity has been found to be nonlinear, contrary to other pure metal and alloy systems. Finally, a break in slope in the rising part of the shock profile has been identified as the Hugoniot elastic limit in NiTi. Conversion to the one-dimensional stress equivalent, and comparison to quasistatic data indicates that NiTi exhibits significant strain-rate sensitivity.

The Prabhakar or three parameter Mittag-Leffler function: Theory and application

NASA Astrophysics Data System (ADS)

Garra, Roberto; Garrappa, Roberto

2018-03-01

The Prabhakar function (namely, a three parameter Mittag-Leffler function) is investigated. This function plays a fundamental role in the description of the anomalous dielectric properties in disordered materials and heterogeneous systems manifesting simultaneous nonlocality and nonlinearity and, more generally, in models of Havriliak-Negami type. After reviewing some of the main properties of the function, the asymptotic expansion for large arguments is investigated in the whole complex plane and, with major emphasis, along the negative semi-axis. Fractional integral and derivative operators of Prabhakar type are hence considered and some nonlinear heat conduction equations with memory involving Prabhakar derivatives are studied.

LIMS for Lasers 2015 for achieving long-term accuracy and precision of δ2H, δ17O, and δ18O of waters using laser absorption spectrometry

USGS Publications Warehouse

Coplen, Tyler B.; Wassenaar, Leonard I

2015-01-01

Although laser absorption spectrometry (LAS) instrumentation is easy to use, its incorporation into laboratory operations is not easy, owing to extensive offline manipulation of comma-separated-values files for outlier detection, between-sample memory correction, nonlinearity (δ-variation with water amount) correction, drift correction, normalization to VSMOW-SLAP scales, and difficulty in performing long-term QA/QC audits. METHODS: A Microsoft Access relational-database application, LIMS (Laboratory Information Management System) for Lasers 2015, was developed. It automates LAS data corrections and manages clients, projects, samples, instrument-sample lists, and triple-isotope (δ(17) O, δ(18) O, and δ(2) H values) instrumental data for liquid-water samples. It enables users to (1) graphically evaluate sample injections for variable water yields and high isotope-delta variance; (2) correct for between-sample carryover, instrumental drift, and δ nonlinearity; and (3) normalize final results to VSMOW-SLAP scales. RESULTS: Cost-free LIMS for Lasers 2015 enables users to obtain improved δ(17) O, δ(18) O, and δ(2) H values with liquid-water LAS instruments, even those with under-performing syringes. For example, LAS δ(2) HVSMOW measurements of USGS50 Lake Kyoga (Uganda) water using an under-performing syringe having ±10 % variation in water concentration gave +31.7 ± 1.6 ‰ (2-σ standard deviation), compared with the reference value of +32.8 ± 0.4 ‰, after correction for variation in δ value with water concentration, between-sample memory, and normalization to the VSMOW-SLAP scale. CONCLUSIONS: LIMS for Lasers 2015 enables users to create systematic, well-founded instrument templates, import δ(2) H, δ(17) O, and δ(18) O results, evaluate performance with automatic graphical plots, correct for δ nonlinearity due to variable water concentration, correct for between-sample memory, adjust for drift, perform VSMOW-SLAP normalization, and perform long-term QA/QC audits easily.

Effects of heat treatment on shape-setting and non-linearmechanical properties of Nitinol stent

NASA Astrophysics Data System (ADS)

Liu, Xiaopeng; Wang, Yinong; Qi, Min; Yang, Dazhi

2007-07-01

NiTi shape memory alloy is a temperature sensitive material with non-linear mechanical properties and good biocompatibility, which can be used for medical devices such as stent, catheter guide wire and orthodontic wire. The majority of nitinol stents are of the self-expanding type basing on the superelasticity. Nitinol stents are shape set into the open condition and compressed and inserted into the delivery catheter. Additional the shape-setting treatment can be used as a tool to accurately tune the transformation temperatures and mechanical properties. In this study, different heat treatments have been performed on the Ti-50.7at%Ni alloy wires. And results of shape-setting, austenite transformation finish temperature and non-linear mechanical property of NiTi shape memory alloy at body temperature have been investigated. The experimental results show that the proper shape-setting temperature should be chosen between 450-550 °C. And the shape-setting results were stabilization when the NiTi wires were constrain-treated at 500 and 550°C and ageing time longer than 10 minutes. The austenite finish temperatures increased with ageing time and increased first and then decreased with ageing temperature. The peak values were obtained at 400°C. When the heat treatments was performed at the same temperature, both the upper plateau stresses and lower plateau stresses decreased with the ageing time. Most of treated nitinol wires owned good recovery ability at body temperature and the permanent sets were less than 0.05% when short time ageing treatment was performed at 500°C.

Olfactory recognition memory is disrupted in young mice with chronic low-level lead exposure

PubMed Central

Flores-Montoya, Mayra Gisel; Alvarez, Juan Manuel; Sobin, Christina

2015-01-01

Chronic developmental lead exposure yielding very low blood lead burden is an unresolved child public health problem. Few studies have attempted to model neurobehavioral changes in young animals following very low level exposure, and studies are needed to identify tests that are sensitive to the neurobehavioral changes that may occur. Mechanisms of action are not yet known however results have suggested that hippocampus/dentate gyrus may be uniquely vulnerable to early chronic low-level lead exposure. This study examined the sensitivity of a novel odor recognition task to differences in pre-adolescent C57BL/6J mice chronically exposed from birth to PND 28, to 0 ppm (control), 30 ppm (low-dose), or 330 ppm (higher-dose) lead acetate (N = 33). Blood lead levels (BLLs) determined by ICP-MS ranged from 0.02 to 20.31 µg/dL. Generalized linear mixed model analyses with litter as a random effect showed a significant interaction of BLL × sex. As BLLs increased olfactory recognition memory decreased in males. Among females, non-linear effects were observed at lower but not higher levels of lead exposure. The novel odor detection task is sensitive to effects associated with early chronic low-level lead exposure in young C57BL/6J mice. PMID:25936521

The role of groundwater in hydrological processes and memory

NASA Astrophysics Data System (ADS)

Lo, Min-Hui

The interactions between soil moisture and groundwater play important roles in controlling Earth's climate, by changing the terrestrial water cycle. However, most contemporary land surface models (LSMs) used for climate modeling lack any representation of groundwater aquifers. In this dissertation, the effects of water table dynamics on the National Center for Atmospheric Research (NCAR) Community Land Model (CLM) and Community Atmosphere Model (CAM) hydrology and land-atmosphere simulations are investigated. First, a simple, lumped unconfined aquifer model is incorporated into the CLM, in which the water table is interactively coupled to the soil moisture through groundwater recharge fluxes. The recent availability of GRACE water storage data provides a unique opportunity to constrain LSMs simulations of terrestrial hydrology. A multi-objective calibration framework using GRACE and streamflow data is developed. This approach improves parameter estimation and reduces the uncertainty of water table simulations in the CLM. Next, experiments are conducted with the off-line CLM to explore the effects of groundwater on land surface memory. Results show that feedbacks of groundwater on land surface memory can be positive, negative, or neutral depending on water table dynamics. The CAM-CLM is further utilized to investigate the effects of water table dynamics on spatial-temporal variations of precipitation. Results indicate that groundwater can increase short-term (seasonal) and long-term (interannual) memory of precipitation for some regions with suitable groundwater table depth. Finally, lower tropospheric water vapor is increased due to the presence of groundwater in the model. However, the impact of groundwater on the spatial distribution of precipitation is not globally homogeneous. In the boreal summer, tropical land regions show a positive (negative) anomaly over the Northern (Southern) Hemisphere. The increased tropical precipitation follows the climatology of the convective zone rather than that of evapotranspiration. In contrast, evapotranspiration is the major contribution to the increased precipitation in the transition climatic zone (e.g., Central North America), where the land and atmosphere are strongly coupled. This dissertation reveals the highly nonlinear responses of precipitation and soil moisture to the groundwater representation in the model, and also underscores the importance of subsurface hydrological memory processes in the climate system.

Exploiting short-term memory in soft body dynamics as a computational resource.

PubMed

Nakajima, K; Li, T; Hauser, H; Pfeifer, R

2014-11-06

Soft materials are not only highly deformable, but they also possess rich and diverse body dynamics. Soft body dynamics exhibit a variety of properties, including nonlinearity, elasticity and potentially infinitely many degrees of freedom. Here, we demonstrate that such soft body dynamics can be employed to conduct certain types of computation. Using body dynamics generated from a soft silicone arm, we show that they can be exploited to emulate functions that require memory and to embed robust closed-loop control into the arm. Our results suggest that soft body dynamics have a short-term memory and can serve as a computational resource. This finding paves the way towards exploiting passive body dynamics for control of a large class of underactuated systems. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Noise Estimation in Electroencephalogram Signal by Using Volterra Series Coefficients

PubMed Central

Hassani, Malihe; Karami, Mohammad Reza

2015-01-01

The Volterra model is widely used for nonlinearity identification in practical applications. In this paper, we employed Volterra model to find the nonlinearity relation between electroencephalogram (EEG) signal and the noise that is a novel approach to estimate noise in EEG signal. We show that by employing this method. We can considerably improve the signal to noise ratio by the ratio of at least 1.54. An important issue in implementing Volterra model is its computation complexity, especially when the degree of nonlinearity is increased. Hence, in many applications it is urgent to reduce the complexity of computation. In this paper, we use the property of EEG signal and propose a new and good approximation of delayed input signal to its adjacent samples in order to reduce the computation of finding Volterra series coefficients. The computation complexity is reduced by the ratio of at least 1/3 when the filter memory is 3. PMID:26284176

Parallel Computation of the Jacobian Matrix for Nonlinear Equation Solvers Using MATLAB

NASA Technical Reports Server (NTRS)

Rose, Geoffrey K.; Nguyen, Duc T.; Newman, Brett A.

2017-01-01

Demonstrating speedup for parallel code on a multicore shared memory PC can be challenging in MATLAB due to underlying parallel operations that are often opaque to the user. This can limit potential for improvement of serial code even for the so-called embarrassingly parallel applications. One such application is the computation of the Jacobian matrix inherent to most nonlinear equation solvers. Computation of this matrix represents the primary bottleneck in nonlinear solver speed such that commercial finite element (FE) and multi-body-dynamic (MBD) codes attempt to minimize computations. A timing study using MATLAB's Parallel Computing Toolbox was performed for numerical computation of the Jacobian. Several approaches for implementing parallel code were investigated while only the single program multiple data (spmd) method using composite objects provided positive results. Parallel code speedup is demonstrated but the goal of linear speedup through the addition of processors was not achieved due to PC architecture.

Structurally Engineered Nanoporous Ta2O5-x Selector-Less Memristor for High Uniformity and Low Power Consumption.

PubMed

Kwon, Soonbang; Kim, Tae-Wook; Jang, Seonghoon; Lee, Jae-Hwang; Kim, Nam Dong; Ji, Yongsung; Lee, Chul-Ho; Tour, James M; Wang, Gunuk

2017-10-04

A memristor architecture based on metal-oxide materials would have great promise in achieving exceptional energy efficiency and higher scalability in next-generation electronic memory systems. Here, we propose a facile method for fabricating selector-less memristor arrays using an engineered nanoporous Ta 2 O 5-x architecture. The device was fabricated in the form of crossbar arrays, and it functions as a switchable rectifier with a self-embedded nonlinear switching behavior and ultralow power consumption (∼2.7 × 10 -6 W), which results in effective suppression of crosstalk interference. In addition, we determined that the essential switching elements, such as the programming power, the sneak current, the nonlinearity value, and the device-to-device uniformity, could be enhanced by in-depth structural engineering of the pores in the Ta 2 O 5-x layer. Our results, on the basis of the structural engineering of metal-oxide materials, could provide an attractive approach for fabricating simple and cost-efficient memristor arrays with acceptable device uniformity and low power consumption without the need for additional addressing selectors.

Anti-synchronization control of BAM memristive neural networks with multiple proportional delays and stochastic perturbations

NASA Astrophysics Data System (ADS)

Wang, Weiping; Yuan, Manman; Luo, Xiong; Liu, Linlin; Zhang, Yao

2018-01-01

Proportional delay is a class of unbounded time-varying delay. A class of bidirectional associative memory (BAM) memristive neural networks with multiple proportional delays is concerned in this paper. First, we propose the model of BAM memristive neural networks with multiple proportional delays and stochastic perturbations. Furthermore, by choosing suitable nonlinear variable transformations, the BAM memristive neural networks with multiple proportional delays can be transformed into the BAM memristive neural networks with constant delays. Based on the drive-response system concept, differential inclusions theory and Lyapunov stability theory, some anti-synchronization criteria are obtained. Finally, the effectiveness of proposed criteria are demonstrated through numerical examples.

Experimental study of directionally solidified ferromagnetic shape memory alloy under multi-field coupling

NASA Astrophysics Data System (ADS)

Zhu, Yuping; Chen, Tao; Teng, Yao; Liu, Bingfei; Xue, Lijun

2016-11-01

Directionally solidified, polycrystalline Ni-Mn-Ga is studied in this paper. The polycrystalline Ni-Mn-Ga samples were cut at different angles to solidification direction. The magnetic field induced strain under constant stress and the temperature-induced strain under constant magnetic field during the loading-unloading cycle were measured. The experimental results show that the mechanical behavior during the loading-unloading cycle of the material is nonlinear and anisotropic. Based on the experimental results, the effects of multi-field coupling factors, such as stress, magnetic field, temperature and cutting angle on the mechanical behaviors were analyzed. Some useful conclusions were obtained, which will provide guidance for practical applications.

A Dynamical Model of Pitch Memory Provides an Improved Basis for Implied Harmony Estimation.

PubMed

Kim, Ji Chul

2017-01-01

Tonal melody can imply vertical harmony through a sequence of tones. Current methods for automatic chord estimation commonly use chroma-based features extracted from audio signals. However, the implied harmony of unaccompanied melodies can be difficult to estimate on the basis of chroma content in the presence of frequent nonchord tones. Here we present a novel approach to automatic chord estimation based on the human perception of pitch sequences. We use cohesion and inhibition between pitches in auditory short-term memory to differentiate chord tones and nonchord tones in tonal melodies. We model short-term pitch memory as a gradient frequency neural network, which is a biologically realistic model of auditory neural processing. The model is a dynamical system consisting of a network of tonotopically tuned nonlinear oscillators driven by audio signals. The oscillators interact with each other through nonlinear resonance and lateral inhibition, and the pattern of oscillatory traces emerging from the interactions is taken as a measure of pitch salience. We test the model with a collection of unaccompanied tonal melodies to evaluate it as a feature extractor for chord estimation. We show that chord tones are selectively enhanced in the response of the model, thereby increasing the accuracy of implied harmony estimation. We also find that, like other existing features for chord estimation, the performance of the model can be improved by using segmented input signals. We discuss possible ways to expand the present model into a full chord estimation system within the dynamical systems framework.

Age and CD4 count at initiation of antiretroviral therapy in HIV-infected children: effects on long-term T-cell reconstitution.

PubMed

Lewis, Joanna; Walker, A Sarah; Castro, Hannah; De Rossi, Anita; Gibb, Diana M; Giaquinto, Carlo; Klein, Nigel; Callard, Robin

2012-02-15

Effective therapies and reduced AIDS-related morbidity and mortality have shifted the focus in pediatric human immunodeficiency virus (HIV) from minimizing short-term disease progression to maintaining optimal long-term health. We describe the effects of children's age and pre-antiretroviral therapy (ART) CD4 count on long-term CD4 T-cell reconstitution. CD4 counts in perinatally HIV-infected, therapy-naive children in the Paediatric European Network for the Treatment of AIDS 5 trial were monitored following initiation of ART for a median 5.7 years. In a substudy, naive and memory CD4 counts were recorded. Age-standardized measurements were analyzed using monophasic, asymptotic nonlinear mixed-effects models. One hundred twenty-seven children were studied. Older children had lower age-adjusted CD4 counts in the long term and at treatment initiation (P < .001). At all ages, lower counts before treatment were associated with impaired recovery (P < .001). Age-adjusted naive CD4 counts increased on a timescale comparable to overall CD4 T-cell reconstitution, whereas age-adjusted memory CD4 counts increased less, albeit on a faster timescale. It appears the immature immune system can recover well from HIV infection via the naive pool. However, this potential is progressively damaged with age and/or duration of infection. Current guidelines may therefore not optimize long-term immunological health.

Arbitrary order 2D virtual elements for polygonal meshes: part II, inelastic problem

NASA Astrophysics Data System (ADS)

Artioli, E.; Beirão da Veiga, L.; Lovadina, C.; Sacco, E.

2017-10-01

The present paper is the second part of a twofold work, whose first part is reported in Artioli et al. (Comput Mech, 2017. doi: 10.1007/s00466-017-1404-5), concerning a newly developed Virtual element method (VEM) for 2D continuum problems. The first part of the work proposed a study for linear elastic problem. The aim of this part is to explore the features of the VEM formulation when material nonlinearity is considered, showing that the accuracy and easiness of implementation discovered in the analysis inherent to the first part of the work are still retained. Three different nonlinear constitutive laws are considered in the VEM formulation. In particular, the generalized viscoelastic model, the classical Mises plasticity with isotropic/kinematic hardening and a shape memory alloy constitutive law are implemented. The versatility with respect to all the considered nonlinear material constitutive laws is demonstrated through several numerical examples, also remarking that the proposed 2D VEM formulation can be straightforwardly implemented as in a standard nonlinear structural finite element method framework.

CUDA Optimization Strategies for Compute- and Memory-Bound Neuroimaging Algorithms

PubMed Central

Lee, Daren; Dinov, Ivo; Dong, Bin; Gutman, Boris; Yanovsky, Igor; Toga, Arthur W.

2011-01-01

As neuroimaging algorithms and technology continue to grow faster than CPU performance in complexity and image resolution, data-parallel computing methods will be increasingly important. The high performance, data-parallel architecture of modern graphical processing units (GPUs) can reduce computational times by orders of magnitude. However, its massively threaded architecture introduces challenges when GPU resources are exceeded. This paper presents optimization strategies for compute- and memory-bound algorithms for the CUDA architecture. For compute-bound algorithms, the registers are reduced through variable reuse via shared memory and the data throughput is increased through heavier thread workloads and maximizing the thread configuration for a single thread block per multiprocessor. For memory-bound algorithms, fitting the data into the fast but limited GPU resources is achieved through reorganizing the data into self-contained structures and employing a multi-pass approach. Memory latencies are reduced by selecting memory resources whose cache performance are optimized for the algorithm's access patterns. We demonstrate the strategies on two computationally expensive algorithms and achieve optimized GPU implementations that perform up to 6× faster than unoptimized ones. Compared to CPU implementations, we achieve peak GPU speedups of 129× for the 3D unbiased nonlinear image registration technique and 93× for the non-local means surface denoising algorithm. PMID:21159404

CUDA optimization strategies for compute- and memory-bound neuroimaging algorithms.

PubMed

Lee, Daren; Dinov, Ivo; Dong, Bin; Gutman, Boris; Yanovsky, Igor; Toga, Arthur W

2012-06-01

As neuroimaging algorithms and technology continue to grow faster than CPU performance in complexity and image resolution, data-parallel computing methods will be increasingly important. The high performance, data-parallel architecture of modern graphical processing units (GPUs) can reduce computational times by orders of magnitude. However, its massively threaded architecture introduces challenges when GPU resources are exceeded. This paper presents optimization strategies for compute- and memory-bound algorithms for the CUDA architecture. For compute-bound algorithms, the registers are reduced through variable reuse via shared memory and the data throughput is increased through heavier thread workloads and maximizing the thread configuration for a single thread block per multiprocessor. For memory-bound algorithms, fitting the data into the fast but limited GPU resources is achieved through reorganizing the data into self-contained structures and employing a multi-pass approach. Memory latencies are reduced by selecting memory resources whose cache performance are optimized for the algorithm's access patterns. We demonstrate the strategies on two computationally expensive algorithms and achieve optimized GPU implementations that perform up to 6× faster than unoptimized ones. Compared to CPU implementations, we achieve peak GPU speedups of 129× for the 3D unbiased nonlinear image registration technique and 93× for the non-local means surface denoising algorithm. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Facilitation of memory encoding in primate hippocampus by a neuroprosthesis that promotes task-specific neural firing

NASA Astrophysics Data System (ADS)

Hampson, Robert E.; Song, Dong; Opris, Ioan; Santos, Lucas M.; Shin, Dae C.; Gerhardt, Greg A.; Marmarelis, Vasilis Z.; Berger, Theodore W.; Deadwyler, Sam A.

2013-12-01

Objective. Memory accuracy is a major problem in human disease and is the primary factor that defines Alzheimer’s, ageing and dementia resulting from impaired hippocampal function in the medial temporal lobe. Development of a hippocampal memory neuroprosthesis that facilitates normal memory encoding in nonhuman primates (NHPs) could provide the basis for improving memory in human disease states. Approach. NHPs trained to perform a short-term delayed match-to-sample (DMS) memory task were examined with multi-neuron recordings from synaptically connected hippocampal cell fields, CA1 and CA3. Recordings were analyzed utilizing a previously developed nonlinear multi-input multi-output (MIMO) neuroprosthetic model, capable of extracting CA3-to-CA1 spatiotemporal firing patterns during DMS performance. Main results. The MIMO model verified that specific CA3-to-CA1 firing patterns were critical for the successful encoding of sample phase information on more difficult DMS trials. This was validated by the delivery of successful MIMO-derived encoding patterns via electrical stimulation to the same CA1 recording locations during the sample phase which facilitated task performance in the subsequent, delayed match phase, on difficult trials that required more precise encoding of sample information. Significance. These findings provide the first successful application of a neuroprosthesis designed to enhance and/or repair memory encoding in primate brain.

Facilitation of Memory Encoding in Primate Hippocampus by a Neuroprosthesis that Promotes Task Specific Neural Firing

PubMed Central

Hampson, Robert E.; Song, Dong; Opris, Ioan; Santos, Lucas M.; Shin, Dae C.; Gerhardt, Greg A.; Marmarelis, Vasilis Z.; Berger, Theodore W.; Deadwyler, Sam A.

2014-01-01

Objective Memory accuracy is a major problem in human disease and is the primary factor that defines Alzheimer’s’, aging and dementia resulting from impaired hippocampal function in medial temporal lobe. Development of a hippocampal memory neuroprosthesis that facilitates normal memory encoding in nonhuman primates (NHPs) could provide the basis for improving memory in human disease states. Approach NHPs trained to perform a short-term delayed match to sample (DMS) memory task were examined with multi-neuron recordings from synaptically connected hippocampal cell fields, CA1 and CA3. Recordings were analyzed utilizing a previously developed nonlinear multi-input multi-output (MIMO) neuroprosthetic model, capable of extracting CA3-to-CA1 spatiotemporal firing patterns during DMS performance. Main Results The MIMO model verified that specific CA3-to-CA1 firing patterns were critical for successful encoding of Sample phase information on more difficult DMS trials. This was validated by delivery of successful MIMO-derived encoding patterns via electrical stimulation to the same CA1 recording locations during the Sample phase which facilitated task performance in the subsequent delayed Match phase on difficult trials that required more precise encoding of Sample information. Significance These findings provide the first successful application of a neuroprosthesis designed to enhance and/or repair memory encoding in primate brain. PMID:24216292

Spin-based single-photon transistor, dynamic random access memory, diodes, and routers in semiconductors

NASA Astrophysics Data System (ADS)

Hu, C. Y.

2016-12-01

The realization of quantum computers and quantum Internet requires not only quantum gates and quantum memories, but also transistors at single-photon levels to control the flow of information encoded on single photons. Single-photon transistor (SPT) is an optical transistor in the quantum limit, which uses a single photon to open or block a photonic channel. In sharp contrast to all previous SPT proposals which are based on single-photon nonlinearities, here I present a design for a high-gain and high-speed (up to THz) SPT based on a linear optical effect: giant circular birefringence induced by a single spin in a double-sided optical microcavity. A gate photon sets the spin state via projective measurement and controls the light propagation in the optical channel. This spin-cavity transistor can be directly configured as diodes, routers, DRAM units, switches, modulators, etc. Due to the duality as quantum gate and transistor, the spin-cavity unit provides a solid-state platform ideal for future Internet: a mixture of all-optical Internet with quantum Internet.

Return Intervals Approach to Financial Fluctuations

NASA Astrophysics Data System (ADS)

Wang, Fengzhong; Yamasaki, Kazuko; Havlin, Shlomo; Stanley, H. Eugene

Financial fluctuations play a key role for financial markets studies. A new approach focusing on properties of return intervals can help to get better understanding of the fluctuations. A return interval is defined as the time between two successive volatilities above a given threshold. We review recent studies and analyze the 1000 most traded stocks in the US stock markets. We find that the distribution of the return intervals has a well approximated scaling over a wide range of thresholds. The scaling is also valid for various time windows from one minute up to one trading day. Moreover, these results are universal for stocks of different countries, commodities, interest rates as well as currencies. Further analysis shows some systematic deviations from a scaling law, which are due to the nonlinear correlations in the volatility sequence. We also examine the memory in return intervals for different time scales, which are related to the long-term correlations in the volatility. Furthermore, we test two popular models, FIGARCH and fractional Brownian motion (fBm). Both models can catch the memory effect but only fBm shows a good scaling in the return interval distribution.

Coupled Kinetic-MHD Simulations of Divertor Heat Load with ELM Perturbations

NASA Astrophysics Data System (ADS)

Cummings, Julian; Chang, C. S.; Park, Gunyoung; Sugiyama, Linda; Pankin, Alexei; Klasky, Scott; Podhorszki, Norbert; Docan, Ciprian; Parashar, Manish

2010-11-01

The effect of Type-I ELM activity on divertor plate heat load is a key component of the DOE OFES Joint Research Target milestones for this year. In this talk, we present simulations of kinetic edge physics, ELM activity, and the associated divertor heat loads in which we couple the discrete guiding-center neoclassical transport code XGC0 with the nonlinear extended MHD code M3D using the End-to-end Framework for Fusion Integrated Simulations, or EFFIS. In these coupled simulations, the kinetic code and the MHD code run concurrently on the same massively parallel platform and periodic data exchanges are performed using a memory-to-memory coupling technology provided by EFFIS. The M3D code models the fast ELM event and sends frequent updates of the magnetic field perturbations and electrostatic potential to XGC0, which in turn tracks particle dynamics under the influence of these perturbations and collects divertor particle and energy flux statistics. We describe here how EFFIS technologies facilitate these coupled simulations and discuss results for DIII-D, NSTX and Alcator C-Mod tokamak discharges.

Hysteresis modeling of magnetic shape memory alloy actuator based on Krasnosel'skii-Pokrovskii model.

PubMed

Zhou, Miaolei; Wang, Shoubin; Gao, Wei

2013-01-01

As a new type of intelligent material, magnetically shape memory alloy (MSMA) has a good performance in its applications in the actuator manufacturing. Compared with traditional actuators, MSMA actuator has the advantages as fast response and large deformation; however, the hysteresis nonlinearity of the MSMA actuator restricts its further improving of control precision. In this paper, an improved Krasnosel'skii-Pokrovskii (KP) model is used to establish the hysteresis model of MSMA actuator. To identify the weighting parameters of the KP operators, an improved gradient correction algorithm and a variable step-size recursive least square estimation algorithm are proposed in this paper. In order to demonstrate the validity of the proposed modeling approach, simulation experiments are performed, simulations with improved gradient correction algorithm and variable step-size recursive least square estimation algorithm are studied, respectively. Simulation results of both identification algorithms demonstrate that the proposed modeling approach in this paper can establish an effective and accurate hysteresis model for MSMA actuator, and it provides a foundation for improving the control precision of MSMA actuator.

Hysteresis Modeling of Magnetic Shape Memory Alloy Actuator Based on Krasnosel'skii-Pokrovskii Model

PubMed Central

Wang, Shoubin; Gao, Wei

2013-01-01

As a new type of intelligent material, magnetically shape memory alloy (MSMA) has a good performance in its applications in the actuator manufacturing. Compared with traditional actuators, MSMA actuator has the advantages as fast response and large deformation; however, the hysteresis nonlinearity of the MSMA actuator restricts its further improving of control precision. In this paper, an improved Krasnosel'skii-Pokrovskii (KP) model is used to establish the hysteresis model of MSMA actuator. To identify the weighting parameters of the KP operators, an improved gradient correction algorithm and a variable step-size recursive least square estimation algorithm are proposed in this paper. In order to demonstrate the validity of the proposed modeling approach, simulation experiments are performed, simulations with improved gradient correction algorithm and variable step-size recursive least square estimation algorithm are studied, respectively. Simulation results of both identification algorithms demonstrate that the proposed modeling approach in this paper can establish an effective and accurate hysteresis model for MSMA actuator, and it provides a foundation for improving the control precision of MSMA actuator. PMID:23737730

Locally optimum nonlinearities for DCT watermark detection.

PubMed

Briassouli, Alexia; Strintzis, Michael G

2004-12-01

The issue of copyright protection of digital multimedia data has attracted a lot of attention during the last decade. An efficient copyright protection method that has been gaining popularity is watermarking, i.e., the embedding of a signature in a digital document that can be detected only by its rightful owner. Watermarks are usually blindly detected using correlating structures, which would be optimal in the case of Gaussian data. However, in the case of DCT-domain image watermarking, the data is more heavy-tailed and the correlator is clearly suboptimal. Nonlinear receivers have been shown to be particularly well suited for the detection of weak signals in heavy-tailed noise, as they are locally optimal. This motivates the use of the Gaussian-tailed zero-memory nonlinearity, as well as the locally optimal Cauchy nonlinearity for the detection of watermarks in DCT transformed images. We analyze the performance of these schemes theoretically and compare it to that of the traditionally used Gaussian correlator, but also to the recently proposed generalized Gaussian detector, which outperforms the correlator. The theoretical analysis and the actual performance of these systems is assessed through experiments, which verify the theoretical analysis and also justify the use of nonlinear structures for watermark detection. The performance of the correlator and the nonlinear detectors in the presence of quantization is also analyzed, using results from dither theory, and also verified experimentally.

Physicochemical analog for modeling superimposed and coded memories

NASA Astrophysics Data System (ADS)

Ensanian, Minas

1992-07-01

The mammalian brain is distinguished by a life-time of memories being stored within the same general region of physicochemical space, and having two extraordinary features. First, memories to varying degrees are superimposed, as well as coded. Second, instantaneous recall of past events can often be affected by relatively simple, and seemingly unrelated sensory clues. For the purposes of attempting to mathematically model such complex behavior, and for gaining additional insights, it would be highly advantageous to be able to simulate or mimic similar behavior in a nonbiological entity where some analogical parameters of interest can reasonably be controlled. It has recently been discovered that in nonlinear accumulative metal fatigue memories (related to mechanical deformation) can be superimposed and coded in the crystal lattice, and that memory, that is, the total number of stress cycles can be recalled (determined) by scanning not the surfaces but the `edges' of the objects. The new scanning technique known as electrotopography (ETG) now makes the state space modeling of metallic networks possible. The author provides an overview of the new field and outlines the areas that are of immediate interest to the science of artificial neural networks.

Earthquake models using rate and state friction and fast multipoles

NASA Astrophysics Data System (ADS)

Tullis, T.

2003-04-01

The most realistic current earthquake models employ laboratory-derived non-linear constitutive laws. These are the rate and state friction laws having both a non-linear viscous or direct effect and an evolution effect in which frictional resistance depends on time of stationary contact and has a memory of past slip velocity that fades with slip. The frictional resistance depends on the log of the slip velocity as well as the log of stationary hold time, and the fading memory involves an approximately exponential decay with slip. Due to the nonlinearly of these laws, analytical earthquake models are not attainable and numerical models are needed. The situation is even more difficult if true dynamic models are sought that deal with inertial forces and slip velocities on the order of 1 m/s as are observed during dynamic earthquake slip. Additional difficulties that exist if the dynamic slip phase of earthquakes is modeled arise from two sources. First, many physical processes might operate during dynamic slip, but they are only poorly understood, the relative importance of the processes is unknown, and the processes are even more nonlinear than those described by the current rate and state laws. Constitutive laws describing such behaviors are still being developed. Second, treatment of inertial forces and the influence that dynamic stresses from elastic waves may have on slip on the fault requires keeping track of the history of slip on remote parts of the fault as far into the past as it takes waves to travel from there. This places even more stringent requirements on computer time. Challenges for numerical modeling of complete earthquake cycles are that both time steps and mesh sizes must be small. Time steps must be milliseconds during dynamic slip, and yet models must represent earthquake cycles 100 years or more in length; methods using adaptive step sizes are essential. Element dimensions need to be on the order of meters, both to approximate continuum behavior adequately and to model microseismicity as well as large earthquakes. In order to model significant sized earthquakes this requires millions of elements. Modeling methods like the boundary element method that involve Green's functions normally require computation times that increase with the number N of elements squared, so using large N becomes impossible. We have adapted the Fast Multipole method to this problem in which the influence of sufficiently remote elements are grouped together and the elements are indexed such that the computations more efficient when run on parallel computers. Compute time varies with N log N rather than N squared. Computer programs are available that use this approach (http://www.servogrid.org/slide/GEM/PARK). Whether the multipole approach can be adapted to dynamic modeling is unclear.

A space release/deployment system actuated by shape memory wires

NASA Astrophysics Data System (ADS)

Fragnito, Marino; Vetrella and, Sergio

2002-11-01

In this paper, the design of an innovative hold down/release and deployment device actuated by shape memory wires, to be used for the first time for the S MA RT microsatellite solar wings is shown. The release and deployment mechanisms are actuated by a Shape Memory wire (Nitinol), which allows a complete symmetrical and synchronous release, in a very short time, of the four wings in pairs. The hold down kinematic mechanism is preloaded to avoid vibration nonlinearities and unwanted deployment at launch. The deployment mechanism is a simple pulley system. The stiffness of the deployed panel-hinge system needs to be dimensioned in order to meet the on-orbit requirement for attitude control. One-way roller clutches are used to keep the panel at the desired angle during the mission. An ad hoc software has been developed to simulate both the release and deployment operations, coupling the SMA wire behavior with the system mechanics.

Suppressing the memory state of floating gate transistors with repeated femtosecond laser backside irradiations

NASA Astrophysics Data System (ADS)

Chambonneau, Maxime; Souiki-Figuigui, Sarra; Chiquet, Philippe; Della Marca, Vincenzo; Postel-Pellerin, Jérémy; Canet, Pierre; Portal, Jean-Michel; Grojo, David

2017-04-01

We demonstrate that infrared femtosecond laser pulses with intensity above the two-photon ionization threshold of crystalline silicon induce charge transport through the tunnel oxide in floating gate Metal-Oxide-Semiconductor transistor devices. With repeated irradiations of Flash memory cells, we show how the laser-produced free-electrons naturally redistribute on both sides of the tunnel oxide until the electric field of the transistor is suppressed. This ability enables us to determine in a nondestructive, rapid and contactless way the flat band and the neutral threshold voltages of the tested device. The physical mechanisms including nonlinear ionization, quantum tunneling of free-carriers, and flattening of the band diagram are discussed for interpreting the experiments. The possibility to control the carriers in memory transistors with ultrashort pulses holds promises for fast and remote device analyses (reliability, security, and defectivity) and for considerable developments in the growing field of ultrafast microelectronics.

Complex-valued multistate associative memory with nonlinear multilevel functions for gray-level image reconstruction.

PubMed

Tanaka, Gouhei; Aihara, Kazuyuki

2009-09-01

A widely used complex-valued activation function for complex-valued multistate Hopfield networks is revealed to be essentially based on a multilevel step function. By replacing the multilevel step function with other multilevel characteristics, we present two alternative complex-valued activation functions. One is based on a multilevel sigmoid function, while the other on a characteristic of a multistate bifurcating neuron. Numerical experiments show that both modifications to the complex-valued activation function bring about improvements in network performance for a multistate associative memory. The advantage of the proposed networks over the complex-valued Hopfield networks with the multilevel step function is more outstanding when a complex-valued neuron represents a larger number of multivalued states. Further, the performance of the proposed networks in reconstructing noisy 256 gray-level images is demonstrated in comparison with other recent associative memories to clarify their advantages and disadvantages.

Laser beam propagation through bulk nonlinear media: Numerical simulation and experiment

NASA Astrophysics Data System (ADS)

Kovsh, Dmitriy I.

This dissertation describes our efforts in modeling the propagation of high intensity laser pulses through optical systems consisting of one or multiple nonlinear elements. These nonlinear elements can be up to 103 times thicker than the depth of focus of the laser beam, so that the beam size changes drastically within the medium. The set of computer codes developed are organized in a software package (NLO_BPM). The ultrafast nonlinearities of the bound-electronic n2 and two-photon absorption as well as time dependent excited-state, free-carrier and thermal nonlinearities are included in the codes for modeling propagation of picosecond to nanosecond pulses and pulse trains. Various cylindrically symmetric spatial distributions of the input beam are modeled. We use the cylindrical symmetry typical of laser outputs to reduce the CPU and memory requirements making modeling a real- time task on PC's. The hydrodynamic equations describing the rarefaction of the medium due to heating and electrostriction are solved in the transient regime to determine refractive index changes on a nanosecond time scale. This effect can be simplified in some cases by an approximation that assumes an instantaneous expansion. We also find that the index change obtained from the photo-acoustic equation overshoots its steady-state value once the ratio between the pulse width and the acoustic transit time is greater than unity. We numerically study the sensitivity of the closed- aperture Z-scan experiment to nonlinear refraction for various input beam profiles. If the beam has a ring structure with a minimum (or zero) on axis in the far field, the sensitivity of Z-scan measurements can be increased by up to one order of magnitude. The linear propagation module integrated with the nonlinear beam propagation codes allows the simulation of typical experiments such as Z-scan and optical limiting experiments. We have used these codes to model the performance of optical limiters. We study two of the most promising limiter designs: the monolithic self-protective semiconductor limiter (MONOPOL) and a multi-cell tandem limiter based on a liquid solution of reverse saturable absorbing organic dye. The numerical outputs show good agreement with experimental results up to input energies where nonlinear scattering becomes significant.

Equilibration in one-dimensional quantum hydrodynamic systems

NASA Astrophysics Data System (ADS)

Sotiriadis, Spyros

2017-10-01

We study quench dynamics and equilibration in one-dimensional quantum hydrodynamics, which provides effective descriptions of the density and velocity fields in gapless quantum gases. We show that the information content of the large time steady state is inherently connected to the presence of ballistically moving localised excitations. When such excitations are present, the system retains memory of initial correlations up to infinite times, thus evading decoherence. We demonstrate this connection in the context of the Luttinger model, the simplest quantum hydrodynamic model, and in the quantum KdV equation. In the standard Luttinger model, memory of all initial correlations is preserved throughout the time evolution up to infinitely large times, as a result of the purely ballistic dynamics. However nonlinear dispersion or interactions, when separately present, lead to spreading and delocalisation that suppress the above effect by eliminating the memory of non-Gaussian correlations. We show that, for any initial state that satisfies sufficient clustering of correlations, the steady state is Gaussian in terms of the bosonised or fermionised fields in the dispersive or interacting case respectively. On the other hand, when dispersion and interaction are simultaneously present, a semiclassical approximation suggests that localisation is restored as the two effects compensate each other and solitary waves are formed. Solitary waves, or simply solitons, are experimentally observed in quantum gases and theoretically predicted based on semiclassical approaches, but the question of their stability at the quantum level remains to a large extent an open problem. We give a general overview on the subject and discuss the relevance of our findings to general out of equilibrium problems. Dedicated to John Cardy on the occasion of his 70th birthday.

Dopamine modulation of GABAergic function enables network stability and input selectivity for sustaining working memory in a computational model of the prefrontal cortex.

PubMed

Lew, Sergio E; Tseng, Kuei Y

2014-12-01

Dopamine modulation of GABAergic transmission in the prefrontal cortex (PFC) is thought to be critical for sustaining cognitive processes such as working memory and decision-making. Here, we developed a neurocomputational model of the PFC that includes physiological features of the facilitatory action of dopamine on fast-spiking interneurons to assess how a GABAergic dysregulation impacts on the prefrontal network stability and working memory. We found that a particular non-linear relationship between dopamine transmission and GABA function is required to enable input selectivity in the PFC for the formation and retention of working memory. Either degradation of the dopamine signal or the GABAergic function is sufficient to elicit hyperexcitability in pyramidal neurons and working memory impairments. The simulations also revealed an inverted U-shape relationship between working memory and dopamine, a function that is maintained even at high levels of GABA degradation. In fact, the working memory deficits resulting from reduced GABAergic transmission can be rescued by increasing dopamine tone and vice versa. We also examined the role of this dopamine-GABA interaction for the termination of working memory and found that the extent of GABAergic excitation needed to reset the PFC network begins to occur when the activity of fast-spiking interneurons surpasses 40 Hz. Together, these results indicate that the capability of the PFC to sustain working memory and network stability depends on a robust interplay of compensatory mechanisms between dopamine tone and the activity of local GABAergic interneurons.

Electromechanical properties of lead zirconate titanate piezoceramics under the influence of mechanical stresses.

PubMed

Zhang, Q M; Zhao, J

1999-01-01

In lead zirconate titanate piezoceramics, external stresses can cause substantial changes in the piezoelectric coefficients, dielectric constant, and elastic compliance due to nonlinear effects and stress depoling effects. In both soft and hard PZT piezoceramics, the aging can produce a memory effect that will facilitate the recovery of the poled state in the ceramics from momentary electric or stress depoling. In hard PZT ceramics, the local defect fields built up during the aging process can stabilize the ceramic against external stress depoling that results in a marked increase in the piezoelectric coefficient and electromechanical coupling factor in the ceramic under the stress. Although soft PZT ceramics can be easily stress depoled (losing piezoelectricity), a DC bias electric field, parallel to the original poling direction, can be employed to maintain the ceramic poling state so that the ceramic can be used at high stresses without depoling.

Preisach modeling and compensation for smart material hysteresis

NASA Astrophysics Data System (ADS)

Hughes, Declan C.; Wen, John T.

1995-02-01

Many of the Smart materials being investigated (e.g., Shape Memory Alloys (SMAs), piezoceramics, and magnetostrictives) exhibit significant hysteresis effects, especially when driven with large control signals. In this paper the similarity between the microscopic domain kinematics that generate static hysteresis effects, or ferromagnetics, piezoceramics and SMAs is noted. The Preisach independent domain hysteresis model, and its derivatives, have been shown to be a comprehensive class of hysteresis operator that captures the major features of ferromagnetic hysteresis, and hence it is proposed here as a suitable model for piezoceramic and SMA hysteresis also. This basic Preisach model is used to model piezoceramic sheet actuators bonded to a flexible aluminum beam, and a Nitinol SMA wire muscle that applies a bending force to the end of the beam. A numerical inverse Preisach hysteresis series compensator is also proposed and applied in a real time experiment thereby reducing the apparent nonlinear hysteresis effects for the piezoceramic actuator quasi-static case.

Learning During Stressful Times

PubMed Central

Shors, Tracey J.

2012-01-01

Stressful life events can have profound effects on our cognitive and motor abilities, from those that could be construed as adaptive to those not so. In this review, I discuss the general notion that acute stressful experience necessarily impairs our abilities to learn and remember. The effects of stress on operant conditioning, that is, learned helplessness, as well as those on classical conditioning procedures are discussed in the context of performance and adaptation. Studies indicating sex differences in learning during stressful times are discussed, as are those attributing different responses to the existence of multiple memory systems and nonlinear relationships. The intent of this review is to highlight the apparent plasticity of the stress response, how it might have evolved to affect both performance and learning processes, and the potential problems with interpreting stress effects on learning as either good or bad. An appreciation for its plasticity may provide new avenues for investigating its underlying neuronal mechanisms. PMID:15054128

Multiscale high-order/low-order (HOLO) algorithms and applications

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

Chacon, Luis; Chen, Guangye; Knoll, Dana Alan

Here, we review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. Themore » HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.« less

Multiscale high-order/low-order (HOLO) algorithms and applications

DOE PAGES

Chacon, Luis; Chen, Guangye; Knoll, Dana Alan; ...

2016-11-11

Here, we review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. Themore » HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.« less

Thermo-magneto-elastoplastic coupling model of metal magnetic memory testing method for ferromagnetic materials

NASA Astrophysics Data System (ADS)

Shi, Pengpeng; Zhang, Pengcheng; Jin, Ke; Chen, Zhenmao; Zheng, Xiaojing

2018-04-01

Metal magnetic memory (MMM) testing (also known as micro-magnetic testing) is a new non-destructive electromagnetic testing method that can diagnose ferromagnetic materials at an early stage by measuring the MMM signal directly on the material surface. Previous experiments have shown that many factors affect MMM signals, in particular, the temperature, the elastoplastic state, and the complex environmental magnetic field. However, the fact that there have been only a few studies of either how these factors affect the signals or the physical coupling mechanisms among them seriously limits the industrial applications of MMM testing. In this paper, a nonlinear constitutive relation for a ferromagnetic material considering the influences of temperature and elastoplastic state is established under a weak magnetic field and is used to establish a nonlinear thermo-magneto-elastoplastic coupling model of MMM testing. Comparing with experimental data verifies that the proposed theoretical model can accurately describe the thermo-magneto-elastoplastic coupling influence on MMM signals. The proposed theoretical model can predict the MMM signals in a complex environment and so is expected to provide a theoretical basis for improving the degree of quantification in MMM testing.

Iterative load-balancing method with multigrid level relaxation for particle simulation with short-range interactions

NASA Astrophysics Data System (ADS)

Furuichi, Mikito; Nishiura, Daisuke

2017-10-01

We developed dynamic load-balancing algorithms for Particle Simulation Methods (PSM) involving short-range interactions, such as Smoothed Particle Hydrodynamics (SPH), Moving Particle Semi-implicit method (MPS), and Discrete Element method (DEM). These are needed to handle billions of particles modeled in large distributed-memory computer systems. Our method utilizes flexible orthogonal domain decomposition, allowing the sub-domain boundaries in the column to be different for each row. The imbalances in the execution time between parallel logical processes are treated as a nonlinear residual. Load-balancing is achieved by minimizing the residual within the framework of an iterative nonlinear solver, combined with a multigrid technique in the local smoother. Our iterative method is suitable for adjusting the sub-domain frequently by monitoring the performance of each computational process because it is computationally cheaper in terms of communication and memory costs than non-iterative methods. Numerical tests demonstrated the ability of our approach to handle workload imbalances arising from a non-uniform particle distribution, differences in particle types, or heterogeneous computer architecture which was difficult with previously proposed methods. We analyzed the parallel efficiency and scalability of our method using Earth simulator and K-computer supercomputer systems.

Data-driven Climate Modeling and Prediction

NASA Astrophysics Data System (ADS)

Kondrashov, D. A.; Chekroun, M.

2016-12-01

Global climate models aim to simulate a broad range of spatio-temporal scales of climate variability with state vector having many millions of degrees of freedom. On the other hand, while detailed weather prediction out to a few days requires high numerical resolution, it is fairly clear that a major fraction of large-scale climate variability can be predicted in a much lower-dimensional phase space. Low-dimensional models can simulate and predict this fraction of climate variability, provided they are able to account for linear and nonlinear interactions between the modes representing large scales of climate dynamics, as well as their interactions with a much larger number of modes representing fast and small scales. This presentation will highlight several new applications by Multilayered Stochastic Modeling (MSM) [Kondrashov, Chekroun and Ghil, 2015] framework that has abundantly proven its efficiency in the modeling and real-time forecasting of various climate phenomena. MSM is a data-driven inverse modeling technique that aims to obtain a low-order nonlinear system of prognostic equations driven by stochastic forcing, and estimates both the dynamical operator and the properties of the driving noise from multivariate time series of observations or a high-end model's simulation. MSM leads to a system of stochastic differential equations (SDEs) involving hidden (auxiliary) variables of fast-small scales ranked by layers, which interact with the macroscopic (observed) variables of large-slow scales to model the dynamics of the latter, and thus convey memory effects. New MSM climate applications focus on development of computationally efficient low-order models by using data-adaptive decomposition methods that convey memory effects by time-embedding techniques, such as Multichannel Singular Spectrum Analysis (M-SSA) [Ghil et al. 2002] and recently developed Data-Adaptive Harmonic (DAH) decomposition method [Chekroun and Kondrashov, 2016]. In particular, new results by DAH-MSM modeling and prediction of Arctic Sea Ice, as well as decadal predictions of near-surface Earth temperatures will be presented.

Fractal and multifractal models for extreme bursts in space plasmas.

NASA Astrophysics Data System (ADS)

Watkins, Nicholas; Chapman, Sandra; Credgington, Dan; Rosenberg, Sam; Sanchez, Raul

2010-05-01

Space plasmas may be said to show at least two types of "universality". One type arises from the fact that plasma physics underpins all astrophysical systems, while another arises from the generic properties of coupled nonlinear physical systems, a branch of the emerging science of complexity. Much work in complexity science is contributing to the physical understanding of the ways by which complex interactions in such systems cause driven or random perturbations to be nonlinearly amplified in amplitude and/or spread out over a wide range of frequencies. These mechanisms lead to non-Gaussian fluctuations and long-ranged temporal memory (referred to by Mandelbrot as the "Noah" and "Joseph" effects, respectively). This poster discusses a standard toy model (linear fractional stable motion, LFSM) which combines the Noah and Joseph effects in a controllable way. I will describe how LFSM is being used to explore the interplay of the above two effects in the distribution of bursts above thresholds, with applications to extreme events in space time series. I will describe ongoing work to improve the accuracy of maximum likelihood-based estimation of burst size and waiting time distributions for LFSM first reported in Watkins et al [Space Science Review, 2005; PRE, 2009]. The relevance of turbulent cascades to space plasmas necessitates comparison between this model and multifractal models, and early results will be described [Watkins et al, PRL comment, 2009].

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

Kalinin, Sergei V.; Jesse, Stephen; Yang, Yaodong

Here, the nonlinear response of a ferroic to external fields has been studied for decades, garnering interest for both understanding fundamental physics, as well as technological applications such as memory devices. Yet, the behavior of ferroelectrics at mesoscopic regimes remains poorly understood, and the scale limits of theories developed for macroscopic regimes are not well tested experimentally. Here, we test the link between piezo-nonlinearity and local piezoelectric strain hysteresis, via AC-field dependent measurements in conjunction with first order reversal curve (FORC) measurements on (K,Na)NbO 3 crystals with band-excitation piezoelectric force microscopy. The correlation coefficient between nonlinearity amplitude and the FORCmore » of the polarization switching shows a clear decrease in correlation with increasing AC bias, suggesting the impact of domain wall clamping on the DC measurement case. Further, correlation of polynomial fitting terms from the nonlinear measurements with the hysteresis loop area reveals that the largest correlations are reserved for the quadratic terms, which is expected for irreversible domain wall motion contributions that impact both piezoelectric behavior as well as minor loop formation. These confirm the link between local piezoelectric nonlinearity, domain wall motion and minor loop formation, and suggest that existing theories (such as Preisach) are applicable at these length scales, with associated implications for future nanoscale devices.« less

Manipulating femtosecond spin-orbit torques with laser pulse sequences to control magnetic memory states and ringing

NASA Astrophysics Data System (ADS)

Lingos, P. C.; Wang, J.; Perakis, I. E.

2015-05-01

Femtosecond (fs) coherent control of collective order parameters is important for nonequilibrium phase dynamics in correlated materials. Here, we propose such control of ferromagnetic order based on using nonadiabatic optical manipulation of electron-hole (e -h ) photoexcitations to create fs carrier-spin pulses with controllable direction and time profile. These spin pulses are generated due to the time-reversal symmetry breaking arising from nonperturbative spin-orbit and magnetic exchange couplings of coherent photocarriers. By tuning the nonthermal populations of exchange-split, spin-orbit-coupled semiconductor band states, we can excite fs spin-orbit torques that control complex magnetization pathways between multiple magnetic memory states. We calculate the laser-induced fs magnetic anisotropy in the time domain by using density matrix equations of motion rather than the quasiequilibrium free energy. By comparing to pump-probe experiments, we identify a "sudden" out-of-plane magnetization canting displaying fs magnetic hysteresis, which agrees with switchings measured by the static Hall magnetoresistivity. This fs transverse spin-canting switches direction with magnetic state and laser frequency, which distinguishes it from the longitudinal nonlinear optical and demagnetization effects. We propose that sequences of clockwise or counterclockwise fs spin-orbit torques, photoexcited by shaping two-color laser-pulse sequences analogous to multidimensional nuclear magnetic resonance (NMR) spectroscopy, can be used to timely suppress or enhance magnetic ringing and switching rotation in magnetic memories.

Controllable SET process in O-Ti-Sb-Te based phase change memory for synaptic application

NASA Astrophysics Data System (ADS)

Ren, Kun; Li, Ruiheng; Chen, Xin; Wang, Yong; Shen, Jiabin; Xia, Mengjiao; Lv, Shilong; Ji, Zhenguo; Song, Zhitang

2018-02-01

The nonlinear resistance change and small bit resolution of phase change memory (PCM) under identical operation pulses will limit its performance as a synaptic device. The octahedral Ti-Te units in Ti-Sb-Te, regarded as nucleation seeds, are degenerated when Ti is bonded with O, causing a slower crystallization and a controllable SET process in PCM cells. A linear resistance change under identical pulses, a resolution of ˜8 bits, and an ON/OFF ratio of ˜102 has been achieved in O-Ti-Sb-Te based PCM, showing its potential application as a synaptic device to improve recognition performance of the neural network.

Subgrid-scale parameterization and low-frequency variability: a response theory approach

NASA Astrophysics Data System (ADS)

Demaeyer, Jonathan; Vannitsem, Stéphane

2016-04-01

Weather and climate models are limited in the possible range of resolved spatial and temporal scales. However, due to the huge space- and time-scale ranges involved in the Earth System dynamics, the effects of many sub-grid processes should be parameterized. These parameterizations have an impact on the forecasts or projections. It could also affect the low-frequency variability present in the system (such as the one associated to ENSO or NAO). An important question is therefore to know what is the impact of stochastic parameterizations on the Low-Frequency Variability generated by the system and its model representation. In this context, we consider a stochastic subgrid-scale parameterization based on the Ruelle's response theory and proposed in Wouters and Lucarini (2012). We test this approach in the context of a low-order coupled ocean-atmosphere model, detailed in Vannitsem et al. (2015), for which a part of the atmospheric modes is considered as unresolved. A natural separation of the phase-space into a slow invariant set and its fast complement allows for an analytical derivation of the different terms involved in the parameterization, namely the average, the fluctuation and the long memory terms. Its application to the low-order system reveals that a considerable correction of the low-frequency variability along the invariant subset can be obtained. This new approach of scale separation opens new avenues of subgrid-scale parameterizations in multiscale systems used for climate forecasts. References: Vannitsem S, Demaeyer J, De Cruz L, Ghil M. 2015. Low-frequency variability and heat transport in a low-order nonlinear coupled ocean-atmosphere model. Physica D: Nonlinear Phenomena 309: 71-85. Wouters J, Lucarini V. 2012. Disentangling multi-level systems: averaging, correlations and memory. Journal of Statistical Mechanics: Theory and Experiment 2012(03): P03 003.

A long time ago, where were the galaxies far, far away?

NASA Astrophysics Data System (ADS)

Sirko, Edwin

How did the universe get from then to now ? I examine this broad cosmological problem from two perspectives: forward and backward. In the forward perspective, I implement a method of generating initial conditions for N -body simulations that accurately models real-space statistical properties, such as the mass variance in spheres and the correlation function. The method requires running ensembles of simulations because the power in the DC mode is no longer assumed to be zero. For moderately sized boxes, I demonstrate that the new method corrects the previously widely ignored underestimate in the mass variance in spheres and the shape of the correlation function. In the backward perspective, I use reconstruction techniques to transform a simulated or observed cosmological density field back in time to the early universe. A simple reconstruction technique is used to sharpen the baryon acoustic peak in the correlation function in simulations. At z = 0.3, one can reduce the sample variance error bar on the acoustic scale by at least a factor of 2 and in principle by nearly a factor of 4. This has significant implications for future observational surveys aiming to measure the cosmological distance scale. Another reconstruction technique, Monge-Ampere-Kantorovich reconstruction, is used on evolved N -body simulations to calibrate its effectiveness in recovering the linear power spectrum. A new "memory model" parametrizes the evolution of Fourier modes into two parameters that describe the amount of memory a given mode retains and how much the mode has been scrambled by nonlinear evolution. Reconstruction is spectacularly successful in restoring the memory of Fourier modes and reducing the scrambling; however, the success of reconstruction is not so obvious when considering the power spectrum alone. I apply reconstruction to a volume-limited sample of galaxies from the Sloan Digital Sky Survey and conclude that linear bias is not a good model in the range 0.01 h Mpc -1 [Special characters omitted.] k [Special characters omitted.] 0.5 h Mpc -1 . The most impressive success of reconstruction applied to real data is that the confidence interval on the normalization of the power spectrum is typically halved when using the reconstructed instead of the nonlinear power spectrum.

Mild traumatic brain injury: graph-model characterization of brain networks for episodic memory.

PubMed

Tsirka, Vasso; Simos, Panagiotis G; Vakis, Antonios; Kanatsouli, Kassiani; Vourkas, Michael; Erimaki, Sofia; Pachou, Ellie; Stam, Cornelis Jan; Micheloyannis, Sifis

2011-02-01

Episodic memory is among the cognitive functions that can be affected in the acute phase following mild traumatic brain injury (MTBI). The present study used EEG recordings to evaluate global synchronization and network organization of rhythmic activity during the encoding and recognition phases of an episodic memory task varying in stimulus type (kaleidoscope images, pictures, words, and pseudowords). Synchronization of oscillatory activity was assessed using a linear and nonlinear connectivity estimator and network analyses were performed using algorithms derived from graph theory. Twenty five MTBI patients (tested within days post-injury) and healthy volunteers were closely matched on demographic variables, verbal ability, psychological status variables, as well as on overall task performance. Patients demonstrated sub-optimal network organization, as reflected by changes in graph parameters in the theta and alpha bands during both encoding and recognition. There were no group differences in spectral energy during task performance or on network parameters during a control condition (rest). Evidence of less optimally organized functional networks during memory tasks was more prominent for pictorial than for verbal stimuli. Copyright © 2010 Elsevier B.V. All rights reserved.

An energy- and charge-conserving, implicit, electrostatic particle-in-cell algorithm

NASA Astrophysics Data System (ADS)

Chen, G.; Chacón, L.; Barnes, D. C.

2011-08-01

This paper discusses a novel fully implicit formulation for a one-dimensional electrostatic particle-in-cell (PIC) plasma simulation approach. Unlike earlier implicit electrostatic PIC approaches (which are based on a linearized Vlasov-Poisson formulation), ours is based on a nonlinearly converged Vlasov-Ampére (VA) model. By iterating particles and fields to a tight nonlinear convergence tolerance, the approach features superior stability and accuracy properties, avoiding most of the accuracy pitfalls in earlier implicit PIC implementations. In particular, the formulation is stable against temporal (Courant-Friedrichs-Lewy) and spatial (aliasing) instabilities. It is charge- and energy-conserving to numerical round-off for arbitrary implicit time steps (unlike the earlier "energy-conserving" explicit PIC formulation, which only conserves energy in the limit of arbitrarily small time steps). While momentum is not exactly conserved, errors are kept small by an adaptive particle sub-stepping orbit integrator, which is instrumental to prevent particle tunneling (a deleterious effect for long-term accuracy). The VA model is orbit-averaged along particle orbits to enforce an energy conservation theorem with particle sub-stepping. As a result, very large time steps, constrained only by the dynamical time scale of interest, are possible without accuracy loss. Algorithmically, the approach features a Jacobian-free Newton-Krylov solver. A main development in this study is the nonlinear elimination of the new-time particle variables (positions and velocities). Such nonlinear elimination, which we term particle enslavement, results in a nonlinear formulation with memory requirements comparable to those of a fluid computation, and affords us substantial freedom in regards to the particle orbit integrator. Numerical examples are presented that demonstrate the advertised properties of the scheme. In particular, long-time ion acoustic wave simulations show that numerical accuracy does not degrade even with very large implicit time steps, and that significant CPU gains are possible.

Exact charge and energy conservation in implicit PIC with mapped computational meshes

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

Chen, Guangye; Barnes, D. C.

This paper discusses a novel fully implicit formulation for a one-dimensional electrostatic particle-in-cell (PIC) plasma simulation approach. Unlike earlier implicit electrostatic PIC approaches (which are based on a linearized Vlasov Poisson formulation), ours is based on a nonlinearly converged Vlasov Amp re (VA) model. By iterating particles and fields to a tight nonlinear convergence tolerance, the approach features superior stability and accuracy properties, avoiding most of the accuracy pitfalls in earlier implicit PIC implementations. In particular, the formulation is stable against temporal (Courant Friedrichs Lewy) and spatial (aliasing) instabilities. It is charge- and energy-conserving to numerical round-off for arbitrary implicitmore » time steps (unlike the earlier energy-conserving explicit PIC formulation, which only conserves energy in the limit of arbitrarily small time steps). While momentum is not exactly conserved, errors are kept small by an adaptive particle sub-stepping orbit integrator, which is instrumental to prevent particle tunneling (a deleterious effect for long-term accuracy). The VA model is orbit-averaged along particle orbits to enforce an energy conservation theorem with particle sub-stepping. As a result, very large time steps, constrained only by the dynamical time scale of interest, are possible without accuracy loss. Algorithmically, the approach features a Jacobian-free Newton Krylov solver. A main development in this study is the nonlinear elimination of the new-time particle variables (positions and velocities). Such nonlinear elimination, which we term particle enslavement, results in a nonlinear formulation with memory requirements comparable to those of a fluid computation, and affords us substantial freedom in regards to the particle orbit integrator. Numerical examples are presented that demonstrate the advertised properties of the scheme. In particular, long-time ion acoustic wave simulations show that numerical accuracy does not degrade even with very large implicit time steps, and that significant CPU gains are possible.« less

Focus scanning with feedback control for fiber-optic nonlinear endomicroscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Li, Ang; Liang, Wenxuan; Li, Xingde

2017-02-01

Fiber-optic nonlinear endomicroscopy represents a strong promise to enable translation of nonlinear microscopy technologies to in vivo applications, particularly imaging of internal organs. Two-dimensional imaging beam scanning has been accomplished by using fiber-optic scanners or MEMS scanners. Yet nonlinear endomicroscopy still cannot perform rapid and reliable depth or focus scanning while maintaining a small form factor. Shape memory alloy (SMA) wire had shown promise in extending 2D endoscopic imaging to the third dimension. By Joule heating, the SMA wire would contract and move the endomicroscope optics to change beam focus. However, this method suffered from hysteresis, and was susceptible to change in ambient temperature, making it difficult to achieve accurate and reliable depth scanning. Here we present a feedback-controlled SMA actuator which addressed these challenges. The core of the feedback loop was a Hall effect sensor. By measuring the magnetic flux density from a tiny magnet attached to the SMA wire, contraction distance of the SMA wire could be tracked in real time. The distance was then fed to the PID algorithm running in a microprocessor, which computed the error between the command position and the current position of the actuator. The current running through the SMA wire was adjusted accordingly. Our feedback-controlled SMA actuator had a tube-like shape with outer diameter of 5.5 mm and length of 25 mm, and was designed to house the endomicroscope inside. Initial test showed that it allowed more than 300 microns of travel distance, with an average positioning error of less than 2 microns. 3D imaging experiments with the endomicroscope is underway, and its imaging performance will be assessed and discussed.

Olfactory recognition memory is disrupted in young mice with chronic low-level lead exposure.

PubMed

Flores-Montoya, Mayra Gisel; Alvarez, Juan Manuel; Sobin, Christina

2015-07-02

Chronic developmental lead exposure yielding very low blood lead burden is an unresolved child public health problem. Few studies have attempted to model neurobehavioral changes in young animals following very low level exposure, and studies are needed to identify tests that are sensitive to the neurobehavioral changes that may occur. Mechanisms of action are not yet known however results have suggested that hippocampus/dentate gyrus may be uniquely vulnerable to early chronic low-level lead exposure. This study examined the sensitivity of a novel odor recognition task to differences in pre-adolescent C57BL/6J mice chronically exposed from birth to PND 28, to 0 ppm (control), 30 ppm (low-dose), or 330 ppm (higher-dose) lead acetate (N=33). Blood lead levels (BLLs) determined by ICP-MS ranged from 0.02 to 20.31 μg/dL. Generalized linear mixed model analyses with litter as a random effect showed a significant interaction of BLL×sex. As BLLs increased olfactory recognition memory decreased in males. Among females, non-linear effects were observed at lower but not higher levels of lead exposure. The novel odor detection task is sensitive to effects associated with early chronic low-level lead exposure in young C57BL/6J mice. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Coexistence of Multiple Nonlinear States in a Tristable Passive Kerr Resonator

NASA Astrophysics Data System (ADS)

Anderson, Miles; Wang, Yadong; Leo, François; Coen, Stéphane; Erkintalo, Miro; Murdoch, Stuart G.

2017-07-01

Passive Kerr cavities driven by coherent laser fields display a rich landscape of nonlinear physics, including bistability, pattern formation, and localized dissipative structures (solitons). Their conceptual simplicity has for several decades offered an unprecedented window into nonlinear cavity dynamics, providing insights into numerous systems and applications ranging from all-optical memory devices to microresonator frequency combs. Yet despite the decades of study, a recent theoretical work has surprisingly alluded to an entirely new and unexplored paradigm in the regime where nonlinearly tilted cavity resonances overlap with one another [T. Hansson and S. Wabnitz, J. Opt. Soc. Am. B 32, 1259 (2015), 10.1364/JOSAB.32.001259]. We use synchronously driven fiber ring resonators to experimentally access this regime and observe the rise of new nonlinear dissipative states. Specifically, we observe, for the first time to the best of our knowledge, the stable coexistence of temporal Kerr cavity solitons and extended modulation instability (Turing) patterns, and perform real-time measurements that unveil the dynamics of the ensuing nonlinear structure. When operating in the regime of continuous wave tristability, we further observe the coexistence of two distinct cavity soliton states, one of which can be identified as a "super" cavity soliton, as predicted by Hansson and Wabnitz. Our experimental findings are in excellent agreement with theoretical analyses and numerical simulations of the infinite-dimensional Ikeda map that governs the cavity dynamics. The results from our work reveal that experimental systems can support complex combinations of distinct nonlinear states, and they could have practical implications to future microresonator-based frequency comb sources.

A cost-effective line-based light-balancing technique using adaptive processing.

PubMed

Hsia, Shih-Chang; Chen, Ming-Huei; Chen, Yu-Min

2006-09-01

The camera imaging system has been widely used; however, the displaying image appears to have an unequal light distribution. This paper presents novel light-balancing techniques to compensate uneven illumination based on adaptive signal processing. For text image processing, first, we estimate the background level and then process each pixel with nonuniform gain. This algorithm can balance the light distribution while keeping a high contrast in the image. For graph image processing, the adaptive section control using piecewise nonlinear gain is proposed to equalize the histogram. Simulations show that the performance of light balance is better than the other methods. Moreover, we employ line-based processing to efficiently reduce the memory requirement and the computational cost to make it applicable in real-time systems.

Organo-metallic elements for associative information processing

NASA Astrophysics Data System (ADS)

Potember, Richard S.; Poehler, Theodore O.

1989-01-01

In the three years of the program we have: (1) built and tested a 4 bit element matrix device for possible use in high density content-addressable memories systems; (2) established a test and evaluation laboratory to examine optical materials for nonlinear effects, saturable absorption, harmonic generation and photochromism; (3) successfully designed, constructed and operated a codeposition processing system that enables organic materials to be deposited on a variety of substrates to produce optical grade coatings and films. This system is also compatible with other traditional microelectronic techniques; (4) used the sol-gel process with colloidal AgTCNQ to fabricate high speed photochromic switches; (5) develop and applied for patent coverage to make VO2 optical switching materials via the sol-gel processing using vanadium (IV) alkoxide compounds.

A general decay result of a viscoelastic equation with past history and boundary feedback

NASA Astrophysics Data System (ADS)

Messaoudi, Salim A.; Al-Gharabli, Mohammad M.

2015-08-01

In this paper, we consider a viscoelastic equation with a nonlinear feedback localized on a part of the boundary and in the presence of infinite memory term. In the domain as well as on a part of the boundary, we use the multiplier method and some properties of the convex functions to prove an explicit and general decay result.

LIMS for Lasers 2015 for achieving long-term accuracy and precision of δ2H, δ17O, and δ18O of waters using laser absorption spectrometry

USGS Publications Warehouse

Coplen, Tyler B.; Wassenaar, Leonard I

2015-01-01

RationaleAlthough laser absorption spectrometry (LAS) instrumentation is easy to use, its incorporation into laboratory operations is not easy, owing to extensive offline manipulation of comma-separated-values files for outlier detection, between-sample memory correction, nonlinearity (δ-variation with water amount) correction, drift correction, normalization to VSMOW-SLAP scales, and difficulty in performing long-term QA/QC audits.MethodsA Microsoft Access relational-database application, LIMS (Laboratory Information Management System) for Lasers 2015, was developed. It automates LAS data corrections and manages clients, projects, samples, instrument-sample lists, and triple-isotope (δ17O, δ18O, and δ2H values) instrumental data for liquid-water samples. It enables users to (1) graphically evaluate sample injections for variable water yields and high isotope-delta variance; (2) correct for between-sample carryover, instrumental drift, and δ nonlinearity; and (3) normalize final results to VSMOW-SLAP scales.ResultsCost-free LIMS for Lasers 2015 enables users to obtain improved δ17O, δ18O, and δ2H values with liquid-water LAS instruments, even those with under-performing syringes. For example, LAS δ2HVSMOW measurements of USGS50 Lake Kyoga (Uganda) water using an under-performing syringe having ±10 % variation in water concentration gave +31.7 ± 1.6 ‰ (2-σ standard deviation), compared with the reference value of +32.8 ± 0.4 ‰, after correction for variation in δ value with water concentration, between-sample memory, and normalization to the VSMOW-SLAP scale.ConclusionsLIMS for Lasers 2015 enables users to create systematic, well-founded instrument templates, import δ2H, δ17O, and δ18O results, evaluate performance with automatic graphical plots, correct for δ nonlinearity due to variable water concentration, correct for between-sample memory, adjust for drift, perform VSMOW-SLAP normalization, and perform long-term QA/QC audits easily. Published in 2015. This article is a U.S. Government work and is in the public domain in the USA.

Strange nonchaotic attractors for computation

NASA Astrophysics Data System (ADS)

Sathish Aravindh, M.; Venkatesan, A.; Lakshmanan, M.

2018-05-01

We investigate the response of quasiperiodically driven nonlinear systems exhibiting strange nonchaotic attractors (SNAs) to deterministic input signals. We show that if one uses two square waves in an aperiodic manner as input to a quasiperiodically driven double-well Duffing oscillator system, the response of the system can produce logical output controlled by such a forcing. Changing the threshold or biasing of the system changes the output to another logic operation and memory latch. The interplay of nonlinearity and quasiperiodic forcing yields logical behavior, and the emergent outcome of such a system is a logic gate. It is further shown that the logical behaviors persist even for an experimental noise floor. Thus the SNA turns out to be an efficient tool for computation.

Quantum information processing with a travelling wave of light

NASA Astrophysics Data System (ADS)

Serikawa, Takahiro; Shiozawa, Yu; Ogawa, Hisashi; Takanashi, Naoto; Takeda, Shuntaro; Yoshikawa, Jun-ichi; Furusawa, Akira

2018-02-01

We exploit quantum information processing on a traveling wave of light, expecting emancipation from thermal noise, easy coupling to fiber communication, and potentially high operation speed. Although optical memories are technically challenging, we have an alternative approach to apply multi-step operations on traveling light, that is, continuous-variable one-way computation. So far our achievement includes generation of a one-million-mode entangled chain in time-domain, mode engineering of nonlinear resource states, and real-time nonlinear feedforward. Although they are implemented with free space optics, we are also investigating photonic integration and performed quantum teleportation with a passive liner waveguide chip as a demonstration of entangling, measurement, and feedforward. We also suggest a loop-based architecture as another model of continuous-variable computing.

Stabilization of the SIESTA MHD Equilibrium Code Using Rapid Cholesky Factorization

NASA Astrophysics Data System (ADS)

Hirshman, S. P.; D'Azevedo, E. A.; Seal, S. K.

2016-10-01

The SIESTA MHD equilibrium code solves the discretized nonlinear MHD force F ≡ J X B - ∇p for a 3D plasma which may contain islands and stochastic regions. At each nonlinear evolution step, it solves a set of linearized MHD equations which can be written r ≡ Ax - b = 0, where A is the linearized MHD Hessian matrix. When the solution norm | x| is small enough, the nonlinear force norm will be close to the linearized force norm | r| 0 obtained using preconditioned GMRES. In many cases, this procedure works well and leads to a vanishing nonlinear residual (equilibrium) after several iterations in SIESTA. In some cases, however, | x|>1 results and the SIESTA code has to be restarted to obtain nonlinear convergence. In order to make SIESTA more robust and avoid such restarts, we have implemented a new rapid QR factorization of the Hessian which allows us to rapidly and accurately solve the least-squares problem AT r = 0, subject to the condition | x|<1. This avoids large contributions to the nonlinear force terms and in general makes the convergence sequence of SIESTA much more stable. The innovative rapid QR method is based on a pairwise row factorization of the tri-diagonal Hessian. It provides a complete Cholesky factorization while preserving the memory allocation of A. This work was supported by the U.S. D.O.E. contract DE-AC05-00OR22725.

Vegetation anomalies caused by antecedent precipitation in most of the world

NASA Astrophysics Data System (ADS)

Papagiannopoulou, C.; Miralles, D. G.; Dorigo, W. A.; Verhoest, N. E. C.; Depoorter, M.; Waegeman, W.

2017-07-01

Quantifying environmental controls on vegetation is critical to predict the net effect of climate change on global ecosystems and the subsequent feedback on climate. Following a non-linear Granger causality framework based on a random forest predictive model, we exploit the current wealth of multi-decadal satellite data records to uncover the main drivers of monthly vegetation variability at the global scale. Results indicate that water availability is the most dominant factor driving vegetation globally: about 61% of the vegetated surface was primarily water-limited during 1981-2010. This included semiarid climates but also transitional ecoregions. Intra-annually, temperature controls Northern Hemisphere deciduous forests during the growing season, while antecedent precipitation largely dominates vegetation dynamics during the senescence period. The uncovered dependency of global vegetation on water availability is substantially larger than previously reported. This is owed to the ability of the framework to (1) disentangle the co-linearities between radiation/temperature and precipitation, and (2) quantify non-linear impacts of climate on vegetation. Our results reveal a prolonged effect of precipitation anomalies in dry regions: due to the long memory of soil moisture and the cumulative, non-linear, response of vegetation, water-limited regions show sensitivity to the values of precipitation occurring three months earlier. Meanwhile, the impacts of temperature and radiation anomalies are more immediate and dissipate shortly, pointing to a higher resilience of vegetation to these anomalies. Despite being infrequent by definition, hydro-climatic extremes are responsible for up to 10% of the vegetation variability during the 1981-2010 period in certain areas, particularly in water-limited ecosystems. Our approach is a first step towards a quantitative comparison of the resistance and resilience signature of different ecosystems, and can be used to benchmark Earth system models in their representations of past vegetation sensitivity to changes in climate.

Localization of Non-Linearly Modeled Autonomous Mobile Robots Using Out-of-Sequence Measurements

PubMed Central

Besada-Portas, Eva; Lopez-Orozco, Jose A.; Lanillos, Pablo; de la Cruz, Jesus M.

2012-01-01

This paper presents a state of the art of the estimation algorithms dealing with Out-of-Sequence (OOS) measurements for non-linearly modeled systems. The state of the art includes a critical analysis of the algorithm properties that takes into account the applicability of these techniques to autonomous mobile robot navigation based on the fusion of the measurements provided, delayed and OOS, by multiple sensors. Besides, it shows a representative example of the use of one of the most computationally efficient approaches in the localization module of the control software of a real robot (which has non-linear dynamics, and linear and non-linear sensors) and compares its performance against other approaches. The simulated results obtained with the selected OOS algorithm shows the computational requirements that each sensor of the robot imposes to it. The real experiments show how the inclusion of the selected OOS algorithm in the control software lets the robot successfully navigate in spite of receiving many OOS measurements. Finally, the comparison highlights that not only is the selected OOS algorithm among the best performing ones of the comparison, but it also has the lowest computational and memory cost. PMID:22736962

Localization of non-linearly modeled autonomous mobile robots using out-of-sequence measurements.

PubMed

Besada-Portas, Eva; Lopez-Orozco, Jose A; Lanillos, Pablo; de la Cruz, Jesus M

2012-01-01

This paper presents a state of the art of the estimation algorithms dealing with Out-of-Sequence (OOS) measurements for non-linearly modeled systems. The state of the art includes a critical analysis of the algorithm properties that takes into account the applicability of these techniques to autonomous mobile robot navigation based on the fusion of the measurements provided, delayed and OOS, by multiple sensors. Besides, it shows a representative example of the use of one of the most computationally efficient approaches in the localization module of the control software of a real robot (which has non-linear dynamics, and linear and non-linear sensors) and compares its performance against other approaches. The simulated results obtained with the selected OOS algorithm shows the computational requirements that each sensor of the robot imposes to it. The real experiments show how the inclusion of the selected OOS algorithm in the control software lets the robot successfully navigate in spite of receiving many OOS measurements. Finally, the comparison highlights that not only is the selected OOS algorithm among the best performing ones of the comparison, but it also has the lowest computational and memory cost.

On the multifractal effects generated by monofractal signals

NASA Astrophysics Data System (ADS)

Grech, Dariusz; Pamuła, Grzegorz

2013-12-01

We study quantitatively the level of false multifractal signal one may encounter while analyzing multifractal phenomena in time series within multifractal detrended fluctuation analysis (MF-DFA). The investigated effect appears as a result of finite length of used data series and is additionally amplified by the long-term memory the data eventually may contain. We provide the detailed quantitative description of such apparent multifractal background signal as a threshold in spread of generalized Hurst exponent values Δh or a threshold in the width of multifractal spectrum Δα below which multifractal properties of the system are only apparent, i.e. do not exist, despite Δα≠0 or Δh≠0. We find this effect quite important for shorter or persistent series and we argue it is linear with respect to autocorrelation exponent γ. Its strength decays according to power law with respect to the length of time series. The influence of basic linear and nonlinear transformations applied to initial data in finite time series with various levels of long memory is also investigated. This provides additional set of semi-analytical results. The obtained formulas are significant in any interdisciplinary application of multifractality, including physics, financial data analysis or physiology, because they allow to separate the ‘true’ multifractal phenomena from the apparent (artificial) multifractal effects. They should be a helpful tool of the first choice to decide whether we do in particular case with the signal with real multiscaling properties or not.

The narcoleptic cognitive pupillary response.

PubMed

O'Neill, W D; Trick, K P

2001-09-01

It has been reported that narcoleptics exhibit deficits in short-term memory, list recall, and stimulus frequency estimation compared with control subjects. It is also well-known that pupil dilation during cognitive tasks is a measure of subject attention state. Here we present results from six narcoleptics and six controls, a total of 360 experimental records in which pupillograms were made during cognitive tests, which indicate that narcoleptics begin pupillary dilations at a smaller diameter, begin dilating earlier poststimulus, attain higher pupillary diameter velocities, yet achieve the same equilibrium dilation diameter as controls. These findings are derived from statistical tests performed on the parameters of a nonlinear regression model of pupillary cognitive dilation as a function of time. In our experiments, the standard 1-s interdigit time between cognitive stimuli was increased to 2.3 s, which yielded pupillographic time records showing that the process of short-term memory overload sets in gradually at about four memory digits for controls and three memory digits for narcoleptics. We suggest our results can be partially explained by a narcoleptic stimulus-encoding deficit, which limits the time available for subjects to rehearse cognitive tasks. However, we also report the unexpected finding that the inferred encoding deficit is a transient one in that repeated tasks at the same memory load elicit a near normal naroleptic pupillary dilation.

Enhanced spatial resolution in fluorescence molecular tomography using restarted L1-regularized nonlinear conjugate gradient algorithm.

PubMed

Shi, Junwei; Liu, Fei; Zhang, Guanglei; Luo, Jianwen; Bai, Jing

2014-04-01

Owing to the high degree of scattering of light through tissues, the ill-posedness of fluorescence molecular tomography (FMT) inverse problem causes relatively low spatial resolution in the reconstruction results. Unlike L2 regularization, L1 regularization can preserve the details and reduce the noise effectively. Reconstruction is obtained through a restarted L1 regularization-based nonlinear conjugate gradient (re-L1-NCG) algorithm, which has been proven to be able to increase the computational speed with low memory consumption. The algorithm consists of inner and outer iterations. In the inner iteration, L1-NCG is used to obtain the L1-regularized results. In the outer iteration, the restarted strategy is used to increase the convergence speed of L1-NCG. To demonstrate the performance of re-L1-NCG in terms of spatial resolution, simulation and physical phantom studies with fluorescent targets located with different edge-to-edge distances were carried out. The reconstruction results show that the re-L1-NCG algorithm has the ability to resolve targets with an edge-to-edge distance of 0.1 cm at a depth of 1.5 cm, which is a significant improvement for FMT.

Nonlinear aerodynamic effects on bodies in supersonic flow

NASA Technical Reports Server (NTRS)

Pittman, J. L.; Siclari, M. J.

1984-01-01

The supersonic flow about generic bodies was analyzed to identify the elments of the nonlinear flow and to determine the influence of geometry and flow conditions on the magnitude of these nonlinearities. The nonlinear effects were attributed to separated-flow nonlinearities and attached-flow nonlinearities. The nonlinear attached-flow contribution was further broken down into large-disturbance effects and entropy effects. Conical, attached-flow bundaries were developed to illustrate the flow regimes where the nonlinear effects are significant, and the use of these boundaries for angle of attack and three-dimensional geometries was indicated. Normal-force and pressure comparisons showed that the large-disturbance and separated-flow effects were the dominant nonlinear effects at low supersonic Mach numbers and that the entropy effects were dominant for high supersonic Mach number flow. The magnitude of all the nonlinear effects increased with increasing angle of attack. A full-potential method, NCOREL, which includes an approximate entropy correction, was shown to provide accurate attached-flow pressure estimates from Mach 1.6 through 4.6.

Holographic Associative Memory Employing Phase Conjugation

NASA Astrophysics Data System (ADS)

Soffer, B. H.; Marom, E.; Owechko, Y.; Dunning, G.

1986-12-01

The principle of information retrieval by association has been suggested as a basis for parallel computing and as the process by which human memory functions.1 Various associative processors have been proposed that use electronic or optical means. Optical schemes,2-7 in particular, those based on holographic principles,8'8' are well suited to associative processing because of their high parallelism and information throughput. Previous workers8 demonstrated that holographically stored images can be recalled by using relatively complicated reference images but did not utilize nonlinear feedback to reduce the large cross talk that results when multiple objects are stored and a partial or distorted input is used for retrieval. These earlier approaches were limited in their ability to reconstruct the output object faithfully from a partial input.

Design and application of shape memory actuators

NASA Astrophysics Data System (ADS)

Mertmann, M.; Vergani, G.

2008-05-01

The use of shape memory alloys in actuators allows the development of robust, simple and lightweight elements for application in a multitude of different industries. Over the years, the intermetallic compound Nickel-Titanium (NiTi or Nitinol) together with its ternary and quaternary derivates has gained general acceptance as a standard alloy. Even though as many as 99% of all shape memory actuator applications make use of Nitinol there are certain properties of this alloy system which require further research in order to find improvements and new markets: • Lack of higher transformation temperatures in the available alloys in order to open the field of automotive applications (Mf temperature > 80 °C) • Non-linearity in the electrical resistivity in order to improve the controllability of the actuator, • Wide hysteresis in the temperature-vs.-strain behaviour, which has a signi-ficant effect on both, the dynamics of the actuator and its controllability. Hence, there is a constant strive in the field towards an improvement of the related properties. However, these improvements are not always just alloy composition related. There is also a tremendous potential in the thermomechanical treatment of the material and in the design of the actuator. Significant improvement steps are already possible if the usage of the existent materials is optimized for the projected application and if the actuator system is designed in the most efficient way. This paper provides an overview about existent designs, applications and alloys for use in actuators, as well as examples of new shape memory actuator application with improved performance. It also gives an overview about general design rules and reflects about the strengths of the material and the related opportunities for its application.

A model for ferromagnetic shape memory thin film actuators

NASA Astrophysics Data System (ADS)

Lee, Kwok-Lun; Seelecke, Stefan

2005-05-01

The last decade has witnessed the discovery of materials combining shape memory behavior with ferromagnetic properties (FSMAs), see James & Wuttig1, James et al.2, Ullakko et al.3. These materials feature the so-called giant magnetostrain effect, which, in contrast to conventional magnetostriction is due motion of martensite twins. This effect has motivated the development of a new class of active materials transducers, which combine intrinsic sensing capabilities with superior actuation speed and improved efficiency when compared to conventional shape memory alloys. Currently, thin film technology is being developed intensively in order to pave the way for applications in micro- and nanotechnology. As an example, Kohl et al., recently proposed a novel actuation mechanism based on NiMnGa thin film technology, which makes use of both the ferromagnetic transition and the martensitic transformation allowing the realization of an almost perfect antagonism in a single component part. The implementation of the mechanism led to the award-winning development of an optical microscanner. Possible applications in nanotechnology arise, e.g., by combination of smart NiMnGa actuators with scanning probe technologies. The key aspect of Kohl's device is the fact that it employs electric heating for actuation, which requires a thermo-magneto-mechanical model for analysis. The research presented in this paper aims at the development of a model that simulates this particular material behavior. It is based on ideas originally developed for conventional shape memory alloy behavior, (Mueller & Achenbach, Achenbach, Seelecke, Seelecke & Mueller) and couples it with a simple expression for the nonlinear temperature- and position-dependent effective magnetic force. This early and strongly simplified version does not account for a full coupling between SMA behavior and ferromagnetism yet, and does not incorporate the hysteretic character of the magnetization phenomena either. It can however be used to explain the basic actuation mechanism and highlight the role of coupled magnetic and martensitic transformation with respect to the actuator performance. In particular will we be able to develop guidelines for desirable alloy compositions, such that the resulting transition temperatures guarantee optimized actuator performance.

Computational mechanics analysis tools for parallel-vector supercomputers

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.; Nguyen, Duc T.; Baddourah, Majdi; Qin, Jiangning

1993-01-01

Computational algorithms for structural analysis on parallel-vector supercomputers are reviewed. These parallel algorithms, developed by the authors, are for the assembly of structural equations, 'out-of-core' strategies for linear equation solution, massively distributed-memory equation solution, unsymmetric equation solution, general eigensolution, geometrically nonlinear finite element analysis, design sensitivity analysis for structural dynamics, optimization search analysis and domain decomposition. The source code for many of these algorithms is available.

Optical storage with electromagnetically induced transparency in cold atoms at a high optical depth

NASA Astrophysics Data System (ADS)

Zhang, Shanchao; Zhou, Shuyu; Liu, Chang; Chen, J. F.; Wen, Jianming; Loy, M. M. T.; Wong, G. K. L.; Du, Shengwang

2012-06-01

We report experimental demonstration of efficient optical storage with electromagnetically induced transparency (EIT) in a dense cold ^85Rb atomic ensemble trapped in a two-dimensional magneto-optical trap. By varying the optical depth (OD) from 0 to 140, we observe that the optimal storage efficiency for coherent optical pulses has a saturation value of 50% as OD > 50. Our result is consistent with that obtained from hot vapor cell experiments which suggest that a four-wave mixing nonlinear process degrades the EIT storage coherence and efficiency. We apply this EIT quantum memory for narrow-band single photons with controllable waveforms, and obtain an optimal storage efficiency of 49±3% for single-photon wave packets. This is the highest single-photon storage efficiency reported up to today and brings the EIT atomic quantum memory close to practical application because an efficiency of above 50% is necessary to operate the memory within non-cloning regime and beat the classical limit.

A mixed parallel strategy for the solution of coupled multi-scale problems at finite strains

NASA Astrophysics Data System (ADS)

Lopes, I. A. Rodrigues; Pires, F. M. Andrade; Reis, F. J. P.

2018-02-01

A mixed parallel strategy for the solution of homogenization-based multi-scale constitutive problems undergoing finite strains is proposed. The approach aims to reduce the computational time and memory requirements of non-linear coupled simulations that use finite element discretization at both scales (FE^2). In the first level of the algorithm, a non-conforming domain decomposition technique, based on the FETI method combined with a mortar discretization at the interface of macroscopic subdomains, is employed. A master-slave scheme, which distributes tasks by macroscopic element and adopts dynamic scheduling, is then used for each macroscopic subdomain composing the second level of the algorithm. This strategy allows the parallelization of FE^2 simulations in computers with either shared memory or distributed memory architectures. The proposed strategy preserves the quadratic rates of asymptotic convergence that characterize the Newton-Raphson scheme. Several examples are presented to demonstrate the robustness and efficiency of the proposed parallel strategy.

Long Memory in STOCK Market Volatility: the International Evidence

NASA Astrophysics Data System (ADS)

Yang, Chunxia; Hu, Sen; Xia, Bingying; Wang, Rui

2012-08-01

It is still a hot topic to catch the auto-dependence behavior of volatility. Here, based on the measurement of average volatility, under different observation window size, we investigated the dependence of successive volatility of several main stock indices and their simulated GARCH(1, 1) model, there were obvious linear auto-dependence in the logarithm of volatility under a small observation window size and nonlinear auto-dependence under a big observation. After calculating the correlation and mutual information of the logarithm of volatility for Dow Jones Industrial Average during different periods, we find that some influential events can change the correlation structure and the volatilities of different periods have distinct influence on that of the remote future. Besides, GARCH model could produce similar behavior of dependence as real data and long memory property. But our analyses show that the auto-dependence of volatility in GARCH is different from that in real data, and the long memory is undervalued by GARCH.

Speech research: Studies on the nature of speech, instrumentation for its investigation, and practical applications

NASA Astrophysics Data System (ADS)

Liberman, A. M.

1982-03-01

This report is one of a regular series on the status and progress of studies on the nature of speech, instrumentation for its investigation and practical applications. Manuscripts cover the following topics: Speech perception and memory coding in relation to reading ability; The use of orthographic structure by deaf adults: Recognition of finger-spelled letters; Exploring the information support for speech; The stream of speech; Using the acoustic signal to make inferences about place and duration of tongue-palate contact. Patterns of human interlimb coordination emerge from the the properties of nonlinear limit cycle oscillatory processes: Theory and data; Motor control: Which themes do we orchestrate? Exploring the nature of motor control in Down's syndrome; Periodicity and auditory memory: A pilot study; Reading skill and language skill: On the role of sign order and morphological structure in memory for American Sign Language sentences; Perception of nasal consonants with special reference to Catalan; and Speech production Characteristics of the hearing impaired.

Micromechanics of composites with shape memory alloy fibers in uniform thermal fields

NASA Technical Reports Server (NTRS)

Birman, Victor; Saravanos, Dimitris A.; Hopkins, Dale A.

1995-01-01

Analytical procedures are developed for a composite system consisting of shape memory alloy fibers within an elastic matrix subject to uniform temperature fluctuations. Micromechanics for the calculation of the equivalent properties of the composite are presented by extending the multi-cell model to incorporate shape memory alloy fibers. A three phase concentric cylinder model is developed for the analysis of local stresses which includes the fiber, the matrix, and the surrounding homogenized composite. The solution addresses the complexities induced by the nonlinear dependence of the in-situ martensite fraction of the fibers to the local stresses and temperature, and the local stresses developed from interactions between the fibers and matrix during the martensitic and reverse phase transformations. Results are presented for a nitinol/epoxy composite. The applications illustrate the response of the composite in isothermal longitudinal loading and unloading, and in temperature induced actuation. The local stresses developed in the composite under various stages of the martensitic and reverse phase transformation are also shown.

Science-Grade Observing Systems as Process Observatories: Mapping and Understanding Nonlinearity and Multiscale Memory with Models and Observations

NASA Astrophysics Data System (ADS)

Barros, A. P.; Wilson, A. M.; Miller, D. K.; Tao, J.; Genereux, D. P.; Prat, O.; Petersen, W. A.; Brunsell, N. A.; Petters, M. D.; Duan, Y.

2015-12-01

Using the planet as a study domain and collecting observations over unprecedented ranges of spatial and temporal scales, NASA's EOS (Earth Observing System) program was an agent of transformational change in Earth Sciences over the last thirty years. The remarkable space-time organization and variability of atmospheric and terrestrial moist processes that emerged from the analysis of comprehensive satellite observations provided much impetus to expand the scope of land-atmosphere interaction studies in Hydrology and Hydrometeorology. Consequently, input and output terms in the mass and energy balance equations evolved from being treated as fluxes that can be used as boundary conditions, or forcing, to being viewed as dynamic processes of a coupled system interacting at multiple scales. Measurements of states or fluxes are most useful if together they map, reveal and/or constrain the underlying physical processes and their interactions. This can only be accomplished through an integrated observing system designed to capture the coupled physics, including nonlinear feedbacks and tipping points. Here, we first review and synthesize lessons learned from hydrometeorology studies in the Southern Appalachians and in the Southern Great Plains using both ground-based and satellite observations, physical models and data-assimilation systems. We will specifically focus on mapping and understanding nonlinearity and multiscale memory of rainfall-runoff processes in mountainous regions. It will be shown that beyond technical rigor, variety, quantity and duration of measurements, the utility of observing systems is determined by their interpretive value in the context of physical models to describe the linkages among different observations. Second, we propose a framework for designing science-grade and science-minded process-oriented integrated observing and modeling platforms for hydrometeorological studies.

Interpreting the g loadings of intelligence test composite scores in light of Spearman's law of diminishing returns.

PubMed

Reynolds, Matthew R

2013-03-01

The linear loadings of intelligence test composite scores on a general factor (g) have been investigated recently in factor analytic studies. Spearman's law of diminishing returns (SLODR), however, implies that the g loadings of test scores likely decrease in magnitude as g increases, or they are nonlinear. The purpose of this study was to (a) investigate whether the g loadings of composite scores from the Differential Ability Scales (2nd ed.) (DAS-II, C. D. Elliott, 2007a, Differential Ability Scales (2nd ed.). San Antonio, TX: Pearson) were nonlinear and (b) if they were nonlinear, to compare them with linear g loadings to demonstrate how SLODR alters the interpretation of these loadings. Linear and nonlinear confirmatory factor analysis (CFA) models were used to model Nonverbal Reasoning, Verbal Ability, Visual Spatial Ability, Working Memory, and Processing Speed composite scores in four age groups (5-6, 7-8, 9-13, and 14-17) from the DAS-II norming sample. The nonlinear CFA models provided better fit to the data than did the linear models. In support of SLODR, estimates obtained from the nonlinear CFAs indicated that g loadings decreased as g level increased. The nonlinear portion for the nonverbal reasoning loading, however, was not statistically significant across the age groups. Knowledge of general ability level informs composite score interpretation because g is less likely to produce differences, or is measured less, in those scores at higher g levels. One implication is that it may be more important to examine the pattern of specific abilities at higher general ability levels. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Membrane wrinkling patterns and control with SMA and SMPC actuators

NASA Astrophysics Data System (ADS)

Lu, Mingyu; Li, Yunliang; Tan, Huifeng; Zhou, Limin

2009-07-01

Wrinkling is a main factor affecting the performance of the membrane structures and is always considered to be a failure as it can cause dramatic decrease of shape accuracy. The study of membrane wrinkling control has the analytical and experimental meanings. In this paper, a feasible membrane shape control method is presented. An expression of wrinkle wavelength using stress extremum principle is established based on the tension field theory and the Von Karman large deflection formula which verifies the generation and evolution reason of membrane wrinkles. The control mechanism for membrane wrinkles is developed using shape memory alloy (SMA) and shape memory polymer composite (SMPC) actuators which are attached to the boundaries of the membrane for producing contraction/expansion forces to adjust the shape of the membrane. The whole control process is monitored by photogrammetric technique. Numerical simulations are also conducted using ANSYS finite element software with the nonlinear post-buckling analytical method. Both the experimental and numerical results show that the amplitudes of wrinkles are effectively controlled by SMA and SMPC actuators. The method introduced in this paper provides the foundation for shape control of the membrane wrinkling and is important to the future work on vibration control of space membrane structures.

Shape memory alloy resistance behaviour at high altitude for feedback control

NASA Astrophysics Data System (ADS)

Ng, W. T.; Sedan, M. F.; Abdullah, E. J.; Azrad, S.; Harithuddin, A. S. M.

2017-12-01

Many recent aerospace technologies are using smart actuators to reduce the system's complexity and increase its reliability. One such actuator is shape memory alloy (SMA) actuator, which is lightweight, produces high force and large deflection. However, some disadvantages in using SMA actuators have been identified and they include nonlinear response of the strain to input current, hysteresis characteristic that results in inaccurate control and less than optimum system performance, high operating temperatures, slow response and also high requirement of electrical power to obtain the desired actuation forces. It is still unknown if the SMA actuators can perform effectively at high altitude with low surrounding temperature. The work presented here covers the preliminary process of verifying the feasibility of using resistance as feedback control at high altitude for aerospace applications. Temperature and resistance of SMA actuator at high altitude is investigated by conducting an experiment onboard a high altitude balloon. The results from the high altitude experiment indicate that the resistance or voltage drop of the SMA wire is not significantly affected by the low surrounding temperature at high altitude as compared to the temperature of SMA. Resistance feedback control for SMA actuators may be suitable for aerospace applications.

A numerical scheme for nonlinear Helmholtz equations with strong nonlinear optical effects.

PubMed

Xu, Zhengfu; Bao, Gang

2010-11-01

A numerical scheme is presented to solve the nonlinear Helmholtz (NLH) equation modeling second-harmonic generation (SHG) in photonic bandgap material doped with a nonlinear χ((2)) effect and the NLH equation modeling wave propagation in Kerr type gratings with a nonlinear χ((3)) effect in the one-dimensional case. Both of these nonlinear phenomena arise as a result of the combination of high electromagnetic mode density and nonlinear reaction from the medium. When the mode intensity of the incident wave is significantly strong, which makes the nonlinear effect non-negligible, numerical methods based on the linearization of the essentially nonlinear problem will become inadequate. In this work, a robust, stable numerical scheme is designed to simulate the NLH equations with strong nonlinearity.

Nonlinear correlations impair quantification of episodic memory by mesial temporal BOLD activity.

PubMed

Klamer, Silke; Zeltner, Lena; Erb, Michael; Klose, Uwe; Wagner, Kathrin; Frings, Lars; Groen, Georg; Veil, Cornelia; Rona, Sabine; Lerche, Holger; Milian, Monika

2013-07-01

Episodic memory processes can be investigated using different functional MRI (fMRI) paradigms. The purpose of the present study was to examine correlations between neuropsychological memory test scores and BOLD signal changes during fMRI scanning using three different memory tasks. Twenty-eight right-handed healthy subjects underwent three paradigms, (a) a word pair, (b) a space-labyrinth, and (c) a face-name association paradigm. These paradigms were compared for their value in memory quantification and lateralization by calculating correlations between the BOLD signals in the mesial temporal lobe and behavioral data derived from a neuropsychological test battery. As expected, group analysis showed left-sided activation for the verbal, a tendency to right-sided activation for the spatial, and bilateral activation for the face-name paradigm. No linear correlations were observed between neuropsychological data and activation in the temporo-mesial region. However, we found significant u-shaped correlations between behavioral memory performance and activation in both the verbal and the face-name paradigms, that is, BOLD signal changes were greater not only among participants who performed best on the neuropsychological tests, but also among the poorest performers. The figural learning task did not correlate with the activations in the space-labyrinth paradigm at all. We interpreted the u-shaped correlations to be due to compensatory hippocampal activations associated with low performance when people try unsuccessfully to remember presented items. Because activation levels did not linearly increase with memory performance, the latter cannot be quantified by fMRI alone, but only be used in conjunction with neuropsychological testing. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Alterations in memory networks in mild cognitive impairment and Alzheimer's disease: an independent component analysis.

PubMed

Celone, Kim A; Calhoun, Vince D; Dickerson, Bradford C; Atri, Alireza; Chua, Elizabeth F; Miller, Saul L; DePeau, Kristina; Rentz, Doreen M; Selkoe, Dennis J; Blacker, Deborah; Albert, Marilyn S; Sperling, Reisa A

2006-10-04

Memory function is likely subserved by multiple distributed neural networks, which are disrupted by the pathophysiological process of Alzheimer's disease (AD). In this study, we used multivariate analytic techniques to investigate memory-related functional magnetic resonance imaging (fMRI) activity in 52 individuals across the continuum of normal aging, mild cognitive impairment (MCI), and mild AD. Independent component analyses revealed specific memory-related networks that activated or deactivated during an associative memory paradigm. Across all subjects, hippocampal activation and parietal deactivation demonstrated a strong reciprocal relationship. Furthermore, we found evidence of a nonlinear trajectory of fMRI activation across the continuum of impairment. Less impaired MCI subjects showed paradoxical hyperactivation in the hippocampus compared with controls, whereas more impaired MCI subjects demonstrated significant hypoactivation, similar to the levels observed in the mild AD subjects. We found a remarkably parallel curve in the pattern of memory-related deactivation in medial and lateral parietal regions with greater deactivation in less-impaired MCI and loss of deactivation in more impaired MCI and mild AD subjects. Interestingly, the failure of deactivation in these regions was also associated with increased positive activity in a neocortical attentional network in MCI and AD. Our findings suggest that loss of functional integrity of the hippocampal-based memory systems is directly related to alterations of neural activity in parietal regions seen over the course of MCI and AD. These data may also provide functional evidence of the interaction between neocortical and medial temporal lobe pathology in early AD.

Triple shape memory polymers by 4D printing

NASA Astrophysics Data System (ADS)

Bodaghi, M.; Damanpack, A. R.; Liao, W. H.

2018-06-01

This article aims at introducing triple shape memory polymers (SMPs) by four-dimensional (4D) printing technology and shaping adaptive structures for mechanical/bio-medical devices. The main approach is based on arranging hot–cold programming of SMPs with fused decomposition modeling technology to engineer adaptive structures with triple shape memory effect (SME). Experiments are conducted to characterize elasto-plastic and hyper-elastic thermo-mechanical material properties of SMPs in low and high temperatures at large deformation regime. The feasibility of the dual and triple SMPs with self-bending features is demonstrated experimentally. It is advantageous in situations either where it is desired to perform mechanical manipulations on the 4D printed objects for specific purposes or when they experience cold programming inevitably before activation. A phenomenological 3D constitutive model is developed for quantitative understanding of dual/triple SME of SMPs fabricated by 4D printing in the large deformation range. Governing equations of equilibrium are established for adaptive structures on the basis of the nonlinear Green–Lagrange strains. They are then solved by developing a finite element approach along with an elastic-predictor plastic-corrector return map procedure accomplished by the Newton–Raphson method. The computational tool is applied to simulate dual/triple SMP structures enabled by 4D printing and explore hot–cold programming mechanisms behind material tailoring. It is shown that the 4D printed dual/triple SMPs have great potential in mechanical/bio-medical applications such as self-bending gripers/stents and self-shrinking/tightening staples.

Neuropsychological basic deficits in preschoolers at risk for ADHD: a meta-analysis.

PubMed

Pauli-Pott, Ursula; Becker, Katja

2011-06-01

Widely accepted neuropsychological theories on attention deficit hyperactivity disorder (ADHD) assume that the complex symptoms of the disease arise from developmentally preceding neuropsychological basic deficits. These deficits in executive functions and delay aversion are presumed to emerge in the preschool period. The corresponding normative developmental processes include phases of relative stability and rapid change. These non-linear developmental processes might have implications for concurrent and predictive associations between basic deficits and ADHD symptoms. To derive a description of the nature and strength of these associations, a meta-analysis was conducted. It is assumed that weighted mean effect sizes differ between basic deficits and depend on age. The meta-analysis included 25 articles (n=3005 children) in which associations between assessments of basic deficits (i.e. response inhibition, interference control, delay aversion, working memory, flexibility, and vigilance/arousal) in the preschool period and concurrent or subsequent ADHD symptoms or diagnosis of ADHD had been analyzed. For response inhibition and delay aversion, mean effect sizes were of medium to large magnitude while the mean effect size for working memory was small. Meta-regression analyses revealed that effect sizes of delay aversion tasks significantly decreased with increasing age while effect sizes of interference control tasks and Continuous Performance Tests (CPTs) significantly increased. Depending on the normative maturational course of each skill, time windows might exist that allow for a more or less valid assessment of a specific deficit. In future research these time windows might help to describe early developing forms of ADHD and to identify children at risk. Copyright © 2011 Elsevier Ltd. All rights reserved.

Quantifying the Number of Discriminable Coincident Dendritic Input Patterns through Dendritic Tree Morphology

PubMed Central

Zippo, Antonio G.; Biella, Gabriele E. M.

2015-01-01

Current developments in neuronal physiology are unveiling novel roles for dendrites. Experiments have shown mechanisms of non-linear synaptic NMDA dependent activations, able to discriminate input patterns through the waveforms of the excitatory postsynaptic potentials. Contextually, the synaptic clustering of inputs is the principal cellular strategy to separate groups of common correlated inputs. Dendritic branches appear to work as independent discriminating units of inputs potentially reflecting an extraordinary repertoire of pattern memories. However, it is unclear how these observations could impact our comprehension of the structural correlates of memory at the cellular level. This work investigates the discrimination capabilities of neurons through computational biophysical models to extract a predicting law for the dendritic input discrimination capability (M). By this rule we compared neurons from a neuron reconstruction repository (neuromorpho.org). Comparisons showed that primate neurons were not supported by an equivalent M preeminence and that M is not uniformly distributed among neuron types. Remarkably, neocortical neurons had substantially less memory capacity in comparison to those from non-cortical regions. In conclusion, the proposed rule predicts the inherent neuronal spatial memory gathering potentially relevant anatomical and evolutionary considerations about the brain cytoarchitecture. PMID:26100354

How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks

PubMed Central

Rombouts, Jaldert O.; Bohte, Sander M.; Roelfsema, Pieter R.

2015-01-01

Intelligence is our ability to learn appropriate responses to new stimuli and situations. Neurons in association cortex are thought to be essential for this ability. During learning these neurons become tuned to relevant features and start to represent them with persistent activity during memory delays. This learning process is not well understood. Here we develop a biologically plausible learning scheme that explains how trial-and-error learning induces neuronal selectivity and working memory representations for task-relevant information. We propose that the response selection stage sends attentional feedback signals to earlier processing levels, forming synaptic tags at those connections responsible for the stimulus-response mapping. Globally released neuromodulators then interact with tagged synapses to determine their plasticity. The resulting learning rule endows neural networks with the capacity to create new working memory representations of task relevant information as persistent activity. It is remarkably generic: it explains how association neurons learn to store task-relevant information for linear as well as non-linear stimulus-response mappings, how they become tuned to category boundaries or analog variables, depending on the task demands, and how they learn to integrate probabilistic evidence for perceptual decisions. PMID:25742003

Nonlinear Analysis in Counseling Research

ERIC Educational Resources Information Center

Balkin, Richard S.; Richey Gosnell, Katelyn M.; Holmgren, Andrew; Osborne, Jason W.

2017-01-01

Nonlinear effects are both underreported and underrepresented in counseling research. We provide a rationale for evaluating nonlinear effects and steps to evaluate nonlinear relationships in counseling research. Two heuristic examples are provided along with discussion of the results and advantages to evaluating nonlinear effects.

Memcapacitor model and its application in chaotic oscillator with memristor.

PubMed

Wang, Guangyi; Zang, Shouchi; Wang, Xiaoyuan; Yuan, Fang; Iu, Herbert Ho-Ching

2017-01-01

Memristors and memcapacitors are two new nonlinear elements with memory. In this paper, we present a Hewlett-Packard memristor model and a charge-controlled memcapacitor model and design a new chaotic oscillator based on the two models for exploring the characteristics of memristors and memcapacitors in nonlinear circuits. Furthermore, many basic dynamical behaviors of the oscillator, including equilibrium sets, Lyapunov exponent spectrums, and bifurcations with various circuit parameters, are investigated theoretically and numerically. Our analysis results show that the proposed oscillator possesses complex dynamics such as an infinite number of equilibria, coexistence oscillation, and multi-stability. Finally, a discrete model of the chaotic oscillator is given and the main statistical properties of this oscillator are verified via Digital Signal Processing chip experiments and National Institute of Standards and Technology tests.

Parametric reduced models for the nonlinear Schrödinger equation

NASA Astrophysics Data System (ADS)

Harlim, John; Li, Xiantao

2015-05-01

Reduced models for the (defocusing) nonlinear Schrödinger equation are developed. In particular, we develop reduced models that only involve the low-frequency modes given noisy observations of these modes. The ansatz of the reduced parametric models are obtained by employing a rational approximation and a colored-noise approximation, respectively, on the memory terms and the random noise of a generalized Langevin equation that is derived from the standard Mori-Zwanzig formalism. The parameters in the resulting reduced models are inferred from noisy observations with a recently developed ensemble Kalman filter-based parametrization method. The forecasting skill across different temperature regimes are verified by comparing the moments up to order four, a two-time correlation function statistics, and marginal densities of the coarse-grained variables.

Parametric reduced models for the nonlinear Schrödinger equation.

PubMed

Harlim, John; Li, Xiantao

2015-05-01

Reduced models for the (defocusing) nonlinear Schrödinger equation are developed. In particular, we develop reduced models that only involve the low-frequency modes given noisy observations of these modes. The ansatz of the reduced parametric models are obtained by employing a rational approximation and a colored-noise approximation, respectively, on the memory terms and the random noise of a generalized Langevin equation that is derived from the standard Mori-Zwanzig formalism. The parameters in the resulting reduced models are inferred from noisy observations with a recently developed ensemble Kalman filter-based parametrization method. The forecasting skill across different temperature regimes are verified by comparing the moments up to order four, a two-time correlation function statistics, and marginal densities of the coarse-grained variables.

Coding of cognitive magnitude: compressed scaling of numerical information in the primate prefrontal cortex.

PubMed

Nieder, Andreas; Miller, Earl K

2003-01-09

Whether cognitive representations are better conceived as language-based, symbolic representations or perceptually related, analog representations is a subject of debate. If cognitive processes parallel perceptual processes, then fundamental psychophysical laws should hold for each. To test this, we analyzed both behavioral and neuronal representations of numerosity in the prefrontal cortex of rhesus monkeys. The data were best described by a nonlinearly compressed scaling of numerical information, as postulated by the Weber-Fechner law or Stevens' law for psychophysical/sensory magnitudes. This nonlinear compression was observed on the neural level during the acquisition phase of the task and maintained through the memory phase with no further compression. These results suggest that certain cognitive and perceptual/sensory representations share the same fundamental mechanisms and neural coding schemes.

Adaptive Nonlinear RF Cancellation for Improved Isolation in Simultaneous Transmit–Receive Systems

NASA Astrophysics Data System (ADS)

Kiayani, Adnan; Waheed, Muhammad Zeeshan; Anttila, Lauri; Abdelaziz, Mahmoud; Korpi, Dani; Syrjala, Ville; Kosunen, Marko; Stadius, Kari; Ryynanen, Jussi; Valkama, Mikko

2018-05-01

This paper proposes an active radio frequency (RF) cancellation solution to suppress the transmitter (TX) passband leakage signal in radio transceivers supporting simultaneous transmission and reception. The proposed technique is based on creating an opposite-phase baseband equivalent replica of the TX leakage signal in the transceiver digital front-end through adaptive nonlinear filtering of the known transmit data, to facilitate highly accurate cancellation under a nonlinear TX power amplifier (PA). The active RF cancellation is then accomplished by employing an auxiliary transmitter chain, to generate the actual RF cancellation signal, and combining it with the received signal at the receiver (RX) low noise amplifier (LNA) input. A closed-loop parameter learning approach, based on the decorrelation principle, is also developed to efficiently estimate the coefficients of the nonlinear cancellation filter in the presence of a nonlinear TX PA with memory, finite passive isolation, and a nonlinear RX LNA. The performance of the proposed cancellation technique is evaluated through comprehensive RF measurements adopting commercial LTE-Advanced transceiver hardware components. The results show that the proposed technique can provide an additional suppression of up to 54 dB for the TX passband leakage signal at the RX LNA input, even at considerably high transmit power levels and with wide transmission bandwidths. Such novel cancellation solution can therefore substantially improve the TX-RX isolation, hence reducing the requirements on passive isolation and RF component linearity, as well as increasing the efficiency and flexibility of the RF spectrum use in the emerging 5G radio networks.

Buckling analysis of SMA bonded sandwich structure – using FEM

NASA Astrophysics Data System (ADS)

Katariya, Pankaj V.; Das, Arijit; Panda, Subrata K.

2018-03-01

Thermal buckling strength of smart sandwich composite structure (bonded with shape memory alloy; SMA) examined numerically via a higher-order finite element model in association with marching technique. The excess geometrical distortion of the structure under the elevated environment modeled through Green’s strain function whereas the material nonlinearity counted with the help of marching method. The system responses are computed numerically by solving the generalized eigenvalue equations via a customized MATLAB code. The comprehensive behaviour of the current finite element solutions (minimum buckling load parameter) is established by solving the adequate number of numerical examples including the given input parameter. The current numerical model is extended further to check the influence of various structural parameter of the sandwich panel on the buckling temperature including the SMA effect and reported in details.

A MULTICORE BASED PARALLEL IMAGE REGISTRATION METHOD

PubMed Central

Yang, Lin; Gong, Leiguang; Zhang, Hong; Nosher, John L.; Foran, David J.

2012-01-01

Image registration is a crucial step for many image-assisted clinical applications such as surgery planning and treatment evaluation. In this paper we proposed a landmark based nonlinear image registration algorithm for matching 2D image pairs. The algorithm was shown to be effective and robust under conditions of large deformations. In landmark based registration, the most important step is establishing the correspondence among the selected landmark points. This usually requires an extensive search which is often computationally expensive. We introduced a nonregular data partition algorithm using the K-means clustering algorithm to group the landmarks based on the number of available processing cores. The step optimizes the memory usage and data transfer. We have tested our method using IBM Cell Broadband Engine (Cell/B.E.) platform. PMID:19964921

Optical computing and neural networks; Proceedings of the Meeting, National Chiao Tung Univ., Hsinchu, Taiwan, Dec. 16, 17, 1992

NASA Technical Reports Server (NTRS)

Hsu, Ken-Yuh (Editor); Liu, Hua-Kuang (Editor)

1992-01-01

The present conference discusses optical neural networks, photorefractive nonlinear optics, optical pattern recognition, digital and analog processors, and holography and its applications. Attention is given to bifurcating optical information processing, neural structures in digital halftoning, an exemplar-based optical neural net classifier for color pattern recognition, volume storage in photorefractive disks, and microlaser-based compact optical neuroprocessors. Also treated are the optical implementation of a feature-enhanced optical interpattern-associative neural network model and its optical implementation, an optical pattern binary dual-rail logic gate module, a theoretical analysis for holographic associative memories, joint transform correlators, image addition and subtraction via the Talbot effect, and optical wavelet-matched filters. (No individual items are abstracted in this volume)

Optical computing and neural networks; Proceedings of the Meeting, National Chiao Tung Univ., Hsinchu, Taiwan, Dec. 16, 17, 1992

NASA Astrophysics Data System (ADS)

Hsu, Ken-Yuh; Liu, Hua-Kuang

The present conference discusses optical neural networks, photorefractive nonlinear optics, optical pattern recognition, digital and analog processors, and holography and its applications. Attention is given to bifurcating optical information processing, neural structures in digital halftoning, an exemplar-based optical neural net classifier for color pattern recognition, volume storage in photorefractive disks, and microlaser-based compact optical neuroprocessors. Also treated are the optical implementation of a feature-enhanced optical interpattern-associative neural network model and its optical implementation, an optical pattern binary dual-rail logic gate module, a theoretical analysis for holographic associative memories, joint transform correlators, image addition and subtraction via the Talbot effect, and optical wavelet-matched filters. (No individual items are abstracted in this volume)

Computational mechanics analysis tools for parallel-vector supercomputers

NASA Technical Reports Server (NTRS)

Storaasli, O. O.; Nguyen, D. T.; Baddourah, M. A.; Qin, J.

1993-01-01

Computational algorithms for structural analysis on parallel-vector supercomputers are reviewed. These parallel algorithms, developed by the authors, are for the assembly of structural equations, 'out-of-core' strategies for linear equation solution, massively distributed-memory equation solution, unsymmetric equation solution, general eigen-solution, geometrically nonlinear finite element analysis, design sensitivity analysis for structural dynamics, optimization algorithm and domain decomposition. The source code for many of these algorithms is available from NASA Langley.

Dynamical Systems Approach to Endothelial Heterogeneity

PubMed Central

Regan, Erzsébet Ravasz; Aird, William C.

2012-01-01

Rationale Objective Here we reexamine our current understanding of the molecular basis of endothelial heterogeneity. We introduce multistability as a new explanatory framework in vascular biology. Methods We draw on the field of non-linear dynamics to propose a dynamical systems framework for modeling multistability and its derivative properties, including robustness, memory, and plasticity. Conclusions Our perspective allows for both a conceptual and quantitative description of system-level features of endothelial regulation. PMID:22723222

Associative Memory In A Phase Conjugate Resonator Cavity Utilizing A Hologram

NASA Astrophysics Data System (ADS)

Owechko, Y.; Marom, E.; Soffer, B. H.; Dunning, G.

1987-01-01

The principle of information retrieval by association has been suggested as a basis for parallel computing and as the process by which human memory functions.1 Various associative processors have been proposed that use electronic or optical means. Optical schemes,2-7 in particular, those based on holographic principles,3,6,7 are well suited to associative processing because of their high parallelism and information throughput. Previous workers8 demonstrated that holographically stored images can be recalled by using relatively complicated reference images but did not utilize nonlinear feedback to reduce the large cross talk that results when multiple objects are stored and a partial or distorted input is used for retrieval. These earlier approaches were limited in their ability to reconstruct the output object faithfully from a partial input.

Non-binary LDPC-coded modulation for high-speed optical metro networks with backpropagation

NASA Astrophysics Data System (ADS)

Arabaci, Murat; Djordjevic, Ivan B.; Saunders, Ross; Marcoccia, Roberto M.

2010-01-01

To simultaneously mitigate the linear and nonlinear channel impairments in high-speed optical communications, we propose the use of non-binary low-density-parity-check-coded modulation in combination with a coarse backpropagation method. By employing backpropagation, we reduce the memory in the channel and in return obtain significant reductions in the complexity of the channel equalizer which is exponentially proportional to the channel memory. We then compensate for the remaining channel distortions using forward error correction based on non-binary LDPC codes. We propose non-binary-LDPC-coded modulation scheme because, compared to bit-interleaved binary-LDPC-coded modulation scheme employing turbo equalization, the proposed scheme lowers the computational complexity and latency of the overall system while providing impressively larger coding gains.

How long is the memory of the US stock market?

NASA Astrophysics Data System (ADS)

Ferreira, Paulo; Dionísio, Andreia

2016-06-01

The Efficient Market Hypothesis (EMH), one of the most important hypothesis in financial economics, argues that return rates have no memory (correlation) which implies that agents cannot make abnormal profits in financial markets, due to the possibility of arbitrage operations. With return rates for the US stock market, we corroborate the fact that with a linear approach, return rates do not show evidence of correlation. However, linear approaches might not be complete or global, since return rates could suffer from nonlinearities. Using detrended cross-correlation analysis and its correlation coefficient, a methodology which analyzes long-range behavior between series, we show that the long-range correlation of return rates only ends in the 149th lag, which corresponds to about seven months. Does this result undermine the EMH?

The influence of the uplink noise on the performance of satellite data transmission systems

NASA Astrophysics Data System (ADS)

Dewal, Vrinda P.

The problem of transmission of binary phase shift keying (BPSK) modulated digital data through a bandlimited nonlinear satellite channel in the presence of uplink, downlink Gaussian noise and intersymbol interface is examined. The satellite transponder is represented by a zero memory bandpass nonlinearity, with AM/AM conversion. The proposed optimum linear receiver structure consists of tapped-delay lines followed by a decision device. The linear receiver is designed to minimize the mean square error that is a function of the intersymbol interface, the uplink and the downlink noise. The minimum mean square error equalizer (MMSE) is derived using the Wiener-Kolmogorov theory. In this receiver, the decision about the transmitted signal is made by taking into account the received sequence of present sample, and the interfering past and future samples, which represent the intersymbol interference (ISI). Illustrative examples of the receiver structures are considered for the nonlinear channels with a symmetrical and asymmetrical frequency responses of the transmitter filter. The transponder nonlinearity is simulated by a polynomial using only the first and the third orders terms. A computer simulation determines the tap gain coefficients of the MMSE equalizer that adapt to the various uplink and downlink noise levels. The performance of the MMSE equalizer is evaluated in terms of an estimate of the average probability of error.

Improvement of Nonlinearity Correction for BESIII ETOF Upgrade

NASA Astrophysics Data System (ADS)

Sun, Weijia; Cao, Ping; Ji, Xiaolu; Fan, Huanhuan; Dai, Hongliang; Zhang, Jie; Liu, Shubin; An, Qi

2015-08-01

An improved scheme to implement integral non-linearity (INL) correction of time measurements in the Beijing Spectrometer III Endcap Time-of-Flight (BESIII ETOF) upgrade system is presented in this paper. During upgrade, multi-gap resistive plate chambers (MRPC) are introduced as ETOF detectors which increases the total number of time measurement channels to 1728. The INL correction method adopted in BESIII TOF proved to be of limited use, because the sharply increased number of electronic channels required for reading out the detector strips degrade the system configuration efficiency severely. Furthermore, once installed into the spectrometer, BESIII TOF electronics do not support the TDCs' nonlinearity evaluation online. In this proposed method, INL data used for the correction algorithm are automatically imported from a non-volatile read-only memory (ROM) instead of from data acquisition software. This guarantees the real-time performance and system efficiency of the INL correction, especially for the ETOF upgrades with massive number of channels. Besides, a signal that is not synchronized to the system 41.65 MHz clock from BEPCII is sent to the frontend electronics (FEE) to simulate pseudo-random test pulses for the purpose of online nonlinearity evaluation. Test results show that the time measuring INL errors in one module with 72 channels can be corrected online and in real time.

MARE2DEM: a 2-D inversion code for controlled-source electromagnetic and magnetotelluric data

NASA Astrophysics Data System (ADS)

Key, Kerry

2016-10-01

This work presents MARE2DEM, a freely available code for 2-D anisotropic inversion of magnetotelluric (MT) data and frequency-domain controlled-source electromagnetic (CSEM) data from onshore and offshore surveys. MARE2DEM parametrizes the inverse model using a grid of arbitrarily shaped polygons, where unstructured triangular or quadrilateral grids are typically used due to their ease of construction. Unstructured grids provide significantly more geometric flexibility and parameter efficiency than the structured rectangular grids commonly used by most other inversion codes. Transmitter and receiver components located on topographic slopes can be tilted parallel to the boundary so that the simulated electromagnetic fields accurately reproduce the real survey geometry. The forward solution is implemented with a goal-oriented adaptive finite-element method that automatically generates and refines unstructured triangular element grids that conform to the inversion parameter grid, ensuring accurate responses as the model conductivity changes. This dual-grid approach is significantly more efficient than the conventional use of a single grid for both the forward and inverse meshes since the more detailed finite-element meshes required for accurate responses do not increase the memory requirements of the inverse problem. Forward solutions are computed in parallel with a highly efficient scaling by partitioning the data into smaller independent modeling tasks consisting of subsets of the input frequencies, transmitters and receivers. Non-linear inversion is carried out with a new Occam inversion approach that requires fewer forward calls. Dense matrix operations are optimized for memory and parallel scalability using the ScaLAPACK parallel library. Free parameters can be bounded using a new non-linear transformation that leaves the transformed parameters nearly the same as the original parameters within the bounds, thereby reducing non-linear smoothing effects. Data balancing normalization weights for the joint inversion of two or more data sets encourages the inversion to fit each data type equally well. A synthetic joint inversion of marine CSEM and MT data illustrates the algorithm's performance and parallel scaling on up to 480 processing cores. CSEM inversion of data from the Middle America Trench offshore Nicaragua demonstrates a real world application. The source code and MATLAB interface tools are freely available at http://mare2dem.ucsd.edu.

Quasi-dynamic Earthquake Cycle Simulation in a Viscoelastic Medium with Memory Variables

NASA Astrophysics Data System (ADS)

Hirahara, K.; Ohtani, M.; Shikakura, Y.

2011-12-01

Earthquake cycle simulations based on rate and state friction laws have successfully reproduced the observed complex earthquake cycles at subduction zones. Most of simulations have assumed elastic media. The lower crust and the upper mantle have, however, viscoelastic properties, which cause postseismic stress relaxation. Hence the slip evolution on the plate interfaces or the faults in long earthquake cycles is different from that in elastic media. Especially, the viscoelasticity plays an important role in the interactive occurrence of inland and great interplate earthquakes. In viscoelastic media, the stress is usually calculated by the temporal convolution of the slip response function matrix and the slip deficit rate vector, which needs the past history of slip rates at all cells. Even if properly truncating the convolution, it requires huge computations. This is why few simulation studies have considered viscoelastic media so far. In this study, we examine the method using memory variables or anelastic functions, which has been developed for the time-domain finite-difference calculation of seismic waves in a dissipative medium (e.g., Emmerich and Korn,1987; Moczo and Kristek, 2005). The procedure for stress calculation with memory variables is as follows. First, we approximate the time-domain slip response function calculated in a viscoelastic medium with a series of relaxation functions with coefficients and relaxation times derived from a generalized Maxell body model. Then we can define the time-domain material-independent memory variable or anelastic function for each relaxation mechanism. Each time-domain memory variable satisfies the first-order differential equation. As a result, we can calculate the stress simply by the product of the unrelaxed modulus and the slip deficit subtracted from the sum of memory variables without temporal convolution. With respect to computational cost, we can summarize as in the followings. Dividing the plate interface into N cells, in elastic media, the stress at all cells is calculated by the product of the slip response function matrix and the slip deficit vector. The computational cost is O(N**2). With H-matrices method, we can reduce this to O(N)-O(NlogN) (Ohtani et al. 2011). The memory size is also reduced from O(N**2) to O(N). In viscoelastic media, the product of the unrelaxed modulus matrix and the vector of the slip deficit subtracted from the sum of memory variables costs O(N) with H-matrices method, which is the same as in elastic ones. If we use m relaxation functions, m x N differential equations are additionally solved at a time. The increase in memory size is (4m+1) x N**2. For approximation of slip response function, we need to estimate coefficients and relaxation times for m relaxation functions non-linearly with constraints. Because it is difficult to execute the non-linear least square estimation with constraints, we consider only m=2 with satisfying constraints. Test calculations in a layered or 3-D heterogeneous viscoelastic structure show this gives the satisfactory approximation. As an example, we report a 2-D earthquake cycle simulation for the 2011 giant Tohoku earthquake in a layered viscoelastic medium.

AQUASOL: An efficient solver for the dipolar Poisson–Boltzmann–Langevin equation

PubMed Central

Koehl, Patrice; Delarue, Marc

2010-01-01

The Poisson–Boltzmann (PB) formalism is among the most popular approaches to modeling the solvation of molecules. It assumes a continuum model for water, leading to a dielectric permittivity that only depends on position in space. In contrast, the dipolar Poisson–Boltzmann–Langevin (DPBL) formalism represents the solvent as a collection of orientable dipoles with nonuniform concentration; this leads to a nonlinear permittivity function that depends both on the position and on the local electric field at that position. The differences in the assumptions underlying these two models lead to significant differences in the equations they generate. The PB equation is a second order, elliptic, nonlinear partial differential equation (PDE). Its response coefficients correspond to the dielectric permittivity and are therefore constant within each subdomain of the system considered (i.e., inside and outside of the molecules considered). While the DPBL equation is also a second order, elliptic, nonlinear PDE, its response coefficients are nonlinear functions of the electrostatic potential. Many solvers have been developed for the PB equation; to our knowledge, none of these can be directly applied to the DPBL equation. The methods they use may adapt to the difference; their implementations however are PBE specific. We adapted the PBE solver originally developed by Holst and Saied [J. Comput. Chem. 16, 337 (1995)] to the problem of solving the DPBL equation. This solver uses a truncated Newton method with a multigrid preconditioner. Numerical evidences suggest that it converges for the DPBL equation and that the convergence is superlinear. It is found however to be slow and greedy in memory requirement for problems commonly encountered in computational biology and computational chemistry. To circumvent these problems, we propose two variants, a quasi-Newton solver based on a simplified, inexact Jacobian and an iterative self-consistent solver that is based directly on the PBE solver. While both methods are not guaranteed to converge, numerical evidences suggest that they do and that their convergence is also superlinear. Both variants are significantly faster than the solver based on the exact Jacobian, with a much smaller memory footprint. All three methods have been implemented in a new code named AQUASOL, which is freely available. PMID:20151727

AQUASOL: An efficient solver for the dipolar Poisson-Boltzmann-Langevin equation.

PubMed

Koehl, Patrice; Delarue, Marc

2010-02-14

The Poisson-Boltzmann (PB) formalism is among the most popular approaches to modeling the solvation of molecules. It assumes a continuum model for water, leading to a dielectric permittivity that only depends on position in space. In contrast, the dipolar Poisson-Boltzmann-Langevin (DPBL) formalism represents the solvent as a collection of orientable dipoles with nonuniform concentration; this leads to a nonlinear permittivity function that depends both on the position and on the local electric field at that position. The differences in the assumptions underlying these two models lead to significant differences in the equations they generate. The PB equation is a second order, elliptic, nonlinear partial differential equation (PDE). Its response coefficients correspond to the dielectric permittivity and are therefore constant within each subdomain of the system considered (i.e., inside and outside of the molecules considered). While the DPBL equation is also a second order, elliptic, nonlinear PDE, its response coefficients are nonlinear functions of the electrostatic potential. Many solvers have been developed for the PB equation; to our knowledge, none of these can be directly applied to the DPBL equation. The methods they use may adapt to the difference; their implementations however are PBE specific. We adapted the PBE solver originally developed by Holst and Saied [J. Comput. Chem. 16, 337 (1995)] to the problem of solving the DPBL equation. This solver uses a truncated Newton method with a multigrid preconditioner. Numerical evidences suggest that it converges for the DPBL equation and that the convergence is superlinear. It is found however to be slow and greedy in memory requirement for problems commonly encountered in computational biology and computational chemistry. To circumvent these problems, we propose two variants, a quasi-Newton solver based on a simplified, inexact Jacobian and an iterative self-consistent solver that is based directly on the PBE solver. While both methods are not guaranteed to converge, numerical evidences suggest that they do and that their convergence is also superlinear. Both variants are significantly faster than the solver based on the exact Jacobian, with a much smaller memory footprint. All three methods have been implemented in a new code named AQUASOL, which is freely available.

A Generic Nonlinear Aerodynamic Model for Aircraft

NASA Technical Reports Server (NTRS)

Grauer, Jared A.; Morelli, Eugene A.

2014-01-01

A generic model of the aerodynamic coefficients was developed using wind tunnel databases for eight different aircraft and multivariate orthogonal functions. For each database and each coefficient, models were determined using polynomials expanded about the state and control variables, and an othgonalization procedure. A predicted squared-error criterion was used to automatically select the model terms. Modeling terms picked in at least half of the analyses, which totalled 45 terms, were retained to form the generic nonlinear aerodynamic (GNA) model. Least squares was then used to estimate the model parameters and associated uncertainty that best fit the GNA model to each database. Nonlinear flight simulations were used to demonstrate that the GNA model produces accurate trim solutions, local behavior (modal frequencies and damping ratios), and global dynamic behavior (91% accurate state histories and 80% accurate aerodynamic coefficient histories) under large-amplitude excitation. This compact aerodynamics model can be used to decrease on-board memory storage requirements, quickly change conceptual aircraft models, provide smooth analytical functions for control and optimization applications, and facilitate real-time parametric system identification.

Nonlinear Inference in Partially Observed Physical Systems and Deep Neural Networks

NASA Astrophysics Data System (ADS)

Rozdeba, Paul J.

The problem of model state and parameter estimation is a significant challenge in nonlinear systems. Due to practical considerations of experimental design, it is often the case that physical systems are partially observed, meaning that data is only available for a subset of the degrees of freedom required to fully model the observed system's behaviors and, ultimately, predict future observations. Estimation in this context is highly complicated by the presence of chaos, stochasticity, and measurement noise in dynamical systems. One of the aims of this dissertation is to simultaneously analyze state and parameter estimation in as a regularized inverse problem, where the introduction of a model makes it possible to reverse the forward problem of partial, noisy observation; and as a statistical inference problem using data assimilation to transfer information from measurements to the model states and parameters. Ultimately these two formulations achieve the same goal. Similar aspects that appear in both are highlighted as a means for better understanding the structure of the nonlinear inference problem. An alternative approach to data assimilation that uses model reduction is then examined as a way to eliminate unresolved nonlinear gating variables from neuron models. In this formulation, only measured variables enter into the model, and the resulting errors are themselves modeled by nonlinear stochastic processes with memory. Finally, variational annealing, a data assimilation method previously applied to dynamical systems, is introduced as a potentially useful tool for understanding deep neural network training in machine learning by exploiting similarities between the two problems.

Identification of Linear and Nonlinear Aerodynamic Impulse Responses Using Digital Filter Techniques

NASA Technical Reports Server (NTRS)

Silva, Walter A.

1997-01-01

This paper discusses the mathematical existence and the numerically-correct identification of linear and nonlinear aerodynamic impulse response functions. Differences between continuous-time and discrete-time system theories, which permit the identification and efficient use of these functions, will be detailed. Important input/output definitions and the concept of linear and nonlinear systems with memory will also be discussed. It will be shown that indicial (step or steady) responses (such as Wagner's function), forced harmonic responses (such as Theodorsen's function or those from doublet lattice theory), and responses to random inputs (such as gusts) can all be obtained from an aerodynamic impulse response function. This paper establishes the aerodynamic impulse response function as the most fundamental, and, therefore, the most computationally efficient, aerodynamic function that can be extracted from any given discrete-time, aerodynamic system. The results presented in this paper help to unify the understanding of classical two-dimensional continuous-time theories with modern three-dimensional, discrete-time theories. First, the method is applied to the nonlinear viscous Burger's equation as an example. Next the method is applied to a three-dimensional aeroelastic model using the CAP-TSD (Computational Aeroelasticity Program - Transonic Small Disturbance) code and then to a two-dimensional model using the CFL3D Navier-Stokes code. Comparisons of accuracy and computational cost savings are presented. Because of its mathematical generality, an important attribute of this methodology is that it is applicable to a wide range of nonlinear, discrete-time problems.

Identification of Linear and Nonlinear Aerodynamic Impulse Responses Using Digital Filter Techniques

NASA Technical Reports Server (NTRS)

Silva, Walter A.

1997-01-01

This paper discusses the mathematical existence and the numerically-correct identification of linear and nonlinear aerodynamic impulse response functions. Differences between continuous-time and discrete-time system theories, which permit the identification and efficient use of these functions, will be detailed. Important input/output definitions and the concept of linear and nonlinear systems with memory will also be discussed. It will be shown that indicial (step or steady) responses (such as Wagner's function), forced harmonic responses (such as Tbeodorsen's function or those from doublet lattice theory), and responses to random inputs (such as gusts) can all be obtained from an aerodynamic impulse response function. This paper establishes the aerodynamic impulse response function as the most fundamental, and, therefore, the most computationally efficient, aerodynamic function that can be extracted from any given discrete-time, aerodynamic system. The results presented in this paper help to unify the understanding of classical two-dimensional continuous-time theories with modem three-dimensional, discrete-time theories. First, the method is applied to the nonlinear viscous Burger's equation as an example. Next the method is applied to a three-dimensional aeroelastic model using the CAP-TSD (Computational Aeroelasticity Program - Transonic Small Disturbance) code and then to a two-dimensional model using the CFL3D Navier-Stokes code. Comparisons of accuracy and computational cost savings are presented. Because of its mathematical generality, an important attribute of this methodology is that it is applicable to a wide range of nonlinear, discrete-time problems.

A novel nonlinear damage resonance intermodulation effect for structural health monitoring

NASA Astrophysics Data System (ADS)

Ciampa, Francesco; Scarselli, Gennaro; Meo, Michele

2017-04-01

This paper is aimed at developing a theoretical model able to predict the generation of nonlinear elastic effects associated to the interaction of ultrasonic waves with the steady-state nonlinear response of local defect resonance (LDR). The LDR effect is used in nonlinear elastic wave spectroscopy to enhance the excitation of the material damage at its local resonance, thus to dramatically increase the vibrational amplitude of material nonlinear phenomena. The main result of this work is to prove both analytically and experimentally the generation of novel nonlinear elastic wave effects, here named as nonlinear damage resonance intermodulation, which correspond to a nonlinear intermodulation between the driving frequency and the LDR one. Beside this intermodulation effect, other nonlinear elastic wave phenomena such as higher harmonics of the input frequency and superharmonics of LDR frequency were found. The analytical model relies on solving the nonlinear equation of motion governing bending displacement under the assumption of both quadratic and cubic nonlinear defect approximation. Experimental tests on a damaged composite laminate confirmed and validated these predictions and showed that using continuous periodic excitation, the nonlinear structural phenomena associated to LDR could also be featured at locations different from the damage resonance. These findings will provide new opportunities for material damage detection using nonlinear ultrasounds.

Homogenized description and retrieval method of nonlinear metasurfaces

NASA Astrophysics Data System (ADS)

Liu, Xiaojun; Larouche, Stéphane; Smith, David R.

2018-03-01

A patterned, plasmonic metasurface can strongly scatter incident light, functioning as an extremely low-profile lens, filter, reflector or other optical device. When the metasurface is patterned uniformly, its linear optical properties can be expressed using effective surface electric and magnetic polarizabilities obtained through a homogenization procedure. The homogenized description of a nonlinear metasurface, however, presents challenges both because of the inherent anisotropy of the medium as well as the much larger set of potential wave interactions available, making it challenging to assign effective nonlinear parameters to the otherwise inhomogeneous layer of metamaterial elements. Here we show that a homogenization procedure can be developed to describe nonlinear metasurfaces, which derive their nonlinear response from the enhanced local fields arising within the structured plasmonic elements. With the proposed homogenization procedure, we are able to assign effective nonlinear surface polarization densities to a nonlinear metasurface, and link these densities to the effective nonlinear surface susceptibilities and averaged macroscopic pumping fields across the metasurface. These effective nonlinear surface polarization densities are further linked to macroscopic nonlinear fields through the generalized sheet transition conditions (GSTCs). By inverting the GSTCs, the effective nonlinear surface susceptibilities of the metasurfaces can be solved for, leading to a generalized retrieval method for nonlinear metasurfaces. The application of the homogenization procedure and the GSTCs are demonstrated by retrieving the nonlinear susceptibilities of a SiO2 nonlinear slab. As an example, we investigate a nonlinear metasurface which presents nonlinear magnetoelectric coupling in near infrared regime. The method is expected to apply to any patterned metasurface whose thickness is much smaller than the wavelengths of operation, with inclusions of arbitrary geometry and material composition, across the electromagnetic spectrum.

Additive scales in degenerative disease--calculation of effect sizes and clinical judgment.

PubMed

Riepe, Matthias W; Wilkinson, David; Förstl, Hans; Brieden, Andreas

2011-12-16

The therapeutic efficacy of an intervention is often assessed in clinical trials by scales measuring multiple diverse activities that are added to produce a cumulative global score. Medical communities and health care systems subsequently use these data to calculate pooled effect sizes to compare treatments. This is done because major doubt has been cast over the clinical relevance of statistically significant findings relying on p values with the potential to report chance findings. Hence in an aim to overcome this pooling the results of clinical studies into a meta-analyses with a statistical calculus has been assumed to be a more definitive way of deciding of efficacy. We simulate the therapeutic effects as measured with additive scales in patient cohorts with different disease severity and assess the limitations of an effect size calculation of additive scales which are proven mathematically. We demonstrate that the major problem, which cannot be overcome by current numerical methods, is the complex nature and neurobiological foundation of clinical psychiatric endpoints in particular and additive scales in general. This is particularly relevant for endpoints used in dementia research. 'Cognition' is composed of functions such as memory, attention, orientation and many more. These individual functions decline in varied and non-linear ways. Here we demonstrate that with progressive diseases cumulative values from multidimensional scales are subject to distortion by the limitations of the additive scale. The non-linearity of the decline of function impedes the calculation of effect sizes based on cumulative values from these multidimensional scales. Statistical analysis needs to be guided by boundaries of the biological condition. Alternatively, we suggest a different approach avoiding the error imposed by over-analysis of cumulative global scores from additive scales.

Application of morphological associative memories and Fourier descriptors for classification of noisy subsurface signatures

NASA Astrophysics Data System (ADS)

Ortiz, Jorge L.; Parsiani, Hamed; Tolstoy, Leonid

2004-02-01

This paper presents a method for recognition of Noisy Subsurface Images using Morphological Associative Memories (MAM). MAM are type of associative memories that use a new kind of neural networks based in the algebra system known as semi-ring. The operations performed in this algebraic system are highly nonlinear providing additional strength when compared to other transformations. Morphological associative memories are a new kind of neural networks that provide a robust performance with noisy inputs. Two representations of morphological associative memories are used called M and W matrices. M associative memory provides a robust association with input patterns corrupted by dilative random noise, while the W associative matrix performs a robust recognition in patterns corrupted with erosive random noise. The robust performance of MAM is used in combination of the Fourier descriptors for the recognition of underground objects in Ground Penetrating Radar (GPR) images. Multiple 2-D GPR images of a site are made available by NASA-SSC center. The buried objects in these images appear in the form of hyperbolas which are the results of radar backscatter from the artifacts or objects. The Fourier descriptors of the prototype hyperbola-like and shapes from non-hyperbola shapes in the sub-surface images are used to make these shapes scale-, shift-, and rotation-invariant. Typical hyperbola-like and non-hyperbola shapes are used to calculate the morphological associative memories. The trained MAMs are used to process other noisy images to detect the presence of these underground objects. The outputs from the MAM using the noisy patterns may be equal to the training prototypes, providing a positive identification of the artifacts. The results are images with recognized hyperbolas which indicate the presence of buried artifacts. A model using MATLAB has been developed and results are presented.

Improved Quasi-Newton method via PSB update for solving systems of nonlinear equations

NASA Astrophysics Data System (ADS)

Mamat, Mustafa; Dauda, M. K.; Waziri, M. Y.; Ahmad, Fadhilah; Mohamad, Fatma Susilawati

2016-10-01

The Newton method has some shortcomings which includes computation of the Jacobian matrix which may be difficult or even impossible to compute and solving the Newton system in every iteration. Also, the common setback with some quasi-Newton methods is that they need to compute and store an n × n matrix at each iteration, this is computationally costly for large scale problems. To overcome such drawbacks, an improved Method for solving systems of nonlinear equations via PSB (Powell-Symmetric-Broyden) update is proposed. In the proposed method, the approximate Jacobian inverse Hk of PSB is updated and its efficiency has improved thereby require low memory storage, hence the main aim of this paper. The preliminary numerical results show that the proposed method is practically efficient when applied on some benchmark problems.

Quantum Associative Neural Network with Nonlinear Search Algorithm

NASA Astrophysics Data System (ADS)

Zhou, Rigui; Wang, Huian; Wu, Qian; Shi, Yang

2012-03-01

Based on analysis on properties of quantum linear superposition, to overcome the complexity of existing quantum associative memory which was proposed by Ventura, a new storage method for multiply patterns is proposed in this paper by constructing the quantum array with the binary decision diagrams. Also, the adoption of the nonlinear search algorithm increases the pattern recalling speed of this model which has multiply patterns to O( {log2}^{2^{n -t}} ) = O( n - t ) time complexity, where n is the number of quantum bit and t is the quantum information of the t quantum bit. Results of case analysis show that the associative neural network model proposed in this paper based on quantum learning is much better and optimized than other researchers' counterparts both in terms of avoiding the additional qubits or extraordinary initial operators, storing pattern and improving the recalling speed.

BA07PRO103: Modeling Warfighter Physical and Cognitive Performance While Wearing CB Protective Equipment: A Trade-Space Analysis Tool

DTIC Science & Technology

2012-10-31

Development and Engineering Center 15 Kansas St., Natick, MA 01760 Telephone: (508) 233-5597 Email : thaddeus.t.brunye.civ@mail.mil Submitted to: Mr...Salvatore Clementi 8725 John J. Kingman Road Stop 6201 Fort Belvoir, Virginia 22060-6201 Telephone: (703) 767-6275 Email : salvatore.clementi...detection, memory, attention/vigilance, and multitasking /decision-making. A non-linear dynamical systems approach was developed that described Soldier

Optomechanically induced spontaneous symmetry breaking

NASA Astrophysics Data System (ADS)

Miri, Mohammad-Ali; Verhagen, Ewold; Alú, Andrea

2017-05-01

We explore the dynamics of spontaneous breakdown of mirror symmetry in a pair of identical optomechanical cavities symmetrically coupled to a waveguide. Large optical intensities enable optomechanically induced nonlinear detuning of the optical resonators, resulting in a pitchfork bifurcation. We investigate the stability of this regime and explore the possibility of inducing multistability. By injecting proper trigger pulses, the proposed structure can toggle between two asymmetric stable states, thus serving as a low-noise nanophotonic all-optical switch or memory element.

PLL jitter reduction by utilizing a ferroelectric capacitor as a VCO timing element.

PubMed

Pauls, Greg; Kalkur, Thottam S

2007-06-01

Ferroelectric capacitors have steadily been integrated into semiconductor processes due to their potential as storage elements within memory devices. Polarization reversal within ferroelectric capacitors creates a high nonlinear dielectric constant along with a hysteresis profile. Due to these attributes, a phase-locked loop (PLL), when based on a ferroelectric capacitor, has the advantage of reduced cycle-to-cycle jitter. PLLs based on ferroelectric capacitors represent a new research area for reduction of oscillator jitter.

Memory Efficient Evaluations of Nonlinear Stochastic Equations and C3 Applications.

DTIC Science & Technology

1987-12-01

time. In the 1960’s, when Massachusetts Institute of Technology’s Marvin Minsky [16] and others criticized the concept on the grounds of .nsufficient...recognize letters of the alphabet [231. Minsky and Papert [16] criticized the perceptron, asserting that too little is known of the human brain to...1987). [15] Kinoshita, J. and Palevsky, N. G., "Computing with neural networks," High Technology (May 1987). . [16] Minsky , M. and Papert, S

Fractional dynamics of globally slow transcription and its impact on deterministic genetic oscillation.

PubMed

Wei, Kun; Gao, Shilong; Zhong, Suchuan; Ma, Hong

2012-01-01

In dynamical systems theory, a system which can be described by differential equations is called a continuous dynamical system. In studies on genetic oscillation, most deterministic models at early stage are usually built on ordinary differential equations (ODE). Therefore, gene transcription which is a vital part in genetic oscillation is presupposed to be a continuous dynamical system by default. However, recent studies argued that discontinuous transcription might be more common than continuous transcription. In this paper, by appending the inserted silent interval lying between two neighboring transcriptional events to the end of the preceding event, we established that the running time for an intact transcriptional event increases and gene transcription thus shows slow dynamics. By globally replacing the original time increment for each state increment by a larger one, we introduced fractional differential equations (FDE) to describe such globally slow transcription. The impact of fractionization on genetic oscillation was then studied in two early stage models--the Goodwin oscillator and the Rössler oscillator. By constructing a "dual memory" oscillator--the fractional delay Goodwin oscillator, we suggested that four general requirements for generating genetic oscillation should be revised to be negative feedback, sufficient nonlinearity, sufficient memory and proper balancing of timescale. The numerical study of the fractional Rössler oscillator implied that the globally slow transcription tends to lower the chance of a coupled or more complex nonlinear genetic oscillatory system behaving chaotically.

Multi-functional surface acoustic wave sensor for monitoring enviromental and structural condition

NASA Astrophysics Data System (ADS)

Furuya, Y.; Kon, T.; Okazaki, T.; Saigusa, Y.; Nomura, T.

2006-03-01

As a first step to develop a health monitoring system with active and embedded nondestructive evaluation devices for the machineries and structures, multi-functional SAW (surface acoustic wave) device was developed. A piezoelectric LiNbO3(x-y cut) materials were used as a SAW substrate on which IDT(20μm pitch) was produced by lithography. On the surface of a path of SAW between IDTs, environmentally active material films of shape memory Ti50Ni41Cu(at%) with non-linear hysteresis and superelastic Ti48Ni43Cu(at%) with linear deformation behavior were formed by magnetron-sputtering technique. In this study, these two kinds of shape memory alloys SMA) system were used to measure 1) loading level, 2) phase transformation and 3)stress-strain hysteresis under cyclic loading by utilizing their linearity and non-linearity deformation behaviors. Temperature and stress dependencies of SAW signal were also investigated in the non-sputtered film state. Signal amplitude and phase change of SAW were chosen to measure as the sensing parameters. As a result, temperature, stress level, phase transformation in SMA depending on temperature and mechanical damage accumulation could be measured by the proposed multi-functional SAW sensor. Moreover, the wireless SAW sensing system which has a unique feature of no supplying electric battery was constructed, and the same characteristic evaluation is confirmed in comparison with wired case.

Longitudinal development of frontoparietal activity during feedback learning: Contributions of age, performance, working memory and cortical thickness.

PubMed

Peters, Sabine; Van Duijvenvoorde, Anna C K; Koolschijn, P Cédric M P; Crone, Eveline A

2016-06-01

Feedback learning is a crucial skill for cognitive flexibility that continues to develop into adolescence, and is linked to neural activity within a frontoparietal network. Although it is well conceptualized that activity in the frontoparietal network changes during development, there is surprisingly little consensus about the direction of change. Using a longitudinal design (N=208, 8-27 years, two measurements in two years), we investigated developmental trajectories in frontoparietal activity during feedback learning. Our first aim was to test for linear and nonlinear developmental trajectories in dorsolateral prefrontal cortex (DLPFC), superior parietal cortex (SPC), supplementary motor area (SMA) and anterior cingulate cortex (ACC). Second, we tested which factors (task performance, working memory, cortical thickness) explained additional variance in time-related changes in activity besides age. Developmental patterns for activity in DLPFC and SPC were best characterized by a quadratic age function leveling off/peaking in late adolescence. There was a linear increase in SMA and a linear decrease with age in ACC activity. In addition to age, task performance explained variance in DLPFC and SPC activity, whereas cortical thickness explained variance in SMA activity. Together, these findings provide a novel perspective of linear and nonlinear developmental changes in the frontoparietal network during feedback learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Multifractal analysis of information processing in hippocampal neural ensembles during working memory under Δ9-tetrahydrocannabinol administration

PubMed Central

Fetterhoff, Dustin; Opris, Ioan; Simpson, Sean L.; Deadwyler, Sam A.; Hampson, Robert E.; Kraft, Robert A.

2014-01-01

Background Multifractal analysis quantifies the time-scale-invariant properties in data by describing the structure of variability over time. By applying this analysis to hippocampal interspike interval sequences recorded during performance of a working memory task, a measure of long-range temporal correlations and multifractal dynamics can reveal single neuron correlates of information processing. New method Wavelet leaders-based multifractal analysis (WLMA) was applied to hippocampal interspike intervals recorded during a working memory task. WLMA can be used to identify neurons likely to exhibit information processing relevant to operation of brain–computer interfaces and nonlinear neuronal models. Results Neurons involved in memory processing (“Functional Cell Types” or FCTs) showed a greater degree of multifractal firing properties than neurons without task-relevant firing characteristics. In addition, previously unidentified FCTs were revealed because multifractal analysis suggested further functional classification. The cannabinoid-type 1 receptor partial agonist, tetrahydrocannabinol (THC), selectively reduced multifractal dynamics in FCT neurons compared to non-FCT neurons. Comparison with existing methods WLMA is an objective tool for quantifying the memory-correlated complexity represented by FCTs that reveals additional information compared to classification of FCTs using traditional z-scores to identify neuronal correlates of behavioral events. Conclusion z-Score-based FCT classification provides limited information about the dynamical range of neuronal activity characterized by WLMA. Increased complexity, as measured with multifractal analysis, may be a marker of functional involvement in memory processing. The level of multifractal attributes can be used to differentially emphasize neural signals to improve computational models and algorithms underlying brain–computer interfaces. PMID:25086297

Evaluation of nonlinearity and validity of nonlinear modeling for complex time series.

PubMed

Suzuki, Tomoya; Ikeguchi, Tohru; Suzuki, Masuo

2007-10-01

Even if an original time series exhibits nonlinearity, it is not always effective to approximate the time series by a nonlinear model because such nonlinear models have high complexity from the viewpoint of information criteria. Therefore, we propose two measures to evaluate both the nonlinearity of a time series and validity of nonlinear modeling applied to it by nonlinear predictability and information criteria. Through numerical simulations, we confirm that the proposed measures effectively detect the nonlinearity of an observed time series and evaluate the validity of the nonlinear model. The measures are also robust against observational noises. We also analyze some real time series: the difference of the number of chickenpox and measles patients, the number of sunspots, five Japanese vowels, and the chaotic laser. We can confirm that the nonlinear model is effective for the Japanese vowel /a/, the difference of the number of measles patients, and the chaotic laser.

Evaluation of nonlinearity and validity of nonlinear modeling for complex time series

NASA Astrophysics Data System (ADS)

Suzuki, Tomoya; Ikeguchi, Tohru; Suzuki, Masuo

2007-10-01

Even if an original time series exhibits nonlinearity, it is not always effective to approximate the time series by a nonlinear model because such nonlinear models have high complexity from the viewpoint of information criteria. Therefore, we propose two measures to evaluate both the nonlinearity of a time series and validity of nonlinear modeling applied to it by nonlinear predictability and information criteria. Through numerical simulations, we confirm that the proposed measures effectively detect the nonlinearity of an observed time series and evaluate the validity of the nonlinear model. The measures are also robust against observational noises. We also analyze some real time series: the difference of the number of chickenpox and measles patients, the number of sunspots, five Japanese vowels, and the chaotic laser. We can confirm that the nonlinear model is effective for the Japanese vowel /a/, the difference of the number of measles patients, and the chaotic laser.

Multiscale modeling of nanostructured ZnO based devices for optoelectronic applications: Dynamically-coupled structural fields, charge, and thermal transport processes

NASA Astrophysics Data System (ADS)

Abdullah, Abdulmuin; Alqahtani, Saad; Nishat, Md Rezaul Karim; Ahmed, Shaikh; SIU Nanoelectronics Research Group Team

Recently, hybrid ZnO nanostructures (such as ZnO deposited on ZnO-alloys, Si, GaN, polymer, conducting oxides, and organic compounds) have attracted much attention for their possible applications in optoelectronic devices (such as solar cells, light emitting and laser diodes), as well as in spintronics (such as spin-based memory, and logic). However, efficiency and performance of these hybrid ZnO devices strongly depend on an intricate interplay of complex, nonlinear, highly stochastic and dynamically-coupled structural fields, charge, and thermal transport processes at different length and time scales, which have not yet been fully assessed experimentally. In this work, we study the effects of these coupled processes on the electronic and optical emission properties in nanostructured ZnO devices. The multiscale computational framework employs the atomistic valence force-field molecular mechanics, models for linear and non-linear polarization, the 8-band sp3s* tight-binding models, and coupling to a TCAD toolkit to determine the terminal properties of the device. A series of numerical experiments are performed (by varying different nanoscale parameters such as size, geometry, crystal cut, composition, and electrostatics) that mainly aim to improve the efficiency of these devices. Supported by the U.S. National Science Foundation Grant No. 1102192.

Nonlinear integral equations for the sausage model

NASA Astrophysics Data System (ADS)

Ahn, Changrim; Balog, Janos; Ravanini, Francesco

2017-08-01

The sausage model, first proposed by Fateev, Onofri, and Zamolodchikov, is a deformation of the O(3) sigma model preserving integrability. The target space is deformed from the sphere to ‘sausage’ shape by a deformation parameter ν. This model is defined by a factorizable S-matrix which is obtained by deforming that of the O(3) sigma model by a parameter λ. Clues for the deformed sigma model are provided by various UV and IR information through the thermodynamic Bethe ansatz (TBA) analysis based on the S-matrix. Application of TBA to the sausage model is, however, limited to the case of 1/λ integer where the coupled integral equations can be truncated to a finite number. In this paper, we propose a finite set of nonlinear integral equations (NLIEs), which are applicable to generic value of λ. Our derivation is based on T-Q relations extracted from the truncated TBA equations. For a consistency check, we compute next-leading order corrections of the vacuum energy and extract the S-matrix information in the IR limit. We also solved the NLIE both analytically and numerically in the UV limit to get the effective central charge and compared with that of the zero-mode dynamics to obtain exact relation between ν and λ. Dedicated to the memory of Petr Petrovich Kulish.

Second-Order Nonlinear Optical Properties of a Dithienylethene-Indolinooxazolidine Hybrid: A Joint Experimental and Theoretical Investigation.

PubMed

Bondu, Flavie; Quertinmont, Jean; Rodriguez, Vincent; Pozzo, Jean-Luc; Plaquet, Aurélie; Champagne, Benoît; Castet, Frédéric

2015-12-14

The nonlinear optical (NLO) properties of a double photochrome molecular switch are reported for the first time by considering the four trans forms of a dithienylethene-indolinooxazolidine hybrid. The four forms are characterized by means of hyper-Rayleigh scattering (HRS) experiments and quantum chemical calculations. Experimental measurements provide evidence that the pH- and light-triggered transformations between the different forms of the hybrid are accompanied by large variations of the first hyperpolarizability, which makes this compound an effective multistate NLO switch. Quantum chemical calculations conducted at the time-dependent Hartree-Fock and time-dependent DFT levels agree with the experimental data and allow a complete rationalization of the NLO responses of the different forms. The HRS signal of the forms with an open indolinooxazolidine moiety are more than one order of magnitude larger than that measured for the other forms, whereas the open/closed status of the dithienylethene subunit barely influences the dynamic NLO properties. However, extrapolation of the NLO responses to the static limit leads to univocally distinguishable intrinsic responses for three of the various forms. This hybrid system thus acts as a highly efficient multistate NLO switch for eventual exploitation in optical memory systems with multiple storage and nondestructive readout capacity. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Film thickness measurement based on nonlinear phase analysis using a Linnik microscopic white-light spectral interferometer.

PubMed

Guo, Tong; Chen, Zhuo; Li, Minghui; Wu, Juhong; Fu, Xing; Hu, Xiaotang

2018-04-20

Based on white-light spectral interferometry and the Linnik microscopic interference configuration, the nonlinear phase components of the spectral interferometric signal were analyzed for film thickness measurement. The spectral interferometric signal was obtained using a Linnik microscopic white-light spectral interferometer, which includes the nonlinear phase components associated with the effective thickness, the nonlinear phase error caused by the double-objective lens, and the nonlinear phase of the thin film itself. To determine the influence of the effective thickness, a wavelength-correction method was proposed that converts the effective thickness into a constant value; the nonlinear phase caused by the effective thickness can then be determined and subtracted from the total nonlinear phase. A method for the extraction of the nonlinear phase error caused by the double-objective lens was also proposed. Accurate thickness measurement of a thin film can be achieved by fitting the nonlinear phase of the thin film after removal of the nonlinear phase caused by the effective thickness and by the nonlinear phase error caused by the double-objective lens. The experimental results demonstrated that both the wavelength-correction method and the extraction method for the nonlinear phase error caused by the double-objective lens improve the accuracy of film thickness measurements.

Influence of unbalance on the nonlinear dynamical response and stability of flexible rotor-bearing systems

NASA Technical Reports Server (NTRS)

Gunter, E. J.; Humphris, R. R.; Springer, H.

1983-01-01

In this paper, some of the effects of unbalance on the nonlinear response and stability of flexible rotor-bearing systems is presented from both a theoretical and experimental standpoint. In a linear system, operating above its stability threshold, the amplitude of motion grows exponentially with time and the orbits become unbounded. In an actual system, this is not necessarily the case. The actual amplitudes of motion may be bounded due to various nonlinear effects in the system. These nonlinear effects cause limit cycles of motion. Nonlinear effects are inherent in fluid film bearings and seals. Other contributors to nonlinear effects are shafts, couplings and foundations. In addition to affecting the threshold of stability, the nonlinear effects can cause jump phenomena to occur at not only the critical speeds, but also at stability onset or restabilization speeds.

Experiments and Analyses of Data Transfers Over Wide-Area Dedicated Connections

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

Rao, Nageswara S.; Liu, Qiang; Sen, Satyabrata

Dedicated wide-area network connections are increasingly employed in high-performance computing and big data scenarios. One might expect the performance and dynamics of data transfers over such connections to be easy to analyze due to the lack of competing traffic. However, non-linear transport dynamics and end-system complexities (e.g., multi-core hosts and distributed filesystems) can in fact make analysis surprisingly challenging. We present extensive measurements of memory-to-memory and disk-to-disk file transfers over 10 Gbps physical and emulated connections with 0–366 ms round trip times (RTTs). For memory-to-memory transfers, profiles of both TCP and UDT throughput as a function of RTT show concavemore » and convex regions; large buffer sizes and more parallel flows lead to wider concave regions, which are highly desirable. TCP and UDT both also display complex throughput dynamics, as indicated by their Poincare maps and Lyapunov exponents. For disk-to-disk transfers, we determine that high throughput can be achieved via a combination of parallel I/O threads, parallel network threads, and direct I/O mode. Our measurements also show that Lustre filesystems can be mounted over long-haul connections using LNet routers, although challenges remain in jointly optimizing file I/O and transport method parameters to achieve peak throughput.« less

Limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method for the parameter estimation on geographically weighted ordinal logistic regression model (GWOLR)

NASA Astrophysics Data System (ADS)

Saputro, Dewi Retno Sari; Widyaningsih, Purnami

2017-08-01

In general, the parameter estimation of GWOLR model uses maximum likelihood method, but it constructs a system of nonlinear equations, making it difficult to find the solution. Therefore, an approximate solution is needed. There are two popular numerical methods: the methods of Newton and Quasi-Newton (QN). Newton's method requires large-scale time in executing the computation program since it contains Jacobian matrix (derivative). QN method overcomes the drawback of Newton's method by substituting derivative computation into a function of direct computation. The QN method uses Hessian matrix approach which contains Davidon-Fletcher-Powell (DFP) formula. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is categorized as the QN method which has the DFP formula attribute of having positive definite Hessian matrix. The BFGS method requires large memory in executing the program so another algorithm to decrease memory usage is needed, namely Low Memory BFGS (LBFGS). The purpose of this research is to compute the efficiency of the LBFGS method in the iterative and recursive computation of Hessian matrix and its inverse for the GWOLR parameter estimation. In reference to the research findings, we found out that the BFGS and LBFGS methods have arithmetic operation schemes, including O(n2) and O(nm).

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

Lin, Paul T.; Shadid, John N.; Tsuji, Paul H.

Here, this study explores the performance and scaling of a GMRES Krylov method employed as a smoother for an algebraic multigrid (AMG) preconditioned Newton- Krylov solution approach applied to a fully-implicit variational multiscale (VMS) nite element (FE) resistive magnetohydrodynamics (MHD) formulation. In this context a Newton iteration is used for the nonlinear system and a Krylov (GMRES) method is employed for the linear subsystems. The efficiency of this approach is critically dependent on the scalability and performance of the AMG preconditioner for the linear solutions and the performance of the smoothers play a critical role. Krylov smoothers are considered inmore » an attempt to reduce the time and memory requirements of existing robust smoothers based on additive Schwarz domain decomposition (DD) with incomplete LU factorization solves on each subdomain. Three time dependent resistive MHD test cases are considered to evaluate the method. The results demonstrate that the GMRES smoother can be faster due to a decrease in the preconditioner setup time and a reduction in outer GMRESR solver iterations, and requires less memory (typically 35% less memory for global GMRES smoother) than the DD ILU smoother.« less

Low-Storage, Explicit Runge-Kutta Schemes for the Compressible Navier-Stokes Equations

NASA Technical Reports Server (NTRS)

Kennedy, Chistopher A.; Carpenter, Mark H.; Lewis, R. Michael

1999-01-01

The derivation of storage explicit Runge-Kutta (ERK) schemes has been performed in the context of integrating the compressible Navier-Stokes equations via direct numerical simulation. Optimization of ERK methods is done across the broad range of properties, such as stability and accuracy efficiency, linear and nonlinear stability, error control reliability, step change stability, and dissipation/dispersion accuracy, subject to varying degrees of memory economization. Following van der Houwen and Wray, 16 ERK pairs are presented using from two to five registers of memory per equation, per grid point and having accuracies from third- to fifth-order. Methods have been assessed using the differential equation testing code DETEST, and with the 1D wave equation. Two of the methods have been applied to the DNS of a compressible jet as well as methane-air and hydrogen-air flames. Derived 3(2) and 4(3) pairs are competitive with existing full-storage methods. Although a substantial efficiency penalty accompanies use of two- and three-register, fifth-order methods, the best contemporary full-storage methods can be pearl), matched while still saving two to three registers of memory.

An optimized treatment for algorithmic differentiation of an important glaciological fixed-point problem

DOE PAGES

Goldberg, Daniel N.; Narayanan, Sri Hari Krishna; Hascoet, Laurent; ...

2016-05-20

We apply an optimized method to the adjoint generation of a time-evolving land ice model through algorithmic differentiation (AD). The optimization involves a special treatment of the fixed-point iteration required to solve the nonlinear stress balance, which differs from a straightforward application of AD software, and leads to smaller memory requirements and in some cases shorter computation times of the adjoint. The optimization is done via implementation of the algorithm of Christianson (1994) for reverse accumulation of fixed-point problems, with the AD tool OpenAD. For test problems, the optimized adjoint is shown to have far lower memory requirements, potentially enablingmore » larger problem sizes on memory-limited machines. In the case of the land ice model, implementation of the algorithm allows further optimization by having the adjoint model solve a sequence of linear systems with identical (as opposed to varying) matrices, greatly improving performance. Finally, the methods introduced here will be of value to other efforts applying AD tools to ice models, particularly ones which solve a hybrid shallow ice/shallow shelf approximation to the Stokes equations.« less

Feedback coupling in dynamical systems

NASA Astrophysics Data System (ADS)

Trimper, Steffen; Zabrocki, Knud

2003-05-01

Different evolution models are considered with feedback-couplings. In particular, we study the Lotka-Volterra system under the influence of a cumulative term, the Ginzburg-Landau model with a convolution memory term and chemical rate equations with time delay. The memory leads to a modified dynamical behavior. In case of a positive coupling the generalized Lotka-Volterra system exhibits a maximum gain achieved after a finite time, but the population will die out in the long time limit. In the opposite case, the time evolution is terminated in a crash. Due to the nonlinear feedback coupling the two branches of a bistable model are controlled by the the strength and the sign of the memory. For a negative coupling the system is able to switch over between both branches of the stationary solution. The dynamics of the system is further controlled by the initial condition. The diffusion-limited reaction is likewise studied in case the reacting entities are not available simultaneously. Whereas for an external feedback the dynamics is altered, but the stationary solution remain unchanged, a self-organized internal feedback leads to a time persistent solution.

Minimum envelope roughness pulse design for reduced amplifier distortion in parallel excitation.

PubMed

Grissom, William A; Kerr, Adam B; Stang, Pascal; Scott, Greig C; Pauly, John M

2010-11-01

Parallel excitation uses multiple transmit channels and coils, each driven by independent waveforms, to afford the pulse designer an additional spatial encoding mechanism that complements gradient encoding. In contrast to parallel reception, parallel excitation requires individual power amplifiers for each transmit channel, which can be cost prohibitive. Several groups have explored the use of low-cost power amplifiers for parallel excitation; however, such amplifiers commonly exhibit nonlinear memory effects that distort radio frequency pulses. This is especially true for pulses with rapidly varying envelopes, which are common in parallel excitation. To overcome this problem, we introduce a technique for parallel excitation pulse design that yields pulses with smoother envelopes. We demonstrate experimentally that pulses designed with the new technique suffer less amplifier distortion than unregularized pulses and pulses designed with conventional regularization.

Fractional Brownian motion run with a multi-scaling clock mimics diffusion of spherical colloids in microstructural fluids.

PubMed

Park, Moongyu; Cushman, John Howard; O'Malley, Dan

2014-09-30

The collective molecular reorientations within a nematic liquid crystal fluid bathing a spherical colloid cause the colloid to diffuse anomalously on a short time scale (i.e., as a non-Brownian particle). The deformations and fluctuations of long-range orientational order in the liquid crystal profoundly influence the transient diffusive regimes. Here we show that an anisotropic fractional Brownian process run with a nonlinear multiscaling clock effectively mimics this collective and transient phenomenon. This novel process has memory, Gaussian increments, and a multiscale mean square displacement that can be chosen independently from the fractal dimension of a particle trajectory. The process is capable of modeling multiscale sub-, super-, or classical diffusion. The finite-size Lyapunov exponents for this multiscaling process are defined for future analysis of related mixing processes.

Stochastic coupled cluster theory: Efficient sampling of the coupled cluster expansion

NASA Astrophysics Data System (ADS)

Scott, Charles J. C.; Thom, Alex J. W.

2017-09-01

We consider the sampling of the coupled cluster expansion within stochastic coupled cluster theory. Observing the limitations of previous approaches due to the inherently non-linear behavior of a coupled cluster wavefunction representation, we propose new approaches based on an intuitive, well-defined condition for sampling weights and on sampling the expansion in cluster operators of different excitation levels. We term these modifications even and truncated selections, respectively. Utilising both approaches demonstrates dramatically improved calculation stability as well as reduced computational and memory costs. These modifications are particularly effective at higher truncation levels owing to the large number of terms within the cluster expansion that can be neglected, as demonstrated by the reduction of the number of terms to be sampled when truncating at triple excitations by 77% and hextuple excitations by 98%.

Kinetics of porous silicon growth studied using flicker-noise spectroscopy

NASA Astrophysics Data System (ADS)

Parkhutik, V.; Timashev, S.

2000-05-01

The mechanism of the formation of porous silicon (PS) is studied using flicker noise spectroscopy (FNS), a new phenomenological method that allows us to analyze the evolution of nonlinear dissipative systems in time, space and energy. FNS is based on the ideas of deterministic chaos in complex macro- and microsystems. It allows us to obtain a set of empiric parameters ("passport data") which characterize the state of the system and change of its properties due to the evolution in time, energy, and space. The FNS method permits us to get new information about the kinetics of growth of PS and its properties. Thus, the PS formation mechanisms at n-Si and p-Si, as revealed using the FNS, seem to be essentially different. p-Si shows larger "memory" in the sequence of individual events involved in PS growth than n-Si (if anodized without light illumination). The influence of the anodization variables (such as current density, HF concentration, duration of the process, light illumination) onto the "passport data" of PS is envisaged. The increase of the current density increases memory of the PS formation process, when each forthcoming individual event is more correlated with the preceding one. Increasing current density triggers electrochemical reactions that are negligible at lower currents. Light illumination also produces a positive effect onto the "memory" of the system. The FNS makes it possible to distinguish different stages of the continuous anodization process which are apparently associated with increasing pore length. Thus, FNS is a very sensitive tool in analysis of the PS formation and other complex electrochemical systems as well.

Nonlinear Ion Harmonics in the Paul Trap with Added Octopole Field: Theoretical Characterization and New Insight into Nonlinear Resonance Effect.

PubMed

Xiong, Caiqiao; Zhou, Xiaoyu; Zhang, Ning; Zhan, Lingpeng; Chen, Yongtai; Nie, Zongxiu

2016-02-01

The nonlinear harmonics within the ion motion are the fingerprint of the nonlinear fields. They are exclusively introduced by these nonlinear fields and are responsible to some specific nonlinear effects such as nonlinear resonance effect. In this article, the ion motion in the quadrupole field with a weak superimposed octopole component, described by the nonlinear Mathieu equation (NME), was studied by using the analytical harmonic balance (HB) method. Good accuracy of the HB method, which was comparable with that of the numerical fourth-order Runge-Kutta (4th RK), was achieved in the entire first stability region, except for the points at the stability boundary (i.e., β = 1) and at the nonlinear resonance condition (i.e., β = 0.5). Using the HB method, the nonlinear 3β harmonic series introduced by the octopole component and the resultant nonlinear resonance effect were characterized. At nonlinear resonance, obvious resonant peaks were observed in the nonlinear 3β series of ion motion, but were not found in the natural harmonics. In addition, both resonant excitation and absorption peaks could be observed, simultaneously. These are two unique features of the nonlinear resonance, distinguishing it from the normal resonance. Finally, an approximation equation was given to describe the corresponding working parameter, q nr , at nonlinear resonance. This equation can help avoid the sensitivity degradation due to the operation of ion traps at the nonlinear resonance condition.

LTP saturation and spatial learning disruption: effects of task variables and saturation levels.

PubMed

Barnes, C A; Jung, M W; McNaughton, B L; Korol, D L; Andreasson, K; Worley, P F

1994-10-01

The prediction that "saturation" of LTP/LTE at hippocampal synapses should impair spatial learning was reinvestigated in the light of a more specific consideration of the theory of Hebbian associative networks, which predicts a nonlinear relationship between LTP "saturation" and memory impairment. This nonlinearity may explain the variable results of studies that have addressed the effects of LTP "saturation" on behavior. The extent of LTP "saturation" in fascia dentata produced by the standard chronic LTP stimulation protocol was assessed both electrophysiologically and through the use of an anatomical marker (activation of the immediate-early gene zif268). Both methods point to the conclusion that the standard protocols used to induce LTP do not "saturate" the process at any dorsoventral level, and leave the ventral half of the hippocampus virtually unaffected. LTP-inducing, bilateral perforant path stimulation led to a significant deficit in the reversal of a well-learned spatial response on the Barnes circular platform task as reported previously, yet in the same animals produced no deficit in learning the Morris water task (for which previous results have been conflicting). The behavioral deficit was not a consequence of any after-discharge in the hippocampal EEG. In contrast, administration of maximal electroconvulsive shock led to robust zif268 activation throughout the hippocampus, enhancement of synaptic responses, occlusion of LTP produced by discrete high-frequency stimulation, and spatial learning deficits in the water task. These data provide further support for the involvement of LTP-like synaptic enhancement in spatial learning.

Modelling nonlinearity in superconducting split ring resonator and its effects on metamaterial structures

NASA Astrophysics Data System (ADS)

Mazdouri, Behnam; Mohammad Hassan Javadzadeh, S.

2017-09-01

Superconducting materials are intrinsically nonlinear, because of nonlinear Meissner effect (NLME). Considering nonlinear behaviors, such as harmonic generation and intermodulation distortion (IMD) in superconducting structures, are very important. In this paper, we proposed distributed nonlinear circuit model for superconducting split ring resonators (SSRRs). This model can be analyzed by using Harmonic Balance method (HB) as a nonlinear solver. Thereafter, we considered a superconducting metamaterial filter which was based on split ring resonators and we calculated fundamental and third-order IMD signals. There are good agreement between nonlinear results from proposed model and measured ones. Additionally, based on the proposed nonlinear model and by using a novel method, we considered nonlinear effects on main parameters in the superconducting metamaterial structures such as phase constant (β) and attenuation factor (α).

Slave finite element for non-linear analysis of engine structures. Volume 2: Programmer's manual and user's manual

NASA Technical Reports Server (NTRS)

Witkop, D. L.; Dale, B. J.; Gellin, S.

1991-01-01

The programming aspects of SFENES are described in the User's Manual. The information presented is provided for the installation programmer. It is sufficient to fully describe the general program logic and required peripheral storage. All element generated data is stored externally to reduce required memory allocation. A separate section is devoted to the description of these files thereby permitting the optimization of Input/Output (I/O) time through efficient buffer descriptions. Individual subroutine descriptions are presented along with the complete Fortran source listings. A short description of the major control, computation, and I/O phases is included to aid in obtaining an overall familiarity with the program's components. Finally, a discussion of the suggested overlay structure which allows the program to execute with a reasonable amount of memory allocation is presented.

Effects of weak nonlinearity on the dispersion relation and frequency band-gaps of a periodic Bernoulli–Euler beam

PubMed Central

Thomsen, Jon Juel

2016-01-01

The paper deals with analytically predicting the effects of weak nonlinearity on the dispersion relation and frequency band-gaps of a periodic Bernoulli–Euler beam performing bending oscillations. Two cases are considered: (i) large transverse deflections, where nonlinear (true) curvature, nonlinear material and nonlinear inertia owing to longitudinal motions of the beam are taken into account, and (ii) mid-plane stretching nonlinearity. A novel approach is employed, the method of varying amplitudes. As a result, the isolated as well as combined effects of the considered sources of nonlinearities are revealed. It is shown that nonlinear inertia has the most substantial impact on the dispersion relation of a non-uniform beam by removing all frequency band-gaps. Explanations of the revealed effects are suggested, and validated by experiments and numerical simulation. PMID:27118899

3D numerical simulation of the long range propagation of acoustical shock waves through a heterogeneous and moving medium

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

Luquet, David; Marchiano, Régis; Coulouvrat, François, E-mail: francois.coulouvrat@upmc.fr

2015-10-28

Many situations involve the propagation of acoustical shock waves through flows. Natural sources such as lightning, volcano explosions, or meteoroid atmospheric entries, emit loud, low frequency, and impulsive sound that is influenced by atmospheric wind and turbulence. The sonic boom produced by a supersonic aircraft and explosion noises are examples of intense anthropogenic sources in the atmosphere. The Buzz-Saw-Noise produced by turbo-engine fan blades rotating at supersonic speed also propagates in a fast flow within the engine nacelle. Simulating these situations is challenging, given the 3D nature of the problem, the long range propagation distances relative to the central wavelength,more » the strongly nonlinear behavior of shocks associated to a wide-band spectrum, and finally the key role of the flow motion. With this in view, the so-called FLHOWARD (acronym for FLow and Heterogeneous One-Way Approximation for Resolution of Diffraction) method is presented with three-dimensional applications. A scalar nonlinear wave equation is established in the framework of atmospheric applications, assuming weak heterogeneities and a slow wind. It takes into account diffraction, absorption and relaxation properties of the atmosphere, quadratic nonlinearities including weak shock waves, heterogeneities of the medium in sound speed and density, and presence of a flow (assuming a mean stratified wind and 3D turbulent ? flow fluctuations of smaller amplitude). This equation is solved in the framework of the one-way method. A split-step technique allows the splitting of the non-linear wave equation into simpler equations, each corresponding to a physical effect. Each sub-equation is solved using an analytical method if possible, and finite-differences otherwise. Nonlinear effects are solved in the time domain, and others in the frequency domain. Homogeneous diffraction is handled by means of the angular spectrum method. Ground is assumed perfectly flat and rigid. Due to the 3D aspect, the code was massively parallelized using the single program, multiple data paradigm with the Message Passing Interfaces (MPI) for distributed memory architectures. This allows us to handle problems in the order of a thousand billion mesh points in the four dimensions (3 dimensions of space plus time). The validity of the method has been thoroughly evaluated on many cases with known solutions: linear piston, scattering of plane wave by a heterogeneous sphere, propagation in a waveguide with a shear flow, scattering by a finite amplitude vortex and nonlinear propagation in a thermoviscous medium. This validation process allows for a detailed assessment of the advantages and limitations of the method. Finally, applications to atmospheric propagation of shock waves will be presented.« less

3D numerical simulation of the long range propagation of acoustical shock waves through a heterogeneous and moving medium

NASA Astrophysics Data System (ADS)

Luquet, David; Marchiano, Régis; Coulouvrat, François

2015-10-01

Many situations involve the propagation of acoustical shock waves through flows. Natural sources such as lightning, volcano explosions, or meteoroid atmospheric entries, emit loud, low frequency, and impulsive sound that is influenced by atmospheric wind and turbulence. The sonic boom produced by a supersonic aircraft and explosion noises are examples of intense anthropogenic sources in the atmosphere. The Buzz-Saw-Noise produced by turbo-engine fan blades rotating at supersonic speed also propagates in a fast flow within the engine nacelle. Simulating these situations is challenging, given the 3D nature of the problem, the long range propagation distances relative to the central wavelength, the strongly nonlinear behavior of shocks associated to a wide-band spectrum, and finally the key role of the flow motion. With this in view, the so-called FLHOWARD (acronym for FLow and Heterogeneous One-Way Approximation for Resolution of Diffraction) method is presented with three-dimensional applications. A scalar nonlinear wave equation is established in the framework of atmospheric applications, assuming weak heterogeneities and a slow wind. It takes into account diffraction, absorption and relaxation properties of the atmosphere, quadratic nonlinearities including weak shock waves, heterogeneities of the medium in sound speed and density, and presence of a flow (assuming a mean stratified wind and 3D turbulent ? flow fluctuations of smaller amplitude). This equation is solved in the framework of the one-way method. A split-step technique allows the splitting of the non-linear wave equation into simpler equations, each corresponding to a physical effect. Each sub-equation is solved using an analytical method if possible, and finite-differences otherwise. Nonlinear effects are solved in the time domain, and others in the frequency domain. Homogeneous diffraction is handled by means of the angular spectrum method. Ground is assumed perfectly flat and rigid. Due to the 3D aspect, the code was massively parallelized using the single program, multiple data paradigm with the Message Passing Interfaces (MPI) for distributed memory architectures. This allows us to handle problems in the order of a thousand billion mesh points in the four dimensions (3 dimensions of space plus time). The validity of the method has been thoroughly evaluated on many cases with known solutions: linear piston, scattering of plane wave by a heterogeneous sphere, propagation in a waveguide with a shear flow, scattering by a finite amplitude vortex and nonlinear propagation in a thermoviscous medium. This validation process allows for a detailed assessment of the advantages and limitations of the method. Finally, applications to atmospheric propagation of shock waves will be presented.

Deformation behavior of carbon-fiber reinforced shape-memory-polymer composites used for deployable structures (Conference Presentation)

NASA Astrophysics Data System (ADS)

Lan, Xin; Liu, Liwu; Li, Fengfeng; Pan, Chengtong; Liu, Yanju; Leng, Jinsong

2017-04-01

Shape memory polymers (SMPs) are a new type of smart material, they perform large reversible deformation with a certain external stimulus (e.g., heat and electricity). The properties (e.g., stiffness, strength and other mechanically static or quasi-static load-bearing capacity) are primarily considered for conventional resin-based composite materials which are mainly used for structural materials. By contrast, the mechanical actuating performance with finite deformation is considered for the shape memory polymers and their composites which can be used for both structural materials and functional materials. For shape memory polymers and their composites, the performance of active deformation is expected to further promote the development in smart active deformation structures, such as deployable space structures and morphing wing aircraft. The shape memory polymer composites (SMPCs) are also one type of High Strain Composite (HSC). The space deployable structures based on carbon fiber reinforced shape memory polymer composites (SMPCs) show great prospects. Considering the problems that SMPCs are difficult to meet the practical applications in space deployable structures in the recent ten years, this paper aims to research the mechanics of deformation, actuation and failure of SMPCs. In the overall view of the shape memory polymer material's nonlinearity (nonlinearity and stress softening in the process of pre-deformation and recovery, relaxation in storage process, irreversible deformation), by the multiple verifications among theory, finite element and experiments, one obtains the deformation and actuation mechanism for the process of "pre-deformation, energy storage and actuation" and its non-fracture constraint domain. Then, the parameters of SMPCs will be optimized. Theoretical analysis is realized by the strain energy function, additionally considering the interaction strain energy between the fiber and the matrix. For the common resin-based or soft-material-based composites under pure bending deformation, we expect to uniformly explain the whole process of buckling occurrence, evolution and finally failure, especially for the early evolution characteristics of fiber microbuckling inside the microstructures. The research results are meaningful for the practical applications for SMPC deployable structures in space. Considering the deformation mechanisms of SMPCs, the local post-microbuckling is required for the unidirectional fiber reinforced composite materials, at the conditions of its large geometrical deflection. The cross section of SMPC is divided into three areas: non-buckling stretching area, non-buckling compressive area, and buckling compressive area. Three variables are considered: critical buckling position, and neutral plane, the fiber buckling half-wavelength. Considering the condition of the small strain and large displacement, the strain energy expression of the SMP/fiber system was derived, which contains two types, e.g., strain energy of SMP and fiber. According to the minimum energy principle, the expression for all key parameters were derived, including the critical buckling curvature, neutral plane position, the buckling half-wavelength, fiber buckling amplitude, and strain.

Time-dependent effects of cortisol on the contextualization of emotional memories.

PubMed

van Ast, Vanessa A; Cornelisse, Sandra; Meeter, Martijn; Joëls, Marian; Kindt, Merel

2013-12-01

The inability to store fearful memories into their original encoding context is considered to be an important vulnerability factor for the development of anxiety disorders like posttraumatic stress disorder. Altered memory contextualization most likely involves effects of the stress hormone cortisol, acting via receptors located in the memory neurocircuitry. Cortisol via these receptors induces rapid nongenomic effects followed by slower genomic effects, which are thought to modulate cognitive function in opposite, complementary ways. Here, we targeted these time-dependent effects of cortisol during memory encoding and tested subsequent contextualization of emotional and neutral memories. In a double-blind, placebo-controlled design, 64 men were randomly assigned to one of three groups: 1) received 10 mg hydrocortisone 30 minutes (rapid cortisol effects) before a memory encoding task; 2) received 10 mg hydrocortisone 210 minutes (slow cortisol) before a memory encoding task; or 3) received placebo at both times. During encoding, participants were presented with neutral and emotional words in unique background pictures. Approximately 24 hours later, context dependency of their memories was assessed. Recognition data revealed that cortisol's rapid effects impair emotional memory contextualization, while cortisol's slow effects enhance it. Neutral memory contextualization remained unaltered by cortisol, irrespective of the timing of the drug. This study shows distinct time-dependent effects of cortisol on the contextualization of specifically emotional memories. The results suggest that rapid effects of cortisol may lead to impaired emotional memory contextualization, while slow effects of cortisol may confer protection against emotional memory generalization. © 2013 Society of Biological Psychiatry.

Filtering Non-Linear Transfer Functions on Surfaces.

PubMed

Heitz, Eric; Nowrouzezahrai, Derek; Poulin, Pierre; Neyret, Fabrice

2014-07-01

Applying non-linear transfer functions and look-up tables to procedural functions (such as noise), surface attributes, or even surface geometry are common strategies used to enhance visual detail. Their simplicity and ability to mimic a wide range of realistic appearances have led to their adoption in many rendering problems. As with any textured or geometric detail, proper filtering is needed to reduce aliasing when viewed across a range of distances, but accurate and efficient transfer function filtering remains an open problem for several reasons: transfer functions are complex and non-linear, especially when mapped through procedural noise and/or geometry-dependent functions, and the effects of perspective and masking further complicate the filtering over a pixel's footprint. We accurately solve this problem by computing and sampling from specialized filtering distributions on the fly, yielding very fast performance. We investigate the case where the transfer function to filter is a color map applied to (macroscale) surface textures (like noise), as well as color maps applied according to (microscale) geometric details. We introduce a novel representation of a (potentially modulated) color map's distribution over pixel footprints using Gaussian statistics and, in the more complex case of high-resolution color mapped microsurface details, our filtering is view- and light-dependent, and capable of correctly handling masking and occlusion effects. Our approach can be generalized to filter other physical-based rendering quantities. We propose an application to shading with irradiance environment maps over large terrains. Our framework is also compatible with the case of transfer functions used to warp surface geometry, as long as the transformations can be represented with Gaussian statistics, leading to proper view- and light-dependent filtering results. Our results match ground truth and our solution is well suited to real-time applications, requires only a few lines of shader code (provided in supplemental material, which can be found on the Computer Society Digital Library at http://doi.ieeecomputersociety.org/10.1109/TVCG.2013.102), is high performance, and has a negligible memory footprint.

Retrieval of all effective susceptibilities in nonlinear metamaterials

NASA Astrophysics Data System (ADS)

Larouche, Stéphane; Radisic, Vesna

2018-04-01

Electromagnetic metamaterials offer a great avenue to engineer and amplify the nonlinear response of materials. Their electric, magnetic, and magnetoelectric linear and nonlinear response are related to their structure, providing unprecedented liberty to control those properties. Both the linear and the nonlinear properties of metamaterials are typically anisotropic. While the methods to retrieve the effective linear properties are well established, existing nonlinear retrieval methods have serious limitations. In this work, we generalize a nonlinear transfer matrix approach to account for all nonlinear susceptibility terms and show how to use this approach to retrieve all effective nonlinear susceptibilities of metamaterial elements. The approach is demonstrated using sum frequency generation, but can be applied to other second-order or higher-order processes.

Nonlinear magnetoelectric effect and magnetostriction in piezoelectric CsCuCl{sub 3} in paramagnetic and antiferromagnetic states

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

Kharkovskiy, A. I., E-mail: akharkovskiy@inbox.ru; L.F. Vereshchagin Institute for High Pressure Physics RAS, 142190 Troitsk, Moscow; Shaldin, Yu. V.

2016-01-07

The direct nonlinear magnetoelectric (ME) effect and the magnetostriction of piezoelectric CsCuCl{sub 3} single crystals were comprehensively studied over a wide temperature range in stationary magnetic fields of up to 14 T. The direct nonlinear ME effect measurements were also performed in pulsed magnetic fields up to 31 T, at liquid helium temperature in the antiferromagnetic (AF) state for the crystallographic direction in which effect has the maximum value. The nonlinear ME effect was quadratic in the paramagnetic state for the whole range of magnetic fields. In the AF state the phase transition between different configurations of spins manifested itself as plateau-likemore » peculiarity on the nonlinear ME effect. The nonlinear ME effect was saturated by the phase transition to the spin-saturated paramagnetic state. Two contributions to the nonlinear ME effects in CsCuCl{sub 3} were extracted from the experimental data: the intrinsic ME effect originated from the magnetoelectric interactions, and the extrinsic one, which resulted from a magnetostriction-induced piezoelectric effect.« less

Can Oxytocin Enhance the Placebo Effect?

ClinicalTrials.gov

2018-02-06

Oxytocin Effect on Memory Performance During Phase 1; Oxytocin Effect on Memory Performance During Phase 2; Oxytocin Effect on Memory Performance During Phase 3; Oxytocin Effect on Memory Performance During Phase 4

Towards phase-coherent caloritronics in superconducting circuits

NASA Astrophysics Data System (ADS)

Fornieri, Antonio; Giazotto, Francesco

2017-10-01

The emerging field of phase-coherent caloritronics (from the Latin word calor, heat) is based on the possibility of controlling heat currents by using the phase difference of the superconducting order parameter. The goal is to design and implement thermal devices that can control energy transfer with a degree of accuracy approaching that reached for charge transport by contemporary electronic components. This can be done by making use of the macroscopic quantum coherence intrinsic to superconducting condensates, which manifests itself through the Josephson effect and the proximity effect. Here, we review recent experimental results obtained in the realization of heat interferometers and thermal rectifiers, and discuss a few proposals for exotic nonlinear phase-coherent caloritronic devices, such as thermal transistors, solid-state memories, phase-coherent heat splitters, microwave refrigerators, thermal engines and heat valves. Besides being attractive from the fundamental physics point of view, these systems are expected to have a vast impact on many cryogenic microcircuits requiring energy management, and possibly lay the first stone for the foundation of electronic thermal logic.

Towards phase-coherent caloritronics in superconducting circuits.

PubMed

Fornieri, Antonio; Giazotto, Francesco

2017-10-06

The emerging field of phase-coherent caloritronics (from the Latin word calor, heat) is based on the possibility of controlling heat currents by using the phase difference of the superconducting order parameter. The goal is to design and implement thermal devices that can control energy transfer with a degree of accuracy approaching that reached for charge transport by contemporary electronic components. This can be done by making use of the macroscopic quantum coherence intrinsic to superconducting condensates, which manifests itself through the Josephson effect and the proximity effect. Here, we review recent experimental results obtained in the realization of heat interferometers and thermal rectifiers, and discuss a few proposals for exotic nonlinear phase-coherent caloritronic devices, such as thermal transistors, solid-state memories, phase-coherent heat splitters, microwave refrigerators, thermal engines and heat valves. Besides being attractive from the fundamental physics point of view, these systems are expected to have a vast impact on many cryogenic microcircuits requiring energy management, and possibly lay the first stone for the foundation of electronic thermal logic.

Characterization of Nonlinear Systems with Memory by Means of Volterra Expansions with Frequency Partitioning: Application to a Cicada Mating Call

DTIC Science & Technology

2010-06-15

Partitioning Application to a Cicada Mating Call Albert H. Nuttall Adaptive Methods Inc. Derke R. Hughes NUWC Division Newport IVAVSEA WARFARE...Frequency Partitioning: Application to a Cicada Mating Call 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Albert H... cicada mating call with a distinctly non-white and non-Gaussian excitation gives good results for the estimated first- and second-order kernels and

Adaptive Implicit Non-Equilibrium Radiation Diffusion

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

Philip, Bobby; Wang, Zhen; Berrill, Mark A

2013-01-01

We describe methods for accurate and efficient long term time integra- tion of non-equilibrium radiation diffusion systems: implicit time integration for effi- cient long term time integration of stiff multiphysics systems, local control theory based step size control to minimize the required global number of time steps while control- ling accuracy, dynamic 3D adaptive mesh refinement (AMR) to minimize memory and computational costs, Jacobian Free Newton-Krylov methods on AMR grids for efficient nonlinear solution, and optimal multilevel preconditioner components that provide level independent solver convergence.

Newton-like methods for Navier-Stokes solution

NASA Astrophysics Data System (ADS)

Qin, N.; Xu, X.; Richards, B. E.

1992-12-01

The paper reports on Newton-like methods called SFDN-alpha-GMRES and SQN-alpha-GMRES methods that have been devised and proven as powerful schemes for large nonlinear problems typical of viscous compressible Navier-Stokes solutions. They can be applied using a partially converged solution from a conventional explicit or approximate implicit method. Developments have included the efficient parallelization of the schemes on a distributed memory parallel computer. The methods are illustrated using a RISC workstation and a transputer parallel system respectively to solve a hypersonic vortical flow.

Glucose effects on long-term memory performance: duration and domain specificity.

PubMed

Owen, Lauren; Finnegan, Yvonne; Hu, Henglong; Scholey, Andrew B; Sünram-Lea, Sandra I

2010-08-01

Previous research has suggested that long-term verbal declarative memory is particularly sensitive to enhancement by glucose loading; however, investigation of glucose effects on certain memory domains has hitherto been neglected. Therefore, domain specificity of glucose effects merits further elucidation. The aim of the present research was to provide a more comprehensive investigation of the possible effects of glucose administration on different aspects of memory by 1) contrasting the effect of glucose administration on different memory domains (implicit/explicit memory; verbal/non-verbal memory, and recognition/familiarity processes), 2) investigating whether potential effects on memory domains differ depending on the dose of glucose administered (25 g versus 60 g), 3) exploring the duration of the glucose facilitation effect (assessment of memory performance 35 min and 1 week after encoding). A double-blind between-subjects design was used to test the effects of administration of 25 and 60 g glucose on memory performance. Implicit memory was improved following administration of 60 g of glucose. Glucose supplementation failed to improve face recognition performance but significantly improved performance of word recall and recognition following administration of 60 g of glucose. However, effects were not maintained 1 week following encoding. Improved implicit memory performance following glucose administration has not been reported before. Furthermore, the current data tentatively suggest that level of processing may determine the required glucose dosage to demonstrate memory improvement and that higher dosages may be able to exert effects on memory pertaining to both hippocampal and non-hippocampal brain regions.

Improved Statistical Fault Detection Technique and Application to Biological Phenomena Modeled by S-Systems.

PubMed

Mansouri, Majdi; Nounou, Mohamed N; Nounou, Hazem N

2017-09-01

In our previous work, we have demonstrated the effectiveness of the linear multiscale principal component analysis (PCA)-based moving window (MW)-generalized likelihood ratio test (GLRT) technique over the classical PCA and multiscale principal component analysis (MSPCA)-based GLRT methods. The developed fault detection algorithm provided optimal properties by maximizing the detection probability for a particular false alarm rate (FAR) with different values of windows, and however, most real systems are nonlinear, which make the linear PCA method not able to tackle the issue of non-linearity to a great extent. Thus, in this paper, first, we apply a nonlinear PCA to obtain an accurate principal component of a set of data and handle a wide range of nonlinearities using the kernel principal component analysis (KPCA) model. The KPCA is among the most popular nonlinear statistical methods. Second, we extend the MW-GLRT technique to one that utilizes exponential weights to residuals in the moving window (instead of equal weightage) as it might be able to further improve fault detection performance by reducing the FAR using exponentially weighed moving average (EWMA). The developed detection method, which is called EWMA-GLRT, provides improved properties, such as smaller missed detection and FARs and smaller average run length. The idea behind the developed EWMA-GLRT is to compute a new GLRT statistic that integrates current and previous data information in a decreasing exponential fashion giving more weight to the more recent data. This provides a more accurate estimation of the GLRT statistic and provides a stronger memory that will enable better decision making with respect to fault detection. Therefore, in this paper, a KPCA-based EWMA-GLRT method is developed and utilized in practice to improve fault detection in biological phenomena modeled by S-systems and to enhance monitoring process mean. The idea behind a KPCA-based EWMA-GLRT fault detection algorithm is to combine the advantages brought forward by the proposed EWMA-GLRT fault detection chart with the KPCA model. Thus, it is used to enhance fault detection of the Cad System in E. coli model through monitoring some of the key variables involved in this model such as enzymes, transport proteins, regulatory proteins, lysine, and cadaverine. The results demonstrate the effectiveness of the proposed KPCA-based EWMA-GLRT method over Q , GLRT, EWMA, Shewhart, and moving window-GLRT methods. The detection performance is assessed and evaluated in terms of FAR, missed detection rates, and average run length (ARL 1 ) values.

Graphene-clad tapered fiber: effective nonlinearity and propagation losses.

PubMed

Gorbach, A V; Marini, A; Skryabin, D V

2013-12-15

We derive a pulse propagation equation for a graphene-clad optical fiber, treating the optical response of the graphene and nonlinearity of the dielectric fiber core as perturbations in asymptotic expansion of Maxwell equations. We analyze the effective nonlinear and attenuation coefficients due to the graphene layer. Based on the recent experimental measurements of the nonlinear graphene conductivity, we predict considerable enhancement of the effective nonlinearity for subwavelength fiber core diameters.

A simple exposure-time theory for all time-nonlocal transport formulations and beyond.

NASA Astrophysics Data System (ADS)

Ginn, T. R.; Schreyer, L. G.

2016-12-01

Anomalous transport or better put, anomalous non-transport, of solutes or flowing water or suspended colloids or bacteria etc. has been the subject of intense analyses with multiple formulations appearing in scientific literature from hydrology to geomorphology to chemical engineering, to environmental microbiology to mathematical physics. Primary focus has recently been on time-nonlocal mass conservation formulations such as multirate mass transfer, fractional-time advection-dispersion, continuous-time random walks, and dual porosity modeling approaches, that employ a convolution with a memory function to reflect respective conceptual models of delays in transport. These approaches are effective or "proxy" ones that do not always distinguish transport from immobilzation delays, are generally without connection to measurable physicochemical properties, and involve variously fractional calculus, inverse Laplace or Fourier transformations, and/or complex stochastic notions including assumptions of stationarity or ergodicity at the observation scale. Here we show a much simpler approach to time-nonlocal (non-)transport that is free of all these things, and is based on expressing the memory function in terms of a rate of mobilization of immobilized mass that is a function of the continguous time immobilized. Our approach treats mass transfer completely independently from the transport process, and it allows specification of actual immobilization mechanisms or delays. To our surprize we found that for all practical purposes any memory function can be expressed this way, including all of those associated with the multi-rate mass transfer approaches, original powerlaw, different truncated powerlaws, fractional-derivative, etc. More intriguing is the fact that the exposure-time approach can be used to construct heretofore unseen memory functions, e.g., forms that generate oscillating tails of breakthrough curves such as may occur in sediment transport, forms for delay-differential equations, and so on. Because the exposure-time approach is both simple and localized, it provides a promising platform for launching forays into non-Markovian and/or nonlinear processes and into upscaling age-dependent multicomponent reaction systems.

Exponential stability preservation in semi-discretisations of BAM networks with nonlinear impulses

NASA Astrophysics Data System (ADS)

Mohamad, Sannay; Gopalsamy, K.

2009-01-01

This paper demonstrates the reliability of a discrete-time analogue in preserving the exponential convergence of a bidirectional associative memory (BAM) network that is subject to nonlinear impulses. The analogue derived from a semi-discretisation technique with the value of the time-step fixed is treated as a discrete-time dynamical system while its exponential convergence towards an equilibrium state is studied. Thereby, a family of sufficiency conditions governing the network parameters and the impulse magnitude and frequency is obtained for the convergence. As special cases, one can obtain from our results, those corresponding to the non-impulsive discrete-time BAM networks and also those corresponding to continuous-time (impulsive and non-impulsive) systems. A relation between the Lyapunov exponent of the non-impulsive system and that of the impulsive system involving the size of the impulses and the inter-impulse intervals is obtained.

Theory of strong turbulence by renormalization

NASA Technical Reports Server (NTRS)

Tchen, C. M.

1981-01-01

The hydrodynamical equations of turbulent motions are inhomogeneous and nonlinear in their inertia and force terms and will generate a hierarchy. A kinetic method was developed to transform the hydrodynamic equations into a master equation governing the velocity distribution, as a function of the time, the position and the velocity as an independent variable. The master equation presents the advantage of being homogeneous and having fewer nonlinear terms and is therefore simpler for the investigation of closure. After the closure by means of a cascade scaling procedure, the kinetic equation is derived and possesses a memory which represents the nonMarkovian character of turbulence. The kinetic equation is transformed back to the hydrodynamical form to yield an energy balance in the cascade form. Normal and anomalous transports are analyzed. The theory is described for incompressible, compressible and plasma turbulence. Applications of the method to problems relating to sound generation and the propagation of light in a nonfrozen turbulence are considered.

Parallel filtering in global gyrokinetic simulations

NASA Astrophysics Data System (ADS)

Jolliet, S.; McMillan, B. F.; Villard, L.; Vernay, T.; Angelino, P.; Tran, T. M.; Brunner, S.; Bottino, A.; Idomura, Y.

2012-02-01

In this work, a Fourier solver [B.F. McMillan, S. Jolliet, A. Bottino, P. Angelino, T.M. Tran, L. Villard, Comp. Phys. Commun. 181 (2010) 715] is implemented in the global Eulerian gyrokinetic code GT5D [Y. Idomura, H. Urano, N. Aiba, S. Tokuda, Nucl. Fusion 49 (2009) 065029] and in the global Particle-In-Cell code ORB5 [S. Jolliet, A. Bottino, P. Angelino, R. Hatzky, T.M. Tran, B.F. McMillan, O. Sauter, K. Appert, Y. Idomura, L. Villard, Comp. Phys. Commun. 177 (2007) 409] in order to reduce the memory of the matrix associated with the field equation. This scheme is verified with linear and nonlinear simulations of turbulence. It is demonstrated that the straight-field-line angle is the coordinate that optimizes the Fourier solver, that both linear and nonlinear turbulent states are unaffected by the parallel filtering, and that the k∥ spectrum is independent of plasma size at fixed normalized poloidal wave number.

An Optimization Code for Nonlinear Transient Problems of a Large Scale Multidisciplinary Mathematical Model

NASA Astrophysics Data System (ADS)

Takasaki, Koichi

This paper presents a program for the multidisciplinary optimization and identification problem of the nonlinear model of large aerospace vehicle structures. The program constructs the global matrix of the dynamic system in the time direction by the p-version finite element method (pFEM), and the basic matrix for each pFEM node in the time direction is described by a sparse matrix similarly to the static finite element problem. The algorithm used by the program does not require the Hessian matrix of the objective function and so has low memory requirements. It also has a relatively low computational cost, and is suited to parallel computation. The program was integrated as a solver module of the multidisciplinary analysis system CUMuLOUS (Computational Utility for Multidisciplinary Large scale Optimization of Undense System) which is under development by the Aerospace Research and Development Directorate (ARD) of the Japan Aerospace Exploration Agency (JAXA).

Theoretical analysis and Vsim simulation of a low-voltage high-efficiency 250 GHz gyrotron

NASA Astrophysics Data System (ADS)

An, Chenxiang; Zhang, Dian; Zhang, Jun; Zhong, Huihuang

2018-02-01

Low-voltage, high-frequency gyrotrons with hundreds of watts of power are useful in radar, magnetic resonance spectroscopy and plasma diagnostic applications. In this paper, a 10 kV, 478 W, 250 GHz gyrotron with an efficiency of nearly 40% and a pitch ratio of 1.5 was designed through linear and nonlinear numerical analyses and Vsim particle-in-cell (PIC) simulation. Vsim is a highly efficient parallel PIC code, but it has seldom been used to carry out electron beam wave interaction simulations of gyro-devices. The setting up of the parameters required for the Vsim simulations of the gyrotron is presented. The results of Vsim simulations agree well with that of nonlinear numerical calculation. The commercial software Vsim7.2 completed the 3D gyrotron simulation in 80 h using a 20 core, 2.2 GHz personal computer with 256 GBytes of memory.

Functional expansion representations of artificial neural networks

NASA Technical Reports Server (NTRS)

Gray, W. Steven

1992-01-01

In the past few years, significant interest has developed in using artificial neural networks to model and control nonlinear dynamical systems. While there exists many proposed schemes for accomplishing this and a wealth of supporting empirical results, most approaches to date tend to be ad hoc in nature and rely mainly on heuristic justifications. The purpose of this project was to further develop some analytical tools for representing nonlinear discrete-time input-output systems, which when applied to neural networks would give insight on architecture selection, pruning strategies, and learning algorithms. A long term goal is to determine in what sense, if any, a neural network can be used as a universal approximator for nonliner input-output maps with memory (i.e., realized by a dynamical system). This property is well known for the case of static or memoryless input-output maps. The general architecture under consideration in this project was a single-input, single-output recurrent feedforward network.

Towards spontaneous parametric down-conversion at low temperatures

NASA Astrophysics Data System (ADS)

Akatiev, Dmitrii; Boldyrev, Kirill; Kuzmin, Nikolai; Latypov, Ilnur; Popova, Marina; Shkalikov, Andrey; Kalachev, Alexey

2017-10-01

The possibility of observing spontaneous parametric down-conversion in doped nonlinear crystals at low temperatures, which would be useful for combining heralded single-photon sources and quantum memories, is studied theoretically. The ordinary refractive index of a lithium niobate crystal doped with magnesium oxide LiNbO3:MgO is measured at liquid nitrogen and helium temperatures. On the basis of the experimental data, the coefficients of the Sellmeier equation are determined for the temperatures from 5 to 300 K. In addition, a poling period of the nonlinear crystal has been calculated for observing type-0 spontaneous parametric down-conversion (ooo-synchronism) at the liquid helium temperature under pumping at the wavelength of λp = 532 nm and emission of the signal field at the wavelength of λs = 794 nm, which corresponds to the resonant absorption line of Tm3+ doped ions.

Working memory capacity and the spacing effect in cued recall.

PubMed

Delaney, Peter F; Godbole, Namrata R; Holden, Latasha R; Chang, Yoojin

2018-07-01

Spacing repetitions typically improves memory (the spacing effect). In three cued recall experiments, we explored the relationship between working memory capacity and the spacing effect. People with higher working memory capacity are more accurate on memory tasks that require retrieval relative to people with lower working memory capacity. The experiments used different retention intervals and lags between repetitions, but were otherwise similar. Working memory capacity and spacing of repetitions both improved memory in most of conditions, but they did not interact, suggesting additive effects. The results are consistent with the ACT-R model's predictions, and with a study-phase recognition process underpinning the spacing effect in cued recall.

Few-Photon Nonlinearity with an Atomic Ensemble in an Optical Cavity

NASA Astrophysics Data System (ADS)

Tanji, Haruka

2011-12-01

This thesis investigates the effect of the cavity vacuum field on the dispersive properties of an atomic ensemble in a strongly coupled high-finesse cavity. In particular, we demonstrate vacuum-induced transparency (VIT). The light absorption by the ensemble is suppressed by up to 40% in the presence of a cavity vacuum field. The sharp transparency peak is accompanied by the reduction in the group velocity of a light pulse, measured to be as low as 1800 m/s. This observation is a large step towards the realization of photon number-state filters, recently proposed by Nikoghosyan et al. Furthermore, we demonstrate few-photon optical nonlinearity, where the transparency is increased from 40% to 80% with ˜12 photons in the cavity mode. The result may be viewed as all-optical switching, where the transmission of photons in one mode may be controlled by 12 photons in another. These studies point to the possibility of nonlinear interaction between photons in different free-space modes, a scheme that circumvents cavity-coupling losses that plague cavity-based quantum information processing. Potential applications include advanced quantum devices such as photonic quantum gates, photon-number resolving detectors, and single-photon transistors. In the efforts leading up to these results, we investigate the collective enhancement of atomic coupling to a single mode of a low-finesse cavity. With the strong collective coupling, we obtain exquisite control of quantum states in the atom-photon coupled system. In this system, we demonstrate a heralded single-photon source with 84% conditional efficiency, a quantum bus for deterministic entanglement of two remote ensembles, and heralded polarization-state quantum memory with fidelity above 90%.

Psychoactive drugs and false memory: comparison of dextroamphetamine and delta-9-tetrahydrocannabinol on false recognition

PubMed Central

Ballard, Michael E.; Gallo, David A.; de Wit, Harriet

2014-01-01

Rationale Several psychoactive drugs are known to influence episodic memory. However, these drugs’ effects on false memory, or the tendency to incorrectly remember nonstudied information, remain poorly understood. Objectives Here, we examined the effects of two commonly used psychoactive drugs, one with memory-enhancing properties (dextroamphetamine; AMP), and another with memory-impairing properties (Δ9-tetrahydrocannabinol; THC), on false memory using the Deese/Roediger–McDermott (DRM) illusion. Methods Two parallel studies were conducted in which healthy volunteers received either AMP (0, 10, and 20 mg) or THC (0, 7.5, and 15 mg) in within-subjects, randomized, double-blind designs. Participants studied DRM word lists under the influence of the drugs, and their recognition memory for the studied words was tested 2 days later, under sober conditions. Results As expected, AMP increased memory of studied words relative to placebo, and THC reduced memory of studied words. Although neither drug significantly affected false memory relative to placebo, AMP increased false memory relative to THC. Across participants, both drugs’ effects on true memory were positively correlated with their effects on false memory. Conclusions Our results indicate that AMP and THC have opposing effects on true memory, and these effects appear to correspond to similar, albeit more subtle, effects on false memory. These findings are consistent with previous research using the DRM illusion and provide further evidence that psychoactive drugs can affect the encoding processes that ultimately result in the creation of false memories. PMID:21647577

Psychoactive drugs and false memory: comparison of dextroamphetamine and δ-9-tetrahydrocannabinol on false recognition.

PubMed

Ballard, Michael E; Gallo, David A; de Wit, Harriet

2012-01-01

Several psychoactive drugs are known to influence episodic memory. However, these drugs' effects on false memory, or the tendency to incorrectly remember nonstudied information, remain poorly understood. Here, we examined the effects of two commonly used psychoactive drugs, one with memory-enhancing properties (dextroamphetamine; AMP), and another with memory-impairing properties (Δ(9)-tetrahydrocannabinol; THC), on false memory using the Deese/Roediger-McDermott (DRM) illusion. Two parallel studies were conducted in which healthy volunteers received either AMP (0, 10, and 20 mg) or THC (0, 7.5, and 15 mg) in within-subjects, randomized, double-blind designs. Participants studied DRM word lists under the influence of the drugs, and their recognition memory for the studied words was tested 2 days later, under sober conditions. As expected, AMP increased memory of studied words relative to placebo, and THC reduced memory of studied words. Although neither drug significantly affected false memory relative to placebo, AMP increased false memory relative to THC. Across participants, both drugs' effects on true memory were positively correlated with their effects on false memory. Our results indicate that AMP and THC have opposing effects on true memory, and these effects appear to correspond to similar, albeit more subtle, effects on false memory. These findings are consistent with previous research using the DRM illusion and provide further evidence that psychoactive drugs can affect the encoding processes that ultimately result in the creation of false memories.

Giant Kerr response of ultrathin gold films from quantum size effect.

PubMed

Qian, Haoliang; Xiao, Yuzhe; Liu, Zhaowei

2016-10-10

With the size of plasmonic devices entering into the nanoscale region, the impact of quantum physics needs to be considered. In the past, the quantum size effect on linear material properties has been studied extensively. However, the nonlinear aspects have not been explored much so far. On the other hand, much effort has been put into the field of integrated nonlinear optics and a medium with large nonlinearity is desirable. Here we study the optical nonlinear properties of a nanometre scale gold quantum well by using the z-scan method and nonlinear spectrum broadening technique. The quantum size effect results in a giant optical Kerr susceptibility, which is four orders of magnitude higher than the intrinsic value of bulk gold and several orders larger than traditional nonlinear media. Such high nonlinearity enables efficient nonlinear interaction within a microscopic footprint, making quantum metallic films a promising candidate for integrated nonlinear optical applications.

Neutral and emotional episodic memory: global impairment after lorazepam or scopolamine.

PubMed

Kamboj, Sunjeev K; Curran, H Valerie

2006-11-01

Benzodiazepines and anticholinergic drugs have repeatedly been shown to impair episodic memory for emotionally neutral material in humans. However, their effect on memory for emotionally laden stimuli has been relatively neglected. We sought to investigate the effects of the benzodiazepine, lorazepam, and the anticholinergic, scopolamine, on incidental episodic memory for neutral and emotional components of a narrative memory task in humans. A double-blind, placebo-controlled independent group design was used with 48 healthy volunteers to examine the effects of these drugs on emotional and neutral episodic memory. As expected, the emotional memory advantage was retained for recall and recognition memory under placebo conditions. However, lorazepam and scopolamine produced anterograde recognition memory impairments on both the neutral and emotional components of the narrative, although floor effects were obtained for recall memory. Furthermore, compared with placebo, recognition memory for both central (gist) and peripheral (detail) aspects of neutral and emotional elements of the narrative was poorer after either drug. Benzodiazepine-induced GABAergic enhancement or scopolamine-induced cholinergic hypofunction results in a loss of the enhancing effect of emotional arousal on memory. Furthermore, lorazepam- and scopolamine-induced memory impairment for both gist (which is amygdala dependent) and detail raises the possibility that their effects on emotional memory do not depend only on the amygdala. We discuss the results with reference to potential clinical/forensic implications of processing emotional memories under conditions of globally impaired episodic memory.

Sensitivity of negative subsequent memory and task-negative effects to age and associative memory performance.

PubMed

de Chastelaine, Marianne; Mattson, Julia T; Wang, Tracy H; Donley, Brian E; Rugg, Michael D

2015-07-01

The present fMRI experiment employed associative recognition to investigate the relationships between age and encoding-related negative subsequent memory effects and task-negative effects. Young, middle-aged and older adults (total n=136) were scanned while they made relational judgments on visually presented word pairs. In a later memory test, the participants made associative recognition judgments on studied, rearranged (items studied on different trials) and new pairs. Several regions, mostly localized to the default mode network, demonstrated negative subsequent memory effects in an across age-group analysis. All but one of these regions also demonstrated task-negative effects, although there was no correlation between the size of the respective effects. Whereas negative subsequent memory effects demonstrated a graded attenuation with age, task-negative effects declined markedly between the young and the middle-aged group, but showed no further reduction in the older group. Negative subsequent memory effects did not correlate with memory performance within any age group. By contrast, in the older group only, task-negative effects predicted later memory performance. The findings demonstrate that negative subsequent memory and task-negative effects depend on dissociable neural mechanisms and likely reflect distinct cognitive processes. The relationship between task-negative effects and memory performance in the older group might reflect the sensitivity of these effects to variations in amount of age-related neuropathology. This article is part of a Special Issue entitled SI: Memory. Copyright © 2014 Elsevier B.V. All rights reserved.

Age differences in perceptions of memory strategy effectiveness for recent and remote memory.

PubMed

Lineweaver, Tara T; Horhota, Michelle; Crumley, Jessica; Geanon, Catherine T; Juett, Jacqueline J

2018-03-01

We examined whether young and older adults hold different beliefs about the effectiveness of memory strategies for specific types of memory tasks and whether memory strategies are perceived to be differentially effective for young, middle-aged, and older targets. Participants rated the effectiveness of five memory strategies for 10 memory tasks at three target ages (20, 50, and 80 years old). Older adults did not strongly differentiate strategy effectiveness, viewing most strategies as similarly effective across memory tasks. Young adults held strategy-specific beliefs, endorsing external aids and physical health as more effective than a positive attitude or internal strategies, without substantial differentiation based on task. We also found differences in anticipated strategy effectiveness for targets of different ages. Older adults described cognitive and physical health strategies as more effective for older than middle-aged targets, whereas young adults expected these strategies to be equally effective for middle-aged and older target adults.

Regional hippocampal volumes and development predict learning and memory.

PubMed

Tamnes, Christian K; Walhovd, Kristine B; Engvig, Andreas; Grydeland, Håkon; Krogsrud, Stine K; Østby, Ylva; Holland, Dominic; Dale, Anders M; Fjell, Anders M

2014-01-01

The hippocampus is an anatomically and functionally heterogeneous structure, but longitudinal studies of its regional development are scarce and it is not known whether protracted maturation of the hippocampus in adolescence is related to memory development. First, we investigated hippocampal subfield development using 170 longitudinally acquired brain magnetic resonance imaging scans from 85 participants aged 8-21 years. Hippocampal subfield volumes were estimated by the use of automated segmentation of 7 subfields, including the cornu ammonis (CA) sectors and the dentate gyrus (DG), while longitudinal subfield volumetric change was quantified using a nonlinear registration procedure. Second, associations between subfield volumes and change and verbal learning/memory across multiple retention intervals (5 min, 30 min and 1 week) were tested. It was hypothesized that short and intermediate memory would be more closely related to CA2-3/CA4-DG and extended, remote memory to CA1. Change rates were significantly different across hippocampal subfields, but nearly all subfields showed significant volume decreases over time throughout adolescence. Several subfield volumes were larger in the right hemisphere and in males, while for change rates there were no hemisphere or sex differences. Partly in support of the hypotheses, greater volume of CA1 and CA2-3 was related to recall and retention after an extended delay, while longitudinal reduction of CA2-3 and CA4-DG was related to learning. This suggests continued regional development of the hippocampus across adolescence and that volume and volume change in specific subfields differentially predict verbal learning and memory over different retention intervals, but future high-resolution studies are called for. © 2014 S. Karger AG, Basel.

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

Zhu, Z. W., E-mail: zhuzhiwen@tju.edu.cn; Li, X. M., E-mail: lixinmiaotju@163.com; Xu, J., E-mail: xujia-ld@163.com

A kind of magnetic shape memory alloy (MSMA) microgripper is proposed in this paper, and its nonlinear dynamic characteristics are studied when the stochastic perturbation is considered. Nonlinear differential items are introduced to explain the hysteretic phenomena of MSMA, and the constructive relationships among strain, stress, and magnetic field intensity are obtained by the partial least-square regression method. The nonlinear dynamic model of a MSMA microgripper subjected to in-plane stochastic excitation is developed. The stationary probability density function of the system’s response is obtained, the transition sets of the system are determined, and the conditions of stochastic bifurcation are obtained.more » The homoclinic and heteroclinic orbits of the system are given, and the boundary of the system’s safe basin is obtained by stochastic Melnikov integral method. The numerical and experimental results show that the system’s motion depends on its parameters, and stochastic Hopf bifurcation appears in the variation of the parameters; the area of the safe basin decreases with the increase of the stochastic excitation, and the boundary of the safe basin becomes fractal. The results of this paper are helpful for the application of MSMA microgripper in engineering fields.« less